pairplot
There are 0 repository under pairplot topic.
labrijisaad / Car-Price-Prediction
Car Price Prediction
Language:Jupyter Notebook 8lovpatel93 / PIMA_Indian_Diabetes_DataSet
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
Language:Jupyter Notebook 3vaitybharati / Assignment-05-Multiple-Linear-Regression-1
Multiple-Linear-Regression-1. Consider only the below columns and prepare a prediction model for predicting Price of Toyota Corolla.
Language:Jupyter Notebook 3Assignment-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.
Language:Jupyter Notebook 3jayeshbhandarkar / Iris-Dataset-Prediction-using-Unsupervised-ML
Iris-Dataset-Prediction-using-Unsupervised-ML This project involves the analysis of the Iris dataset using Python. It includes code to determine the optimum number of clusters using the K-means clustering algorithm, visualizations such as scatter plot, pair plots and hist plots, and other insights into the dataset.
Language:Jupyter Notebook 2- Project_Zlatan
siddarthkrishna10 / Project_Zlatan
A simple analysis of Zlatan Ibrahimović's club career.
Language:Python 2 - Language:Jupyter Notebook 1
c-susan / datasci_3b_visualization
HHA507 / Data Science / Assignment 3b / Data Visualization with Seaborn and Plotly
Language:Jupyter Notebook 1d4rthm4ul / Data-imputation-and-visualization-intermediate
Imputation and Visualization of a dirty bank data with the help of NumPy, Pandas, Matplotlip and Seaborn libraries.
Language:Jupyter Notebook 1ttariqaziz / python_plots_cheat_sheet
Python matplotlib, seaborn and plotly plots cheat sheet
Language:Jupyter Notebook 1Strip Plot, Grouping with Strip Plot, Swarm Plot, Box and Violin Plot, placing plots together, Combining the plots, Joint Plot, Density Plot, Pair Plot
Language:Jupyter Notebook 1Seaborn 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
Language:Jupyter Notebook 1Visualization using Matplotlib and Seaborn
Language:Jupyter Notebook 1andrewsunsanto / DSBAProject1
1st Project for the Post Graduate Programme in Data Science and Business Analytics at the University of Texas at Austin - Exploratory Data Analysis
Language:Jupyter Notebook 0kristiyamashita / MIT-ADSP---Diabetes-Analysis
This project involves analyzing different aspects of Diabetes in the Pima Indians tribe by doing Exploratory Data Analysis.
Language:Jupyter Notebook 0Mahamad-Jameer-Makandar / Data-Visualization-on-Honey-Production-dataset-using-seaborn-and-matplotlib-libraries
Explore honey production dynamics (1998-2012) in the U.S. amid declining bee populations using Python's seaborn and matplotlib. Visualize key attributes like colonies, yield, production, price, and stocks to draw insights into the impact on American honey agriculture.
Language:Jupyter Notebook 0Munster2020 / HDIP_CSDA_PROJECT
Higher Diploma in Science in Computing (Data Analytics) - Programme Module: Programming and Scripting (COMP08049)
Language:Python 0muskans12 / Seaborn-Visualization
Seaborn is a Python data visualization library based on matplotlib . It provides a high-level interface for drawing attractive and informative statistical graphics.
Language:Jupyter Notebook 0nikita-bachhas / A-Technical-Review-of-Clustering
This project analyses different clustering methods over three different datasets
Language:Jupyter Notebook 0PatilSukanya / Assignment-05.-Multiple-Linear-Regression-Q1
Used libraries and functions as follows:
Language:Jupyter Notebook 0Used libraries and functions as follows:
Language:Jupyter Notebook 0phancykemunto / Exploratory-Data-Analysis-EDA-
Exploratory data analysis is an approach to analyzing data sets to summarize their main characteristics, often using statistical graphics and other data visualization methods. In this exercise, iris data was visualized using box plots, pairplot, subplot, and scatter plots for better comprehension of the dataset.
Language:Python 0RakshaSaxena / Python-Data-Visualization
Python- Data Visualization
Language:Jupyter Notebook 0shwetapardhi / Assignment-05-Multiple-Linear-Regression-1
Multiple-Linear-Regression-1. Consider only the below columns and prepare a prediction model for predicting Price of Toyota Corolla.p
Language:Jupyter Notebook 0Sumanmhalsank02 / Correlation-in-Stock-Market
Correlation between 5 stock prices
Language:Python 0ashishyadav24092000 / KNN-Algorithm
Performing the K-Nearest-Neighbor Algorithm.
Here we will be taking two dataset from the seaborn library itself i.e. the tip and iris dataset to perform continuous and categorical datapoint visualisations.
Language:Jupyter Notebook- Language:Gnuplot
Develop-Packt / Exploring-and-Visualizing-Data-with-Python
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.
Language:Jupyter Notebookelsahsu / store_features_effect_on_sales
finding correlation between store features and sales
Language:Jupyter NotebookKr1shna304 / GRIP_Prediction_Using_Unupervised_ML
This repository contains the file for the task that was done as part of my internship in The Sparks Foundation with specialization - Data Science & Business Analytics.
Language:Jupyter NotebookUsed libraries and functions as follows:
Language:Jupyter NotebookPrem-98 / Simple-Linear-Regression
simple linear regression assignment
Language:Jupyter NotebookPriyankaSett / obesity_multiclassification
Given a person's data, the task is to predict that in which category the person's weight should fit in. This is a Multiclassification project.
Language:Jupyter NotebookSaurav0129 / Steel-Industry-Energy-Consumption-Prediction
The dataset used for this project is taken from the official UCI Machine Learning Repository.
Language:Jupyter Notebookvpfahad / Housing-price-Advanced-regressionn
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.
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