Python Pandas : how to create a column which is a fixed date + the # days in another column

Question

我需要向数据框中添加一列，以便第 0 行是 2019 年 2 月 15 日。第 1 行是第 16 行，依此类推。我尝试过使用索引:

import numpy as np
import pandas as pd
df=pd.DataFrame()
df['a']=np.arange(10,20)
df['date from index']=df.apply( lambda x: pd.to_datetime('15-2-2019') + pd.DateOffset(days=x.index), axis=1 )

但我得到:

TypeError: ('must be str, not int', 'occurred at index 0')

我承认我不明白。我尝试创建一个显式列来代替索引:

df=pd.DataFrame()
df['a']=np.arange(10,20)
df['counter']=np.arange(0,df.shape[0])
df['date from counter']=df.apply( lambda x: pd.to_datetime('15-2-2019') + pd.DateOffset(days=x['counter']), axis=1 )

但这给了我:

TypeError: ('unsupported type for timedelta days component: numpy.int32', 'occurred at index 0')

我做错了什么？

Answer 1

使用to_timedelta用于将值转换为日时间增量或使用参数origin，指定开始日期，参数unit位于to_datetime :

df['date from index']= pd.to_datetime('15-2-2019') + pd.to_timedelta(df.index, 'd')
df['date from counter']= pd.to_datetime('15-2-2019') + pd.to_timedelta(df['counter'], 'd')

df['date from index1']= pd.to_datetime(df.index, origin='15-02-2019', unit='d')
df['date from counter1']= pd.to_datetime(df['counter'], origin='15-02-2019', unit='d')
print(df.head())
    a  counter date from index date from counter date from index1  \
0  10        0      2019-02-15        2019-02-15       2019-02-15   
1  11        1      2019-02-16        2019-02-16       2019-02-16   
2  12        2      2019-02-17        2019-02-17       2019-02-17   
3  13        3      2019-02-18        2019-02-18       2019-02-18   
4  14        4      2019-02-19        2019-02-19       2019-02-19   

  date from counter1  
0         2019-02-15  
1         2019-02-16  
2         2019-02-17  
3         2019-02-18  
4         2019-02-19