The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

Travis-CI Build Status

prenoms

The goal of prenoms is to give the names of babies born in Quebec between 1980 and 2020.

Installation

You can install prenoms from github with:

# install.packages("devtools")
devtools::install_github("desautm/prenoms")

Example 1

Here is the graph of the first names of the four members of my family, between 1980 and 2020.

library(tidyverse)
#> -- Attaching packages --------------------------------------- tidyverse 1.3.1 --
#> v ggplot2 3.3.3     v purrr   0.3.4
#> v tibble  3.1.1     v dplyr   1.0.5
#> v tidyr   1.1.3     v stringr 1.4.0
#> v readr   1.4.0     v forcats 0.5.1
#> -- Conflicts ------------------------------------------ tidyverse_conflicts() --
#> x dplyr::filter() masks stats::filter()
#> x dplyr::lag()    masks stats::lag()
library(prenoms)
family <- prenoms %>%
  filter(
    name == "Marc-Andre" & sex == "M" |
    name == "Laurent" & sex == "M" |
    name == "Melanie" & sex == "F" |
    name == "Anna" & sex == "F"
  ) %>%
  group_by(name, year, sex) %>%
  summarise(n = sum(n)) %>%
  arrange(year)
#> `summarise()` has grouped output by 'name', 'year'. You can override using the `.groups` argument.

ggplot(data = family, aes(x = year, y = n, color = name))+
  geom_line()+
  scale_x_continuous( breaks = seq(1980, 2020, by = 5))

Example 2

The five most popular female names in 2020.

prenoms %>%
  filter(year == 2020 & sex == "F") %>%
  select(year, sex, name, n) %>%
  arrange(desc(n)) %>%
  head(5)
#> # A tibble: 5 x 4
#>    year sex   name          n
#>   <int> <chr> <chr>     <int>
#> 1  2020 F     Olivia      543
#> 2  2020 F     Alice       491
#> 3  2020 F     Emma        491
#> 4  2020 F     Charlie     488
#> 5  2020 F     Charlotte   449

Example 3

The five most popular male names in 2020.

prenoms %>%
  filter(year == 2020 & sex == "M") %>%
  select(year, sex, name, n) %>%
  arrange(desc(n)) %>%
  head(5)
#> # A tibble: 5 x 4
#>    year sex   name        n
#>   <int> <chr> <chr>   <int>
#> 1  2020 M     Liam      661
#> 2  2020 M     William   644
#> 3  2020 M     Noah      639
#> 4  2020 M     Thomas    594
#> 5  2020 M     Leo       572

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.