我必须分析在给定时间段内使用应用程序的用户的活动,句点是开始和结束时间戳。我尝试使用条形图,但我不知道如何在间隔中包含小时数。 例如:uid = 2的用户在[18,19,20,21]
使用该应用程序我的数据框如下:
uid sex start end
1 0 2000-01-28 16:47:00 2000-01-28 17:47:00
2 1 2000-01-28 18:07:00 2000-01-28 21:47:00
3 1 2000-01-28 18:47:00 2000-01-28 20:17:00
4 0 2000-01-28 08:00:00 2000-01-28 10:00:00
5 1 2000-01-28 02:05:00 2000-01-28 02:30:00
6 0 2000-01-28 15:10:00 2000-01-28 18:04:00
7 0 2000-01-28 01:50:00 2000-01-28 03:00:00
df['hour_s'] = pd.to_datetime(df['start']).apply(lambda x: x.hour)
df['hour_e'] = pd.to_datetime(df['end']).apply(lambda x: x.hour)
uid sex start end hour_s hour_e
1 0 2000-01-28 16:47:00 2000-01-28 17:47:00 16 17
2 1 2000-01-28 18:07:00 2000-01-28 21:47:00 18 21
3 1 2000-01-28 18:47:00 2000-01-28 20:17:00 18 20
4 0 2000-01-28 08:00:00 2000-01-28 10:00:00 08 10
5 1 2000-01-28 02:05:00 2000-01-28 02:30:00 02 02
6 0 2000-01-28 15:10:00 2000-01-28 18:04:00 15 18
7 0 2000-01-28 01:50:00 2000-01-28 03:00:00 01 03
我必须找到特定时间内的用户数量
答案 0 :(得分:1)
我不确定您是否正在寻找甘特图。如果是这样,@ViníciusAguiar的提示就在评论中。
从上一行开始
我必须找到特定时间内的用户数量
似乎您需要一个直方图,显示按小时数转动的用户数量(频率)。 如果是这种情况,你可以这样做:
#! /usr/bin/python3
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
# Read the data
df=pd.read_csv("data.csv")
# Get all hours per user (per observation)
def sum_hours(obs):
return(list(range(obs['hour_s'],obs['hour_e']+1,1)))
# Get all existing activity hours (No matter which user)
Hours2D=list(df.apply(sum_hours,axis=1))
# Get all existing hours
HoursFlat=[hour for sublist in Hours2D for hour in sublist]
plt.hist(HoursFlat,rwidth=0.5,range=(0,24))
plt.xticks(np.arange(0,24, 1.0))
plt.xlabel('Hour of day')
plt.ylabel('Users')
plt.show()
data.csv是您提供的样本:
uid, sex,start,end,hour_s,hour_e
1,0,2000-01-28 16:47:00,2000-01-28 17:47:00,16,17
2,1,2000-01-28 18:07:00,2000-01-28 21:47:00,18,21
3,1,2000-01-28 18:47:00,2000-01-28 20:17:00,18,20
4,0,2000-01-28 08:00:00,2000-01-28 10:00:00,08,10
5,1,2000-01-28 02:05:00,2000-01-28 02:30:00,02,02
6,0,2000-01-28 15:10:00,2000-01-28 18:04:00,15,18
7,0,2000-01-28 01:50:00,2000-01-28 03:00:00,01,03