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R package helda (HELpful functions for Data Analysis in R)

Overview

This package provides functionalities that aim at facilitating and saving time when analysing data.

Installation

You can install helda from CRAN by simply running:

install.packages("helda")

Development version

To get a bug fix, or use a feature from the development version, you can install helda from this GitHub repository.

# install.packages("devtools")
devtools::install_github("Redcart/helda")

Usage

This is a quick introduction to the lift curve function of the package:

library(helda)

data_training <- titanic_training
data_validation <- titanic_validation

model_glm <- glm(formula = "Survived ~ Pclass + Sex + Age + 
                 SibSp + Fare + Embarked",
                 data = data_training,
                 family = binomial(link = "logit"))

predictions <- predict(object = model_glm, 
                       newdata = data_validation, 
                       type = "response")

plot <- lift_curve(predictions = predictions, 
                   true_labels = data_validation$Survived, 
                   positive_label = 1)

plot

Getting help

If you encounter a clear bug, please file a minimal reproducible example on the issues section of the repository.

Author

Simon Corde

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Version

Install

install.packages('helda')

Monthly Downloads

116

Version

1.1.5

License

GPL-3

Issues

Pull Requests

Stars

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Maintainer

Last Published

January 6th, 2021

Functions in helda (1.1.5)

lift_effect

Lift effect curve
create_formula

Create a formula
cluster_centroid

Centroid of a cluster
kmeans_procedure

K-means procedure
compute_inertia_ahc

Intra group inertia for choosing the optimal number of clusters in Agglomerative Clustering
lift_curve

Lift curve graph
gap_to_fill

Filling intermediate gaps in a time serie
compute_global_inertia

Inertia of a data frame
titanic_training

Titanic training data set
create_calendar

Complete empty calendar
proc_freq

SAS proc freq in R
titanic_testing

Titanic testing data set
titanic_validation

Titanic validation data set
start_end_to_fill

Function for filling start and end gaps in time series
world_countries_pop

World countries population from 1960 to 2018
windows_to_linux_path

Convert windows path into linux path