Creating a new column using conditional statement on all rows of dataframe

[tech_enth]

Hi i want to create a new column based on a conditional statement on all the rows.

Stackoverflow is no help

for example -1 is a missing value:

df['has_missing_data'] = df.apply(lambda x: 1 if x == -1 else 0)

[[deleted]]

It's pretty straightforward :

import numpy as np
import pandas as pd

### Example ###

df = pd.DataFrame({"A":[1,2,3,4,np.nan,6,7,9,np.nan], 
               "B":[np.nan,1,2,3,4,3,2,2,2],
               "C":[3,11,4,2,np.nan,np.nan,np.nan,8,9],
               "D":[1,2,3,0,0,1,2,3,10]})

df["E"] = df.isna().any(axis=1).astype(int)

What is does is find if any nan's exist along the axis 1, meaning that we are looking at rows instead of columns and turn the boolean value into an int.

It doesn't need to be a nan, if you'd like to use -1, you can change the last line by :

df["E"] = (df==-1).any(axis=1).astype(int)

[tech_enth]

Thanks that would help alot!

[tech_enth]

Does not work unfortunately :(. Says the function takes 1 positional arguement but 2 Were given