A Inputting data

This chapter will illustrate how to input data that is stored in csv files in various common formats.

one response variable

If your data look like this:

  Year Species metric.tons
 2018,   Fish1,           1
 2019,   Fish1,           2
 2018,   Fish2,           3
 2019,   Fish2,           4
 2018,   Fish3,           6
 2019,   Fish4,          NA

with this code:

test <- read.csv("Data/test.csv", stringsAsFactors = FALSE)
save(test, file="test.RData")

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Many response variables

Read in a file where the data are in columns. If your data look like this with each species (or site) across the columns:

Year,Anchovy,Sardine,Chub mackerel,Horse mackerel,Mackerel,Jack Mackerel
1964,5449.2,12984.4,1720.7,4022.4,NA,NA
1965,4263.5,10611.1,1278.5,4158.3,NA,NA
1966,5146.4,11437.8,802.6,3012.1,NA,NA

Use this code:

test <- read.csv("Data/test.csv", stringsAsFactors = FALSE)
reshape2::melt(test, id="Year", value.name="metric.tons", variable.name="Species")
save(test, file="test.RData")

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Many response variables, two time variables

If your data also have, say, a month (or qtr) column, use this code:

Year,Month,Anchovy,Sardine,Chub mackerel,Horse mackerel,Mackerel,Jack Mackerel
1964,1,5449.2,12984.4,1720.7,4022.4,NA,NA
1964,2,4263.5,10611.1,1278.5,4158.3,NA,NA
1964,3,5146.4,11437.8,802.6,3012.1,NA,NA

Use this code:

test <- read.csv("Data/test.csv", stringsAsFactors = FALSE)
reshape2::melt(test, id=c("Year","Month"), value.name="metric.tons", variable.name="Species")
save(test, file="test.RData")

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One response variable, multiple explanatory variables

Year, Anchovy, SST,  Mackerel
1964, 5449.2,  24.4, 1720.7
1965, 4263.5,  30.1, 1278.5
1966, 5146.4,  23.8,  802.6

Use this code:

test <- read.csv("Data/test.csv", stringsAsFactors = FALSE)
save(test, file="test.RData")

Use this lm() model (or gam() etc):

fit <- lm(Anchovy ~ SST + Mackerel, data=test)