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?