Say I have a dataframe like this:
I know I can drop levels so that I have columns: ['Season', 'Players', 'Teams']. Is there a function in pandas where I can collapse 'First team' name into a column so that the entire column says 'First team'?
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1 Answer
IIUC, you can do a few different things, here are two ways:
Where dummy dataframe,
df = pd.DataFrame(np.random.randint(0,100,(5,3)),
columns = pd.MultiIndex.from_tuples([('Season', 'Season'),
('First team', 'Players'),
('First team', 'Teams')]))
Input dummy dataframe:
Season First team
Season Players Teams
0 28 41 53
1 62 87 87
2 43 94 4
3 23 12 93
4 14 43 62
Then use droplevel:
df = df.droplevel(0, axis=1)
Output:
Season Players Teams
0 54 94 19
1 54 47 91
2 56 35 40
3 37 68 14
4 17 78 68
Or flatten multiindex column header using list comprehension:
df.columns = [f'{i}_{j}' for i, j in df.columns]
#Also, can use df.columns = df.columns.map('_'.join)
df
Output:
Season_Season First team_Players First team_Teams
0 54 94 19
1 54 47 91
2 56 35 40
3 37 68 14
4 17 78 68