This Jupyter Notebook contains a comprehensive descriptive statistical analysis of a dataset. Descriptive statistics are an integral part of the Exploratory Data Analysis (EDA) process, helping data analysts to compare variables, understand data distribution, identify outliers, and perform calculations for making predictions.
- Clone or download this repository to your local machine.
- Ensure you have Jupyter Notebook installed. If not, you can install it using Anaconda or pip.
- Open the Jupyter Notebook file (
Descriptive_Statistical_Analysis.ipynb) in your Jupyter Notebook environment. - Execute the code cells step by step to replicate the analysis or modify it for your specific dataset.
- import dataset
Aknowledgemen: Data provided by Google Learning under fair use.
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy import stats
import statsmodels.api as sm