The World Weather Analysis repo utilizes Python and Jupyter Notebook in conjunction with decision and repetition statements, data structures, Pandas, Matplotlib, NumPy, CitiPy, and SciPy statistics to retrieve and use data from OpenWeatherMap and Google Map API. The APIs are used to "get" requests from a server, retrieve and store values from a …

Exploration of descriptive and inferential statistical methods using Python and Jupyter Notebook.

In this project, we wanted to determine how college football has changed over time and focus on if the value of defense is diminishing in games. If so, what factors are possibly making this happen and what can we see happening for the future.

Practice exercise from Georgia Tech Data Analytics Boot Camp. Analysis, graphs & maps based on random latitudes/longitudes from Python Citipy library and Open Weather Map API.

Data Science projects for learning : Machine learning, Data analysis etc.

Used MatplotLib to compare the performance of a drug of interest versus other treatment regimens.

Linear Regression Model for Car Price Prediction based on one or more features.

Statistics with Python - ANOVA - T-test

Using matplotlib to create graphs to better visualize data from a fictional medical study on mice

We performed some statistical analysis of Iris Dataset.

Gather data from APIs then create plots using matplotlib to show the fact that temperatures increase as the get closer to the equator

API and Weather Data visualization: Data Visualization based on weather data, vacation itinerary and vacation search

data-analysis labs. 50/50 made with Oleh Tonkoshkur

Website using Bootstrap to demonstrate how Mercedes has dominated the hybrid era in Formula One. Visualizations and data exploration displayed in a Jupyter Notebook.

The objective is to build a ML-based solution (linear regression model) to develop a dynamic pricing strategy for used and refurbished smartphones, identifying factors that significantly influence it.

The aim is to develop an ML- based predictive classification model (logistic regression & decision trees) to predict which hotel booking is likely to be canceled. This is done by analysing different attributes of customer's booking details. Being able to predict accurately in advance if a booking is likely to be canceled will help formulate prof…

Statistical Analsis of Boston Housing dataset . Part of Statistics for Data Science with Python - IBM @coursera

Here i have taken an example of a school called as ABN Public School.In this we performed chi square test of independence to determine whether the variables 'gender' and 'student motivation' are independent of each other or not.

In this we have taken a sample data to check if that data follows normal distribution or not. A hypothesis test is performed to check this using the chi-square test pf goodness of fit.