how to make histogram with dates in format aaaa-mm-dd in R

[wesleysc352]

I have a database with dates of florestal burn. I want make a histogram wiht this dates
I would like to generate a histogram with these dates and check which dates are more frequent

[nirgrahamuk]

to start you

library(tidyverse)
set.seed(42)
(mydates <- tibble(d=sample(seq.Date(from=as.Date("2019/01/01"),
                to=as.Date("2021/01/01")-1,
                by=1),
       size = 2000,
       replace=TRUE
       )))

(mydates_summarised <- group_by(mydates,
                                d) %>% summarise(count=n()) )

(maxcount <- max(mydates_summarised$count))

mydates_summarised <- mutate(mydates_summarised,
                             maxgroup = count==maxcount)


ggplot(data=mydates_summarised,
       mapping=aes(x=d,y=count,fill=maxgroup)) + geom_col()

[wesleysc352]

215/5000

I'm sorry but I was unable to execute the code, as numerous errors were generated.

I am a novice in R, you could help me to perform this task, I am sending a file with my data.

thank you very much

Date
2010-09-21
2010-09-21
2010-09-21
2010-09-21
2010-09-21
2010-09-21
2010-09-21
2010-10-18
2011-07-08
2011-07-08
2011-07-09
2011-07-09
2011-08-06
2011-08-13
2011-08-16
2011-08-16
2011-08-31
2011-08-31
2011-09-13
2011-09-13
2011-09-13
2011-09-13
2012-09-10
2012-09-08
2012-10-01
2012-11-22
2013-02-19
2013-03-05
2013-08-03
2013-08-14
2014-08-20
2013-09-13
2015-03-16
2015-03-14
2015-08-13
2020-04-11
2020-04-18
2020-04-18
2020-04-22
2020-04-22
2020-04-23
2020-04-23
2020-04-23
2020-04-27
2020-04-27
2020-04-27
2020-04-29
2020-04-29
2020-05-11
2020-04-28
2020-04-28
2020-06-12
2020-06-12
2020-06-12
2020-06-12
2020-08-11
2020-08-15
2020-08-15
2020-08-15
2020-08-29
2020-08-29
2020-08-29
2020-08-29
2015-10-19
2017-09-10
2018-03-23
2018-06-24
2018-09-11
2018-11-11
2018-11-11
2019-02-06
2019-02-22
2019-03-12
2019-04-14
2019-07-31
2019-07-31
2019-07-31
2016-11-06
2017-07-13
2017-07-13
2017-07-13
2017-07-24
2017-07-24
2017-08-30
2017-08-30
2017-08-30
2017-08-30
2017-03-25

[andresrcs]

Ideally, you should ask your questions with a REPRoducible EXample (reprex), since you are new here I'm going to make one for you this time.

Consider that a histogram implies binding of values so you have to choose a binwidth suitable for your needs.

library(tidyverse)
library(lubridate)

sample_df <- data.frame(
        Date = c("2010-09-21","2010-09-21","2010-09-21",
                 "2010-09-21","2010-09-21","2010-09-21","2010-09-21",
                 "2010-10-18","2011-07-08","2011-07-08","2011-07-09","2011-07-09",
                 "2011-08-06","2011-08-13","2011-08-16","2011-08-16",
                 "2011-08-31","2011-08-31","2011-09-13","2011-09-13","2011-09-13",
                 "2011-09-13","2012-09-10","2012-09-08","2012-10-01",
                 "2012-11-22","2013-02-19","2013-03-05","2013-08-03","2013-08-14",
                 "2014-08-20","2013-09-13","2015-03-16","2015-03-14",
                 "2015-08-13","2020-04-11","2020-04-18","2020-04-18","2020-04-22",
                 "2020-04-22","2020-04-23","2020-04-23","2020-04-23",
                 "2020-04-27","2020-04-27","2020-04-27","2020-04-29","2020-04-29",
                 "2020-05-11","2020-04-28","2020-04-28","2020-06-12",
                 "2020-06-12","2020-06-12","2020-06-12","2020-08-11","2020-08-15",
                 "2020-08-15","2020-08-15","2020-08-29","2020-08-29",
                 "2020-08-29","2020-08-29","2015-10-19","2017-09-10","2018-03-23",
                 "2018-06-24","2018-09-11","2018-11-11","2018-11-11",
                 "2019-02-06","2019-02-22","2019-03-12","2019-04-14","2019-07-31",
                 "2019-07-31","2019-07-31","2016-11-06","2017-07-13",
                 "2017-07-13","2017-07-13","2017-07-24","2017-07-24","2017-08-30",
                 "2017-08-30","2017-08-30","2017-08-30","2017-03-25")
)

sample_df %>% 
    mutate(Date = ymd(Date)) %>% 
    ggplot(aes(Date)) +
    geom_histogram()

^{Created on 2020-09-04 by the reprex package (v0.3.0)}

[nirgrahamuk]

@wesleysc352

I'm sorry but I was unable to execute the code, as numerous errors were generated.

You will only get help with understanding and solving errors if you share what the errors are....