So i have a dataframe like:
and i want an output like:
The rows in df1 are nothing but combinations of the column names, wherever the combination name matches with the column names, that cell will be made as 1 and rest 0
Any idea how to achieve this?
I a trying to loop through each row and do a string contains condition but kind of stuck.
Here is a straightforward way (one-liner) of doing this using explode, get_dummies, and groupby
import pandas as pd
df = pd.DataFrame(['a',['a','b'],['a','b','c'], ['b','c','d'], ['b', 'd']])
multihot = pd.get_dummies(df.iloc[:,0].explode()).groupby(level=0).sum()
result = df.join(multihot)
print(result)
0 a b c d
0 a 1 0 0 0
1 [a, b] 1 1 0 0
2 [a, b, c] 1 1 1 0
3 [b, c, d] 0 1 1 1
4 [b, d] 0 1 0 1
Just make sure that the first column of your input df is the column that contains the lists.
This seems a bit hacky but should do the trick though:
import numpy as np
import pandas as pd
df = pd.DataFrame(np.zeros((2, 4)), columns=["a", "b", "c", "d"], index=["a", ["a", "b"]])
pd.DataFrame(df.index.map(lambda l: pd.get_dummies(l, columns=df.columns).agg("sum")).tolist(), index=df.index).fillna(0)
# a b
# a 1.0 0.0
# [a, b] 1.0 1.0
I was able to do it using below code
df.reset_index(inplace=True)
for i in range(1,len(df.columns)):
df.iloc[:, i]= df['index'].apply(lambda x: 1 if df.columns[i] in(x) else 0)
df