if-else for multiple conditions dataframe

Question

I don't know how to right properly the following idea: I have a dataframe that has two columns, and many many rows. I want to create a new column based on the data in these two columns, such that if there's 1 in one of them the value will be 1, otherwise 0. Something like that:

if (df['col1']==1 | df['col2']==1):
   df['newCol']=1
else:
   df['newCol']=0

I tried to use .loc function in different ways but i get different errors, so either I'm not using it correctly, or this is not the right solution...

Would appreciate your help. Thanks!

Possible duplicate of this post: [pandas-conditional-creation-of-a-series-dataframe-column](https://stackoverflow.com/questions/19913659/pandas-conditional-creation-of-a-series-dataframe-column) — Alexandre B., Jun 10 '19 at 11:31

Vishnudev Krishnadas · Answer 1 · 2019-06-10T11:35:49.943

1

Simply use np.where or np.select

df['newCol'] = np.where((df['col1']==1 | df['col2']==1), 1, 0)

OR

df['newCol'] = np.select([cond1, cond2, cond3], [choice1, choice2, choice3], default=def_value)

When a particular condition is true replace with the corresponding choice(np.select).

edited Jun 10 '19 at 11:35

answered Jun 10 '19 at 11:30

Vishnudev Krishnadas

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Mohamed Thasin ah · Answer 2 · 2019-06-10T11:34:30.393

0

one way to solve this using .loc,

df.loc[(df['col1'] == 1 | df['col2']==1) ,'newCol'] = 1
df['newCol'].fillna(0,inplace=True)

incase if you want newcol as string use,

df.loc[(df['col1'] == 1 | df['col2']==1) ,'newCol'] = '1'
df['newCol'].fillna('0',inplace=True)

or

df['newCol']=df['newCol'].astype(str)

edited Jun 10 '19 at 11:34

answered Jun 10 '19 at 11:28

Mohamed Thasin ah

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thanks. but this is only for case where value is boolean. What would i do if i want the new column to be string? – user3080219 Jun 10 '19 at 11:29
can you show me a sample data? where the above one doesn't work – Mohamed Thasin ah Jun 10 '19 at 11:30
here's an example that won't compile: ``` data['status'] = np.where((not(pd.isnull(le_data['mode'])))|pd.isnull(le_data['status']), 'not_active', 'active') ``` – user3080219 Jun 10 '19 at 13:23

if-else for multiple conditions dataframe

2 Answers2