Why are all values NaN after mapping 'player_name' column in Pandas Data Frame?

[Arman777]

I have two data frames df1 and df2

df1 has two columns 'player_name' and 'player_id'.

Similarly df2 has 'player_id' column.

From this configuration I want to pass 'player_name' column to df2 by using 'player_id'. For this reason I have tried something like this,

df2['player_name'] = df2['player_api_id'].map(df1['player_name'])

The code runs without error and I obtain 'player_name' column in df2 but all the values are NaN. I did not understand why this happens.

 

[Borg]

Two questions. Are the two dataframes the same size and do they share a column that acts like a primary key? If so, then I would use a merge with just the column that you want to add and its key from the other dataframe.

 

[Arman777]

You can look at the data from here

https://www.kaggle.com/hugomathien/soccer

I am only interested in Player and Player_Attributes datas. In those data as you can see there are two columns that has the same name; player_api_id.

So as I have said before I want to move player_name from the Player data to Player_Attributes by using the player_api_id.

Are the two dataframes the same size

Nope

ey share a column that acts like a primary key?

I guess so

 

[Borg]

Sorry, I was responding from my phone and didn't read closely enough.

df2['player_name'] = df2['player_api_id'].map(df1['player_name'])

If you want to add player names to df2 from df1, you would need to replace the df1['player_name'] part with a dictionary of IDs and player names from df1. Assuming that the Player table has no duplicates, something like this:
player_name_dictionary = dict(zip(df1.player_api_id, df1.player_name)) df2['player_name'] = df2['player_api_id'].map(player_name_dictionary)

 

[Arman777]

Sorry, I was responding from my phone and didn't read closely enough.

If you want to add player names to df2 from df1, you would need to replace the df1['player_name'] part with a dictionary of IDs and player names from df1. Assuming that the Player table has no duplicates, something like this:
player_name_dictionary = dict(zip(df1.player_api_id, df1.player_name)) df2['player_name'] = df2['player_api_id'].map(player_name_dictionary)

thanks a lot. It works