pairplot

The objective of the dataset is to diagnostically predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset

Seaborn Visualization on Titanic Dataset Visual exploration of different features on No. of people survived or otherwise Visualization using FacetGrid function, Lambda function and criterion function Visualization of subplots

Multiple-Linear-Regression-1. Consider only the below columns and prepare a prediction model for predicting Price of Toyota Corolla.

Assignment-05-Multiple-Linear-Regression-2. Prepare a prediction model for profit of 50_startups data. Do transformations for getting better predictions of profit and make a table containing R^2 value for each prepared model. R&D Spend -- Research and devolop spend in the past few years Administration -- spend on administration in the past few years Marketing Spend -- spend on Marketing in the past few years State -- states from which data is collected Profit -- profit of each state in the past few years.

Visualization using Matplotlib and Seaborn

A simple analysis of Zlatan Ibrahimović's club career.

Strip Plot, Grouping with Strip Plot, Swarm Plot, Box and Violin Plot, placing plots together, Combining the plots, Joint Plot, Density Plot, Pair Plot

Scatterplot matrices with gnuplot using gretl

simple linear regression assignment

Higher Diploma in Science in Computing (Data Analytics) - Programme Module: Programming and Scripting (COMP08049)

Ask a home buyer to describe their dream house, and they probably won't begin with the height of the basement ceiling or the proximity to an east-west railroad. But this playground competition's dataset proves that much more influences price negotiations than the number of bedrooms or a white-picket fence. With 79 explanatory variables describing (almost) every aspect of residential homes in Ames, Iowa, this competition challenges you to predict the final price of each home.

Imputation and Visualization of a dirty bank data with the help of NumPy, Pandas, Matplotlip and Seaborn libraries.

Perform exploratory data analysis to visualize the distribution of values in a dataset, analyze relationships using correlation, and locate and fix data problems including missing values.

1st Project for the Post Graduate Programme in Data Science and Business Analytics at the University of Texas at Austin - Exploratory Data Analysis

Correlation between 5 stock prices