Purpose

Explore rodent data from the Portal Project.

List of tasks:

  1. Load data from database
  2. Clean data into time series
  3. Make plot

Read in packages

library(dplyr)
library(ggplot2)

Data

data <- read.csv("https://ndownloader.figshare.com/files/2292172")
head(data)
##   record_id month day year plot_id species_id sex hindfoot_length weight
## 1         1     7  16 1977       2         NL   M              32     NA
## 2         2     7  16 1977       3         NL   M              33     NA
## 3         3     7  16 1977       2         DM   F              37     NA
## 4         4     7  16 1977       7         DM   M              36     NA
## 5         5     7  16 1977       3         DM   M              35     NA
## 6         6     7  16 1977       1         PF   M              14     NA

The data includes 49 species.

Clean up data and plot

Summarize data for number of occurrences per year and per species.

time_series <- data %>% 
  group_by(species_id, year) %>% 
  summarize(count = n())
## `summarise()` has grouped output by 'species_id'. You can override using the `.groups` argument.
head(time_series)
## # A tibble: 6 × 3
## # Groups:   species_id [1]
##   species_id  year count
##   <chr>      <int> <int>
## 1 ""          1977    16
## 2 ""          1978    56
## 3 ""          1979    61
## 4 ""          1980    40
## 5 ""          1981    55
## 6 ""          1982    14

Plot the time series.