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This small project will demonstrate the data analysis of real estate data set stored into Mysql database.

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data_analysis_using_database

This project will demonstrate the data analysis of real estate data set stored into Mysql database.

Objective:

  • Create engine to establish connection with mysql database using sqlalchemy and pymysql.
  • Generate dataframes using pandas.
  • Display sections of dataframe, e.g Location and Price.
  • Display number of properties at each location.

Steps To Run:

For this demonstration, I am using the Jupyter Notebook, open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text.

Step 1:

Establish a connection with the mysql database using sqlalchemy's create_engine. Use your own credentials.

Database.

Step 2:

Create a virtual enviroment and install dependencies by running requirements.txt.

$ pip install virtualenv env

$ source env/bin/activate

$ pip install -r requirements.txt

Step 3:

Run the script.

$ jupyter notebook

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This small project will demonstrate the data analysis of real estate data set stored into Mysql database.

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