need to fill the non-null values to NaN based on column name-CodePudding

enter image description here here need to update the non-null values of the columns values where specific text contains want to make them to nan values based on the column names. attached image for you reference.

CodePudding user response：

Consider the following dataset

Replace column name with nan. But this won't replace any other string e.g. X0 contains value oth.

df.apply(lambda s: s.replace({s.name: np.nan}))

Replace all string with nan

df.apply(lambda s: pd.to_numeric(s, errors='coerce'))

Replace all string with nan on subset of columns

COLS = ['X0', 'X2']
df.apply(lambda s: pd.to_numeric(s, errors='coerce') if s.name in COLS else s)

Note: I have used pandas apply function but same result can be achieved with for loop

CodePudding user response：

Is this what you are looking for?

import pandas as pd
import numpy as np

# Create a sample DataFrame
df = pd.DataFrame({'col1': [1, 'col1', 3, 4], 'col2': [5, 6, 'col2', 8]})

df = df.apply(lambda x: x.replace({x.name: np.nan}))

print(df)