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| import pandas as pd | |
| import gradio as gr | |
| import matplotlib.pyplot as plt | |
| import seaborn as sns | |
| from seaborn import FacetGrid | |
| import plotly.express as px | |
| import plotly.graph_objs as go | |
| HEIGHT = 600 | |
| WIDTH = 1000 | |
| def plot_daily_invalid_trades_plotly(invalid_trades: pd.DataFrame): | |
| fig = px.histogram(invalid_trades, x="creation_date") | |
| return gr.Plot(value=fig) | |
| def plot_daily_dist_invalid_trades(invalid_trades: pd.DataFrame): | |
| """Function to paint the distribution of daily invalid trades, no matter which market""" | |
| sns.set_theme(palette="viridis") | |
| plt.figure(figsize=(25, 10)) | |
| plot2 = sns.histplot(data=invalid_trades, x="creation_date", kde=True) | |
| plt.xlabel("Creation date") | |
| plt.ylabel("Daily number of invalid trades") | |
| plt.xticks(rotation=45, ha="right") | |
| daily_trades_fig = plot2.get_figure() | |
| return gr.Plot(value=daily_trades_fig) | |
| 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() | |
| ) | |
| daily_invalid_markets["creation_date"] = daily_invalid_markets[ | |
| "creation_date" | |
| ].astype(str) | |
| daily_invalid_markets.columns = daily_invalid_markets.columns.astype(str) | |
| return gr.LinePlot( | |
| value=daily_invalid_markets, | |
| x="creation_date", | |
| y="nr_markets", | |
| y_title="nr_markets", | |
| interactive=True, | |
| show_actions_button=True, | |
| tooltip=["creation_date", "nr_markets", "trades_count"], | |
| height=HEIGHT, | |
| width=WIDTH, | |
| ) | |
| def plotly_daily_nr_invalid_markets(invalid_trades: pd.DataFrame) -> gr.Plot: | |
| daily_invalid_markets = ( | |
| invalid_trades.groupby("creation_date") | |
| .agg(trades_count=("title", "count"), nr_markets=("title", "nunique")) | |
| .reset_index() | |
| ) | |
| # Create the Plotly figure | |
| fig = go.Figure() | |
| # Add the line trace | |
| fig.add_trace( | |
| go.Scatter( | |
| x=daily_invalid_markets["creation_date"], | |
| y=daily_invalid_markets["nr_markets"], | |
| mode="lines+markers", | |
| name="Number of Markets", | |
| hovertemplate="<b>Date:</b> %{x}<br>" | |
| + "<b>Number of Markets:</b> %{y}<br>" | |
| + "<b>Trades Count:</b> %{text}<br>", | |
| text=daily_invalid_markets["trades_count"], # Used in the tooltip | |
| ) | |
| ) | |
| # Customize the layout | |
| fig.update_layout( | |
| title="Daily Invalid Markets", | |
| xaxis_title="Market Creation Date", | |
| yaxis_title="Number of Markets", | |
| xaxis=dict( | |
| tickangle=-45, # Rotate x-axis labels by -45 degrees | |
| tickfont=dict(size=10), # Adjust font size if needed | |
| ), | |
| width=1000, # Adjusted for better fit on laptop screens | |
| height=600, # Adjusted for better fit on laptop screens | |
| hovermode="closest", # Improve tooltip behavior | |
| # template="plotly_white", # Optional: set a cleaner background | |
| ) | |
| return gr.Plot( | |
| value=fig, | |
| ) | |
| 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: pd.DataFrame = ( | |
| invalid_trades.title.value_counts().reset_index() | |
| ) | |
| print(top_invalid_markets.head(5)) | |
| top_invalid_markets = top_invalid_markets.head(5) | |
| top_invalid_markets.rename(columns={"count": "nr_invalid_trades"}, inplace=True) | |
| return gr.DataFrame(top_invalid_markets) | |