Pandas - Working on CSV

Lecture 14:- Pandas - Working on CSV

In Pandas, you can easily work with CSV (Comma-Separated Values) files, which are commonly used for storing tabular data. Pandas provides the read_csv() function to read data from a CSV file and create a DataFrame, and the to_csv() function to save a DataFrame to a CSV file. Here's how you can work with CSV files using Pandas:

Reading CSV File: To read data from a CSV file and create a DataFrame, you can use the pd.read_csv() function. It automatically parses the data and creates a DataFrame with appropriate data types.

The read_csv() function can handle various options such as specifying the delimiter, header row, specifying columns to read, handling missing values, and more. You can refer to the Pandas documentation for additional options.

Saving DataFrame to CSV File: To save a DataFrame to a CSV file, you can use the to_csv() function. It writes the DataFrame contents to a CSV file that can be easily shared or used for further analysis.

The index=False argument prevents writing the row index to the CSV file. If you want to keep the index in the CSV file, you can omit this argument or set it to True.

Working with CSV Options: When reading or writing CSV files, you may need to specify additional options based on the structure of the CSV file. For example:

These are some of the basic operations for working with CSV files using Pandas. Pandas is highly flexible, and it allows you to handle various CSV file structures and configurations. It is an excellent tool for data manipulation and analysis with tabular data stored in CSV format.

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# Reading CSV with a custom delimiter (e.g., tab-separated) df = pd.read_csv('data.tsv', delimiter='\t') # Reading CSV with specific columns and header df = pd.read_csv('data.csv', usecols=['Name', 'Age', 'City'], header=0) # Writing CSV with specific options (e.g., encoding and decimal separator) df.to_csv('output.csv', index=False, encoding='utf-8', decimal=',')

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import pandas as pd # Assuming you have a DataFrame named 'df' df.to_csv('output.csv', index=False)

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import pandas as pd # Read data from a CSV file and create a DataFrame df = pd.read_csv('data.csv')