https://github.com/shanukatiyar111/project3
PYTHON + SQL PROJECT- ANALYSIS OF ORDER DATA USING JUPYTER NOTEBOOK AND SSMS
https://github.com/shanukatiyar111/project3
jupyter kaggle kaggle-dataset pandas python sql ssms
Last synced: 4 months ago
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PYTHON + SQL PROJECT- ANALYSIS OF ORDER DATA USING JUPYTER NOTEBOOK AND SSMS
- Host: GitHub
- URL: https://github.com/shanukatiyar111/project3
- Owner: shanukatiyar111
- Created: 2024-07-09T11:40:52.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-07-12T13:54:27.000Z (almost 2 years ago)
- Last Synced: 2025-03-01T14:41:42.054Z (over 1 year ago)
- Topics: jupyter, kaggle, kaggle-dataset, pandas, python, sql, ssms
- Language: Jupyter Notebook
- Homepage:
- Size: 10.7 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Project3
1. About Dataset-
This dataset contains the 2022 and 2023 global mart sales datasets.
2. Used Python version 3.10.10 and Jupyter version 7.2.1 for this project.
3. Used Kaggle API to Download Data from Kaggle.
4. Used Jupyter Notebook to read data into Pandas dataframe, and transform data using Python.
5. Transformation includes-
renaming column ,
changing data type,
adding calculated columns
dropping unnecessary columns
6. Used SQLalchemy to load data into df_orders table into prebuilt Database project4python_sql.
5. Used window authentication to load data into SSMS and ODBC driver for connection.
6. Analysis of Data in SSMS includes -
find the top 10 highest revenue-generating product
find the top 5 products in each region by highest revenue-generating
find month-over-month growth for years 2022 and 2023
for each category which month has the highest sales
which subcategory has the highest YoY growth