How to count the number of lines in a CSV file in Python?

Counting the number of lines in a CSV file in Python means determining how many rows the file contains, including or excluding the header depending on your needs. For example, if your CSV file has 100 data rows plus one header row, the total line count is 101. We will use the following dataset to demonstrate these operations:

import pandas as pd

res = pd.read_csv('Data.csv')
print(res)

Output

Using sum()

This method reads the file line by line and counts each one. It’s a pure Python approach, very fast and memory efficient and it works even if the file is huge.

with open('Data.csv', 'r', encoding='utf-8') as f:
    res = sum(1 for line in f)
print(res)

Output

11

Explanation: Inside the with block, a generator expression iterates over each line in the file (for line in f) and yields 1 for every line. The sum() function then adds all those 1s, effectively counting the number of lines in the file.

Using wc-l

wc -l is a Unix command that counts the number of lines in a file. Here, we run that command from Python using subprocess.

import subprocess

res = int(subprocess.check_output(['wc', '-l', 'Data.csv']).split()[0])
print(res)

Output

11

Explanation: subprocess.check_output runs the command wc -l Data.csv, which counts the number of lines in the file. The output is split into parts and the first part (the line count) is converted to an integer and stored in res.

Using Pandas with chunksize

This is the simplest and most straightforward way to count the number of rows. You load the whole CSV file into a pandas DataFrame and count how many rows it has.

import pandas as pd

res = sum(len(chunk) for chunk in pd.read_csv('Data.csv', chunksize=10000))
print(res + 1) # data rows + header

Output

11

Explanation: pd.read_csv('Data.csv', chunksize=10000) reads the CSV in chunks of up to 10,000 rows. len(chunk) counts rows per chunk and sum(...) totals all data rows (excluding the header). Adding 1 accounts for the header, so the final output is the total lines in the CSV.

Using len(pd.read_csv(...))

This is the simplest and most straightforward way to count the number of rows. You load the whole CSV file into a pandas DataFrame and count how many rows it has.

import pandas as pd

df = pd.read_csv('Data.csv')
print(len(df) + 1)  # data rows + header

Output

11

Explanation: pd.read_csv('Data.csv') loads the CSV into a DataFrame df. len(df) counts only the data rows, excluding the header. Adding +1 includes the header row, so len(df) + 1 gives the total number of lines in the CSV file.

Related articles

• sum()
• len()
• Pandas