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relper's Introduction

Introduction

Welcome to relper, an R package designed to make data preparation, cleaning, and visualization a breeze.

Created by a senior statistician, relper is a collection of functions that have been refined over the years to provide a comprehensive set of tools for data cleaning and visualization.

With relper, you can easily transform and format your data, compute important metrics, check conditions, and even use lovely and varied color palettes. Some of the key features of relper include:

  • Data transformation and formatting: offers a variety of functions to help you format your data.

  • Metrics: provides functions to compute important metrics, such as the coefficient of variation.

  • Condition checking: allows you to check conditions, such as determining if a number is even or odd.

  • Color palettes: includes beautiful and varied color palettes, inspired by popular TV series and movies.

  • ggplot2 extension: complements ggplot2, e.g., by allowing you to add an identity line to a scatter plot with single command.

  • String manipulation: offers functions to manipulate strings, such as keeping only a specific type of character.

The ultimate goal of relper is to simplify data analysis by providing a variety of useful functions that will shorten your steps and make data analysis more efficient. Try relperand discover how it can streamline your data analysis workflow.

Installation

You can install the developer version of relper with:

remotes::install_github("vbfelix/relper")

relper's People

Contributors

data-ga avatar larissabf avatar vbfelix avatar

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Forkers

larissabf

relper's Issues

Create calc_perc

Compute percentage, considering multiples variables to count and also a main variable

Solve case of repetitition in row_number_unique

df <- structure(list(ColA = c("A", "A", "B", "B", "C", "C", "A", "A",
"B", "B"), ColB = c(2L, 1L, 3L, 5L, 2L, 5L, 1L, 3L, 7L, 1L),
ColC = c(1L, 1L, 2L, 2L, 3L, 3L, 1L, 1L, 2L, 2L)),
class = "data.frame", row.names = c(NA, -10L))

library(dplyr)
library(relper)

data %>%
mutate(aux = row_number_unique(ColA))

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