I want to take a dataframe that has single head and add mutli-index head columns. The columns that will be multi head are all IDs. I then have IDs and names in a 2nd dataframe.
Here is my example data
df = pd.DataFrame({"A": ['fay','fee','fie','foe']})
df1 = pd.DataFrame(np.random.randint(0,10,size=(4,4)), columns=['012','015','016','018'])
df1 = pd.merge(df,df1, right_index = True, left_index = True)
df2 = pd.DataFrame({'id':['018','015','012','016'], 'name':['boom','bing', 'bota','bada']})
dict_id = dict(zip(df2.id,df2.name))
for the next part how do I make it multilayered like show below?
bota bing bada boom
A 012 015 016 018
____________________________
0 fay 0 3 1 5
1 fee 1 2 9 7
2 fie 5 1 0 3
3 foe 0 7 8 5
Create MultiIndex by Index.map with assign list to columns names:
df1.columns = [df1.columns.map(dict_id).fillna(''), df1.columns]
print (df1)
bota bing bada boom
A 012 015 016 018
0 fay 9 7 4 4
1 fee 2 3 1 1
2 fie 6 4 5 1
3 foe 8 6 4 4