CODEWITHSUNDEEP
pythonpandas
Kartheek Palepu
Kartheek Palepu

Reputation: 972

Python - Divide the column into multiple columns using Split

I have a Pandas dataframe like this {each row in B is a string with values joined with | symbol}:

A B
a 1|2|3
b 2|4|5
c 3|2|5

I want to create columns which say that the value is present in that row(of column B) or not:

A B     1 2 3 4 5
a 1|2|3 1 1 1 0 0
b 2|4|5 0 1 0 1 1
c 3|5   0 0 1 0 1

I have tried this by looping the columns. But, can it be done using lambda or comprehensions?

Upvotes: 4

Views: 583

Answers (2)

jezrael
jezrael

Reputation: 862661

You can try get_dummies:

print df
   A      B
0  a  1|2|3
1  b  2|4|5
2  c  3|2|5

print df.B.str.get_dummies(sep='|')
   1  2  3  4  5
0  1  1  1  0  0
1  0  1  0  1  1
2  0  1  1  0  1

And if you need old column B use join:

print df.join(df.B.str.get_dummies(sep='|'))
   A      B  1  2  3  4  5
0  a  1|2|3  1  1  1  0  0
1  b  2|4|5  0  1  0  1  1
2  c  3|2|5  0  1  1  0  1

Upvotes: 4

Sagar Waghmode
Sagar Waghmode

Reputation: 777

Hope this helps.

In [19]: df
Out[19]: 
   A      B
0  a  1|2|3
1  b  2|4|5
2  c  3|2|5

In [20]: op = df.merge(df.B.apply(lambda s: pd.Series(dict((col, 1)  for col in s.split('|')))), 
left_index=True, right_index=True).fillna(0)

In [21]: op
Out[21]: 
   A      B  1  2  3  4  5
0  a  1|2|3  1  1  1  0  0
1  b  2|4|5  0  1  0  1  1
2  c  3|2|5  0  1  1  0  1

Upvotes: 1

Related Questions