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https://github.com/tigureis/data-preparation-from-kickstarter-campaigns

Kickstarter Data Prep: A hands-on guide to basic data cleaning and transformation.
https://github.com/tigureis/data-preparation-from-kickstarter-campaigns

data-cleaning data-construction data-integration data-science data-selection numpy pandas

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Kickstarter Data Prep: A hands-on guide to basic data cleaning and transformation.

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README

          

This project focuses on preparing a Kickstarter campaign database and demonstrating basic data preparation techniques commonly used in data science and machine learning. It involves cleaning, transforming, and integrating data from multiple sources to create a dataset ready for further analysis.

## Project Overview

This project aims to provide a hands-on learning experience for basic data preparation techniques. By working through this project, you will learn how to:

1. **Import and Explore Data:** Load data from CSV files using Pandas, and explore its structure and content.
2. **Clean Data:** Handle missing values, remove irrelevant columns, and correct data types.
3. **Construct Data:** Create new features from existing data, such as campaign duration.
4. **Integrate Data:** Merge data from different sources into a single, unified dataset.

**This project serves as an educational resource for understanding fundamental data preparation concepts. It is not intended for comprehensive Kickstarter campaign analysis.**

## Data

The data for this project is stored in the following files:

* `DataPrepFinal.csv`: Contains information about Kickstarter campaigns, including ID, category, goal, launch date, and deadline.
* `campaign.csv`: Provides additional campaign details, such as the textual description and other attributes.
* `invested.csv`: Includes information about the backers, including their age, location, and investment amount.

## Dependencies

* Python 3.7 or higher
* pandas
* numpy