PyVizNotebook is a collection of Matplotlib visualizations demonstrating a wide range of plot types and techniques for data visualization. Whether you're a beginner looking to learn or an experienced developer seeking inspiration, this repository offers a diverse set of examples to explore.

Data Analysis of countries GDP using Jupyter(Python) Notebook in VS Code

This repository contains a Jupyter Notebook exploring the adult income dataset. The notebook performs Exploratory Data Analysis (EDA), including visualizations with charts and graphs. Additionally, it implements various classification models to predict income and analyzes their accuracy.

This GitHub repository hosts a comprehensive analysis notebook for Upstox, a popular online stock trading platform, with a powerful Medallion architecture. The analysis is designed to provide insights into your trading strategies, portfolio performance, and market trends.

This repository hosts a machine learning-based mushroom identification system, utilizing scikit-learn models in a Jupyter notebook. The project analyzes and processes a Kaggle dataset to train a model that classifies mushrooms as edible or poisonous, providing a reliable tool for mushroom enthusiasts and foragers.

Salifort motors (a fictional company) has high employee turnover recently. With the given data, we are about to explore the reasons that might have caused the employee turnover and suggest ways to improve employee satisfaction and retain them long term. Jupyter notebooks done for Google Advanced Data Analytics Course from coursera.

Pandas Mastry Notebook is a repository dedicated to exploring the capabilities of the pandas library for data manipulation, analysis, and visualization in Python. Dive into a variety of data operations, analytical techniques, and visualization methods to uncover insights from your datasets.

Inside this repository, you'll discover a comprehensive notebook dedicated to showcasing various NumPy array methods and operations. From basic array manipulation to advanced techniques, I've compiled a collection of examples and explanations to help both beginners and seasoned Python developers deepen their understanding of NumPy.

This project analyzes Schools data using Pandas/ Jupyter Notebook.

This repository consists of jupyter notebook file which explains about Numpy .

Documentação de estudo dos notebooks iPython do curso de Ciência de Dados da EBAC.

pada 2 notebook berikut akan ditampilkan data persebaran desa maju dan mandiri di kalimantan timur. Dimana data-data pada tabel yang diolah pada notebook didapatkan dengan melakukan webscraping di laman website DPMPD Provinsi Kalimantan TImur

A notebook on Employee Survey using statistical techniques and visualizations to uncover trends and insights int

If you want to learn how to analyze a sports event like the T20 World Cup, this notebook is for you. This notebook will take you through the task of T20 World Cup 2022 analysis using Python.

This is a data analysis poject with a dataset of 18 columns and 232725 rows analyzed using Numpy and Pandas and Visualized using Matplotlib and Seaborn using Jupyter Notebook

I apply EDA and some machine learning algorithms to penguin size in antartica dataset. I start with EDA first and then I will apply Machine Learning algorithm in different notebook

In this notebook the User Review of the movie KGF Chapter-2 in the IMDb website is used to train the classification model for classifying whether the review is negative ,neutral or positive.

Follow the Jupyter Notebook to learn the Basics of R language for Data Analytics. Learn stuff like Data Manipulation, Data Cleaning, Binding of Multiple csvs, Creating Visualizations using GGPlot2 and performing One-Tailed/Two-Tailed TTests.

The title of the project is “Predict Blood Donations”. It uses python as language, data science, and machine learning as the field of operation, TPOT library for model selection, logistic regression for model building, and jupyter notebook as the code editor.

For this project, you will be working to understand the results of an A/B test run by an e-commerce website. Your goal is to work through this notebook to help the company understand if they should implement the new page, keep the old page, or perhaps run the experiment longer to make their decision.