use only year for datetime index - pandas dataframe

Question

I've properly converted my year column into a datetime index, however the month and date are inaccurate and unneeded seeing my dataset only includes year. I've used the format parameter to set year only, however it's still showing as "%Y-%M-%D" format.

Original data:

    index   song              year  artist          genre
0   0       ego-remix         2009  beyonce knowles Pop
1   1       shes-tell-me      2009  save            Rock
2   2       hello             2009  yta             Pop 
3   3       the rock          2009  term            R&B 
4   4       black-culture     2009  hughey          Country

conducted a few more scrubbing techniques with the above code.

Then here are example rows from my dataframe code:

clean_df.index = pd.to_datetime(clean_df['year'], format='%Y')
clean_df = clean_df.drop(['index', 'year'], 1)
clean_df.sort_index(inplace=True)
clean_df.head()


year        song      artist    genre   

1970-01-01  hey now   caravan   Rock    
1970-01-01  show me   abc       Rock    
1970-01-01  hey now   xyz       Pop 
1970-01-01  tell me   foxy      R&B 
1970-01-01  move up   curtis    R&B

Is there any other method to be used to set index as annual only?

Answer 1

You were close

clean_df.index = pd.to_datetime(clean_df['year'], format='%Y-%m-%d').year

It's hard to provide the actual correct format needed because I don't have your original data, but you just need to transform to date object and then call the year parameter

Answer 2

I had a similar issue. Solved it this way:

    df['Year'] = df.Year.astype(np.datetime64)
    df['Year'] = df.Year.dt.year
    df.set_index('Year')

Output should only show the year with 4 digits.