E-Commerce Data Cleaning and Insights Preparation in Google Sheets or Excel -- 2
Budget: $30 – $250 USD
Clean and organize an e-commerce dataset containing product information across multiple categories. The dataset currently has issues such as missing values, inconsistent formatting, and duplicate entries that must be resolved. Once the data is cleaned, we require insights and visualizations to highlight trends in product categories, pricing, and discounts, which will help inform business decisions.
Key Requirements:
- The data cleaning process will involve:
1. Identifying and handling missing values, such as replacing missing prices with the average price for the respective category.
2. Standardizing data formats to ensure consistency
3. Correcting inconsistencies and unifying similar entries
4. Dealing with duplicate entries by retaining the most complete record for each product.
After cleaning the dataset, you will create visualizations to provide insights, including:
- A bar chart showing the number of listings for each product category.
- A pie chart displaying the percentage distribution of products across price ranges (Low, Medium, and High).
These visualizations should be included in a separate tab of the final spreadsheet.
Deliverables:
The final deliverable will be a Google Sheets or Excel file containing:
- The cleaned dataset
- The requested visualizations
- A brief summary explaining the cleaning process and highlighting any insights derived from the visualizations.
Dataset
Use the Dirty E-Commerce Data dataset from Kaggle, available here https://www.kaggle.com/datasets/oleksiimartusiuk/e-commerce-data-shein.
Key Requirements:
- The data cleaning process will involve:
1. Identifying and handling missing values, such as replacing missing prices with the average price for the respective category.
2. Standardizing data formats to ensure consistency
3. Correcting inconsistencies and unifying similar entries
4. Dealing with duplicate entries by retaining the most complete record for each product.
After cleaning the dataset, you will create visualizations to provide insights, including:
- A bar chart showing the number of listings for each product category.
- A pie chart displaying the percentage distribution of products across price ranges (Low, Medium, and High).
These visualizations should be included in a separate tab of the final spreadsheet.
Deliverables:
The final deliverable will be a Google Sheets or Excel file containing:
- The cleaned dataset
- The requested visualizations
- A brief summary explaining the cleaning process and highlighting any insights derived from the visualizations.
Dataset
Use the Dirty E-Commerce Data dataset from Kaggle, available here https://www.kaggle.com/datasets/oleksiimartusiuk/e-commerce-data-shein.