stock-operation/user_events/monitor/GenerateReport.py

# -*- coding: utf-8 -*-
"""
@author: zsc
@time: 2024/11/18
@desc:  报告生成
"""
import time
import random
from collections import defaultdict
import matplotlib.pyplot as plt
import numpy as np

# 报告生成模块
class ReportGenerator:
    def __init__(self, data, anomalies, segments, process_stats, action_stats, product_stats, channel_stats):
        self.data = data
        self.anomalies = anomalies
        self.segments = segments
        self.process_stats = process_stats
        self.action_stats = action_stats
        self.product_stats = product_stats
        self.channel_stats = channel_stats

    def generate(self):
        # 生成用户行为报告，并展示成图表形式
        report = {
            'total_users': len(set([user_actions['user'] for user_actions in self.data])),
            'total_actions': sum(len(user_actions['actions']) for user_actions in self.data),
            'anomalies': self.anomalies,
            'user_segments': self.segments,
            'process_stats': self.process_stats,
            'action_stats': self.action_stats,
            'product_stats': self.product_stats,
            'channel_stats': self.channel_stats
        }

        # 打印报告摘要
        print("报告摘要:")
        print(f"总客户数: {report['total_users']}")
        print(f"总行为次数: {report['total_actions']}")
        print(f"异常客户: {report['anomalies']}")
        print(f"客户分群-高活跃用户: {report['user_segments']['高活跃用户']},")
        print(f"客户分群-低活跃用户: {report['user_segments']['低活跃用户']},")

        # 展示每个流程的行为次数漏斗图
        for process, actions in self.process_stats.items():
            self.plot_bar(actions, f"{process} 漏斗图")

        # 展示行为统计图表
        self.plot_stats(self.action_stats, "行为次数统计")

        # 展示产品统计图表
        self.plot_stats(self.product_stats, "分产品统计")

        # 展示渠道统计图表
        self.plot_stats(self.channel_stats, "分渠道统计")

        return report

    def plot_stats(self, stats, title):
        # 生成并展示统计图表
        labels, values = zip(*stats.items())
        plt.figure(figsize=(12, 6))  # 增加图表宽度
        plt.bar(labels, values)
        plt.title(title)
        plt.xticks(rotation=45, ha='right', fontsize=10)  # 旋转标签，右对齐，减小字体大小
        plt.tight_layout()  # 调整布局以避免标签被截断
        plt.show()

    def plot_bar(self, actions, title):
        # 生成并展示逆序的水平柱状图
        labels = list(actions.keys())
        values = list(actions.values())

        # 根据值对标签和值进行排序（从小到大，以实现逆序显示）
        sorted_indices = np.argsort(values)
        labels = np.array(labels)[sorted_indices].tolist()
        values = np.array(values)[sorted_indices].tolist()

        # 水平柱状图的矩形位置
        positions = np.arange(len(labels))

        fig, ax = plt.subplots(figsize=(10, 6))
        ax.barh(positions, values, color='teal')

        # 在矩形旁边添加具体数值
        for i, value in enumerate(values):
            ax.text(value, positions[i], str(value),
                    ha='right', va='center', color='black', fontsize=10)

        # 设置横坐标和纵坐标
        ax.set_yticks(positions)
        ax.set_yticklabels(labels)
        ax.set_xlabel('行为次数')
        ax.set_ylabel('')

        ax.set_title(title)

        plt.tight_layout()  # 调整布局
        plt.show()

# 设置matplotlib支持中文
plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签
plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号