Title: Exploratory Analysis and Price Prediction on Avocado data

1. Project Motivation
2. Installation
3. Data
4. Implementation
5. Results

Project Motivation

This notebook explores the avocado sales data from 2015 to 2018. The aim of this project is to explore the historical data on avocado prices and sales volume in multiple US markets, examine and display the relationship between the features as well as predict the price of avocado over various timelines.

The analysis answered questions including:

a) The cities with the least most avocado sold b) Average avocado sales per year

Built models to predict avocado prices, using Linear Regression and Decision Tree Regressor.

Installation

Python V-3.

Python Libraries:

• Scikit Learn.
• Pandas.
• Numpy.
• Seaborn
• Matplotlib.

Data

This data was downloaded from the Kaggle

Implementation

Two regression models were run on the data, including Linear Regression and Decision Tree Regressor. A data ratio of 70:30 was used for both models and performance was reviewed using the mean squared error metric and r2_score for overall accuracy.

Result

The details and insights gotten from the results are detailed in the code.