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Base Layer of R Scripts for Data Analysis and Automation

This repository contains a collection of R scripts that serve as a base layer for various data analysis, automation, and utility tasks. Each script is designed to be easily adaptable, allowing you to modify and build upon them to suit your specific needs.

Table of Contents

Automation Reports
Data Import
Data Manipulation
Data Visualisation
Geospatial Analysis
Statistical Analysis
Text Mining
Time Series
Utility
Web Scraping

Data Import

Link to Scripts

  • Description: This section contains scripts for importing data from various formats such as CSV, Excel, JSON, and databases. The scripts utilize functions like read.csv(), readxl::read_excel(), jsonlite::fromJSON(), and DBI::dbReadTable().
  • Usage: Use these scripts to import data from different sources into R for analysis.

Data Manipulation

Link to Scripts

  • Description: This section provides scripts for data manipulation tasks, such as reshaping data, summarizing, filtering, and joining datasets using packages like dplyr, tidyr, and data.table.
  • Usage: Adapt these scripts to clean, transform, and prepare data for analysis.

Data Visualisation

Link to Scripts

  • Description: Contains scripts for creating data visualizations using ggplot2 and tmap. Includes basic plots, custom themes, faceting, and interactive plots.
  • Usage: Use these scripts to create various types of visualizations, such as scatter plots, bar charts, line plots, and interactive maps.

Geospatial Analysis

Link to Scripts

  • Description: This section includes scripts for handling spatial data using packages like sf and sp. It covers reading and writing shapefiles, spatial joins, and mapping.
  • Usage: Employ these scripts to perform geospatial analysis, create maps, and handle spatial datasets.

Statistical Analysis

Link to Scripts

  • Description: Provides scripts for performing various statistical analyses, including hypothesis testing, regression models, and model diagnostics using packages like stats, car, and broom.
  • Usage: Utilize these scripts for inferential statistics and predictive modeling.

Text Mining

Link to Scripts

  • Description: Scripts for text mining and natural language processing (NLP) tasks, such as text preprocessing, tokenization, sentiment analysis, and topic modeling using tm, tidytext, and syuzhet.
  • Usage: Use these scripts to analyze textual data, perform sentiment analysis, and build text-based models.

Time Series

Link to Scripts

  • Description: This section covers scripts for time series analysis, including decomposition, forecasting with ARIMA, and exponential smoothing models using packages like forecast and xts.
  • Usage: Apply these scripts to analyze and forecast time series data for various applications.

Utility

Link to Scripts

  • Description: Contains utility scripts for repetitive tasks such as file management, custom functions, logging, error handling, and automation.
  • Usage: Adapt these scripts for file handling, error handling, logging, and other utility functions to improve workflow efficiency.

Web Scraping

Link to Scripts

  • Description: This section includes scripts for web scraping using the rvest package. Covers extracting data from websites, parsing HTML content, and handling JSON from APIs.
  • Usage: Use these scripts to extract data from websites and interact with web APIs.

Getting Started

Each script is designed to be a starting point for specific data tasks. Feel free to adapt and extend these scripts to fit your unique requirements. Make sure to review the dependencies for each script and install the necessary packages before running them.

Contributing

If you have additional scripts or improvements to share, please feel free to submit a pull request. Contributions are always welcome!

License

This repository is licensed under the MIT License. See the LICENSE file for more details.

Contact

For any questions or feedback, please contact us at [[email protected]].