Combine timeseries data from two different sensors in R

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I have timeseries data from 2 sensors recoding independently. They were both started at different start times and record data at different intervals. Sensor 1 records every one second while sensor 2 records every 2 seconds. I want to combine both these datasets into a single dataframe in order to ggplot. Can someone help me out? If there are other better options than ggplot and dataframes, please let me know. Thanks for the help. I included sample data (not actual, let me know if I did not include the right sample under):

dput(reading1)
structure(list(time = structure(c(-2209030842, -2209030841, -2209030840, 
-2209030839, -2209030838, -2209030837, -2209030836, -2209030835, 
-2209030834, -2209030833, -2209030832, -2209030831, -2209030830, 
-2209030829, -2209030828, -2209030827, -2209030826, -2209030825, 
-2209030824), class = c("POSIXct", "POSIXt"), tzone = "UTC"), 
    `reading 1` = c(0.004, 0.003, 0.003, 0.013, 0.021, 0.008, 
    0.004, 0.005, 0.004, 0.007, 0.003, 0.004, 0.002, 0.003, 0.004, 
    0.004, 0.005, 0.001, 0.003)), class = c("tbl_df", "tbl", 
"data.frame"), row.names = c(NA, -19L))

dput(reading2)
structure(list(Date = structure(c(-2209031012, -2209031009, -2209031007, 
-2209031005, -2209031003, -2209030982, -2209030981, -2209030976, 
-2209030974, -2209030972, -2209030970, -2209030949, -2209030882, 
-2209030879, -2209030877, -2209030875, -2209030873, -2209030871, 
-2209030850, -2209030849, -2209030838, -2209030816, -2209030814, 
-2209030811, -2209030808, -2209030806, -2209030804, -2209030783, 
-2209030782, -2209030780, -2209030778, -2209030775, -2209030773, 
-2209030771, -2209030750, -2209030749, -2209030747, -2209030742, 
-2209030740, -2209030738, -2209030717, -2209030705, -2209030684, 
-2209030683, -2209030681, -2209030679, -2209030676, -2209030674, 
-2209030672, -2209030651, -2209030650, -2209030648, -2209030646, 
-2209030644, -2209030641, -2209030639), class = c("POSIXct", 
"POSIXt"), tzone = "UTC"), `reading 2` = c(8, 8, 8, 8, 8, 6, 
6, 8, 8, 8, 8, 6, 7, 7, 7, 7, 7, 7, 6, 6, 6, 6, 6, 6, 6, 6, 6, 
5, 5, 5, 5, 5, 5, 5, 6, 6, 6, 7, 7, 7, 6, 6, 6, 6, 6, 6, 6, 6, 
6, 6, 6, 6, 6, 6, 6, 6)), class = c("tbl_df", "tbl", "data.frame"
), row.names = c(NA, -56L))
time-series ggplot2 dataframe r
1 Answers

You could combine them using dplyr like this:

combined <- bind_rows(
 reading1 %>% rename(reading = `reading 1`) %>% mutate(sensor = 1),
 reading2 %>% rename(reading = `reading 2`, time = Date) %>% 
   mutate(sensor = 2)) %>%
  arrange(time)

combined
#> # A tibble: 75 x 3
#>    time                reading sensor
#>    <dttm>                <dbl>  <dbl>
#>  1 1899-12-31 12:16:28       8      2
#>  2 1899-12-31 12:16:31       8      2
#>  3 1899-12-31 12:16:33       8      2
#>  4 1899-12-31 12:16:35       8      2
#>  5 1899-12-31 12:16:37       8      2
#>  6 1899-12-31 12:16:58       6      2
#>  7 1899-12-31 12:16:59       6      2
#>  8 1899-12-31 12:17:04       8      2
#>  9 1899-12-31 12:17:06       8      2
#> 10 1899-12-31 12:17:08       8      2
#> # ... with 65 more rows

Having your data in long format like this allows for easier plotting, for example:

library(ggplot2)

ggplot(combined, aes(time, reading, color = factor(sensor))) +
  geom_line(size = 1) +
  theme_bw(base_size = 16) +
  scale_color_brewer(palette = "Set1", name = "Sensor")

enter image description here Created on 2022-05-19 by the reprex package (v2.0.1)

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