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Exploratory Data Analysis on CardioGoodFitness Treadmills..!

Objective:

- What is EDA?
- Descriptive Analysis - Five point summary
- Visualization - Overview of Matlplot, Seaborn and plotly
- Univariate Analysis - Histogram(contineous), Boxplot(contineous), Countplot(Categorical)
- Bivariate Analysis - Scatterplot(contineous), Barplot(Categorical), Strip-plpot(categorical-contineous)
- Multivariate Analysis - Introducing Hue, Pairplot, Heatmap.

What is EDA?

  • used to analyse a dataset and understand its key characteristics.
  • Understand the pattern in the data and form hypothesis.
  • Identify outliers, Missing data, Incorrect data.

Cardio Good Fitness Case Study - Descriptive Statistics

The market research team at Adright is assigned the task to identify the profile of the typical customer for each treadmill product offered by CarfioGood Fitness. The market research team decides to investigate whether there are differences across the product lines with respect to customer characteristics. The team decides to coolect data on individuals who purchased a treadmill at a CardioGoodFitness retail store during the prior three months. The data are stored in the CardioGoodFItness.csv file.

The team identifies the following customer variables to study:

  • product purchased, TM195, TM498, or TM798;
  • gender;
  • age, in years;
  • education, in years;
  • relationship status, single or partnered;
  • annual household income ;
  • average number of times the customer plans to use the treadmill each week;
  • average number of miles the customer expects to walk/run each week;
  • and self-rated fitness on an 1-to-5 scale, where 1 is poor shape and 5 is excellent shape.
# Import required libraries.
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sb
# Load data into the dataframe.
customer_data = pd.read_csv("CardioGoodFitness.csv")