Início / user-17621438

Ryan Gary's questions

Martin Hope
Ryan Gary
Asked: 2025-04-16 01:10:34 +0800 CST
  • 6

Tenho um dataframe parecido com este:

data pesca dia_do_torneio pescador período_ffs usados_ffs
30/01/2025 Lago Conroe 1 Vila Martin P1 verdadeiro
31/01/2025 Lago Conroe 2 Vila Martin P2 verdadeiro
2025-02-1 Lago Conroe 3 Vila Martin P1 verdadeiro
2025-02-13 Corrente Harris 1 Vila Martin P3 verdadeiro 
structure(list(date = structure(c(1738195200, 1738281600, 1738368000, 
1739404800, 1741219200, 1741305600, 1743638400, 1743724800, 1743811200
), tzone = "UTC", class = c("POSIXct", "POSIXt")), fishery = c("Lake Conroe", 
"Lake Conroe", "Lake Conroe", "Harris Chain", "Lake Murray", 
"Lake Murray", "Lake Guntersville", "Lake Guntersville", "Lake Guntersville"
), tournament_day = c(1, 2, 3, 1, 1, 2, 1, 2, 3), angler = c("Martin Villa", 
"Martin Villa", "Martin Villa", "Martin Villa", "Martin Villa", 
"Martin Villa", "Martin Villa", "Martin Villa", "Martin Villa"
), ffs_period = c("P1", "P2", "P1", "P3", "P1", "P1", "P3", "P2", 
"P1"), used_ffs = c(TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, 
TRUE, TRUE)), row.names = c(NA, -9L), class = c("tbl_df", "tbl", 
"data.frame"))

Meu problema é que existem 3 observações "ffs_period" para cada data única: P1, P2, P3. Só tenho dados para a observação "used_ffs" que é "TRUE". Para as duas observações adicionais para cada data, pescaria, dia do torneio e pescador, preciso preencher as duas linhas restantes com "ffs_period" e "used_ffs", que não estão presentes. Por exemplo, a primeira observação em que "ffs_period" é P1 e "used_ffs" é TRUE, eu precisaria preencher duas linhas com a mesma data, pescaria, dia do torneio e pescador, em que "ffs_period" é P2 e P3 e used_ffs é FALSE para ambos. O resultado final seria assim:

data pesca dia_do_torneio pescador período_ffs usados_ffs
30/01/2025 Lago Conroe 1 Vila Martin P1 verdadeiro
30/01/2025 Lago Conroe 1 Vila Martin P2 FALSO
30/01/2025 Lago Conroe 1 Vila Martin P3 FALSO
31/01/2025 Lago Conroe 2 Vila Martin P1 FALSO
31/01/2025 Lago Conroe 2 Vila Martin P2 verdadeiro
31/01/2025 Lago Conroe 2 Vila Martin P3 FALSO
2025-02-1 Lago Conroe 3 Vila Martin P1 verdadeiro
2025-02-1 Lago Conroe 3 Vila Martin P2 FALSO
2025-02-1 Lago Conroe 3 Vila Martin P3 FALSO
2025-02-13 Corrente Harris 1 Vila Martin P1 FALSO
2025-02-13 Corrente Harris 1 Vila Martin P2 FALSO
2025-02-13 Corrente Harris 1 Vila Martin P3 verdadeiro

Isso é possível? Ou é muito complicado?

Martin Hope
Ryan Gary
Asked: 2024-08-21 23:10:37 +0800 CST
  • 5

Eu tenho um quadro de dados parecido com este:

structure(list(datetime = structure(c(1559347200, 1559350800, 
1559354400, 1559358000, 1559361600, 1559365200, 1559368800, 1559372400, 
1559376000, 1559379600), tzone = "UTC", class = c("POSIXct", 
"POSIXt")), BUSwt = c(77.8154, 77.2538, 76.9325, 76.81235, 76.6544, 
76.3403, 76.16165, 76.22375, 76.47035, 76.74395), MBwt = c(78.3653, 
78.53495, 78.6074, 78.30725, 78.0368, 77.9477, 77.8946, 77.927, 
78.12455, 78.23615), SUSwt = c(76.2575, 76.0055, 75.7265, 75.425, 
75.137, 74.849, 74.651, 74.624, 74.696, 74.8535)), row.names = c(NA, 
-10L), class = c("tbl_df", "tbl", "data.frame"))

Possui 5 anos de dados de data e hora para as três colunas variáveis ​​"BUSwt", "MBwt" e "SUSwt". Quero calcular a média, o mínimo e o máximo dessas variáveis ​​para cada data e hora específicas ao longo dos 5 anos de dados. Um exemplo desses dados seria:

datahora BUSwt_mean BUSwt_max BUSwt_min MBwt_mean MBwt_max MBwt_min SUSwt_mean SUSwt_max SUSwt_min
06-01 00:00:00 xx xx xx xx xx xx xx xx xx
06-01 01:00:00 xx xx xx xx xx xx xx xx xx
06-01 02:00:00 xx xx xx xx xx xx xx xx xx
06-01 03:00:00 xx xx xx xx xx xx xx xx xx
06-01 04:00:00 xx xx xx xx xx xx xx xx xx

Meu código atual para criar o quadro de dados é assim:

WaterData <- BUSdata %>%
  left_join(MBdata, by = "datetime") %>%
  left_join(SUSdata, by = "datetime")

Existe uma maneira de fazer isso continuando em um cano?

Martin Hope
Ryan Gary
Asked: 2024-07-27 00:08:48 +0800 CST
  • 5

Este é um subconjunto do dataframe que tenho:

structure(list(name = c("waldorf", "waldorf", "waldorf", "waldorf", 
"waldorf", "waldorf", "waldorf", "waldorf", "waldorf", "waldorf", 
"waldorf", "waldorf", "waldorf", "waldorf", "waldorf", "waldorf", 
"waldorf", "waldorf", "waldorf", "waldorf", "waldorf", "waldorf", 
"waldorf", "waldorf"), date = structure(c(1559347200, 1559347200, 
1559347200, 1559347200, 1559347200, 1559347200, 1559347200, 1559347200, 
1559347200, 1559347200, 1559347200, 1559347200, 1559347200, 1559347200, 
1559347200, 1559347200, 1559347200, 1559347200, 1559347200, 1559347200, 
1559347200, 1559347200, 1559347200, 1559347200), tzone = "UTC", class = c("POSIXct", 
"POSIXt")), time = structure(c(0, 3600, 7200, 10800, 14400, 18000, 
21600, 25200, 28800, 32400, 36000, 39600, 43200, 46800, 50400, 
54000, 57600, 61200, 64800, 68400, 72000, 75600, 79200, 82800
), class = c("hms", "difftime"), units = "secs"), datetime = structure(c(1559347200, 
1559350800, 1559354400, 1559358000, 1559361600, 1559365200, 1559368800, 
1559372400, 1559376000, 1559379600, 1559383200, 1559386800, 1559390400, 
1559394000, 1559397600, 1559401200, 1559404800, 1559408400, 1559412000, 
1559415600, 1559419200, 1559422800, 1559426400, 1559430000), tzone = "UTC", class = c("POSIXct", 
"POSIXt")), temp = c(72.9, 70.6, 69.7, 69.6, 68, 68.1, 67.9, 
67.8, 69.6, 71.9, 75.6, 78.3, 80.1, 80.8, 82.8, 83.5, 83.3, 82.9, 
81.5, 79.4, 77.6, 72.4, 70.6, 69.8)), row.names = c(NA, -24L), class = c("tbl_df", 
"tbl", "data.frame"))

O quadro de dados expandido contém dados de temperatura por hora durante 5 anos de dias. Como posso usar a data e hora ou as outras colunas para calcular a temperatura média das 13h às 17h para cada dia no quadro de dados? Posso fazer isso em uma string dplyr?

Martin Hope
Ryan Gary
Asked: 2024-05-10 23:30:21 +0800 CST
  • 5

Eu tenho dois quadros de dados de comprimento desigual, um quadro de dados contém um subconjunto de datas do primeiro quadro de dados e cada um deles tem colunas diferentes:

Quadro de dados 1:

structure(list(date = structure(c(19241, 19249, 19252, 19255, 
19259, 19260, 19268, 19286, 19288, 19290, 19294, 19302, 19306, 
19307, 19310, 19315, 19318, 19330, 19332, 19334, 19341, 19343, 
19344, 19363, 19365, 19367, 19373, 19382, 19385, 19400, 19405, 
19406, 19408, 19410, 19415, 19418, 19421, 19435, 19438, 19441, 
19444, 19449, 19454, 19463, 19467, 19468, 19476, 19480, 19494, 
19497, 19498, 19500, 19504, 19507, 19512, 19519, 19523, 19525, 
19535, 19546, 19547, 19550, 19557, 19560, 19565, 19585, 19587, 
19588, 19589, 19592, 19595), class = "Date"), month = c(9, 9, 
9, 9, 9, 9, 10, 10, 10, 10, 10, 11, 11, 11, 11, 11, 11, 12, 12, 
12, 12, 12, 12, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 3, 3, 3, 
3, 3, 3, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 
7, 7, 7, 7, 7, 7, 8, 8, 8, 8, 8, 8), season = c("Fall", "Fall", 
"Fall", "Fall", "Fall", "Fall", "Fall", "Fall", "Fall", "Fall", 
"Fall", "Fall", "Fall", "Fall", "Fall", "Fall", "Fall", "Winter", 
"Winter", "Winter", "Winter", "Winter", "Winter", "Winter", "Winter", 
"Winter", "Winter", "Winter", "Winter", "Winter", "Winter", "Winter", 
"Winter", "Winter", "Winter", "Spring", "Spring", "Spring", "Spring", 
"Spring", "Spring", "Spring", "Spring", "Spring", "Spring", "Spring", 
"Spring", "Spring", "Spring", "Spring", "Spring", "Spring", "Spring", 
"Spring", "Summer", "Summer", "Summer", "Summer", "Summer", "Summer", 
"Summer", "Summer", "Summer", "Summer", "Summer", "Summer", "Summer", 
"Summer", "Summer", "Summer", "Summer"), daytype = c("Weekday", 
"Weekday", "Weekend/Holiday", "Weekday", "Weekend/Holiday", "Weekend/Holiday", 
"Weekend/Holiday", "Weekday", "Weekend/Holiday", "Weekday", "Weekend/Holiday", 
"Weekend/Holiday", "Weekday", "Weekend/Holiday", "Weekday", "Weekend/Holiday", 
"Weekday", "Weekend/Holiday", "Weekday", "Weekday", "Weekday", 
"Weekend/Holiday", "Weekend/Holiday", "Weekday", "Weekend/Holiday", 
"Weekday", "Weekday", "Weekday", "Weekend/Holiday", "Weekend/Holiday", 
"Weekday", "Weekend/Holiday", "Weekday", "Weekday", "Weekday", 
"Weekday", "Weekend/Holiday", "Weekend/Holiday", "Weekday", "Weekend/Holiday", 
"Weekday", "Weekend/Holiday", "Weekday", "Weekend/Holiday", "Weekday", 
"Weekday", "Weekend/Holiday", "Weekday", "Weekday", "Weekend/Holiday", 
"Weekend/Holiday", "Weekday", "Weekend/Holiday", "Weekday", "Weekend/Holiday", 
"Weekend/Holiday", "Weekday", "Weekend/Holiday", "Weekday", "Weekend/Holiday", 
"Weekend/Holiday", "Weekday", "Weekday", "Weekend/Holiday", "Weekday", 
"Weekday", "Weekday", "Weekend/Holiday", "Weekend/Holiday", "Weekday", 
"Weekend/Holiday"), total_effort_mean = c(0, 0, 4.11092592592593, 
0, 0, 0, 0, 0, 0, 0, 0, 7.09981481481481, 7.02314814814815, 42.0277777777778, 
0, 0, 17.0518518518519, 3.3362962962963, 6.65444444444444, 0, 
0, 0, 3.295, 9.98138888888889, 30.0266666666667, 0, 0, 0, 6.95314814814815, 
18.1203703703704, 33.1041666666667, 81.1657407407407, 44.5388888888889, 
3.73407407407407, 11.3738888888889, 0, 15.4440740740741, 4.02666666666667, 
12.1866666666667, 45.0765740740741, 12.4, 71.2662037037037, 29.7519444444444, 
34.8207407407407, 13.1905555555556, 0, 0, 4.53222222222222, 0, 
0, 9.37611111111111, 0, 28.37, 0, 0, 0, 0, 0, 28.8261111111111, 
0, 0, 0, 0, 9.38574074074074, 0, 0, 0, 0, 0, 0, 0)), class = c("grouped_df", 
"tbl_df", "tbl", "data.frame"), row.names = c(NA, -71L), groups = structure(list(
    date = structure(c(19241, 19249, 19252, 19255, 19259, 19260, 
    19268, 19286, 19288, 19290, 19294, 19302, 19306, 19307, 19310, 
    19315, 19318, 19330, 19332, 19334, 19341, 19343, 19344, 19363, 
    19365, 19367, 19373, 19382, 19385, 19400, 19405, 19406, 19408, 
    19410, 19415, 19418, 19421, 19435, 19438, 19441, 19444, 19449, 
    19454, 19463, 19467, 19468, 19476, 19480, 19494, 19497, 19498, 
    19500, 19504, 19507, 19512, 19519, 19523, 19525, 19535, 19546, 
    19547, 19550, 19557, 19560, 19565, 19585, 19587, 19588, 19589, 
    19592, 19595), class = "Date"), .rows = structure(list(1L, 
        2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 
        15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 
        26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 
        37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 
        48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 
        59L, 60L, 61L, 62L, 63L, 64L, 65L, 66L, 67L, 68L, 69L, 
        70L, 71L), ptype = integer(0), class = c("vctrs_list_of", 
    "vctrs_vctr", "list"))), class = c("tbl_df", "tbl", "data.frame"
), row.names = c(NA, -71L), .drop = TRUE))

Quadro de dados 2:

structure(list(date = structure(c(19306, 19307, 19318, 19332, 
19363, 19400, 19405, 19406, 19408, 19415, 19421, 19438, 19441, 
19444, 19449, 19454, 19467, 19498, 19535, 19560), class = "Date"), 
    kCPUE_mean = c(1.6491067338525, 0.413793103448276, 0, 0.536672629695885, 
    0, 0, 0.290541824256615, 0.206362854686156, 0.217817454360528, 
    0, 0.923530060205667, 1.59412955465587, 0.4085480691282, 
    0, 0, 4.97787610619469, 0.910815939278937, 0, 0, 0), rCPUE_mean = c(0, 
    0, 0.37344398340249, 0, 0.300651411391348, 0, 0.0562148657089319, 
    0, 0, 1.05324751316559, 0, 1.59412955465587, 0, 3.46699352127473, 
    4.17056683136478, 0, 0, 0, 0, 0), cCPUE_mean = c(1.6491067338525, 
    0.413793103448276, 0.37344398340249, 0.536672629695885, 0.300651411391348, 
    0, 0.346756689965547, 0.206362854686156, 0.217817454360528, 
    1.05324751316559, 0.923530060205667, 3.18825910931174, 0.4085480691282, 
    3.46699352127473, 4.17056683136478, 4.97787610619469, 0.910815939278937, 
    0, 0, 0)), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, 
-20L))

Gostaria de mesclar esses quadros de dados, mas onde não houver observação de uma data no quadro de dados 2, gostaria que os valores de kCPUE_mean, rCPUE_mean e cCPUE_mean fossem 0. Isso é possível com código? Isso também poderia ser feito em um tubo dplyr?

Martin Hope
Ryan Gary
Asked: 2023-10-25 03:27:45 +0800 CST
  • 5

Eu tenho um dataframe parecido com este:

structure(list(Date = structure(c(18876, 18878, 18876, 18878, 
18876, 18878), class = "Date"), effort = c(2371.5, 1950.66666666667, 
6107.25, 3318.66666666667, 4154.83867521367, 2073.10096153846
), type = c("aerial", "aerial", "TLAcmeth", "TLAcmeth", "TLAmeandaily", 
"TLAmeandaily")), row.names = c(NA, -6L), class = c("tbl_df", 
"tbl", "data.frame"))

Como posso transpor esse data frame para ter quatro colunas uma para a data e uma para cada "tipo", deve ficar assim:

Data aéreo TLAcmeth TLAmeandaily
06/09/2021 2371,5 6107.25 4154.839
08/09/2021 1950.667 3318.667 2073.101
Martin Hope
Ryan Gary
Asked: 2023-10-10 23:29:13 +0800 CST
  • 6

Eu tenho um dataframe parecido com este:

structure(list(Date = structure(c(1630544400, 1630548000, 1630551600, 
1630555200, 1630558800, 1630562400, 1630566000, 1630569600, 1630573200, 
1630576800, 1630580400, 1630630800, 1630634400, 1630638000, 1630641600, 
1630645200, 1630648800, 1630652400, 1630656000, 1630659600), tzone = "America/Chicago", class = c("POSIXct", 
"POSIXt")), daytime = c("Night", "Night", "Night", "Night", "Morning", 
"Morning", "Morning", "Morning", "Morning", "Morning", "Morning", 
"Night", "Night", "Night", "Night", "Morning", "Morning", "Morning", 
"Morning", "Morning")), row.names = c(NA, -20L), class = c("tbl_df", 
"tbl", "data.frame"))

Gostaria de criar outra coluna para agrupar a noite e a manhã sequencialmente para que a saída ficasse assim:

   Date                daytime        nightcount
   <dttm>              <chr>          <dbl>
 1 2021-09-01 20:00:00 Night            1
 2 2021-09-01 21:00:00 Night            1  
 3 2021-09-01 22:00:00 Night            1
 4 2021-09-01 23:00:00 Night            1
 5 2021-09-02 00:00:00 Morning          1
 6 2021-09-02 01:00:00 Morning          1
 7 2021-09-02 02:00:00 Morning          1
 8 2021-09-02 03:00:00 Morning          1
 9 2021-09-02 04:00:00 Morning          1
10 2021-09-02 05:00:00 Morning          1
11 2021-09-02 06:00:00 Morning          1
12 2021-09-02 20:00:00 Night            2
13 2021-09-02 21:00:00 Night            2  
14 2021-09-02 22:00:00 Night            2
15 2021-09-02 23:00:00 Night            2  
16 2021-09-03 00:00:00 Morning          2
17 2021-09-03 01:00:00 Morning          2
18 2021-09-03 02:00:00 Morning          2
19 2021-09-03 03:00:00 Morning          2
20 2021-09-03 04:00:00 Morning          2

Existe uma solução fácil para isso usando dplyr?