python-2.7 - 在python中按时间分组和绘制数据

Question

我有一个 csv 文件，我正在尝试绘制每月某些值的平均值。我的 csv 文件的结构如下所示，所以我认为我应该每天对我的数据进行分组，然后是每月分组以计算平均值。

timestamp,heure,lat,lon,impact,type
2007-01-01 00:00:00,13:58:43,33.837,-9.205,10.3,1
2007-01-02 00:00:00,00:07:28,34.5293,-10.2384,17.7,1
2007-01-02 00:00:00,23:01:03,35.0617,-1.435,-17.1,2
2007-01-03 00:00:00,01:14:29,36.5685,0.9043,36.8,1
2007-01-03 00:00:00,05:03:51,34.1919,-12.5061,-48.9,1

我正在使用此代码:

import pandas as pd
import seaborn as sns
import numpy as np
import matplotlib.pyplot as plt

df= pd.read_csv("ave.txt", sep=',', names =["timestamp","heure","lat","lon","impact","type"])
daily = df.set_index('timestamp').groupby(pd.TimeGrouper(key='timestamp', freq='D', axis=1), axis=1)['impact'].count()
monthly = daily.groupby(pd.TimeGrouper(freq='M')).mean()
ax = monthly.plot(kind='bar')
plt.show()

但是，我不断收到这样的错误:

KeyError: 'The grouper name timestamp is not found'

有任何想法吗 ？？

Answer 1

您收到此错误是因为您设置了 timestamp列到 index .尝试删除 key='timestamp'来自 TimeGrouper()或 set_index方法，它应该按您的预期分组:

daily = df.set_index('timestamp').groupby(pd.TimeGrouper(freq='D', axis=1), axis=1)['impact'].count()

或者

daily = df.groupby(pd.TimeGrouper(key='timestamp', freq='D', axis=1), axis=1)['impact'].count()