how to create new pandas column where list value ==df index but list is a different length to orignal dataframe

Question

I would like to add a new column to my orignal dataframe where my list values == dataframe index add 1 else 0. However, my list isn't the same size... I tried with a for loop but its too slow.. and wanted to either do it with a list comp or vectorized ( or any other way thats quick).. any ideas on how i do it

My Data:

list =[501,205,432,....]

my code:

df = df.reset_index(drop=True)

for r in range(0,len(df)):
    for peak in peaks:
        if df.index[r]==peak:
            df.loc[r,"peaks"]=1
        else:
            df.loc[r,"peaks"]=0

Answer 1

Try using isin on index:

import pandas as pd

df = pd.DataFrame({'a': {100: 1, 200: 2, 300: 3, 400: 4, 500: 5}})

peaks = [300, 400, 500]

df['peaks'] = df.index.isin(peaks).astype(int)

print(df)

---

Vectorized via numpy

import pandas as pd
import numpy as np

df = pd.DataFrame({'a': {100: 1, 200: 2, 300: 3, 400: 4, 500: 5}})

peaks = [300, 400, 500]

df['peaks'] = np.where(df.index.isin(peaks), 1, 0)

print(df)

---

Output:

     a  peaks
100  1      0
200  2      0
300  3      1
400  4      1
500  5      1