51 lines
1.7 KiB
Python
51 lines
1.7 KiB
Python
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import pandas as pd
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import matplotlib.pyplot as plt
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import seaborn as sns
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from .basePlotAnalysis import BasePlotAnalysis
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from flask import current_app, url_for
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import matplotlib
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matplotlib.use('Agg')
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class PlotTopActiveUsers(BasePlotAnalysis):
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"""
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Class for analyzing the most active users and generating a bar chart.
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Attributes:
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name (str): The name of the analysis.
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description (str): A brief description of the analysis.
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plot_filename (str): The filename for the output plot.
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note (str): Additional notes for the analysis.
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"""
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name = "Top Active Users"
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description = "Displays the most active users based on their number of recorded actions."
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plot_filename = "bar_activity-per-user.png"
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note = ""
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def transform_data(self, df: pd.DataFrame) -> pd.DataFrame:
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"""
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Transform data for the bar plot.
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Parameters:
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df (pd.DataFrame): The input DataFrame containing user activity data.
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Returns:
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pd.DataFrame: The transformed DataFrame with active counts per user.
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"""
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df = df[df['was_active'] == True].groupby('name').size().reset_index(name='active_count')
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return df
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def plot_data(self, df: pd.DataFrame):
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"""
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Generate bar plot.
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Parameters:
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df (pd.DataFrame): The transformed DataFrame containing active counts per user.
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"""
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# create a barplot from active counts sorted by active count
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plt.figure(figsize=(10, 6))
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sns.barplot(x='active_count', y='name', data=df.sort_values('active_count', ascending=False))
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plt.xticks(rotation=90)
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plt.title('Minutes Active')
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plt.xlabel('Player')
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plt.ylabel('Active Count')
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