Catch (table) by fleet, gear type, sector

Catch (table) by fleet, gear type, sector

table_total_catch(
  dat,
  unit_label = "mt",
  era = NULL,
  interactive = TRUE,
  module = NULL,
  scale_amount = 1,
  digits = 2,
  make_rda = FALSE,
  tables_dir = getwd()
)

Arguments

dat

Data frame or list. A tibble or named list of tibbles (input as `list()`) returned from convert_output.

If inputting a list of tibbles, the first tibble's reference point defined in `ref_line` is used to plot a reference line or calculate relative spawning biomass.

unit_label

String. Abbreviated catch units

Default: "mt"

era

String. Era of data.

Default: "time"

Options: "early", "time", "fore" (forecast), or NULL (all data)

interactive

Logical. TRUE/FALSE; indicate whether the environment is interactive.

Default: `FALSE`

module

Character vector. (Optional) Module name found in `dat$module_name`. If selecting >1 module, place them in a vector like c("module1", "module2").

Default: NULL

If the interactive and >1 module_name is found, user will select the module_name in the console. @seealso [filter_data()]

scale_amount

Number. A number to scale the y-axis values.

Default: 1

digits

Number. Numeric value indicating the number of digits catch values in the table will be rounded to.

Default: 2

make_rda

Logical. TRUE/FALSE; indicate whether to save the object and make an automated caption and alternative text in the form of an `rda` object. If TRUE, the rda will be exported to the folder indicated in the argument "figures_dir".

Default: `FALSE`.

tables_dir

Path. The location of the folder containing the generated table rda files ("tables") that will be created if the argument `make_rda` = TRUE.

Default: the working directory (`getwd()`)

Value

A table ready of landed catch by fleet and year.

Details

The input is from an assessment model output file translated to a standardized output (convert_output). There are options to return a [gt::gt()] object or export an rda object containing a gt-based table, caption, and LaTeX-based table.

See also

[convert_output()], [filter_data()], [process_table()], [export_kqs()], [insert_kqs()], [create_rda()]

Examples

table_total_catch(stockplotr::example_data,
  module = "TIME_SERIES"
)


  
Year
      
Fleet 1 (mt)
      
Fleet 2 (mt)
    
1874
0
0
1875
0
0
1876
0
3.02
1877
0
3.02
1878
0
3.02
1879
0
3.02
1880
0
34.89
1881
0
66.76
1882
0
98.63
1883
0
130.5
1884
0
162.37
1885
0
194.24
1886
0
226.11
1887
0
257.99
1888
0
289.86
1889
0
321.73
1890
0
353.61
1891
0
385.48
1892
0
417.36
1893
0
449.27
1894
0
481.15
1895
0
513.03
1896
0.73
544.91
1897
0.59
576.79
1898
0.46
608.67
1899
0.45
640.55
1900
0.44
672.44
1901
0.43
704.32
1902
0.41
736.21
1903
0.4
768.1
1904
0.39
799.99
1905
0.38
831.88
1906
0.36
863.77
1907
0.35
895.66
1908
0.34
927.55
1909
0.33
959.45
1910
0.31
991.34
1911
0.3
1,023.24
1912
0.29
1,055.14
1913
0.28
1,087.04
1914
0.26
1,118.94
1915
0.25
1,150.84
1916
0.24
1,167.81
1917
0.23
1,590.92
1918
0.21
1,281
1919
0.2
1,007.77
1920
0.19
696.62
1921
0.18
887.83
1922
0.16
1,283.82
1923
0.15
1,291.63
1924
0.14
1,610.52
1925
0.13
1,597.3
1926
0.11
1,576.8
1927
0.11
1,910.46
1928
0
1,874.42
1929
4.63
2,134.32
1930
3.68
1,991.7
1931
51.56
1,886.27
1932
125.28
1,682.95
1933
163.37
1,282.87
1934
207.07
3,359.06
1935
260.58
2,707.65
1936
346.24
1,545.22
1937
594.62
2,472.88
1938
404.2
2,991.5
1939
1,123.62
3,510.33
1940
1,808.06
2,161.89
1941
2,316.25
1,226.01
1942
5,790.37
839.28
1943
5,881.66
1,261.26
1944
3,338.32
1,541.38
1945
2,923.69
1,616.5
1946
4,792.04
3,657.75
1947
2,659.33
4,043.94
1948
5,920.19
6,988.12
1949
2,470.95
6,805.64
1950
4,446.51
6,005.6
1951
3,258.15
3,758.37
1952
2,595.41
3,984.55
1953
1,243.64
4,597.78
1954
1,904.23
5,747.53
1955
1,960.15
4,989.68
1956
1,716.21
3,884.65
1957
3,159.25
4,828.19
1958
2,676.14
4,342.2
1959
2,063.52
3,631.08
1960
3,107.7
3,415
1961
3,035.39
4,682.49
1962
3,940.13
4,212.59
1963
3,623.23
4,613.81
1964
2,786.84
3,753.34
1965
2,710.72
3,694.54
1966
2,891.12
4,054.51
1967
2,782.17
3,839.03
1968
2,457.01
4,011.85
1969
2,852.8
4,007.38
1970
3,502.32
4,743.78
1971
3,950.76
4,786.46
1972
4,001.51
4,916.56
1973
4,947.9
4,004.12
1974
6,219.16
4,788.35
1975
6,033.15
4,581.86
1976
4,250.73
4,187.19
1977
3,819.6
3,111.8
1978
5,611.27
3,765.94
1979
5,022.28
4,444.33
1980
4,231.46
3,423.52
1981
3,732.91
2,565.05
1982
5,552.57
2,524.33
1983
4,948.58
1,816.7
1984
3,492.21
1,846.72
1985
2,991.51
2,682.44
1986
3,122.84
2,290.55
1987
4,230.02
2,627.01
1988
4,156.33
2,533.69
1989
4,013.42
2,644.47
1990
3,309.96
2,119.1
1991
3,635.06
2,309.92
1992
3,124.88
1,691.44
1993
3,243.69
1,434.11
1994
2,565.51
1,695.85
1995
3,292.61
1,820.02
1996
3,113.79
2,507.16
1997
3,441.85
2,561.94
1998
3,057.61
1,452.59
1999
2,866.29
1,733.6
2000
3,847.55
1,956.53
2001
3,908.12
1,759.97
2002
4,215.76
1,473.56
2003
5,154.13
1,246.13
2004
4,540.65
1,499.31
2005
6,055.27
2,318.56
2006
5,703.25
2,281.3
2007
4,096.1
2,791.55
2008
3,991.77
2,814.12
2009
4,042.26
1,622.37
2010
1,956.03
701.58
2011
2,300.68
536.2
2012
2,716.08
667.91
2013
5,367.06
1,436.83
2014
5,378.33
1,881.17
2015
6,284.08
1,742.76
2016
6,789.69
1,423.51
2017
6,968.11
1,854.2
2018
6,873.82
1,831.8
2019
6,257.37
1,613.41
2020
4,658.66
1,632.67
2021
6,325.23
2,331.53
2022
6,296.82
2,903.22
2023
3,182.84
6,389.7
2024
2,793.22
5,668.27
2025
2,347.85
4,852.75
2026
2,209.93
4,659.44
2027
2,146.54
4,604.49
2028
2,146.27
4,652.26
2029
2,176.16
4,734.24
2030
2,212.46
4,809.2
2031
2,242.44
4,860.7
2032
2,260.69
4,884.99
2033
2,272.78
4,898.19
2034
2,278.06
4,900.48

table_total_catch(
  stockplotr::example_data,
  unit_label = "lbs",
  module = "TIME_SERIES",
  digits = 4,
  scale_amount = 100
)


  
Year
      
Fleet 1 (hundreds of lbs)
      
Fleet 2 (hundreds of lbs)
    
1874
0
0
1875
0
0
1876
0
0.0302
1877
0
0.0302
1878
0
0.0302
1879
0
0.0302
1880
0
0.3489
1881
0
0.6676
1882
0
0.9863
1883
0
1.305
1884
0
1.6237
1885
0
1.9424
1886
0
2.2611
1887
0
2.5799
1888
0
2.8986
1889
0
3.2173
1890
0
3.5361
1891
0
3.8548
1892
0
4.1736
1893
0
4.4927
1894
0
4.8115
1895
0
5.1303
1896
0.0073
5.4491
1897
0.0059
5.7679
1898
0.0046
6.0867
1899
0.0045
6.4055
1900
0.0044
6.7244
1901
0.0043
7.0432
1902
0.0041
7.3621
1903
0.004
7.681
1904
0.0039
7.9999
1905
0.0038
8.3188
1906
0.0036
8.6377
1907
0.0035
8.9566
1908
0.0034
9.2755
1909
0.0033
9.5945
1910
0.0031
9.9134
1911
0.003
10.2324
1912
0.0029
10.5514
1913
0.0028
10.8704
1914
0.0026
11.1894
1915
0.0025
11.5084
1916
0.0024
11.6781
1917
0.0023
15.9092
1918
0.0021
12.81
1919
0.002
10.0777
1920
0.0019
6.9662
1921
0.0018
8.8783
1922
0.0016
12.8382
1923
0.0015
12.9163
1924
0.0014
16.1052
1925
0.0013
15.973
1926
0.0011
15.768
1927
0.0011
19.1046
1928
0
18.7442
1929
0.0463
21.3432
1930
0.0368
19.917
1931
0.5156
18.8627
1932
1.2528
16.8295
1933
1.6337
12.8287
1934
2.0707
33.5906
1935
2.6058
27.0765
1936
3.4623
15.4522
1937
5.9462
24.7288
1938
4.042
29.915
1939
11.2362
35.1033
1940
18.0806
21.6189
1941
23.1625
12.2601
1942
57.9037
8.3928
1943
58.8166
12.6126
1944
33.3832
15.4138
1945
29.2369
16.165
1946
47.9204
36.5775
1947
26.5933
40.4394
1948
59.2019
69.8812
1949
24.7095
68.0564
1950
44.4651
60.056
1951
32.5815
37.5837
1952
25.9541
39.8455
1953
12.4364
45.9778
1954
19.0423
57.4753
1955
19.6015
49.8968
1956
17.1621
38.8465
1957
31.5925
48.2819
1958
26.7614
43.422
1959
20.6352
36.3108
1960
31.077
34.15
1961
30.3539
46.8249
1962
39.4013
42.1259
1963
36.2323
46.1381
1964
27.8684
37.5334
1965
27.1072
36.9454
1966
28.9112
40.5451
1967
27.8217
38.3903
1968
24.5701
40.1185
1969
28.528
40.0738
1970
35.0232
47.4378
1971
39.5076
47.8646
1972
40.0151
49.1656
1973
49.479
40.0412
1974
62.1916
47.8835
1975
60.3315
45.8186
1976
42.5073
41.8719
1977
38.196
31.118
1978
56.1127
37.6594
1979
50.2228
44.4433
1980
42.3146
34.2352
1981
37.3291
25.6505
1982
55.5257
25.2433
1983
49.4858
18.167
1984
34.9221
18.4672
1985
29.9151
26.8244
1986
31.2284
22.9055
1987
42.3002
26.2701
1988
41.5633
25.3369
1989
40.1342
26.4447
1990
33.0996
21.191
1991
36.3506
23.0991
1992
31.2488
16.9144
1993
32.4369
14.3411
1994
25.6551
16.9585
1995
32.9261
18.2002
1996
31.1379
25.0716
1997
34.4185
25.6194
1998
30.5761
14.5259
1999
28.6629
17.336
2000
38.4755
19.5653
2001
39.0812
17.5997
2002
42.1576
14.7356
2003
51.5413
12.4613
2004
45.4065
14.9931
2005
60.5527
23.1856
2006
57.0325
22.813
2007
40.961
27.9155
2008
39.9177
28.1412
2009
40.4226
16.2237
2010
19.5603
7.0158
2011
23.0068
5.362
2012
27.1608
6.6791
2013
53.6706
14.3683
2014
53.7833
18.8117
2015
62.8408
17.4276
2016
67.8969
14.2351
2017
69.6811
18.542
2018
68.7382
18.318
2019
62.5737
16.1341
2020
46.5866
16.3267
2021
63.2523
23.3153
2022
62.9682
29.0322
2023
31.8284
63.897
2024
27.9322
56.6827
2025
23.4785
48.5275
2026
22.0993
46.5944
2027
21.4654
46.0449
2028
21.4627
46.5226
2029
21.7616
47.3424
2030
22.1246
48.092
2031
22.4244
48.607
2032
22.607
48.8499
2033
22.7278
48.9819
2034
22.7807
49.0048