A terminal spreadsheet multitool for discovering and arranging data

This project analyzes and visualizes the Used Car Prices from the Automobile dataset in order to predict the most probable car price

Advanced data wrangling for python

Understand the relationships between various features in relation with the sale price of a house using exploratory data analysis and statistical analysis. Applied ML algorithms such as Multiple Linear Regression, Ridge Regression and Lasso Regression in combination with cross validation. Performed parameter tuning, compared the test scores and suggested a best model to predict the final sale price of a house. Seaborn is used to plot graphs and scikit learn package is used for statistical analysis.

通过Python对OpenStreetMap的数据集进行整理和清洗。

DataTutor: Data Science Code Comprehension Tools.

Python Data Analytics, Machine Learning & Natural Language Processing

course website for data science tools 1

A collection of projects as part of the Python for Data Science program at GreyAtom EduTech Pvt Ltd

Research Lab Script in R

Udacity Data Analyst NanoDegree Data Wrangling course project

My collection of visualizing different datasets using (Matplotlib, Seaborn, and Folium) packages for Python

Web and Cloud Computing

This repository is a collection of all the solutions of tasks that were assigned to me during my Data Analytics Virtual Internship Experience Program at Quantium. 💻📚📊

This repository is demonstration of Pandas library of Python's super powers.

Why data analysis? , How to understand the problem, what to do for data analysis, and how clean the data for building Machine Learning models

Data Analysis On Demand course

This is to wrangle and analyze data from WeRateDogs Twitter archive.

This is an exercise on the use of python for data wrangling based on the book "Python for Data Analysis" by Wes McKinney

Aggregate data in R using simple SQL commands

Gather data from Twitter API and provide insights

This assignment is based on a dataset of credit card transactions that you can download from Link to download the dataset Each row in the dataset refers to one credit card purchase by a cardholder. Each cardholder belongs to an agency. Each transaction has information about the amount, date, merchant and merchant category, as well as a description of the expense.

Repository containing self built case studies and analysis leveraging most of the phases in the entire executable data science chain end to end, ranging from harvesting of resources to building cutting edge deep dive data models.