Compare several dataframe columns to list-CodePudding

I have a Dataframe like this (the columns are not side by side):

 Num A Num B Num C Marked
0  213   314   512
1  612   516   713
2  613   678   125
3  163   813   312

And a list like list = [612,813,512,713]

I now want to compare, if a value from the list is present in the dataframe, and mark it with 1, else with 0, so that the output is:

 Num A Num B Num C Marked
0  213   314   512      1
1  612   516   713      1
2  613   678   125      0
3  163   813   312      1

I only found out how to do this with a single column:

import pandas as pd
import numpy as np

path = "path"
wb = pd.ExcelFile(path)
df = wb.parse("Sheet1")

list = [612,813,512,713]

df['Marked'] = df.Num_A.isin.(list).astype(int)

How can you make this to consider all columns?

Thanks in Advance!

CodePudding user response：

You can use np.isin method to check if numbers in lst exist in df along columns and then convert it to integer value:

df['Marked'] = np.isin(df.values,lst).any(axis=1).astype(int)

CodePudding user response：

Generate a 2. df, use the isin there, add prefix to columns of second dataframe, then join them together:

lst = [612,813,512,713]

df.join(df.isin(lst).add_prefix('Marked_'))