Comparing two data frames columns and assigning Zero and One

I have a dataframe and a list, which includes a part of columns' name from my dataframe as follows:

 my_frame:
           col1, col2, col3, ..., coln
              2,    3,    4, ..., 2
              5,    8,    5, ..., 1
              6,    1,    8, ..., 9

 my_list:
             ['col1','col3','coln']

Now, I want to create an array with the size of my original dataframe (total number of columns) which consists only zero and one. Basically I want the array includes 1 if the there is a similar columns name in "my_list", otherwise 0. My desired output should be like this:

  my_array={[1,0,1,0,0,...,1]}

Solution

This should help u:

import pandas as pd

dictt = {'a':[1,2,3],
         'b':[4,5,6],
         'c':[7,8,9]}

df = pd.DataFrame(dictt)

my_list = ['a','h','g','c']

my_array = []

for column in df.columns:
    if column in my_list:
        my_array.append(1)
    else:
        my_array.append(0)
print(my_array)

Output:

[1, 0, 1]

If u wanna use my_array as a numpy array instead of a list, then use this:

import pandas as pd
import numpy as np

dictt = {'a':[1,2,3],
         'b':[4,5,6],
         'c':[7,8,9]}

df = pd.DataFrame(dictt)

my_list = ['a','h','g','c']

my_array = np.empty(0,dtype = int)

for column in df.columns:
    if column in my_list:
        my_array = np.append(my_array,1)
    else:
        my_array = np.append(my_array,0)
print(my_array)

Output:

[1 0 1]

I have used test data in my code for easier understanding. U can replace the test data with ur actual data (i.e replace my test dataframe with ur actual dataframe). Hope that this helps!