Trying to merge 2 dataframes but get ValueError

These are my two dataframes saved in two variables:

> print(df.head())>          club_name  tr_jan  tr_dec  year    0  ADO Den Haag    1368    1422  2010    1  ADO Den Haag    1455    1477  2011    2  ADO Den Haag    1461    1443  2012    3  ADO Den Haag    1437    1383  2013    4  ADO Den Haag    1386    1422  2014> print(rankingdf.head())>           club_name  ranking  year    0    ADO Den Haag    12    2010    1    ADO Den Haag    13    2011    2    ADO Den Haag    11    2012    3    ADO Den Haag    14    2013    4    ADO Den Haag    17    2014

I'm trying to merge these two using this code:

new_df = df.merge(ranking_df, on=['club_name', 'year'], how='left')

The how='left' is added because I have less datapoints in my ranking_df than in my standard df.

The expected behaviour is as such:

> print(new_df.head()) >       club_name  tr_jan  tr_dec  year    ranking0  ADO Den Haag    1368    1422  2010    121  ADO Den Haag    1455    1477  2011    132  ADO Den Haag    1461    1443  2012    113  ADO Den Haag    1437    1383  2013    144  ADO Den Haag    1386    1422  2014    17

But I get this error:

ValueError: You are trying to merge on object and int64 columns. If you wish to proceed you should use pd.concat

But I do not wish to use concat since I want to merge the trees not just add them on.

Another behaviour that's weird in my mind is that my code works if I save the first df to .csv and then load that .csv into a dataframe.

The code for that:

df = pd.DataFrame(data_points, columns=['club_name', 'tr_jan', 'tr_dec', 'year'])df.to_csv('preliminary.csv')df = pd.read_csv('preliminary.csv', index_col=0)ranking_df = pd.DataFrame(rankings, columns=['club_name', 'ranking', 'year'])new_df = df.merge(ranking_df, on=['club_name', 'year'], how='left')

I think that it has to do with the index_col=0 parameter. But I have no idea to fix it without having to save it, it doesn't matter much but is kind of an annoyance that I have to do that.