An interactive scatterplot visualization.
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Updated
Jan 27, 2017 - Processing
An interactive scatterplot visualization.
Single Cell Expression Atlas t-SNE plot
Estimating tip% for the noble souls that get pizza for you!
In this project, the task is to build a sentiment classifier, which will detect how positive or negative each tweet is. We will create a csv file, which contains columns for the Number of Retweets, Number of Replies, Positive Score (which is how many happy words are in the tweet), Negative Score (which is how many angry words are in the tweet), …
D3.js-based Interactive Visualization Comparing 2014 ACS 1-year Estimates (US Census Bureau & CDC) of Obesity, Smoking, and Lack of Healthcare Rates in Each State to Poverty Rates, Median Age, and Median Household Income
Investigating a 2014 demographics dataset to create interactive visualizations
This is a collection of Python scripts that I have written while learning how to code. These scripts are used for graphing in Python, using libraries such as Seaborn, Matplotlib, and Numpy.
This repository provides the code to analyze the enrollment funnel at geographic, First Source Code, high schools, and academic level. It captures data for enrollments in Fall 2017, Fall 2018, and Fall 2019 Freshmen from the US for a private university.
[Personal Project] - Project:- custom-charts-clone, Built with love
Analyzed cryptocurrencies data using unsupervised machine learning model, PCA, K-means and visualized with 3D and scatter plot.
This python code shows howw regression is handled in case of categorical variables using duumies. It calculates the multiple regression code and shows the regression table. It also performs the residual analysis.
Plotting of the Confidence interval and Prediction interval for a Linear Regression model.
The first project from a Data Scientist with Python track by DataCamp
Data visualization - qualitative & quantitative data (Airbnb listings for NY)
In this project, I created a Scatter Plot Graph using D3 with a dataset provided by FreeCodeCamp.
This project focusing on statistical analysis to understand and prepare data for potential machine learning applications. The dataset house_price.csv includes property prices in Bangalore. The analysis aims to perform exploratory data analysis (EDA), detect and handle outliers, check data distribution and normality, and analyze correlations.
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
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