Analyzing the historical cryptocurrency trading dataset, to portrait its dynamic landscape and dig into features of crypt currencies to figure out if any patterns in their price movement.
In this online program, I completed similar tasks that KPMG Graduates do in the company. I learned what it is like working at one of the world’s best data analytics team, and built skills required to excel as a analytics consultant.
A Python data manipulation and analysis project that examines and visualizes the popularity of widely used data science tools R and Pandas across 3 Stack Exchange subcommunities (Stack Overflow, Cross Validated, Data Science) through the use of the Stack Exchange API and multiple Python libraries such as Pandas, JSON, Requests, and Matplotlib.
In this project, I used a combination of data manipulation and visualization to explore television data. I also looked at Super Bowl Data, generating insights into game outcomes, viewership, and even halftime shows.
Manipulating Data excel data in power query so that it works in our JLL Corrigo System and is built automatically. (Names and amounts have been changed for privacy)
Practical Computing for Data Analytics Homework 2: This project was based on census data regarding Michigan socio-economic data. Visualizations were made to bring out paterns in the data and draw conclusions. ggplot and dplyer were the primary packages used in this project for data manipulation and visualizations. A primary theme in this assignment was the differences between the Upper Peninsula and Lower Peninsula. There were vast differences in populations and the type of employment that one would typically find in each geographic region.
An important part of business is planning for the future and ensuring that the business survives changing market conditions. Some businesses do this remarkably well and last for hundreds of years. In this project, I explored data from BusinessFinancing.co.uk on the world's oldest businesses: when were they founded, and which industries do they belong to? Like many business problems, the data we'll explore is contained in several different datasets. In order to understand the world's oldest businesses, we will first need to use joining techniques to merge our data. From there, we can use manipulation tools such as grouping and filtering to answer questions about these historic businesses.
Had to develop a customer segmentation to define marketing strategy. The dataset summarized the usage behavior of about 9000 active credit card holders during the last 6 months. The file is at a customer level with 18 behavioral metrics..
In this project, we are going to analyze international debt data collected by The World Bank. The dataset contains information about the amount of debt (in USD) owed by developing countries across several categories.
Analyzing various apps found on the Google Play Store with the help of different python libraries. The dataset is chosen from Kaggle. It is the web scraped data of 10k Play Store apps for analyzing the Android market. It consists of in total of 10841 rows and 13 columns.
In 1847, the Hungarian physician Ignaz Semmelweis made a breakthough discovery: he discovers handwashing. Contaminated hands was a major cause of childbed fever and by enforcing handwashing at his hospital he saved hundreds of lives.
Everyone is welcome to add more algorithms to this project. This repo is new so we need contributions from all.