Plot temperature over time (date)

Question

I am trying to plot temperature over time (in the form of a date), however, I am not sure how to.

See here my original table in Excel:

Or as R code:

dput(Average_temperature_period)
structure(list(Sample = c("ZS_IG_1", "AK_SN_1", "JP_IG_2", "AW_IG_1", 
"SBB_SN_1", "AW_IG_2", "JvH_IG_3", "JvH_IG_2", "SBB_SN_4", "SBB_SN_3", 
"SBB_SN_2", "EF_SN_1", "JP_IG_2", "JvH_IG_3", "EF_SN_1", "JvH_IG_2", 
"AK_SN_1", "ZS_IG_1", "AW_IG_1", "SBB_SN_1", "AW_IG_2", "SBB_SN_4", 
"SBB_SN_3", "SBB_SN_2"), Sampling_date = c("23/03/2022", "24/03/2022", 
"25/03/2022", "25/03/2022", "25/03/2022", "25/03/2022", "29/03/2022", 
"29/03/2022", "01/04/2022", "01/04/2022", "01/04/2022", "12/04/2022", 
"25/04/2022", "26/04/2022", "28/04/2022", "29/04/2022", "03/05/2022", 
"04/05/2022", "10/05/2022", "10/05/2022", "11/05/2022", "11/05/2022", 
"12/05/2022", "12/05/2022"), Period = c("March", "March", "March", 
"March", "March", "March", "March", "March", "March", "March", 
"March", "March", "AprilMay", "AprilMay", "AprilMay", "AprilMay", 
"AprilMay", "AprilMay", "AprilMay", "AprilMay", "AprilMay", "AprilMay", 
"AprilMay", "AprilMay"), Average_temperature_field = c(7.137037037, 
6.966666667, 10.55555556, 7.281481481, 6.874074074, 9.211111111, 
9.662962963, 8.12962963, 6.707407407, 6.774074074, 7.162962963, 
8.114814815, NA, 11.74814815, 13.51111111, 11.29259259, 15.4962963, 
NA, 15.45925926, 17.14814815, 17.72592593, 15.84074074, 16.85555556, 
19.78148148), Average_moisture_field = c(33.48518519, 47.35555556, 
32.54814815, 34.01851852, 38.66666667, 31.71851852, 23.54814815, 
26.83333333, 42.47777778, 29.45555556, 44.50740741, 40.27407407, 
25.77407407, 18.91481481, 26.67777778, 16.27407407, 25.38518519, 
19.9962963, 18.27777778, 16.14074074, 22.86666667, 23.48518519, 
13.93703704, 20.92222222)), row.names = c(NA, 24L), class = "data.frame")

See here my code in R thus far:

##### Soil temperature graph
Average_temperature_period <- read.csv("~/Desktop/First Internship/MicroResp/R/R script/Average_temperature_period.csv")

Average_temperature_period$Sampling_date <- as.character(Average_temperature_period$Sampling_date)

Average_temperature_period <- Average_temperature_period[c(1:24),c(1:5)]


# Change order x axis (past to present)
Average_temperature_period$Sampling_date <- factor(Average_temperature_period$Sampling_date, levels = c("23/03/22","24/03/22","25/03/22","29/03/22","01/04/22","12/04/22","25/04/22","26/04/22","28/04/22","29/04/22","03/05/22","04/05/22","10/05/22","11/05/22","12/05/22"))

# Plot average temperature against the date
ggplot(data=Average_temperature_period, aes(x=Sampling_date, y=Average_temperature_field)) +
  geom_smooth(method = "lm", se=FALSE, color="black", aes(group=1)) + 
  theme_classic() +
  ylab("Average soil temperature (°C)") + 
  xlab("Sampling date")

The x axis keeps on showing 'NA' for the sampling date. Does anyone know why and how to fix it? I would like to have the x axis in order of date (past to present).

Hi Stefanie, welcome to Stack Overflow. Could you please provide your data as text, [not an image](https://meta.stackoverflow.com/a/285557/17303805)? Run `dput(Average_temperature_period)` in R and copy/paste into your post. See [here](https://stackoverflow.com/a/5963610/17303805) for more on asking effective R questions on SO. — zephryl, Nov 25 '22 at 18:10
What do you mean exactly? Isnt the date column already in a date format? — Stefanie van den Berg, Nov 25 '22 at 18:10
@zephryl, thank you for the suggestion. I have attached the R code via dput in this post. — Stefanie van den Berg, Nov 25 '22 at 18:15
Perhaps store the data.frame state right after `read.csv()` , in your current `dput()` all dates are just `NA`s. — margusl, Nov 25 '22 at 18:22
In R, "23/03/2022" is just text ("character") data. R has a data type called Date, which is what you want to do calculations and plotting. in base R, you'd use `as.Date(YOUR_DATES, format = "%d/%m/%Y")` or perhaps more convenient to use `lubridate::dmy(YOUR_DATES)`, where `dmy` is the function for parsing dates in day-month-year order. — Jon Spring, Nov 25 '22 at 18:35

TarJae · Accepted Answer · 2022-11-25T18:46:56.720

Update with the new data and request of OP: adding this line drop_na(Average_temperature_field) %>%

library(tidyverse)
library(lubridate)
df %>% 
  drop_na(Average_temperature_field) %>% 
  mutate(Sampling_date = dmy(Sampling_date)) %>% 
  group_by(Sampling_date) %>% 
  summarise(avg_temp_day = mean(Average_temperature_field,na.rm = TRUE)) %>% 
  ggplot(aes(x = Sampling_date, y=avg_temp_day))+
  geom_point()+
  geom_line()+
  scale_x_date(date_labels="%d %b",date_breaks  ="1 day")+
  theme_bw()+
  theme(axis.text.x = element_text(angle = 45, vjust = 0.5, hjust=1))

First answer: Here is one way to do it. You have sometimes two temperatures per day so I used the mean for this day:

library(tidyverse)
library(lubridate)
df %>% 
  mutate(Sampling_date = dmy(Sampling_date)) %>% 
  group_by(Sampling_date) %>% 
 summarise(avg_temp_day = mean(Average_temperature_field,na.rm = TRUE)) %>% 
  ggplot(aes(x = Sampling_date, y=avg_temp_day))+
  geom_point()+
  geom_line()+
  scale_x_date(date_labels="%d %b",date_breaks  ="2 day")+
  theme_bw()+
  theme(axis.text.x = element_text(angle = 45, vjust = 0.5, hjust=1))

data:

df <- structure(list(Sample = c("ZS_IG_1", "AK_SN_1", "JP_IG_2", "AW_IG_1", 
"SBB_SN_1", "AW_IG_2", "JvH_IG_3", "JvH_IG_2", "SBB_SN_4", "SBB_SN_3", 
"SBB_SN_2", "EF_SN_1", "JP_IG_2", "JvH_IG_3", "EF_SN_1", "JvH_IG_2", 
"AK_SN_1", "ZS_IG_1", "AW_IG_1", "SBB_SN_1", "AW_IG_2", "SBB_SN_4", 
"SBB_SN_3", "SBB_SN_2"), Sampling_date = c("23/03/2022", "24/03/2022", 
"25/03/2022", "25/03/2022", "25/03/2022", "25/03/2022", "29/03/2022", 
"29/03/2022", "01/04/2022", "01/04/2022", "01/04/2022", "12/04/2022", 
"25/04/2022", "26/04/2022", "28/04/2022", "29/04/2022", "03/05/2022", 
"04/05/2022", "10/05/2022", "10/05/2022", "11/05/2022", "11/05/2022", 
"12/05/2022", "12/05/2022"), Period = c("March", "March", "March", 
"March", "March", "March", "March", "March", "March", "March", 
"March", "March", "AprilMay", "AprilMay", "AprilMay", "AprilMay", 
"AprilMay", "AprilMay", "AprilMay", "AprilMay", "AprilMay", "AprilMay", 
"AprilMay", "AprilMay"), Average_temperature_field = c(33.48518519, 
47.35555556, 32.54814815, 34.01851852, 38.66666667, 31.71851852, 
23.54814815, 26.83333333, 42.47777778, 29.45555556, 44.50740741, 
40.27407407, 25.77407407, 11.74814815, 13.51111111, 11.29259259, 
15.4962963, 19.9962963, 15.45925926, 17.14814815, 17.72592593, 
15.84074074, 16.85555556, 19.78148148), Average_moisture_field = c(7.137037037, 
6.966666667, 10.55555556, 7.281481481, 6.874074074, 9.211111111, 
9.662962963, 8.12962963, 6.707407407, 6.774074074, 7.162962963, 
8.114814815, NA, 18.91481481, 26.67777778, 16.27407407, 25.38518519, 
NA, 18.27777778, 16.14074074, 22.86666667, 23.48518519, 13.93703704, 
20.92222222)), class = "data.frame", row.names = c(NA, -24L))

Thank you so much for the quick and helpful reply. This is exactly what I wanted. — Stefanie van den Berg, Nov 25 '22 at 18:30
I was just wondering one more thing: I accidentally attached the wrong temperature/moisture data here. The correct format is now attached in the original post. However, when I use your code, I obtain 'gaps' in the graph. Could you help me with this problem? — Stefanie van den Berg, Nov 25 '22 at 18:36
I checked it. with your new data the gaps are correct. Indicating that you have no data on thiese days! So we can't now how the curve will proceed, becausse we have no data. So it is ok of have an interrupted line! If you don't want an interrupted line, add this line: `drop_na(Average_temperature_field) %>%` as second line after `df %>%`. But be sure that you want to do this! — TarJae, Nov 25 '22 at 18:45
Great, that worked perfectly. Thanks for helping me out and have a wonderful day! — Stefanie van den Berg, Nov 25 '22 at 18:50

Plot temperature over time (date)

1 Answers1