Animated D3 scatter plot extension for qlik sense.

Check it out here... http://nbviewer.jupyter.org/github/igerardoh/book-reader/blob/master/file_reader.ipynb

Interactive chart created with Javascript, Bootstrap 4 HTML and CSS, D3.js, and D3 Tooltip

A study to compare the performance of the company's drug of interest, Capomulin, versus the other treatment regimens. Generate all of the tables and figures needed for the technical report of the study and a top-level summary of the study results.

This is for reference purpose. Plotly helps to create interactive charts. This package mainly helps for data scientists for creative productive graphs, Mainly in presentation time it is useful

Interactive data visualization using D3.js to show some state-level data about three risk factors (obesity, smoking and lack of healthcare) plotted against three perhaps underlying factors (income, poverty rate and age) based on 2014 U.S. Census data. Find it here: https://sheetalbongale.github.io/D3-Data-Journalism/

Various visualizations of the iris dataset

Using data from US Census Bureau, then using D3 to visualize in a way to be useful to the public.

This project is in two parts. First, WeatherPy visualizes the weather of 500+ cities across the world of varying distances from the equator, using Python script, CityPy, and OpenWeatherMap APIs. The second part, VacationPy, uses Jupiter-Gmaps and the Google Places API to create a heatmap and filter down cities.

A project that I created for freeCodeCamp that displays a scatterplot using D3.js.

Chart Me is a visualization software that helps to represent data using different visualization tools to help the human mind comprehend the information easily.

Basic scatter plots with overlayed linear fit and ideal trend lines for visualizing estimator performance

A Scala.js library for Command Line Interface Visualizations.

Notebooks used to solve exercises brought by professor Gabriela Uhrigshardt, who teaches Programming Techniques II at Let's Code Data Science 815

Python matplotlib, seaborn and plotly plots cheat sheet

Multiple Linear Regression Analysis of Mileage Actual observations vs Predicted Observation

Conducting Exploratory Data Analysis of White Wine Quality Dataset

HBFC Bank's project analyzes 5000 customer records, aiming to convert depositors into personal loan customers. Advanced skills in statistical analysis and tools like Excel uncover key insights, including a 9.6% personal loan uptake. Diverse demographics and strategic findings inform recommendations for future marketing campaigns.