https://github.com/nialled69/sugarcane-production-project

Exploratory Data Analysis (Univariate and Bivariate analysis) on World-wide Sugarcane Production dataset.
https://github.com/nialled69/sugarcane-production-project

csv data-visualization dataanalysis-projects eda jupyter-notebook matplotlib-pyplot pandas-dataframe python3 seaborn

Last synced: 7 days ago
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Exploratory Data Analysis (Univariate and Bivariate analysis) on World-wide Sugarcane Production dataset.

• Host: GitHub
• URL: https://github.com/nialled69/sugarcane-production-project
• Owner: Nialled69
• Created: 2024-05-16T12:49:09.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2024-05-19T18:02:38.000Z (6 months ago)
• Last Synced: 2024-05-19T19:23:22.395Z (6 months ago)
• Topics: csv, data-visualization, dataanalysis-projects, eda, jupyter-notebook, matplotlib-pyplot, pandas-dataframe, python3, seaborn
• Language: Jupyter Notebook
• Homepage:
• Size: 604 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Sugarcane-Production-Project - An Exploratory Data-Analysis project

A step-by-step Data Analysis on the World-wide Sugarcane production dataset (Dataset available in the Repository)

## How to initialise the project ? 🌆

- Download Anaconda Navigator from [here](https://www.anaconda.com/download/success)

- Install Anaconda and run `Jupyter Notebook` from the conda GUI.

- Clone this repository by running the below line

  

```cmd

git clone https://github.com/Nialled69/Sugarcane-Production-Project.git

```

## Project Features

- Data is cleaned first thouroughly and the cleaned data is saved

- Univariate and Bivariate Analysis are then done on the cleaned dataset

- Data Visualisation is done

You can explore all of this once you clone the repo and initiate the project

*Thank You for reading. Hope you have a great day !!*