Perfoming data analysis on different types wines collected from vivino.com

About the dataset: The data was collected by scraping using the popular web automation library in python called Selenium. It was collected from vivino.com. The number of wine information collected is 1200 consisting of 6 different types of wines namely: Red, Rose, Sparkly, Fortified, Dessert, and White. The wines collected include ratings on a scale of 5 The price for the wines collected is from 10 dollars up until 500 dollars The data collected will be cleaned, processed, and then used for analysis by answering the research questions below.

Research Questions:

How does the average rating of each wine type compare to its price? Which wine type has the highest average rating? What is the distribution of prices for each wine type in the dataset? Which country produces the most wine in the dataset? Which country produces the best wine based on the ratings? Does the year of production affect the Price of the Wine?

installing seaborn !pip install seaborn importing various libraries import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns import warnings

So we used the wine dataset scraped from vivino.com to answer some of the questions given in the description section above to make analysis which will help the company in its next proceedings.

./my_project argument1 argument2

Egbuna Chinedu Victor Murphy Ogbeide Orobosa

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