Packages

Note about packages: there’s many that can be used, but since every package has their own ways of calculating data, we’ll stick to tidyverse for now.

library(tidyverse)

Birthweight data

Difference between this reading and the practice with Danielle is that this dataset is in a folder, keep in mind when coding in the future

birthw_data <- read.csv(file = "data/birthweight_data.csv")

Mean birthweight for twins and singletons

Remember to use print function so the data can be seen in the final knitted output

birthw_summary <- birthw_data %>%
  group_by(plurality) %>%
  summarise(mean_birthw = mean(birthweight)) %>%
  ungroup
print(birthw_summary)
## # A tibble: 2 × 2
##   plurality mean_birthw
##   <chr>           <dbl>
## 1 singleton       3248.
## 2 twin            2311.

Table 1: mean birth weight of singleton and twin newborns

Earliest gestational age for each ethicity group

Note about summarise() function: we can custom the output names for the summaries (mean_gestation_age in this case)

earlyGage <- birthw_data %>%
  group_by(child_ethn) %>%
  summarise(min_gestation_age = min(gestation_age_w)) %>%
  ungroup
print(earlyGage)
## # A tibble: 10 × 2
##    child_ethn                        min_gestation_age
##    <chr>                             <chr>            
##  1 Aboriginal/Torres Strait Islander 33               
##  2 African/African-American          26               
##  3 Caucasian                         26               
##  4 East Asian                        33               
##  5 Hispanic/Latino                   37               
##  6 Middle-Eastern                    28               
##  7 Missing                           36               
##  8 Polynesian/Melanesian             28               
##  9 South Asian                       28               
## 10 South-East Asian                  29

Table 2: minimum gestational age of mothers by ethnicity

Notes about piping and useful sources

piping (%>%) is a useful function that automatically saves the steps in sequencial order, it’s the easiest logically.

This blog has a goood explanation of using group_by() and summarise() function in R.

Summary of birth weight by plurality into csv

use write_csv() function

write_csv(birthw_summary, file = "birthweight_summary.csv")