CODEWITHSUNDEEP
pandasdataframe
user3447653
user3447653

Reputation: 4148

Filtering all rows based on a specific value in Pandas dataframe

I have a dataframe that has "yes" when a condition is satisfied and "no" when it is not. Now, I would like to retrieve all the rows that has "No" in it.

I tried with this code:

 df2 = df[df['Logs'].astype(str).str.contains('No')] 
 df3 = df[df['Jobs'].astype(str).str.contains('No')] 
 df4 = df[df['Performance'].astype(str).str.contains('No')] 
 df5 = df2 | df3 | df4

I got the error "unsupported operand types".

For example:

 MachineName    Logs   Jobs   Performance
 121            Yes    No      Yes
 122            Yes    Yes     Yes
 123            Yes    No      No
 125            Yes    Yes     Yes
 126            No     No      No

Output:

 MachineName    Logs   Jobs   Performance
 121            Yes    No      Yes
 123            Yes    No      No
 126            No     No      No

Upvotes: 1

Views: 158

Answers (1)

root
root

Reputation: 33793

Do an equality check on all columns you want to be 'No', and then use any to get a Boolean array.

condition = (df[['Logs', 'Jobs', 'Performance']] == 'No').any(axis=1)
df2 = df[condition]

The resulting output is as expected:

   MachineName Logs Jobs Performance
0          121  Yes   No         Yes
2          123  Yes   No          No
4          126   No   No          No

Upvotes: 1

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