After changing column type to string, hours, minutes and seconds are missing from the date-CodePudding

I am have a dataframe loaded from a file containing a time series and values

      datetime              value_a
0     2019-08-19 00:00:00   194.32000000
1     2019-08-20 00:00:00   202.24000000
2     2019-08-21 00:00:00   196.55000000
3     2019-08-22 00:00:00   187.45000000
4     2019-08-23 00:00:00   190.36000000

After I try to convert first column to string, the hours minutes and seconds vanish.

     datetime     value_a
0    2019-08-19   194.32000000
1    2019-08-20   202.24000000
2    2019-08-21   196.55000000
3    2019-08-22   187.45000000
4    2019-08-23   190.36000000

Code snipped

df['datetime'] = df['datetime'].astype(str)

I kinda need the format %Y-%m-%d %H:%M:%S, because we are using it later.

What is wrong?

NOTE: I initially though that the issue is during conversion from object to datetime, however thanks to user @SomeDude, I have discovered that I am loosing h/m/s during to string conversion.

CodePudding user response：

It seems like the error can be fixed by using different type conversion method with explicit format definition.

df['datetime'] = df['datetime'].dt.strftime("%Y-%m-%d %H:%M:%S")

This works.

CodePudding user response：

You're saying "I don't like the default format".

Ok. So be explicit, include HMS in it when you re-format.

>>> df = pd.DataFrame([dict(datetime='2019-08-19 00:00:00', value_a=194.32)])
>>> df['datetime'] = pd.to_datetime(df.datetime)
>>> 
>>> df['datetime'] = df.datetime.dt.strftime("%Y-%m-%d %H:%M:%S")
>>> df
              datetime  value_a
0  2019-08-19 00:00:00   194.32