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
Last synced: 3 months ago
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Kickstarter Data Prep: A hands-on guide to basic data cleaning and transformation.
- Host: GitHub
- URL: https://github.com/tigureis/data-preparation-from-kickstarter-campaigns
- Owner: tigureis
- Created: 2024-11-25T23:34:21.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-12-05T21:10:28.000Z (over 1 year ago)
- Last Synced: 2025-03-23T10:45:36.502Z (over 1 year ago)
- Topics: data-cleaning, data-construction, data-integration, data-science, data-selection, numpy, pandas
- Language: Jupyter Notebook
- Homepage:
- Size: 6.75 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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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