Import data

data <- read_excel("../00_data/myData.xlsx")

data
## # A tibble: 21,560 × 12
##     year gnis_id geometry   metad…¹ numbe…² parkn…³ region state unit_…⁴ unit_…⁵
##    <dbl>   <dbl> <chr>      <chr>     <dbl> <chr>   <chr>  <chr> <chr>   <chr>  
##  1  1904 1163670 POLYGON    NA            1 Crater… PW     OR    CRLA    Crater…
##  2  1941 1531834 MULTIPOLY… NA            1 Lake R… PW     WA    LARO    Lake R…
##  3  1961 2055170 MULTIPOLY… NA            1 Lewis … PW     WA    LEWI    Lewis …
##  4  1935 1530459 MULTIPOLY… NA            1 Olympic PW     WA    OLYM    Olympi…
##  5  1982  277263 POLYGON    NA            1 Santa … PW     CA    SAMO    Santa …
##  6  1919  578853 MULTIPOLY… NA            1 NA      NE     ME    ACAD    Acadia…
##  7  1969 1329499 MULTIPOLY… NA            1 NA      IM     TX    AMIS    Amista…
##  8  1967  589056 POLYGON    NA            1 NA      NE     MD    ASIS    Assate…
##  9  1944 1377082 POLYGON    NA            1 NA      IM     TX    BIBE    Big Be…
## 10  1989  302659 POLYGON    NA            1 NA      SE     FL    BICY    Big Cy…
## # … with 21,550 more rows, 2 more variables: unit_type <chr>, visitors <dbl>,
## #   and abbreviated variable names ¹​metadata, ²​number_of_records, ³​parkname,
## #   ⁴​unit_code, ⁵​unit_name

Explain data and variables

The data I selected is the National Park Visits data set from Tidy Tuesday. It looks at the number of visitors at many national parks located across the United States between the years 1904 to 2016, as well as a number of other variables. The variables that I used to answer my question were year, parkname, region, state, unit_name, unit_type, and visitors. Year is the year the data was from, parkname and unit_name are the names of the national park, region and state are where they are located, unit_type is the type of park it is, and visitors are the number of visitors that visited that park that year.

Define Question

Has the number of visits to National parks increased or decreased over the years?

Analyze data to answer the question

# Scatter plot of the number of visitors per year based on region
ggplot(data = data) +
    geom_point(mapping = aes(x = year, y = visitors, color = region)) +
    ylim(0,10000000)
## Warning: Removed 492 rows containing missing values (geom_point).

# Count how much data was collected per region
data %>%
    
    mutate(region = fct_relevel(region,
                                "NT", "AK", "NC", "MW", "PW", "SE", "NE", "IM")) %>%
    ggplot(aes(region, color = region)) +
    geom_bar()

# Individual scatter plots for the two regions with the most data
IM_region <- filter(data, region == "IM")
ggplot(data = IM_region) +
    geom_point(mapping = aes(x = year, y = visitors, color = region)) +
    ylim(0,6000000)
## Warning: Removed 83 rows containing missing values (geom_point).

NE_region <- filter(data, region == "NE")
ggplot(data = NE_region) +
    geom_point(mapping = aes(x = year, y = visitors, color = region)) +
    ylim(0,10000000)
## Warning: Removed 74 rows containing missing values (geom_point).

# Mean number of visitors in the year 1910
beg_data <- filter(data, year == 1910)
mean(beg_data$visitors)
## [1] 19268.44
# Mean number of visitors in the year 2010
end_data <- filter(data, year == 2010)
mean(end_data$visitors)
## [1] 762982.4

Interpret

To find out if the number of visits to national parks has increased or decreased over the years I first created a scatter plot to show the number of visitors per year per region. Because of the size of my data set, it is hard to read. Next, I counted how much data was collected for each region. I found that the IM and NE regions had the most data. So I created the exact same scatter plot for just the IM region and for the NE region. Both of regions contained parks that maintained relatively low visitors throughout the whole dataset. However, it is clear there is an upward trend in both of these plots as well as the one including all of the regions.

Another method I used to answer my question was by finding the mean number of visitors. I filtered the data first to just include data from 1910, one of the earliest years in this data set, and then to 2010, one of the latest years in the data set. I took the mean number of visitors from each of these years and found that in 2010 the mean number of visitors was just about 40 times greater than the mean number of visitors in 1910.

After organizing the data in different ways I am confident that the number of visitors at national parks has increased since 1904. I think it is because transportation became more accessible over the years and information about the parks spread by word of mouth, publications, and newer technology.