Automate the process of visualization.

Udacity Data Analyst Nanodegree - Project III

Samples for Azure Databricks Orientation

This repository contains project materials for the Spring 2024 STAT 208 class, specifically for Team 8. All materials are the property of Team 8, University of California, Riverside, A. Gary Anderson School of Management. Thank you for viewing our repository.

Udacity Data Analyst Nanodegree - Project V

This repo consist of projects on: Data Wrangling, Data Visualization and Machine Learning

Data Analyst Nanodegree - Data Visualization project

Data Analyst Nanodegree - Data Visualization

Statistical exploration, analysis, and visualization of 2012 PISA international education survey

Predicting Sales and Demand of Walmart Data

we aim to predict trends in the Canadian market basket using sentiment analysis techniques. Sentiment analysis involves analyzing text data to determine the sentiment expressed, whether positive, negative, or neutral.

Personal financial record keeping and analysis app made in python with statistics and visual summaries.

HHA507 / Data Science / Assignment 3 / Exploratory Data Analysis

A/B tests are very commonly performed by data analysts and data scientists. It is important that you get some practice working with the difficulties of these.

Perform data analysis of service request (311) calls from New York City. I have utilized data wrangling techniques to understand the pattern in the data and visualize the major types of complaints.

This is a wine dataset containing 1599 rows and 12 columns with factors like alcohol, color, PH, residual sugar, sulfur-dioxide was used to determine the quality of wine varying with color.

Udacity Data Analyst Nanodegree Project II

This data set contains 113,937 loans with 81 variables on each loan, including loan amount, borrower rate (or interest rate), current loan status, borrower income, and many others. The analysis explore the factors and patterns in the creditworthiness of borrowers and the borrowing trend of Prosper Loan Business.

This data contains 113,937 loans with 81 variables on each loan, I have provided 30+ visualizations of a selected few variable features that best explain and give insights to how loans are measured and to what factors that determine a loan interest

Performed an exploratory data analysis using python and presented explanatory plots that convey insights of data.