Advanced Data Storage and Data Retrieval with `Jupyter Notebook`, `SQLite` and `SQLAlchemy`

Climate Analysis of Hawaii Temperature and Precipitation. Exploration in Jupyter Notebook, and a Flask-API.

Using Python in Jupyter Notebook to recreate queries for imaginary stakeholders. Demonstrates connecting to MySQL, exporting tables to Excel, merging data, cleaning datasets, and counting orders. Visualizations include bar plots, revenue plots, pie charts, scatter charts, and map manipulation with geopandas. Dataset from MySQL.

Data Scientist/ Engineer spent majority of their time to clean-up data as it's not always "clean" due to many reasons, such as inconsistent user inputs, defective sensors, typos, special characters, etc. In this project, 2 Jupyter Notebooks with Python libraries: Pandas, SQLAlchemy & Psycopg were used to clean and load data into SQLite Database.

Working on small dataset which has 26k records.

DA Project 3: Personal Medical Insurance Analysis using SQL Magic on Jupyter notebook.

A climate analysis conducted to assist with planning a trip to Honolulu, HI. This analysis uses Python, SQLAlchemy, Flask and Pandas in Jupyter notebook to analyze and share the climate data from a sqlite database.