Exploring Descriptive Statistics Using Pandas and Seaborn. Quantitative approach and Visual approach
Descriptive statistics include those that summarize the central tendency, dispersion, and shape of a dataset’s distribution.
Imported all the libraries needed for statistical plots and created a dataframe from the dataset given in
This dataset contains Height, Weight, Age, BMI, and Gender columns. Let’s calculate descriptive statistics for this dataset.
The code used in this project is available as a Jupyter Notebook on GitHub.
import numpy as np import pandas as pd import matplotlib.pyplot as plt % matplotlib inline df=pd.read_csv("bmi.csv") df
Measure of central tendency is used to describe the middle/center value of the data.
Mean, Median, Mode are measures of central tendency.
average valueof the dataset.
Formula to calculate mean
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