time_analysis.py

import pandas as pd
from matplotlib import pyplot as plt
from datetime import datetime


def time_ana(msg_file='msg.csv', figsize=(12, 8)):
    print('时域处理')
    data = pd.read_csv(f'input_data/{msg_file}', usecols=['StrTime'],
                       parse_dates=['StrTime']).dropna()
    data['year-month'] = data['StrTime'].apply(lambda x: str(x.year)+'/'+str(x.month).zfill(2))
    data['hour'] = data['StrTime'].apply(lambda x: str(x.hour).zfill(2))
    # 计算时间跨度
    date0 = data.loc[0, 'StrTime'].date()
    date1 = data.loc[data.shape[0] - 1, 'StrTime'].date()
    n_date = (date1 - date0).days + 1
    print(f"第一天：{date0.strftime('%Y-%m-%d')}\n最后一天：{date1.strftime('%Y-%m-%d')}\n"
          f"共计{n_date}天")
    # 月度数据
    data_yearmonth = data.groupby(by='year-month')['year-month'].count()
    # 时均数据
    data_hour = data.groupby(by='hour')['hour'].count() / n_date
    data_hour0_index = set(str(each).zfill(2) for each in range(24)) - set(data_hour.index)
    data_hour0 = pd.Series([0 for _ in range(len(data_hour0_index))], data_hour0_index)
    data_hour = pd.concat((data_hour, data_hour0))
    data_hour.sort_index(inplace=True)
    x1 = list(range(len(data_yearmonth)))
    plt.close('all')
    plt.figure(1, figsize=figsize)
    plt.rc('font', family='SimSun', size=15)
    start, end = 0, 13 - date0.month
    for n_year in range(date1.year - date0.year + 1):
        plt.bar(x1[start:end], data_yearmonth.iloc[start:end])
        start = end
        end += 12
    months_ind = [each.split('/')[1] for each in data_yearmonth.index.to_list()]
    plt.xticks(x1, months_ind, rotation=60)
    plt.ylabel('消息条数')
    plt.savefig('figs/月度消息数量变化.png')
    plt.figure(2, figsize=figsize)
    x2 = list(range(24))
    plt.bar(x2, data_hour)
    plt.xticks(x2, data_hour.index)
    plt.xlabel('小时', fontsize=20)
    plt.ylabel('平均消息条数', fontsize=20)
    plt.savefig('figs/小时消息数量变化.png')
    print('=' * 20)


if __name__ == '__main__':
    time_ana()