{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import gc\n",
    "sns.set_style(\"darkgrid\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "pd.set_option('display.float_format', lambda x: '%.3f' % x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Preparation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "tools = pd.read_parquet('../data/tools.parquet')\n",
    "fpmms = pd.read_parquet('../data/fpmms.parquet')\n",
    "summary_traders = pd.read_parquet('../data/summary_profitability.parquet')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "currentAnswer\n",
       "No     66982\n",
       "Yes    42810\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tools.currentAnswer.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_trades = pd.read_parquet('../data/all_trades_profitability.parquet')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 26861 entries, 0 to 26860\n",
      "Data columns (total 21 columns):\n",
      " #   Column                  Non-Null Count  Dtype              \n",
      "---  ------                  --------------  -----              \n",
      " 0   trader_address          26861 non-null  object             \n",
      " 1   market_creator          26861 non-null  object             \n",
      " 2   trade_id                26861 non-null  object             \n",
      " 3   creation_timestamp      26861 non-null  datetime64[ns, UTC]\n",
      " 4   title                   26861 non-null  object             \n",
      " 5   market_status           26861 non-null  object             \n",
      " 6   collateral_amount       26861 non-null  float64            \n",
      " 7   outcome_index           26861 non-null  object             \n",
      " 8   trade_fee_amount        26861 non-null  float64            \n",
      " 9   outcomes_tokens_traded  26861 non-null  float64            \n",
      " 10  current_answer          26861 non-null  int64              \n",
      " 11  is_invalid              26861 non-null  bool               \n",
      " 12  winning_trade           26861 non-null  bool               \n",
      " 13  earnings                26861 non-null  float64            \n",
      " 14  redeemed                26861 non-null  bool               \n",
      " 15  redeemed_amount         26861 non-null  float64            \n",
      " 16  num_mech_calls          26861 non-null  int64              \n",
      " 17  mech_fee_amount         26861 non-null  float64            \n",
      " 18  net_earnings            26861 non-null  float64            \n",
      " 19  roi                     26861 non-null  float64            \n",
      " 20  staking                 26861 non-null  object             \n",
      "dtypes: bool(3), datetime64[ns, UTC](1), float64(8), int64(2), object(7)\n",
      "memory usage: 3.8+ MB\n"
     ]
    }
   ],
   "source": [
    "all_trades.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_trades.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    8210.000000\n",
       "mean        0.129631\n",
       "std        22.449193\n",
       "min        -1.000000\n",
       "25%        -1.000000\n",
       "50%         0.117954\n",
       "75%         0.541716\n",
       "max      2032.090177\n",
       "Name: roi, dtype: float64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_trades.roi.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2032.0901766222644"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max(all_trades.roi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    8.210000e+03\n",
       "mean     1.269746e-02\n",
       "std      1.381237e-02\n",
       "min      2.000000e-07\n",
       "25%      3.200000e-03\n",
       "50%      1.014609e-02\n",
       "75%      2.000000e-02\n",
       "max      4.400000e-01\n",
       "Name: trade_fee_amount, dtype: float64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_trades.trade_fee_amount.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "to_investigate = all_trades.loc[all_trades[\"roi\"]==max(all_trades.roi)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>trader_address</th>\n",
       "      <th>market_creator</th>\n",
       "      <th>trade_id</th>\n",
       "      <th>creation_timestamp</th>\n",
       "      <th>title</th>\n",
       "      <th>market_status</th>\n",
       "      <th>collateral_amount</th>\n",
       "      <th>outcome_index</th>\n",
       "      <th>trade_fee_amount</th>\n",
       "      <th>outcomes_tokens_traded</th>\n",
       "      <th>current_answer</th>\n",
       "      <th>is_invalid</th>\n",
       "      <th>winning_trade</th>\n",
       "      <th>earnings</th>\n",
       "      <th>redeemed</th>\n",
       "      <th>redeemed_amount</th>\n",
       "      <th>num_mech_calls</th>\n",
       "      <th>mech_fee_amount</th>\n",
       "      <th>net_earnings</th>\n",
       "      <th>roi</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>928</th>\n",
       "      <td>0x3666da333dadd05083fef9ff6ddee588d26e4307</td>\n",
       "      <td>quickstart</td>\n",
       "      <td>0x11cf6ec9649097127238ffb789b0703da448d9fa0x36...</td>\n",
       "      <td>2024-09-15 02:02:05+00:00</td>\n",
       "      <td>Will Apple launch the iPhone 16 by 15 Septembe...</td>\n",
       "      <td>CLOSED</td>\n",
       "      <td>0.00001</td>\n",
       "      <td>0</td>\n",
       "      <td>2.000000e-07</td>\n",
       "      <td>0.020738</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0.020738</td>\n",
       "      <td>True</td>\n",
       "      <td>0.020738</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.020727</td>\n",
       "      <td>2032.090177</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 trader_address market_creator  \\\n",
       "928  0x3666da333dadd05083fef9ff6ddee588d26e4307     quickstart   \n",
       "\n",
       "                                              trade_id  \\\n",
       "928  0x11cf6ec9649097127238ffb789b0703da448d9fa0x36...   \n",
       "\n",
       "           creation_timestamp  \\\n",
       "928 2024-09-15 02:02:05+00:00   \n",
       "\n",
       "                                                 title market_status  \\\n",
       "928  Will Apple launch the iPhone 16 by 15 Septembe...        CLOSED   \n",
       "\n",
       "     collateral_amount outcome_index  trade_fee_amount  \\\n",
       "928            0.00001             0      2.000000e-07   \n",
       "\n",
       "     outcomes_tokens_traded  current_answer  is_invalid  winning_trade  \\\n",
       "928                0.020738               0       False           True   \n",
       "\n",
       "     earnings  redeemed  redeemed_amount  num_mech_calls  mech_fee_amount  \\\n",
       "928  0.020738      True         0.020738               0              0.0   \n",
       "\n",
       "     net_earnings          roi  \n",
       "928      0.020727  2032.090177  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "to_investigate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "928    0.036337\n",
       "dtype: float64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(to_investigate.net_earnings -(to_investigate.trade_fee_amount + 2*0.01)) / (to_investigate.collateral_amount + to_investigate.trade_fee_amount + 2*0.01)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "trades_no_mech = all_trades.loc[all_trades[\"num_mech_calls\"]==0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 1649 entries, 61 to 8201\n",
      "Data columns (total 20 columns):\n",
      " #   Column                  Non-Null Count  Dtype              \n",
      "---  ------                  --------------  -----              \n",
      " 0   trader_address          1649 non-null   object             \n",
      " 1   market_creator          1649 non-null   object             \n",
      " 2   trade_id                1649 non-null   object             \n",
      " 3   creation_timestamp      1649 non-null   datetime64[ns, UTC]\n",
      " 4   title                   1649 non-null   object             \n",
      " 5   market_status           1649 non-null   object             \n",
      " 6   collateral_amount       1649 non-null   float64            \n",
      " 7   outcome_index           1649 non-null   object             \n",
      " 8   trade_fee_amount        1649 non-null   float64            \n",
      " 9   outcomes_tokens_traded  1649 non-null   float64            \n",
      " 10  current_answer          1649 non-null   int64              \n",
      " 11  is_invalid              1649 non-null   bool               \n",
      " 12  winning_trade           1649 non-null   bool               \n",
      " 13  earnings                1649 non-null   float64            \n",
      " 14  redeemed                1649 non-null   bool               \n",
      " 15  redeemed_amount         1649 non-null   float64            \n",
      " 16  num_mech_calls          1649 non-null   int64              \n",
      " 17  mech_fee_amount         1649 non-null   float64            \n",
      " 18  net_earnings            1649 non-null   float64            \n",
      " 19  roi                     1649 non-null   float64            \n",
      "dtypes: bool(3), datetime64[ns, UTC](1), float64(8), int64(2), object(6)\n",
      "memory usage: 236.7+ KB\n"
     ]
    }
   ],
   "source": [
    "trades_no_mech.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.20085261875761268"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(trades_no_mech)/len(all_trades)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    1649.000000\n",
       "mean        1.378776\n",
       "std        50.053860\n",
       "min        -1.000000\n",
       "25%        -1.000000\n",
       "50%         0.199740\n",
       "75%         0.673038\n",
       "max      2032.090177\n",
       "Name: roi, dtype: float64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trades_no_mech.roi.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 17067 entries, 0 to 17066\n",
      "Data columns (total 19 columns):\n",
      " #   Column                  Non-Null Count  Dtype              \n",
      "---  ------                  --------------  -----              \n",
      " 0   trader_address          17067 non-null  object             \n",
      " 1   trade_id                17067 non-null  object             \n",
      " 2   creation_timestamp      17067 non-null  datetime64[ns, UTC]\n",
      " 3   title                   17067 non-null  object             \n",
      " 4   market_status           17067 non-null  object             \n",
      " 5   collateral_amount       17067 non-null  float64            \n",
      " 6   outcome_index           17067 non-null  object             \n",
      " 7   trade_fee_amount        17067 non-null  float64            \n",
      " 8   outcomes_tokens_traded  17067 non-null  float64            \n",
      " 9   current_answer          17067 non-null  int64              \n",
      " 10  is_invalid              17067 non-null  bool               \n",
      " 11  winning_trade           17067 non-null  bool               \n",
      " 12  earnings                17067 non-null  float64            \n",
      " 13  redeemed                17067 non-null  bool               \n",
      " 14  redeemed_amount         17067 non-null  float64            \n",
      " 15  num_mech_calls          17067 non-null  int64              \n",
      " 16  mech_fee_amount         17067 non-null  float64            \n",
      " 17  net_earnings            17067 non-null  float64            \n",
      " 18  roi                     17067 non-null  float64            \n",
      "dtypes: bool(3), datetime64[ns, UTC](1), float64(8), int64(2), object(5)\n",
      "memory usage: 2.1+ MB\n"
     ]
    }
   ],
   "source": [
    "all_trades.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2024-05-12 00:04:25+0000', tz='UTC')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_trades.creation_timestamp.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2024-07-14 01:09:10+0000', tz='UTC')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_trades.creation_timestamp.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2024-07-08 02:29:40+0000', tz='UTC')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_trades.creation_timestamp.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(339443, 22)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(28911882, 34138429)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(tools.shape)\n",
    "tools.request_block.min(), tools.request_block.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(89518, 22)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(33989007, 34993418)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(tools.shape)\n",
    "tools.request_block.min(), tools.request_block.max()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Error analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Error analysis only starts from block 321. We weren't capturing the error message prior"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['prediction-online', 'prediction-offline', 'normal-sme-generator',\n",
       "       'strong-sme-generator', 'prediction-online-sme',\n",
       "       'prediction-offline-sme', 'claude-prediction-offline', 'openai',\n",
       "       'claude-prediction-online',\n",
       "       'prediction-sentence-embedding-conservative',\n",
       "       'prediction-online-summarized-info',\n",
       "       'prediction-sentence-embedding-bold',\n",
       "       'prediction-online-sum-url-content',\n",
       "       'openai-gpt-3.5-turbo-instruct',\n",
       "       'resolve-market-reasoning-gpt-3.5-turbo',\n",
       "       'resolve-market-reasoning-gpt-4', 'prediction-request-rag',\n",
       "       'prediction-request-reasoning',\n",
       "       'prediction-request-reasoning-claude', 'prediction-url-cot-claude',\n",
       "       'prediction-request-rag-claude', 'native_transfer_request',\n",
       "       'native_transfer'], dtype=object)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tools.tool.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 339443 entries, 0 to 339442\n",
      "Data columns (total 22 columns):\n",
      " #   Column                   Non-Null Count   Dtype  \n",
      "---  ------                   --------------   -----  \n",
      " 0   request_id               339443 non-null  object \n",
      " 1   request_block            339443 non-null  int64  \n",
      " 2   prompt_request           339443 non-null  object \n",
      " 3   tool                     339443 non-null  object \n",
      " 4   nonce                    339443 non-null  object \n",
      " 5   trader_address           339443 non-null  object \n",
      " 6   deliver_block            339443 non-null  int64  \n",
      " 7   error                    339440 non-null  float64\n",
      " 8   error_message            56715 non-null   object \n",
      " 9   prompt_response          252711 non-null  object \n",
      " 10  mech_address             286960 non-null  object \n",
      " 11  p_yes                    282717 non-null  float64\n",
      " 12  p_no                     282717 non-null  float64\n",
      " 13  confidence               282717 non-null  float64\n",
      " 14  info_utility             282717 non-null  float64\n",
      " 15  vote                     256610 non-null  object \n",
      " 16  win_probability          282717 non-null  float64\n",
      " 17  title                    329340 non-null  object \n",
      " 18  currentAnswer            267690 non-null  object \n",
      " 19  request_time             339443 non-null  object \n",
      " 20  request_month_year       339443 non-null  object \n",
      " 21  request_month_year_week  339443 non-null  object \n",
      "dtypes: float64(6), int64(2), object(14)\n",
      "memory usage: 57.0+ MB\n"
     ]
    }
   ],
   "source": [
    "tools.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2023-07-12 11:58:40'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tools.request_time.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "inc_tools = [\n",
    "    'prediction-online', \n",
    "    'prediction-offline', \n",
    "    'claude-prediction-online', \n",
    "    'claude-prediction-offline', \n",
    "    'prediction-offline-sme',\n",
    "    'prediction-online-sme',\n",
    "    'prediction-request-rag',\n",
    "    'prediction-request-reasoning',\n",
    "    'prediction-url-cot-claude', \n",
    "    'prediction-request-rag-claude',\n",
    "    'prediction-request-reasoning-claude'\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# include only tools that are in inc_tools\n",
    "tools_inc = tools[tools['tool'].isin(inc_tools)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "error = tools_inc.groupby(['tool', 'request_month_year_week', 'error']).size().unstack().fillna(0).reset_index()\n",
    "error[\"error_perc\"] = (error[1] / (error[0] + error[1])) * 100\n",
    "error[\"total_requests\"] = error[0] + error[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "error_total = (\n",
    "    error.groupby(\"request_month_year_week\")\n",
    "    .agg({\"total_requests\": \"sum\", 1: \"sum\", 0: \"sum\"})\n",
    "    .reset_index()\n",
    ")\n",
    "error_total[\"error_perc\"] = (error_total[1] / error_total[\"total_requests\"]) * 100\n",
    "error_total.columns = error_total.columns.astype(str)\n",
    "error_total[\"error_perc\"] = error_total[\"error_perc\"].apply(lambda x: round(x, 4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>error</th>\n",
       "      <th>request_month_year_week</th>\n",
       "      <th>total_requests</th>\n",
       "      <th>1</th>\n",
       "      <th>0</th>\n",
       "      <th>error_perc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2023-07-10/2023-07-16</td>\n",
       "      <td>44.000</td>\n",
       "      <td>31.000</td>\n",
       "      <td>13.000</td>\n",
       "      <td>70.454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2023-07-17/2023-07-23</td>\n",
       "      <td>56.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>56.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2023-07-24/2023-07-30</td>\n",
       "      <td>48.000</td>\n",
       "      <td>5.000</td>\n",
       "      <td>43.000</td>\n",
       "      <td>10.417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2023-07-31/2023-08-06</td>\n",
       "      <td>922.000</td>\n",
       "      <td>203.000</td>\n",
       "      <td>719.000</td>\n",
       "      <td>22.017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2023-08-07/2023-08-13</td>\n",
       "      <td>313.000</td>\n",
       "      <td>9.000</td>\n",
       "      <td>304.000</td>\n",
       "      <td>2.875</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "error request_month_year_week  total_requests       1       0  error_perc\n",
       "0       2023-07-10/2023-07-16          44.000  31.000  13.000      70.454\n",
       "1       2023-07-17/2023-07-23          56.000   0.000  56.000       0.000\n",
       "2       2023-07-24/2023-07-30          48.000   5.000  43.000      10.417\n",
       "3       2023-07-31/2023-08-06         922.000 203.000 719.000      22.017\n",
       "4       2023-08-07/2023-08-13         313.000   9.000 304.000       2.875"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "error_total.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Error Percentage by Month-Year')"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 6))\n",
    "ax=sns.lineplot(error_total, x='request_month_year_week', y='error_perc',color=\"green\")\n",
    "ax.set_xticklabels(ax.get_xticklabels(), rotation=90)\n",
    "plt.xlabel('Month-Year')\n",
    "plt.ylabel('Error Percentage')\n",
    "plt.title('Error Percentage by Month-Year')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>error</th>\n",
       "      <th>error_perc</th>\n",
       "      <th>total_requests</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tool</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>prediction-request-rag-claude</th>\n",
       "      <td>13.498</td>\n",
       "      <td>1704.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>prediction-request-rag</th>\n",
       "      <td>12.041</td>\n",
       "      <td>490.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>prediction-online-sme</th>\n",
       "      <td>9.076</td>\n",
       "      <td>2457.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>prediction-online</th>\n",
       "      <td>4.769</td>\n",
       "      <td>2516.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>prediction-request-reasoning</th>\n",
       "      <td>3.247</td>\n",
       "      <td>5883.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>prediction-request-reasoning-claude</th>\n",
       "      <td>1.408</td>\n",
       "      <td>639.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>claude-prediction-offline</th>\n",
       "      <td>0.000</td>\n",
       "      <td>107.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>claude-prediction-online</th>\n",
       "      <td>0.000</td>\n",
       "      <td>241.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>prediction-offline</th>\n",
       "      <td>0.000</td>\n",
       "      <td>1453.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>prediction-url-cot-claude</th>\n",
       "      <td>0.000</td>\n",
       "      <td>293.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "error                                error_perc  total_requests\n",
       "tool                                                           \n",
       "prediction-request-rag-claude            13.498        1704.000\n",
       "prediction-request-rag                   12.041         490.000\n",
       "prediction-online-sme                     9.076        2457.000\n",
       "prediction-online                         4.769        2516.000\n",
       "prediction-request-reasoning              3.247        5883.000\n",
       "prediction-request-reasoning-claude       1.408         639.000\n",
       "claude-prediction-offline                 0.000         107.000\n",
       "claude-prediction-online                  0.000         241.000\n",
       "prediction-offline                        0.000        1453.000\n",
       "prediction-url-cot-claude                 0.000         293.000"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "error[error['request_month_year_week'] == '2024-05-20/2024-05-26'].groupby('tool').agg({'error_perc': 'mean', 'total_requests': 'sum'}).sort_values('error_perc', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>error</th>\n",
       "      <th>tool</th>\n",
       "      <th>request_month_year_week</th>\n",
       "      <th>0.000</th>\n",
       "      <th>1.000</th>\n",
       "      <th>error_perc</th>\n",
       "      <th>total_requests</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>claude-prediction-offline</td>\n",
       "      <td>2024-05-20/2024-05-26</td>\n",
       "      <td>107.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>107.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>claude-prediction-offline</td>\n",
       "      <td>2024-05-13/2024-05-19</td>\n",
       "      <td>203.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>203.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>claude-prediction-offline</td>\n",
       "      <td>2024-05-06/2024-05-12</td>\n",
       "      <td>156.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>156.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>claude-prediction-offline</td>\n",
       "      <td>2024-04-29/2024-05-05</td>\n",
       "      <td>531.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>531.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>claude-prediction-offline</td>\n",
       "      <td>2024-04-22/2024-04-28</td>\n",
       "      <td>816.000</td>\n",
       "      <td>5.000</td>\n",
       "      <td>0.609</td>\n",
       "      <td>821.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "error                       tool  request_month_year_week   0.000  1.000  \\\n",
       "19     claude-prediction-offline    2024-05-20/2024-05-26 107.000  0.000   \n",
       "18     claude-prediction-offline    2024-05-13/2024-05-19 203.000  0.000   \n",
       "17     claude-prediction-offline    2024-05-06/2024-05-12 156.000  0.000   \n",
       "16     claude-prediction-offline    2024-04-29/2024-05-05 531.000  0.000   \n",
       "15     claude-prediction-offline    2024-04-22/2024-04-28 816.000  5.000   \n",
       "\n",
       "error   error_perc   total_requests  \n",
       "19           0.000          107.000  \n",
       "18           0.000          203.000  \n",
       "17           0.000          156.000  \n",
       "16           0.000          531.000  \n",
       "15           0.609          821.000  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# clude-prediction-offline\n",
    "claude_prediction_offline = error[error['tool'] == 'claude-prediction-offline']\n",
    "claude_prediction_offline = claude_prediction_offline.sort_values('request_month_year_week', ascending=False)\n",
    "claude_prediction_offline.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>error</th>\n",
       "      <th>tool</th>\n",
       "      <th>request_month_year_week</th>\n",
       "      <th>0.000</th>\n",
       "      <th>1.000</th>\n",
       "      <th>error_perc</th>\n",
       "      <th>total_requests</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>claude-prediction-online</td>\n",
       "      <td>2024-05-20/2024-05-26</td>\n",
       "      <td>241.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>241.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>claude-prediction-online</td>\n",
       "      <td>2024-05-13/2024-05-19</td>\n",
       "      <td>37.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>37.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>claude-prediction-online</td>\n",
       "      <td>2024-05-06/2024-05-12</td>\n",
       "      <td>176.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>176.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>claude-prediction-online</td>\n",
       "      <td>2024-04-29/2024-05-05</td>\n",
       "      <td>192.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>192.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>claude-prediction-online</td>\n",
       "      <td>2024-04-22/2024-04-28</td>\n",
       "      <td>1937.000</td>\n",
       "      <td>155.000</td>\n",
       "      <td>7.409</td>\n",
       "      <td>2092.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "error                      tool  request_month_year_week    0.000   1.000  \\\n",
       "54     claude-prediction-online    2024-05-20/2024-05-26  241.000   0.000   \n",
       "53     claude-prediction-online    2024-05-13/2024-05-19   37.000   0.000   \n",
       "52     claude-prediction-online    2024-05-06/2024-05-12  176.000   0.000   \n",
       "51     claude-prediction-online    2024-04-29/2024-05-05  192.000   0.000   \n",
       "50     claude-prediction-online    2024-04-22/2024-04-28 1937.000 155.000   \n",
       "\n",
       "error   error_perc   total_requests  \n",
       "54           0.000          241.000  \n",
       "53           0.000           37.000  \n",
       "52           0.000          176.000  \n",
       "51           0.000          192.000  \n",
       "50           7.409         2092.000  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# claude-prediction-online\n",
    "claude_prediction_online = error[error['tool'] == 'claude-prediction-online']\n",
    "claude_prediction_online = claude_prediction_online.sort_values('request_month_year_week', ascending=False)\n",
    "claude_prediction_online.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>error</th>\n",
       "      <th>tool</th>\n",
       "      <th>request_month_year_week</th>\n",
       "      <th>0.000</th>\n",
       "      <th>1.000</th>\n",
       "      <th>error_perc</th>\n",
       "      <th>total_requests</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>prediction-offline</td>\n",
       "      <td>2024-05-20/2024-05-26</td>\n",
       "      <td>1453.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1453.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>prediction-offline</td>\n",
       "      <td>2024-05-13/2024-05-19</td>\n",
       "      <td>4270.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.023</td>\n",
       "      <td>4271.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>prediction-offline</td>\n",
       "      <td>2024-05-06/2024-05-12</td>\n",
       "      <td>2500.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>2500.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>prediction-offline</td>\n",
       "      <td>2024-04-29/2024-05-05</td>\n",
       "      <td>1825.000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>0.109</td>\n",
       "      <td>1827.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>prediction-offline</td>\n",
       "      <td>2024-04-22/2024-04-28</td>\n",
       "      <td>381.000</td>\n",
       "      <td>375.000</td>\n",
       "      <td>49.603</td>\n",
       "      <td>756.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "error                tool  request_month_year_week    0.000   1.000  \\\n",
       "84     prediction-offline    2024-05-20/2024-05-26 1453.000   0.000   \n",
       "83     prediction-offline    2024-05-13/2024-05-19 4270.000   1.000   \n",
       "82     prediction-offline    2024-05-06/2024-05-12 2500.000   0.000   \n",
       "81     prediction-offline    2024-04-29/2024-05-05 1825.000   2.000   \n",
       "80     prediction-offline    2024-04-22/2024-04-28  381.000 375.000   \n",
       "\n",
       "error   error_perc   total_requests  \n",
       "84           0.000         1453.000  \n",
       "83           0.023         4271.000  \n",
       "82           0.000         2500.000  \n",
       "81           0.109         1827.000  \n",
       "80          49.603          756.000  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# prediction-offline\n",
    "prediction_offline = error[error['tool'] == 'prediction-offline']\n",
    "prediction_offline = prediction_offline.sort_values('request_month_year_week', ascending=False)\n",
    "prediction_offline.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>error</th>\n",
       "      <th>tool</th>\n",
       "      <th>request_month_year_week</th>\n",
       "      <th>0.000</th>\n",
       "      <th>1.000</th>\n",
       "      <th>error_perc</th>\n",
       "      <th>total_requests</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>prediction-online</td>\n",
       "      <td>2024-05-20/2024-05-26</td>\n",
       "      <td>2396.000</td>\n",
       "      <td>120.000</td>\n",
       "      <td>4.769</td>\n",
       "      <td>2516.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>prediction-online</td>\n",
       "      <td>2024-05-13/2024-05-19</td>\n",
       "      <td>2642.000</td>\n",
       "      <td>393.000</td>\n",
       "      <td>12.949</td>\n",
       "      <td>3035.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>prediction-online</td>\n",
       "      <td>2024-05-06/2024-05-12</td>\n",
       "      <td>2840.000</td>\n",
       "      <td>266.000</td>\n",
       "      <td>8.564</td>\n",
       "      <td>3106.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>prediction-online</td>\n",
       "      <td>2024-04-29/2024-05-05</td>\n",
       "      <td>2155.000</td>\n",
       "      <td>24.000</td>\n",
       "      <td>1.101</td>\n",
       "      <td>2179.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>prediction-online</td>\n",
       "      <td>2024-04-22/2024-04-28</td>\n",
       "      <td>252.000</td>\n",
       "      <td>153.000</td>\n",
       "      <td>37.778</td>\n",
       "      <td>405.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "error               tool  request_month_year_week    0.000   1.000  \\\n",
       "139    prediction-online    2024-05-20/2024-05-26 2396.000 120.000   \n",
       "138    prediction-online    2024-05-13/2024-05-19 2642.000 393.000   \n",
       "137    prediction-online    2024-05-06/2024-05-12 2840.000 266.000   \n",
       "136    prediction-online    2024-04-29/2024-05-05 2155.000  24.000   \n",
       "135    prediction-online    2024-04-22/2024-04-28  252.000 153.000   \n",
       "\n",
       "error   error_perc   total_requests  \n",
       "139          4.769         2516.000  \n",
       "138         12.949         3035.000  \n",
       "137          8.564         3106.000  \n",
       "136          1.101         2179.000  \n",
       "135         37.778          405.000  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# prediction-online\n",
    "prediction_online = error[error['tool'] == 'prediction-online']\n",
    "prediction_online = prediction_online.sort_values('request_month_year_week', ascending=False)\n",
    "prediction_online.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>error</th>\n",
       "      <th>tool</th>\n",
       "      <th>request_month_year_week</th>\n",
       "      <th>0.000</th>\n",
       "      <th>1.000</th>\n",
       "      <th>error_perc</th>\n",
       "      <th>total_requests</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>prediction-offline-sme</td>\n",
       "      <td>2024-04-29/2024-05-05</td>\n",
       "      <td>8.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>prediction-offline-sme</td>\n",
       "      <td>2024-04-22/2024-04-28</td>\n",
       "      <td>159.000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>1.242</td>\n",
       "      <td>161.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>prediction-offline-sme</td>\n",
       "      <td>2024-04-15/2024-04-21</td>\n",
       "      <td>717.000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>0.278</td>\n",
       "      <td>719.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>prediction-offline-sme</td>\n",
       "      <td>2024-04-08/2024-04-14</td>\n",
       "      <td>4.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>4.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>prediction-offline-sme</td>\n",
       "      <td>2024-04-01/2024-04-07</td>\n",
       "      <td>197.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.505</td>\n",
       "      <td>198.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "error                    tool  request_month_year_week   0.000  1.000  \\\n",
       "104    prediction-offline-sme    2024-04-29/2024-05-05   8.000  0.000   \n",
       "103    prediction-offline-sme    2024-04-22/2024-04-28 159.000  2.000   \n",
       "102    prediction-offline-sme    2024-04-15/2024-04-21 717.000  2.000   \n",
       "101    prediction-offline-sme    2024-04-08/2024-04-14   4.000  0.000   \n",
       "100    prediction-offline-sme    2024-04-01/2024-04-07 197.000  1.000   \n",
       "\n",
       "error   error_perc   total_requests  \n",
       "104          0.000            8.000  \n",
       "103          1.242          161.000  \n",
       "102          0.278          719.000  \n",
       "101          0.000            4.000  \n",
       "100          0.505          198.000  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# prediction-offline-sme\n",
    "prediction_offline_sme = error[error['tool'] == 'prediction-offline-sme']\n",
    "prediction_offline_sme = prediction_offline_sme.sort_values('request_month_year_week', ascending=False)\n",
    "prediction_offline_sme.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>error</th>\n",
       "      <th>tool</th>\n",
       "      <th>request_month_year_week</th>\n",
       "      <th>0.000</th>\n",
       "      <th>1.000</th>\n",
       "      <th>error_perc</th>\n",
       "      <th>total_requests</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>prediction-online-sme</td>\n",
       "      <td>2024-05-20/2024-05-26</td>\n",
       "      <td>2234.000</td>\n",
       "      <td>223.000</td>\n",
       "      <td>9.076</td>\n",
       "      <td>2457.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>prediction-online-sme</td>\n",
       "      <td>2024-05-13/2024-05-19</td>\n",
       "      <td>3141.000</td>\n",
       "      <td>668.000</td>\n",
       "      <td>17.537</td>\n",
       "      <td>3809.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>prediction-online-sme</td>\n",
       "      <td>2024-05-06/2024-05-12</td>\n",
       "      <td>3799.000</td>\n",
       "      <td>562.000</td>\n",
       "      <td>12.887</td>\n",
       "      <td>4361.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>prediction-online-sme</td>\n",
       "      <td>2024-04-29/2024-05-05</td>\n",
       "      <td>2534.000</td>\n",
       "      <td>6.000</td>\n",
       "      <td>0.236</td>\n",
       "      <td>2540.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>prediction-online-sme</td>\n",
       "      <td>2024-04-22/2024-04-28</td>\n",
       "      <td>2679.000</td>\n",
       "      <td>1075.000</td>\n",
       "      <td>28.636</td>\n",
       "      <td>3754.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "error                   tool  request_month_year_week    0.000    1.000  \\\n",
       "175    prediction-online-sme    2024-05-20/2024-05-26 2234.000  223.000   \n",
       "174    prediction-online-sme    2024-05-13/2024-05-19 3141.000  668.000   \n",
       "173    prediction-online-sme    2024-05-06/2024-05-12 3799.000  562.000   \n",
       "172    prediction-online-sme    2024-04-29/2024-05-05 2534.000    6.000   \n",
       "171    prediction-online-sme    2024-04-22/2024-04-28 2679.000 1075.000   \n",
       "\n",
       "error   error_perc   total_requests  \n",
       "175          9.076         2457.000  \n",
       "174         17.537         3809.000  \n",
       "173         12.887         4361.000  \n",
       "172          0.236         2540.000  \n",
       "171         28.636         3754.000  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# prediction-online-sme\n",
    "prediction_online_sme = error[error['tool'] == 'prediction-online-sme']\n",
    "prediction_online_sme = prediction_online_sme.sort_values('request_month_year_week', ascending=False)\n",
    "prediction_online_sme.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>error</th>\n",
       "      <th>tool</th>\n",
       "      <th>request_month_year_week</th>\n",
       "      <th>0.000</th>\n",
       "      <th>1.000</th>\n",
       "      <th>error_perc</th>\n",
       "      <th>total_requests</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>prediction-request-rag</td>\n",
       "      <td>2024-05-20/2024-05-26</td>\n",
       "      <td>431.000</td>\n",
       "      <td>59.000</td>\n",
       "      <td>12.041</td>\n",
       "      <td>490.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>prediction-request-rag</td>\n",
       "      <td>2024-05-13/2024-05-19</td>\n",
       "      <td>355.000</td>\n",
       "      <td>55.000</td>\n",
       "      <td>13.415</td>\n",
       "      <td>410.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>prediction-request-rag</td>\n",
       "      <td>2024-05-06/2024-05-12</td>\n",
       "      <td>470.000</td>\n",
       "      <td>125.000</td>\n",
       "      <td>21.008</td>\n",
       "      <td>595.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>prediction-request-rag</td>\n",
       "      <td>2024-04-29/2024-05-05</td>\n",
       "      <td>544.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>544.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>prediction-request-rag</td>\n",
       "      <td>2024-04-22/2024-04-28</td>\n",
       "      <td>2011.000</td>\n",
       "      <td>881.000</td>\n",
       "      <td>30.463</td>\n",
       "      <td>2892.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "error                    tool  request_month_year_week    0.000   1.000  \\\n",
       "188    prediction-request-rag    2024-05-20/2024-05-26  431.000  59.000   \n",
       "187    prediction-request-rag    2024-05-13/2024-05-19  355.000  55.000   \n",
       "186    prediction-request-rag    2024-05-06/2024-05-12  470.000 125.000   \n",
       "185    prediction-request-rag    2024-04-29/2024-05-05  544.000   0.000   \n",
       "184    prediction-request-rag    2024-04-22/2024-04-28 2011.000 881.000   \n",
       "\n",
       "error   error_perc   total_requests  \n",
       "188         12.041          490.000  \n",
       "187         13.415          410.000  \n",
       "186         21.008          595.000  \n",
       "185          0.000          544.000  \n",
       "184         30.463         2892.000  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# prediction-request-rag\n",
    "prediction_request_rag = error[error['tool'] == 'prediction-request-rag']\n",
    "prediction_request_rag = prediction_request_rag.sort_values('request_month_year_week', ascending=False)\n",
    "prediction_request_rag.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>error</th>\n",
       "      <th>tool</th>\n",
       "      <th>request_month_year_week</th>\n",
       "      <th>0.000</th>\n",
       "      <th>1.000</th>\n",
       "      <th>error_perc</th>\n",
       "      <th>total_requests</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>prediction-request-reasoning-claude</td>\n",
       "      <td>2024-05-20/2024-05-26</td>\n",
       "      <td>630.000</td>\n",
       "      <td>9.000</td>\n",
       "      <td>1.408</td>\n",
       "      <td>639.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>prediction-request-reasoning-claude</td>\n",
       "      <td>2024-05-13/2024-05-19</td>\n",
       "      <td>309.000</td>\n",
       "      <td>205.000</td>\n",
       "      <td>39.883</td>\n",
       "      <td>514.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>212</th>\n",
       "      <td>prediction-request-reasoning-claude</td>\n",
       "      <td>2024-05-06/2024-05-12</td>\n",
       "      <td>478.000</td>\n",
       "      <td>54.000</td>\n",
       "      <td>10.150</td>\n",
       "      <td>532.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211</th>\n",
       "      <td>prediction-request-reasoning-claude</td>\n",
       "      <td>2024-04-29/2024-05-05</td>\n",
       "      <td>218.000</td>\n",
       "      <td>8.000</td>\n",
       "      <td>3.540</td>\n",
       "      <td>226.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>210</th>\n",
       "      <td>prediction-request-reasoning-claude</td>\n",
       "      <td>2024-04-22/2024-04-28</td>\n",
       "      <td>2053.000</td>\n",
       "      <td>575.000</td>\n",
       "      <td>21.880</td>\n",
       "      <td>2628.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "error                                 tool  request_month_year_week    0.000  \\\n",
       "214    prediction-request-reasoning-claude    2024-05-20/2024-05-26  630.000   \n",
       "213    prediction-request-reasoning-claude    2024-05-13/2024-05-19  309.000   \n",
       "212    prediction-request-reasoning-claude    2024-05-06/2024-05-12  478.000   \n",
       "211    prediction-request-reasoning-claude    2024-04-29/2024-05-05  218.000   \n",
       "210    prediction-request-reasoning-claude    2024-04-22/2024-04-28 2053.000   \n",
       "\n",
       "error   1.000   error_perc   total_requests  \n",
       "214     9.000        1.408          639.000  \n",
       "213   205.000       39.883          514.000  \n",
       "212    54.000       10.150          532.000  \n",
       "211     8.000        3.540          226.000  \n",
       "210   575.000       21.880         2628.000  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# prediction-request-reasoning-claude\n",
    "prediction_request_reasoning_claude = error[error['tool'] == 'prediction-request-reasoning-claude']\n",
    "prediction_request_reasoning_claude = prediction_request_reasoning_claude.sort_values('request_month_year_week', ascending=False)\n",
    "prediction_request_reasoning_claude.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>error</th>\n",
       "      <th>tool</th>\n",
       "      <th>request_month_year_week</th>\n",
       "      <th>0.000</th>\n",
       "      <th>1.000</th>\n",
       "      <th>error_perc</th>\n",
       "      <th>total_requests</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>prediction-request-rag-claude</td>\n",
       "      <td>2024-05-20/2024-05-26</td>\n",
       "      <td>1474.000</td>\n",
       "      <td>230.000</td>\n",
       "      <td>13.498</td>\n",
       "      <td>1704.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>prediction-request-rag-claude</td>\n",
       "      <td>2024-05-13/2024-05-19</td>\n",
       "      <td>2378.000</td>\n",
       "      <td>274.000</td>\n",
       "      <td>10.332</td>\n",
       "      <td>2652.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>prediction-request-rag-claude</td>\n",
       "      <td>2024-05-06/2024-05-12</td>\n",
       "      <td>2850.000</td>\n",
       "      <td>777.000</td>\n",
       "      <td>21.423</td>\n",
       "      <td>3627.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>prediction-request-rag-claude</td>\n",
       "      <td>2024-04-29/2024-05-05</td>\n",
       "      <td>1313.000</td>\n",
       "      <td>8.000</td>\n",
       "      <td>0.606</td>\n",
       "      <td>1321.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>prediction-request-rag-claude</td>\n",
       "      <td>2024-04-22/2024-04-28</td>\n",
       "      <td>1113.000</td>\n",
       "      <td>345.000</td>\n",
       "      <td>23.663</td>\n",
       "      <td>1458.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "error                           tool  request_month_year_week    0.000  \\\n",
       "196    prediction-request-rag-claude    2024-05-20/2024-05-26 1474.000   \n",
       "195    prediction-request-rag-claude    2024-05-13/2024-05-19 2378.000   \n",
       "194    prediction-request-rag-claude    2024-05-06/2024-05-12 2850.000   \n",
       "193    prediction-request-rag-claude    2024-04-29/2024-05-05 1313.000   \n",
       "192    prediction-request-rag-claude    2024-04-22/2024-04-28 1113.000   \n",
       "\n",
       "error   1.000   error_perc   total_requests  \n",
       "196   230.000       13.498         1704.000  \n",
       "195   274.000       10.332         2652.000  \n",
       "194   777.000       21.423         3627.000  \n",
       "193     8.000        0.606         1321.000  \n",
       "192   345.000       23.663         1458.000  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prediction_request_rag_claude = error[error['tool'] == 'prediction-request-rag-claude']\n",
    "prediction_request_rag_claude = prediction_request_rag_claude.sort_values('request_month_year_week', ascending=False)\n",
    "prediction_request_rag_claude.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>error</th>\n",
       "      <th>tool</th>\n",
       "      <th>request_month_year_week</th>\n",
       "      <th>0.000</th>\n",
       "      <th>1.000</th>\n",
       "      <th>error_perc</th>\n",
       "      <th>total_requests</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>222</th>\n",
       "      <td>prediction-url-cot-claude</td>\n",
       "      <td>2024-05-20/2024-05-26</td>\n",
       "      <td>293.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>293.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>221</th>\n",
       "      <td>prediction-url-cot-claude</td>\n",
       "      <td>2024-05-13/2024-05-19</td>\n",
       "      <td>93.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>93.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>prediction-url-cot-claude</td>\n",
       "      <td>2024-05-06/2024-05-12</td>\n",
       "      <td>225.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>225.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219</th>\n",
       "      <td>prediction-url-cot-claude</td>\n",
       "      <td>2024-04-29/2024-05-05</td>\n",
       "      <td>270.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>270.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>218</th>\n",
       "      <td>prediction-url-cot-claude</td>\n",
       "      <td>2024-04-22/2024-04-28</td>\n",
       "      <td>1506.000</td>\n",
       "      <td>65.000</td>\n",
       "      <td>4.137</td>\n",
       "      <td>1571.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "error                       tool  request_month_year_week    0.000  1.000  \\\n",
       "222    prediction-url-cot-claude    2024-05-20/2024-05-26  293.000  0.000   \n",
       "221    prediction-url-cot-claude    2024-05-13/2024-05-19   93.000  0.000   \n",
       "220    prediction-url-cot-claude    2024-05-06/2024-05-12  225.000  0.000   \n",
       "219    prediction-url-cot-claude    2024-04-29/2024-05-05  270.000  0.000   \n",
       "218    prediction-url-cot-claude    2024-04-22/2024-04-28 1506.000 65.000   \n",
       "\n",
       "error   error_perc   total_requests  \n",
       "222          0.000          293.000  \n",
       "221          0.000           93.000  \n",
       "220          0.000          225.000  \n",
       "219          0.000          270.000  \n",
       "218          4.137         1571.000  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prediction_url_cot_claude = error[error['tool'] == 'prediction-url-cot-claude']\n",
    "prediction_url_cot_claude = prediction_url_cot_claude.sort_values('request_month_year_week', ascending=False)\n",
    "prediction_url_cot_claude.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'tools_inc' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[7], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mdel\u001b[39;00m tools\n\u001b[0;32m----> 2\u001b[0m \u001b[38;5;28;01mdel\u001b[39;00m \u001b[43mtools_inc\u001b[49m\n\u001b[1;32m      3\u001b[0m \u001b[38;5;28;01mdel\u001b[39;00m error\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01mdel\u001b[39;00m error_total\n",
      "\u001b[0;31mNameError\u001b[0m: name 'tools_inc' is not defined"
     ]
    }
   ],
   "source": [
    "del tools\n",
    "del tools_inc\n",
    "del error\n",
    "del error_total\n",
    "\n",
    "gc.collect()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Win analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "# only include non error requests\n",
    "tools_non_error = tools_inc[tools_inc['error'] != 1]\n",
    "tools_non_error['currentAnswer'].replace('no', 'No', inplace=True)\n",
    "tools_non_error['currentAnswer'].replace('yes', 'Yes', inplace=True)\n",
    "tools_non_error = tools_non_error[tools_non_error['currentAnswer'].isin(['Yes', 'No'])]\n",
    "tools_non_error = tools_non_error[tools_non_error['vote'].isin(['Yes', 'No'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "tools_non_error['win'] = tools_non_error['currentAnswer'] == tools_non_error['vote']\n",
    "tools_non_error['win'] = tools_non_error['win'].astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "wins = tools_non_error.groupby(['tool', 'request_month_year_week', 'win']).size().unstack().fillna(0)\n",
    "wins['win_perc'] = (wins[1] / (wins[0] + wins[1]))*100\n",
    "wins.reset_index(inplace=True)\n",
    "wins['total_request'] = wins[0] + wins[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['claude-prediction-offline', 'claude-prediction-online',\n",
       "       'prediction-offline', 'prediction-offline-sme',\n",
       "       'prediction-online', 'prediction-online-sme',\n",
       "       'prediction-request-rag', 'prediction-request-rag-claude',\n",
       "       'prediction-request-reasoning',\n",
       "       'prediction-request-reasoning-claude', 'prediction-url-cot-claude'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wins['tool'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>win</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>win_perc</th>\n",
       "      <th>total_request</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>request_month_year_week</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-07-17/2023-07-23</th>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>50.000</td>\n",
       "      <td>2.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-07-24/2023-07-30</th>\n",
       "      <td>12.000</td>\n",
       "      <td>12.000</td>\n",
       "      <td>50.000</td>\n",
       "      <td>24.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-07-31/2023-08-06</th>\n",
       "      <td>360.000</td>\n",
       "      <td>229.000</td>\n",
       "      <td>41.979</td>\n",
       "      <td>589.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-07/2023-08-13</th>\n",
       "      <td>177.000</td>\n",
       "      <td>110.000</td>\n",
       "      <td>44.123</td>\n",
       "      <td>287.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-14/2023-08-20</th>\n",
       "      <td>784.000</td>\n",
       "      <td>559.000</td>\n",
       "      <td>41.623</td>\n",
       "      <td>1343.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-21/2023-08-27</th>\n",
       "      <td>596.000</td>\n",
       "      <td>502.000</td>\n",
       "      <td>45.719</td>\n",
       "      <td>1098.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-28/2023-09-03</th>\n",
       "      <td>958.000</td>\n",
       "      <td>502.000</td>\n",
       "      <td>34.384</td>\n",
       "      <td>1460.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-04/2023-09-10</th>\n",
       "      <td>1609.000</td>\n",
       "      <td>1418.000</td>\n",
       "      <td>46.845</td>\n",
       "      <td>3027.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-11/2023-09-17</th>\n",
       "      <td>1171.000</td>\n",
       "      <td>1380.000</td>\n",
       "      <td>54.096</td>\n",
       "      <td>2551.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-18/2023-09-24</th>\n",
       "      <td>2150.000</td>\n",
       "      <td>2307.000</td>\n",
       "      <td>60.968</td>\n",
       "      <td>4457.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-25/2023-10-01</th>\n",
       "      <td>992.000</td>\n",
       "      <td>817.000</td>\n",
       "      <td>47.635</td>\n",
       "      <td>1809.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-10-02/2023-10-08</th>\n",
       "      <td>1625.000</td>\n",
       "      <td>1842.000</td>\n",
       "      <td>54.240</td>\n",
       "      <td>3467.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-10-09/2023-10-15</th>\n",
       "      <td>1594.000</td>\n",
       "      <td>2096.000</td>\n",
       "      <td>57.281</td>\n",
       "      <td>3690.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-10-16/2023-10-22</th>\n",
       "      <td>1291.000</td>\n",
       "      <td>1623.000</td>\n",
       "      <td>55.496</td>\n",
       "      <td>2914.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-10-23/2023-10-29</th>\n",
       "      <td>1018.000</td>\n",
       "      <td>1084.000</td>\n",
       "      <td>50.802</td>\n",
       "      <td>2102.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-10-30/2023-11-05</th>\n",
       "      <td>541.000</td>\n",
       "      <td>825.000</td>\n",
       "      <td>64.848</td>\n",
       "      <td>1366.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-06/2023-11-12</th>\n",
       "      <td>1545.000</td>\n",
       "      <td>1776.000</td>\n",
       "      <td>69.014</td>\n",
       "      <td>3321.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-13/2023-11-19</th>\n",
       "      <td>1825.000</td>\n",
       "      <td>2056.000</td>\n",
       "      <td>55.202</td>\n",
       "      <td>3881.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-20/2023-11-26</th>\n",
       "      <td>1567.000</td>\n",
       "      <td>1874.000</td>\n",
       "      <td>58.482</td>\n",
       "      <td>3441.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-27/2023-12-03</th>\n",
       "      <td>1555.000</td>\n",
       "      <td>1773.000</td>\n",
       "      <td>67.721</td>\n",
       "      <td>3328.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-04/2023-12-10</th>\n",
       "      <td>1245.000</td>\n",
       "      <td>1470.000</td>\n",
       "      <td>33.705</td>\n",
       "      <td>2715.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-11/2023-12-17</th>\n",
       "      <td>1462.000</td>\n",
       "      <td>1788.000</td>\n",
       "      <td>52.404</td>\n",
       "      <td>3250.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-18/2023-12-24</th>\n",
       "      <td>1332.000</td>\n",
       "      <td>1557.000</td>\n",
       "      <td>46.687</td>\n",
       "      <td>2889.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-25/2023-12-31</th>\n",
       "      <td>1397.000</td>\n",
       "      <td>1257.000</td>\n",
       "      <td>48.222</td>\n",
       "      <td>2654.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-01-01/2024-01-07</th>\n",
       "      <td>2159.000</td>\n",
       "      <td>1713.000</td>\n",
       "      <td>43.436</td>\n",
       "      <td>3872.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-01-08/2024-01-14</th>\n",
       "      <td>1034.000</td>\n",
       "      <td>890.000</td>\n",
       "      <td>41.597</td>\n",
       "      <td>1924.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-01-15/2024-01-21</th>\n",
       "      <td>2228.000</td>\n",
       "      <td>1758.000</td>\n",
       "      <td>40.827</td>\n",
       "      <td>3986.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-01-22/2024-01-28</th>\n",
       "      <td>2036.000</td>\n",
       "      <td>1970.000</td>\n",
       "      <td>31.617</td>\n",
       "      <td>4006.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-01-29/2024-02-04</th>\n",
       "      <td>2303.000</td>\n",
       "      <td>1791.000</td>\n",
       "      <td>37.106</td>\n",
       "      <td>4094.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-02-05/2024-02-11</th>\n",
       "      <td>2149.000</td>\n",
       "      <td>2189.000</td>\n",
       "      <td>49.808</td>\n",
       "      <td>4338.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-02-12/2024-02-18</th>\n",
       "      <td>1979.000</td>\n",
       "      <td>1956.000</td>\n",
       "      <td>55.949</td>\n",
       "      <td>3935.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-02-19/2024-02-25</th>\n",
       "      <td>1788.000</td>\n",
       "      <td>2002.000</td>\n",
       "      <td>57.697</td>\n",
       "      <td>3790.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-02-26/2024-03-03</th>\n",
       "      <td>2299.000</td>\n",
       "      <td>2350.000</td>\n",
       "      <td>42.051</td>\n",
       "      <td>4649.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-03-04/2024-03-10</th>\n",
       "      <td>4523.000</td>\n",
       "      <td>3500.000</td>\n",
       "      <td>44.989</td>\n",
       "      <td>8023.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-03-11/2024-03-17</th>\n",
       "      <td>4516.000</td>\n",
       "      <td>4705.000</td>\n",
       "      <td>56.713</td>\n",
       "      <td>9221.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-03-18/2024-03-24</th>\n",
       "      <td>5561.000</td>\n",
       "      <td>5581.000</td>\n",
       "      <td>52.903</td>\n",
       "      <td>11142.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-03-25/2024-03-31</th>\n",
       "      <td>5200.000</td>\n",
       "      <td>6965.000</td>\n",
       "      <td>54.644</td>\n",
       "      <td>12165.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-04-01/2024-04-07</th>\n",
       "      <td>2923.000</td>\n",
       "      <td>4258.000</td>\n",
       "      <td>61.323</td>\n",
       "      <td>7181.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-04-08/2024-04-14</th>\n",
       "      <td>1331.000</td>\n",
       "      <td>3412.000</td>\n",
       "      <td>69.522</td>\n",
       "      <td>4743.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "win                            0        1  win_perc  total_request\n",
       "request_month_year_week                                           \n",
       "2023-07-17/2023-07-23      1.000    1.000    50.000          2.000\n",
       "2023-07-24/2023-07-30     12.000   12.000    50.000         24.000\n",
       "2023-07-31/2023-08-06    360.000  229.000    41.979        589.000\n",
       "2023-08-07/2023-08-13    177.000  110.000    44.123        287.000\n",
       "2023-08-14/2023-08-20    784.000  559.000    41.623       1343.000\n",
       "2023-08-21/2023-08-27    596.000  502.000    45.719       1098.000\n",
       "2023-08-28/2023-09-03    958.000  502.000    34.384       1460.000\n",
       "2023-09-04/2023-09-10   1609.000 1418.000    46.845       3027.000\n",
       "2023-09-11/2023-09-17   1171.000 1380.000    54.096       2551.000\n",
       "2023-09-18/2023-09-24   2150.000 2307.000    60.968       4457.000\n",
       "2023-09-25/2023-10-01    992.000  817.000    47.635       1809.000\n",
       "2023-10-02/2023-10-08   1625.000 1842.000    54.240       3467.000\n",
       "2023-10-09/2023-10-15   1594.000 2096.000    57.281       3690.000\n",
       "2023-10-16/2023-10-22   1291.000 1623.000    55.496       2914.000\n",
       "2023-10-23/2023-10-29   1018.000 1084.000    50.802       2102.000\n",
       "2023-10-30/2023-11-05    541.000  825.000    64.848       1366.000\n",
       "2023-11-06/2023-11-12   1545.000 1776.000    69.014       3321.000\n",
       "2023-11-13/2023-11-19   1825.000 2056.000    55.202       3881.000\n",
       "2023-11-20/2023-11-26   1567.000 1874.000    58.482       3441.000\n",
       "2023-11-27/2023-12-03   1555.000 1773.000    67.721       3328.000\n",
       "2023-12-04/2023-12-10   1245.000 1470.000    33.705       2715.000\n",
       "2023-12-11/2023-12-17   1462.000 1788.000    52.404       3250.000\n",
       "2023-12-18/2023-12-24   1332.000 1557.000    46.687       2889.000\n",
       "2023-12-25/2023-12-31   1397.000 1257.000    48.222       2654.000\n",
       "2024-01-01/2024-01-07   2159.000 1713.000    43.436       3872.000\n",
       "2024-01-08/2024-01-14   1034.000  890.000    41.597       1924.000\n",
       "2024-01-15/2024-01-21   2228.000 1758.000    40.827       3986.000\n",
       "2024-01-22/2024-01-28   2036.000 1970.000    31.617       4006.000\n",
       "2024-01-29/2024-02-04   2303.000 1791.000    37.106       4094.000\n",
       "2024-02-05/2024-02-11   2149.000 2189.000    49.808       4338.000\n",
       "2024-02-12/2024-02-18   1979.000 1956.000    55.949       3935.000\n",
       "2024-02-19/2024-02-25   1788.000 2002.000    57.697       3790.000\n",
       "2024-02-26/2024-03-03   2299.000 2350.000    42.051       4649.000\n",
       "2024-03-04/2024-03-10   4523.000 3500.000    44.989       8023.000\n",
       "2024-03-11/2024-03-17   4516.000 4705.000    56.713       9221.000\n",
       "2024-03-18/2024-03-24   5561.000 5581.000    52.903      11142.000\n",
       "2024-03-25/2024-03-31   5200.000 6965.000    54.644      12165.000\n",
       "2024-04-01/2024-04-07   2923.000 4258.000    61.323       7181.000\n",
       "2024-04-08/2024-04-14   1331.000 3412.000    69.522       4743.000"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wins.groupby('request_month_year_week').agg({\n",
    "    0: 'sum',\n",
    "    1: 'sum',\n",
    "    'win_perc': 'mean',\n",
    "    'total_request': 'sum'\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>win</th>\n",
       "      <th>request_month_year_week</th>\n",
       "      <th>win_perc</th>\n",
       "      <th>total_request</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2023-09-18/2023-09-24</td>\n",
       "      <td>100.000</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2023-09-25/2023-10-01</td>\n",
       "      <td>58.333</td>\n",
       "      <td>48.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2023-10-02/2023-10-08</td>\n",
       "      <td>61.783</td>\n",
       "      <td>157.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2023-10-09/2023-10-15</td>\n",
       "      <td>60.588</td>\n",
       "      <td>680.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2023-10-16/2023-10-22</td>\n",
       "      <td>58.791</td>\n",
       "      <td>364.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2023-10-23/2023-10-29</td>\n",
       "      <td>47.143</td>\n",
       "      <td>70.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2023-10-30/2023-11-05</td>\n",
       "      <td>67.647</td>\n",
       "      <td>34.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2023-11-20/2023-11-26</td>\n",
       "      <td>100.000</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2023-11-27/2023-12-03</td>\n",
       "      <td>57.143</td>\n",
       "      <td>7.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2023-12-04/2023-12-10</td>\n",
       "      <td>66.667</td>\n",
       "      <td>6.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2023-12-11/2023-12-17</td>\n",
       "      <td>50.000</td>\n",
       "      <td>2.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2023-12-25/2023-12-31</td>\n",
       "      <td>55.814</td>\n",
       "      <td>43.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2024-01-01/2024-01-07</td>\n",
       "      <td>28.400</td>\n",
       "      <td>250.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2024-01-08/2024-01-14</td>\n",
       "      <td>35.789</td>\n",
       "      <td>190.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2024-01-15/2024-01-21</td>\n",
       "      <td>36.986</td>\n",
       "      <td>292.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2024-01-22/2024-01-28</td>\n",
       "      <td>45.387</td>\n",
       "      <td>271.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2024-01-29/2024-02-04</td>\n",
       "      <td>29.555</td>\n",
       "      <td>247.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2024-02-05/2024-02-11</td>\n",
       "      <td>49.064</td>\n",
       "      <td>267.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2024-02-12/2024-02-18</td>\n",
       "      <td>63.300</td>\n",
       "      <td>297.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2024-02-19/2024-02-25</td>\n",
       "      <td>65.362</td>\n",
       "      <td>690.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2024-03-18/2024-03-24</td>\n",
       "      <td>71.575</td>\n",
       "      <td>781.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2024-03-25/2024-03-31</td>\n",
       "      <td>69.052</td>\n",
       "      <td>3648.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2024-04-01/2024-04-07</td>\n",
       "      <td>60.991</td>\n",
       "      <td>2402.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2024-04-08/2024-04-14</td>\n",
       "      <td>62.205</td>\n",
       "      <td>635.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "win request_month_year_week  win_perc  total_request\n",
       "11    2023-09-18/2023-09-24   100.000          1.000\n",
       "12    2023-09-25/2023-10-01    58.333         48.000\n",
       "13    2023-10-02/2023-10-08    61.783        157.000\n",
       "14    2023-10-09/2023-10-15    60.588        680.000\n",
       "15    2023-10-16/2023-10-22    58.791        364.000\n",
       "16    2023-10-23/2023-10-29    47.143         70.000\n",
       "17    2023-10-30/2023-11-05    67.647         34.000\n",
       "18    2023-11-20/2023-11-26   100.000          1.000\n",
       "19    2023-11-27/2023-12-03    57.143          7.000\n",
       "20    2023-12-04/2023-12-10    66.667          6.000\n",
       "21    2023-12-11/2023-12-17    50.000          2.000\n",
       "22    2023-12-25/2023-12-31    55.814         43.000\n",
       "23    2024-01-01/2024-01-07    28.400        250.000\n",
       "24    2024-01-08/2024-01-14    35.789        190.000\n",
       "25    2024-01-15/2024-01-21    36.986        292.000\n",
       "26    2024-01-22/2024-01-28    45.387        271.000\n",
       "27    2024-01-29/2024-02-04    29.555        247.000\n",
       "28    2024-02-05/2024-02-11    49.064        267.000\n",
       "29    2024-02-12/2024-02-18    63.300        297.000\n",
       "30    2024-02-19/2024-02-25    65.362        690.000\n",
       "31    2024-03-18/2024-03-24    71.575        781.000\n",
       "32    2024-03-25/2024-03-31    69.052       3648.000\n",
       "33    2024-04-01/2024-04-07    60.991       2402.000\n",
       "34    2024-04-08/2024-04-14    62.205        635.000"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# select only claude-prediction-online and plot request_month_year_week vs win_perc\n",
    "claude_prediction_online = wins[wins['tool'] == 'claude-prediction-online']\n",
    "claude_prediction_online = claude_prediction_online[['request_month_year_week', 'win_perc', 'total_request']]\n",
    "claude_prediction_online = claude_prediction_online.sort_values(by='request_month_year_week')\n",
    "\n",
    "claude_prediction_online.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>win</th>\n",
       "      <th>request_month_year_week</th>\n",
       "      <th>win_perc</th>\n",
       "      <th>total_request</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2023-09-18/2023-09-24</td>\n",
       "      <td>16.667</td>\n",
       "      <td>6.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2023-09-25/2023-10-01</td>\n",
       "      <td>53.205</td>\n",
       "      <td>156.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2023-10-02/2023-10-08</td>\n",
       "      <td>53.333</td>\n",
       "      <td>285.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2023-10-09/2023-10-15</td>\n",
       "      <td>60.477</td>\n",
       "      <td>377.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2023-10-16/2023-10-22</td>\n",
       "      <td>57.854</td>\n",
       "      <td>522.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2023-10-23/2023-10-29</td>\n",
       "      <td>56.383</td>\n",
       "      <td>376.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2023-10-30/2023-11-05</td>\n",
       "      <td>72.000</td>\n",
       "      <td>75.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2023-11-06/2023-11-12</td>\n",
       "      <td>100.000</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2023-11-13/2023-11-19</td>\n",
       "      <td>100.000</td>\n",
       "      <td>2.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2023-12-18/2023-12-24</td>\n",
       "      <td>20.000</td>\n",
       "      <td>5.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2024-03-25/2024-03-31</td>\n",
       "      <td>100.000</td>\n",
       "      <td>2.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "win request_month_year_week  win_perc  total_request\n",
       "0     2023-09-18/2023-09-24    16.667          6.000\n",
       "1     2023-09-25/2023-10-01    53.205        156.000\n",
       "2     2023-10-02/2023-10-08    53.333        285.000\n",
       "3     2023-10-09/2023-10-15    60.477        377.000\n",
       "4     2023-10-16/2023-10-22    57.854        522.000\n",
       "5     2023-10-23/2023-10-29    56.383        376.000\n",
       "6     2023-10-30/2023-11-05    72.000         75.000\n",
       "7     2023-11-06/2023-11-12   100.000          1.000\n",
       "8     2023-11-13/2023-11-19   100.000          2.000\n",
       "9     2023-12-18/2023-12-24    20.000          5.000\n",
       "10    2024-03-25/2024-03-31   100.000          2.000"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# select only claude-prediction-offline and plot request_month_year_week vs win_perc\n",
    "claude_prediction_offline = wins[wins['tool'] == 'claude-prediction-offline']\n",
    "claude_prediction_offline = claude_prediction_offline[['request_month_year_week', 'win_perc', 'total_request']]\n",
    "claude_prediction_offline = claude_prediction_offline.sort_values(by='request_month_year_week')\n",
    "\n",
    "claude_prediction_offline.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>win</th>\n",
       "      <th>request_month_year_week</th>\n",
       "      <th>win_perc</th>\n",
       "      <th>total_request</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>2023-07-17/2023-07-23</td>\n",
       "      <td>50.000</td>\n",
       "      <td>2.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>2023-07-24/2023-07-30</td>\n",
       "      <td>50.000</td>\n",
       "      <td>24.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>2023-07-31/2023-08-06</td>\n",
       "      <td>38.306</td>\n",
       "      <td>543.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>2023-08-07/2023-08-13</td>\n",
       "      <td>38.246</td>\n",
       "      <td>285.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>2023-08-14/2023-08-20</td>\n",
       "      <td>41.623</td>\n",
       "      <td>1343.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>2023-08-21/2023-08-27</td>\n",
       "      <td>45.719</td>\n",
       "      <td>1098.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>2023-08-28/2023-09-03</td>\n",
       "      <td>34.384</td>\n",
       "      <td>1460.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>2023-09-04/2023-09-10</td>\n",
       "      <td>46.845</td>\n",
       "      <td>3027.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>2023-09-11/2023-09-17</td>\n",
       "      <td>54.096</td>\n",
       "      <td>2551.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>2023-09-18/2023-09-24</td>\n",
       "      <td>51.602</td>\n",
       "      <td>4246.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>2023-09-25/2023-10-01</td>\n",
       "      <td>43.876</td>\n",
       "      <td>743.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>2023-10-02/2023-10-08</td>\n",
       "      <td>50.538</td>\n",
       "      <td>837.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>2023-10-09/2023-10-15</td>\n",
       "      <td>50.976</td>\n",
       "      <td>973.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>2023-10-16/2023-10-22</td>\n",
       "      <td>56.146</td>\n",
       "      <td>903.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>2023-10-23/2023-10-29</td>\n",
       "      <td>48.822</td>\n",
       "      <td>594.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>2023-10-30/2023-11-05</td>\n",
       "      <td>60.392</td>\n",
       "      <td>664.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>2023-11-06/2023-11-12</td>\n",
       "      <td>52.533</td>\n",
       "      <td>1757.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>2023-11-13/2023-11-19</td>\n",
       "      <td>53.892</td>\n",
       "      <td>2004.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>2023-11-20/2023-11-26</td>\n",
       "      <td>53.202</td>\n",
       "      <td>1780.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>2023-11-27/2023-12-03</td>\n",
       "      <td>54.253</td>\n",
       "      <td>1058.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>2023-12-04/2023-12-10</td>\n",
       "      <td>47.500</td>\n",
       "      <td>80.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>2023-12-11/2023-12-17</td>\n",
       "      <td>52.174</td>\n",
       "      <td>23.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>2023-12-18/2023-12-24</td>\n",
       "      <td>69.863</td>\n",
       "      <td>73.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>2023-12-25/2023-12-31</td>\n",
       "      <td>41.509</td>\n",
       "      <td>53.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>2024-01-01/2024-01-07</td>\n",
       "      <td>0.000</td>\n",
       "      <td>2.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>2024-01-22/2024-01-28</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>2024-03-25/2024-03-31</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "win request_month_year_week  win_perc  total_request\n",
       "72    2023-07-17/2023-07-23    50.000          2.000\n",
       "73    2023-07-24/2023-07-30    50.000         24.000\n",
       "74    2023-07-31/2023-08-06    38.306        543.000\n",
       "75    2023-08-07/2023-08-13    38.246        285.000\n",
       "76    2023-08-14/2023-08-20    41.623       1343.000\n",
       "77    2023-08-21/2023-08-27    45.719       1098.000\n",
       "78    2023-08-28/2023-09-03    34.384       1460.000\n",
       "79    2023-09-04/2023-09-10    46.845       3027.000\n",
       "80    2023-09-11/2023-09-17    54.096       2551.000\n",
       "81    2023-09-18/2023-09-24    51.602       4246.000\n",
       "82    2023-09-25/2023-10-01    43.876        743.000\n",
       "83    2023-10-02/2023-10-08    50.538        837.000\n",
       "84    2023-10-09/2023-10-15    50.976        973.000\n",
       "85    2023-10-16/2023-10-22    56.146        903.000\n",
       "86    2023-10-23/2023-10-29    48.822        594.000\n",
       "87    2023-10-30/2023-11-05    60.392        664.000\n",
       "88    2023-11-06/2023-11-12    52.533       1757.000\n",
       "89    2023-11-13/2023-11-19    53.892       2004.000\n",
       "90    2023-11-20/2023-11-26    53.202       1780.000\n",
       "91    2023-11-27/2023-12-03    54.253       1058.000\n",
       "92    2023-12-04/2023-12-10    47.500         80.000\n",
       "93    2023-12-11/2023-12-17    52.174         23.000\n",
       "94    2023-12-18/2023-12-24    69.863         73.000\n",
       "95    2023-12-25/2023-12-31    41.509         53.000\n",
       "96    2024-01-01/2024-01-07     0.000          2.000\n",
       "97    2024-01-22/2024-01-28     0.000          1.000\n",
       "98    2024-03-25/2024-03-31     0.000          1.000"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# select only prediction-online and plot request_month_year_week vs win_perc\n",
    "prediction_online = wins[wins['tool'] == 'prediction-online']\n",
    "prediction_online = prediction_online[['request_month_year_week', 'win_perc', 'total_request']]\n",
    "prediction_online = prediction_online.sort_values(by='request_month_year_week')\n",
    "\n",
    "prediction_online.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>win</th>\n",
       "      <th>request_month_year_week</th>\n",
       "      <th>win_perc</th>\n",
       "      <th>total_request</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2023-07-31/2023-08-06</td>\n",
       "      <td>45.652</td>\n",
       "      <td>46.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>2023-08-07/2023-08-13</td>\n",
       "      <td>50.000</td>\n",
       "      <td>2.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>2023-09-18/2023-09-24</td>\n",
       "      <td>51.128</td>\n",
       "      <td>133.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>2023-09-25/2023-10-01</td>\n",
       "      <td>36.864</td>\n",
       "      <td>236.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>2023-10-02/2023-10-08</td>\n",
       "      <td>50.077</td>\n",
       "      <td>651.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>2023-10-09/2023-10-15</td>\n",
       "      <td>52.392</td>\n",
       "      <td>418.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>2023-10-16/2023-10-22</td>\n",
       "      <td>52.658</td>\n",
       "      <td>395.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>2023-10-23/2023-10-29</td>\n",
       "      <td>45.503</td>\n",
       "      <td>189.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>2023-10-30/2023-11-05</td>\n",
       "      <td>75.000</td>\n",
       "      <td>40.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>2023-11-13/2023-11-19</td>\n",
       "      <td>50.000</td>\n",
       "      <td>2.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>2023-11-20/2023-11-26</td>\n",
       "      <td>33.333</td>\n",
       "      <td>3.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>2023-11-27/2023-12-03</td>\n",
       "      <td>88.235</td>\n",
       "      <td>17.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>2023-12-04/2023-12-10</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>2023-12-18/2023-12-24</td>\n",
       "      <td>50.000</td>\n",
       "      <td>6.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>2024-01-01/2024-01-07</td>\n",
       "      <td>100.000</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>2024-03-11/2024-03-17</td>\n",
       "      <td>62.808</td>\n",
       "      <td>406.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>2024-03-18/2024-03-24</td>\n",
       "      <td>54.453</td>\n",
       "      <td>2448.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>2024-03-25/2024-03-31</td>\n",
       "      <td>58.729</td>\n",
       "      <td>2360.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>2024-04-01/2024-04-07</td>\n",
       "      <td>57.055</td>\n",
       "      <td>652.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>2024-04-08/2024-04-14</td>\n",
       "      <td>75.641</td>\n",
       "      <td>468.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "win request_month_year_week  win_perc  total_request\n",
       "35    2023-07-31/2023-08-06    45.652         46.000\n",
       "36    2023-08-07/2023-08-13    50.000          2.000\n",
       "37    2023-09-18/2023-09-24    51.128        133.000\n",
       "38    2023-09-25/2023-10-01    36.864        236.000\n",
       "39    2023-10-02/2023-10-08    50.077        651.000\n",
       "40    2023-10-09/2023-10-15    52.392        418.000\n",
       "41    2023-10-16/2023-10-22    52.658        395.000\n",
       "42    2023-10-23/2023-10-29    45.503        189.000\n",
       "43    2023-10-30/2023-11-05    75.000         40.000\n",
       "44    2023-11-13/2023-11-19    50.000          2.000\n",
       "45    2023-11-20/2023-11-26    33.333          3.000\n",
       "46    2023-11-27/2023-12-03    88.235         17.000\n",
       "47    2023-12-04/2023-12-10     0.000          1.000\n",
       "48    2023-12-18/2023-12-24    50.000          6.000\n",
       "49    2024-01-01/2024-01-07   100.000          1.000\n",
       "50    2024-03-11/2024-03-17    62.808        406.000\n",
       "51    2024-03-18/2024-03-24    54.453       2448.000\n",
       "52    2024-03-25/2024-03-31    58.729       2360.000\n",
       "53    2024-04-01/2024-04-07    57.055        652.000\n",
       "54    2024-04-08/2024-04-14    75.641        468.000"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# select only prediction-offline and plot request_month_year_week vs win_perc\n",
    "prediction_offline = wins[wins['tool'] == 'prediction-offline']\n",
    "prediction_offline = prediction_offline[['request_month_year_week', 'win_perc', 'total_request']]\n",
    "prediction_offline = prediction_offline.sort_values(by='request_month_year_week')\n",
    "\n",
    "prediction_offline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>win</th>\n",
       "      <th>request_month_year_week</th>\n",
       "      <th>win_perc</th>\n",
       "      <th>total_request</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>2023-09-18/2023-09-24</td>\n",
       "      <td>83.333</td>\n",
       "      <td>6.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>2023-09-25/2023-10-01</td>\n",
       "      <td>45.545</td>\n",
       "      <td>303.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>2023-10-02/2023-10-08</td>\n",
       "      <td>54.208</td>\n",
       "      <td>701.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>2023-10-09/2023-10-15</td>\n",
       "      <td>58.883</td>\n",
       "      <td>591.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>2023-10-16/2023-10-22</td>\n",
       "      <td>54.407</td>\n",
       "      <td>329.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>2023-10-23/2023-10-29</td>\n",
       "      <td>51.064</td>\n",
       "      <td>517.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>2023-10-30/2023-11-05</td>\n",
       "      <td>60.265</td>\n",
       "      <td>302.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>2023-11-13/2023-11-19</td>\n",
       "      <td>20.000</td>\n",
       "      <td>10.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>2023-11-20/2023-11-26</td>\n",
       "      <td>50.000</td>\n",
       "      <td>14.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>2023-11-27/2023-12-03</td>\n",
       "      <td>86.667</td>\n",
       "      <td>15.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>2023-12-04/2023-12-10</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>2023-12-18/2023-12-24</td>\n",
       "      <td>40.000</td>\n",
       "      <td>5.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>2024-03-11/2024-03-17</td>\n",
       "      <td>60.947</td>\n",
       "      <td>169.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>2024-03-18/2024-03-24</td>\n",
       "      <td>44.016</td>\n",
       "      <td>493.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>2024-03-25/2024-03-31</td>\n",
       "      <td>60.000</td>\n",
       "      <td>10.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>2024-04-01/2024-04-07</td>\n",
       "      <td>61.039</td>\n",
       "      <td>77.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>2024-04-08/2024-04-14</td>\n",
       "      <td>50.000</td>\n",
       "      <td>2.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "win request_month_year_week  win_perc  total_request\n",
       "55    2023-09-18/2023-09-24    83.333          6.000\n",
       "56    2023-09-25/2023-10-01    45.545        303.000\n",
       "57    2023-10-02/2023-10-08    54.208        701.000\n",
       "58    2023-10-09/2023-10-15    58.883        591.000\n",
       "59    2023-10-16/2023-10-22    54.407        329.000\n",
       "60    2023-10-23/2023-10-29    51.064        517.000\n",
       "61    2023-10-30/2023-11-05    60.265        302.000\n",
       "62    2023-11-13/2023-11-19    20.000         10.000\n",
       "63    2023-11-20/2023-11-26    50.000         14.000\n",
       "64    2023-11-27/2023-12-03    86.667         15.000\n",
       "65    2023-12-04/2023-12-10     0.000          1.000\n",
       "66    2023-12-18/2023-12-24    40.000          5.000\n",
       "67    2024-03-11/2024-03-17    60.947        169.000\n",
       "68    2024-03-18/2024-03-24    44.016        493.000\n",
       "69    2024-03-25/2024-03-31    60.000         10.000\n",
       "70    2024-04-01/2024-04-07    61.039         77.000\n",
       "71    2024-04-08/2024-04-14    50.000          2.000"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# select only prediction-offline-sme and plot request_month_year_week vs win_perc\n",
    "prediction_offline_sme = wins[wins['tool'] == 'prediction-offline-sme']\n",
    "prediction_offline_sme = prediction_offline_sme[['request_month_year_week', 'win_perc', 'total_request']]\n",
    "prediction_offline_sme = prediction_offline_sme.sort_values(by='request_month_year_week')\n",
    "\n",
    "prediction_offline_sme"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>win</th>\n",
       "      <th>request_month_year_week</th>\n",
       "      <th>win_perc</th>\n",
       "      <th>total_request</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>2023-09-18/2023-09-24</td>\n",
       "      <td>63.077</td>\n",
       "      <td>65.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>2023-09-25/2023-10-01</td>\n",
       "      <td>47.988</td>\n",
       "      <td>323.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>2023-10-02/2023-10-08</td>\n",
       "      <td>55.502</td>\n",
       "      <td>836.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>2023-10-09/2023-10-15</td>\n",
       "      <td>60.369</td>\n",
       "      <td>651.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>2023-10-16/2023-10-22</td>\n",
       "      <td>53.117</td>\n",
       "      <td>401.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>2023-10-23/2023-10-29</td>\n",
       "      <td>55.899</td>\n",
       "      <td>356.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>2023-10-30/2023-11-05</td>\n",
       "      <td>53.785</td>\n",
       "      <td>251.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>2023-11-06/2023-11-12</td>\n",
       "      <td>54.511</td>\n",
       "      <td>1563.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>2023-11-13/2023-11-19</td>\n",
       "      <td>52.120</td>\n",
       "      <td>1863.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>2023-11-20/2023-11-26</td>\n",
       "      <td>55.873</td>\n",
       "      <td>1643.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>2023-11-27/2023-12-03</td>\n",
       "      <td>52.308</td>\n",
       "      <td>2231.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>2023-12-04/2023-12-10</td>\n",
       "      <td>54.359</td>\n",
       "      <td>2627.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>2023-12-11/2023-12-17</td>\n",
       "      <td>55.039</td>\n",
       "      <td>3225.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>2023-12-18/2023-12-24</td>\n",
       "      <td>53.571</td>\n",
       "      <td>2800.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>2023-12-25/2023-12-31</td>\n",
       "      <td>47.342</td>\n",
       "      <td>2558.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>2024-01-01/2024-01-07</td>\n",
       "      <td>45.344</td>\n",
       "      <td>3619.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>2024-01-08/2024-01-14</td>\n",
       "      <td>47.405</td>\n",
       "      <td>1734.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>2024-01-15/2024-01-21</td>\n",
       "      <td>44.667</td>\n",
       "      <td>3694.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>2024-01-22/2024-01-28</td>\n",
       "      <td>49.464</td>\n",
       "      <td>3734.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>2024-01-29/2024-02-04</td>\n",
       "      <td>44.658</td>\n",
       "      <td>3847.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>2024-02-05/2024-02-11</td>\n",
       "      <td>50.553</td>\n",
       "      <td>4071.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>2024-02-12/2024-02-18</td>\n",
       "      <td>48.598</td>\n",
       "      <td>3638.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>2024-02-19/2024-02-25</td>\n",
       "      <td>50.032</td>\n",
       "      <td>3100.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>2024-02-26/2024-03-03</td>\n",
       "      <td>51.717</td>\n",
       "      <td>4368.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>2024-03-04/2024-03-10</td>\n",
       "      <td>54.806</td>\n",
       "      <td>3454.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>2024-03-11/2024-03-17</td>\n",
       "      <td>55.848</td>\n",
       "      <td>3044.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>2024-03-18/2024-03-24</td>\n",
       "      <td>48.639</td>\n",
       "      <td>2535.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>2024-03-25/2024-03-31</td>\n",
       "      <td>41.345</td>\n",
       "      <td>1398.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>2024-04-01/2024-04-07</td>\n",
       "      <td>59.435</td>\n",
       "      <td>1097.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>2024-04-08/2024-04-14</td>\n",
       "      <td>68.281</td>\n",
       "      <td>413.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "win request_month_year_week  win_perc  total_request\n",
       "99    2023-09-18/2023-09-24    63.077         65.000\n",
       "100   2023-09-25/2023-10-01    47.988        323.000\n",
       "101   2023-10-02/2023-10-08    55.502        836.000\n",
       "102   2023-10-09/2023-10-15    60.369        651.000\n",
       "103   2023-10-16/2023-10-22    53.117        401.000\n",
       "104   2023-10-23/2023-10-29    55.899        356.000\n",
       "105   2023-10-30/2023-11-05    53.785        251.000\n",
       "106   2023-11-06/2023-11-12    54.511       1563.000\n",
       "107   2023-11-13/2023-11-19    52.120       1863.000\n",
       "108   2023-11-20/2023-11-26    55.873       1643.000\n",
       "109   2023-11-27/2023-12-03    52.308       2231.000\n",
       "110   2023-12-04/2023-12-10    54.359       2627.000\n",
       "111   2023-12-11/2023-12-17    55.039       3225.000\n",
       "112   2023-12-18/2023-12-24    53.571       2800.000\n",
       "113   2023-12-25/2023-12-31    47.342       2558.000\n",
       "114   2024-01-01/2024-01-07    45.344       3619.000\n",
       "115   2024-01-08/2024-01-14    47.405       1734.000\n",
       "116   2024-01-15/2024-01-21    44.667       3694.000\n",
       "117   2024-01-22/2024-01-28    49.464       3734.000\n",
       "118   2024-01-29/2024-02-04    44.658       3847.000\n",
       "119   2024-02-05/2024-02-11    50.553       4071.000\n",
       "120   2024-02-12/2024-02-18    48.598       3638.000\n",
       "121   2024-02-19/2024-02-25    50.032       3100.000\n",
       "122   2024-02-26/2024-03-03    51.717       4368.000\n",
       "123   2024-03-04/2024-03-10    54.806       3454.000\n",
       "124   2024-03-11/2024-03-17    55.848       3044.000\n",
       "125   2024-03-18/2024-03-24    48.639       2535.000\n",
       "126   2024-03-25/2024-03-31    41.345       1398.000\n",
       "127   2024-04-01/2024-04-07    59.435       1097.000\n",
       "128   2024-04-08/2024-04-14    68.281        413.000"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# select only prediction-online-sme and plot request_month_year_week vs win_perc\n",
    "prediction_online_sme = wins[wins['tool'] == 'prediction-online-sme']\n",
    "prediction_online_sme = prediction_online_sme[['request_month_year_week', 'win_perc', 'total_request']]\n",
    "prediction_online_sme = prediction_online_sme.sort_values(by='request_month_year_week')\n",
    "\n",
    "prediction_online_sme.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>win</th>\n",
       "      <th>request_month_year_week</th>\n",
       "      <th>win_perc</th>\n",
       "      <th>total_request</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>2024-02-26/2024-03-03</td>\n",
       "      <td>32.384</td>\n",
       "      <td>281.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>2024-03-04/2024-03-10</td>\n",
       "      <td>35.172</td>\n",
       "      <td>4569.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>2024-03-11/2024-03-17</td>\n",
       "      <td>47.251</td>\n",
       "      <td>5602.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>2024-03-18/2024-03-24</td>\n",
       "      <td>45.834</td>\n",
       "      <td>4885.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>2024-03-25/2024-03-31</td>\n",
       "      <td>51.273</td>\n",
       "      <td>4006.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>2024-04-01/2024-04-07</td>\n",
       "      <td>57.021</td>\n",
       "      <td>1289.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>2024-04-08/2024-04-14</td>\n",
       "      <td>70.376</td>\n",
       "      <td>692.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "win request_month_year_week  win_perc  total_request\n",
       "129   2024-02-26/2024-03-03    32.384        281.000\n",
       "130   2024-03-04/2024-03-10    35.172       4569.000\n",
       "131   2024-03-11/2024-03-17    47.251       5602.000\n",
       "132   2024-03-18/2024-03-24    45.834       4885.000\n",
       "133   2024-03-25/2024-03-31    51.273       4006.000\n",
       "134   2024-04-01/2024-04-07    57.021       1289.000\n",
       "135   2024-04-08/2024-04-14    70.376        692.000"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# select only prediction-request-rag and plot request_month_year_week vs win_perc\n",
    "prediction_request_rag = wins[wins['tool'] == 'prediction-request-rag']\n",
    "prediction_request_rag = prediction_request_rag[['request_month_year_week', 'win_perc', 'total_request']]\n",
    "prediction_request_rag = prediction_request_rag.sort_values(by='request_month_year_week')\n",
    "\n",
    "prediction_request_rag.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>win</th>\n",
       "      <th>request_month_year_week</th>\n",
       "      <th>win_perc</th>\n",
       "      <th>total_request</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>2024-03-25/2024-03-31</td>\n",
       "      <td>56.757</td>\n",
       "      <td>740.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>2024-04-01/2024-04-07</td>\n",
       "      <td>58.025</td>\n",
       "      <td>1458.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>2024-04-08/2024-04-14</td>\n",
       "      <td>73.679</td>\n",
       "      <td>1003.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "win request_month_year_week  win_perc  total_request\n",
       "138   2024-03-25/2024-03-31    56.757        740.000\n",
       "139   2024-04-01/2024-04-07    58.025       1458.000\n",
       "140   2024-04-08/2024-04-14    73.679       1003.000"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prediction_request_reasoning = wins[wins['tool'] == 'prediction-request-reasoning']\n",
    "prediction_request_reasoning = prediction_request_reasoning[['request_month_year_week', 'win_perc', 'total_request']]\n",
    "prediction_request_reasoning = prediction_request_reasoning.sort_values(by='request_month_year_week')\n",
    "\n",
    "prediction_request_reasoning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>win</th>\n",
       "      <th>request_month_year_week</th>\n",
       "      <th>win_perc</th>\n",
       "      <th>total_request</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>2024-04-01/2024-04-07</td>\n",
       "      <td>68.387</td>\n",
       "      <td>155.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>2024-04-08/2024-04-14</td>\n",
       "      <td>78.514</td>\n",
       "      <td>619.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "win request_month_year_week  win_perc  total_request\n",
       "141   2024-04-01/2024-04-07    68.387        155.000\n",
       "142   2024-04-08/2024-04-14    78.514        619.000"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prediction_request_reasoning_claude = wins[wins['tool'] == 'prediction-request-reasoning-claude']\n",
    "prediction_request_reasoning_claude = prediction_request_reasoning_claude[['request_month_year_week', 'win_perc', 'total_request']]\n",
    "prediction_request_reasoning_claude = prediction_request_reasoning_claude.sort_values(by='request_month_year_week')\n",
    "\n",
    "prediction_request_reasoning_claude"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>win</th>\n",
       "      <th>request_month_year_week</th>\n",
       "      <th>win_perc</th>\n",
       "      <th>total_request</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>2024-04-01/2024-04-07</td>\n",
       "      <td>68.627</td>\n",
       "      <td>51.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>2024-04-08/2024-04-14</td>\n",
       "      <td>74.184</td>\n",
       "      <td>337.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "win request_month_year_week  win_perc  total_request\n",
       "136   2024-04-01/2024-04-07    68.627         51.000\n",
       "137   2024-04-08/2024-04-14    74.184        337.000"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prediction_request_rag_claude = wins[wins['tool'] == 'prediction-request-rag-claude']\n",
    "prediction_request_rag_claude = prediction_request_rag_claude[['request_month_year_week', 'win_perc', 'total_request']]\n",
    "prediction_request_rag_claude = prediction_request_rag_claude.sort_values(by='request_month_year_week')\n",
    "\n",
    "prediction_request_rag_claude"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>win</th>\n",
       "      <th>request_month_year_week</th>\n",
       "      <th>win_perc</th>\n",
       "      <th>total_request</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>2024-04-08/2024-04-14</td>\n",
       "      <td>72.822</td>\n",
       "      <td>574.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "win request_month_year_week  win_perc  total_request\n",
       "143   2024-04-08/2024-04-14    72.822        574.000"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prediction_url_cot_claude = wins[wins['tool'] == 'prediction-url-cot-claude']\n",
    "prediction_url_cot_claude = prediction_url_cot_claude[['request_month_year_week', 'win_perc', 'total_request']]\n",
    "prediction_url_cot_claude = prediction_url_cot_claude.sort_values(by='request_month_year_week')\n",
    "\n",
    "prediction_url_cot_claude.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. Profitability analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_trades['creation_timestamp'] = pd.to_datetime(all_trades['creation_timestamp'])\n",
    "all_trades = all_trades[all_trades['current_answer'].isin([0., 1., -1.])].reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of traders: 184\n",
      "Number of trades: 18,941\n"
     ]
    }
   ],
   "source": [
    "print(f\"Number of traders: {len(summary_traders):,}\")\n",
    "print(f\"Number of trades: {all_trades['trade_id'].nunique():,}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Number of trades')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot num trades over time\n",
    "plt.figure(figsize=(10,6))\n",
    "all_trades['creation_timestamp'].dt.date.value_counts().sort_index().plot(title='Number of trades over time')\n",
    "plt.xticks(rotation=45)\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('Number of trades')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Number of trades')"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot num trades over time\n",
    "plt.figure(figsize=(10,6))\n",
    "all_trades['creation_timestamp'].dt.date.value_counts().sort_index().plot(title='Number of trades over time')\n",
    "plt.xticks(rotation=45)\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('Number of trades')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2024-05-18 00:25:10+00:00 2024-07-14 01:09:10+00:00\n"
     ]
    }
   ],
   "source": [
    "print(all_trades['creation_timestamp'].min(), all_trades['creation_timestamp'].max())\n",
    "all_trades['month_year'] = all_trades['creation_timestamp'].dt.to_period('M')\n",
    "all_trades['month_year_week'] = all_trades['creation_timestamp'].dt.to_period('W')\n",
    "all_trades['winning_trade'] = all_trades['winning_trade'].astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['trader_address', 'trade_id', 'creation_timestamp', 'title',\n",
       "       'market_status', 'collateral_amount', 'outcome_index',\n",
       "       'trade_fee_amount', 'outcomes_tokens_traded', 'current_answer',\n",
       "       'is_invalid', 'winning_trade', 'earnings', 'redeemed',\n",
       "       'redeemed_amount', 'num_mech_calls', 'mech_fee_amount', 'net_earnings',\n",
       "       'roi', 'month_year', 'month_year_week'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_trades.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "month_year\n",
       "2023-07   0.385\n",
       "2023-08   0.473\n",
       "2023-09   0.442\n",
       "2023-10   0.497\n",
       "2023-11   0.488\n",
       "2023-12   0.498\n",
       "2024-01   0.470\n",
       "2024-02   0.489\n",
       "2024-03   0.499\n",
       "2024-04   0.513\n",
       "Freq: M, Name: winning_trade, dtype: float64"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_trades.groupby(['month_year'])['winning_trade'].sum() / all_trades.groupby(['month_year'])['winning_trade'].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "month_year\n",
       "2024-05   0.547\n",
       "2024-06   0.576\n",
       "2024-07   0.575\n",
       "Freq: M, Name: winning_trade, dtype: float64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_trades.groupby(['month_year'])['winning_trade'].sum() / all_trades.groupby(['month_year'])['winning_trade'].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Winning trade percentage over time'}, xlabel='month_year_week'>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "all_trades.groupby('month_year_week')['winning_trade'].mean().plot(title='Winning trade percentage over time', figsize=(10,6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Winning trade percentage over time'}, xlabel='month_year_week'>"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "all_trades.groupby('month_year_week')['winning_trade'].mean().plot(title='Winning trade percentage over time', figsize=(10,6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Mechanical calls over time'}, xlabel='month_year_week'>"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#only plot from september 2023\n",
    "all_trades[all_trades['creation_timestamp'] > '2023-09-01'].groupby('month_year_week')['num_mech_calls'].quantile([0.25, 0.5, 0.75]).unstack().plot(title='Mechanical calls over time', figsize=(10,6)) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Collateral amount quantiles over time'}, xlabel='month_year_week'>"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "all_trades.groupby('month_year_week')['collateral_amount'].quantile([0.25, 0.5, 0.75]).unstack().plot(title='Collateral amount quantiles over time', figsize=(10,6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Earnings quantiles over time'}, xlabel='month_year_week'>"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "all_trades.groupby('month_year_week')['earnings'].quantile([0.25, 0.5, 0.75]).unstack().plot(title='Earnings quantiles over time', figsize=(10,6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Net earnings quantiles over time'}, xlabel='month_year_week'>"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot new earnings from september 2023\n",
    "all_trades[all_trades['creation_timestamp'] > '2023-09-01'].groupby('month_year_week')['net_earnings'].quantile([0.25, 0.5, 0.75]).unstack().plot(title='Net earnings quantiles over time', figsize=(10,6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'ROI quantiles over time'}, xlabel='month_year_week'>"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# roi from september 2023\n",
    "all_trades[all_trades['creation_timestamp'] > '2023-09-01'].groupby('month_year_week')['roi'].quantile([0.25, 0.5, 0.75]).unstack().plot(title='ROI quantiles over time', figsize=(10,6))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "del all_trades\n",
    "gc.collect()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "del tools\n",
    "gc.collect()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.3"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}