Lab 1: Intro to R

library(tidyverse)
library(openintro)

#load arbuthnot dataframe
data(arbuthnot)

Exercise 1

Write the expression that you would use to view counts of girls in the arbuthnot data frame.

arbuthnot$girls

##  [1] 4683 4457 4102 4590 4839 4820 4928 4605 4457 4952 4784 5332 5200 4910 4617
## [16] 3997 3919 3395 3536 3181 2746 2722 2840 2908 2959 3179 3349 3382 3289 3013
## [31] 2781 3247 4107 4803 4881 5681 4858 4319 5322 5560 5829 5719 6061 6120 5822
## [46] 5738 5717 5847 6203 6033 6041 6299 6533 6744 7158 7127 7246 7119 7214 7101
## [61] 7167 7302 7392 7316 7483 6647 6713 7229 7767 7626 7452 7061 7514 7656 7683
## [76] 5738 7779 7417 7687 7623 7380 7288

Exercise 2

Is there an apparent trend in the number of girls baptized over the
years? How would you describe it? (To ensure that your lab report is
comprehensive, be sure to include the code needed to make the plot
as well as your written interpretation.).

ggplot (data = arbuthnot, aes(x = year, y = girls))+
  geom_line()

Between 1640 and 1650 there was a sharp decline in the number of girls baptized, reaching a low of less than 3,000. With the exception of one or two years where there were declines in baptized girls, the number of girls baptized from 1658 to 1700 steadily increased, peaking at approx 7,700 in 1697.

Exercise 3

Now, generate a plot of the proportion of boys born over time. What do you see?

#add new column to dataframe named proportion
arbuthnot <- arbuthnot %>%
  mutate(total = boys + girls)

arbuthnot$total

##  [1]  9901  9315  8524  9584  9997  9855 10034  9522  9160 10311 10150 10850
## [13] 10670 10370  9410  8104  7966  7163  7332  6544  5825  5612  6071  6128
## [25]  6155  6620  7004  7050  6685  6170  5990  6971  8855 10019 10292 11722
## [37]  9972  8997 10938 11633 12335 11997 12510 12563 11895 11851 11775 12399
## [49] 12626 12601 12288 12847 13355 13653 14735 14702 14730 14694 14951 14588
## [61] 14771 15211 15054 14918 15159 13632 13976 14861 15829 16052 15363 14639
## [73] 15616 15687 15448 11851 16145 15369 16066 15862 15220 14928

arbuthnot <- arbuthnot %>%
  mutate(boy_ratio = boys/total)

arbuthnot$boy_ratio 

##  [1] 0.5270175 0.5215244 0.5187705 0.5210768 0.5159548 0.5109082 0.5088698
##  [8] 0.5163831 0.5134279 0.5197362 0.5286700 0.5085714 0.5126523 0.5265188
## [15] 0.5093518 0.5067868 0.5080341 0.5260366 0.5177305 0.5139059 0.5285837
## [22] 0.5149679 0.5322023 0.5254569 0.5192526 0.5197885 0.5218447 0.5202837
## [29] 0.5080030 0.5116694 0.5357262 0.5342132 0.5361942 0.5206108 0.5257482
## [36] 0.5153557 0.5128359 0.5199511 0.5134394 0.5220493 0.5274422 0.5232975
## [43] 0.5155076 0.5128552 0.5105507 0.5158214 0.5144798 0.5284297 0.5087122
## [50] 0.5212285 0.5083822 0.5096910 0.5108199 0.5060426 0.5142178 0.5152360
## [57] 0.5080788 0.5155165 0.5174905 0.5132301 0.5147925 0.5199527 0.5089677
## [64] 0.5095857 0.5063659 0.5123973 0.5196766 0.5135590 0.5093183 0.5249190
## [71] 0.5149385 0.5176583 0.5188268 0.5119526 0.5026541 0.5158214 0.5181790
## [78] 0.5174052 0.5215362 0.5194175 0.5151117 0.5117899

ggplot(data = arbuthnot, aes( x = year, y = boy_ratio))+
  geom_line()

Exercise 4

What does present data frame look like. 

data('present', package='openintro')

data(present)
dim(present)

## [1] 63  3

Using the dim function, we see the data frame has 63 rows and 3 columns

Exercise 5

Compare the count of boys to girls.

colSums(present[ , c(2,3)])

##      boys     girls 
## 118792776 113016646

print ("The total number of boys is 118792776, and 113016646 girls baptized in the present dataframe")

## [1] "The total number of boys is 118792776, and 113016646 girls baptized in the present dataframe"

Exercise 6

what is the proportion of boys to girls baptized in the present?

present <- present %>%
  mutate(boy_to_girl_ratio = boys / girls)


ggplot(data = present, aes(x = boy_to_girl_ratio, y = year))+
  geom_line() 

Exercise 7

Find the maximum number in the boys column

present %>%
  summarize (max = max(boys) )

## # A tibble: 1 × 1
##       max
##     <dbl>
## 1 2186274