Chunked reading for large files in Data Analysis Python - Mini Project: Build & Apply

Chunked reading for large files

📖 Scenario: Imagine you have a very large sales data file that cannot fit into your computer's memory all at once. You want to analyze this data step-by-step without crashing your program.

🎯 Goal: You will learn how to read a large CSV file in small parts called chunks, process each chunk, and combine the results to get the total sales.

📋 What You'll Learn

Create a variable with the file path to the sales data CSV

Set a chunk size to control how many rows to read at once

Use pandas to read the CSV file in chunks

Calculate the total sales from all chunks

Print the final total sales

💡 Why This Matters

🌍 Real World

Large companies often have huge data files that cannot fit into memory. Reading data in chunks helps analyze such files efficiently.

💼 Career

Data analysts and data scientists use chunked reading to handle big data files without crashing their programs.

1

Set the file path for the sales data

Create a variable called file_path and set it to the string 'sales_data.csv'.

Data Analysis Python

# Create a variable called file_path and set it to 'sales_data.csv'
# Your code here

Hint

Use a simple assignment like file_path = 'sales_data.csv'.

2

Set the chunk size for reading the file

Create a variable called chunk_size and set it to the integer 1000.

Data Analysis Python

file_path = 'sales_data.csv'
# Create a variable called chunk_size and set it to 1000
# Your code here

Hint

Set chunk_size to 1000 to read 1000 rows at a time.

3

Read the CSV file in chunks and sum the sales

Import pandas as pd. Create a variable called total_sales and set it to 0. Use pd.read_csv with file_path and chunksize=chunk_size to read the file in chunks. Use a for loop with the variable chunk to iterate over the chunks. Inside the loop, add the sum of the 'sales' column of each chunk to total_sales.

Data Analysis Python

file_path = 'sales_data.csv'
chunk_size = 1000
# Import pandas as pd
# Create total_sales = 0
# Use pd.read_csv with chunksize=chunk_size
# Use for chunk in ... to iterate
# Add sum of 'sales' column in chunk to total_sales
# Your code here

Hint

Use pd.read_csv(file_path, chunksize=chunk_size) to get chunks. Sum the 'sales' column in each chunk and add to total_sales.

4

Print the total sales

Write a print statement to display the text 'Total sales:' followed by the value of total_sales.

Data Analysis Python

import pandas as pd

file_path = 'sales_data.csv'
chunk_size = 1000

total_sales = 0
for chunk in pd.read_csv(file_path, chunksize=chunk_size):
    total_sales += chunk['sales'].sum()

# Print the total sales
# Your code here

Hint

Use print('Total sales:', total_sales) to show the result.