dog_data_analysis.Rmd

---
title: "dog_data_analysis"
author: "VM"
date: "11/11/2020"
output: 
  html_document:
    number_sections: yes
    toc: yes
    toc_float: yes
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

# Load libraries and read data
```{r}
library(tidyverse)
library(ggplot2)
dog_data <- read_csv("~/dirty_data_project/task6/clean_data/clean_dog_data.csv")
```
# Q1
## The client only counts a valid email address as one ending in ‘.com’. How many survey results have a valid email address.
```{r}
dog_data %>% 
  select(email) %>% 
  drop_na() %>% 
  mutate(valid_email = str_detect(email, "[A-Za-z]+\\.com")) %>% 
  summarise(total = sum(valid_email))
```
# Q2
## What’s the average amount spent on dog food for each dog size.
```{r}
dog_data %>% 
  select(dog_size, amount_spent_on_dog_food) %>% 
  drop_na(amount_spent_on_dog_food, dog_size) %>%
  group_by(dog_size) %>% 
  summarise(avg = mean(amount_spent_on_dog_food))
```
# Q3
## For owners whose surname starts with a letter in the second half of the alphabet (N onwards) what is the average age of their dog?
```{r}
dog_data %>% 
  select(last_name, dog_age) %>% 
  mutate(starts_n = str_detect(last_name, "^[N-Z]+")) %>% 
  drop_na(dog_age) %>% 
  summarise(avg_age = mean(dog_age))
```
# Q4 
## The dog_age column is the age in dog years. If the conversion is 1 human year = 6 dog years, then what is the average human age for dogs of each gender?
```{r}
dog_age <- dog_data %>% 
  select(dog_gender, dog_age) %>% 
  mutate(human_dog_age = dog_age/6) %>% 
  drop_na(dog_age, dog_gender) %>% 
  group_by(dog_gender) %>% 
  summarise(avg_age = mean(human_dog_age))

dog_age
```
# Q5
## Create a plot of results of question 4.
```{r}
ggplot() +
  geom_col(data = dog_age, aes(x = dog_gender, y = avg_age), colour = "black", fill="pink") +
  labs(title = "Plot of dog gender over average age") +
  theme_classic()

```