Pandas – flatten columns

Question

After:

aggregating with sum()
grouping by ['country', 'match_id']
creating a mean column with mean(axis=1)

I ended up with this:

                     Gls  Ast  avg_attack 
                     sum  sum 
country    match_id
Argentina  20eb96e2  0.10 0.20 0.15
           18eb43e2  0.20 0.30 0.25
...

Now, how do I flatten my dataframe back to this?

country     match_id Gls  Ast  avg_attack 
Argentina  20eb96e2  0.10 0.20 0.15
Argentina  18eb43e2  0.20 0.30 0.25

Asked By: 8-Bit Borges

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Source

Answer 1

Use pandas.Index.get_level_values to flatten the hierarchical index in columns then pandas.DataFrame.reset_index to reset the multi index in rows.

df.columns = df.columns.get_level_values(0)
out = df.reset_index()

# Output :

print(out)

     Country  match_id  Gls   Ast   avg_attack
0  Argentina  20eb96e2  0.10  0.20        0.15
1  Argentina  18eb43e2  0.20  0.30        0.25

Answered By: abokey

Pandas – flatten columns

Question:

Answers:

# Output :