R Notebook

library(tidyverse)

Registered S3 methods overwritten by 'dbplyr':
  method         from
  print.tbl_lazy     
  print.tbl_sql      
── Attaching packages ──────────────────────────────────────────────────────────────── tidyverse 1.3.0 ──
✓ ggplot2 3.3.3     ✓ purrr   0.3.4
✓ tibble  3.0.5     ✓ dplyr   1.0.3
✓ tidyr   1.1.2     ✓ stringr 1.4.0
✓ readr   1.4.0     ✓ forcats 0.5.0
── Conflicts ─────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
x dplyr::filter() masks stats::filter()
x dplyr::lag()    masks stats::lag()

library(readxl)

install.packages("readxl")

Error in install.packages : Updating loaded packages

install.packages("readxl")

Error in install.packages : Updating loaded packages

install.packages("ggplot2")

Restarting R session...

stress <- readxl::read_excel("stress.xlsx")

stress

stress <- stress %>% 
  mutate(gender = as.factor(gender))


stress %>% 
  count(gender)

I only had females take my survey because I only wanted to analyze how they cope with stress and if there is a correlation between their major, sport, eating habits, and sleeping habits.

stress <- stress %>% 
  mutate(play = as.factor(play))


stress %>% 
  count(play)

9 people did not play a sport and 18 did.

stress %>% 
  drop_na(major) %>% 
  ggplot(aes(x = major)) +
  geom_bar() +
  facet_wrap(vars(play)) +
  coord_flip() +
  theme_minimal() +
  labs(y = "Number of people", 
       x = "play sport", 
       title = "does the subject play a sport")

This shows if the person played a sport and what their majors were.

stress <- stress %>% 
  mutate(stress = as.factor(stress))


stress %>% 
  count(stress)

9 people answered “sometimes” to the question that said “are you more stressed in your competition season compared to the off season?” and 18 people answered “yes”.

stress %>% 
  drop_na(stress) %>% 
  ggplot(aes(x = stress)) +
  geom_bar() +
  facet_wrap(vars(play)) +
  coord_flip() +
  theme_minimal() +
  labs(y = "Number of People", 
       x = "stress", 
       title = "play a sport")

This shows a correlation between stress level and if they play a sport or not.

stress %>% 
  drop_na(stress) %>% 
  ggplot(aes(x = stress)) +
  geom_bar() +
  facet_wrap(vars(season)) +
  coord_flip() +
  theme_minimal() +
  labs(y = "Number of People", 
       x = "stress", 
       title = "if their stress is higher in season")

People that played a sport have a higher stress level in their competition season than their off season.

stress %>% 
  drop_na(stress) %>% 
  ggplot(aes(x = stress)) +
  geom_bar() +
  facet_wrap(vars(sleep)) +
  coord_flip() +
  theme_minimal() +
  labs(y = "Number of People", 
       x = "stress", 
       title = "get enough sleep?")

People that answered “yes” they are stressed, often times did not get enough sleep.

stress %>% 
  drop_na(stress) %>% 
  ggplot(aes(x = stress)) +
  geom_bar() +
  facet_wrap(vars(food)) +
  coord_flip() +
  theme_minimal() +
  labs(y = "Number of People", 
       x = "stress", 
       title = "eat healthy food?")

This did not show a correlation between stress level and healthy foods.

stress %>% 
  drop_na(stress) %>% 
  ggplot(aes(x = stress)) +
  geom_bar() +
  facet_wrap(vars(cope)) +
  coord_flip() +
  theme_minimal() +
  labs(y = "Number of People", 
       x = "stress", 
       title = "know how to cope with stress?")

The majority of people who are stressed state that they do know how to cope with their stress.

stress %>% 
  drop_na(stress) %>% 
  ggplot(aes(x = stress)) +
  geom_bar() +
  facet_wrap(vars(working)) +
  coord_flip() +
  theme_minimal() +
  labs(y = "Number of People", 
       x = "stress", 
       title = "is the coping working?")

Even though people answered that they do know how to cope with stress, a majority said that they do not know how to cope with it.

stress %>% 
  drop_na(gender) %>% 
  ggplot(aes(x = gender)) +
  geom_bar() +
  facet_wrap(vars(level)) +
  coord_flip() +
  theme_minimal() +
  labs(y = "Number of People", 
       x = "stress", 
       title = "stress level 1-10 ")

All the participants answered a questions asking them to rate their stress. (1=low, 10=high)