So konvertieren Sie eine Spalte in DateTime in Pandas
df['col'] = pd.to_datetime(df['col'])
Joyous Jay
df['col'] = pd.to_datetime(df['col'])df['Dates'] = pd.to_datetime(df['Dates'], format='%y%m%d')
df['Date'] = df['Date'].astype('datetime64[ns]')
dtype = pd.SparseDtype(np.dtype('datetime64[ns]'))
series = pd.Series(df.date, dtype=dtype)
df['date']=np.array(series)# convert the 'Date' column to datetime format
df['Date']= pd.to_datetime(df['Date'])
# Check the format of 'Date' column
df.info()# convert the 'Date' column to datetime format
df['Date']= pd.to_datetime(df['Date'])
# Check the format of 'Date' column
df.info()#Converting column to datetime dtype while loading file.
#Create a date parser function
d_parser = lambda x: pd.to_datetime(x)
df = pd.read_csv(file_name.csv, parse_dates=['date_column'], date_parser=d_parser)
#If date is not in parseable format, use
pd.to_datetime.strptime(x, format)
#Eg. format for '2017-03-13 04-PM' is '%Y-%M-%D %I-%p'
#Datetime Formatting Codes - http://bit.ly/python-dt-fmtdf['col'] = pd.to_datetime(df['col'])