CODEWITHSUNDEEP
pandas
8-Bit Borges
8-Bit Borges

Reputation: 10033

Pandas - map values from one dataframe to another

I have this df:

 df_selected = pd.DataFrame({'player':['Keno', 'Filipe Luís', 'Thiago Galhardo'],
                             'selected': [2868.755, 776.147, 2696.853],
                             'ranking':[1,3,2]})

which prints:

            player        selected  ranking
0             Keno        2868.755        1
1      Filipe Luís         776.147        3
2  Thiago Galhardo        2696.853        2

and this one:

df_player = pd.DataFrame({'name':['Keno', 'Filipe Luís', 'Thiago Galhardo', 'SomePlayer'],
                    'team': ['Atlético-MG', 'Flamengo', 'Internacional', 'SomeTeam']})

which prints:

            player           team
0             Keno    Atlético-MG
1      Filipe Luís       Flamengo
2  Thiago Galhardo  Internacional
3           Fulano   TimeQualquer

Now I would like to check if a given player from df_player is in df_selected and, if so, fetch its ranking position and add it to a new column in df_player. If the player is not in df_selected, then add 0 value to its ranking. I've tried:

for ind, player in df_player.iterrows():
    for index, selected in df_selected.iterrows():

        if player.player == selected.player:
            df_player['ranking'].iloc[ind] = selected.ranking
        else:
            df_player['ranking'].iloc[ind] = 0

But it is not working, and there must be a simpler way of mapping those items.

Desired result for player_df:

            player         team    ranking
0             Keno    Atlético-MG        1
1      Filipe Luís       Flamengo        3
2  Thiago Galhardo  Internacional        2
3       SomePlayer       SomeTeam        0

What am I missing?

Upvotes: 1

Views: 239

Answers (2)

wwnde
wwnde

Reputation: 26676

create dictionary of player; ranking from df_selected using dict(zip()) and map to df_player['name']

df_player['ranking']=df_player['name'].map(dict(zip(df_selected.player,df_selected.ranking))).fillna(0).astype(int)
print(df_player)
 

          name           team  ranking
0             Keno    Atlético-MG        1
1      Filipe Luís       Flamengo        3
2  Thiago Galhardo  Internacional        2
3       SomePlayer       SomeTeam        0

Upvotes: 1

Tom
Tom

Reputation: 1063

Here's how I do it.

merge_dict = dict(zip(df_selected['player'], df_selected['ranking']))
df_player['ranking'] = df_player['player'].map(merge_dict)

I think that solves your problem, and will be much faster than your for loop.

Upvotes: 0

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