How To Calculate Average For Every Column In A Csv File

We are given a CSV file and our task is to find the average of each column in Python using different approaches. In this article, we will see how we can calculate the average for every column in a CSV file.

Example:

Input: data.csv
Age,Salary
30,50000
25,60000
28,55000

Output: Average Age: 27.67, Average Salary: 55000.00

Calculate the Average For Every Column in a Python CSV file

Below are some of the ways by which we can calculate the average for every column in a Python CSV file:

1. Using CSV module and Manual Calculation
2. Using Pandas Library
3. Using NumPy Library

data.csv

Age,Salary
30,50000
25,60000
28,55000

Using the csv and Manual Calculation

In this example, the Python program reads a CSV file ('data.csv'), calculates the sum and count of numeric values in each column, and then computes and prints the average for each column, handling non-numeric values gracefully. The results are displayed with two decimal places.

Output:

Average Age: 27.67
Average Salary: 55000.00

Using Pandas Library

In this example, the Python script uses the Pandas library to read a CSV file ('data.csv') into a DataFrame. It then calculates the average for each column using the mean() function and displays the results, providing a concise and efficient approach for calculating column averages in a CSV dataset.

Output:

Average for each column:
Age 27.666667
Salary 55000.000000
dtype: float64

Using NumPy Library

In this example, the Python script utilizes the NumPy library to read a CSV file ('data.csv') and convert it into a NumPy array of integers, skipping the header row. It then calculates the average for specific columns (Age and Salary) using np.mean() and displays the results with two decimal places. This approach provides a concise method for computing column averages in a CSV dataset with numerical data.

Output:

Average Age: 27.67
Average Salary: $55000.00