CODEWITHSUNDEEP
pythonpandas
user12907213
user12907213

Reputation:

New column with values 1/0 in pandas

I have this dataframe having one column of my interest:

Col1   
code 
goal
python
detail

I would like to create a new column, Col2 having values 1 or 0 depending on rows' value in Col1; specifically:

My output would be:

Col1       Col2
code        0
goal        1
python      0
detail      1

I tried

# set default value
df['Col2'] = 0

# update according to conditions
df.loc[df['Col1'].str.contains('goal'), 'Col2'] = 1
df.loc[df['Col1'].str.contains('detail'), 'Col2'] = 1
df.loc[df['Col1'].str.contains('objective'), 'Col2'] = 1

but this seems to be partially wrong. I think I should use apply and consider word x in my_list rather than doing manually (it would be difficult in case of many, many!, values in the list).

I hope you can help me.

Upvotes: 0

Views: 1315

Answers (2)

sushanth
sushanth

Reputation: 8302

Use np.where + Series.isin

import numpy as np

my_list=['goal', 'detail', 'objective']

df['Col2'] = np.where(df.Col1.isin(my_list), 1, 0)

or as mentioned by @Ch3steR

df['Col2'] = df.Col1.isin(my_list).astype('int')

     Col1  Col2
0   code      0
1    goal     1
2  python     0
3  detail     1

Upvotes: 1

pfuhlert
pfuhlert

Reputation: 531

How about apply:

import pandas as pd


df = pd.DataFrame(data = ['code', 'goal', 'python', 'detail'], columns = ['Col1'])

mylist=['goal', 'detail', 'objective']

df['Col2'] = df['Col1'].apply(lambda cell: 1 if cell in mylist else 0)

gives

     Col1  Col2
0    code     0
1    goal     1
2  python     0
3  detail     1

Upvotes: 0

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