EBolinVA / Netflix_Analysis

Data clean-up, building tables, creating queries

Netflix_Analysis

Data clean-up, building tables, creating queries

Overview

Exploring data cleaning and merging with a Kaggle dataset of Netflix Movies and TV Shows. I am practicing the Extract, Transform, Load (ETL) process of cleaning data.

Resources

• Netflix Movies and TV Shows, 6 .csv files downloaded from Kaggle.
• GitHub
• Excel
• Pandas
• Jupyter Notebook
• QuickDBD
• SQL
• pgAdmin 4
• Python 3.7.13

Process

• Create a GitHub repository and clone to local computer
• Download Kaggle .csv files into local folder
• Using Excel, open and inspect each file
• Open .ipynb Jupyter Notebook to create DataFrames using the .csv data
• Check datatypes, Null values, and reformat columns as needed
• Drop unnecessary columns
• Create a movies_df ...
• Open new canvas on QuickDBD and create relational diagram (ERD) of files
• Write SQL code to create tables and build Netflix database on pgAdmin
• Import .csv files into new tables on pgAdmin