Hugging Face's logo

Datasets:
imageomics
/
IDLE-OO-Camera-Traps

Tasks:
Image Classification
Zero-Shot Classification
Modalities:
Image
Text
Formats:
imagefolder
Languages:
English
Latin
Size:
1K - 10K
ArXiv:
Tags:
biology
image
imageomics
animals
CV
balanced
DOI:
Libraries:
Datasets
Dataset card Data Studio Files
xet
 Community
12
egrace479 commited on
Commit
d4eceaf
·
1 Parent(s): 81e2858

LILA BC full camera trap information with notebook exploring available data.

Browse files

The CSV includes links to all images for the 18 camera trap datasets plus taxonomic info.

Files changed (3) hide show
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  2. lila_image_urls_and_labels.csv +3 -0
  3. lilabc_CT.ipynb +2104 -0
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+ {
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+ "cells": [
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+ {
4
+ "cell_type": "code",
5
+ "execution_count": 1,
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+ "metadata": {},
7
+ "outputs": [],
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+ "source": [
9
+ "import pandas as pd\n",
10
+ "import seaborn as sns\n",
11
+ "\n",
12
+ "sns.set_style(\"whitegrid\")"
13
+ ]
14
+ },
15
+ {
16
+ "cell_type": "code",
17
+ "execution_count": 2,
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+ "metadata": {},
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+ "outputs": [
20
+ {
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+ "name": "stderr",
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+ "output_type": "stream",
23
+ "text": [
24
+ "/var/folders/nv/f0fq1p1n1_3b11x579py_0q80000gq/T/ipykernel_612/1962403499.py:1: DtypeWarning: Columns (7,8,9,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29) have mixed types. Specify dtype option on import or set low_memory=False.\n",
25
+ " df = pd.read_csv(\"lila_image_urls_and_labels.csv\")\n"
26
+ ]
27
+ },
28
+ {
29
+ "data": {
30
+ "text/html": [
31
+ "<div>\n",
32
+ "<style scoped>\n",
33
+ " .dataframe tbody tr th:only-of-type {\n",
34
+ " vertical-align: middle;\n",
35
+ " }\n",
36
+ "\n",
37
+ " .dataframe tbody tr th {\n",
38
+ " vertical-align: top;\n",
39
+ " }\n",
40
+ "\n",
41
+ " .dataframe thead th {\n",
42
+ " text-align: right;\n",
43
+ " }\n",
44
+ "</style>\n",
45
+ "<table border=\"1\" class=\"dataframe\">\n",
46
+ " <thead>\n",
47
+ " <tr style=\"text-align: right;\">\n",
48
+ " <th></th>\n",
49
+ " <th>dataset_name</th>\n",
50
+ " <th>url</th>\n",
51
+ " <th>image_id</th>\n",
52
+ " <th>sequence_id</th>\n",
53
+ " <th>location_id</th>\n",
54
+ " <th>frame_num</th>\n",
55
+ " <th>original_label</th>\n",
56
+ " <th>scientific_name</th>\n",
57
+ " <th>common_name</th>\n",
58
+ " <th>datetime</th>\n",
59
+ " <th>...</th>\n",
60
+ " <th>suborder</th>\n",
61
+ " <th>infraorder</th>\n",
62
+ " <th>superfamily</th>\n",
63
+ " <th>family</th>\n",
64
+ " <th>subfamily</th>\n",
65
+ " <th>tribe</th>\n",
66
+ " <th>genus</th>\n",
67
+ " <th>species</th>\n",
68
+ " <th>subspecies</th>\n",
69
+ " <th>variety</th>\n",
70
+ " </tr>\n",
71
+ " </thead>\n",
72
+ " <tbody>\n",
73
+ " <tr>\n",
74
+ " <th>0</th>\n",
75
+ " <td>Caltech Camera Traps</td>\n",
76
+ " <td>https://lilablobssc.blob.core.windows.net/calt...</td>\n",
77
+ " <td>Caltech Camera Traps : 5968c0f9-23d2-11e8-a6a3...</td>\n",
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+ " <td>Caltech Camera Traps : 6f2160eb-5567-11e8-990e...</td>\n",
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+ " <td>Caltech Camera Traps : 26</td>\n",
80
+ " <td>1</td>\n",
81
+ " <td>empty</td>\n",
82
+ " <td>NaN</td>\n",
83
+ " <td>NaN</td>\n",
84
+ " <td>10-04-2013 13:31:53</td>\n",
85
+ " <td>...</td>\n",
86
+ " <td>NaN</td>\n",
87
+ " <td>NaN</td>\n",
88
+ " <td>NaN</td>\n",
89
+ " <td>NaN</td>\n",
90
+ " <td>NaN</td>\n",
91
+ " <td>NaN</td>\n",
92
+ " <td>NaN</td>\n",
93
+ " <td>NaN</td>\n",
94
+ " <td>NaN</td>\n",
95
+ " <td>NaN</td>\n",
96
+ " </tr>\n",
97
+ " <tr>\n",
98
+ " <th>1</th>\n",
99
+ " <td>Caltech Camera Traps</td>\n",
100
+ " <td>https://lilablobssc.blob.core.windows.net/calt...</td>\n",
101
+ " <td>Caltech Camera Traps : 5a0b016f-23d2-11e8-a6a3...</td>\n",
102
+ " <td>Caltech Camera Traps : 6f27ed66-5567-11e8-9e92...</td>\n",
103
+ " <td>Caltech Camera Traps : 26</td>\n",
104
+ " <td>1</td>\n",
105
+ " <td>deer</td>\n",
106
+ " <td>odocoileus</td>\n",
107
+ " <td>deer</td>\n",
108
+ " <td>11-04-2013 18:37:07</td>\n",
109
+ " <td>...</td>\n",
110
+ " <td>ruminantia</td>\n",
111
+ " <td>NaN</td>\n",
112
+ " <td>NaN</td>\n",
113
+ " <td>cervidae</td>\n",
114
+ " <td>capreolinae</td>\n",
115
+ " <td>odocoileini</td>\n",
116
+ " <td>odocoileus</td>\n",
117
+ " <td>NaN</td>\n",
118
+ " <td>NaN</td>\n",
119
+ " <td>NaN</td>\n",
120
+ " </tr>\n",
121
+ " <tr>\n",
122
+ " <th>2</th>\n",
123
+ " <td>Caltech Camera Traps</td>\n",
124
+ " <td>https://lilablobssc.blob.core.windows.net/calt...</td>\n",
125
+ " <td>Caltech Camera Traps : 59b93afb-23d2-11e8-a6a3...</td>\n",
126
+ " <td>Caltech Camera Traps : 6f04895c-5567-11e8-a3d6...</td>\n",
127
+ " <td>Caltech Camera Traps : 38</td>\n",
128
+ " <td>2</td>\n",
129
+ " <td>cat</td>\n",
130
+ " <td>felis catus</td>\n",
131
+ " <td>cat</td>\n",
132
+ " <td>05-09-2012 07:33:45</td>\n",
133
+ " <td>...</td>\n",
134
+ " <td>NaN</td>\n",
135
+ " <td>NaN</td>\n",
136
+ " <td>NaN</td>\n",
137
+ " <td>felidae</td>\n",
138
+ " <td>felinae</td>\n",
139
+ " <td>NaN</td>\n",
140
+ " <td>felis</td>\n",
141
+ " <td>felis catus</td>\n",
142
+ " <td>NaN</td>\n",
143
+ " <td>NaN</td>\n",
144
+ " </tr>\n",
145
+ " <tr>\n",
146
+ " <th>3</th>\n",
147
+ " <td>Caltech Camera Traps</td>\n",
148
+ " <td>https://lilablobssc.blob.core.windows.net/calt...</td>\n",
149
+ " <td>Caltech Camera Traps : 59641f56-23d2-11e8-a6a3...</td>\n",
150
+ " <td>Caltech Camera Traps : 6f0385b5-5567-11e8-a80b...</td>\n",
151
+ " <td>Caltech Camera Traps : 38</td>\n",
152
+ " <td>2</td>\n",
153
+ " <td>opossum</td>\n",
154
+ " <td>didelphis virginiana</td>\n",
155
+ " <td>virginia opossum</td>\n",
156
+ " <td>03-29-2012 02:34:13</td>\n",
157
+ " <td>...</td>\n",
158
+ " <td>NaN</td>\n",
159
+ " <td>NaN</td>\n",
160
+ " <td>NaN</td>\n",
161
+ " <td>didelphidae</td>\n",
162
+ " <td>didelphinae</td>\n",
163
+ " <td>didelphini</td>\n",
164
+ " <td>didelphis</td>\n",
165
+ " <td>didelphis virginiana</td>\n",
166
+ " <td>NaN</td>\n",
167
+ " <td>NaN</td>\n",
168
+ " </tr>\n",
169
+ " <tr>\n",
170
+ " <th>4</th>\n",
171
+ " <td>Caltech Camera Traps</td>\n",
172
+ " <td>https://lilablobssc.blob.core.windows.net/calt...</td>\n",
173
+ " <td>Caltech Camera Traps : 5a1e5306-23d2-11e8-a6a3...</td>\n",
174
+ " <td>Caltech Camera Traps : 6f0a3ccf-5567-11e8-92fb...</td>\n",
175
+ " <td>Caltech Camera Traps : 33</td>\n",
176
+ " <td>2</td>\n",
177
+ " <td>empty</td>\n",
178
+ " <td>NaN</td>\n",
179
+ " <td>NaN</td>\n",
180
+ " <td>05-08-2012 19:23:36</td>\n",
181
+ " <td>...</td>\n",
182
+ " <td>NaN</td>\n",
183
+ " <td>NaN</td>\n",
184
+ " <td>NaN</td>\n",
185
+ " <td>NaN</td>\n",
186
+ " <td>NaN</td>\n",
187
+ " <td>NaN</td>\n",
188
+ " <td>NaN</td>\n",
189
+ " <td>NaN</td>\n",
190
+ " <td>NaN</td>\n",
191
+ " <td>NaN</td>\n",
192
+ " </tr>\n",
193
+ " </tbody>\n",
194
+ "</table>\n",
195
+ "<p>5 rows × 30 columns</p>\n",
196
+ "</div>"
197
+ ],
198
+ "text/plain": [
199
+ " dataset_name url \n",
200
+ "0 Caltech Camera Traps https://lilablobssc.blob.core.windows.net/calt... \\\n",
201
+ "1 Caltech Camera Traps https://lilablobssc.blob.core.windows.net/calt... \n",
202
+ "2 Caltech Camera Traps https://lilablobssc.blob.core.windows.net/calt... \n",
203
+ "3 Caltech Camera Traps https://lilablobssc.blob.core.windows.net/calt... \n",
204
+ "4 Caltech Camera Traps https://lilablobssc.blob.core.windows.net/calt... \n",
205
+ "\n",
206
+ " image_id \n",
207
+ "0 Caltech Camera Traps : 5968c0f9-23d2-11e8-a6a3... \\\n",
208
+ "1 Caltech Camera Traps : 5a0b016f-23d2-11e8-a6a3... \n",
209
+ "2 Caltech Camera Traps : 59b93afb-23d2-11e8-a6a3... \n",
210
+ "3 Caltech Camera Traps : 59641f56-23d2-11e8-a6a3... \n",
211
+ "4 Caltech Camera Traps : 5a1e5306-23d2-11e8-a6a3... \n",
212
+ "\n",
213
+ " sequence_id \n",
214
+ "0 Caltech Camera Traps : 6f2160eb-5567-11e8-990e... \\\n",
215
+ "1 Caltech Camera Traps : 6f27ed66-5567-11e8-9e92... \n",
216
+ "2 Caltech Camera Traps : 6f04895c-5567-11e8-a3d6... \n",
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+ "3 Caltech Camera Traps : 6f0385b5-5567-11e8-a80b... \n",
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+ "4 Caltech Camera Traps : 6f0a3ccf-5567-11e8-92fb... \n",
219
+ "\n",
220
+ " location_id frame_num original_label scientific_name \n",
221
+ "0 Caltech Camera Traps : 26 1 empty NaN \\\n",
222
+ "1 Caltech Camera Traps : 26 1 deer odocoileus \n",
223
+ "2 Caltech Camera Traps : 38 2 cat felis catus \n",
224
+ "3 Caltech Camera Traps : 38 2 opossum didelphis virginiana \n",
225
+ "4 Caltech Camera Traps : 33 2 empty NaN \n",
226
+ "\n",
227
+ " common_name datetime ... suborder infraorder \n",
228
+ "0 NaN 10-04-2013 13:31:53 ... NaN NaN \\\n",
229
+ "1 deer 11-04-2013 18:37:07 ... ruminantia NaN \n",
230
+ "2 cat 05-09-2012 07:33:45 ... NaN NaN \n",
231
+ "3 virginia opossum 03-29-2012 02:34:13 ... NaN NaN \n",
232
+ "4 NaN 05-08-2012 19:23:36 ... NaN NaN \n",
233
+ "\n",
234
+ " superfamily family subfamily tribe genus \n",
235
+ "0 NaN NaN NaN NaN NaN \\\n",
236
+ "1 NaN cervidae capreolinae odocoileini odocoileus \n",
237
+ "2 NaN felidae felinae NaN felis \n",
238
+ "3 NaN didelphidae didelphinae didelphini didelphis \n",
239
+ "4 NaN NaN NaN NaN NaN \n",
240
+ "\n",
241
+ " species subspecies variety \n",
242
+ "0 NaN NaN NaN \n",
243
+ "1 NaN NaN NaN \n",
244
+ "2 felis catus NaN NaN \n",
245
+ "3 didelphis virginiana NaN NaN \n",
246
+ "4 NaN NaN NaN \n",
247
+ "\n",
248
+ "[5 rows x 30 columns]"
249
+ ]
250
+ },
251
+ "execution_count": 2,
252
+ "metadata": {},
253
+ "output_type": "execute_result"
254
+ }
255
+ ],
256
+ "source": [
257
+ "df = pd.read_csv(\"lila_image_urls_and_labels.csv\")\n",
258
+ "df.head()"
259
+ ]
260
+ },
261
+ {
262
+ "cell_type": "code",
263
+ "execution_count": 4,
264
+ "metadata": {},
265
+ "outputs": [
266
+ {
267
+ "data": {
268
+ "text/plain": [
269
+ "Index(['dataset_name', 'url', 'image_id', 'sequence_id', 'location_id',\n",
270
+ " 'frame_num', 'original_label', 'scientific_name', 'common_name',\n",
271
+ " 'datetime', 'annotation_level', 'kingdom', 'phylum', 'subphylum',\n",
272
+ " 'superclass', 'class', 'subclass', 'infraclass', 'superorder', 'order',\n",
273
+ " 'suborder', 'infraorder', 'superfamily', 'family', 'subfamily', 'tribe',\n",
274
+ " 'genus', 'species', 'subspecies', 'variety'],\n",
275
+ " dtype='object')"
276
+ ]
277
+ },
278
+ "execution_count": 4,
279
+ "metadata": {},
280
+ "output_type": "execute_result"
281
+ }
282
+ ],
283
+ "source": [
284
+ "df.columns"
285
+ ]
286
+ },
287
+ {
288
+ "cell_type": "code",
289
+ "execution_count": 5,
290
+ "metadata": {},
291
+ "outputs": [
292
+ {
293
+ "data": {
294
+ "text/plain": [
295
+ "annotation_level\n",
296
+ "sequence 12710844\n",
297
+ "unknown 3382215\n",
298
+ "image 740789\n",
299
+ "Name: count, dtype: int64"
300
+ ]
301
+ },
302
+ "execution_count": 5,
303
+ "metadata": {},
304
+ "output_type": "execute_result"
305
+ }
306
+ ],
307
+ "source": [
308
+ "df.annotation_level.value_counts()"
309
+ ]
310
+ },
311
+ {
312
+ "cell_type": "markdown",
313
+ "metadata": {},
314
+ "source": [
315
+ "Annotation level indicates iimage vs sequence (or unknown), not analogous to `taxonomy_level` from lila-taxonomy-mapping_release.csv. It seems `original_label` may be the analogous column."
316
+ ]
317
+ },
318
+ {
319
+ "cell_type": "code",
320
+ "execution_count": 9,
321
+ "metadata": {},
322
+ "outputs": [
323
+ {
324
+ "data": {
325
+ "text/html": [
326
+ "<div>\n",
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+ "<style scoped>\n",
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+ " .dataframe tbody tr th:only-of-type {\n",
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+ " vertical-align: middle;\n",
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+ " }\n",
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+ "\n",
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+ " .dataframe tbody tr th {\n",
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+ " vertical-align: top;\n",
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+ " }\n",
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+ "\n",
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+ " .dataframe thead th {\n",
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+ " text-align: right;\n",
338
+ " }\n",
339
+ "</style>\n",
340
+ "<table border=\"1\" class=\"dataframe\">\n",
341
+ " <thead>\n",
342
+ " <tr style=\"text-align: right;\">\n",
343
+ " <th></th>\n",
344
+ " <th>dataset_name</th>\n",
345
+ " <th>url</th>\n",
346
+ " <th>image_id</th>\n",
347
+ " <th>sequence_id</th>\n",
348
+ " <th>location_id</th>\n",
349
+ " <th>frame_num</th>\n",
350
+ " <th>original_label</th>\n",
351
+ " <th>scientific_name</th>\n",
352
+ " <th>common_name</th>\n",
353
+ " <th>datetime</th>\n",
354
+ " <th>...</th>\n",
355
+ " <th>suborder</th>\n",
356
+ " <th>infraorder</th>\n",
357
+ " <th>superfamily</th>\n",
358
+ " <th>family</th>\n",
359
+ " <th>subfamily</th>\n",
360
+ " <th>tribe</th>\n",
361
+ " <th>genus</th>\n",
362
+ " <th>species</th>\n",
363
+ " <th>subspecies</th>\n",
364
+ " <th>variety</th>\n",
365
+ " </tr>\n",
366
+ " </thead>\n",
367
+ " <tbody>\n",
368
+ " <tr>\n",
369
+ " <th>14570597</th>\n",
370
+ " <td>Snapshot Camdeboo</td>\n",
371
+ " <td>https://lilablobssc.blob.core.windows.net/snap...</td>\n",
372
+ " <td>Snapshot Camdeboo : CDB_S1/B04/B04_R1/CDB_S1_B...</td>\n",
373
+ " <td>Snapshot Camdeboo : CDB_S1#B04#1#126</td>\n",
374
+ " <td>Snapshot Camdeboo : B04</td>\n",
375
+ " <td>1</td>\n",
376
+ " <td>monkeyvervet</td>\n",
377
+ " <td>chlorocebus pygerythrus</td>\n",
378
+ " <td>vervet monkey</td>\n",
379
+ " <td>NaN</td>\n",
380
+ " <td>...</td>\n",
381
+ " <td>haplorhini</td>\n",
382
+ " <td>simiiformes</td>\n",
383
+ " <td>NaN</td>\n",
384
+ " <td>cercopithecidae</td>\n",
385
+ " <td>cercopithecinae</td>\n",
386
+ " <td>cercopithecini</td>\n",
387
+ " <td>chlorocebus</td>\n",
388
+ " <td>chlorocebus pygerythrus</td>\n",
389
+ " <td>NaN</td>\n",
390
+ " <td>NaN</td>\n",
391
+ " </tr>\n",
392
+ " <tr>\n",
393
+ " <th>13334717</th>\n",
394
+ " <td>Snapshot Serengeti</td>\n",
395
+ " <td>https://lilablobssc.blob.core.windows.net/snap...</td>\n",
396
+ " <td>Snapshot Serengeti : S10/C05/C05_R1/S10_C05_R1...</td>\n",
397
+ " <td>Snapshot Serengeti : SER_S10#C05#1#719</td>\n",
398
+ " <td>Snapshot Serengeti : C05</td>\n",
399
+ " <td>3</td>\n",
400
+ " <td>empty</td>\n",
401
+ " <td>NaN</td>\n",
402
+ " <td>NaN</td>\n",
403
+ " <td>01-18-2015 09:23:50</td>\n",
404
+ " <td>...</td>\n",
405
+ " <td>NaN</td>\n",
406
+ " <td>NaN</td>\n",
407
+ " <td>NaN</td>\n",
408
+ " <td>NaN</td>\n",
409
+ " <td>NaN</td>\n",
410
+ " <td>NaN</td>\n",
411
+ " <td>NaN</td>\n",
412
+ " <td>NaN</td>\n",
413
+ " <td>NaN</td>\n",
414
+ " <td>NaN</td>\n",
415
+ " </tr>\n",
416
+ " <tr>\n",
417
+ " <th>11278580</th>\n",
418
+ " <td>Snapshot Serengeti</td>\n",
419
+ " <td>https://lilablobssc.blob.core.windows.net/snap...</td>\n",
420
+ " <td>Snapshot Serengeti : S7/T10/T10_R3/S7_T10_R3_I...</td>\n",
421
+ " <td>Snapshot Serengeti : SER_S7#T10#3#325</td>\n",
422
+ " <td>Snapshot Serengeti : T10</td>\n",
423
+ " <td>2</td>\n",
424
+ " <td>hartebeest</td>\n",
425
+ " <td>alcelaphus buselaphus</td>\n",
426
+ " <td>hartebeest</td>\n",
427
+ " <td>11-17-2013 11:54:56</td>\n",
428
+ " <td>...</td>\n",
429
+ " <td>ruminantia</td>\n",
430
+ " <td>NaN</td>\n",
431
+ " <td>NaN</td>\n",
432
+ " <td>bovidae</td>\n",
433
+ " <td>antilopinae</td>\n",
434
+ " <td>alcelaphini</td>\n",
435
+ " <td>alcelaphus</td>\n",
436
+ " <td>alcelaphus buselaphus</td>\n",
437
+ " <td>NaN</td>\n",
438
+ " <td>NaN</td>\n",
439
+ " </tr>\n",
440
+ " <tr>\n",
441
+ " <th>9459516</th>\n",
442
+ " <td>Snapshot Serengeti</td>\n",
443
+ " <td>https://lilablobssc.blob.core.windows.net/snap...</td>\n",
444
+ " <td>Snapshot Serengeti : S5/G07/G07_R1/S5_G07_R1_I...</td>\n",
445
+ " <td>Snapshot Serengeti : SER_S5#G07#1#859</td>\n",
446
+ " <td>Snapshot Serengeti : G07</td>\n",
447
+ " <td>3</td>\n",
448
+ " <td>empty</td>\n",
449
+ " <td>NaN</td>\n",
450
+ " <td>NaN</td>\n",
451
+ " <td>06-05-2012 13:24:53</td>\n",
452
+ " <td>...</td>\n",
453
+ " <td>NaN</td>\n",
454
+ " <td>NaN</td>\n",
455
+ " <td>NaN</td>\n",
456
+ " <td>NaN</td>\n",
457
+ " <td>NaN</td>\n",
458
+ " <td>NaN</td>\n",
459
+ " <td>NaN</td>\n",
460
+ " <td>NaN</td>\n",
461
+ " <td>NaN</td>\n",
462
+ " <td>NaN</td>\n",
463
+ " </tr>\n",
464
+ " <tr>\n",
465
+ " <th>2969662</th>\n",
466
+ " <td>NACTI</td>\n",
467
+ " <td>https://lilablobssc.blob.core.windows.net/nact...</td>\n",
468
+ " <td>NACTI : FL-33_07_06_2016_FL-33_0018047.JPG</td>\n",
469
+ " <td>NACTI : unknown</td>\n",
470
+ " <td>NACTI : Archbold, FL</td>\n",
471
+ " <td>-1</td>\n",
472
+ " <td>bos taurus</td>\n",
473
+ " <td>bos taurus</td>\n",
474
+ " <td>domestic cow</td>\n",
475
+ " <td>NaN</td>\n",
476
+ " <td>...</td>\n",
477
+ " <td>ruminantia</td>\n",
478
+ " <td>NaN</td>\n",
479
+ " <td>NaN</td>\n",
480
+ " <td>bovidae</td>\n",
481
+ " <td>bovinae</td>\n",
482
+ " <td>bovini</td>\n",
483
+ " <td>bos</td>\n",
484
+ " <td>bos taurus</td>\n",
485
+ " <td>NaN</td>\n",
486
+ " <td>NaN</td>\n",
487
+ " </tr>\n",
488
+ " <tr>\n",
489
+ " <th>1361914</th>\n",
490
+ " <td>NACTI</td>\n",
491
+ " <td>https://lilablobssc.blob.core.windows.net/nact...</td>\n",
492
+ " <td>NACTI : CA-45_08_03_2015_CA-45_0007619.jpg</td>\n",
493
+ " <td>NACTI : unknown</td>\n",
494
+ " <td>NACTI : Lebec, California</td>\n",
495
+ " <td>-1</td>\n",
496
+ " <td>bos taurus</td>\n",
497
+ " <td>bos taurus</td>\n",
498
+ " <td>domestic cow</td>\n",
499
+ " <td>NaN</td>\n",
500
+ " <td>...</td>\n",
501
+ " <td>ruminantia</td>\n",
502
+ " <td>NaN</td>\n",
503
+ " <td>NaN</td>\n",
504
+ " <td>bovidae</td>\n",
505
+ " <td>bovinae</td>\n",
506
+ " <td>bovini</td>\n",
507
+ " <td>bos</td>\n",
508
+ " <td>bos taurus</td>\n",
509
+ " <td>NaN</td>\n",
510
+ " <td>NaN</td>\n",
511
+ " </tr>\n",
512
+ " <tr>\n",
513
+ " <th>560812</th>\n",
514
+ " <td>NACTI</td>\n",
515
+ " <td>https://lilablobssc.blob.core.windows.net/nact...</td>\n",
516
+ " <td>NACTI : 2016_Unit074_Ivan093_img0754.jpg</td>\n",
517
+ " <td>NACTI : unknown</td>\n",
518
+ " <td>NACTI : San Juan Mntns, Colorado</td>\n",
519
+ " <td>-1</td>\n",
520
+ " <td>cervus elaphus</td>\n",
521
+ " <td>cervus elaphus</td>\n",
522
+ " <td>red deer</td>\n",
523
+ " <td>NaN</td>\n",
524
+ " <td>...</td>\n",
525
+ " <td>ruminantia</td>\n",
526
+ " <td>NaN</td>\n",
527
+ " <td>NaN</td>\n",
528
+ " <td>cervidae</td>\n",
529
+ " <td>cervinae</td>\n",
530
+ " <td>cervini</td>\n",
531
+ " <td>cervus</td>\n",
532
+ " <td>cervus elaphus</td>\n",
533
+ " <td>NaN</td>\n",
534
+ " <td>NaN</td>\n",
535
+ " </tr>\n",
536
+ " <tr>\n",
537
+ " <th>6040643</th>\n",
538
+ " <td>Idaho Camera Traps</td>\n",
539
+ " <td>https://lilablobssc.blob.core.windows.net/idah...</td>\n",
540
+ " <td>Idaho Camera Traps : loc_0026_im_007478</td>\n",
541
+ " <td>Idaho Camera Traps : loc_0026_seq_006588</td>\n",
542
+ " <td>Idaho Camera Traps : 26</td>\n",
543
+ " <td>0</td>\n",
544
+ " <td>empty</td>\n",
545
+ " <td>NaN</td>\n",
546
+ " <td>NaN</td>\n",
547
+ " <td>02-18-2016 06:10:00</td>\n",
548
+ " <td>...</td>\n",
549
+ " <td>NaN</td>\n",
550
+ " <td>NaN</td>\n",
551
+ " <td>NaN</td>\n",
552
+ " <td>NaN</td>\n",
553
+ " <td>NaN</td>\n",
554
+ " <td>NaN</td>\n",
555
+ " <td>NaN</td>\n",
556
+ " <td>NaN</td>\n",
557
+ " <td>NaN</td>\n",
558
+ " <td>NaN</td>\n",
559
+ " </tr>\n",
560
+ " <tr>\n",
561
+ " <th>1855600</th>\n",
562
+ " <td>NACTI</td>\n",
563
+ " <td>https://lilablobssc.blob.core.windows.net/nact...</td>\n",
564
+ " <td>NACTI : FL-07_08_16_2016_FL-07_0242508.JPG</td>\n",
565
+ " <td>NACTI : unknown</td>\n",
566
+ " <td>NACTI : Archbold, FL</td>\n",
567
+ " <td>-1</td>\n",
568
+ " <td>equus africanus</td>\n",
569
+ " <td>equus africanus</td>\n",
570
+ " <td>african wild ass</td>\n",
571
+ " <td>NaN</td>\n",
572
+ " <td>...</td>\n",
573
+ " <td>NaN</td>\n",
574
+ " <td>NaN</td>\n",
575
+ " <td>NaN</td>\n",
576
+ " <td>equidae</td>\n",
577
+ " <td>NaN</td>\n",
578
+ " <td>NaN</td>\n",
579
+ " <td>equus</td>\n",
580
+ " <td>equus africanus</td>\n",
581
+ " <td>NaN</td>\n",
582
+ " <td>NaN</td>\n",
583
+ " </tr>\n",
584
+ " <tr>\n",
585
+ " <th>9890853</th>\n",
586
+ " <td>Snapshot Serengeti</td>\n",
587
+ " <td>https://lilablobssc.blob.core.windows.net/snap...</td>\n",
588
+ " <td>Snapshot Serengeti : S5/Q12/Q12_R4/S5_Q12_R4_I...</td>\n",
589
+ " <td>Snapshot Serengeti : SER_S5#Q12#4#343</td>\n",
590
+ " <td>Snapshot Serengeti : Q12</td>\n",
591
+ " <td>1</td>\n",
592
+ " <td>empty</td>\n",
593
+ " <td>NaN</td>\n",
594
+ " <td>NaN</td>\n",
595
+ " <td>11-09-2012 18:46:47</td>\n",
596
+ " <td>...</td>\n",
597
+ " <td>NaN</td>\n",
598
+ " <td>NaN</td>\n",
599
+ " <td>NaN</td>\n",
600
+ " <td>NaN</td>\n",
601
+ " <td>NaN</td>\n",
602
+ " <td>NaN</td>\n",
603
+ " <td>NaN</td>\n",
604
+ " <td>NaN</td>\n",
605
+ " <td>NaN</td>\n",
606
+ " <td>NaN</td>\n",
607
+ " </tr>\n",
608
+ " </tbody>\n",
609
+ "</table>\n",
610
+ "<p>10 rows × 30 columns</p>\n",
611
+ "</div>"
612
+ ],
613
+ "text/plain": [
614
+ " dataset_name \n",
615
+ "14570597 Snapshot Camdeboo \\\n",
616
+ "13334717 Snapshot Serengeti \n",
617
+ "11278580 Snapshot Serengeti \n",
618
+ "9459516 Snapshot Serengeti \n",
619
+ "2969662 NACTI \n",
620
+ "1361914 NACTI \n",
621
+ "560812 NACTI \n",
622
+ "6040643 Idaho Camera Traps \n",
623
+ "1855600 NACTI \n",
624
+ "9890853 Snapshot Serengeti \n",
625
+ "\n",
626
+ " url \n",
627
+ "14570597 https://lilablobssc.blob.core.windows.net/snap... \\\n",
628
+ "13334717 https://lilablobssc.blob.core.windows.net/snap... \n",
629
+ "11278580 https://lilablobssc.blob.core.windows.net/snap... \n",
630
+ "9459516 https://lilablobssc.blob.core.windows.net/snap... \n",
631
+ "2969662 https://lilablobssc.blob.core.windows.net/nact... \n",
632
+ "1361914 https://lilablobssc.blob.core.windows.net/nact... \n",
633
+ "560812 https://lilablobssc.blob.core.windows.net/nact... \n",
634
+ "6040643 https://lilablobssc.blob.core.windows.net/idah... \n",
635
+ "1855600 https://lilablobssc.blob.core.windows.net/nact... \n",
636
+ "9890853 https://lilablobssc.blob.core.windows.net/snap... \n",
637
+ "\n",
638
+ " image_id \n",
639
+ "14570597 Snapshot Camdeboo : CDB_S1/B04/B04_R1/CDB_S1_B... \\\n",
640
+ "13334717 Snapshot Serengeti : S10/C05/C05_R1/S10_C05_R1... \n",
641
+ "11278580 Snapshot Serengeti : S7/T10/T10_R3/S7_T10_R3_I... \n",
642
+ "9459516 Snapshot Serengeti : S5/G07/G07_R1/S5_G07_R1_I... \n",
643
+ "2969662 NACTI : FL-33_07_06_2016_FL-33_0018047.JPG \n",
644
+ "1361914 NACTI : CA-45_08_03_2015_CA-45_0007619.jpg \n",
645
+ "560812 NACTI : 2016_Unit074_Ivan093_img0754.jpg \n",
646
+ "6040643 Idaho Camera Traps : loc_0026_im_007478 \n",
647
+ "1855600 NACTI : FL-07_08_16_2016_FL-07_0242508.JPG \n",
648
+ "9890853 Snapshot Serengeti : S5/Q12/Q12_R4/S5_Q12_R4_I... \n",
649
+ "\n",
650
+ " sequence_id \n",
651
+ "14570597 Snapshot Camdeboo : CDB_S1#B04#1#126 \\\n",
652
+ "13334717 Snapshot Serengeti : SER_S10#C05#1#719 \n",
653
+ "11278580 Snapshot Serengeti : SER_S7#T10#3#325 \n",
654
+ "9459516 Snapshot Serengeti : SER_S5#G07#1#859 \n",
655
+ "2969662 NACTI : unknown \n",
656
+ "1361914 NACTI : unknown \n",
657
+ "560812 NACTI : unknown \n",
658
+ "6040643 Idaho Camera Traps : loc_0026_seq_006588 \n",
659
+ "1855600 NACTI : unknown \n",
660
+ "9890853 Snapshot Serengeti : SER_S5#Q12#4#343 \n",
661
+ "\n",
662
+ " location_id frame_num original_label \n",
663
+ "14570597 Snapshot Camdeboo : B04 1 monkeyvervet \\\n",
664
+ "13334717 Snapshot Serengeti : C05 3 empty \n",
665
+ "11278580 Snapshot Serengeti : T10 2 hartebeest \n",
666
+ "9459516 Snapshot Serengeti : G07 3 empty \n",
667
+ "2969662 NACTI : Archbold, FL -1 bos taurus \n",
668
+ "1361914 NACTI : Lebec, California -1 bos taurus \n",
669
+ "560812 NACTI : San Juan Mntns, Colorado -1 cervus elaphus \n",
670
+ "6040643 Idaho Camera Traps : 26 0 empty \n",
671
+ "1855600 NACTI : Archbold, FL -1 equus africanus \n",
672
+ "9890853 Snapshot Serengeti : Q12 1 empty \n",
673
+ "\n",
674
+ " scientific_name common_name datetime ... \n",
675
+ "14570597 chlorocebus pygerythrus vervet monkey NaN ... \\\n",
676
+ "13334717 NaN NaN 01-18-2015 09:23:50 ... \n",
677
+ "11278580 alcelaphus buselaphus hartebeest 11-17-2013 11:54:56 ... \n",
678
+ "9459516 NaN NaN 06-05-2012 13:24:53 ... \n",
679
+ "2969662 bos taurus domestic cow NaN ... \n",
680
+ "1361914 bos taurus domestic cow NaN ... \n",
681
+ "560812 cervus elaphus red deer NaN ... \n",
682
+ "6040643 NaN NaN 02-18-2016 06:10:00 ... \n",
683
+ "1855600 equus africanus african wild ass NaN ... \n",
684
+ "9890853 NaN NaN 11-09-2012 18:46:47 ... \n",
685
+ "\n",
686
+ " suborder infraorder superfamily family \n",
687
+ "14570597 haplorhini simiiformes NaN cercopithecidae \\\n",
688
+ "13334717 NaN NaN NaN NaN \n",
689
+ "11278580 ruminantia NaN NaN bovidae \n",
690
+ "9459516 NaN NaN NaN NaN \n",
691
+ "2969662 ruminantia NaN NaN bovidae \n",
692
+ "1361914 ruminantia NaN NaN bovidae \n",
693
+ "560812 ruminantia NaN NaN cervidae \n",
694
+ "6040643 NaN NaN NaN NaN \n",
695
+ "1855600 NaN NaN NaN equidae \n",
696
+ "9890853 NaN NaN NaN NaN \n",
697
+ "\n",
698
+ " subfamily tribe genus \n",
699
+ "14570597 cercopithecinae cercopithecini chlorocebus \\\n",
700
+ "13334717 NaN NaN NaN \n",
701
+ "11278580 antilopinae alcelaphini alcelaphus \n",
702
+ "9459516 NaN NaN NaN \n",
703
+ "2969662 bovinae bovini bos \n",
704
+ "1361914 bovinae bovini bos \n",
705
+ "560812 cervinae cervini cervus \n",
706
+ "6040643 NaN NaN NaN \n",
707
+ "1855600 NaN NaN equus \n",
708
+ "9890853 NaN NaN NaN \n",
709
+ "\n",
710
+ " species subspecies variety \n",
711
+ "14570597 chlorocebus pygerythrus NaN NaN \n",
712
+ "13334717 NaN NaN NaN \n",
713
+ "11278580 alcelaphus buselaphus NaN NaN \n",
714
+ "9459516 NaN NaN NaN \n",
715
+ "2969662 bos taurus NaN NaN \n",
716
+ "1361914 bos taurus NaN NaN \n",
717
+ "560812 cervus elaphus NaN NaN \n",
718
+ "6040643 NaN NaN NaN \n",
719
+ "1855600 equus africanus NaN NaN \n",
720
+ "9890853 NaN NaN NaN \n",
721
+ "\n",
722
+ "[10 rows x 30 columns]"
723
+ ]
724
+ },
725
+ "execution_count": 9,
726
+ "metadata": {},
727
+ "output_type": "execute_result"
728
+ }
729
+ ],
730
+ "source": [
731
+ "df.sample(10)"
732
+ ]
733
+ },
734
+ {
735
+ "cell_type": "code",
736
+ "execution_count": 7,
737
+ "metadata": {},
738
+ "outputs": [
739
+ {
740
+ "name": "stdout",
741
+ "output_type": "stream",
742
+ "text": [
743
+ "<class 'pandas.core.frame.DataFrame'>\n",
744
+ "RangeIndex: 16833848 entries, 0 to 16833847\n",
745
+ "Data columns (total 30 columns):\n",
746
+ " # Column Non-Null Count Dtype \n",
747
+ "--- ------ -------------- ----- \n",
748
+ " 0 dataset_name 16833848 non-null object\n",
749
+ " 1 url 16833848 non-null object\n",
750
+ " 2 image_id 16833848 non-null object\n",
751
+ " 3 sequence_id 16833848 non-null object\n",
752
+ " 4 location_id 16833848 non-null object\n",
753
+ " 5 frame_num 16833848 non-null int64 \n",
754
+ " 6 original_label 16833848 non-null object\n",
755
+ " 7 scientific_name 7675398 non-null object\n",
756
+ " 8 common_name 7675398 non-null object\n",
757
+ " 9 datetime 13000606 non-null object\n",
758
+ " 10 annotation_level 16833848 non-null object\n",
759
+ " 11 kingdom 7675398 non-null object\n",
760
+ " 12 phylum 7659814 non-null object\n",
761
+ " 13 subphylum 7657475 non-null object\n",
762
+ " 14 superclass 79 non-null object\n",
763
+ " 15 class 7657475 non-null object\n",
764
+ " 16 subclass 7040121 non-null object\n",
765
+ " 17 infraclass 7039950 non-null object\n",
766
+ " 18 superorder 6997230 non-null object\n",
767
+ " 19 order 7279843 non-null object\n",
768
+ " 20 suborder 5781039 non-null object\n",
769
+ " 21 infraorder 508734 non-null object\n",
770
+ " 22 superfamily 446568 non-null object\n",
771
+ " 23 family 7177009 non-null object\n",
772
+ " 24 subfamily 5790398 non-null object\n",
773
+ " 25 tribe 5157365 non-null object\n",
774
+ " 26 genus 6978606 non-null object\n",
775
+ " 27 species 6516375 non-null object\n",
776
+ " 28 subspecies 21298 non-null object\n",
777
+ " 29 variety 1480 non-null object\n",
778
+ "dtypes: int64(1), object(29)\n",
779
+ "memory usage: 3.8+ GB\n"
780
+ ]
781
+ }
782
+ ],
783
+ "source": [
784
+ "df.info(show_counts = True)"
785
+ ]
786
+ },
787
+ {
788
+ "cell_type": "code",
789
+ "execution_count": 8,
790
+ "metadata": {},
791
+ "outputs": [
792
+ {
793
+ "data": {
794
+ "text/plain": [
795
+ "dataset_name 18\n",
796
+ "url 16731838\n",
797
+ "image_id 16731838\n",
798
+ "sequence_id 4772756\n",
799
+ "location_id 6129\n",
800
+ "frame_num 11005\n",
801
+ "original_label 1121\n",
802
+ "scientific_name 821\n",
803
+ "common_name 902\n",
804
+ "datetime 6572613\n",
805
+ "annotation_level 3\n",
806
+ "kingdom 1\n",
807
+ "phylum 2\n",
808
+ "subphylum 5\n",
809
+ "superclass 1\n",
810
+ "class 8\n",
811
+ "subclass 3\n",
812
+ "infraclass 2\n",
813
+ "superorder 5\n",
814
+ "order 53\n",
815
+ "suborder 17\n",
816
+ "infraorder 9\n",
817
+ "superfamily 12\n",
818
+ "family 159\n",
819
+ "subfamily 69\n",
820
+ "tribe 46\n",
821
+ "genus 476\n",
822
+ "species 667\n",
823
+ "subspecies 8\n",
824
+ "variety 1\n",
825
+ "dtype: int64"
826
+ ]
827
+ },
828
+ "execution_count": 8,
829
+ "metadata": {},
830
+ "output_type": "execute_result"
831
+ }
832
+ ],
833
+ "source": [
834
+ "df.nunique()"
835
+ ]
836
+ },
837
+ {
838
+ "cell_type": "markdown",
839
+ "metadata": {},
840
+ "source": [
841
+ "We have 667 unique species indicated (matches lila-taxonomy-mapping_release.csv after dropping humans, seems to have two more distinct genera though)."
842
+ ]
843
+ },
844
+ {
845
+ "cell_type": "code",
846
+ "execution_count": 10,
847
+ "metadata": {},
848
+ "outputs": [
849
+ {
850
+ "data": {
851
+ "text/html": [
852
+ "<div>\n",
853
+ "<style scoped>\n",
854
+ " .dataframe tbody tr th:only-of-type {\n",
855
+ " vertical-align: middle;\n",
856
+ " }\n",
857
+ "\n",
858
+ " .dataframe tbody tr th {\n",
859
+ " vertical-align: top;\n",
860
+ " }\n",
861
+ "\n",
862
+ " .dataframe thead th {\n",
863
+ " text-align: right;\n",
864
+ " }\n",
865
+ "</style>\n",
866
+ "<table border=\"1\" class=\"dataframe\">\n",
867
+ " <thead>\n",
868
+ " <tr style=\"text-align: right;\">\n",
869
+ " <th></th>\n",
870
+ " <th>dataset_name</th>\n",
871
+ " <th>url</th>\n",
872
+ " <th>image_id</th>\n",
873
+ " <th>sequence_id</th>\n",
874
+ " <th>location_id</th>\n",
875
+ " <th>frame_num</th>\n",
876
+ " <th>original_label</th>\n",
877
+ " <th>scientific_name</th>\n",
878
+ " <th>common_name</th>\n",
879
+ " <th>datetime</th>\n",
880
+ " <th>...</th>\n",
881
+ " <th>suborder</th>\n",
882
+ " <th>infraorder</th>\n",
883
+ " <th>superfamily</th>\n",
884
+ " <th>family</th>\n",
885
+ " <th>subfamily</th>\n",
886
+ " <th>tribe</th>\n",
887
+ " <th>genus</th>\n",
888
+ " <th>species</th>\n",
889
+ " <th>subspecies</th>\n",
890
+ " <th>variety</th>\n",
891
+ " </tr>\n",
892
+ " </thead>\n",
893
+ " <tbody>\n",
894
+ " </tbody>\n",
895
+ "</table>\n",
896
+ "<p>0 rows × 30 columns</p>\n",
897
+ "</div>"
898
+ ],
899
+ "text/plain": [
900
+ "Empty DataFrame\n",
901
+ "Columns: [dataset_name, url, image_id, sequence_id, location_id, frame_num, original_label, scientific_name, common_name, datetime, annotation_level, kingdom, phylum, subphylum, superclass, class, subclass, infraclass, superorder, order, suborder, infraorder, superfamily, family, subfamily, tribe, genus, species, subspecies, variety]\n",
902
+ "Index: []\n",
903
+ "\n",
904
+ "[0 rows x 30 columns]"
905
+ ]
906
+ },
907
+ "execution_count": 10,
908
+ "metadata": {},
909
+ "output_type": "execute_result"
910
+ }
911
+ ],
912
+ "source": [
913
+ "#check for humans\n",
914
+ "df.loc[df.species == \"homo sapien\"]"
915
+ ]
916
+ },
917
+ {
918
+ "cell_type": "markdown",
919
+ "metadata": {},
920
+ "source": [
921
+ "Let's start by removing entries with `original_label`: `empty`."
922
+ ]
923
+ },
924
+ {
925
+ "cell_type": "code",
926
+ "execution_count": 11,
927
+ "metadata": {},
928
+ "outputs": [],
929
+ "source": [
930
+ "df_cleaned = df.loc[df.original_label != \"empty\"]"
931
+ ]
932
+ },
933
+ {
934
+ "cell_type": "markdown",
935
+ "metadata": {},
936
+ "source": [
937
+ "We started with 16,833,848 entries, and are left with 8,448,597 after removing all labeled as `empty`, so about half the images. \n",
938
+ "\n",
939
+ "Note that there are still about 2 million that don't have the species label, 1.5 million that are missing genus designation."
940
+ ]
941
+ },
942
+ {
943
+ "cell_type": "code",
944
+ "execution_count": 13,
945
+ "metadata": {},
946
+ "outputs": [
947
+ {
948
+ "name": "stdout",
949
+ "output_type": "stream",
950
+ "text": [
951
+ "<class 'pandas.core.frame.DataFrame'>\n",
952
+ "Index: 8448597 entries, 1 to 16833847\n",
953
+ "Data columns (total 2 columns):\n",
954
+ " # Column Non-Null Count Dtype \n",
955
+ "--- ------ -------------- ----- \n",
956
+ " 0 genus 6978606 non-null object\n",
957
+ " 1 species 6516375 non-null object\n",
958
+ "dtypes: object(2)\n",
959
+ "memory usage: 193.4+ MB\n"
960
+ ]
961
+ }
962
+ ],
963
+ "source": [
964
+ "df_cleaned[['genus', 'species']].info(show_counts = True)"
965
+ ]
966
+ },
967
+ {
968
+ "cell_type": "code",
969
+ "execution_count": 14,
970
+ "metadata": {},
971
+ "outputs": [
972
+ {
973
+ "data": {
974
+ "text/plain": [
975
+ "genus 476\n",
976
+ "species 667\n",
977
+ "dtype: int64"
978
+ ]
979
+ },
980
+ "execution_count": 14,
981
+ "metadata": {},
982
+ "output_type": "execute_result"
983
+ }
984
+ ],
985
+ "source": [
986
+ "df_cleaned[['genus', 'species']].nunique()"
987
+ ]
988
+ },
989
+ {
990
+ "cell_type": "code",
991
+ "execution_count": 15,
992
+ "metadata": {},
993
+ "outputs": [
994
+ {
995
+ "data": {
996
+ "text/plain": [
997
+ "Series([], Name: count, dtype: int64)"
998
+ ]
999
+ },
1000
+ "execution_count": 15,
1001
+ "metadata": {},
1002
+ "output_type": "execute_result"
1003
+ }
1004
+ ],
1005
+ "source": [
1006
+ "df_cleaned.loc[df_cleaned['genus'].isna(), 'species'].value_counts()"
1007
+ ]
1008
+ },
1009
+ {
1010
+ "cell_type": "markdown",
1011
+ "metadata": {},
1012
+ "source": [
1013
+ "All entries missing `genus` are also missing `species`, so we'll drop all entries with null `genus`."
1014
+ ]
1015
+ },
1016
+ {
1017
+ "cell_type": "code",
1018
+ "execution_count": 16,
1019
+ "metadata": {},
1020
+ "outputs": [],
1021
+ "source": [
1022
+ "df_genusSpecies = df_cleaned.dropna(subset = \"genus\")"
1023
+ ]
1024
+ },
1025
+ {
1026
+ "cell_type": "code",
1027
+ "execution_count": 17,
1028
+ "metadata": {},
1029
+ "outputs": [
1030
+ {
1031
+ "name": "stdout",
1032
+ "output_type": "stream",
1033
+ "text": [
1034
+ "<class 'pandas.core.frame.DataFrame'>\n",
1035
+ "Index: 6978606 entries, 1 to 16833847\n",
1036
+ "Data columns (total 30 columns):\n",
1037
+ " # Column Non-Null Count Dtype \n",
1038
+ "--- ------ -------------- ----- \n",
1039
+ " 0 dataset_name 6978606 non-null object\n",
1040
+ " 1 url 6978606 non-null object\n",
1041
+ " 2 image_id 6978606 non-null object\n",
1042
+ " 3 sequence_id 6978606 non-null object\n",
1043
+ " 4 location_id 6978606 non-null object\n",
1044
+ " 5 frame_num 6978606 non-null int64 \n",
1045
+ " 6 original_label 6978606 non-null object\n",
1046
+ " 7 scientific_name 6978606 non-null object\n",
1047
+ " 8 common_name 6978606 non-null object\n",
1048
+ " 9 datetime 4022446 non-null object\n",
1049
+ " 10 annotation_level 6978606 non-null object\n",
1050
+ " 11 kingdom 6978606 non-null object\n",
1051
+ " 12 phylum 6978606 non-null object\n",
1052
+ " 13 subphylum 6978606 non-null object\n",
1053
+ " 14 superclass 59 non-null object\n",
1054
+ " 15 class 6978606 non-null object\n",
1055
+ " 16 subclass 6792311 non-null object\n",
1056
+ " 17 infraclass 6792252 non-null object\n",
1057
+ " 18 superorder 6755335 non-null object\n",
1058
+ " 19 order 6978606 non-null object\n",
1059
+ " 20 suborder 5679493 non-null object\n",
1060
+ " 21 infraorder 508660 non-null object\n",
1061
+ " 22 superfamily 346788 non-null object\n",
1062
+ " 23 family 6978606 non-null object\n",
1063
+ " 24 subfamily 5789159 non-null object\n",
1064
+ " 25 tribe 5157009 non-null object\n",
1065
+ " 26 genus 6978606 non-null object\n",
1066
+ " 27 species 6516375 non-null object\n",
1067
+ " 28 subspecies 21298 non-null object\n",
1068
+ " 29 variety 1480 non-null object\n",
1069
+ "dtypes: int64(1), object(29)\n",
1070
+ "memory usage: 1.6+ GB\n"
1071
+ ]
1072
+ }
1073
+ ],
1074
+ "source": [
1075
+ "df_genusSpecies.info(show_counts = True)"
1076
+ ]
1077
+ },
1078
+ {
1079
+ "cell_type": "code",
1080
+ "execution_count": 18,
1081
+ "metadata": {},
1082
+ "outputs": [
1083
+ {
1084
+ "data": {
1085
+ "text/plain": [
1086
+ "dataset_name 18\n",
1087
+ "url 6901819\n",
1088
+ "image_id 6901819\n",
1089
+ "sequence_id 1046985\n",
1090
+ "location_id 6017\n",
1091
+ "frame_num 6068\n",
1092
+ "original_label 972\n",
1093
+ "scientific_name 754\n",
1094
+ "common_name 815\n",
1095
+ "datetime 2576256\n",
1096
+ "annotation_level 3\n",
1097
+ "kingdom 1\n",
1098
+ "phylum 2\n",
1099
+ "subphylum 2\n",
1100
+ "superclass 1\n",
1101
+ "class 5\n",
1102
+ "subclass 2\n",
1103
+ "infraclass 2\n",
1104
+ "superorder 5\n",
1105
+ "order 49\n",
1106
+ "suborder 14\n",
1107
+ "infraorder 7\n",
1108
+ "superfamily 9\n",
1109
+ "family 152\n",
1110
+ "subfamily 69\n",
1111
+ "tribe 46\n",
1112
+ "genus 476\n",
1113
+ "species 667\n",
1114
+ "subspecies 8\n",
1115
+ "variety 1\n",
1116
+ "dtype: int64"
1117
+ ]
1118
+ },
1119
+ "execution_count": 18,
1120
+ "metadata": {},
1121
+ "output_type": "execute_result"
1122
+ }
1123
+ ],
1124
+ "source": [
1125
+ "df_genusSpecies.nunique()"
1126
+ ]
1127
+ },
1128
+ {
1129
+ "cell_type": "markdown",
1130
+ "metadata": {},
1131
+ "source": [
1132
+ "This leaves us with 476 unique genera and 667 unique species among the remaining 6,978,606 entries in the 18 datasets.\n",
1133
+ "\n",
1134
+ "There are about 77,000 non-unique URLs. Does this mean there are duplicated entries for images or are they sequences? This is the same number of unique `image_id`, so unclear."
1135
+ ]
1136
+ },
1137
+ {
1138
+ "cell_type": "code",
1139
+ "execution_count": 23,
1140
+ "metadata": {},
1141
+ "outputs": [
1142
+ {
1143
+ "data": {
1144
+ "text/plain": [
1145
+ "False 6825717\n",
1146
+ "True 152889\n",
1147
+ "Name: count, dtype: int64"
1148
+ ]
1149
+ },
1150
+ "execution_count": 23,
1151
+ "metadata": {},
1152
+ "output_type": "execute_result"
1153
+ }
1154
+ ],
1155
+ "source": [
1156
+ "df_genusSpecies.duplicated(subset = ['url'], keep = False).value_counts()"
1157
+ ]
1158
+ },
1159
+ {
1160
+ "cell_type": "markdown",
1161
+ "metadata": {},
1162
+ "source": [
1163
+ "This tracks with the rough estimate, as we see a total of 152,889 entries that are duplicates of each other, with a total of 76,787 that have been duplicated (see below)."
1164
+ ]
1165
+ },
1166
+ {
1167
+ "cell_type": "code",
1168
+ "execution_count": 24,
1169
+ "metadata": {},
1170
+ "outputs": [
1171
+ {
1172
+ "data": {
1173
+ "text/plain": [
1174
+ "False 6901819\n",
1175
+ "True 76787\n",
1176
+ "Name: count, dtype: int64"
1177
+ ]
1178
+ },
1179
+ "execution_count": 24,
1180
+ "metadata": {},
1181
+ "output_type": "execute_result"
1182
+ }
1183
+ ],
1184
+ "source": [
1185
+ "df_genusSpecies.duplicated(subset = ['url'], keep = 'first').value_counts()"
1186
+ ]
1187
+ },
1188
+ {
1189
+ "cell_type": "code",
1190
+ "execution_count": 25,
1191
+ "metadata": {},
1192
+ "outputs": [
1193
+ {
1194
+ "data": {
1195
+ "text/plain": [
1196
+ "False 6901819\n",
1197
+ "True 76787\n",
1198
+ "Name: count, dtype: int64"
1199
+ ]
1200
+ },
1201
+ "execution_count": 25,
1202
+ "metadata": {},
1203
+ "output_type": "execute_result"
1204
+ }
1205
+ ],
1206
+ "source": [
1207
+ "df_genusSpecies.duplicated(subset = ['url', 'image_id'], keep = 'first').value_counts()"
1208
+ ]
1209
+ },
1210
+ {
1211
+ "cell_type": "markdown",
1212
+ "metadata": {},
1213
+ "source": [
1214
+ "These match the duplicated `image_id`s as well. Perhaps this is more than one animal in the frame?"
1215
+ ]
1216
+ },
1217
+ {
1218
+ "cell_type": "code",
1219
+ "execution_count": 29,
1220
+ "metadata": {},
1221
+ "outputs": [
1222
+ {
1223
+ "name": "stderr",
1224
+ "output_type": "stream",
1225
+ "text": [
1226
+ "/var/folders/nv/f0fq1p1n1_3b11x579py_0q80000gq/T/ipykernel_612/1632903565.py:1: SettingWithCopyWarning: \n",
1227
+ "A value is trying to be set on a copy of a slice from a DataFrame.\n",
1228
+ "Try using .loc[row_indexer,col_indexer] = value instead\n",
1229
+ "\n",
1230
+ "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
1231
+ " df_genusSpecies['url_dupe'] = df_genusSpecies.duplicated(subset = ['url'], keep = False)\n"
1232
+ ]
1233
+ }
1234
+ ],
1235
+ "source": [
1236
+ "df_genusSpecies['url_dupe'] = df_genusSpecies.duplicated(subset = ['url'], keep = False)"
1237
+ ]
1238
+ },
1239
+ {
1240
+ "cell_type": "code",
1241
+ "execution_count": 30,
1242
+ "metadata": {},
1243
+ "outputs": [
1244
+ {
1245
+ "data": {
1246
+ "text/html": [
1247
+ "<div>\n",
1248
+ "<style scoped>\n",
1249
+ " .dataframe tbody tr th:only-of-type {\n",
1250
+ " vertical-align: middle;\n",
1251
+ " }\n",
1252
+ "\n",
1253
+ " .dataframe tbody tr th {\n",
1254
+ " vertical-align: top;\n",
1255
+ " }\n",
1256
+ "\n",
1257
+ " .dataframe thead th {\n",
1258
+ " text-align: right;\n",
1259
+ " }\n",
1260
+ "</style>\n",
1261
+ "<table border=\"1\" class=\"dataframe\">\n",
1262
+ " <thead>\n",
1263
+ " <tr style=\"text-align: right;\">\n",
1264
+ " <th></th>\n",
1265
+ " <th>dataset_name</th>\n",
1266
+ " <th>url</th>\n",
1267
+ " <th>image_id</th>\n",
1268
+ " <th>sequence_id</th>\n",
1269
+ " <th>location_id</th>\n",
1270
+ " <th>frame_num</th>\n",
1271
+ " <th>original_label</th>\n",
1272
+ " <th>scientific_name</th>\n",
1273
+ " <th>common_name</th>\n",
1274
+ " <th>datetime</th>\n",
1275
+ " <th>...</th>\n",
1276
+ " <th>infraorder</th>\n",
1277
+ " <th>superfamily</th>\n",
1278
+ " <th>family</th>\n",
1279
+ " <th>subfamily</th>\n",
1280
+ " <th>tribe</th>\n",
1281
+ " <th>genus</th>\n",
1282
+ " <th>species</th>\n",
1283
+ " <th>subspecies</th>\n",
1284
+ " <th>variety</th>\n",
1285
+ " <th>url_dupe</th>\n",
1286
+ " </tr>\n",
1287
+ " </thead>\n",
1288
+ " <tbody>\n",
1289
+ " <tr>\n",
1290
+ " <th>15355844</th>\n",
1291
+ " <td>SWG Camera Traps</td>\n",
1292
+ " <td>https://lilablobssc.blob.core.windows.net/swg-...</td>\n",
1293
+ " <td>SWG Camera Traps : cebffb73-8c29-11eb-92ab-000...</td>\n",
1294
+ " <td>SWG Camera Traps : e42a22f0-8c29-11eb-9c41-000...</td>\n",
1295
+ " <td>SWG Camera Traps : loc_0263</td>\n",
1296
+ " <td>2</td>\n",
1297
+ " <td>large_antlered_muntjac</td>\n",
1298
+ " <td>muntiacus vuquangensis</td>\n",
1299
+ " <td>large-antlered muntjac</td>\n",
1300
+ " <td>06-24-2019 19:36:35</td>\n",
1301
+ " <td>...</td>\n",
1302
+ " <td>NaN</td>\n",
1303
+ " <td>NaN</td>\n",
1304
+ " <td>cervidae</td>\n",
1305
+ " <td>cervinae</td>\n",
1306
+ " <td>muntiacini</td>\n",
1307
+ " <td>muntiacus</td>\n",
1308
+ " <td>muntiacus vuquangensis</td>\n",
1309
+ " <td>NaN</td>\n",
1310
+ " <td>NaN</td>\n",
1311
+ " <td>False</td>\n",
1312
+ " </tr>\n",
1313
+ " <tr>\n",
1314
+ " <th>15098255</th>\n",
1315
+ " <td>SWG Camera Traps</td>\n",
1316
+ " <td>https://lilablobssc.blob.core.windows.net/swg-...</td>\n",
1317
+ " <td>SWG Camera Traps : cc2b9e0b-8c29-11eb-bd63-000...</td>\n",
1318
+ " <td>SWG Camera Traps : 2801caa6-8c2a-11eb-9118-000...</td>\n",
1319
+ " <td>SWG Camera Traps : loc_0512</td>\n",
1320
+ " <td>2</td>\n",
1321
+ " <td>ferret_badger</td>\n",
1322
+ " <td>melogale</td>\n",
1323
+ " <td>ferret badger</td>\n",
1324
+ " <td>07-08-2020 21:03:55</td>\n",
1325
+ " <td>...</td>\n",
1326
+ " <td>NaN</td>\n",
1327
+ " <td>NaN</td>\n",
1328
+ " <td>mustelidae</td>\n",
1329
+ " <td>helictidinae</td>\n",
1330
+ " <td>NaN</td>\n",
1331
+ " <td>melogale</td>\n",
1332
+ " <td>NaN</td>\n",
1333
+ " <td>NaN</td>\n",
1334
+ " <td>NaN</td>\n",
1335
+ " <td>False</td>\n",
1336
+ " </tr>\n",
1337
+ " <tr>\n",
1338
+ " <th>15750309</th>\n",
1339
+ " <td>SWG Camera Traps</td>\n",
1340
+ " <td>https://lilablobssc.blob.core.windows.net/swg-...</td>\n",
1341
+ " <td>SWG Camera Traps : d29fd7c0-8c29-11eb-9d65-000...</td>\n",
1342
+ " <td>SWG Camera Traps : 39b3e643-8c2a-11eb-b05f-000...</td>\n",
1343
+ " <td>SWG Camera Traps : loc_0588</td>\n",
1344
+ " <td>7</td>\n",
1345
+ " <td>stump_tailed_macaque</td>\n",
1346
+ " <td>macaca arctoides</td>\n",
1347
+ " <td>stump-tailed macaque</td>\n",
1348
+ " <td>08-26-2019 10:52:49</td>\n",
1349
+ " <td>...</td>\n",
1350
+ " <td>simiiformes</td>\n",
1351
+ " <td>NaN</td>\n",
1352
+ " <td>cercopithecidae</td>\n",
1353
+ " <td>cercopithecinae</td>\n",
1354
+ " <td>papionini</td>\n",
1355
+ " <td>macaca</td>\n",
1356
+ " <td>macaca arctoides</td>\n",
1357
+ " <td>NaN</td>\n",
1358
+ " <td>NaN</td>\n",
1359
+ " <td>False</td>\n",
1360
+ " </tr>\n",
1361
+ " <tr>\n",
1362
+ " <th>812622</th>\n",
1363
+ " <td>NACTI</td>\n",
1364
+ " <td>https://lilablobssc.blob.core.windows.net/nact...</td>\n",
1365
+ " <td>NACTI : CA-17_07_01_2016_CA-17_0038090.JPG</td>\n",
1366
+ " <td>NACTI : unknown</td>\n",
1367
+ " <td>NACTI : Lebec, California</td>\n",
1368
+ " <td>-1</td>\n",
1369
+ " <td>bos taurus</td>\n",
1370
+ " <td>bos taurus</td>\n",
1371
+ " <td>domestic cow</td>\n",
1372
+ " <td>NaN</td>\n",
1373
+ " <td>...</td>\n",
1374
+ " <td>NaN</td>\n",
1375
+ " <td>NaN</td>\n",
1376
+ " <td>bovidae</td>\n",
1377
+ " <td>bovinae</td>\n",
1378
+ " <td>bovini</td>\n",
1379
+ " <td>bos</td>\n",
1380
+ " <td>bos taurus</td>\n",
1381
+ " <td>NaN</td>\n",
1382
+ " <td>NaN</td>\n",
1383
+ " <td>False</td>\n",
1384
+ " </tr>\n",
1385
+ " <tr>\n",
1386
+ " <th>2050788</th>\n",
1387
+ " <td>NACTI</td>\n",
1388
+ " <td>https://lilablobssc.blob.core.windows.net/nact...</td>\n",
1389
+ " <td>NACTI : FL-12_08_04_2016_FL-12_0071339.JPG</td>\n",
1390
+ " <td>NACTI : unknown</td>\n",
1391
+ " <td>NACTI : Archbold, FL</td>\n",
1392
+ " <td>-1</td>\n",
1393
+ " <td>bos taurus</td>\n",
1394
+ " <td>bos taurus</td>\n",
1395
+ " <td>domestic cow</td>\n",
1396
+ " <td>NaN</td>\n",
1397
+ " <td>...</td>\n",
1398
+ " <td>NaN</td>\n",
1399
+ " <td>NaN</td>\n",
1400
+ " <td>bovidae</td>\n",
1401
+ " <td>bovinae</td>\n",
1402
+ " <td>bovini</td>\n",
1403
+ " <td>bos</td>\n",
1404
+ " <td>bos taurus</td>\n",
1405
+ " <td>NaN</td>\n",
1406
+ " <td>NaN</td>\n",
1407
+ " <td>False</td>\n",
1408
+ " </tr>\n",
1409
+ " <tr>\n",
1410
+ " <th>12610859</th>\n",
1411
+ " <td>Snapshot Serengeti</td>\n",
1412
+ " <td>https://lilablobssc.blob.core.windows.net/snap...</td>\n",
1413
+ " <td>Snapshot Serengeti : S9/F07/F07_R2/S9_F07_R2_I...</td>\n",
1414
+ " <td>Snapshot Serengeti : SER_S9#F07#2#50</td>\n",
1415
+ " <td>Snapshot Serengeti : F07</td>\n",
1416
+ " <td>1</td>\n",
1417
+ " <td>elephant</td>\n",
1418
+ " <td>loxodonta africana</td>\n",
1419
+ " <td>african bush elephant</td>\n",
1420
+ " <td>10-16-2014 09:44:07</td>\n",
1421
+ " <td>...</td>\n",
1422
+ " <td>NaN</td>\n",
1423
+ " <td>NaN</td>\n",
1424
+ " <td>elephantidae</td>\n",
1425
+ " <td>NaN</td>\n",
1426
+ " <td>NaN</td>\n",
1427
+ " <td>loxodonta</td>\n",
1428
+ " <td>loxodonta africana</td>\n",
1429
+ " <td>NaN</td>\n",
1430
+ " <td>NaN</td>\n",
1431
+ " <td>True</td>\n",
1432
+ " </tr>\n",
1433
+ " <tr>\n",
1434
+ " <th>2463379</th>\n",
1435
+ " <td>NACTI</td>\n",
1436
+ " <td>https://lilablobssc.blob.core.windows.net/nact...</td>\n",
1437
+ " <td>NACTI : FL-21_07_29_2015_FL-21_0010466.jpg</td>\n",
1438
+ " <td>NACTI : unknown</td>\n",
1439
+ " <td>NACTI : Archbold, FL</td>\n",
1440
+ " <td>-1</td>\n",
1441
+ " <td>bos taurus</td>\n",
1442
+ " <td>bos taurus</td>\n",
1443
+ " <td>domestic cow</td>\n",
1444
+ " <td>NaN</td>\n",
1445
+ " <td>...</td>\n",
1446
+ " <td>NaN</td>\n",
1447
+ " <td>NaN</td>\n",
1448
+ " <td>bovidae</td>\n",
1449
+ " <td>bovinae</td>\n",
1450
+ " <td>bovini</td>\n",
1451
+ " <td>bos</td>\n",
1452
+ " <td>bos taurus</td>\n",
1453
+ " <td>NaN</td>\n",
1454
+ " <td>NaN</td>\n",
1455
+ " <td>False</td>\n",
1456
+ " </tr>\n",
1457
+ " <tr>\n",
1458
+ " <th>1296206</th>\n",
1459
+ " <td>NACTI</td>\n",
1460
+ " <td>https://lilablobssc.blob.core.windows.net/nact...</td>\n",
1461
+ " <td>NACTI : CA-42_10_06_2016_CA-42_0022200.JPG</td>\n",
1462
+ " <td>NACTI : unknown</td>\n",
1463
+ " <td>NACTI : Lebec, California</td>\n",
1464
+ " <td>-1</td>\n",
1465
+ " <td>lynx rufus</td>\n",
1466
+ " <td>lynx rufus</td>\n",
1467
+ " <td>bobcat</td>\n",
1468
+ " <td>NaN</td>\n",
1469
+ " <td>...</td>\n",
1470
+ " <td>NaN</td>\n",
1471
+ " <td>NaN</td>\n",
1472
+ " <td>felidae</td>\n",
1473
+ " <td>felinae</td>\n",
1474
+ " <td>NaN</td>\n",
1475
+ " <td>lynx</td>\n",
1476
+ " <td>lynx rufus</td>\n",
1477
+ " <td>NaN</td>\n",
1478
+ " <td>NaN</td>\n",
1479
+ " <td>False</td>\n",
1480
+ " </tr>\n",
1481
+ " <tr>\n",
1482
+ " <th>4026992</th>\n",
1483
+ " <td>WCS Camera Traps</td>\n",
1484
+ " <td>https://lilablobssc.blob.core.windows.net/wcs-...</td>\n",
1485
+ " <td>WCS Camera Traps : 098d7290-92d5-11e9-bb41-000...</td>\n",
1486
+ " <td>WCS Camera Traps : bol-017-d0050-90</td>\n",
1487
+ " <td>WCS Camera Traps : 650</td>\n",
1488
+ " <td>12</td>\n",
1489
+ " <td>tayassu pecari</td>\n",
1490
+ " <td>tayassu pecari</td>\n",
1491
+ " <td>white-lipped peccary</td>\n",
1492
+ " <td>08-28-2012 11:19:47</td>\n",
1493
+ " <td>...</td>\n",
1494
+ " <td>NaN</td>\n",
1495
+ " <td>NaN</td>\n",
1496
+ " <td>tayassuidae</td>\n",
1497
+ " <td>NaN</td>\n",
1498
+ " <td>NaN</td>\n",
1499
+ " <td>tayassu</td>\n",
1500
+ " <td>tayassu pecari</td>\n",
1501
+ " <td>NaN</td>\n",
1502
+ " <td>NaN</td>\n",
1503
+ " <td>False</td>\n",
1504
+ " </tr>\n",
1505
+ " <tr>\n",
1506
+ " <th>4754539</th>\n",
1507
+ " <td>WCS Camera Traps</td>\n",
1508
+ " <td>https://lilablobssc.blob.core.windows.net/wcs-...</td>\n",
1509
+ " <td>WCS Camera Traps : 8f8a4dee-92d5-11e9-a3af-000...</td>\n",
1510
+ " <td>WCS Camera Traps : unknown</td>\n",
1511
+ " <td>WCS Camera Traps : 4326</td>\n",
1512
+ " <td>-1</td>\n",
1513
+ " <td>tinamus major</td>\n",
1514
+ " <td>tinamus major</td>\n",
1515
+ " <td>great tinamou</td>\n",
1516
+ " <td>07-31-2013 05:43:18</td>\n",
1517
+ " <td>...</td>\n",
1518
+ " <td>NaN</td>\n",
1519
+ " <td>NaN</td>\n",
1520
+ " <td>tinamidae</td>\n",
1521
+ " <td>NaN</td>\n",
1522
+ " <td>NaN</td>\n",
1523
+ " <td>tinamus</td>\n",
1524
+ " <td>tinamus major</td>\n",
1525
+ " <td>NaN</td>\n",
1526
+ " <td>NaN</td>\n",
1527
+ " <td>False</td>\n",
1528
+ " </tr>\n",
1529
+ " </tbody>\n",
1530
+ "</table>\n",
1531
+ "<p>10 rows × 31 columns</p>\n",
1532
+ "</div>"
1533
+ ],
1534
+ "text/plain": [
1535
+ " dataset_name \n",
1536
+ "15355844 SWG Camera Traps \\\n",
1537
+ "15098255 SWG Camera Traps \n",
1538
+ "15750309 SWG Camera Traps \n",
1539
+ "812622 NACTI \n",
1540
+ "2050788 NACTI \n",
1541
+ "12610859 Snapshot Serengeti \n",
1542
+ "2463379 NACTI \n",
1543
+ "1296206 NACTI \n",
1544
+ "4026992 WCS Camera Traps \n",
1545
+ "4754539 WCS Camera Traps \n",
1546
+ "\n",
1547
+ " url \n",
1548
+ "15355844 https://lilablobssc.blob.core.windows.net/swg-... \\\n",
1549
+ "15098255 https://lilablobssc.blob.core.windows.net/swg-... \n",
1550
+ "15750309 https://lilablobssc.blob.core.windows.net/swg-... \n",
1551
+ "812622 https://lilablobssc.blob.core.windows.net/nact... \n",
1552
+ "2050788 https://lilablobssc.blob.core.windows.net/nact... \n",
1553
+ "12610859 https://lilablobssc.blob.core.windows.net/snap... \n",
1554
+ "2463379 https://lilablobssc.blob.core.windows.net/nact... \n",
1555
+ "1296206 https://lilablobssc.blob.core.windows.net/nact... \n",
1556
+ "4026992 https://lilablobssc.blob.core.windows.net/wcs-... \n",
1557
+ "4754539 https://lilablobssc.blob.core.windows.net/wcs-... \n",
1558
+ "\n",
1559
+ " image_id \n",
1560
+ "15355844 SWG Camera Traps : cebffb73-8c29-11eb-92ab-000... \\\n",
1561
+ "15098255 SWG Camera Traps : cc2b9e0b-8c29-11eb-bd63-000... \n",
1562
+ "15750309 SWG Camera Traps : d29fd7c0-8c29-11eb-9d65-000... \n",
1563
+ "812622 NACTI : CA-17_07_01_2016_CA-17_0038090.JPG \n",
1564
+ "2050788 NACTI : FL-12_08_04_2016_FL-12_0071339.JPG \n",
1565
+ "12610859 Snapshot Serengeti : S9/F07/F07_R2/S9_F07_R2_I... \n",
1566
+ "2463379 NACTI : FL-21_07_29_2015_FL-21_0010466.jpg \n",
1567
+ "1296206 NACTI : CA-42_10_06_2016_CA-42_0022200.JPG \n",
1568
+ "4026992 WCS Camera Traps : 098d7290-92d5-11e9-bb41-000... \n",
1569
+ "4754539 WCS Camera Traps : 8f8a4dee-92d5-11e9-a3af-000... \n",
1570
+ "\n",
1571
+ " sequence_id \n",
1572
+ "15355844 SWG Camera Traps : e42a22f0-8c29-11eb-9c41-000... \\\n",
1573
+ "15098255 SWG Camera Traps : 2801caa6-8c2a-11eb-9118-000... \n",
1574
+ "15750309 SWG Camera Traps : 39b3e643-8c2a-11eb-b05f-000... \n",
1575
+ "812622 NACTI : unknown \n",
1576
+ "2050788 NACTI : unknown \n",
1577
+ "12610859 Snapshot Serengeti : SER_S9#F07#2#50 \n",
1578
+ "2463379 NACTI : unknown \n",
1579
+ "1296206 NACTI : unknown \n",
1580
+ "4026992 WCS Camera Traps : bol-017-d0050-90 \n",
1581
+ "4754539 WCS Camera Traps : unknown \n",
1582
+ "\n",
1583
+ " location_id frame_num original_label \n",
1584
+ "15355844 SWG Camera Traps : loc_0263 2 large_antlered_muntjac \\\n",
1585
+ "15098255 SWG Camera Traps : loc_0512 2 ferret_badger \n",
1586
+ "15750309 SWG Camera Traps : loc_0588 7 stump_tailed_macaque \n",
1587
+ "812622 NACTI : Lebec, California -1 bos taurus \n",
1588
+ "2050788 NACTI : Archbold, FL -1 bos taurus \n",
1589
+ "12610859 Snapshot Serengeti : F07 1 elephant \n",
1590
+ "2463379 NACTI : Archbold, FL -1 bos taurus \n",
1591
+ "1296206 NACTI : Lebec, California -1 lynx rufus \n",
1592
+ "4026992 WCS Camera Traps : 650 12 tayassu pecari \n",
1593
+ "4754539 WCS Camera Traps : 4326 -1 tinamus major \n",
1594
+ "\n",
1595
+ " scientific_name common_name datetime \n",
1596
+ "15355844 muntiacus vuquangensis large-antlered muntjac 06-24-2019 19:36:35 \\\n",
1597
+ "15098255 melogale ferret badger 07-08-2020 21:03:55 \n",
1598
+ "15750309 macaca arctoides stump-tailed macaque 08-26-2019 10:52:49 \n",
1599
+ "812622 bos taurus domestic cow NaN \n",
1600
+ "2050788 bos taurus domestic cow NaN \n",
1601
+ "12610859 loxodonta africana african bush elephant 10-16-2014 09:44:07 \n",
1602
+ "2463379 bos taurus domestic cow NaN \n",
1603
+ "1296206 lynx rufus bobcat NaN \n",
1604
+ "4026992 tayassu pecari white-lipped peccary 08-28-2012 11:19:47 \n",
1605
+ "4754539 tinamus major great tinamou 07-31-2013 05:43:18 \n",
1606
+ "\n",
1607
+ " ... infraorder superfamily family subfamily \n",
1608
+ "15355844 ... NaN NaN cervidae cervinae \\\n",
1609
+ "15098255 ... NaN NaN mustelidae helictidinae \n",
1610
+ "15750309 ... simiiformes NaN cercopithecidae cercopithecinae \n",
1611
+ "812622 ... NaN NaN bovidae bovinae \n",
1612
+ "2050788 ... NaN NaN bovidae bovinae \n",
1613
+ "12610859 ... NaN NaN elephantidae NaN \n",
1614
+ "2463379 ... NaN NaN bovidae bovinae \n",
1615
+ "1296206 ... NaN NaN felidae felinae \n",
1616
+ "4026992 ... NaN NaN tayassuidae NaN \n",
1617
+ "4754539 ... NaN NaN tinamidae NaN \n",
1618
+ "\n",
1619
+ " tribe genus species subspecies variety \n",
1620
+ "15355844 muntiacini muntiacus muntiacus vuquangensis NaN NaN \\\n",
1621
+ "15098255 NaN melogale NaN NaN NaN \n",
1622
+ "15750309 papionini macaca macaca arctoides NaN NaN \n",
1623
+ "812622 bovini bos bos taurus NaN NaN \n",
1624
+ "2050788 bovini bos bos taurus NaN NaN \n",
1625
+ "12610859 NaN loxodonta loxodonta africana NaN NaN \n",
1626
+ "2463379 bovini bos bos taurus NaN NaN \n",
1627
+ "1296206 NaN lynx lynx rufus NaN NaN \n",
1628
+ "4026992 NaN tayassu tayassu pecari NaN NaN \n",
1629
+ "4754539 NaN tinamus tinamus major NaN NaN \n",
1630
+ "\n",
1631
+ " url_dupe \n",
1632
+ "15355844 False \n",
1633
+ "15098255 False \n",
1634
+ "15750309 False \n",
1635
+ "812622 False \n",
1636
+ "2050788 False \n",
1637
+ "12610859 True \n",
1638
+ "2463379 False \n",
1639
+ "1296206 False \n",
1640
+ "4026992 False \n",
1641
+ "4754539 False \n",
1642
+ "\n",
1643
+ "[10 rows x 31 columns]"
1644
+ ]
1645
+ },
1646
+ "execution_count": 30,
1647
+ "metadata": {},
1648
+ "output_type": "execute_result"
1649
+ }
1650
+ ],
1651
+ "source": [
1652
+ "df_genusSpecies.sample(10)"
1653
+ ]
1654
+ },
1655
+ {
1656
+ "cell_type": "code",
1657
+ "execution_count": 31,
1658
+ "metadata": {},
1659
+ "outputs": [
1660
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1661
+ "data": {
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1678
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1679
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1680
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+ " <th>sequence_id</th>\n",
1685
+ " <th>location_id</th>\n",
1686
+ " <th>frame_num</th>\n",
1687
+ " <th>original_label</th>\n",
1688
+ " <th>scientific_name</th>\n",
1689
+ " <th>common_name</th>\n",
1690
+ " <th>datetime</th>\n",
1691
+ " <th>...</th>\n",
1692
+ " <th>infraorder</th>\n",
1693
+ " <th>superfamily</th>\n",
1694
+ " <th>family</th>\n",
1695
+ " <th>subfamily</th>\n",
1696
+ " <th>tribe</th>\n",
1697
+ " <th>genus</th>\n",
1698
+ " <th>species</th>\n",
1699
+ " <th>subspecies</th>\n",
1700
+ " <th>variety</th>\n",
1701
+ " <th>url_dupe</th>\n",
1702
+ " </tr>\n",
1703
+ " </thead>\n",
1704
+ " <tbody>\n",
1705
+ " <tr>\n",
1706
+ " <th>495</th>\n",
1707
+ " <td>Caltech Camera Traps</td>\n",
1708
+ " <td>https://lilablobssc.blob.core.windows.net/calt...</td>\n",
1709
+ " <td>Caltech Camera Traps : 5a1cafe6-23d2-11e8-a6a3...</td>\n",
1710
+ " <td>Caltech Camera Traps : 70139a99-5567-11e8-bb56...</td>\n",
1711
+ " <td>Caltech Camera Traps : 61</td>\n",
1712
+ " <td>3</td>\n",
1713
+ " <td>badger</td>\n",
1714
+ " <td>taxidea taxus</td>\n",
1715
+ " <td>badger</td>\n",
1716
+ " <td>10-20-2013 23:01:55</td>\n",
1717
+ " <td>...</td>\n",
1718
+ " <td>NaN</td>\n",
1719
+ " <td>NaN</td>\n",
1720
+ " <td>mustelidae</td>\n",
1721
+ " <td>taxidiinae</td>\n",
1722
+ " <td>NaN</td>\n",
1723
+ " <td>taxidea</td>\n",
1724
+ " <td>taxidea taxus</td>\n",
1725
+ " <td>NaN</td>\n",
1726
+ " <td>NaN</td>\n",
1727
+ " <td>True</td>\n",
1728
+ " </tr>\n",
1729
+ " <tr>\n",
1730
+ " <th>496</th>\n",
1731
+ " <td>Caltech Camera Traps</td>\n",
1732
+ " <td>https://lilablobssc.blob.core.windows.net/calt...</td>\n",
1733
+ " <td>Caltech Camera Traps : 5a1cafe6-23d2-11e8-a6a3...</td>\n",
1734
+ " <td>Caltech Camera Traps : 70139a99-5567-11e8-bb56...</td>\n",
1735
+ " <td>Caltech Camera Traps : 61</td>\n",
1736
+ " <td>3</td>\n",
1737
+ " <td>coyote</td>\n",
1738
+ " <td>canis latrans</td>\n",
1739
+ " <td>coyote</td>\n",
1740
+ " <td>10-20-2013 23:01:55</td>\n",
1741
+ " <td>...</td>\n",
1742
+ " <td>NaN</td>\n",
1743
+ " <td>NaN</td>\n",
1744
+ " <td>canidae</td>\n",
1745
+ " <td>NaN</td>\n",
1746
+ " <td>NaN</td>\n",
1747
+ " <td>canis</td>\n",
1748
+ " <td>canis latrans</td>\n",
1749
+ " <td>NaN</td>\n",
1750
+ " <td>NaN</td>\n",
1751
+ " <td>True</td>\n",
1752
+ " </tr>\n",
1753
+ " <tr>\n",
1754
+ " <th>2645</th>\n",
1755
+ " <td>Caltech Camera Traps</td>\n",
1756
+ " <td>https://lilablobssc.blob.core.windows.net/calt...</td>\n",
1757
+ " <td>Caltech Camera Traps : 5968bf89-23d2-11e8-a6a3...</td>\n",
1758
+ " <td>Caltech Camera Traps : 6f0b1bdc-5567-11e8-8df3...</td>\n",
1759
+ " <td>Caltech Camera Traps : 43</td>\n",
1760
+ " <td>1</td>\n",
1761
+ " <td>squirrel</td>\n",
1762
+ " <td>sciurus</td>\n",
1763
+ " <td>squirrel</td>\n",
1764
+ " <td>07-24-2011 16:29:50</td>\n",
1765
+ " <td>...</td>\n",
1766
+ " <td>NaN</td>\n",
1767
+ " <td>NaN</td>\n",
1768
+ " <td>sciuridae</td>\n",
1769
+ " <td>sciurinae</td>\n",
1770
+ " <td>sciurini</td>\n",
1771
+ " <td>sciurus</td>\n",
1772
+ " <td>NaN</td>\n",
1773
+ " <td>NaN</td>\n",
1774
+ " <td>NaN</td>\n",
1775
+ " <td>True</td>\n",
1776
+ " </tr>\n",
1777
+ " <tr>\n",
1778
+ " <th>2646</th>\n",
1779
+ " <td>Caltech Camera Traps</td>\n",
1780
+ " <td>https://lilablobssc.blob.core.windows.net/calt...</td>\n",
1781
+ " <td>Caltech Camera Traps : 5968bf89-23d2-11e8-a6a3...</td>\n",
1782
+ " <td>Caltech Camera Traps : 6f0b1bdc-5567-11e8-8df3...</td>\n",
1783
+ " <td>Caltech Camera Traps : 43</td>\n",
1784
+ " <td>1</td>\n",
1785
+ " <td>bobcat</td>\n",
1786
+ " <td>lynx rufus</td>\n",
1787
+ " <td>bobcat</td>\n",
1788
+ " <td>07-24-2011 16:29:50</td>\n",
1789
+ " <td>...</td>\n",
1790
+ " <td>NaN</td>\n",
1791
+ " <td>NaN</td>\n",
1792
+ " <td>felidae</td>\n",
1793
+ " <td>felinae</td>\n",
1794
+ " <td>NaN</td>\n",
1795
+ " <td>lynx</td>\n",
1796
+ " <td>lynx rufus</td>\n",
1797
+ " <td>NaN</td>\n",
1798
+ " <td>NaN</td>\n",
1799
+ " <td>True</td>\n",
1800
+ " </tr>\n",
1801
+ " <tr>\n",
1802
+ " <th>14220</th>\n",
1803
+ " <td>Caltech Camera Traps</td>\n",
1804
+ " <td>https://lilablobssc.blob.core.windows.net/calt...</td>\n",
1805
+ " <td>Caltech Camera Traps : 59a49aa6-23d2-11e8-a6a3...</td>\n",
1806
+ " <td>Caltech Camera Traps : 70139a99-5567-11e8-bb56...</td>\n",
1807
+ " <td>Caltech Camera Traps : 61</td>\n",
1808
+ " <td>1</td>\n",
1809
+ " <td>badger</td>\n",
1810
+ " <td>taxidea taxus</td>\n",
1811
+ " <td>badger</td>\n",
1812
+ " <td>10-20-2013 23:01:53</td>\n",
1813
+ " <td>...</td>\n",
1814
+ " <td>NaN</td>\n",
1815
+ " <td>NaN</td>\n",
1816
+ " <td>mustelidae</td>\n",
1817
+ " <td>taxidiinae</td>\n",
1818
+ " <td>NaN</td>\n",
1819
+ " <td>taxidea</td>\n",
1820
+ " <td>taxidea taxus</td>\n",
1821
+ " <td>NaN</td>\n",
1822
+ " <td>NaN</td>\n",
1823
+ " <td>True</td>\n",
1824
+ " </tr>\n",
1825
+ " <tr>\n",
1826
+ " <th>14221</th>\n",
1827
+ " <td>Caltech Camera Traps</td>\n",
1828
+ " <td>https://lilablobssc.blob.core.windows.net/calt...</td>\n",
1829
+ " <td>Caltech Camera Traps : 59a49aa6-23d2-11e8-a6a3...</td>\n",
1830
+ " <td>Caltech Camera Traps : 70139a99-5567-11e8-bb56...</td>\n",
1831
+ " <td>Caltech Camera Traps : 61</td>\n",
1832
+ " <td>1</td>\n",
1833
+ " <td>coyote</td>\n",
1834
+ " <td>canis latrans</td>\n",
1835
+ " <td>coyote</td>\n",
1836
+ " <td>10-20-2013 23:01:53</td>\n",
1837
+ " <td>...</td>\n",
1838
+ " <td>NaN</td>\n",
1839
+ " <td>NaN</td>\n",
1840
+ " <td>canidae</td>\n",
1841
+ " <td>NaN</td>\n",
1842
+ " <td>NaN</td>\n",
1843
+ " <td>canis</td>\n",
1844
+ " <td>canis latrans</td>\n",
1845
+ " <td>NaN</td>\n",
1846
+ " <td>NaN</td>\n",
1847
+ " <td>True</td>\n",
1848
+ " </tr>\n",
1849
+ " <tr>\n",
1850
+ " <th>45115</th>\n",
1851
+ " <td>Caltech Camera Traps</td>\n",
1852
+ " <td>https://lilablobssc.blob.core.windows.net/calt...</td>\n",
1853
+ " <td>Caltech Camera Traps : 59a7bb76-23d2-11e8-a6a3...</td>\n",
1854
+ " <td>Caltech Camera Traps : 70139a35-5567-11e8-b800...</td>\n",
1855
+ " <td>Caltech Camera Traps : 61</td>\n",
1856
+ " <td>1</td>\n",
1857
+ " <td>badger</td>\n",
1858
+ " <td>taxidea taxus</td>\n",
1859
+ " <td>badger</td>\n",
1860
+ " <td>10-20-2013 23:01:49</td>\n",
1861
+ " <td>...</td>\n",
1862
+ " <td>NaN</td>\n",
1863
+ " <td>NaN</td>\n",
1864
+ " <td>mustelidae</td>\n",
1865
+ " <td>taxidiinae</td>\n",
1866
+ " <td>NaN</td>\n",
1867
+ " <td>taxidea</td>\n",
1868
+ " <td>taxidea taxus</td>\n",
1869
+ " <td>NaN</td>\n",
1870
+ " <td>NaN</td>\n",
1871
+ " <td>True</td>\n",
1872
+ " </tr>\n",
1873
+ " <tr>\n",
1874
+ " <th>45116</th>\n",
1875
+ " <td>Caltech Camera Traps</td>\n",
1876
+ " <td>https://lilablobssc.blob.core.windows.net/calt...</td>\n",
1877
+ " <td>Caltech Camera Traps : 59a7bb76-23d2-11e8-a6a3...</td>\n",
1878
+ " <td>Caltech Camera Traps : 70139a35-5567-11e8-b800...</td>\n",
1879
+ " <td>Caltech Camera Traps : 61</td>\n",
1880
+ " <td>1</td>\n",
1881
+ " <td>coyote</td>\n",
1882
+ " <td>canis latrans</td>\n",
1883
+ " <td>coyote</td>\n",
1884
+ " <td>10-20-2013 23:01:49</td>\n",
1885
+ " <td>...</td>\n",
1886
+ " <td>NaN</td>\n",
1887
+ " <td>NaN</td>\n",
1888
+ " <td>canidae</td>\n",
1889
+ " <td>NaN</td>\n",
1890
+ " <td>NaN</td>\n",
1891
+ " <td>canis</td>\n",
1892
+ " <td>canis latrans</td>\n",
1893
+ " <td>NaN</td>\n",
1894
+ " <td>NaN</td>\n",
1895
+ " <td>True</td>\n",
1896
+ " </tr>\n",
1897
+ " <tr>\n",
1898
+ " <th>50215</th>\n",
1899
+ " <td>Caltech Camera Traps</td>\n",
1900
+ " <td>https://lilablobssc.blob.core.windows.net/calt...</td>\n",
1901
+ " <td>Caltech Camera Traps : 59f5fd71-23d2-11e8-a6a3...</td>\n",
1902
+ " <td>Caltech Camera Traps : 70139a35-5567-11e8-b800...</td>\n",
1903
+ " <td>Caltech Camera Traps : 61</td>\n",
1904
+ " <td>2</td>\n",
1905
+ " <td>badger</td>\n",
1906
+ " <td>taxidea taxus</td>\n",
1907
+ " <td>badger</td>\n",
1908
+ " <td>10-20-2013 23:01:50</td>\n",
1909
+ " <td>...</td>\n",
1910
+ " <td>NaN</td>\n",
1911
+ " <td>NaN</td>\n",
1912
+ " <td>mustelidae</td>\n",
1913
+ " <td>taxidiinae</td>\n",
1914
+ " <td>NaN</td>\n",
1915
+ " <td>taxidea</td>\n",
1916
+ " <td>taxidea taxus</td>\n",
1917
+ " <td>NaN</td>\n",
1918
+ " <td>NaN</td>\n",
1919
+ " <td>True</td>\n",
1920
+ " </tr>\n",
1921
+ " <tr>\n",
1922
+ " <th>50216</th>\n",
1923
+ " <td>Caltech Camera Traps</td>\n",
1924
+ " <td>https://lilablobssc.blob.core.windows.net/calt...</td>\n",
1925
+ " <td>Caltech Camera Traps : 59f5fd71-23d2-11e8-a6a3...</td>\n",
1926
+ " <td>Caltech Camera Traps : 70139a35-5567-11e8-b800...</td>\n",
1927
+ " <td>Caltech Camera Traps : 61</td>\n",
1928
+ " <td>2</td>\n",
1929
+ " <td>coyote</td>\n",
1930
+ " <td>canis latrans</td>\n",
1931
+ " <td>coyote</td>\n",
1932
+ " <td>10-20-2013 23:01:50</td>\n",
1933
+ " <td>...</td>\n",
1934
+ " <td>NaN</td>\n",
1935
+ " <td>NaN</td>\n",
1936
+ " <td>canidae</td>\n",
1937
+ " <td>NaN</td>\n",
1938
+ " <td>NaN</td>\n",
1939
+ " <td>canis</td>\n",
1940
+ " <td>canis latrans</td>\n",
1941
+ " <td>NaN</td>\n",
1942
+ " <td>NaN</td>\n",
1943
+ " <td>True</td>\n",
1944
+ " </tr>\n",
1945
+ " </tbody>\n",
1946
+ "</table>\n",
1947
+ "<p>10 rows × 31 columns</p>\n",
1948
+ "</div>"
1949
+ ],
1950
+ "text/plain": [
1951
+ " dataset_name \n",
1952
+ "495 Caltech Camera Traps \\\n",
1953
+ "496 Caltech Camera Traps \n",
1954
+ "2645 Caltech Camera Traps \n",
1955
+ "2646 Caltech Camera Traps \n",
1956
+ "14220 Caltech Camera Traps \n",
1957
+ "14221 Caltech Camera Traps \n",
1958
+ "45115 Caltech Camera Traps \n",
1959
+ "45116 Caltech Camera Traps \n",
1960
+ "50215 Caltech Camera Traps \n",
1961
+ "50216 Caltech Camera Traps \n",
1962
+ "\n",
1963
+ " url \n",
1964
+ "495 https://lilablobssc.blob.core.windows.net/calt... \\\n",
1965
+ "496 https://lilablobssc.blob.core.windows.net/calt... \n",
1966
+ "2645 https://lilablobssc.blob.core.windows.net/calt... \n",
1967
+ "2646 https://lilablobssc.blob.core.windows.net/calt... \n",
1968
+ "14220 https://lilablobssc.blob.core.windows.net/calt... \n",
1969
+ "14221 https://lilablobssc.blob.core.windows.net/calt... \n",
1970
+ "45115 https://lilablobssc.blob.core.windows.net/calt... \n",
1971
+ "45116 https://lilablobssc.blob.core.windows.net/calt... \n",
1972
+ "50215 https://lilablobssc.blob.core.windows.net/calt... \n",
1973
+ "50216 https://lilablobssc.blob.core.windows.net/calt... \n",
1974
+ "\n",
1975
+ " image_id \n",
1976
+ "495 Caltech Camera Traps : 5a1cafe6-23d2-11e8-a6a3... \\\n",
1977
+ "496 Caltech Camera Traps : 5a1cafe6-23d2-11e8-a6a3... \n",
1978
+ "2645 Caltech Camera Traps : 5968bf89-23d2-11e8-a6a3... \n",
1979
+ "2646 Caltech Camera Traps : 5968bf89-23d2-11e8-a6a3... \n",
1980
+ "14220 Caltech Camera Traps : 59a49aa6-23d2-11e8-a6a3... \n",
1981
+ "14221 Caltech Camera Traps : 59a49aa6-23d2-11e8-a6a3... \n",
1982
+ "45115 Caltech Camera Traps : 59a7bb76-23d2-11e8-a6a3... \n",
1983
+ "45116 Caltech Camera Traps : 59a7bb76-23d2-11e8-a6a3... \n",
1984
+ "50215 Caltech Camera Traps : 59f5fd71-23d2-11e8-a6a3... \n",
1985
+ "50216 Caltech Camera Traps : 59f5fd71-23d2-11e8-a6a3... \n",
1986
+ "\n",
1987
+ " sequence_id \n",
1988
+ "495 Caltech Camera Traps : 70139a99-5567-11e8-bb56... \\\n",
1989
+ "496 Caltech Camera Traps : 70139a99-5567-11e8-bb56... \n",
1990
+ "2645 Caltech Camera Traps : 6f0b1bdc-5567-11e8-8df3... \n",
1991
+ "2646 Caltech Camera Traps : 6f0b1bdc-5567-11e8-8df3... \n",
1992
+ "14220 Caltech Camera Traps : 70139a99-5567-11e8-bb56... \n",
1993
+ "14221 Caltech Camera Traps : 70139a99-5567-11e8-bb56... \n",
1994
+ "45115 Caltech Camera Traps : 70139a35-5567-11e8-b800... \n",
1995
+ "45116 Caltech Camera Traps : 70139a35-5567-11e8-b800... \n",
1996
+ "50215 Caltech Camera Traps : 70139a35-5567-11e8-b800... \n",
1997
+ "50216 Caltech Camera Traps : 70139a35-5567-11e8-b800... \n",
1998
+ "\n",
1999
+ " location_id frame_num original_label scientific_name \n",
2000
+ "495 Caltech Camera Traps : 61 3 badger taxidea taxus \\\n",
2001
+ "496 Caltech Camera Traps : 61 3 coyote canis latrans \n",
2002
+ "2645 Caltech Camera Traps : 43 1 squirrel sciurus \n",
2003
+ "2646 Caltech Camera Traps : 43 1 bobcat lynx rufus \n",
2004
+ "14220 Caltech Camera Traps : 61 1 badger taxidea taxus \n",
2005
+ "14221 Caltech Camera Traps : 61 1 coyote canis latrans \n",
2006
+ "45115 Caltech Camera Traps : 61 1 badger taxidea taxus \n",
2007
+ "45116 Caltech Camera Traps : 61 1 coyote canis latrans \n",
2008
+ "50215 Caltech Camera Traps : 61 2 badger taxidea taxus \n",
2009
+ "50216 Caltech Camera Traps : 61 2 coyote canis latrans \n",
2010
+ "\n",
2011
+ " common_name datetime ... infraorder superfamily \n",
2012
+ "495 badger 10-20-2013 23:01:55 ... NaN NaN \\\n",
2013
+ "496 coyote 10-20-2013 23:01:55 ... NaN NaN \n",
2014
+ "2645 squirrel 07-24-2011 16:29:50 ... NaN NaN \n",
2015
+ "2646 bobcat 07-24-2011 16:29:50 ... NaN NaN \n",
2016
+ "14220 badger 10-20-2013 23:01:53 ... NaN NaN \n",
2017
+ "14221 coyote 10-20-2013 23:01:53 ... NaN NaN \n",
2018
+ "45115 badger 10-20-2013 23:01:49 ... NaN NaN \n",
2019
+ "45116 coyote 10-20-2013 23:01:49 ... NaN NaN \n",
2020
+ "50215 badger 10-20-2013 23:01:50 ... NaN NaN \n",
2021
+ "50216 coyote 10-20-2013 23:01:50 ... NaN NaN \n",
2022
+ "\n",
2023
+ " family subfamily tribe genus species subspecies \n",
2024
+ "495 mustelidae taxidiinae NaN taxidea taxidea taxus NaN \\\n",
2025
+ "496 canidae NaN NaN canis canis latrans NaN \n",
2026
+ "2645 sciuridae sciurinae sciurini sciurus NaN NaN \n",
2027
+ "2646 felidae felinae NaN lynx lynx rufus NaN \n",
2028
+ "14220 mustelidae taxidiinae NaN taxidea taxidea taxus NaN \n",
2029
+ "14221 canidae NaN NaN canis canis latrans NaN \n",
2030
+ "45115 mustelidae taxidiinae NaN taxidea taxidea taxus NaN \n",
2031
+ "45116 canidae NaN NaN canis canis latrans NaN \n",
2032
+ "50215 mustelidae taxidiinae NaN taxidea taxidea taxus NaN \n",
2033
+ "50216 canidae NaN NaN canis canis latrans NaN \n",
2034
+ "\n",
2035
+ " variety url_dupe \n",
2036
+ "495 NaN True \n",
2037
+ "496 NaN True \n",
2038
+ "2645 NaN True \n",
2039
+ "2646 NaN True \n",
2040
+ "14220 NaN True \n",
2041
+ "14221 NaN True \n",
2042
+ "45115 NaN True \n",
2043
+ "45116 NaN True \n",
2044
+ "50215 NaN True \n",
2045
+ "50216 NaN True \n",
2046
+ "\n",
2047
+ "[10 rows x 31 columns]"
2048
+ ]
2049
+ },
2050
+ "execution_count": 31,
2051
+ "metadata": {},
2052
+ "output_type": "execute_result"
2053
+ }
2054
+ ],
2055
+ "source": [
2056
+ "duplicated_urls = df_genusSpecies.loc[df_genusSpecies.url_dupe]\n",
2057
+ "duplicated_urls.head(10)"
2058
+ ]
2059
+ },
2060
+ {
2061
+ "cell_type": "markdown",
2062
+ "metadata": {},
2063
+ "source": [
2064
+ "From this small sample, it looks like they are distinguished by their frame number (`frame_num`) and the animal itself--there is more than one animal (of a different species) in frame so it duplicates the image information because there is an entry for each species of animal in the image."
2065
+ ]
2066
+ },
2067
+ {
2068
+ "cell_type": "markdown",
2069
+ "metadata": {},
2070
+ "source": [
2071
+ "We have 1,046,985 distinct sequence IDs for the 6,901,819 unique image IDs, suggesting an average of 6 images per sequence?"
2072
+ ]
2073
+ },
2074
+ {
2075
+ "cell_type": "code",
2076
+ "execution_count": null,
2077
+ "metadata": {},
2078
+ "outputs": [],
2079
+ "source": []
2080
+ }
2081
+ ],
2082
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