Introduction

hello

My first R code

library(tidyverse)

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.5
✔ forcats   1.0.0     ✔ stringr   1.5.1
✔ ggplot2   3.5.1     ✔ tibble    3.2.1
✔ lubridate 1.9.3     ✔ tidyr     1.3.1
✔ 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

library(ggformula)

Loading required package: scales

Attaching package: 'scales'

The following object is masked from 'package:purrr':

    discard

The following object is masked from 'package:readr':

    col_factor

Loading required package: ggridges

New to ggformula?  Try the tutorials: 
    learnr::run_tutorial("introduction", package = "ggformula")
    learnr::run_tutorial("refining", package = "ggformula")

library(babynames)

babynames

# A tibble: 1,924,665 × 5
    year sex   name          n   prop
   <dbl> <chr> <chr>     <int>  <dbl>
 1  1880 F     Mary       7065 0.0724
 2  1880 F     Anna       2604 0.0267
 3  1880 F     Emma       2003 0.0205
 4  1880 F     Elizabeth  1939 0.0199
 5  1880 F     Minnie     1746 0.0179
 6  1880 F     Margaret   1578 0.0162
 7  1880 F     Ida        1472 0.0151
 8  1880 F     Alice      1414 0.0145
 9  1880 F     Bertha     1320 0.0135
10  1880 F     Sarah      1288 0.0132
# ℹ 1,924,655 more rows

babynames %>% filter (name== "Aditi")

# A tibble: 40 × 5
    year sex   name      n       prop
   <dbl> <chr> <chr> <int>      <dbl>
 1  1977 F     Aditi     5 0.00000304
 2  1978 F     Aditi     9 0.00000548
 3  1979 F     Aditi     9 0.00000522
 4  1980 F     Aditi     6 0.00000337
 5  1982 F     Aditi    10 0.00000551
 6  1983 F     Aditi    12 0.00000671
 7  1984 F     Aditi    10 0.00000555
 8  1985 F     Aditi    17 0.00000921
 9  1986 F     Aditi    22 0.0000119 
10  1987 F     Aditi    21 0.0000112 
# ℹ 30 more rows

babynames %>%  filter(name=="Aditi") %>% 
  gf_line (n~year)

woah ok

cat cat cat cat

babynames %>% filter (name== "Radhika")

# A tibble: 48 × 5
    year sex   name        n       prop
   <dbl> <chr> <chr>   <int>      <dbl>
 1  1966 F     Radhika     5 0.00000285
 2  1971 F     Radhika     6 0.00000342
 3  1972 F     Radhika     7 0.00000434
 4  1973 F     Radhika     6 0.00000386
 5  1974 F     Radhika    13 0.0000083 
 6  1975 F     Radhika     6 0.00000384
 7  1976 F     Radhika    12 0.00000763
 8  1977 F     Radhika     9 0.00000547
 9  1978 F     Radhika    12 0.0000073 
10  1979 F     Radhika    12 0.00000696
# ℹ 38 more rows

babynames %>%  filter(name=="Radhika") %>% 
  gf_line (n~year)

babynames %>% filter(name == "Preeti" | name == "Pretty")

# A tibble: 46 × 5
    year sex   name       n       prop
   <dbl> <chr> <chr>  <int>      <dbl>
 1  1972 F     Preeti     7 0.00000434
 2  1973 F     Preeti     9 0.00000579
 3  1975 F     Preeti     9 0.00000577
 4  1976 F     Preeti    10 0.00000636
 5  1977 F     Preeti     9 0.00000547
 6  1978 F     Preeti    14 0.00000852
 7  1979 F     Preeti     7 0.00000406
 8  1980 F     Preeti    16 0.00000899
 9  1981 F     Preeti    11 0.00000615
10  1982 F     Preeti    10 0.00000551
# ℹ 36 more rows