How to count appearance of all items in a row on Pandas Dataframe [closed]

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II'm currently learning the Pandas library in Python (without AI assistance), and in one of my tasks I needed to count how many times each item appeared in a row of a DataFrame. Here's an example of the CSV I'm using:

ip,datetime,method,url,status,response_time
192.168.0.1,2025-11-16 08:00,GET,/home,200,123
10.0.0.2,2025-11-16 08:01,POST,/login,302,250
172.16.0.5,2025-11-16 08:01,GET,/products,200,87
192.168.0.3,2025-11-16 08:02,GET,/cart,500,105
10.0.0.4,2025-11-16 08:03,GET,/home,200,98
172.16.0.6,2025-11-16 08:04,POST,/checkout,201,210
192.168.0.7,2025-11-16 08:05,GET,/products,404,95
10.0.0.8,2025-11-16 08:06,GET,/home,200,110

Count how many times each URL is called.

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– TylerH, Commented yesterday

iBeMeltin · Accepted Answer · 2025-11-17 21:05:43Z

You can count how many times each URL is called by using value_counts().

See the pandas value_counts documentation

import pandas as pd

data = {
    'ip': ['192.168.0.1', '10.0.0.2', '172.16.0.5', '192.168.0.3', '10.0.0.4', '172.16.0.6', '192.168.0.7', '10.0.0.8'],
    'datetime': ['2025-11-16 08:00', '2025-11-16 08:01', '2025-11-16 08:01', '2025-11-16 08:02',
                 '2025-11-16 08:03', '2025-11-16 08:04', '2025-11-16 08:05', '2025-11-16 08:06'],
    'method': ['GET', 'POST', 'GET', 'GET', 'GET', 'POST', 'GET', 'GET'],
    'url': ['/home', '/login', '/products', '/cart', '/home', '/checkout', '/products', '/home'],
    'status': [200, 302, 200, 500, 200, 201, 404, 200],
    'response_time': [123, 250, 87, 105, 98, 210, 95, 110]
}

df = pd.DataFrame(data)

url_counts = df['url'].value_counts()

print(url_counts)

url
/home        3
/products    2
/login       1
/cart        1
/checkout    1
Name: count, dtype: int64

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