Descriptive analysis of hunting data from J Dulat’s internship
1 Introduction
We have information about hunting bags, hunting effort and hunting areas of 25 hunting teams.
1.1 Hunting areas
Name | h_areas |
Number of rows | 25 |
Number of columns | 11 |
_______________________ | |
Column type frequency: | |
character | 4 |
numeric | 7 |
________________________ | |
Group variables | None |
Variable type: character
skim_variable | n_missing | complete_rate | min | max | empty | n_unique | whitespace |
---|---|---|---|---|---|---|---|
id_team | 0 | 1.0 | 5 | 5 | 0 | 25 | 0 |
microregion | 0 | 1.0 | 6 | 13 | 0 | 10 | 0 |
municipality | 0 | 1.0 | 6 | 22 | 0 | 24 | 0 |
vegetation_cover | 5 | 0.8 | 6 | 90 | 0 | 18 | 0 |
Variable type: numeric
skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
---|---|---|---|---|---|---|---|---|---|---|
area_km2 | 0 | 1.00 | 18.79 | 16.26 | 2.20 | 5.80 | 12.4 | 25.60 | 66.20 | ▇▃▂▁▁ |
mean_h_drives | 2 | 0.92 | 16.09 | 13.07 | 2.00 | 10.00 | 12.0 | 19.00 | 60.00 | ▇▃▁▁▁ |
mean_h_drive_size | 2 | 0.92 | 1.22 | 0.60 | 0.43 | 0.77 | 1.1 | 1.66 | 2.67 | ▇▆▃▃▁ |
perc_plain | 6 | 0.76 | 16.05 | 33.44 | 0.00 | 0.00 | 0.0 | 2.50 | 100.00 | ▇▁▁▁▁ |
perc_piedmont | 6 | 0.76 | 42.37 | 41.31 | 0.00 | 0.00 | 50.0 | 77.50 | 100.00 | ▇▁▅▁▅ |
perc_midmountain | 6 | 0.76 | 41.58 | 44.66 | 0.00 | 0.00 | 35.0 | 100.00 | 100.00 | ▇▁▂▁▅ |
h_days_week | 7 | 0.72 | 2.06 | 0.87 | 1.00 | 1.25 | 2.0 | 2.75 | 4.00 | ▅▇▁▃▁ |
Missing values are concentrated on 8 interviewees out of 25.
Unfortunately, the hunting areas were drawn by hand during the interview and we don’t have the geographically referenced boundaries. As a result, we can not gather environmental or geographical data from official sources and need to rely on the perceptual information given by the interviewees.
For instance, concerning the vegetation cover, the data is given qualitatively as follows:
## [1] "fruitiers emmaquisés"
## [2] "fruitiers"
## [3] "50/50 ciste, arbouses, bruyères et forêt chataigniers et chênes"
## [4] "gros maquis"
## [5] "fruitiers, arbousiers"
## [6] "prairies, maquis dense, cultures"
## [7] "prairies, maquis bas"
## [8] "cultures, fruitiers, maquis"
## [9] "fruitiers, maquis"
## [10] "fruitiers, prairie, maquis"
## [11] "chêne, châtaignier, bruyère"
## [12] "amandiers, figues de barbarie, figues, maquis dense, ciste, chêne vert, olivier, lantisque"
## [13] NA
## [14] "maquis"
## [15] "maquis, chênes, châtaigniers"
## [16] "chênes, châtagniers, fruitiers, luzerne, maquis dense"
## [17] "figues,arbouses, ronces, cistes, genets"
## [18] "chêne, châtaignier, pins"
## [19] "maquis chêne pin"
We have some approximate geographical references from the municipalities and micro-regions so we can locate the hunting teams on a map.
1.2 Hunting bags and effort
Name | hunting_season_2019_jd |
Number of rows | 24 |
Number of columns | 14 |
_______________________ | |
Column type frequency: | |
character | 1 |
logical | 2 |
numeric | 9 |
POSIXct | 2 |
________________________ | |
Group variables | None |
Variable type: character
skim_variable | n_missing | complete_rate | min | max | empty | n_unique | whitespace |
---|---|---|---|---|---|---|---|
id_team | 0 | 1 | 5 | 5 | 0 | 24 | 0 |
Variable type: logical
skim_variable | n_missing | complete_rate | mean | count |
---|---|---|---|---|
dog_blood | 5 | 0.79 | 0.11 | FAL: 17, TRU: 2 |
dog_feet | 5 | 0.79 | 0.11 | FAL: 17, TRU: 2 |
Variable type: numeric
skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
---|---|---|---|---|---|---|---|---|---|---|
hb_2019 | 0 | 1.00 | 101.58 | 93.15 | 20.00 | 40.00 | 56.5 | 116.75 | 330 | ▇▂▁▁▂ |
prior_hunt_pop | 7 | 0.71 | 35.76 | 18.06 | 10.00 | 20.00 | 33.0 | 50.00 | 70 | ▇▆▃▆▃ |
mean_age | 0 | 1.00 | 50.11 | 9.73 | 30.00 | 43.75 | 50.0 | 60.00 | 63 | ▃▃▃▇▇ |
n_hunters_total | 0 | 1.00 | 18.71 | 7.71 | 5.00 | 12.75 | 19.0 | 20.00 | 35 | ▂▇▇▁▃ |
n_hunters_day | 4 | 0.83 | 9.90 | 3.40 | 5.00 | 8.00 | 10.0 | 10.50 | 17 | ▅▆▇▁▅ |
n_dogs_day | 5 | 0.79 | 11.26 | 6.39 | 2.00 | 8.00 | 10.0 | 12.50 | 30 | ▂▇▁▁▁ |
h_days_week | 2 | 0.92 | 2.14 | 0.77 | 1.00 | 2.00 | 2.0 | 2.75 | 4 | ▂▇▁▃▁ |
season_days | 4 | 0.83 | 171.15 | 32.39 | 121.00 | 155.75 | 168.0 | 168.00 | 271 | ▂▇▁▁▁ |
h_days_total | 4 | 0.83 | 49.92 | 19.33 | 17.29 | 42.43 | 48.0 | 58.07 | 96 | ▃▇▁▃▁ |
Variable type: POSIXct
skim_variable | n_missing | complete_rate | min | max | median | n_unique |
---|---|---|---|---|---|---|
season_starts | 4 | 0.83 | 2020-06-01 | 2020-10-01 00:00:00 | 2020-08-15 00:00:00 | 4 |
season_ends | 4 | 0.83 | 2020-12-31 | 2021-02-27 06:00:00 | 2021-01-30 06:00:00 | 8 |
Hunting team Cas_6 did not provide information on its hunting bag for 2019 and thus was removed here.
Missing values are concentrated on 9 interviewees out of 24.