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Update r4ds url #1514

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Sep 15, 2023
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Update r4ds url #1514

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f94708b
Update r4ds url
zekiakyol Sep 3, 2023
42614ea
run `devtools::build_readme()`
zekiakyol Sep 15, 2023
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2 changes: 1 addition & 1 deletion README.Rmd
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Expand Up @@ -24,7 +24,7 @@ knitr::opts_chunk$set(

The goal of readr is to provide a fast and friendly way to read rectangular data from delimited files, such as comma-separated values (CSV) and tab-separated values (TSV).
It is designed to parse many types of data found in the wild, while providing an informative problem report when parsing leads to unexpected results.
If you are new to readr, the best place to start is the [data import chapter](https://r4ds.had.co.nz/data-import.html) in R for Data Science.
If you are new to readr, the best place to start is the [data import chapter](https://r4ds.hadley.nz/data-import) in R for Data Science.

## Installation

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14 changes: 8 additions & 6 deletions README.md
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Expand Up @@ -20,7 +20,7 @@ rectangular data from delimited files, such as comma-separated values
of data found in the wild, while providing an informative problem report
when parsing leads to unexpected results. If you are new to readr, the
best place to start is the [data import
chapter](https://r4ds.had.co.nz/data-import.html) in R for Data Science.
chapter](https://r4ds.hadley.nz/data-import) in R for Data Science.

## Installation

Expand Down Expand Up @@ -52,14 +52,16 @@ readr is part of the core tidyverse, so you can load it with:

``` r
library(tidyverse)
#> ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
#> ✔ ggplot2 3.4.1 ✔ purrr 1.0.1
#> ✔ tibble 3.2.0 ✔ dplyr 1.1.0
#> ✔ tidyr 1.3.0 ✔ stringr 1.5.0
#> ✔ readr 2.1.4.9000 ✔ forcats 1.0.0
#> ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
#> ✔ dplyr 1.1.3 ✔ readr 2.1.4.9000
#> ✔ forcats 1.0.0 ✔ stringr 1.5.0
#> ✔ ggplot2 3.4.3 ✔ tibble 3.2.1
#> ✔ lubridate 1.9.2 ✔ tidyr 1.3.0
#> ✔ purrr 1.0.2
#> ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
#> ✖ dplyr::filter() masks stats::filter()
#> ✖ dplyr::lag() masks stats::lag()
#> ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
```

Of course, you can also load readr as an individual package:
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