why the function not taking the argument value in the assigned column?

Question

def change_date_column_type(df,change_column_name):
   
    
    df=df.assign(change_column_name=df[change_column_name].astype('datetime64'))
    
    # return the result
    return df

result = change_date_column_type(test_df,’release_date’)
print(result)


output:
  movie_title  release_date    genre MPAA_rating change_column_name
0     titanic  Dec 21, 1937    Drama           R         1937-12-21
1      frozen   Feb 9, 1940  Musical          PG         1940-02-09
2       rythm  Nov 13, 1940   Family           G         1940-11-13
3   godfather  Nov 12, 1946    Drama           R         1946-11-12
4         red  Feb 15, 1950  Musical       PG-13         1950-02-15

I want to change the release_Date column type to datetime64, but why the df.assign(change_column_name not taking the argument value and taking the literal value and created new column ? any help would be appreciated

expecting the release_date column to change type as datetime64 using a function call

Asked By: shiviz

||

Source

Answer 1

creating a new column is expected behavior –> see docs for usage of df.assign()

if you don’t want to create a new column then just use astype

def change_date_column_type(df,change_column_name):
    df[change_column_name] = df[change_column_name].astype('datetime64')
    return df

Answered By: will-wright-eng

why the function not taking the argument value in the assigned column?

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