[R] tidyverse: grouped summaries (with summerize)
Rich Shepard
r@hep@rd @end|ng |rom @pp|-eco@y@@com
Mon Sep 13 22:52:42 CEST 2021
I changed the data files so the date-times are in five separate columns:
year, month, day, hour, and minute; for example,
year,month,day,hour,min,cfs
2016,03,03,12,00,149000
2016,03,03,12,10,150000
2016,03,03,12,20,151000
2016,03,03,12,30,156000
2016,03,03,12,40,154000
2016,03,03,12,50,150000
2016,03,03,13,00,153000
2016,03,03,13,10,156000
2016,03,03,13,20,154000
The script is based on the example (on page 59 of 'R for Data Science'):
library('tidyverse')
disc <- read.csv('../data/water/disc.dat', header = TRUE, sep = ',', stringsAsFactors = FALSE)
disc$year <- as.integer(disc$year)
disc$month <- as.integer(disc$month)
disc$day <- as.integer(disc$day)
disc$hour <- as.integer(disc$hour)
disc$min <- as.integer(disc$min)
disc$cfs <- as.double(disc$cfs, length = 6)
# use dplyr to filter() by year, month, day; summarize() to get monthly
# means, sds
disc_by_month <- group_by(disc, year, month)
summarize(disc_by_month, vol = mean(cfs, na.rm = TRUE))
but my syntax is off because the results are:
> source('disc.R')
`summarise()` has grouped output by 'year'. You can override using the `.groups` argument.
Warning messages:
1: In eval(ei, envir) : NAs introduced by coercion
2: In eval(ei, envir) : NAs introduced by coercion
> ls()
[1] "disc" "disc_by_month"
> disc_by_month
# A tibble: 590,940 × 6
# Groups: year, month [66]
year month day hour min cfs
<int> <int> <int> <int> <int> <dbl>
1 2016 3 3 12 0 149000
2 2016 3 3 12 10 150000
3 2016 3 3 12 20 151000
4 2016 3 3 12 30 156000
5 2016 3 3 12 40 154000
6 2016 3 3 12 50 150000
7 2016 3 3 13 0 153000
8 2016 3 3 13 10 156000
9 2016 3 3 13 20 154000
10 2016 3 3 13 30 155000
# … with 590,930 more rows
I have the same results if I use as.numeric rather than as.integer and
as.double. What am I doing incorrectly?
TIA,
Rich
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