Overview

Dataset statistics

Number of variables14
Number of observations1275
Missing cells6
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory142.1 KiB
Average record size in memory114.1 B

Variable types

Text5
Categorical6
DateTime1
Numeric2

Dataset

Description전주시에서 보호중인 유기동물 현황입니다. 공고번호, 공고기간, 보호장소, 접수일시, 발생장소, 축종, 품종, 색상, 성별 등을 제공합니다.항목 : 공고번호, 공고기간, 보호장소, 접수일시, 발생장소, 축종, 품종, 색상, 성별, 체중, 나이, 업무진행단계, 중성화, 처리결과관련부서 : 동물복지과
Author전북특별자치도 전주시
URLhttps://www.data.go.kr/data/15075145/fileData.do

Alerts

처리결과 is highly overall correlated with 업무진행단계High correlation
업무진행단계 is highly overall correlated with 처리결과High correlation
체중 is highly overall correlated with 나이High correlation
나이 is highly overall correlated with 체중High correlation
중성화 is highly imbalanced (57.3%)Imbalance

Reproduction

Analysis started2024-03-15 02:07:38.773160
Analysis finished2024-03-15 02:07:43.120004
Duration4.35 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공고번호
Text

Distinct1274
Distinct (%)100.0%
Missing1
Missing (%)0.1%
Memory size10.1 KiB
2024-03-15T11:07:43.767545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length16
Min length16

Characters and Unicode

Total characters20384
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1274 ?
Unique (%)100.0%

Sample

1st row전북-전주-2022-00104
2nd row전북-전주-2022-00103
3rd row전북-전주-2022-00102
4th row전북-전주-2022-00101
5th row전북-전주-2022-00100
ValueCountFrequency (%)
전북-전주-2022-00104 1
 
0.1%
전북-전주-2021-00435 1
 
0.1%
전북-전주-2021-00428 1
 
0.1%
전북-전주-2021-00429 1
 
0.1%
전북-전주-2021-00430 1
 
0.1%
전북-전주-2021-00431 1
 
0.1%
전북-전주-2021-00432 1
 
0.1%
전북-전주-2021-00433 1
 
0.1%
전북-전주-2021-00424 1
 
0.1%
전북-전주-2021-00436 1
 
0.1%
Other values (1264) 1264
99.2%
2024-03-15T11:07:44.954469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4199
20.6%
- 3822
18.8%
2 3003
14.7%
전 2548
12.5%
1 1791
8.8%
북 1274
 
6.2%
주 1274
 
6.2%
3 359
 
1.8%
4 358
 
1.8%
6 356
 
1.7%
Other values (4) 1400
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11466
56.2%
Other Letter 5096
25.0%
Dash Punctuation 3822
 
18.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4199
36.6%
2 3003
26.2%
1 1791
15.6%
3 359
 
3.1%
4 358
 
3.1%
6 356
 
3.1%
5 355
 
3.1%
7 354
 
3.1%
9 346
 
3.0%
8 345
 
3.0%
Other Letter
ValueCountFrequency (%)
전 2548
50.0%
북 1274
25.0%
주 1274
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 3822
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15288
75.0%
Hangul 5096
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4199
27.5%
- 3822
25.0%
2 3003
19.6%
1 1791
11.7%
3 359
 
2.3%
4 358
 
2.3%
6 356
 
2.3%
5 355
 
2.3%
7 354
 
2.3%
9 346
 
2.3%
Hangul
ValueCountFrequency (%)
전 2548
50.0%
북 1274
25.0%
주 1274
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15288
75.0%
Hangul 5096
 
25.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4199
27.5%
- 3822
25.0%
2 3003
19.6%
1 1791
11.7%
3 359
 
2.3%
4 358
 
2.3%
6 356
 
2.3%
5 355
 
2.3%
7 354
 
2.3%
9 346
 
2.3%
Hangul
ValueCountFrequency (%)
전 2548
50.0%
북 1274
25.0%
주 1274
25.0%

공고기간
Text

Distinct219
Distinct (%)17.2%
Missing1
Missing (%)0.1%
Memory size10.1 KiB
2024-03-15T11:07:45.733658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length21
Mean length21
Min length21

Characters and Unicode

Total characters26754
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)1.9%

Sample

1st row2022-02-06~2022-02-15
2nd row2022-02-06~2022-02-15
3rd row2022-02-06~2022-02-15
4th row2022-02-05~2022-02-14
5th row2022-02-05~2022-02-14
ValueCountFrequency (%)
2021-06-16~2021-06-25 22
 
1.7%
2021-06-14~2021-06-23 20
 
1.6%
2021-02-06~2021-02-15 20
 
1.6%
2021-05-28~2021-06-07 20
 
1.6%
2021-05-31~2021-06-09 18
 
1.4%
2021-06-15~2021-06-24 18
 
1.4%
2021-04-27~2021-05-06 18
 
1.4%
2021-06-02~2021-06-11 17
 
1.3%
2021-07-13~2021-07-22 15
 
1.2%
2021-05-03~2021-05-12 14
 
1.1%
Other values (209) 1092
85.7%
2024-03-15T11:07:46.865344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 6729
25.2%
0 6056
22.6%
- 5096
19.0%
1 3849
14.4%
~ 1274
 
4.8%
5 827
 
3.1%
6 792
 
3.0%
4 603
 
2.3%
3 573
 
2.1%
7 527
 
2.0%
Other values (2) 428
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20384
76.2%
Dash Punctuation 5096
 
19.0%
Math Symbol 1274
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 6729
33.0%
0 6056
29.7%
1 3849
18.9%
5 827
 
4.1%
6 792
 
3.9%
4 603
 
3.0%
3 573
 
2.8%
7 527
 
2.6%
8 240
 
1.2%
9 188
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 5096
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1274
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26754
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 6729
25.2%
0 6056
22.6%
- 5096
19.0%
1 3849
14.4%
~ 1274
 
4.8%
5 827
 
3.1%
6 792
 
3.0%
4 603
 
2.3%
3 573
 
2.1%
7 527
 
2.0%
Other values (2) 428
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26754
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 6729
25.2%
0 6056
22.6%
- 5096
19.0%
1 3849
14.4%
~ 1274
 
4.8%
5 827
 
3.1%
6 792
 
3.0%
4 603
 
2.3%
3 573
 
2.1%
7 527
 
2.0%
Other values (2) 428
 
1.6%

보호장소
Categorical

Distinct11
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
전북특별자치도 전주시 덕진구 인후동1가 806-6
315 
전북특별자치도 전주시 완산구 삼천동1가 592-1
225 
전북특별자치도 전주시 완산구 경원동1가 3-10
183 
전북특별자치도 전주시 완산구 전주천서로 111 (서서학동)
149 
전북특별자치도 전주시 완산구 다가동3가 충경로 11 (다가동3가, 늘푸른동물병원)
101 
Other values (6)
302 

Length

Max length46
Median length39
Mean length29.552157
Min length22

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전북특별자치도 전주시 덕진구 인후동1가 806-6
2nd row전북특별자치도 전주시 덕진구 인후동1가 806-6
3rd row전북특별자치도 전주시 덕진구 인후동1가 806-6
4th row전북특별자치도 전주시 완산구 삼천동1가 592-1
5th row전북특별자치도 전주시 완산구 전주천서로 111 (서서학동)

Common Values

ValueCountFrequency (%)
전북특별자치도 전주시 덕진구 인후동1가 806-6 315
24.7%
전북특별자치도 전주시 완산구 삼천동1가 592-1 225
17.6%
전북특별자치도 전주시 완산구 경원동1가 3-10 183
14.4%
전북특별자치도 전주시 완산구 전주천서로 111 (서서학동) 149
11.7%
전북특별자치도 전주시 완산구 다가동3가 충경로 11 (다가동3가, 늘푸른동물병원) 101
 
7.9%
전북특별자치도 전주시 덕진구 덕진동2가 송천중앙로 17 (덕진동2가) 79
 
6.2%
전북특별자치도 전주시 완산구 서신동 831-4 72
 
5.6%
전북특별자치도 전주시 덕진구 송천동1가 626-42 70
 
5.5%
전북특별자치도 전주시 완산구 서신동 28 56
 
4.4%
전북특별자치도 전주시 덕진구 인후동1가 928-1 20
 
1.6%

Length

2024-03-15T11:07:47.096728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전북특별자치도 1275
18.2%
전주시 1275
18.2%
완산구 791
11.3%
덕진구 484
 
6.9%
인후동1가 335
 
4.8%
806-6 315
 
4.5%
삼천동1가 225
 
3.2%
592-1 225
 
3.2%
다가동3가 202
 
2.9%
경원동1가 183
 
2.6%
Other values (19) 1680
24.0%

접수일시
Date

Distinct218
Distinct (%)17.1%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
Minimum2021-01-01 00:00:00
Maximum2022-02-06 00:00:00
2024-03-15T11:07:47.455314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:07:47.904357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

발생장소
Text

Distinct832
Distinct (%)65.3%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
2024-03-15T11:07:49.144579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length8.8886275
Min length3

Characters and Unicode

Total characters11333
Distinct characters414
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique643 ?
Unique (%)50.4%

Sample

1st row인후동 더샾아파트
2nd row중화산동 현대2차아파트
3rd row아중부영3차아파트
4th row중화산동 골드클레스앞
5th row인후동1가 공원
ValueCountFrequency (%)
주변 102
 
4.0%
근처 67
 
2.6%
송천동 38
 
1.5%
부근 28
 
1.1%
쑥고개 26
 
1.0%
평화동 26
 
1.0%
인근 26
 
1.0%
앞 25
 
1.0%
우아동 22
 
0.9%
완산구 20
 
0.8%
Other values (1050) 2173
85.1%
2024-03-15T11:07:50.635707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1323
 
11.7%
동 504
 
4.4%
1 282
 
2.5%
주 269
 
2.4%
아 268
 
2.4%
2 236
 
2.1%
3 196
 
1.7%
로 184
 
1.6%
변 182
 
1.6%
트 179
 
1.6%
Other values (404) 7710
68.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8328
73.5%
Decimal Number 1426
 
12.6%
Space Separator 1323
 
11.7%
Dash Punctuation 172
 
1.5%
Uppercase Letter 59
 
0.5%
Lowercase Letter 15
 
0.1%
Open Punctuation 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Other Punctuation 3
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 504
 
6.1%
주 269
 
3.2%
아 268
 
3.2%
로 184
 
2.2%
변 182
 
2.2%
트 179
 
2.1%
근 177
 
2.1%
파 175
 
2.1%
길 173
 
2.1%
산 142
 
1.7%
Other values (362) 6075
72.9%
Uppercase Letter
ValueCountFrequency (%)
T 8
13.6%
P 8
13.6%
A 8
13.6%
B 7
11.9%
S 6
10.2%
N 5
8.5%
L 5
8.5%
C 3
 
5.1%
H 3
 
5.1%
K 2
 
3.4%
Other values (3) 4
6.8%
Lowercase Letter
ValueCountFrequency (%)
s 2
13.3%
a 2
13.3%
p 2
13.3%
t 2
13.3%
k 1
6.7%
j 1
6.7%
g 1
6.7%
w 1
6.7%
c 1
6.7%
y 1
6.7%
Decimal Number
ValueCountFrequency (%)
1 282
19.8%
2 236
16.5%
3 196
13.7%
4 139
9.7%
7 115
8.1%
5 100
 
7.0%
0 100
 
7.0%
6 94
 
6.6%
8 87
 
6.1%
9 77
 
5.4%
Other Punctuation
ValueCountFrequency (%)
; 1
33.3%
# 1
33.3%
& 1
33.3%
Space Separator
ValueCountFrequency (%)
1323
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 172
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8328
73.5%
Common 2931
 
25.9%
Latin 74
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 504
 
6.1%
주 269
 
3.2%
아 268
 
3.2%
로 184
 
2.2%
변 182
 
2.2%
트 179
 
2.1%
근 177
 
2.1%
파 175
 
2.1%
길 173
 
2.1%
산 142
 
1.7%
Other values (362) 6075
72.9%
Latin
ValueCountFrequency (%)
T 8
10.8%
P 8
10.8%
A 8
10.8%
B 7
 
9.5%
S 6
 
8.1%
N 5
 
6.8%
L 5
 
6.8%
C 3
 
4.1%
H 3
 
4.1%
s 2
 
2.7%
Other values (14) 19
25.7%
Common
ValueCountFrequency (%)
1323
45.1%
1 282
 
9.6%
2 236
 
8.1%
3 196
 
6.7%
- 172
 
5.9%
4 139
 
4.7%
7 115
 
3.9%
5 100
 
3.4%
0 100
 
3.4%
6 94
 
3.2%
Other values (8) 174
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8328
73.5%
ASCII 3005
 
26.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1323
44.0%
1 282
 
9.4%
2 236
 
7.9%
3 196
 
6.5%
- 172
 
5.7%
4 139
 
4.6%
7 115
 
3.8%
5 100
 
3.3%
0 100
 
3.3%
6 94
 
3.1%
Other values (32) 248
 
8.3%
Hangul
ValueCountFrequency (%)
동 504
 
6.1%
주 269
 
3.2%
아 268
 
3.2%
로 184
 
2.2%
변 182
 
2.2%
트 179
 
2.1%
근 177
 
2.1%
파 175
 
2.1%
길 173
 
2.1%
산 142
 
1.7%
Other values (362) 6075
72.9%

축종
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
개
700 
고양이
567 
기타
 
8

Length

Max length3
Median length1
Mean length1.8956863
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row개
2nd row개
3rd row고양이
4th row고양이
5th row고양이

Common Values

ValueCountFrequency (%)
개 700
54.9%
고양이 567
44.5%
기타 8
 
0.6%

Length

2024-03-15T11:07:51.056393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T11:07:51.381311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개 700
54.9%
고양이 567
44.5%
기타 8
 
0.6%

품종
Text

Distinct58
Distinct (%)4.6%
Missing2
Missing (%)0.2%
Memory size10.1 KiB
2024-03-15T11:07:52.264571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length4.5176748
Min length1

Characters and Unicode

Total characters5751
Distinct characters127
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)1.6%

Sample

1st row말티즈
2nd row삽살개
3rd row한국 고양이
4th row한국 고양이
5th row한국 고양이
ValueCountFrequency (%)
한국 525
28.0%
고양이 525
28.0%
믹스견 450
24.0%
푸들 44
 
2.3%
말티즈 41
 
2.2%
진도견 30
 
1.6%
포메라니안 22
 
1.2%
시츄 11
 
0.6%
리트리버 9
 
0.5%
시바 8
 
0.4%
Other values (67) 211
11.2%
2024-03-15T11:07:53.610926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
603
10.5%
이 536
9.3%
고 529
9.2%
한 525
9.1%
국 525
9.1%
양 525
9.1%
견 480
8.3%
스 471
8.2%
믹 455
7.9%
시 64
 
1.1%
Other values (117) 1038
18.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5143
89.4%
Space Separator 603
 
10.5%
Dash Punctuation 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 536
10.4%
고 529
10.3%
한 525
10.2%
국 525
10.2%
양 525
10.2%
견 480
9.3%
스 471
9.2%
믹 455
8.8%
시 64
 
1.2%
안 54
 
1.0%
Other values (115) 979
19.0%
Space Separator
ValueCountFrequency (%)
603
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5143
89.4%
Common 608
 
10.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 536
10.4%
고 529
10.3%
한 525
10.2%
국 525
10.2%
양 525
10.2%
견 480
9.3%
스 471
9.2%
믹 455
8.8%
시 64
 
1.2%
안 54
 
1.0%
Other values (115) 979
19.0%
Common
ValueCountFrequency (%)
603
99.2%
- 5
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5143
89.4%
ASCII 608
 
10.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
603
99.2%
- 5
 
0.8%
Hangul
ValueCountFrequency (%)
이 536
10.4%
고 529
10.3%
한 525
10.2%
국 525
10.2%
양 525
10.2%
견 480
9.3%
스 471
9.2%
믹 455
8.8%
시 64
 
1.2%
안 54
 
1.0%
Other values (115) 979
19.0%

색상
Text

Distinct159
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
2024-03-15T11:07:54.532035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length3.2447059
Min length1

Characters and Unicode

Total characters4137
Distinct characters73
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)5.6%

Sample

1st row흰색
2nd row흰색
3rd row흰색갈색
4th row갈/검정색
5th row고등어
ValueCountFrequency (%)
흰색 303
22.1%
갈색 151
 
11.0%
검정 71
 
5.2%
흰색검정 65
 
4.7%
흰색갈색 61
 
4.5%
삼색 53
 
3.9%
검정색 40
 
2.9%
검갈색 33
 
2.4%
흰/검정색 28
 
2.0%
검정/흰색 25
 
1.8%
Other values (115) 539
39.4%
2024-03-15T11:07:56.013911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
색 1242
30.0%
흰 620
15.0%
검 421
 
10.2%
갈 380
 
9.2%
정 328
 
7.9%
/ 136
 
3.3%
113
 
2.7%
, 79
 
1.9%
삼 77
 
1.9%
백 66
 
1.6%
Other values (63) 675
16.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3808
92.0%
Other Punctuation 215
 
5.2%
Space Separator 113
 
2.7%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
색 1242
32.6%
흰 620
16.3%
검 421
 
11.1%
갈 380
 
10.0%
정 328
 
8.6%
삼 77
 
2.0%
백 66
 
1.7%
회 64
 
1.7%
치 56
 
1.5%
즈 56
 
1.5%
Other values (59) 498
13.1%
Other Punctuation
ValueCountFrequency (%)
/ 136
63.3%
, 79
36.7%
Space Separator
ValueCountFrequency (%)
113
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3808
92.0%
Common 329
 
8.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
색 1242
32.6%
흰 620
16.3%
검 421
 
11.1%
갈 380
 
10.0%
정 328
 
8.6%
삼 77
 
2.0%
백 66
 
1.7%
회 64
 
1.7%
치 56
 
1.5%
즈 56
 
1.5%
Other values (59) 498
13.1%
Common
ValueCountFrequency (%)
/ 136
41.3%
113
34.3%
, 79
24.0%
+ 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3808
92.0%
ASCII 329
 
8.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
색 1242
32.6%
흰 620
16.3%
검 421
 
11.1%
갈 380
 
10.0%
정 328
 
8.6%
삼 77
 
2.0%
백 66
 
1.7%
회 64
 
1.7%
치 56
 
1.5%
즈 56
 
1.5%
Other values (59) 498
13.1%
ASCII
ValueCountFrequency (%)
/ 136
41.3%
113
34.3%
, 79
24.0%
+ 1
 
0.3%

성별
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
수컷
663 
암컷
590 
미상
 
22

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수컷
2nd row수컷
3rd row수컷
4th row암컷
5th row수컷

Common Values

ValueCountFrequency (%)
수컷 663
52.0%
암컷 590
46.3%
미상 22
 
1.7%

Length

2024-03-15T11:07:56.451787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T11:07:56.801020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수컷 663
52.0%
암컷 590
46.3%
미상 22
 
1.7%

체중
Real number (ℝ)

HIGH CORRELATION 

Distinct172
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1583843
Minimum0
Maximum35
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size11.3 KiB
2024-03-15T11:07:57.254904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.2
Q10.6
median2.6
Q35
95-th percentile16.65
Maximum35
Range35
Interquartile range (IQR)4.4

Descriptive statistics

Standard deviation5.4424463
Coefficient of variation (CV)1.3087887
Kurtosis7.7611625
Mean4.1583843
Median Absolute Deviation (MAD)2
Skewness2.5796642
Sum5301.94
Variance29.620222
MonotonicityNot monotonic
2024-03-15T11:07:57.731286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.3 60
 
4.7%
1.0 57
 
4.5%
0.1 48
 
3.8%
0.6 48
 
3.8%
3.0 44
 
3.5%
0.4 36
 
2.8%
0.2 35
 
2.7%
2.0 34
 
2.7%
0.5 33
 
2.6%
4.0 32
 
2.5%
Other values (162) 848
66.5%
ValueCountFrequency (%)
0.0 1
 
0.1%
0.02 2
 
0.2%
0.06 2
 
0.2%
0.07 1
 
0.1%
0.09 3
 
0.2%
0.1 48
3.8%
0.12 1
 
0.1%
0.14 1
 
0.1%
0.16 4
 
0.3%
0.2 35
2.7%
ValueCountFrequency (%)
35.0 3
 
0.2%
33.0 1
 
0.1%
32.0 1
 
0.1%
30.0 5
0.4%
29.0 1
 
0.1%
28.7 1
 
0.1%
27.0 1
 
0.1%
26.0 1
 
0.1%
25.0 8
0.6%
24.0 1
 
0.1%

나이
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)1.3%
Missing2
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean2019.8028
Minimum2007
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.3 KiB
2024-03-15T11:07:58.138443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2007
5-th percentile2015
Q12019
median2021
Q32021
95-th percentile2021
Maximum2022
Range15
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.2193952
Coefficient of variation (CV)0.0010988178
Kurtosis6.2735357
Mean2019.8028
Median Absolute Deviation (MAD)0
Skewness-2.3148635
Sum2571209
Variance4.9257153
MonotonicityNot monotonic
2024-03-15T11:07:58.413117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2021 740
58.0%
2019 119
 
9.3%
2020 113
 
8.9%
2018 94
 
7.4%
2022 52
 
4.1%
2017 50
 
3.9%
2016 38
 
3.0%
2015 16
 
1.3%
2014 15
 
1.2%
2011 15
 
1.2%
Other values (6) 21
 
1.6%
ValueCountFrequency (%)
2007 1
 
0.1%
2008 3
 
0.2%
2009 2
 
0.2%
2010 1
 
0.1%
2011 15
 
1.2%
2012 2
 
0.2%
2013 12
 
0.9%
2014 15
 
1.2%
2015 16
1.3%
2016 38
3.0%
ValueCountFrequency (%)
2022 52
 
4.1%
2021 740
58.0%
2020 113
 
8.9%
2019 119
 
9.3%
2018 94
 
7.4%
2017 50
 
3.9%
2016 38
 
3.0%
2015 16
 
1.3%
2014 15
 
1.2%
2013 12
 
0.9%

업무진행단계
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
종료
976 
보호중
299 

Length

Max length3
Median length2
Mean length2.2345098
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row보호중
2nd row보호중
3rd row보호중
4th row종료
5th row보호중

Common Values

ValueCountFrequency (%)
종료 976
76.5%
보호중 299
 
23.5%

Length

2024-03-15T11:07:58.784364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T11:07:59.107178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종료 976
76.5%
보호중 299
 
23.5%

중성화
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
아니오
1112 
<NA>
 
93
예
 
70

Length

Max length4
Median length3
Mean length2.9631373
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row아니오
2nd row아니오
3rd row아니오
4th row예
5th row아니오

Common Values

ValueCountFrequency (%)
아니오 1112
87.2%
<NA> 93
 
7.3%
예 70
 
5.5%

Length

2024-03-15T11:07:59.322824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T11:07:59.581055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
아니오 1112
87.2%
na 93
 
7.3%
예 70
 
5.5%

처리결과
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
입양
532 
<NA>
299 
자연사
222 
반환
170 
안락사
 
40

Length

Max length4
Median length2
Mean length2.6745098
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row안락사
5th row<NA>

Common Values

ValueCountFrequency (%)
입양 532
41.7%
<NA> 299
23.5%
자연사 222
17.4%
반환 170
 
13.3%
안락사 40
 
3.1%
방사 12
 
0.9%

Length

2024-03-15T11:08:00.014442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T11:08:00.398134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
입양 532
41.7%
na 299
23.5%
자연사 222
17.4%
반환 170
 
13.3%
안락사 40
 
3.1%
방사 12
 
0.9%

Interactions

2024-03-15T11:07:41.058504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:07:40.412602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:07:41.351580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:07:40.690435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T11:08:00.656991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
보호장소축종품종성별체중나이업무진행단계중성화처리결과
보호장소1.0000.2220.4080.5810.1730.2510.2210.0920.341
축종0.2221.0001.0000.2730.5520.4190.1260.0330.433
품종0.4081.0001.0000.0000.8460.6560.3650.5040.542
성별0.5810.2730.0001.0000.0610.0000.0070.1100.119
체중0.1730.5520.8460.0611.0000.5980.2610.3500.550
나이0.2510.4190.6560.0000.5981.0000.0000.5050.578
업무진행단계0.2210.1260.3650.0070.2610.0001.0000.101NaN
중성화0.0920.0330.5040.1100.3500.5050.1011.0000.196
처리결과0.3410.4330.5420.1190.5500.578NaN0.1961.000
2024-03-15T11:08:01.021373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
축종처리결과업무진행단계중성화보호장소성별
축종1.0000.3630.2080.0540.1310.090
처리결과0.3631.0001.0000.2400.1950.089
업무진행단계0.2081.0001.0000.0640.2110.011
중성화0.0540.2400.0641.0000.0880.182
보호장소0.1310.1950.2110.0881.0000.413
성별0.0900.0890.0110.1820.4131.000
2024-03-15T11:08:01.284814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체중나이보호장소축종성별업무진행단계중성화처리결과
체중1.000-0.6130.0730.3890.0500.1800.2560.261
나이-0.6131.0000.1100.2770.0000.0000.3880.278
보호장소0.0730.1101.0000.1310.4130.2110.0880.195
축종0.3890.2770.1311.0000.0900.2080.0540.363
성별0.0500.0000.4130.0901.0000.0110.1820.089
업무진행단계0.1800.0000.2110.2080.0111.0000.0641.000
중성화0.2560.3880.0880.0540.1820.0641.0000.240
처리결과0.2610.2780.1950.3630.0891.0000.2401.000

Missing values

2024-03-15T11:07:41.794084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T11:07:42.425270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-03-15T11:07:42.904215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

공고번호공고기간보호장소접수일시발생장소축종품종색상성별체중나이업무진행단계중성화처리결과
0전북-전주-2022-001042022-02-06~2022-02-15전북특별자치도 전주시 덕진구 인후동1가 806-62022-02-06인후동 더샾아파트개말티즈흰색수컷4.72015보호중아니오<NA>
1전북-전주-2022-001032022-02-06~2022-02-15전북특별자치도 전주시 덕진구 인후동1가 806-62022-02-06중화산동 현대2차아파트개삽살개흰색수컷18.02018보호중아니오<NA>
2전북-전주-2022-001022022-02-06~2022-02-15전북특별자치도 전주시 덕진구 인후동1가 806-62022-02-06아중부영3차아파트고양이한국 고양이흰색갈색수컷1.22022보호중아니오<NA>
3전북-전주-2022-001012022-02-05~2022-02-14전북특별자치도 전주시 완산구 삼천동1가 592-12022-02-05중화산동 골드클레스앞고양이한국 고양이갈/검정색암컷2.82019종료예안락사
4전북-전주-2022-001002022-02-05~2022-02-14전북특별자치도 전주시 완산구 전주천서로 111 (서서학동)2022-02-05인후동1가 공원고양이한국 고양이고등어수컷0.22022보호중아니오<NA>
5전북-전주-2022-000992022-02-04~2022-02-14전북특별자치도 전주시 덕진구 덕진동2가 송천중앙로 17 (덕진동2가)2022-02-04반월동사무소부근개포메라니안흰색수컷3.02014종료<NA>반환
6전북-전주-2022-000982022-02-03~2022-02-14전북특별자치도 전주시 완산구 삼천동1가 592-12022-02-03대왕장미아파트개믹스견흰색암컷12.02022보호중아니오<NA>
7전북-전주-2022-000972022-02-10~2022-02-21전북특별자치도 전주시 덕진구 인후동1가 806-62022-02-03경기전길 23개믹스견흰색수컷13.02022보호중아니오<NA>
8전북-전주-2022-000962022-02-03~2022-02-14전북특별자치도 전주시 덕진구 인후동1가 806-62022-02-03호성동 동아아파트 도로변고양이한국 고양이흰색검정암컷2.82022보호중아니오<NA>
9전북-전주-2022-000952022-02-02~2022-02-11전북특별자치도 전주시 덕진구 인후동1가 806-62022-02-02원동 청복마을개믹스견흰색암컷7.02022보호중아니오<NA>
공고번호공고기간보호장소접수일시발생장소축종품종색상성별체중나이업무진행단계중성화처리결과
1265전북-전주-2021-000102021-01-04~2021-01-13전북특별자치도 전주시 완산구 전주천서로 111 (서서학동)2021-01-04평화동 노란통닭개믹스견밸갈수컷1.72021종료아니오입양
1266전북-전주-2021-000092021-01-04~2021-01-13전북특별자치도 전주시 완산구 전주천서로 111 (서서학동)2021-01-04평화동 노란통닭개믹스견갈암컷1.82021종료아니오입양
1267전북-전주-2021-000082021-01-04~2021-01-13전북특별자치도 전주시 완산구 전주천서로 111 (서서학동)2021-01-04평화동 노란통닭개믹스견백갈수컷1.72021종료아니오입양
1268전북-전주-2021-000072021-01-03~2021-01-12전북특별자치도 전주시 완산구 경원동1가 3-102021-01-02서신동한일동아아파트경비실고양이한국 고양이흰색검정수컷0.42021종료아니오입양
1269전북-전주-2021-000062021-01-02~2021-01-11전북특별자치도 전주시 덕진구 인후동1가 806-62021-01-02견훤로 181 앞 도로변개믹스견흰색검정수컷10.02019종료아니오반환
1270전북-전주-2021-000052021-01-02~2021-01-11전북특별자치도 전주시 덕진구 인후동1가 806-62021-01-02여의동 대승아파트고양이한국 고양이삼색암컷3.02019종료아니오방사
1271전북-전주-2021-000042021-01-01~2021-01-11전북특별자치도 전주시 덕진구 인후동1가 806-62021-01-01치명자산 주차장개믹스견흰색갈색수컷2.02021종료아니오입양
1272전북-전주-2021-000032021-01-01~2021-01-11전북특별자치도 전주시 덕진구 인후동1가 806-62021-01-01아중초등학교 주변개믹스견흰색검정수컷6.02018종료아니오입양
1273전북-전주-2021-000022021-01-01~2021-01-11전북특별자치도 전주시 완산구 전주천서로 111 (서서학동)2021-01-01평화동 노랑통닭근처 공원개말티즈흰색암컷2.72018종료<NA>입양
1274전북-전주-2021-000012021-01-01~2021-01-11전북특별자치도 전주시 완산구 다가동3가 충경로 11 (다가동3가, 늘푸른동물병원)2021-01-01점미동 고물상 앞개믹스견갈색암컷3.92017종료아니오자연사