Counting Colums In Csv File With Python

I want to count email accounts of male and female separately the code I wrote is not working properly so can anyone help me with this, please here is my code thank you in advance

Solution 1:

use pandas

import pandas as pd

df = pd.read_csv('your_csv_file.csv') # read in csvdf['domain'] = df['email'].apply(lambda x: x[x.index('@')+1:]) # column with just domain

male = {} # setup male dictionary
female = {} # setup female dictionary# iterate on unique domains to get a count of male/female and populate in dictionariesfor domain indf['domain'].unique():   
    male[domain] = df[(df['gender']=='M') & (df['domain']==domain)].shape[0]
    female[domain] = df[(df['gender']=='F') & (df['domain']==domain)].shape[0]

Solution 2:

This can be done in pandas. As your columns are unnamed, use header=None when reading your csv and access the columns by number:

import pandas as pd

df = pd.read_csv('1000 Records.csv', header=None)
df['mailhosts'] = df[6].str.split('@').str[-1]

gp = df.groupby(5)

#count e-mail accounts per gender:print('Female Email Accounts:', gp.get_group('F')['mailhosts'].value_counts())
print('Male Email Accounts:', gp.get_group('M')['mailhosts'].value_counts())

Solution 3:

Here is a solution that counts male and female accounts by domain using just standard Python modules:

import csv
from collections import Counter

males = Counter()
females = Counter()

withopen('1000 Records.csv') as f:
    records = csv.reader(f)
    for record in records:
        _, domain = record[6].split('@')
        gender = record[5]
        if gender.lower() == 'm':
            males.update((domain.lower(),))
        else:
            females.update((domain.lower(),))

    print('Total male accounts:', sum(males.values()))
    print('Total male accounts by domain')
    for k, v in males.items():
        print(k, v)

    print('Total female accounts:', sum(females.values()))
    print('Total female accounts by domain')
    for k, v in females.items():
        print(k, v)