Combine the fid_monitor, station_monitor, and table_monitor functions together.
monitor_all(data, begin_date, house_width = "1", days, save_path)data.frame, required. The input data frame containing the data to be processed.
An optional Date object or character string specifying the beginning date for the data to be processed. If not provided, all dates in the data will be considered.
character, optional. A character string representing the house width. Default is "1".
integer, optional. An integer representing the number of days for the analysis.
character, required. A character string representing the path where the output file will be saved.
# Load CSV data
data <- data.table::fread("C:/Users/Dell/Documents/projects/pptsdm_data/ppt_monitor_test_data.csv")
monitor_all(data, begin_date = "2024-05-01", days = 5, save_path = "C:/Users/Dell/Downloads/test")
#> Warning: Removed 2 rows containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 2 rows containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 3 rows containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 3 rows containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 2 rows containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 3 rows containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).
#> $responder_na
#> location 06-03 06-04 06-05 06-06 06-07 total_nas
#> <char> <int> <int> <int> <int> <int> <num>
#> 1: 501 0 0 0 0 0 0
#> 2: 502 2 1 1 3 2 9
#> 3: 503 0 2 2 0 0 4
#> 4: 504 2 0 2 0 0 4
#> 5: 505 0 0 0 0 0 0
#> 6: 506 0 0 0 0 0 0
#> 7: 507 1 1 1 0 0 3
#> 8: 508 0 0 0 0 1 1
#> 9: 509 0 0 1 0 2 3
#> 10: 510 0 1 2 1 0 4
#>
#> $extreme_weight
#> Key: <location>
#> location 06-03 06-04 06-05 06-06 06-07
#> <int> <num> <num> <num> <num> <num>
#> 1: 501 7.07 4.31 4.12 2.78 5.79
#> 2: 502 5.38 6.86 3.12 6.67 7.32
#> 3: 503 4.82 5.32 6.17 5.19 5.21
#> 4: 504 5.95 3.70 2.41 5.41 3.53
#> 5: 505 1.28 3.37 5.05 4.67 11.30
#> 6: 506 7.69 7.46 4.35 1.28 7.50
#> 7: 507 7.59 3.85 4.29 2.41 8.43
#> 8: 508 1.47 1.37 2.63 1.32 6.10
#> 9: 509 6.84 4.62 4.31 6.78 8.13
#> 10: 510 6.74 3.12 7.58 4.41 8.57
#>
#> $feed_time_n
#> Key: <location>
#> location n_06-03 n_06-04 n_06-05 n_06-06 n_06-07 time_06-03 time_06-04
#> <int> <int> <int> <int> <int> <int> <num> <num>
#> 1: 501 99 116 97 108 121 17.62 18.14
#> 2: 502 93 102 96 75 82 17.24 16.38
#> 3: 503 83 94 81 77 96 18.15 16.92
#> 4: 504 84 81 83 74 85 18.61 17.66
#> 5: 505 78 89 99 107 115 16.82 17.51
#> 6: 506 65 67 69 78 80 18.65 17.29
#> 7: 507 79 78 70 83 83 17.45 15.67
#> 8: 508 68 73 76 76 82 18.12 17.93
#> 9: 509 117 130 116 118 123 17.97 16.86
#> 10: 510 89 96 66 68 70 19.07 19.84
#> time_06-05 time_06-06 time_06-07
#> <num> <num> <num>
#> 1: 18.64 18.62 18.54
#> 2: 16.92 16.48 16.30
#> 3: 15.49 15.84 15.86
#> 4: 16.87 17.10 16.49
#> 5: 16.73 17.26 16.33
#> 6: 17.48 19.43 18.44
#> 7: 15.85 15.88 16.28
#> 8: 17.49 18.09 17.18
#> 9: 17.39 17.98 16.58
#> 10: 17.89 18.17 17.72
#>
#> $low_feedintake
#> location responder 06-03 06-04 06-05 06-06 06-07 sum_feedintake
#> <int> <int> <num> <num> <num> <num> <num> <num>
#> 1: 507 2315012 NA NA NA 0.029 0.003 0.03
#> 2: 502 NA 0.081 0.046 0.056 0.087 0.027 0.30
#> 3: 510 NA NA 0.048 0.208 0.014 NA 0.27
#> 4: 503 NA NA 0.212 0.022 NA NA 0.23
#> 5: 509 NA NA NA 0.010 NA 0.152 0.16
#> 6: 504 NA 0.026 NA 0.023 NA NA 0.05
#> 7: 507 NA 0.010 0.010 0.010 NA NA 0.03
#> 8: 508 NA NA NA NA NA 0.010 0.01
#>
#> $all_feedintake
#> Key: <location>
#> location 06-03 06-04 06-05 06-06 06-07 all_feedintake
#> <char> <num> <num> <num> <num> <num> <num>
#> 1: 501 41.30 43.52 46.97 45.56 46.34 223.69
#> 2: 502 46.95 46.13 49.73 46.41 50.10 239.32
#> 3: 503 51.22 49.40 47.49 48.06 48.47 244.65
#> 4: 504 48.68 49.71 48.49 48.85 47.98 243.70
#> 5: 505 43.64 46.99 47.73 47.40 44.47 230.23
#> 6: 506 47.60 46.10 45.98 50.43 47.72 237.83
#> 7: 507 44.87 41.04 43.98 43.24 44.58 217.71
#> 8: 508 44.22 45.83 43.71 44.74 43.99 222.50
#> 9: 509 48.30 48.09 51.44 50.91 50.07 248.80
#> 10: 510 43.86 47.92 44.62 44.72 46.01 227.12
#>
#> $mean_feedintake
#> Key: <date>
#> date 5_feed all_feedintake 5_n 5_mean_feed
#> <char> <num> <num> <int> <num>
#> 1: 06-03 460.51 460.51 147 3.13
#> 2: 06-04 464.41 464.41 146 3.18
#> 3: 06-05 469.79 469.79 145 3.24
#> 4: 06-06 470.22 470.22 146 3.22
#> 5: 06-07 469.56 469.56 146 3.22
#>
#> $house_weight
#> Key: <date>
#> date house_5
#> <char> <num>
#> 1: 06-03 75.08
#> 2: 06-04 76.42
#> 3: 06-05 77.64
#> 4: 06-06 79.34
#> 5: 06-07 80.61
#>
#> $visit_n_hour
#> Key: <location>
#> location 0 1 2 3 4 5 6 7 8 9 10
#> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int>
#> 1: 501 3 5 4 4 4 3 4 9 5 5 8
#> 2: 502 4 1 3 4 1 2 4 4 4 4 4
#> 3: 503 2 7 4 3 1 3 3 3 4 2 7
#> 4: 504 4 4 1 5 1 2 3 3 3 5 4
#> 5: 505 5 9 4 3 2 4 4 2 4 5 3
#> 6: 506 3 4 2 3 1 1 3 2 4 2 4
#> 7: 507 4 1 5 3 1 2 3 5 4 3 3
#> 8: 508 5 3 1 4 3 3 3 3 4 2 3
#> 9: 509 3 5 5 1 3 2 2 4 6 4 3
#> 10: 510 3 NA 3 2 3 2 1 3 2 3 3
#> 11 12 13 14 15 16 17 18 19 20 21 22
#> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int>
#> 1: 4 4 6 4 9 10 6 6 4 5 3 2
#> 2: 3 3 4 5 5 5 4 5 5 4 1 5
#> 3: 5 4 4 4 4 5 7 5 4 4 1 6
#> 4: 5 3 5 3 9 4 5 3 4 2 1 3
#> 5: 8 7 6 6 6 7 8 6 4 5 4 1
#> 6: 6 2 4 6 3 5 4 3 3 4 5 5
#> 7: 6 5 7 3 4 5 5 4 4 NA NA 5
#> 8: 5 4 3 3 6 5 4 3 3 4 4 3
#> 9: 8 5 5 10 8 12 4 7 3 7 9 3
#> 10: 3 4 2 3 7 5 3 3 2 3 4 2
#> 23
#> <int>
#> 1: 4
#> 2: NA
#> 3: 4
#> 4: 3
#> 5: 2
#> 6: 1
#> 7: 1
#> 8: 2
#> 9: 6
#> 10: 4
#>
#> $feed_time_hour
#> Key: <location>
#> location 0 1 2 3 4 5 6 7 8 9 10
#> <int> <num> <num> <num> <num> <num> <num> <num> <num> <num> <num> <num>
#> 1: 501 9.57 33.95 48.88 59.77 34.53 36.38 50.50 41.57 52.70 55.47 48.17
#> 2: 502 36.35 12.25 37.57 53.27 11.37 18.67 36.13 62.23 42.80 49.67 48.58
#> 3: 503 18.97 39.23 40.38 21.13 6.62 29.62 50.40 41.62 71.25 23.22 50.48
#> 4: 504 33.45 56.98 7.00 68.78 12.65 25.65 34.40 28.45 36.30 60.68 56.87
#> 5: 505 30.82 34.20 17.30 25.02 18.45 46.52 52.07 21.17 45.72 74.60 44.17
#> 6: 506 66.65 50.72 16.48 31.30 8.08 18.82 58.05 47.10 57.83 46.55 54.50
#> 7: 507 41.03 13.78 51.38 44.87 20.98 28.35 39.22 56.10 45.87 49.72 40.87
#> 8: 508 48.92 21.32 6.23 29.35 47.57 70.88 40.70 41.55 50.60 45.07 34.77
#> 9: 509 31.62 78.10 18.28 13.12 26.80 14.27 27.50 66.20 48.47 56.48 53.45
#> 10: 510 20.72 NA 58.38 30.07 59.98 47.35 12.75 55.05 42.08 57.80 54.02
#> 11 12 13 14 15 16 17 18 19 20 21 22
#> <num> <num> <num> <num> <num> <num> <num> <num> <num> <num> <num> <num>
#> 1: 60.68 48.07 48.53 51.03 52.95 43.55 64.73 60.97 55.23 45.68 49.97 21.82
#> 2: 45.80 25.98 51.55 58.68 61.32 56.58 64.05 47.82 65.83 41.63 6.27 43.73
#> 3: 40.33 21.33 50.57 64.28 55.67 48.55 54.83 62.55 41.50 53.48 5.27 45.27
#> 4: 60.58 41.45 68.10 47.85 44.65 60.88 56.72 51.77 46.52 19.98 4.45 23.38
#> 5: 40.10 48.08 32.12 52.98 57.20 44.18 57.08 67.37 56.15 63.82 33.68 1.47
#> 6: 73.53 50.00 50.40 76.15 42.93 58.73 62.28 56.82 58.42 50.52 42.28 27.53
#> 7: 53.45 39.77 44.08 61.90 59.02 59.58 51.63 63.30 54.67 NA NA 48.00
#> 8: 71.40 58.88 55.20 19.07 56.52 55.00 74.32 52.77 45.13 30.10 28.83 25.30
#> 9: 60.33 32.93 46.25 58.73 50.37 63.55 49.32 70.85 42.20 34.58 34.50 7.27
#> 10: 53.03 79.35 35.85 58.28 66.23 54.53 67.92 48.00 25.55 32.32 40.65 27.12
#> 23
#> <num>
#> 1: 37.85
#> 2: NA
#> 3: 15.00
#> 4: 41.63
#> 5: 15.62
#> 6: 0.83
#> 7: 9.15
#> 8: 21.32
#> 9: 15.37
#> 10: 36.28
#>
#> $feed_intake_hour
#> Key: <location>
#> location 0 1 2 3 4 5 6 7 8 9 10
#> <int> <num> <num> <num> <num> <num> <num> <num> <num> <num> <num> <num>
#> 1: 501 0.40 1.10 2.05 2.18 1.90 1.41 2.23 2.26 1.85 2.29 2.13
#> 2: 502 1.73 0.81 1.80 2.45 0.53 1.00 1.76 3.04 1.86 2.58 2.39
#> 3: 503 0.84 1.90 2.20 1.07 0.31 1.37 2.44 2.53 3.84 1.01 2.41
#> 4: 504 1.32 2.61 0.35 3.07 0.72 1.52 1.75 1.34 1.66 2.63 2.85
#> 5: 505 1.29 1.16 0.56 1.21 0.89 2.02 2.39 0.97 2.24 2.87 2.32
#> 6: 506 2.60 2.15 0.72 1.43 0.47 0.66 2.44 2.02 2.72 2.09 2.13
#> 7: 507 1.73 0.60 2.06 2.28 0.82 1.35 1.88 2.61 1.94 2.10 1.48
#> 8: 508 1.81 0.80 0.19 1.09 2.23 3.16 1.59 1.97 1.99 1.92 1.21
#> 9: 509 1.55 4.37 1.29 0.80 1.32 0.45 1.22 3.39 2.64 2.89 2.88
#> 10: 510 0.82 NA 2.50 1.27 2.87 1.63 0.54 2.55 1.76 2.52 2.54
#> 11 12 13 14 15 16 17 18 19 20 21 22
#> <num> <num> <num> <num> <num> <num> <num> <num> <num> <num> <num> <num>
#> 1: 2.28 1.94 2.48 1.78 2.20 1.51 2.42 2.71 2.80 2.26 2.27 0.80
#> 2: 2.19 1.50 2.63 2.89 2.98 2.89 3.69 2.80 3.33 2.38 0.36 2.50
#> 3: 1.92 1.13 2.52 3.35 3.10 2.25 3.01 3.18 1.96 2.48 0.21 2.52
#> 4: 2.91 2.38 3.44 2.35 2.11 3.10 2.93 2.80 2.17 0.88 0.28 1.02
#> 5: 1.47 2.22 1.67 2.65 2.06 2.15 1.64 3.80 3.38 3.34 1.44 0.08
#> 6: 3.11 1.73 2.24 3.74 1.47 1.79 3.10 2.63 3.00 2.27 1.91 1.30
#> 7: 2.43 2.05 1.60 2.75 2.82 2.41 2.75 3.26 3.07 NA NA 2.02
#> 8: 3.38 2.73 2.04 0.87 2.19 2.23 3.39 2.64 2.18 1.21 1.39 0.84
#> 9: 3.29 1.44 1.73 2.42 2.29 2.67 3.44 3.86 1.83 1.59 1.53 0.40
#> 10: 2.24 3.77 1.20 2.77 2.19 2.42 3.39 2.52 1.06 1.61 1.62 0.91
#> 23
#> <num>
#> 1: 1.07
#> 2: NA
#> 3: 0.90
#> 4: 1.79
#> 5: 0.64
#> 6: 0.02
#> 7: 0.56
#> 8: 0.92
#> 9: 0.81
#> 10: 1.30
#>