数据框的日期字段中的空值，如何跳过以将其格式化为日期

Question

I have a DataFrame which have date fields, some of which are containing None values.

I am changing all the dates which are in milliseconds to ddmmyyyy using below but facing issue when the value is None

 dataframe['dt'] =dataframe['dt']/1000.0
        dataframe['dt']=datetime.datetime.fromtimestamp(dataframe['dt']).strftime('%d/%m/%Y')

Tried to disregard the None Values as below, but it is not executing the condition and going directly to else

 dataframe['dt']=np.where(dataframe['dt']==pd.np.nan, pd.np.nan,dataframe['dt']/1000)
        dataframe['dt']=np.where(dataframe['dt']==pd.np.nan, pd.np.nan, datetime.datetime.fromtimestamp(dataframe['dt']).strftime('%d/%m/%Y'))

It is becoming tiring now

Answer 1

您是否尝试过：

pd.to_datetime(dataframe['dt'], unit='ms', format='%d%m%Y', errors='coerce')

Answer 2

You can use the inbuilt method in pandas pd.to_datetime to covert value as DateTime objects. once you convert to Datetime you can change the format more flexibly. If you want to convert the column 'date' to Datetime object, you can do it as below df['date']= pd.to_datetime(df['date'],format='%d/%m/%y', errors='coerce')

errors='coerce will make non convertible items as NaT

Answer 3

You can try apply :

import datetime
import numpy as np
df=pd.DataFrame({'dt':[1564025326921, 1564025327921, None, 1564025328921]})
df['dt'] =df['dt']/1000.0
df['dt']= df['dt'].apply(lambda t: None if np.isnan(t) else datetime.datetime.fromtimestamp(t).strftime('%d/%m/%Y'))
df.head(10)

This will output:

    dt
0   24/07/2019
1   24/07/2019
2   None
3   24/07/2019