Create a mask in Pandas with a loop-CodePudding

rand_samp = fips.sample(n=20)
rand_samp.reset_index(inplace=True)
print(rand_samp)
countys = rand_samp['CountyID'].to_list()
mask = ((temp['CountyID'] == countys[0]) | (temp['CountyID'] == countys[1]) | (temp['CountyID'] == countys[2]) | (temp['CountyID'] == countys[3]) | (temp['CountyID'] == countys[4]) | (temp['CountyID'] == countys[5]) | (temp['CountyID'] == countys[6]) | (temp['CountyID'] == countys[7]) | (temp['CountyID'] == countys[8]) | (temp['CountyID'] == countys[9]) | (temp['CountyID'] == countys[10]) | (temp['CountyID'] == countys[11]) | (temp['CountyID'] == countys[12]) | (temp['CountyID'] == countys[13]) | (temp['CountyID'] == countys[14]) | (temp['CountyID'] == countys[15]) | (temp['CountyID'] == countys[16]) | (temp['CountyID'] == countys[17]) | (temp['CountyID'] == countys[18]) | (temp['CountyID'] == countys[19]))
temp_rand = temp[mask]
temp_rand.reset_index(inplace=True)
temp_rand

I am looking for a better way to make a mask for my dataset that doesn't involve typing out each individual statement. I tried to use a for loop to loop through my list and then append to the new dataset but is there any other ways?

CodePudding user response：

ìsin() is what you are looking for.

import pandas as pd

temp = pd.DataFrame([['USA', 1],['Poland', 8], ['Austria', 3]], columns=['CountyID', 'GDP'])

countys = ['Germany', 'Austria', 'Poland']
mask = temp['CountyID'].isin(countys)
print(mask)

temp_rand = temp[mask]

Output:

0    False
1     True
2     True
Name: CountyID, dtype: bool