magrittr
There are 1 repository under magrittr topic.
daranzolin / ViewPipeSteps
Create tabs of View() output for each chained pipe
Language:R 241- Language:Python 147
- Language:HTML 60
- Language:R 39
tjmahr / MadR_Pipelines
Slides and materials for my talk to the Madison R Users Group
Language:HTML 32- ripeLanguage:R 9
rossellhayes / incase
Pipe-Friendly Vector Replacement with Case Statements
Language:R 8- Language:HTML 7
m-clark / data-manipulation-in-r
Set of slides for a workshop introducing dplyr related functionality, piping and related.
Language:R 5- Language:R 3
- Language:R 2
simonschoe / introduction-to-the-tidyverse
This lecture is part of the "Machine Learning in R" graduate course held at University of Münster, School of Business and Economics (winter term 2021/22). :mortar_board:
Language:HTML 2estebanrucan / taller-de-software-estadistico
Taller de R en Febrero de 2021
Language:HTML 1fevzikaya7 / final_indian_fellas
Indian Ocean Dipole
Language:HTML 1Ilvondir / bigmac-price-analysis
Bigmac price analysis based on data from around the world.
Language:R 1ranjiGT / dbscan-metropolian
Finding clusters from nearby large cities around the world (metropolitan areas) by using the DBSCAN technique
Language:R 1Algunos materiales de apoyo que he ido realizando en el tiempo
Language:TeX 0tboudart / Chicago-Crime-Regression-Analysis
As part of a group project, I developed separate regression models using R to predict the daily number of batteries and robberies in Chicago using four different datasets. I tested interactive and second-order terms and used stepwise feature selection to find the best model with the given data. I tested several potential models using cross-validation and chose the model that minimized the cross-validation errors while striking a balance with the model's simplicity. I checked the residual assumptions and both models exhibit autocorrelation as indicated by rejecting the null hypothesis of the Durbin-Watson Test. If I had more time, I would try using an ARMA model instead of multiple regression.
Language:R 0DNAbased / DataFramed
Working with data in Python, R, and Julia
Language:R- Language:R
gtsa / Accelerometers_Wearable_Data---Getting_and_Cleaning
The purpose of this project is to demonstrate my ability to collect, work with, and clean a data set. The goal is to prepare tidy data that can be used for later analysis.
Language:Rjvicentem / contrast-hypothesis-assignment
Descriptive statistics and contrast hypothesis assignment of Australian athletes data
Language:HTMLExercises using dplyr and ggplot2 R-packages
Language:HTMLExercises using RMarkdown and other R-packages
Language:HTMLExercises using RMarkdown and other R-packages
Language:HTMLExercises using RMarkdown and other R-packages
Language:HTMLlucasiscovici / studyPipe
studyPipe: Convenient pipe in python | Pipe pratique en python
Language:Python
