I have a dataframe which is something like this:
index buyedA total
a 2 4
b 1 2
and I need to turn it into something like this:
index buyedA total
a 1 1
a 1 1
a 0 1
a 0 1
b 1 1
b 0 1
I need for each index as many rows as specified by column total (each one filled with a value of 1), and if column buyedA says 2, I need 2 of those rows filled with a 1.
Is there a way to do so in Python?
Thanks!
Using repeat and a simple groupby
n = df.loc[df.index.repeat(df.total)].assign(total=1)
n['buyedA'] = n.groupby('index').total.cumsum().le(n.buyedA).astype(int)
index buyedA total
0 a 1 1
0 a 1 1
0 a 0 1
0 a 0 1
1 b 1 1
1 b 0 1
Let's try this:
#make sure index is in the dataframe index
df=df.set_index('index')
#use repeat and reindex
df_out = df.reindex(df.index.repeat(df['total'])).assign(total=1)
#Limit buyedA by row number in each group of index
df_out['buyedA'] = ((df_out.groupby('index').cumcount() + 1) <= df_out['buyedA']).mul(1)
df_out
output:
buyedA total
index
a 1 1
a 1 1
a 0 1
a 0 1
b 1 1
b 0 1
