/EDA-on-California-Housing-Dataset

Performing Data cleaning,Exploratory Data Analysis,used visualization libraries to understand data.

Primary LanguageJupyter Notebook

EDA on California Housing Dataset:

  • This project involves an Exploratory Data Analysis (EDA) on the California Housing Dataset, which contains data from the state's housing board.
  • The primary objective is to analyze the dataset based on location, income, house prices, and area (in square yards). The process includes data cleaning using NumPy to handle inconsistencies, followed by data manipulation and preprocessing using Pandas.
  • Null values were addressed appropriately to ensure data integrity. Visualization techniques were employed using Matplotlib and Seaborn to draw comparisons between income levels and house prices, providing deeper insights into housing trends across different regions.
  • some potential insights are higher prices of houses near oceans and inland. The Price increases as number of bedrooms increases. Only 33% of the houses are occupied in the countryside.