Why TidyConsultant?
The TidyConsultant packages are designed in mind for consultants who frequently work with heterogenous small-medium sized tabular data sets and interact with the messy world of MS office. This package builds on prior art from the tidyverse and officeverse and intends to provide useful functions for data scientists of any industry.
Marie Kondo, reknowned tidier
Packages Overview
validata: understand the properties of a data frame. Which columns make the data frame distinct? Do 2 columns have a 1-1 mapping or 1-many mapping between values? What is overlap of unique values between 2 columns? Get quick summary of # unique, missing values, and a variety of properties of numeric columns.
framecleaner: simplifies common dplyr actions directly on a dataframe: automated type coercion, dealing with NAs, padding characters, creating dummies, importing files
tidybins: unified interface to creating and summarizing bins directly in a data frame
presenter: MS excel and powerpoint compatible output, with automated naming and formatting
autostats: simplified formula manipulation and modeling. Designed for quick exploratory analysis and visualization.
Installation and Loading
Loading TidyConsultant automatically installs and attaches the packages in the the TC universe.
You can install and load the released version of TidyConsultant along with tidyverse using the following code
if (!require("pacman")) install.packages("pacman"); library(pacman)
p_load(tidyverse, TidyConsultant)This is a great template to start your R script. Put any additional packages you may need inside the p_load command.
Other good R packages for consulting
outlier detection with random forests robust version of OutlierTree