How to use date as filter












1















My knowledge of R and scripting in general is almost not existent. So I hope you will be patient with this basic question.



library(lubridate)
date.depature <- c("2016.06.16", "2016.11.16", "2017.01.05", "2017.01.12", "2017.02.25")
airport.departure <- c("CDG", "QNY", "QXO", "CDG", "QNY")
airport.arrival <- c("SYD", "CDG", "QNY", "SYD", "QXO")
amount <- c("1", "3", "1", "10", "5")
date.depature <- as_date(date.depature)
df <- data.frame(date.depature, airport.departure, airport.arrival, amount)

xtabs(as.integer(amount) ~ airport.arrival + airport.departure, df)


With this code we get the sum of the amount as a matrix with the airports as row/column. Now I need just the results for




  1. 2017

  2. 2017.01

  3. until 2017.01










share|improve this question



























    1















    My knowledge of R and scripting in general is almost not existent. So I hope you will be patient with this basic question.



    library(lubridate)
    date.depature <- c("2016.06.16", "2016.11.16", "2017.01.05", "2017.01.12", "2017.02.25")
    airport.departure <- c("CDG", "QNY", "QXO", "CDG", "QNY")
    airport.arrival <- c("SYD", "CDG", "QNY", "SYD", "QXO")
    amount <- c("1", "3", "1", "10", "5")
    date.depature <- as_date(date.depature)
    df <- data.frame(date.depature, airport.departure, airport.arrival, amount)

    xtabs(as.integer(amount) ~ airport.arrival + airport.departure, df)


    With this code we get the sum of the amount as a matrix with the airports as row/column. Now I need just the results for




    1. 2017

    2. 2017.01

    3. until 2017.01










    share|improve this question

























      1












      1








      1








      My knowledge of R and scripting in general is almost not existent. So I hope you will be patient with this basic question.



      library(lubridate)
      date.depature <- c("2016.06.16", "2016.11.16", "2017.01.05", "2017.01.12", "2017.02.25")
      airport.departure <- c("CDG", "QNY", "QXO", "CDG", "QNY")
      airport.arrival <- c("SYD", "CDG", "QNY", "SYD", "QXO")
      amount <- c("1", "3", "1", "10", "5")
      date.depature <- as_date(date.depature)
      df <- data.frame(date.depature, airport.departure, airport.arrival, amount)

      xtabs(as.integer(amount) ~ airport.arrival + airport.departure, df)


      With this code we get the sum of the amount as a matrix with the airports as row/column. Now I need just the results for




      1. 2017

      2. 2017.01

      3. until 2017.01










      share|improve this question














      My knowledge of R and scripting in general is almost not existent. So I hope you will be patient with this basic question.



      library(lubridate)
      date.depature <- c("2016.06.16", "2016.11.16", "2017.01.05", "2017.01.12", "2017.02.25")
      airport.departure <- c("CDG", "QNY", "QXO", "CDG", "QNY")
      airport.arrival <- c("SYD", "CDG", "QNY", "SYD", "QXO")
      amount <- c("1", "3", "1", "10", "5")
      date.depature <- as_date(date.depature)
      df <- data.frame(date.depature, airport.departure, airport.arrival, amount)

      xtabs(as.integer(amount) ~ airport.arrival + airport.departure, df)


      With this code we get the sum of the amount as a matrix with the airports as row/column. Now I need just the results for




      1. 2017

      2. 2017.01

      3. until 2017.01







      r date dataframe matrix






      share|improve this question













      share|improve this question











      share|improve this question




      share|improve this question










      asked Nov 19 '18 at 17:21









      ConfusulumConfusulum

      225




      225
























          3 Answers
          3






          active

          oldest

          votes


















          0














          Since you're already using lubridate, I'm going to show you an approach using dplyr (part of the tidyverse alongside lubridate).



          The solutions all apply. filter alongside month, year and as_date functions from lubridate to create conditions to filter your data, then use the pipe %>% to pass that long to xtabs





          library(dplyr)
          #>
          #> Attaching package: 'dplyr'
          #> The following objects are masked from 'package:stats':
          #>
          #> filter, lag
          #> The following objects are masked from 'package:base':
          #>
          #> intersect, setdiff, setequal, union
          library(lubridate)
          #>
          #> Attaching package: 'lubridate'
          #> The following object is masked from 'package:base':
          #>
          #> date

          date.depature <- c("2016.06.16", "2016.11.16", "2017.01.05", "2017.01.12", "2017.02.25")
          airport.departure <- c("CDG", "QNY", "QXO", "CDG", "QNY")
          airport.arrival <- c("SYD", "CDG", "QNY", "SYD", "QXO")
          amount <- c("1", "3", "1", "10", "5")
          date.depature <- as_date(date.depature)
          df <- data.frame(date.depature, airport.departure, airport.arrival, amount)

          # For 2017
          df %>%
          filter(year(date.depature) == 2017) %>%
          xtabs(as.integer(amount) ~ airport.arrival + airport.departure, .)
          #> airport.departure
          #> airport.arrival CDG QNY QXO
          #> CDG 0 0 0
          #> QNY 0 0 1
          #> QXO 0 4 0
          #> SYD 2 0 0

          # 2017.01
          df %>%
          filter(year(date.depature) == 2017, month(date.depature) == 1) %>%
          xtabs(as.integer(amount) ~ airport.arrival + airport.departure, .)
          #> airport.departure
          #> airport.arrival CDG QNY QXO
          #> CDG 0 0 0
          #> QNY 0 0 1
          #> QXO 0 0 0
          #> SYD 2 0 0

          # until 2017.01
          df %>%
          filter(date.depature <= as_date("2017.01.01")) %>%
          xtabs(as.integer(amount) ~ airport.arrival + airport.departure, .)
          #> airport.departure
          #> airport.arrival CDG QNY QXO
          #> CDG 0 3 0
          #> QNY 0 0 0
          #> QXO 0 0 0
          #> SYD 1 0 0


          Created on 2018-11-19 by the reprex package (v0.2.1)






          share|improve this answer































            0














            Why don't you coerce amount to class "integer" when you create df? Just get rid of the double quotes in



            amount <- c("1", "3", "1", "10", "5")


            or



            amount <- as.integer(c("1", "3", "1", "10", "5"))


            This is because as.integer(df$amount) does not return



            c(1, 3, 1, 10, 5)


            When you create the dataframe df that vector is coerced to class "factor" and what you now have is



            as.integer(df$amount)
            #[1] 1 3 1 2 4


            The right way would be



            as.integer(as.character(df$amount))
            #[1] 1 3 1 10 5


            Or more simply:



            date.depature <- c("2016.06.16", "2016.11.16", "2017.01.05", "2017.01.12", "2017.02.25")
            airport.departure <- c("CDG", "QNY", "QXO", "CDG", "QNY")
            airport.arrival <- c("SYD", "CDG", "QNY", "SYD", "QXO")
            amount <- c(1, 3, 1, 10, 5)
            date.depature <- as_date(date.depature)
            df <- data.frame(date.depature, airport.departure, airport.arrival, amount)


            Now the question.



            This is basically a subsetting problem.

            Subset the data extracting the years and months you want then run the same xtabs command.



            df1 <- df[year(df$date.depature) == 2017, ]
            df2 <- df1[month(df1$date.depature) == 1, ]
            df3 <- cbind(df[year(df$date.depature) < 2017, ], df2)


            Now xtabs, with the sub-dataframes above.



            xtabs(amount ~ airport.arrival + airport.departure, df1)
            xtabs(amount ~ airport.arrival + airport.departure, df2)
            xtabs(amount ~ airport.arrival + airport.departure, df3)





            share|improve this answer
























            • Thank you a lot for explaining the integer-problem to me. I was not aware of that.

              – Confusulum
              Nov 20 '18 at 9:57



















            0














            You need to subset date.departure in your xtabs call. For year == 2017:



            xtabs(as.integer(amount) ~ airport.arrival + airport.departure, df[year(df$date.depature)==2017,])


            For year==2017 and month==1:



            xtabs(as.integer(amount) ~ airport.arrival + airport.departure, df[year(df$date.depature)==2017 & month(df$date.departure)==1,])


            And for anything before Jan 2017:



            xtabs(as.integer(amount) ~ airport.arrival + airport.departure, df[df$date.depature<as_date("2017-01-01"),])





            share|improve this answer























              Your Answer






              StackExchange.ifUsing("editor", function () {
              StackExchange.using("externalEditor", function () {
              StackExchange.using("snippets", function () {
              StackExchange.snippets.init();
              });
              });
              }, "code-snippets");

              StackExchange.ready(function() {
              var channelOptions = {
              tags: "".split(" "),
              id: "1"
              };
              initTagRenderer("".split(" "), "".split(" "), channelOptions);

              StackExchange.using("externalEditor", function() {
              // Have to fire editor after snippets, if snippets enabled
              if (StackExchange.settings.snippets.snippetsEnabled) {
              StackExchange.using("snippets", function() {
              createEditor();
              });
              }
              else {
              createEditor();
              }
              });

              function createEditor() {
              StackExchange.prepareEditor({
              heartbeatType: 'answer',
              autoActivateHeartbeat: false,
              convertImagesToLinks: true,
              noModals: true,
              showLowRepImageUploadWarning: true,
              reputationToPostImages: 10,
              bindNavPrevention: true,
              postfix: "",
              imageUploader: {
              brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
              contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
              allowUrls: true
              },
              onDemand: true,
              discardSelector: ".discard-answer"
              ,immediatelyShowMarkdownHelp:true
              });


              }
              });














              draft saved

              draft discarded


















              StackExchange.ready(
              function () {
              StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53379735%2fhow-to-use-date-as-filter%23new-answer', 'question_page');
              }
              );

              Post as a guest















              Required, but never shown

























              3 Answers
              3






              active

              oldest

              votes








              3 Answers
              3






              active

              oldest

              votes









              active

              oldest

              votes






              active

              oldest

              votes









              0














              Since you're already using lubridate, I'm going to show you an approach using dplyr (part of the tidyverse alongside lubridate).



              The solutions all apply. filter alongside month, year and as_date functions from lubridate to create conditions to filter your data, then use the pipe %>% to pass that long to xtabs





              library(dplyr)
              #>
              #> Attaching package: 'dplyr'
              #> The following objects are masked from 'package:stats':
              #>
              #> filter, lag
              #> The following objects are masked from 'package:base':
              #>
              #> intersect, setdiff, setequal, union
              library(lubridate)
              #>
              #> Attaching package: 'lubridate'
              #> The following object is masked from 'package:base':
              #>
              #> date

              date.depature <- c("2016.06.16", "2016.11.16", "2017.01.05", "2017.01.12", "2017.02.25")
              airport.departure <- c("CDG", "QNY", "QXO", "CDG", "QNY")
              airport.arrival <- c("SYD", "CDG", "QNY", "SYD", "QXO")
              amount <- c("1", "3", "1", "10", "5")
              date.depature <- as_date(date.depature)
              df <- data.frame(date.depature, airport.departure, airport.arrival, amount)

              # For 2017
              df %>%
              filter(year(date.depature) == 2017) %>%
              xtabs(as.integer(amount) ~ airport.arrival + airport.departure, .)
              #> airport.departure
              #> airport.arrival CDG QNY QXO
              #> CDG 0 0 0
              #> QNY 0 0 1
              #> QXO 0 4 0
              #> SYD 2 0 0

              # 2017.01
              df %>%
              filter(year(date.depature) == 2017, month(date.depature) == 1) %>%
              xtabs(as.integer(amount) ~ airport.arrival + airport.departure, .)
              #> airport.departure
              #> airport.arrival CDG QNY QXO
              #> CDG 0 0 0
              #> QNY 0 0 1
              #> QXO 0 0 0
              #> SYD 2 0 0

              # until 2017.01
              df %>%
              filter(date.depature <= as_date("2017.01.01")) %>%
              xtabs(as.integer(amount) ~ airport.arrival + airport.departure, .)
              #> airport.departure
              #> airport.arrival CDG QNY QXO
              #> CDG 0 3 0
              #> QNY 0 0 0
              #> QXO 0 0 0
              #> SYD 1 0 0


              Created on 2018-11-19 by the reprex package (v0.2.1)






              share|improve this answer




























                0














                Since you're already using lubridate, I'm going to show you an approach using dplyr (part of the tidyverse alongside lubridate).



                The solutions all apply. filter alongside month, year and as_date functions from lubridate to create conditions to filter your data, then use the pipe %>% to pass that long to xtabs





                library(dplyr)
                #>
                #> Attaching package: 'dplyr'
                #> The following objects are masked from 'package:stats':
                #>
                #> filter, lag
                #> The following objects are masked from 'package:base':
                #>
                #> intersect, setdiff, setequal, union
                library(lubridate)
                #>
                #> Attaching package: 'lubridate'
                #> The following object is masked from 'package:base':
                #>
                #> date

                date.depature <- c("2016.06.16", "2016.11.16", "2017.01.05", "2017.01.12", "2017.02.25")
                airport.departure <- c("CDG", "QNY", "QXO", "CDG", "QNY")
                airport.arrival <- c("SYD", "CDG", "QNY", "SYD", "QXO")
                amount <- c("1", "3", "1", "10", "5")
                date.depature <- as_date(date.depature)
                df <- data.frame(date.depature, airport.departure, airport.arrival, amount)

                # For 2017
                df %>%
                filter(year(date.depature) == 2017) %>%
                xtabs(as.integer(amount) ~ airport.arrival + airport.departure, .)
                #> airport.departure
                #> airport.arrival CDG QNY QXO
                #> CDG 0 0 0
                #> QNY 0 0 1
                #> QXO 0 4 0
                #> SYD 2 0 0

                # 2017.01
                df %>%
                filter(year(date.depature) == 2017, month(date.depature) == 1) %>%
                xtabs(as.integer(amount) ~ airport.arrival + airport.departure, .)
                #> airport.departure
                #> airport.arrival CDG QNY QXO
                #> CDG 0 0 0
                #> QNY 0 0 1
                #> QXO 0 0 0
                #> SYD 2 0 0

                # until 2017.01
                df %>%
                filter(date.depature <= as_date("2017.01.01")) %>%
                xtabs(as.integer(amount) ~ airport.arrival + airport.departure, .)
                #> airport.departure
                #> airport.arrival CDG QNY QXO
                #> CDG 0 3 0
                #> QNY 0 0 0
                #> QXO 0 0 0
                #> SYD 1 0 0


                Created on 2018-11-19 by the reprex package (v0.2.1)






                share|improve this answer


























                  0












                  0








                  0







                  Since you're already using lubridate, I'm going to show you an approach using dplyr (part of the tidyverse alongside lubridate).



                  The solutions all apply. filter alongside month, year and as_date functions from lubridate to create conditions to filter your data, then use the pipe %>% to pass that long to xtabs





                  library(dplyr)
                  #>
                  #> Attaching package: 'dplyr'
                  #> The following objects are masked from 'package:stats':
                  #>
                  #> filter, lag
                  #> The following objects are masked from 'package:base':
                  #>
                  #> intersect, setdiff, setequal, union
                  library(lubridate)
                  #>
                  #> Attaching package: 'lubridate'
                  #> The following object is masked from 'package:base':
                  #>
                  #> date

                  date.depature <- c("2016.06.16", "2016.11.16", "2017.01.05", "2017.01.12", "2017.02.25")
                  airport.departure <- c("CDG", "QNY", "QXO", "CDG", "QNY")
                  airport.arrival <- c("SYD", "CDG", "QNY", "SYD", "QXO")
                  amount <- c("1", "3", "1", "10", "5")
                  date.depature <- as_date(date.depature)
                  df <- data.frame(date.depature, airport.departure, airport.arrival, amount)

                  # For 2017
                  df %>%
                  filter(year(date.depature) == 2017) %>%
                  xtabs(as.integer(amount) ~ airport.arrival + airport.departure, .)
                  #> airport.departure
                  #> airport.arrival CDG QNY QXO
                  #> CDG 0 0 0
                  #> QNY 0 0 1
                  #> QXO 0 4 0
                  #> SYD 2 0 0

                  # 2017.01
                  df %>%
                  filter(year(date.depature) == 2017, month(date.depature) == 1) %>%
                  xtabs(as.integer(amount) ~ airport.arrival + airport.departure, .)
                  #> airport.departure
                  #> airport.arrival CDG QNY QXO
                  #> CDG 0 0 0
                  #> QNY 0 0 1
                  #> QXO 0 0 0
                  #> SYD 2 0 0

                  # until 2017.01
                  df %>%
                  filter(date.depature <= as_date("2017.01.01")) %>%
                  xtabs(as.integer(amount) ~ airport.arrival + airport.departure, .)
                  #> airport.departure
                  #> airport.arrival CDG QNY QXO
                  #> CDG 0 3 0
                  #> QNY 0 0 0
                  #> QXO 0 0 0
                  #> SYD 1 0 0


                  Created on 2018-11-19 by the reprex package (v0.2.1)






                  share|improve this answer













                  Since you're already using lubridate, I'm going to show you an approach using dplyr (part of the tidyverse alongside lubridate).



                  The solutions all apply. filter alongside month, year and as_date functions from lubridate to create conditions to filter your data, then use the pipe %>% to pass that long to xtabs





                  library(dplyr)
                  #>
                  #> Attaching package: 'dplyr'
                  #> The following objects are masked from 'package:stats':
                  #>
                  #> filter, lag
                  #> The following objects are masked from 'package:base':
                  #>
                  #> intersect, setdiff, setequal, union
                  library(lubridate)
                  #>
                  #> Attaching package: 'lubridate'
                  #> The following object is masked from 'package:base':
                  #>
                  #> date

                  date.depature <- c("2016.06.16", "2016.11.16", "2017.01.05", "2017.01.12", "2017.02.25")
                  airport.departure <- c("CDG", "QNY", "QXO", "CDG", "QNY")
                  airport.arrival <- c("SYD", "CDG", "QNY", "SYD", "QXO")
                  amount <- c("1", "3", "1", "10", "5")
                  date.depature <- as_date(date.depature)
                  df <- data.frame(date.depature, airport.departure, airport.arrival, amount)

                  # For 2017
                  df %>%
                  filter(year(date.depature) == 2017) %>%
                  xtabs(as.integer(amount) ~ airport.arrival + airport.departure, .)
                  #> airport.departure
                  #> airport.arrival CDG QNY QXO
                  #> CDG 0 0 0
                  #> QNY 0 0 1
                  #> QXO 0 4 0
                  #> SYD 2 0 0

                  # 2017.01
                  df %>%
                  filter(year(date.depature) == 2017, month(date.depature) == 1) %>%
                  xtabs(as.integer(amount) ~ airport.arrival + airport.departure, .)
                  #> airport.departure
                  #> airport.arrival CDG QNY QXO
                  #> CDG 0 0 0
                  #> QNY 0 0 1
                  #> QXO 0 0 0
                  #> SYD 2 0 0

                  # until 2017.01
                  df %>%
                  filter(date.depature <= as_date("2017.01.01")) %>%
                  xtabs(as.integer(amount) ~ airport.arrival + airport.departure, .)
                  #> airport.departure
                  #> airport.arrival CDG QNY QXO
                  #> CDG 0 3 0
                  #> QNY 0 0 0
                  #> QXO 0 0 0
                  #> SYD 1 0 0


                  Created on 2018-11-19 by the reprex package (v0.2.1)







                  share|improve this answer












                  share|improve this answer



                  share|improve this answer










                  answered Nov 19 '18 at 17:37









                  Jake KauppJake Kaupp

                  5,62721428




                  5,62721428

























                      0














                      Why don't you coerce amount to class "integer" when you create df? Just get rid of the double quotes in



                      amount <- c("1", "3", "1", "10", "5")


                      or



                      amount <- as.integer(c("1", "3", "1", "10", "5"))


                      This is because as.integer(df$amount) does not return



                      c(1, 3, 1, 10, 5)


                      When you create the dataframe df that vector is coerced to class "factor" and what you now have is



                      as.integer(df$amount)
                      #[1] 1 3 1 2 4


                      The right way would be



                      as.integer(as.character(df$amount))
                      #[1] 1 3 1 10 5


                      Or more simply:



                      date.depature <- c("2016.06.16", "2016.11.16", "2017.01.05", "2017.01.12", "2017.02.25")
                      airport.departure <- c("CDG", "QNY", "QXO", "CDG", "QNY")
                      airport.arrival <- c("SYD", "CDG", "QNY", "SYD", "QXO")
                      amount <- c(1, 3, 1, 10, 5)
                      date.depature <- as_date(date.depature)
                      df <- data.frame(date.depature, airport.departure, airport.arrival, amount)


                      Now the question.



                      This is basically a subsetting problem.

                      Subset the data extracting the years and months you want then run the same xtabs command.



                      df1 <- df[year(df$date.depature) == 2017, ]
                      df2 <- df1[month(df1$date.depature) == 1, ]
                      df3 <- cbind(df[year(df$date.depature) < 2017, ], df2)


                      Now xtabs, with the sub-dataframes above.



                      xtabs(amount ~ airport.arrival + airport.departure, df1)
                      xtabs(amount ~ airport.arrival + airport.departure, df2)
                      xtabs(amount ~ airport.arrival + airport.departure, df3)





                      share|improve this answer
























                      • Thank you a lot for explaining the integer-problem to me. I was not aware of that.

                        – Confusulum
                        Nov 20 '18 at 9:57
















                      0














                      Why don't you coerce amount to class "integer" when you create df? Just get rid of the double quotes in



                      amount <- c("1", "3", "1", "10", "5")


                      or



                      amount <- as.integer(c("1", "3", "1", "10", "5"))


                      This is because as.integer(df$amount) does not return



                      c(1, 3, 1, 10, 5)


                      When you create the dataframe df that vector is coerced to class "factor" and what you now have is



                      as.integer(df$amount)
                      #[1] 1 3 1 2 4


                      The right way would be



                      as.integer(as.character(df$amount))
                      #[1] 1 3 1 10 5


                      Or more simply:



                      date.depature <- c("2016.06.16", "2016.11.16", "2017.01.05", "2017.01.12", "2017.02.25")
                      airport.departure <- c("CDG", "QNY", "QXO", "CDG", "QNY")
                      airport.arrival <- c("SYD", "CDG", "QNY", "SYD", "QXO")
                      amount <- c(1, 3, 1, 10, 5)
                      date.depature <- as_date(date.depature)
                      df <- data.frame(date.depature, airport.departure, airport.arrival, amount)


                      Now the question.



                      This is basically a subsetting problem.

                      Subset the data extracting the years and months you want then run the same xtabs command.



                      df1 <- df[year(df$date.depature) == 2017, ]
                      df2 <- df1[month(df1$date.depature) == 1, ]
                      df3 <- cbind(df[year(df$date.depature) < 2017, ], df2)


                      Now xtabs, with the sub-dataframes above.



                      xtabs(amount ~ airport.arrival + airport.departure, df1)
                      xtabs(amount ~ airport.arrival + airport.departure, df2)
                      xtabs(amount ~ airport.arrival + airport.departure, df3)





                      share|improve this answer
























                      • Thank you a lot for explaining the integer-problem to me. I was not aware of that.

                        – Confusulum
                        Nov 20 '18 at 9:57














                      0












                      0








                      0







                      Why don't you coerce amount to class "integer" when you create df? Just get rid of the double quotes in



                      amount <- c("1", "3", "1", "10", "5")


                      or



                      amount <- as.integer(c("1", "3", "1", "10", "5"))


                      This is because as.integer(df$amount) does not return



                      c(1, 3, 1, 10, 5)


                      When you create the dataframe df that vector is coerced to class "factor" and what you now have is



                      as.integer(df$amount)
                      #[1] 1 3 1 2 4


                      The right way would be



                      as.integer(as.character(df$amount))
                      #[1] 1 3 1 10 5


                      Or more simply:



                      date.depature <- c("2016.06.16", "2016.11.16", "2017.01.05", "2017.01.12", "2017.02.25")
                      airport.departure <- c("CDG", "QNY", "QXO", "CDG", "QNY")
                      airport.arrival <- c("SYD", "CDG", "QNY", "SYD", "QXO")
                      amount <- c(1, 3, 1, 10, 5)
                      date.depature <- as_date(date.depature)
                      df <- data.frame(date.depature, airport.departure, airport.arrival, amount)


                      Now the question.



                      This is basically a subsetting problem.

                      Subset the data extracting the years and months you want then run the same xtabs command.



                      df1 <- df[year(df$date.depature) == 2017, ]
                      df2 <- df1[month(df1$date.depature) == 1, ]
                      df3 <- cbind(df[year(df$date.depature) < 2017, ], df2)


                      Now xtabs, with the sub-dataframes above.



                      xtabs(amount ~ airport.arrival + airport.departure, df1)
                      xtabs(amount ~ airport.arrival + airport.departure, df2)
                      xtabs(amount ~ airport.arrival + airport.departure, df3)





                      share|improve this answer













                      Why don't you coerce amount to class "integer" when you create df? Just get rid of the double quotes in



                      amount <- c("1", "3", "1", "10", "5")


                      or



                      amount <- as.integer(c("1", "3", "1", "10", "5"))


                      This is because as.integer(df$amount) does not return



                      c(1, 3, 1, 10, 5)


                      When you create the dataframe df that vector is coerced to class "factor" and what you now have is



                      as.integer(df$amount)
                      #[1] 1 3 1 2 4


                      The right way would be



                      as.integer(as.character(df$amount))
                      #[1] 1 3 1 10 5


                      Or more simply:



                      date.depature <- c("2016.06.16", "2016.11.16", "2017.01.05", "2017.01.12", "2017.02.25")
                      airport.departure <- c("CDG", "QNY", "QXO", "CDG", "QNY")
                      airport.arrival <- c("SYD", "CDG", "QNY", "SYD", "QXO")
                      amount <- c(1, 3, 1, 10, 5)
                      date.depature <- as_date(date.depature)
                      df <- data.frame(date.depature, airport.departure, airport.arrival, amount)


                      Now the question.



                      This is basically a subsetting problem.

                      Subset the data extracting the years and months you want then run the same xtabs command.



                      df1 <- df[year(df$date.depature) == 2017, ]
                      df2 <- df1[month(df1$date.depature) == 1, ]
                      df3 <- cbind(df[year(df$date.depature) < 2017, ], df2)


                      Now xtabs, with the sub-dataframes above.



                      xtabs(amount ~ airport.arrival + airport.departure, df1)
                      xtabs(amount ~ airport.arrival + airport.departure, df2)
                      xtabs(amount ~ airport.arrival + airport.departure, df3)






                      share|improve this answer












                      share|improve this answer



                      share|improve this answer










                      answered Nov 19 '18 at 17:36









                      Rui BarradasRui Barradas

                      16.8k51730




                      16.8k51730













                      • Thank you a lot for explaining the integer-problem to me. I was not aware of that.

                        – Confusulum
                        Nov 20 '18 at 9:57



















                      • Thank you a lot for explaining the integer-problem to me. I was not aware of that.

                        – Confusulum
                        Nov 20 '18 at 9:57

















                      Thank you a lot for explaining the integer-problem to me. I was not aware of that.

                      – Confusulum
                      Nov 20 '18 at 9:57





                      Thank you a lot for explaining the integer-problem to me. I was not aware of that.

                      – Confusulum
                      Nov 20 '18 at 9:57











                      0














                      You need to subset date.departure in your xtabs call. For year == 2017:



                      xtabs(as.integer(amount) ~ airport.arrival + airport.departure, df[year(df$date.depature)==2017,])


                      For year==2017 and month==1:



                      xtabs(as.integer(amount) ~ airport.arrival + airport.departure, df[year(df$date.depature)==2017 & month(df$date.departure)==1,])


                      And for anything before Jan 2017:



                      xtabs(as.integer(amount) ~ airport.arrival + airport.departure, df[df$date.depature<as_date("2017-01-01"),])





                      share|improve this answer




























                        0














                        You need to subset date.departure in your xtabs call. For year == 2017:



                        xtabs(as.integer(amount) ~ airport.arrival + airport.departure, df[year(df$date.depature)==2017,])


                        For year==2017 and month==1:



                        xtabs(as.integer(amount) ~ airport.arrival + airport.departure, df[year(df$date.depature)==2017 & month(df$date.departure)==1,])


                        And for anything before Jan 2017:



                        xtabs(as.integer(amount) ~ airport.arrival + airport.departure, df[df$date.depature<as_date("2017-01-01"),])





                        share|improve this answer


























                          0












                          0








                          0







                          You need to subset date.departure in your xtabs call. For year == 2017:



                          xtabs(as.integer(amount) ~ airport.arrival + airport.departure, df[year(df$date.depature)==2017,])


                          For year==2017 and month==1:



                          xtabs(as.integer(amount) ~ airport.arrival + airport.departure, df[year(df$date.depature)==2017 & month(df$date.departure)==1,])


                          And for anything before Jan 2017:



                          xtabs(as.integer(amount) ~ airport.arrival + airport.departure, df[df$date.depature<as_date("2017-01-01"),])





                          share|improve this answer













                          You need to subset date.departure in your xtabs call. For year == 2017:



                          xtabs(as.integer(amount) ~ airport.arrival + airport.departure, df[year(df$date.depature)==2017,])


                          For year==2017 and month==1:



                          xtabs(as.integer(amount) ~ airport.arrival + airport.departure, df[year(df$date.depature)==2017 & month(df$date.departure)==1,])


                          And for anything before Jan 2017:



                          xtabs(as.integer(amount) ~ airport.arrival + airport.departure, df[df$date.depature<as_date("2017-01-01"),])






                          share|improve this answer












                          share|improve this answer



                          share|improve this answer










                          answered Nov 19 '18 at 17:37









                          iodiod

                          3,8332722




                          3,8332722






























                              draft saved

                              draft discarded




















































                              Thanks for contributing an answer to Stack Overflow!


                              • Please be sure to answer the question. Provide details and share your research!

                              But avoid



                              • Asking for help, clarification, or responding to other answers.

                              • Making statements based on opinion; back them up with references or personal experience.


                              To learn more, see our tips on writing great answers.




                              draft saved


                              draft discarded














                              StackExchange.ready(
                              function () {
                              StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53379735%2fhow-to-use-date-as-filter%23new-answer', 'question_page');
                              }
                              );

                              Post as a guest















                              Required, but never shown





















































                              Required, but never shown














                              Required, but never shown












                              Required, but never shown







                              Required, but never shown

































                              Required, but never shown














                              Required, but never shown












                              Required, but never shown







                              Required, but never shown







                              Popular posts from this blog

                              Guess what letter conforming each word

                              Port of Spain

                              Run scheduled task as local user group (not BUILTIN)