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Would like to change the Date index of the dataframe from the default style into '%m/%d/%Y' format.
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
df.index
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)
Into:
In: df1
Out:
Date Close
01/24/2006 48.812471
01/25/2006 47.448712
01/26/2006 53.341202
01/27/2006 58.728122
01/28/2006 59.481986
01/29/2006 55.691974
I tried this method before...
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'
486
Please notice that you can also specify the output date format other than the default one, by using the dt. strftime() method. For example, you can choose to display the output date as MM/DD/YYYY by specifying dt. strftime('%m/%d/%Y') .
To convert the index of a DataFrame to DatetimeIndex , use Pandas' to_datetime(~) method.
Use astype() to Change datetime to String Format You can use this if the date is already in the format you want it in string form. The below example returns the date as a string with format %Y/%m/%d . dtype of column ConvertedDate will be object ( string ). Yields below output.
Function usedstrftime() can change the date format in python.
Use DatetimeIndex.strftime - instead dt need index:
df1.index = pd.to_datetime(df1.index, format = '%m/%d/%Y').strftime('%Y-%m-%d')
What is same:
df1.index = pd.to_datetime(df1.index, format = '%m/%d/%Y')
df1.index = df1.index.strftime('%Y-%m-%d')
EDIT if need convert DatetimeIndex to another string format:
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
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