pd.series更改列的值

我正嘗試從包含雨季值（VM）和日期（ISTANTE）的csv創建日曆熱圖。pd.series更改列的值

IDSTAZ,SENSORE,ISTANTE,VM 
56,300001896,201601010000,0.0 
56,300001896,201601020000,0.2 
56,300001896,201601030000,0.6 
56,300001896,201601040000,1.8

搜索網頁我寫下面的代碼上：

import pandas as pd 
import calmap 
import matplotlib.pyplot as plt 

df = pd.read_csv('D:\\GIS\\Dati\\Meteo_arpav\\stazione_forno.csv') 
df['DateTime'] = df['ISTANTE'].apply(lambda x: pd.to_datetime(str(x), format='%Y%m%d%H%M')) 
events = pd.Series((df['VM']), index=df['DateTime']) 
a=calmap.calendarplot(events) 
plt.show(a)

它的工作，但是當我創建VM的series所有值成爲NaN。印刷（事件）這就是結果：

DateTime 
2016-01-01 NaN 
2016-01-02 NaN 
2016-01-03 NaN 
2016-01-04 NaN 
2016-01-05 NaN 
2016-01-06 NaN 
2016-01-07 NaN 
2016-01-08 NaN 
2016-01-09 NaN

這樣日曆熱圖出來空。任何想法？

來源

2017-02-24 Daniele Piccolo

看來你需要set_index創建Series：

df['DateTime'] = pd.to_datetime(df['ISTANTE'], format='%Y%m%d%H%M') 
events = df.set_index('DateTime')['VM'] 
print (events) 
DateTime 
2016-01-01 0.0 
2016-01-02 0.2 
2016-01-03 0.6 
2016-01-04 1.8 
Name: VM, dtype: float64

之所以不工作：

events = pd.Series((df['VM']), index=df['DateTime'])

是數據對齊。列（Series）的索引要對齊DatetimeIndex，但值不匹配，所以結果爲NaN s。

來源

2017-02-24 15:28:13 jezrael

太好了。這是正確的答案！我以爲索引是用'events = pd.Series（（df ['VM']），index = df ['DateTime']）''創建的。非常感謝@jezrael –

pd.series更改列的值

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