https://github.com/lkethridge/eda_project
Exploratory Data Analysis Project from TripleTen
https://github.com/lkethridge/eda_project
analytical-thinking bar-chart critical-thinking data-transformation data-visualization exploratory-data-analysis feature-engineering filtering-data histogram line-plot matplotlib pivot-tables python scatter-matrix scatterplot
Last synced: 2 months ago
JSON representation
Exploratory Data Analysis Project from TripleTen
- Host: GitHub
- URL: https://github.com/lkethridge/eda_project
- Owner: LKEthridge
- License: cc0-1.0
- Created: 2025-01-18T22:48:47.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2025-01-19T00:52:45.000Z (5 months ago)
- Last Synced: 2025-02-02T05:28:59.206Z (4 months ago)
- Topics: analytical-thinking, bar-chart, critical-thinking, data-transformation, data-visualization, exploratory-data-analysis, feature-engineering, filtering-data, histogram, line-plot, matplotlib, pivot-tables, python, scatter-matrix, scatterplot
- Language: Jupyter Notebook
- Homepage:
- Size: 6.42 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# EDA_Project
## *This was an Exploratory Data Analysis project for TripleTen. 👩🏽💻*
This project analyzes Instacart's 2017 data to uncover customer shopping habits and patterns. Findings reveal that customers primarily order fresh food, such as produce and dairy, with a strong preference for organic items. Most orders are small (1-5 items), but reorders make up 90% of each order on average. These insights can guide Instacart in optimizing advertising campaigns and customer retention strategies, such as promoting frequently reordered items or offering targeted discounts to re-engage inactive customers.
## Skills Highlighted
🐍 Python
🧐 Exploratory Data Analysis
➡️ Data Transformation
👩🏽💻 Pivot Tables
👀 Data Visualization
📈 matplotlib.pyplot
⚙️ Feature Engineering
🤔 Critical and Analytical Thinking
## Installation & Usage
* This project uses pandas and matplotlib.pyplot. It requires python 3.9.6.
* Due to upload limitations, one data file could not be uploaded to GitHub.