熊猫索引日期时间格式未提供所需的输出Python3

Question

I have tried the following:

df.index= pd.to_datetime(df.index,format="%Y.%m.%d %HH:%MM:%SS")
df.tail()

The output was:

                    open    high    low close
Time                    
2018-07-24 16:25:00 1.16963 1.16976 1.16952 1.16952
2018-07-24 16:26:00 1.16952 1.16952 1.16938 1.16939
2018-07-24 16:27:00 1.16939 1.16940 1.16896 1.16908
2018-07-24 16:28:00 1.16909 1.16929 1.16908 1.16929
2018-07-24 16:29:00 1.16930 1.16932 1.16919 1.16925

I was expecting that the Time index of the dataframe shoud be in the format as shown in the following output:

                    open    high    low close
Time                    
2018.07.24 16:25:00 1.16963 1.16976 1.16952 1.16952
2018.07.24 16:26:00 1.16952 1.16952 1.16938 1.16939
2018.07.24 16:27:00 1.16939 1.16940 1.16896 1.16908
2018.07.24 16:28:00 1.16909 1.16929 1.16908 1.16929
2018.07.24 16:29:00 1.16930 1.16932 1.16919 1.16925

Kindly, help me get through this.

Answer 1

I think you need only one H , M and S :

df = pd.DataFrame({'Time': ['2018.07.24 16:25:00', '2018.07.24 16:26:00', '2018.07.24 16:27:00', '2018.07.24 16:28:00', '2018.07.24 16:29:00'], 'open': [1.16963, 1.1695200000000001, 1.16939, 1.16909, 1.1693], 'high': [1.1697600000000001, 1.1695200000000001, 1.1694, 1.16929, 1.1693200000000001], 'low': [1.1695200000000001, 1.1693799999999999, 1.16896, 1.16908, 1.16919], 'close': [1.1695200000000001, 1.16939, 1.16908, 1.16929, 1.16925]}).set_index('Time')

---

print (df)
                        open     high      low    close
Time                                                   
2018.07.24 16:25:00  1.16963  1.16976  1.16952  1.16952
2018.07.24 16:26:00  1.16952  1.16952  1.16938  1.16939
2018.07.24 16:27:00  1.16939  1.16940  1.16896  1.16908
2018.07.24 16:28:00  1.16909  1.16929  1.16908  1.16929
2018.07.24 16:29:00  1.16930  1.16932  1.16919  1.16925

print (df.index)
Index(['2018.07.24 16:25:00', '2018.07.24 16:26:00', '2018.07.24 16:27:00',
       '2018.07.24 16:28:00', '2018.07.24 16:29:00'],
      dtype='object', name='Time')

If want create Datetimeindex :

df.index= pd.to_datetime(df.index,format="%Y.%m.%d %H:%M:%S")

print (df)
                        open     high      low    close
Time                                                   
2018-07-24 16:25:00  1.16963  1.16976  1.16952  1.16952
2018-07-24 16:26:00  1.16952  1.16952  1.16938  1.16939
2018-07-24 16:27:00  1.16939  1.16940  1.16896  1.16908
2018-07-24 16:28:00  1.16909  1.16929  1.16908  1.16929
2018-07-24 16:29:00  1.16930  1.16932  1.16919  1.16925

print (df.index)
DatetimeIndex(['2018-07-24 16:25:00', '2018-07-24 16:26:00',
               '2018-07-24 16:27:00', '2018-07-24 16:28:00',
               '2018-07-24 16:29:00'],
              dtype='datetime64[ns]', name='Time', freq=None)

But if want custom format of index, use DatetimeIndex.strftime , but DatetimeIndex is lost, indices are strings:

df.index = df.index.strftime("%Y.%m.%d %H:%M:%S")

print (df)
                        open     high      low    close
2018.07.24 16:25:00  1.16963  1.16976  1.16952  1.16952
2018.07.24 16:26:00  1.16952  1.16952  1.16938  1.16939
2018.07.24 16:27:00  1.16939  1.16940  1.16896  1.16908
2018.07.24 16:28:00  1.16909  1.16929  1.16908  1.16929
2018.07.24 16:29:00  1.16930  1.16932  1.16919  1.16925

print (df.index)
Index(['2018.07.24 16:25:00', '2018.07.24 16:26:00', '2018.07.24 16:27:00',
       '2018.07.24 16:28:00', '2018.07.24 16:29:00'],
      dtype='object')