How to Parse a CSV File in Python Using Pandas

When working with substantial amounts of data, you likely won’t have it all handwritten in your Python script. Instead, your data will be sourced from multiple files, databases, or even web APIs.

A common file format that’s extensively used for saving data in a structured manner is the CSV or Comma Separated Values format. In this tutorial, we’ll explore how to parse a CSV file in Python using Pandas.

The Example CSV file (students.csv)

"Name","Age","Grade"
"John",17,"11"
"Alice",16,"10"
"Bob",18,"12"
"Charlie",17,"11"

Step 1 – Importing the Necessary Libraries

First, you need to import the necessary libraries to your Python script. In this case, we are using Pandas, which provides an efficient way to parse CSV files. Make sure that you have the pandas library installed.

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import pandas as pd

Step 2 – Reading the CSV File

Next, we’ll use the function read_csv() provided by pandas to read the CSV file. This function will return a DataFrame which contains the data from the CSV file. Assume we have a CSV file named ‘Students.csv’.

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data_frame = pd.read_csv('students.csv')

Step 3 – Viewing the Parsed Data

After reading the CSV file, you may want to look at the data to verify that everything has been loaded correctly. You can do so using the head() function.

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print(data_frame.head())

Step 4 – Working with the Parsed Data

Once the data has been loaded into the data frame, you can use various Pandas functions to manipulate and analyze the data. For example, you can use the describe() function to get a statistical summary of the data.

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print(data_frame.describe())

Complete Python Code

Let’s put the steps together to form the complete Python script.

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import pandas as pd
 
# Step 2 - Reading the CSV File
data_frame = pd.read_csv('students.csv')
 
# Step 3 - Viewing the Parsed Data
print(data_frame.head())
 
# Step 4 - Working with the Parsed Data
print(data_frame.describe())

Conclusion

In this tutorial, we parsed a CSV file into a pandas DataFrame and performed basic data viewing and analysis. Parsing CSV files using pandas in Python is an essential skill in data science and machine learning as CSV files are ubiquitous in the world of data.

Remember the variety of functions pandas provides, and you’ll be able to explore and manipulate your data more effectively!