tydiverse

Version March 5th 2020 knitr::opts_chunk$set(echo = TRUE) library(tidyverse) ## ── Attaching packages ───────────────────────────────────────────────────────────── tidyverse 1.3.0 ── ## ✓ ggplot2 3.2.1 ✓ purrr 0.3.3 ## ✓ tibble 2.1.3 ✓ dplyr 0.8.4 ## ✓ tidyr 1.0.2 ✓ stringr 1.4.0 ## ✓ readr 1.3.1 ✓ forcats 0.4.0 ## ── Conflicts ──────────────────────────────────────────────────────────────── tidyverse_conflicts() ── ## x dplyr::filter() masks stats::filter() ## x dplyr::lag() masks stats::lag() library(dplyr) library(ggplot2) library(datasets) head(trees) ## Girth Height Volume ## 1 8.

The aim of this workshop is to get familiar with dplyr, an R package to transform and summarize dataframe. The packages lubridate will be sligtly described your_dataset<- read.csv("~/Dropbox/folder1/folder2/awesomedata.csv") # how to read your file bike<-readRDS("~/folder1/folder2/trips.RDS") # here is the dataset I'm using as an example. # don't forget to copy your own path !! library(dplyr) library(lubridate) Description of the database “bike” trips is a dataset containing information on each bike rental: