https://github.com/kingabzpro/julia-dataframes

I will display how it’s easy to use DataFrame.jl, just like pandas in python. I will use simple examples and a few lines of code to demonstrate data manipulation and data visualization. We will be using the famous Heart Disease UCI | Kaggle Dataset which has a binary classification of Heart Disease based on multiple factors.
https://github.com/kingabzpro/julia-dataframes

data-science dataframe heart julia julia-language machine-learning visualization

Last synced: 7 months ago
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I will display how it’s easy to use DataFrame.jl, just like pandas in python. I will use simple examples and a few lines of code to demonstrate data manipulation and data visualization. We will be using the famous Heart Disease UCI | Kaggle Dataset which has a binary classification of Heart Disease based on multiple factors.

• Host: GitHub
• URL: https://github.com/kingabzpro/julia-dataframes
• Owner: kingabzpro
• License: apache-2.0
• Created: 2021-08-26T15:29:31.000Z (about 4 years ago)
• Default Branch: master
• Last Pushed: 2021-08-26T15:35:06.000Z (about 4 years ago)
• Last Synced: 2025-01-17T22:12:03.995Z (9 months ago)
• Topics: data-science, dataframe, heart, julia, julia-language, machine-learning, visualization
• Language: Jupyter Notebook
• Homepage: https://deepnote.com/project/Julia-Dataframes-VcKJvz5LT6KEPsX4IKb7ug
• Size: 1.84 MB
• Stars: 1
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Introduction

Julia is a high-level and general-purpose language that can be used to write code that is fast to execute and easy to implement for scientific calculations. The language is designed to keep all the needs of scientific researchers and data scientists to optimize the experimentation and design implementation. [Julia (programming language)](https://en.wikipedia.org/wiki/Julia_(programming_language)).

> *“Julia was built for scientific computing, machine learning, data mining, large-scale linear algebra, distributed and parallel computing”-developers behind* [*the Julia language*](https://julialang.org/)*.*

![](https://editor.analyticsvidhya.com/uploads/34988Julia-Banner.jpg)

Image by Author | Elements by [Vector_Corp](https://www.freepik.com/free-vector/abstract-digital-wave-particles-background_15681021.htm#page=1&query=data%20science&position=6#position=6&page=1&query=data%20science)

## Overview

In this article, I will be discussing the advantages of Julia language and I will display how it’s easy to use DataFrame.jl, just like pandas in python. I will use simple examples and a few lines of code to demonstrate data manipulation and data visualization. We will be using the famous [Heart Disease UCI | Kaggle](https://www.kaggle.com/ronitf/heart-disease-uci) Dataset which has a binary classification of Heart Disease based on multiple factors.

[![View in Deepnote](https://deepnote.com/static/buttons/view-in-deepnote.svg)](https://deepnote.com/@abid/Julia-Dataframes-VcKJvz5LT6KEPsX4IKb7ug)