Syntax to use df.apply() with datetime.strptime [duplicate]

问题

Consider the following table 'df':

    date        sales  
0   2021-04-10  483  
1   2022-02-03  226  
2   2021-09-23  374  
3   2021-10-17  186  
4   2021-07-17   35

I would like to convert the column date that is currently a string to a date by using apply() and datetime.strptime().

I tried the following:

format_date = "%Y-%m-%d"
df["date_new"] = df.loc[:,"date"].apply(datetime.strptime,df.loc[:,"date"],format_date)

I have the following error.

The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

I tried with different syntaxes (with args and **kwds arguments of apply() but I am always getting an error) such as:

apply() takes exactly 2 arguments (3 given)

Can someone help me with the syntax ? Thank you.

回答1:

You should use pd.to_datetime():

df['date'] = pd.to_datetime(df['date'], format='%Y-%m-%d')

回答2:

You can do this:

df['date_new'] = df['date'].map(lambda date_string: datetime.strptime(date_string, format_string))

Since you are only operating on, and require data from a single column, you should use .map instead of .apply which will give you the entire row/column at once.

If you must use apply:

df['date_new'] = df.apply(lambda row: datetime.strptime(row['date'], format_string), axis=1)

The key here is axis=1, so you go row-wise

来源：https://stackoverflow.com/questions/52633719/syntax-to-use-df-apply-with-datetime-strptime

标签

python

pandas

datetime