Python 熊猫:更改数据帧日期索引格式

Python 熊猫:更改数据帧日期索引格式,python,pandas,dataframe,Python,Pandas,Dataframe,要将数据帧的日期索引从默认样式更改为“%m/%d/%Y”格式 In: df Out: Date Close 2006-01-24 48.812471 2006-01-25 47.448712 2006-01-26 53.341202 2006-01-27 58.728122 2006-01-30 59.481986 2006-01-31 55.691974 指数 Out: DatetimeIndex(['2006-01-04', '2006-01-

要将数据帧的日期索引从默认样式更改为“%m/%d/%Y”格式

In: df
Out: 

  Date     Close     

2006-01-24  48.812471
2006-01-25  47.448712
2006-01-26  53.341202
2006-01-27  58.728122
2006-01-30  59.481986
2006-01-31  55.691974
指数

 Out: 
 DatetimeIndex(['2006-01-04', '2006-01-05', '2006-01-06', '2006-01-09',
           '2006-01-10', '2006-01-11', '2006-01-12', '2006-01-13',
           '2006-01-17', '2006-01-18',
           ...
           '2018-02-21', '2018-02-22', '2018-02-23', '2018-02-26',
           '2018-02-27', '2018-02-28', '2018-03-01', '2018-03-02',
           '2018-03-05', '2018-03-06'],
          dtype='datetime64[ns]', name=u'Date', length=3063, freq=None)
进入:

我以前试过这个方法

 df1.index = pd.to_datetime(df.index, format = '%m/%d/%Y')
 df1.index = df.dt.strftime('%Y-%m-%d')

 AttributeError: 'DataFrame' object has no attribute 'dt'
使用-而不是
dt
need
index

df1.index = pd.to_datetime(df1.index, format = '%m/%d/%Y').strftime('%Y-%m-%d')
相同之处:

df1.index = pd.to_datetime(df1.index, format = '%m/%d/%Y')
df1.index = df1.index.strftime('%Y-%m-%d')
如果需要,请编辑将
DatetimeIndex
转换为其他字符串格式:

print (df1.index)
DatetimeIndex(['2006-01-24', '2006-01-25', '2006-01-26', '2006-01-27',
               '2006-01-30', '2006-01-31'],
              dtype='datetime64[ns]', name='Date', freq=None)


df1.index = df1.index.strftime('%m/%d/%Y')
print (df1)
                Close
01/24/2006  48.812471
01/25/2006  47.448712
01/26/2006  53.341202
01/27/2006  58.728122
01/30/2006  59.481986
01/31/2006  55.691974

为什么索引名“Date”不见了?@Maxi-Use
df=df.rename\u axis(None)
df.index.name=None
@jezreal好的,我试过了,但是在我将更改的版本写入csv后,日期格式恢复为默认格式
df1.index.name='Date'df1.to_csv(路径)哎呀,我不明白。需要
df1.reset_index().到_csv(path+'RSI1.csv',index=False)
print (df1.index)
DatetimeIndex(['2006-01-24', '2006-01-25', '2006-01-26', '2006-01-27',
               '2006-01-30', '2006-01-31'],
              dtype='datetime64[ns]', name='Date', freq=None)


df1.index = df1.index.strftime('%m/%d/%Y')
print (df1)
                Close
01/24/2006  48.812471
01/25/2006  47.448712
01/26/2006  53.341202
01/27/2006  58.728122
01/30/2006  59.481986
01/31/2006  55.691974