import pandas as pd import gradio as gr import matplotlib.pyplot as plt import seaborn as sns from seaborn import FacetGrid def plot_daily_dist_invalid_trades(invalid_trades: pd.DataFrame): """Function to paint the distribution of daily invalid trades, no matter which market""" plot2 = sns.histplot(data=invalid_trades, x="creation_date", kde=True) plt.xticks(rotation=45, ha="right") plt.xlabel("Creation date") plt.ylabel("Daily number of invalid trades") plt.title("Distribution of daily invalid trades over time") return gr.Plot(value=plot2.get_figure()) def plot_daily_nr_invalid_markets(invalid_trades: pd.DataFrame): """Function to paint the number of invalid markets over time""" daily_invalid_markets = ( invalid_trades.groupby("creation_date") .agg(trades_count=("title", "count"), nr_markets=("title", "nunique")) .reset_index() ) sns.set_theme(palette="viridis") plot = sns.lineplot(data=daily_invalid_markets, x="creation_date", y="nr_markets") plt.xticks(rotation=45, ha="right") plt.xlabel("Creation date") plt.ylabel("Daily number of invalid markets") plt.title("Evolution of daily invalid markets over time") return gr.Plot(value=plot.get_figure()) def plot_ratio_invalid_trades_per_market(invalid_trades: pd.DataFrame): """Function to paint the number of invalid trades that the same market accummulates""" cat = invalid_trades["title"] codes, uniques = pd.factorize(cat) # add the IDs as a new column to the original dataframe invalid_trades["title_id"] = codes plot: FacetGrid = sns.displot(invalid_trades, x="title_id") plt.xlabel("market id") plt.ylabel("Total number of invalid trades by market") plt.title("Distribution of invalid trades per market") return gr.Plot(value=plot.figure) def plot_top_invalid_markets(invalid_trades: pd.DataFrame): """Function to paint the top markets with the highest number of invalid trades""" top_invalid_markets = invalid_trades.title.value_counts().reset_index() top_invalid_markets.rename(columns={"count": "nr_invalid_trades"}, inplace=True) plt.figure(figsize=(40, 15)) plot = sns.barplot( top_invalid_markets.head(), x="nr_invalid_trades", y="title", hue="title", dodge=False, ) return gr.Plot(value=plot.get_figure())