cyberosa commited on
Commit
c5bbc45
Β·
1 Parent(s): efbada6

updating notebooks

Browse files
.DS_Store DELETED
Binary file (6.15 kB)
 
.gitignore CHANGED
@@ -3,6 +3,8 @@ __pycache__/
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  *.py[cod]
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  *$py.class
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  # C extensions
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  *.so
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@@ -157,4 +159,4 @@ cython_debug/
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  # be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
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  # and can be added to the global gitignore or merged into this file. For a more nuclear
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  # option (not recommended) you can uncomment the following to ignore the entire idea folder.
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- #.idea/
 
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  *.py[cod]
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  *$py.class
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+ .DS_Store
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+
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  # C extensions
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  *.so
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  # be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
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  # and can be added to the global gitignore or merged into this file. For a more nuclear
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  # option (not recommended) you can uncomment the following to ignore the entire idea folder.
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+ #.idea/
analysis.ipynb β†’ notebooks/analysis.ipynb RENAMED
File without changes
increase_zero_mech_calls.ipynb β†’ notebooks/increase_zero_mech_calls.ipynb RENAMED
File without changes
{nbs β†’ notebooks}/test.ipynb RENAMED
File without changes
{nbs β†’ notebooks}/weekly_analysis.ipynb RENAMED
@@ -52,7 +52,7 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": 6,
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  "metadata": {},
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  "outputs": [
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  {
@@ -60,31 +60,31 @@
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  "output_type": "stream",
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  "text": [
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  "<class 'pandas.core.frame.DataFrame'>\n",
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- "RangeIndex: 92662 entries, 0 to 92661\n",
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  "Data columns (total 19 columns):\n",
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  " # Column Non-Null Count Dtype \n",
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  "--- ------ -------------- ----- \n",
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- " 0 trader_address 92662 non-null object \n",
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- " 1 trade_id 92662 non-null object \n",
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- " 2 creation_timestamp 92662 non-null datetime64[ns, UTC]\n",
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- " 3 title 92662 non-null object \n",
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- " 4 market_status 92662 non-null object \n",
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- " 5 collateral_amount 92662 non-null float64 \n",
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- " 6 outcome_index 92662 non-null object \n",
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- " 7 trade_fee_amount 92662 non-null float64 \n",
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- " 8 outcomes_tokens_traded 92662 non-null float64 \n",
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- " 9 current_answer 92662 non-null int64 \n",
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- " 10 is_invalid 92662 non-null bool \n",
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- " 11 winning_trade 92662 non-null bool \n",
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- " 12 earnings 92662 non-null float64 \n",
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- " 13 redeemed 92662 non-null bool \n",
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- " 14 redeemed_amount 92662 non-null float64 \n",
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- " 15 num_mech_calls 92662 non-null int64 \n",
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- " 16 mech_fee_amount 92662 non-null float64 \n",
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- " 17 net_earnings 92662 non-null float64 \n",
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- " 18 roi 92662 non-null float64 \n",
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  "dtypes: bool(3), datetime64[ns, UTC](1), float64(8), int64(2), object(5)\n",
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- "memory usage: 11.6+ MB\n"
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  ]
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  }
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  ],
@@ -94,7 +94,7 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": 7,
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  "metadata": {},
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  "outputs": [
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  {
@@ -103,7 +103,7 @@
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  "Timestamp('2023-07-12 15:17:25+0000', tz='UTC')"
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  ]
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  },
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- "execution_count": 7,
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  "metadata": {},
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  "output_type": "execute_result"
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  }
@@ -112,6 +112,26 @@
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  "all_trades.creation_timestamp.min()"
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  ]
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  },
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  {
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  "cell_type": "code",
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  "execution_count": 4,
@@ -2363,7 +2383,7 @@
2363
  "claude_prediction_online = claude_prediction_online[['request_month_year_week', 'win_perc', 'total_request']]\n",
2364
  "claude_prediction_online = claude_prediction_online.sort_values(by='request_month_year_week')\n",
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  "\n",
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- "claude_prediction_online"
2367
  ]
2368
  },
2369
  {
@@ -2494,7 +2514,7 @@
2494
  "claude_prediction_offline = claude_prediction_offline[['request_month_year_week', 'win_perc', 'total_request']]\n",
2495
  "claude_prediction_offline = claude_prediction_offline.sort_values(by='request_month_year_week')\n",
2496
  "\n",
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- "claude_prediction_offline"
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  ]
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  },
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  {
@@ -2737,7 +2757,7 @@
2737
  "prediction_online = prediction_online[['request_month_year_week', 'win_perc', 'total_request']]\n",
2738
  "prediction_online = prediction_online.sort_values(by='request_month_year_week')\n",
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  "\n",
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- "prediction_online"
2741
  ]
2742
  },
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  {
@@ -3368,7 +3388,7 @@
3368
  "prediction_online_sme = prediction_online_sme[['request_month_year_week', 'win_perc', 'total_request']]\n",
3369
  "prediction_online_sme = prediction_online_sme.sort_values(by='request_month_year_week')\n",
3370
  "\n",
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- "prediction_online_sme"
3372
  ]
3373
  },
3374
  {
@@ -3471,7 +3491,7 @@
3471
  "prediction_request_rag = prediction_request_rag[['request_month_year_week', 'win_perc', 'total_request']]\n",
3472
  "prediction_request_rag = prediction_request_rag.sort_values(by='request_month_year_week')\n",
3473
  "\n",
3474
- "prediction_request_rag"
3475
  ]
3476
  },
3477
  {
@@ -3739,7 +3759,7 @@
3739
  "prediction_url_cot_claude = prediction_url_cot_claude[['request_month_year_week', 'win_perc', 'total_request']]\n",
3740
  "prediction_url_cot_claude = prediction_url_cot_claude.sort_values(by='request_month_year_week')\n",
3741
  "\n",
3742
- "prediction_url_cot_claude"
3743
  ]
3744
  },
3745
  {
 
52
  },
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  {
54
  "cell_type": "code",
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+ "execution_count": 4,
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  "metadata": {},
57
  "outputs": [
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  {
 
60
  "output_type": "stream",
61
  "text": [
62
  "<class 'pandas.core.frame.DataFrame'>\n",
63
+ "RangeIndex: 95550 entries, 0 to 95549\n",
64
  "Data columns (total 19 columns):\n",
65
  " # Column Non-Null Count Dtype \n",
66
  "--- ------ -------------- ----- \n",
67
+ " 0 trader_address 95550 non-null object \n",
68
+ " 1 trade_id 95550 non-null object \n",
69
+ " 2 creation_timestamp 95550 non-null datetime64[ns, UTC]\n",
70
+ " 3 title 95550 non-null object \n",
71
+ " 4 market_status 95550 non-null object \n",
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+ " 5 collateral_amount 95550 non-null float64 \n",
73
+ " 6 outcome_index 95550 non-null object \n",
74
+ " 7 trade_fee_amount 95550 non-null float64 \n",
75
+ " 8 outcomes_tokens_traded 95550 non-null float64 \n",
76
+ " 9 current_answer 95550 non-null int64 \n",
77
+ " 10 is_invalid 95550 non-null bool \n",
78
+ " 11 winning_trade 95550 non-null bool \n",
79
+ " 12 earnings 95550 non-null float64 \n",
80
+ " 13 redeemed 95550 non-null bool \n",
81
+ " 14 redeemed_amount 95550 non-null float64 \n",
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+ " 15 num_mech_calls 95550 non-null int64 \n",
83
+ " 16 mech_fee_amount 95550 non-null float64 \n",
84
+ " 17 net_earnings 95550 non-null float64 \n",
85
+ " 18 roi 95550 non-null float64 \n",
86
  "dtypes: bool(3), datetime64[ns, UTC](1), float64(8), int64(2), object(5)\n",
87
+ "memory usage: 11.9+ MB\n"
88
  ]
89
  }
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  ],
 
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  },
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  {
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  "cell_type": "code",
97
+ "execution_count": 5,
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  "metadata": {},
99
  "outputs": [
100
  {
 
103
  "Timestamp('2023-07-12 15:17:25+0000', tz='UTC')"
104
  ]
105
  },
106
+ "execution_count": 5,
107
  "metadata": {},
108
  "output_type": "execute_result"
109
  }
 
112
  "all_trades.creation_timestamp.min()"
113
  ]
114
  },
115
+ {
116
+ "cell_type": "code",
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+ "execution_count": 6,
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+ "metadata": {},
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+ "outputs": [
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+ {
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+ "data": {
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+ "text/plain": [
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+ "Timestamp('2024-05-27 02:13:05+0000', tz='UTC')"
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+ ]
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+ },
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+ "execution_count": 6,
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+ "metadata": {},
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+ "output_type": "execute_result"
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+ }
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+ ],
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+ "source": [
132
+ "all_trades.creation_timestamp.max()"
133
+ ]
134
+ },
135
  {
136
  "cell_type": "code",
137
  "execution_count": 4,
 
2383
  "claude_prediction_online = claude_prediction_online[['request_month_year_week', 'win_perc', 'total_request']]\n",
2384
  "claude_prediction_online = claude_prediction_online.sort_values(by='request_month_year_week')\n",
2385
  "\n",
2386
+ "claude_prediction_online.head()"
2387
  ]
2388
  },
2389
  {
 
2514
  "claude_prediction_offline = claude_prediction_offline[['request_month_year_week', 'win_perc', 'total_request']]\n",
2515
  "claude_prediction_offline = claude_prediction_offline.sort_values(by='request_month_year_week')\n",
2516
  "\n",
2517
+ "claude_prediction_offline.head()"
2518
  ]
2519
  },
2520
  {
 
2757
  "prediction_online = prediction_online[['request_month_year_week', 'win_perc', 'total_request']]\n",
2758
  "prediction_online = prediction_online.sort_values(by='request_month_year_week')\n",
2759
  "\n",
2760
+ "prediction_online.head()"
2761
  ]
2762
  },
2763
  {
 
3388
  "prediction_online_sme = prediction_online_sme[['request_month_year_week', 'win_perc', 'total_request']]\n",
3389
  "prediction_online_sme = prediction_online_sme.sort_values(by='request_month_year_week')\n",
3390
  "\n",
3391
+ "prediction_online_sme.head()"
3392
  ]
3393
  },
3394
  {
 
3491
  "prediction_request_rag = prediction_request_rag[['request_month_year_week', 'win_perc', 'total_request']]\n",
3492
  "prediction_request_rag = prediction_request_rag.sort_values(by='request_month_year_week')\n",
3493
  "\n",
3494
+ "prediction_request_rag.head()"
3495
  ]
3496
  },
3497
  {
 
3759
  "prediction_url_cot_claude = prediction_url_cot_claude[['request_month_year_week', 'win_perc', 'total_request']]\n",
3760
  "prediction_url_cot_claude = prediction_url_cot_claude.sort_values(by='request_month_year_week')\n",
3761
  "\n",
3762
+ "prediction_url_cot_claude.head()"
3763
  ]
3764
  },
3765
  {