This repository contains code that utilizes the Pandas library for data manipulation and analysis. Pandas is a powerful Python library that provides easy-to-use data structures and data analysis tools, making it a popular choice for data scientists, analysts, and engineers.
Before running the code, ensure you have the following installed:
- Python (version 3.6 or higher)
- Pandas library (install via
pip install pandas)
It's recommended to set up a virtual environment to keep your dependencies isolated from other projects.
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Clone the repository to your local machine:
git clone https://github.com/your-username/pandas-code.git -
Navigate to the project directory:
cd pandas-code -
Install the required dependencies (if not done already, see Prerequisites):
pip install -r requirements.txt
The code in this repository demonstrates various functionalities of the Pandas library, including:
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Data Loading: How to read data from different file formats such as CSV, Excel, JSON, etc.
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Data Cleaning: Techniques for handling missing values, data imputation, and data transformation.
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Data Manipulation: How to filter, sort, and group data based on specific criteria.
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Data Analysis: Examples of calculating summary statistics, aggregations, and applying mathematical operations.
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Data Visualization: Basic data visualization using Pandas and other compatible visualization libraries like Matplotlib or Seaborn.