Overview

Dataset statistics

Number of variables32
Number of observations57
Missing cells258
Missing cells (%)14.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.5 KiB
Average record size in memory261.3 B

Variable types

Text14
Categorical13
DateTime2
Numeric3

Dataset

Description충남 야생동물 구조센터에서 구조한 야생동물의 종, 구조시점, 위치 자료 및 구조 이후 조치결과에 대한 자료 중, 청양군 내에서 발생한 구조 건에 대한 자료임
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=69&beforeMenuCd=DOM_000000201001001000&publicdatapk=15109281

Alerts

천연기념물 has constant value ""Constant
멸종위기등급 has constant value ""Constant
야생동물보호협약 has constant value ""Constant
이첩 방생 위치 has 43 (75.4%) missing valuesMissing
방생위도 has 46 (80.7%) missing valuesMissing
방생경도 has 46 (80.7%) missing valuesMissing
발견장소상세 has 11 (19.3%) missing valuesMissing
TM구조위도 has 10 (17.5%) missing valuesMissing
TM구조경도 has 10 (17.5%) missing valuesMissing
TM방생위도 has 46 (80.7%) missing valuesMissing
TM방생경도 has 46 (80.7%) missing valuesMissing
접수번호 has unique valuesUnique
구조고도 has 2 (3.5%) zerosZeros

Reproduction

Analysis started2024-01-09 22:38:26.668854
Analysis finished2024-01-09 22:38:27.179764
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

접수번호
Text

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2024-01-10T07:38:27.330151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters513
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)100.0%

Sample

1st row2019-1377
2nd row2019-1158
3rd row2019-1159
4th row2019-1160
5th row2019-1471
ValueCountFrequency (%)
2019-1377 1
 
1.8%
2021-0519 1
 
1.8%
2021-1593 1
 
1.8%
2021-1416 1
 
1.8%
2021-1489 1
 
1.8%
2021-0394 1
 
1.8%
2021-0481 1
 
1.8%
2021-1035 1
 
1.8%
2021-1194 1
 
1.8%
2021-1205 1
 
1.8%
Other values (47) 47
82.5%
2024-01-10T07:38:27.644393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 132
25.7%
0 102
19.9%
1 91
17.7%
- 57
11.1%
9 30
 
5.8%
6 24
 
4.7%
4 20
 
3.9%
5 19
 
3.7%
3 17
 
3.3%
7 11
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 456
88.9%
Dash Punctuation 57
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 132
28.9%
0 102
22.4%
1 91
20.0%
9 30
 
6.6%
6 24
 
5.3%
4 20
 
4.4%
5 19
 
4.2%
3 17
 
3.7%
7 11
 
2.4%
8 10
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 57
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 513
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 132
25.7%
0 102
19.9%
1 91
17.7%
- 57
11.1%
9 30
 
5.8%
6 24
 
4.7%
4 20
 
3.9%
5 19
 
3.7%
3 17
 
3.3%
7 11
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 513
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 132
25.7%
0 102
19.9%
1 91
17.7%
- 57
11.1%
9 30
 
5.8%
6 24
 
4.7%
4 20
 
3.9%
5 19
 
3.7%
3 17
 
3.3%
7 11
 
2.1%

동물국문명
Categorical

Distinct21
Distinct (%)36.8%
Missing0
Missing (%)0.0%
Memory size588.0 B
고라니
17 
너구리
10 
까치
5 
제비
4 
참새
3 
Other values (16)
18 

Length

Max length8
Median length3
Mean length3
Min length2

Unique

Unique14 ?
Unique (%)24.6%

Sample

1st row멧비둘기
2nd row제비
3rd row제비
4th row제비
5th row황로

Common Values

ValueCountFrequency (%)
고라니 17
29.8%
너구리 10
17.5%
까치 5
 
8.8%
제비 4
 
7.0%
참새 3
 
5.3%
멧비둘기 2
 
3.5%
박새 2
 
3.5%
호랑지빠귀 1
 
1.8%
황로 1
 
1.8%
집박쥐 1
 
1.8%
Other values (11) 11
19.3%

Length

2024-01-10T07:38:27.770064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고라니 17
29.8%
너구리 10
17.5%
까치 5
 
8.8%
제비 4
 
7.0%
참새 3
 
5.3%
멧비둘기 2
 
3.5%
박새 2
 
3.5%
파랑새 1
 
1.8%
물총새 1
 
1.8%
대백로 1
 
1.8%
Other values (11) 11
19.3%

강
Categorical

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
포유강(Mammalia)
29 
조강(Aves)
28 

Length

Max length13
Median length13
Mean length10.54386
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row조강(Aves)
2nd row조강(Aves)
3rd row조강(Aves)
4th row조강(Aves)
5th row조강(Aves)

Common Values

ValueCountFrequency (%)
포유강(Mammalia) 29
50.9%
조강(Aves) 28
49.1%

Length

2024-01-10T07:38:27.886444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:38:27.970283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
포유강(mammalia 29
50.9%
조강(aves 28
49.1%

목
Categorical

Distinct9
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Memory size588.0 B
참새목
18 
소목
17 
식육목
10 
황새목
5 
비둘기목
2 
Other values (4)
5 

Length

Max length5
Median length3
Mean length2.7894737
Min length2

Unique

Unique3 ?
Unique (%)5.3%

Sample

1st row비둘기목
2nd row참새목
3rd row참새목
4th row참새목
5th row황새목

Common Values

ValueCountFrequency (%)
참새목 18
31.6%
소목 17
29.8%
식육목 10
17.5%
황새목 5
 
8.8%
비둘기목 2
 
3.5%
파랑새목 2
 
3.5%
박쥐목 1
 
1.8%
딱다구리목 1
 
1.8%
쥐목 1
 
1.8%

Length

2024-01-10T07:38:28.077514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:38:28.210581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
참새목 18
31.6%
소목 17
29.8%
식육목 10
17.5%
황새목 5
 
8.8%
비둘기목 2
 
3.5%
파랑새목 2
 
3.5%
박쥐목 1
 
1.8%
딱다구리목 1
 
1.8%
쥐목 1
 
1.8%

과
Categorical

Distinct15
Distinct (%)26.3%
Missing0
Missing (%)0.0%
Memory size588.0 B
사슴과
17 
개과
10 
까마귀과
6 
왜가리과
5 
제비과
4 
Other values (10)
15 

Length

Max length5
Median length4
Mean length3.2280702
Min length2

Unique

Unique6 ?
Unique (%)10.5%

Sample

1st row비둘기과
2nd row제비과
3rd row제비과
4th row제비과
5th row왜가리과

Common Values

ValueCountFrequency (%)
사슴과 17
29.8%
개과 10
17.5%
까마귀과 6
 
10.5%
왜가리과 5
 
8.8%
제비과 4
 
7.0%
참새과 3
 
5.3%
비둘기과 2
 
3.5%
박새과 2
 
3.5%
지빠귀과 2
 
3.5%
애기박쥐과 1
 
1.8%
Other values (5) 5
 
8.8%

Length

2024-01-10T07:38:28.333612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
사슴과 17
29.8%
개과 10
17.5%
까마귀과 6
 
10.5%
왜가리과 5
 
8.8%
제비과 4
 
7.0%
참새과 3
 
5.3%
비둘기과 2
 
3.5%
박새과 2
 
3.5%
지빠귀과 2
 
3.5%
애기박쥐과 1
 
1.8%
Other values (5) 5
 
8.8%

천연기념물
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size588.0 B
해당없음
57 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row해당없음
2nd row해당없음
3rd row해당없음
4th row해당없음
5th row해당없음

Common Values

ValueCountFrequency (%)
해당없음 57
100.0%

Length

2024-01-10T07:38:28.433212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:38:28.505874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 57
100.0%

멸종위기등급
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size588.0 B
해당없음
57 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row해당없음
2nd row해당없음
3rd row해당없음
4th row해당없음
5th row해당없음

Common Values

ValueCountFrequency (%)
해당없음 57
100.0%

Length

2024-01-10T07:38:28.579782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:38:28.881448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 57
100.0%

야생동물보호협약
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size588.0 B
해당없음
57 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row해당없음
2nd row해당없음
3rd row해당없음
4th row해당없음
5th row해당없음

Common Values

ValueCountFrequency (%)
해당없음 57
100.0%

Length

2024-01-10T07:38:28.960002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:38:29.035461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 57
100.0%

구조일시
Date

Distinct47
Distinct (%)82.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
Minimum2019-05-31 00:00:00
Maximum2022-12-30 00:00:00
2024-01-10T07:38:29.120271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:38:29.235960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)

구조결과일자
Date

Distinct50
Distinct (%)87.7%
Missing0
Missing (%)0.0%
Memory size588.0 B
Minimum2019-05-31 00:00:00
Maximum2023-01-02 00:00:00
2024-01-10T07:38:29.358152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:38:29.485762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

구조결과
Categorical

Distinct7
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Memory size588.0 B
안락사
16 
방생
13 
폐사체
13 
폐사
9 
DOA
4 
Other values (2)
2 

Length

Max length3
Median length3
Mean length2.5789474
Min length2

Unique

Unique2 ?
Unique (%)3.5%

Sample

1st row안락사
2nd row방생
3rd row방생
4th row폐사체
5th row안락사

Common Values

ValueCountFrequency (%)
안락사 16
28.1%
방생 13
22.8%
폐사체 13
22.8%
폐사 9
15.8%
DOA 4
 
7.0%
이첩 1
 
1.8%
계류 1
 
1.8%

Length

2024-01-10T07:38:29.596519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:38:29.700514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안락사 16
28.1%
방생 13
22.8%
폐사체 13
22.8%
폐사 9
15.8%
doa 4
 
7.0%
이첩 1
 
1.8%
계류 1
 
1.8%

이첩 방생 위치
Text

MISSING 

Distinct11
Distinct (%)78.6%
Missing43
Missing (%)75.4%
Memory size588.0 B
2024-01-10T07:38:29.883304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length19.071429
Min length5

Characters and Unicode

Total characters267
Distinct characters56
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

Unique9 ?
Unique (%)64.3%

Sample

1st row충청남도 청양군 정산면 백곡리 76-1
2nd row충청남도 청양군 정산면 백곡리 76-1
3rd row충청남도 청양군 청양읍 읍내리 3-15
4th row충청남도 아산시 송악면 동화리 734
5th row공주시 우성면 단지리 104-1
ValueCountFrequency (%)
충청남도 10
 
15.2%
청양군 5
 
7.6%
성연면 3
 
4.5%
고남리 3
 
4.5%
203-4 3
 
4.5%
예산군 3
 
4.5%
서산시 3
 
4.5%
충남 2
 
3.0%
예산읍 2
 
3.0%
1 2
 
3.0%
Other values (26) 30
45.5%
2024-01-10T07:38:30.155364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
55
20.6%
청 18
 
6.7%
남 16
 
6.0%
산 12
 
4.5%
리 12
 
4.5%
충 12
 
4.5%
도 10
 
3.7%
면 9
 
3.4%
- 8
 
3.0%
군 8
 
3.0%
Other values (46) 107
40.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 167
62.5%
Space Separator 55
 
20.6%
Decimal Number 37
 
13.9%
Dash Punctuation 8
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 18
 
10.8%
남 16
 
9.6%
산 12
 
7.2%
리 12
 
7.2%
충 12
 
7.2%
도 10
 
6.0%
면 9
 
5.4%
군 8
 
4.8%
양 7
 
4.2%
시 5
 
3.0%
Other values (36) 58
34.7%
Decimal Number
ValueCountFrequency (%)
4 7
18.9%
1 7
18.9%
3 6
16.2%
7 4
10.8%
2 4
10.8%
0 4
10.8%
5 3
8.1%
6 2
 
5.4%
Space Separator
ValueCountFrequency (%)
55
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 167
62.5%
Common 100
37.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 18
 
10.8%
남 16
 
9.6%
산 12
 
7.2%
리 12
 
7.2%
충 12
 
7.2%
도 10
 
6.0%
면 9
 
5.4%
군 8
 
4.8%
양 7
 
4.2%
시 5
 
3.0%
Other values (36) 58
34.7%
Common
ValueCountFrequency (%)
55
55.0%
- 8
 
8.0%
4 7
 
7.0%
1 7
 
7.0%
3 6
 
6.0%
7 4
 
4.0%
2 4
 
4.0%
0 4
 
4.0%
5 3
 
3.0%
6 2
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 167
62.5%
ASCII 100
37.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
55
55.0%
- 8
 
8.0%
4 7
 
7.0%
1 7
 
7.0%
3 6
 
6.0%
7 4
 
4.0%
2 4
 
4.0%
0 4
 
4.0%
5 3
 
3.0%
6 2
 
2.0%
Hangul
ValueCountFrequency (%)
청 18
 
10.8%
남 16
 
9.6%
산 12
 
7.2%
리 12
 
7.2%
충 12
 
7.2%
도 10
 
6.0%
면 9
 
5.4%
군 8
 
4.8%
양 7
 
4.2%
시 5
 
3.0%
Other values (36) 58
34.7%

사체처리
Categorical

Distinct7
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Memory size588.0 B
기타
35 
<NA>
15 
폐기
 
3
냉동
 
1
냉동(신냉동창고)(투입박스(일반))
 
1
Other values (2)
 
2

Length

Max length24
Median length2
Mean length3.2807018
Min length2

Unique

Unique4 ?
Unique (%)7.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타 35
61.4%
<NA> 15
26.3%
폐기 3
 
5.3%
냉동 1
 
1.8%
냉동(신냉동창고)(투입박스(일반)) 1
 
1.8%
냉동(구냉동창고)(성체고라니, 개선충너구리) 1
 
1.8%
기타(협조) 1
 
1.8%

Length

2024-01-10T07:38:30.268832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:38:30.356680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 35
60.3%
na 15
25.9%
폐기 3
 
5.2%
냉동 1
 
1.7%
냉동(신냉동창고)(투입박스(일반 1
 
1.7%
냉동(구냉동창고)(성체고라니 1
 
1.7%
개선충너구리 1
 
1.7%
기타(협조 1
 
1.7%

동물성별
Categorical

Distinct4
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
Unknown
34 
Female
12 
Male
10 
Male()
 
1

Length

Max length7
Median length7
Mean length6.245614
Min length4

Unique

Unique1 ?
Unique (%)1.8%

Sample

1st rowUnknown
2nd rowUnknown
3rd rowUnknown
4th rowUnknown
5th rowUnknown

Common Values

ValueCountFrequency (%)
Unknown 34
59.6%
Female 12
 
21.1%
Male 10
 
17.5%
Male() 1
 
1.8%

Length

2024-01-10T07:38:30.469410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:38:30.576898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
unknown 34
59.6%
female 12
 
21.1%
male 11
 
19.3%

동물연령
Categorical

Distinct15
Distinct (%)26.3%
Missing0
Missing (%)0.0%
Memory size588.0 B
0년0월0일
17 
Juvenile
12 
Unknown
8 
Nestling
4 
Adult
4 
Other values (10)
12 

Length

Max length8
Median length7
Mean length6.6842105
Min length5

Unique

Unique8 ?
Unique (%)14.0%

Sample

1st rowJuvenile
2nd rowNestling
3rd rowNestling
4th rowNestling
5th rowAdult

Common Values

ValueCountFrequency (%)
0년0월0일 17
29.8%
Juvenile 12
21.1%
Unknown 8
14.0%
Nestling 4
 
7.0%
Adult 4
 
7.0%
0년10월0일 2
 
3.5%
0년1월0일 2
 
3.5%
0년11월0일 1
 
1.8%
0년3월0일 1
 
1.8%
1년4월0일 1
 
1.8%
Other values (5) 5
 
8.8%

Length

2024-01-10T07:38:30.693396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0년0월0일 17
29.8%
juvenile 12
21.1%
unknown 8
14.0%
nestling 4
 
7.0%
adult 4
 
7.0%
0년10월0일 2
 
3.5%
0년1월0일 2
 
3.5%
0년11월0일 1
 
1.8%
0년3월0일 1
 
1.8%
1년4월0일 1
 
1.8%
Other values (5) 5
 
8.8%

구조위도
Text

Distinct49
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2024-01-10T07:38:30.889047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.7368421
Min length6

Characters and Unicode

Total characters498
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)80.7%

Sample

1st row36.397778
2nd row36.412389
3rd row36.412389
4th row36.412389
5th row36.451222
ValueCountFrequency (%)
36.494083 4
 
7.0%
36.42125 4
 
7.0%
36.412389 3
 
5.3%
36.358083 1
 
1.8%
36.368389 1
 
1.8%
36.397778 1
 
1.8%
36.409639 1
 
1.8%
36.489306 1
 
1.8%
36.556833 1
 
1.8%
36.416 1
 
1.8%
Other values (39) 39
68.4%
2024-01-10T07:38:31.257057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 108
21.7%
6 78
15.7%
. 67
13.5%
4 55
11.0%
2 41
 
8.2%
8 30
 
6.0%
5 30
 
6.0%
9 28
 
5.6%
0 21
 
4.2%
1 21
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 431
86.5%
Other Punctuation 67
 
13.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 108
25.1%
6 78
18.1%
4 55
12.8%
2 41
 
9.5%
8 30
 
7.0%
5 30
 
7.0%
9 28
 
6.5%
0 21
 
4.9%
1 21
 
4.9%
7 19
 
4.4%
Other Punctuation
ValueCountFrequency (%)
. 67
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 498
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 108
21.7%
6 78
15.7%
. 67
13.5%
4 55
11.0%
2 41
 
8.2%
8 30
 
6.0%
5 30
 
6.0%
9 28
 
5.6%
0 21
 
4.2%
1 21
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 498
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 108
21.7%
6 78
15.7%
. 67
13.5%
4 55
11.0%
2 41
 
8.2%
8 30
 
6.0%
5 30
 
6.0%
9 28
 
5.6%
0 21
 
4.2%
1 21
 
4.2%

구조경도
Text

Distinct49
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2024-01-10T07:38:31.459471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9298246
Min length9

Characters and Unicode

Total characters566
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)80.7%

Sample

1st row126.86025
2nd row126.971083
3rd row126.971083
4th row126.971083
5th row126.79225
ValueCountFrequency (%)
126.788833 4
 
7.0%
126.948361 4
 
7.0%
126.971083 3
 
5.3%
126.847028 1
 
1.8%
126.79575 1
 
1.8%
126.86025 1
 
1.8%
126.790472 1
 
1.8%
126.836528 1
 
1.8%
126.877694 1
 
1.8%
126.694528 1
 
1.8%
Other values (39) 39
68.4%
2024-01-10T07:38:31.784983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 88
15.5%
6 84
14.8%
2 81
14.3%
. 67
11.8%
8 58
10.2%
7 43
7.6%
9 38
6.7%
3 32
 
5.7%
4 28
 
4.9%
0 26
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 499
88.2%
Other Punctuation 67
 
11.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 88
17.6%
6 84
16.8%
2 81
16.2%
8 58
11.6%
7 43
8.6%
9 38
7.6%
3 32
 
6.4%
4 28
 
5.6%
0 26
 
5.2%
5 21
 
4.2%
Other Punctuation
ValueCountFrequency (%)
. 67
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 566
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 88
15.5%
6 84
14.8%
2 81
14.3%
. 67
11.8%
8 58
10.2%
7 43
7.6%
9 38
6.7%
3 32
 
5.7%
4 28
 
4.9%
0 26
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 566
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 88
15.5%
6 84
14.8%
2 81
14.3%
. 67
11.8%
8 58
10.2%
7 43
7.6%
9 38
6.7%
3 32
 
5.7%
4 28
 
4.9%
0 26
 
4.6%

구조고도
Real number (ℝ)

ZEROS 

Distinct38
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75.736842
Minimum0
Maximum174
Zeros2
Zeros (%)3.5%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-01-10T07:38:31.906435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile23.6
Q151
median82
Q397
95-th percentile144.8
Maximum174
Range174
Interquartile range (IQR)46

Descriptive statistics

Standard deviation38.109582
Coefficient of variation (CV)0.50318419
Kurtosis-0.13500176
Mean75.736842
Median Absolute Deviation (MAD)24
Skewness0.26230405
Sum4317
Variance1452.3402
MonotonicityNot monotonic
2024-01-10T07:38:32.021276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
51 6
 
10.5%
67 4
 
7.0%
87 3
 
5.3%
36 3
 
5.3%
102 3
 
5.3%
58 2
 
3.5%
91 2
 
3.5%
24 2
 
3.5%
0 2
 
3.5%
95 2
 
3.5%
Other values (28) 28
49.1%
ValueCountFrequency (%)
0 2
3.5%
22 1
 
1.8%
24 2
3.5%
28 1
 
1.8%
29 1
 
1.8%
36 3
5.3%
37 1
 
1.8%
38 1
 
1.8%
41 1
 
1.8%
47 1
 
1.8%
ValueCountFrequency (%)
174 1
 
1.8%
153 1
 
1.8%
148 1
 
1.8%
144 1
 
1.8%
132 1
 
1.8%
127 1
 
1.8%
123 1
 
1.8%
119 1
 
1.8%
104 1
 
1.8%
102 3
5.3%

방생위도
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)72.7%
Missing46
Missing (%)80.7%
Infinite0
Infinite (%)0.0%
Mean36.602711
Minimum36.336335
Maximum36.820878
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-01-10T07:38:32.120797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.336335
5-th percentile36.374362
Q136.433641
median36.668162
Q336.776608
95-th percentile36.820878
Maximum36.820878
Range0.48454223
Interquartile range (IQR)0.34296688

Descriptive statistics

Standard deviation0.18670239
Coefficient of variation (CV)0.0051007805
Kurtosis-1.8315532
Mean36.602711
Median Absolute Deviation (MAD)0.15271506
Skewness-0.071799486
Sum402.62982
Variance0.034857784
MonotonicityNot monotonic
2024-01-10T07:38:32.206910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
36.82087755 3
 
5.3%
36.41238944 2
 
3.5%
36.45489267 1
 
1.8%
36.73233832 1
 
1.8%
36.4805998 1
 
1.8%
36.67008139 1
 
1.8%
36.66816249 1
 
1.8%
36.33633532 1
 
1.8%
(Missing) 46
80.7%
ValueCountFrequency (%)
36.33633532 1
 
1.8%
36.41238944 2
3.5%
36.45489267 1
 
1.8%
36.4805998 1
 
1.8%
36.66816249 1
 
1.8%
36.67008139 1
 
1.8%
36.73233832 1
 
1.8%
36.82087755 3
5.3%
ValueCountFrequency (%)
36.82087755 3
5.3%
36.73233832 1
 
1.8%
36.67008139 1
 
1.8%
36.66816249 1
 
1.8%
36.4805998 1
 
1.8%
36.45489267 1
 
1.8%
36.41238944 2
3.5%
36.33633532 1
 
1.8%

방생경도
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)72.7%
Missing46
Missing (%)80.7%
Infinite0
Infinite (%)0.0%
Mean126.79509
Minimum126.43456
Maximum127.06153
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-01-10T07:38:32.295766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.43456
5-th percentile126.43456
Q1126.62115
median126.86447
Q3126.96873
95-th percentile127.01628
Maximum127.06153
Range0.626965
Interquartile range (IQR)0.34757445

Descriptive statistics

Standard deviation0.24134204
Coefficient of variation (CV)0.0019034021
Kurtosis-0.97894742
Mean126.79509
Median Absolute Deviation (MAD)0.1065683
Skewness-0.88749206
Sum1394.746
Variance0.058245982
MonotonicityNot monotonic
2024-01-10T07:38:32.377903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
126.4345645 3
 
5.3%
126.971038 2
 
3.5%
126.8077397 1
 
1.8%
126.9664151 1
 
1.8%
127.0615295 1
 
1.8%
126.8596661 1
 
1.8%
126.8644697 1
 
1.8%
126.9404261 1
 
1.8%
(Missing) 46
80.7%
ValueCountFrequency (%)
126.4345645 3
5.3%
126.8077397 1
 
1.8%
126.8596661 1
 
1.8%
126.8644697 1
 
1.8%
126.9404261 1
 
1.8%
126.9664151 1
 
1.8%
126.971038 2
3.5%
127.0615295 1
 
1.8%
ValueCountFrequency (%)
127.0615295 1
 
1.8%
126.971038 2
3.5%
126.9664151 1
 
1.8%
126.9404261 1
 
1.8%
126.8644697 1
 
1.8%
126.8596661 1
 
1.8%
126.8077397 1
 
1.8%
126.4345645 3
5.3%

발견장소상세
Text

MISSING 

Distinct34
Distinct (%)73.9%
Missing11
Missing (%)19.3%
Memory size588.0 B
2024-01-10T07:38:32.554930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length8.6956522
Min length3

Characters and Unicode

Total characters400
Distinct characters106
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

Unique30 ?
Unique (%)65.2%

Sample

1st row청양소방서(가지점)
2nd row부전빌라 내
3rd row광대리 이하 세부 주소 누락
4th row주소지 도로 방음벽
5th row주공아파트 내 화단
ValueCountFrequency (%)
주소지 13
 
11.4%
도로변 9
 
7.9%
부근 8
 
7.0%
도로 5
 
4.4%
내부 5
 
4.4%
방음벽 4
 
3.5%
애경산업청양공장 4
 
3.5%
옆 3
 
2.6%
주소 3
 
2.6%
건물 3
 
2.6%
Other values (49) 57
50.0%
2024-01-10T07:38:32.873336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
72
 
18.0%
소 20
 
5.0%
주 19
 
4.8%
지 19
 
4.8%
로 19
 
4.8%
도 15
 
3.8%
부 15
 
3.8%
변 10
 
2.5%
근 10
 
2.5%
내 8
 
2.0%
Other values (96) 193
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 326
81.5%
Space Separator 72
 
18.0%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 20
 
6.1%
주 19
 
5.8%
지 19
 
5.8%
로 19
 
5.8%
도 15
 
4.6%
부 15
 
4.6%
변 10
 
3.1%
근 10
 
3.1%
내 8
 
2.5%
청 7
 
2.1%
Other values (93) 184
56.4%
Space Separator
ValueCountFrequency (%)
72
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 326
81.5%
Common 74
 
18.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 20
 
6.1%
주 19
 
5.8%
지 19
 
5.8%
로 19
 
5.8%
도 15
 
4.6%
부 15
 
4.6%
변 10
 
3.1%
근 10
 
3.1%
내 8
 
2.5%
청 7
 
2.1%
Other values (93) 184
56.4%
Common
ValueCountFrequency (%)
72
97.3%
( 1
 
1.4%
) 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 326
81.5%
ASCII 74
 
18.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
72
97.3%
( 1
 
1.4%
) 1
 
1.4%
Hangul
ValueCountFrequency (%)
소 20
 
6.1%
주 19
 
5.8%
지 19
 
5.8%
로 19
 
5.8%
도 15
 
4.6%
부 15
 
4.6%
변 10
 
3.1%
근 10
 
3.1%
내 8
 
2.5%
청 7
 
2.1%
Other values (93) 184
56.4%

발견주소
Text

Distinct49
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2024-01-10T07:38:33.110657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length20.789474
Min length17

Characters and Unicode

Total characters1185
Distinct characters81
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

Unique46 ?
Unique (%)80.7%

Sample

1st row충청남도 청양군 대치면 작천리 8-6
2nd row충청남도 청양군 정산면 백곡리 76-1
3rd row충청남도 청양군 정산면 백곡리 76-1
4th row충청남도 청양군 정산면 백곡리 76-1
5th row충청남도 청양군 청양읍 송방리 348
ValueCountFrequency (%)
청양군 57
19.8%
충청남도 47
 
16.3%
정산면 13
 
4.5%
청양읍 12
 
4.2%
충남 10
 
3.5%
비봉면 6
 
2.1%
장평면 5
 
1.7%
산 4
 
1.4%
남양면 4
 
1.4%
대치면 4
 
1.4%
Other values (90) 126
43.8%
2024-01-10T07:38:33.456959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
234
19.7%
청 119
 
10.0%
양 73
 
6.2%
남 63
 
5.3%
충 58
 
4.9%
군 57
 
4.8%
리 51
 
4.3%
도 47
 
4.0%
면 45
 
3.8%
1 42
 
3.5%
Other values (71) 396
33.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 731
61.7%
Space Separator 234
 
19.7%
Decimal Number 186
 
15.7%
Dash Punctuation 34
 
2.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 119
16.3%
양 73
10.0%
남 63
 
8.6%
충 58
 
7.9%
군 57
 
7.8%
리 51
 
7.0%
도 47
 
6.4%
면 45
 
6.2%
산 25
 
3.4%
정 17
 
2.3%
Other values (59) 176
24.1%
Decimal Number
ValueCountFrequency (%)
1 42
22.6%
3 27
14.5%
7 25
13.4%
6 24
12.9%
2 22
11.8%
4 14
 
7.5%
8 11
 
5.9%
5 10
 
5.4%
0 6
 
3.2%
9 5
 
2.7%
Space Separator
ValueCountFrequency (%)
234
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 731
61.7%
Common 454
38.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 119
16.3%
양 73
10.0%
남 63
 
8.6%
충 58
 
7.9%
군 57
 
7.8%
리 51
 
7.0%
도 47
 
6.4%
면 45
 
6.2%
산 25
 
3.4%
정 17
 
2.3%
Other values (59) 176
24.1%
Common
ValueCountFrequency (%)
234
51.5%
1 42
 
9.3%
- 34
 
7.5%
3 27
 
5.9%
7 25
 
5.5%
6 24
 
5.3%
2 22
 
4.8%
4 14
 
3.1%
8 11
 
2.4%
5 10
 
2.2%
Other values (2) 11
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 731
61.7%
ASCII 454
38.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
234
51.5%
1 42
 
9.3%
- 34
 
7.5%
3 27
 
5.9%
7 25
 
5.5%
6 24
 
5.3%
2 22
 
4.8%
4 14
 
3.1%
8 11
 
2.4%
5 10
 
2.2%
Other values (2) 11
 
2.4%
Hangul
ValueCountFrequency (%)
청 119
16.3%
양 73
10.0%
남 63
 
8.6%
충 58
 
7.9%
군 57
 
7.8%
리 51
 
7.0%
도 47
 
6.4%
면 45
 
6.2%
산 25
 
3.4%
정 17
 
2.3%
Other values (59) 176
24.1%

발견장소특징
Categorical

Distinct5
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size588.0 B
건물옆
26 
도로변
18 
농경지
6 
기타
6 
숲
 
1

Length

Max length3
Median length3
Mean length2.8596491
Min length1

Unique

Unique1 ?
Unique (%)1.8%

Sample

1st row도로변
2nd row건물옆
3rd row건물옆
4th row건물옆
5th row건물옆

Common Values

ValueCountFrequency (%)
건물옆 26
45.6%
도로변 18
31.6%
농경지 6
 
10.5%
기타 6
 
10.5%
숲 1
 
1.8%

Length

2024-01-10T07:38:33.582239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:38:33.678024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물옆 26
45.6%
도로변 18
31.6%
농경지 6
 
10.5%
기타 6
 
10.5%
숲 1
 
1.8%

발생원인
Categorical

Distinct18
Distinct (%)31.6%
Missing0
Missing (%)0.0%
Memory size588.0 B
차량과의 충돌
12 
전선/건물과의 충돌
11 
어미를 잃음(미아)
7 
기생충 중감염
5 
- 전선/건물과의 충돌
3 
Other values (13)
19 

Length

Max length13
Median length12
Mean length8.5614035
Min length1

Unique

Unique9 ?
Unique (%)15.8%

Sample

1st row차량과의 충돌
2nd row추락
3rd row추락
4th row추락
5th row전선/건물과의 충돌

Common Values

ValueCountFrequency (%)
차량과의 충돌 12
21.1%
전선/건물과의 충돌 11
19.3%
어미를 잃음(미아) 7
12.3%
기생충 중감염 5
8.8%
- 전선/건물과의 충돌 3
 
5.3%
추락 3
 
5.3%
- 어미를 잃음(미아) 3
 
5.3%
- 기생충 중감염 2
 
3.5%
인공구조물에 얽힘 2
 
3.5%
기아 및 탈진 1
 
1.8%
Other values (8) 8
14.0%

Length

2024-01-10T07:38:33.780024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충돌 27
21.6%
전선/건물과의 14
11.2%
차량과의 13
10.4%
어미를 10
 
8.0%
잃음(미아 10
 
8.0%
10
 
8.0%
기생충 7
 
5.6%
중감염 7
 
5.6%
추락 3
 
2.4%
없는 2
 
1.6%
Other values (17) 22
17.6%

발생원인 세부사항
Text

Distinct29
Distinct (%)50.9%
Missing0
Missing (%)0.0%
Memory size588.0 B
2024-01-10T07:38:33.941514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length9.0350877
Min length4

Characters and Unicode

Total characters515
Distinct characters80
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)35.1%

Sample

1st row차량충돌 추정
2nd row둥지째로 추락함
3rd row둥지째로 추락함
4th row둥지째로 추락함
5th row충돌 추정
ValueCountFrequency (%)
충돌 24
17.6%
어미를 10
 
7.4%
차량과의 10
 
7.4%
잃음(미아 10
 
7.4%
기생충 7
 
5.1%
유리 5
 
3.7%
구조물 5
 
3.7%
중감염/개선충 5
 
3.7%
추정 5
 
3.7%
방음벽 4
 
2.9%
Other values (35) 51
37.5%
2024-01-10T07:38:34.267802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
80
 
15.5%
충 42
 
8.2%
돌 29
 
5.6%
미 20
 
3.9%
음 15
 
2.9%
차 15
 
2.9%
량 15
 
2.9%
과 12
 
2.3%
의 12
 
2.3%
염 11
 
2.1%
Other values (70) 264
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 403
78.3%
Space Separator 80
 
15.5%
Open Punctuation 11
 
2.1%
Close Punctuation 11
 
2.1%
Other Punctuation 10
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
충 42
 
10.4%
돌 29
 
7.2%
미 20
 
5.0%
음 15
 
3.7%
차 15
 
3.7%
량 15
 
3.7%
과 12
 
3.0%
의 12
 
3.0%
염 11
 
2.7%
아 11
 
2.7%
Other values (66) 221
54.8%
Space Separator
ValueCountFrequency (%)
80
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 403
78.3%
Common 112
 
21.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
충 42
 
10.4%
돌 29
 
7.2%
미 20
 
5.0%
음 15
 
3.7%
차 15
 
3.7%
량 15
 
3.7%
과 12
 
3.0%
의 12
 
3.0%
염 11
 
2.7%
아 11
 
2.7%
Other values (66) 221
54.8%
Common
ValueCountFrequency (%)
80
71.4%
( 11
 
9.8%
) 11
 
9.8%
/ 10
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 403
78.3%
ASCII 112
 
21.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
80
71.4%
( 11
 
9.8%
) 11
 
9.8%
/ 10
 
8.9%
Hangul
ValueCountFrequency (%)
충 42
 
10.4%
돌 29
 
7.2%
미 20
 
5.0%
음 15
 
3.7%
차 15
 
3.7%
량 15
 
3.7%
과 12
 
3.0%
의 12
 
3.0%
염 11
 
2.7%
아 11
 
2.7%
Other values (66) 221
54.8%

TM구조위도
Text

MISSING 

Distinct39
Distinct (%)83.0%
Missing10
Missing (%)17.5%
Memory size588.0 B
2024-01-10T07:38:34.420251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters470
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

Unique36 ?
Unique (%)76.6%

Sample

1st row36 23 52.0
2nd row36 24 44.6
3rd row36 24 44.6
4th row36 24 44.6
5th row36 27 04.4
ValueCountFrequency (%)
36 47
33.3%
24 8
 
5.7%
25 7
 
5.0%
26 6
 
4.3%
27 6
 
4.3%
29 5
 
3.5%
23 5
 
3.5%
16.5 4
 
2.8%
38.7 4
 
2.8%
44.6 3
 
2.1%
Other values (40) 46
32.6%
2024-01-10T07:38:34.665212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
94
20.0%
3 75
16.0%
6 67
14.3%
2 57
12.1%
. 47
10.0%
5 28
 
6.0%
4 26
 
5.5%
7 20
 
4.3%
1 17
 
3.6%
9 16
 
3.4%
Other values (2) 23
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 329
70.0%
Space Separator 94
 
20.0%
Other Punctuation 47
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 75
22.8%
6 67
20.4%
2 57
17.3%
5 28
 
8.5%
4 26
 
7.9%
7 20
 
6.1%
1 17
 
5.2%
9 16
 
4.9%
0 16
 
4.9%
8 7
 
2.1%
Space Separator
ValueCountFrequency (%)
94
100.0%
Other Punctuation
ValueCountFrequency (%)
. 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 470
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
94
20.0%
3 75
16.0%
6 67
14.3%
2 57
12.1%
. 47
10.0%
5 28
 
6.0%
4 26
 
5.5%
7 20
 
4.3%
1 17
 
3.6%
9 16
 
3.4%
Other values (2) 23
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 470
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
94
20.0%
3 75
16.0%
6 67
14.3%
2 57
12.1%
. 47
10.0%
5 28
 
6.0%
4 26
 
5.5%
7 20
 
4.3%
1 17
 
3.6%
9 16
 
3.4%
Other values (2) 23
 
4.9%

TM구조경도
Text

MISSING 

Distinct39
Distinct (%)83.0%
Missing10
Missing (%)17.5%
Memory size588.0 B
2024-01-10T07:38:34.827656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters517
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

Unique36 ?
Unique (%)76.6%

Sample

1st row126 51 36.9
2nd row126 58 15.9
3rd row126 58 15.9
4th row126 58 15.9
5th row126 47 32.1
ValueCountFrequency (%)
126 46
32.6%
47 11
 
7.8%
48 6
 
4.3%
56 5
 
3.5%
54.1 4
 
2.8%
19.8 4
 
2.8%
58 4
 
2.8%
52 3
 
2.1%
51 3
 
2.1%
50 3
 
2.1%
Other values (47) 52
36.9%
2024-01-10T07:38:35.137508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
94
18.2%
1 73
14.1%
2 61
11.8%
6 60
11.6%
. 47
9.1%
5 39
7.5%
4 38
7.4%
7 25
 
4.8%
3 23
 
4.4%
9 19
 
3.7%
Other values (2) 38
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 376
72.7%
Space Separator 94
 
18.2%
Other Punctuation 47
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 73
19.4%
2 61
16.2%
6 60
16.0%
5 39
10.4%
4 38
10.1%
7 25
 
6.6%
3 23
 
6.1%
9 19
 
5.1%
8 19
 
5.1%
0 19
 
5.1%
Space Separator
ValueCountFrequency (%)
94
100.0%
Other Punctuation
ValueCountFrequency (%)
. 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 517
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
94
18.2%
1 73
14.1%
2 61
11.8%
6 60
11.6%
. 47
9.1%
5 39
7.5%
4 38
7.4%
7 25
 
4.8%
3 23
 
4.4%
9 19
 
3.7%
Other values (2) 38
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 517
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
94
18.2%
1 73
14.1%
2 61
11.8%
6 60
11.6%
. 47
9.1%
5 39
7.5%
4 38
7.4%
7 25
 
4.8%
3 23
 
4.4%
9 19
 
3.7%
Other values (2) 38
7.4%

TM방생위도
Text

MISSING 

Distinct8
Distinct (%)72.7%
Missing46
Missing (%)80.7%
Memory size588.0 B
2024-01-10T07:38:35.257264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters110
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

Unique6 ?
Unique (%)54.5%

Sample

1st row36 24 44.7
2nd row36 24 44.7
3rd row36 27 18.3
4th row36 43 56.2
5th row36 28 50.0
ValueCountFrequency (%)
36 11
33.3%
49 3
 
9.1%
14.4 3
 
9.1%
24 2
 
6.1%
44.7 2
 
6.1%
40 2
 
6.1%
27 1
 
3.0%
18.3 1
 
3.0%
43 1
 
3.0%
56.2 1
 
3.0%
Other values (6) 6
18.2%
2024-01-10T07:38:35.462250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
22
20.0%
4 19
17.3%
3 13
11.8%
6 12
10.9%
. 11
10.0%
2 9
8.2%
0 7
 
6.4%
1 6
 
5.5%
7 4
 
3.6%
9 3
 
2.7%
Other values (2) 4
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77
70.0%
Space Separator 22
 
20.0%
Other Punctuation 11
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 19
24.7%
3 13
16.9%
6 12
15.6%
2 9
11.7%
0 7
 
9.1%
1 6
 
7.8%
7 4
 
5.2%
9 3
 
3.9%
8 2
 
2.6%
5 2
 
2.6%
Space Separator
ValueCountFrequency (%)
22
100.0%
Other Punctuation
ValueCountFrequency (%)
. 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 110
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
22
20.0%
4 19
17.3%
3 13
11.8%
6 12
10.9%
. 11
10.0%
2 9
8.2%
0 7
 
6.4%
1 6
 
5.5%
7 4
 
3.6%
9 3
 
2.7%
Other values (2) 4
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 110
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
22
20.0%
4 19
17.3%
3 13
11.8%
6 12
10.9%
. 11
10.0%
2 9
8.2%
0 7
 
6.4%
1 6
 
5.5%
7 4
 
3.6%
9 3
 
2.7%
Other values (2) 4
 
3.6%

TM방생경도
Text

MISSING 

Distinct8
Distinct (%)72.7%
Missing46
Missing (%)80.7%
Memory size588.0 B
2024-01-10T07:38:35.581297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters121
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

Unique6 ?
Unique (%)54.5%

Sample

1st row126 58 15.8
2nd row126 58 15.8
3rd row126 48 26.0
4th row126 57 59.0
5th row127 03 41.5
ValueCountFrequency (%)
126 10
30.3%
00.2 3
 
9.1%
26 3
 
9.1%
58 2
 
6.1%
15.8 2
 
6.1%
41.5 1
 
3.0%
56 1
 
3.0%
02.4 1
 
3.0%
52 1
 
3.0%
43.9 1
 
3.0%
Other values (8) 8
24.2%
2024-01-10T07:38:35.797410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
22
18.2%
2 21
17.4%
1 15
12.4%
6 15
12.4%
. 11
9.1%
5 11
9.1%
0 10
8.3%
8 5
 
4.1%
4 4
 
3.3%
3 3
 
2.5%
Other values (2) 4
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 88
72.7%
Space Separator 22
 
18.2%
Other Punctuation 11
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 21
23.9%
1 15
17.0%
6 15
17.0%
5 11
12.5%
0 10
11.4%
8 5
 
5.7%
4 4
 
4.5%
3 3
 
3.4%
7 2
 
2.3%
9 2
 
2.3%
Space Separator
ValueCountFrequency (%)
22
100.0%
Other Punctuation
ValueCountFrequency (%)
. 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 121
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
22
18.2%
2 21
17.4%
1 15
12.4%
6 15
12.4%
. 11
9.1%
5 11
9.1%
0 10
8.3%
8 5
 
4.1%
4 4
 
3.3%
3 3
 
2.5%
Other values (2) 4
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 121
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
22
18.2%
2 21
17.4%
1 15
12.4%
6 15
12.4%
. 11
9.1%
5 11
9.1%
0 10
8.3%
8 5
 
4.1%
4 4
 
3.3%
3 3
 
2.5%
Other values (2) 4
 
3.3%

등록체중
Text

Distinct44
Distinct (%)77.2%
Missing0
Missing (%)0.0%
Memory size588.0 B
2024-01-10T07:38:35.946332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.1578947
Min length1

Characters and Unicode

Total characters180
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)71.9%

Sample

1st row162
2nd row0
3rd row0
4th row0
5th row424
ValueCountFrequency (%)
0 12
 
21.1%
126 2
 
3.5%
82 2
 
3.5%
1,178 1
 
1.8%
1,130 1
 
1.8%
3,580 1
 
1.8%
16,100 1
 
1.8%
3840 1
 
1.8%
16140 1
 
1.8%
15620 1
 
1.8%
Other values (34) 34
59.6%
2024-01-10T07:38:36.217325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 37
20.6%
1 36
20.0%
6 23
12.8%
2 21
11.7%
4 16
8.9%
3 15
8.3%
8 12
 
6.7%
5 6
 
3.3%
, 6
 
3.3%
9 4
 
2.2%
Other values (2) 4
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 173
96.1%
Other Punctuation 7
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 37
21.4%
1 36
20.8%
6 23
13.3%
2 21
12.1%
4 16
9.2%
3 15
8.7%
8 12
 
6.9%
5 6
 
3.5%
9 4
 
2.3%
7 3
 
1.7%
Other Punctuation
ValueCountFrequency (%)
, 6
85.7%
. 1
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 180
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 37
20.6%
1 36
20.0%
6 23
12.8%
2 21
11.7%
4 16
8.9%
3 15
8.3%
8 12
 
6.7%
5 6
 
3.3%
, 6
 
3.3%
9 4
 
2.2%
Other values (2) 4
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 180
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 37
20.6%
1 36
20.0%
6 23
12.8%
2 21
11.7%
4 16
8.9%
3 15
8.3%
8 12
 
6.7%
5 6
 
3.3%
, 6
 
3.3%
9 4
 
2.2%
Other values (2) 4
 
2.2%

현재체중
Text

Distinct46
Distinct (%)80.7%
Missing0
Missing (%)0.0%
Memory size588.0 B
2024-01-10T07:38:36.395822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.2280702
Min length1

Characters and Unicode

Total characters184
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)78.9%

Sample

1st row162
2nd row0
3rd row0
4th row0
5th row424
ValueCountFrequency (%)
0 12
 
21.1%
3220 1
 
1.8%
3,580 1
 
1.8%
4320 1
 
1.8%
16140 1
 
1.8%
15620 1
 
1.8%
4570 1
 
1.8%
1100 1
 
1.8%
13520 1
 
1.8%
13040 1
 
1.8%
Other values (36) 36
63.2%
2024-01-10T07:38:36.656912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 43
23.4%
1 39
21.2%
6 20
10.9%
4 19
10.3%
2 16
 
8.7%
3 16
 
8.7%
5 9
 
4.9%
8 6
 
3.3%
, 6
 
3.3%
7 5
 
2.7%
Other values (2) 5
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 176
95.7%
Other Punctuation 8
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 43
24.4%
1 39
22.2%
6 20
11.4%
4 19
10.8%
2 16
 
9.1%
3 16
 
9.1%
5 9
 
5.1%
8 6
 
3.4%
7 5
 
2.8%
9 3
 
1.7%
Other Punctuation
ValueCountFrequency (%)
, 6
75.0%
. 2
 
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 184
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 43
23.4%
1 39
21.2%
6 20
10.9%
4 19
10.3%
2 16
 
8.7%
3 16
 
8.7%
5 9
 
4.9%
8 6
 
3.3%
, 6
 
3.3%
7 5
 
2.7%
Other values (2) 5
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 184
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 43
23.4%
1 39
21.2%
6 20
10.9%
4 19
10.3%
2 16
 
8.7%
3 16
 
8.7%
5 9
 
4.9%
8 6
 
3.3%
, 6
 
3.3%
7 5
 
2.7%
Other values (2) 5
 
2.7%

임상적최종진단
Text

Distinct41
Distinct (%)71.9%
Missing0
Missing (%)0.0%
Memory size588.0 B
2024-01-10T07:38:36.907782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length24
Mean length14.140351
Min length3

Characters and Unicode

Total characters806
Distinct characters160
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)63.2%

Sample

1st row충돌에 의한 우측 완전골 근위부 개방골절
2nd row둥지 추락으로 인한 가벼운 부상
3rd row둥지 추락으로 인한 가벼운 부상
4th row둥지 추락 후 폐사
5th row척추골절 및 좌측 요척골 골절
ValueCountFrequency (%)
및 12
 
5.1%
골절 12
 
5.1%
미아 9
 
3.8%
의한 9
 
3.8%
우측 9
 
3.8%
단순 8
 
3.4%
충돌에 8
 
3.4%
뇌진탕 7
 
3.0%
중감염 7
 
3.0%
개선충 7
 
3.0%
Other values (94) 146
62.4%
2024-01-10T07:38:37.287441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
182
 
22.6%
골 29
 
3.6%
절 23
 
2.9%
충 22
 
2.7%
한 21
 
2.6%
측 16
 
2.0%
개 15
 
1.9%
상 15
 
1.9%
돌 14
 
1.7%
추 13
 
1.6%
Other values (150) 456
56.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 566
70.2%
Space Separator 182
 
22.6%
Lowercase Letter 15
 
1.9%
Other Punctuation 14
 
1.7%
Uppercase Letter 12
 
1.5%
Decimal Number 7
 
0.9%
Close Punctuation 4
 
0.5%
Open Punctuation 4
 
0.5%
Math Symbol 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
골 29
 
5.1%
절 23
 
4.1%
충 22
 
3.9%
한 21
 
3.7%
측 16
 
2.8%
개 15
 
2.7%
상 15
 
2.7%
돌 14
 
2.5%
추 13
 
2.3%
에 13
 
2.3%
Other values (122) 385
68.0%
Lowercase Letter
ValueCountFrequency (%)
r 2
13.3%
a 2
13.3%
s 2
13.3%
e 1
6.7%
d 1
6.7%
g 1
6.7%
m 1
6.7%
n 1
6.7%
u 1
6.7%
t 1
6.7%
Other values (2) 2
13.3%
Uppercase Letter
ValueCountFrequency (%)
L 4
33.3%
C 2
16.7%
H 2
16.7%
B 2
16.7%
T 2
16.7%
Decimal Number
ValueCountFrequency (%)
5 2
28.6%
3 2
28.6%
1 2
28.6%
7 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 12
85.7%
/ 1
 
7.1%
. 1
 
7.1%
Space Separator
ValueCountFrequency (%)
182
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 566
70.2%
Common 213
 
26.4%
Latin 27
 
3.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
골 29
 
5.1%
절 23
 
4.1%
충 22
 
3.9%
한 21
 
3.7%
측 16
 
2.8%
개 15
 
2.7%
상 15
 
2.7%
돌 14
 
2.5%
추 13
 
2.3%
에 13
 
2.3%
Other values (122) 385
68.0%
Latin
ValueCountFrequency (%)
L 4
14.8%
C 2
 
7.4%
H 2
 
7.4%
r 2
 
7.4%
a 2
 
7.4%
s 2
 
7.4%
B 2
 
7.4%
T 2
 
7.4%
e 1
 
3.7%
d 1
 
3.7%
Other values (7) 7
25.9%
Common
ValueCountFrequency (%)
182
85.4%
, 12
 
5.6%
) 4
 
1.9%
( 4
 
1.9%
5 2
 
0.9%
~ 2
 
0.9%
3 2
 
0.9%
1 2
 
0.9%
7 1
 
0.5%
/ 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 566
70.2%
ASCII 240
29.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
182
75.8%
, 12
 
5.0%
) 4
 
1.7%
( 4
 
1.7%
L 4
 
1.7%
C 2
 
0.8%
H 2
 
0.8%
5 2
 
0.8%
r 2
 
0.8%
a 2
 
0.8%
Other values (18) 24
 
10.0%
Hangul
ValueCountFrequency (%)
골 29
 
5.1%
절 23
 
4.1%
충 22
 
3.9%
한 21
 
3.7%
측 16
 
2.8%
개 15
 
2.7%
상 15
 
2.7%
돌 14
 
2.5%
추 13
 
2.3%
에 13
 
2.3%
Other values (122) 385
68.0%

Sample

접수번호동물국문명강목과천연기념물멸종위기등급야생동물보호협약구조일시구조결과일자구조결과이첩 방생 위치사체처리동물성별동물연령구조위도구조경도구조고도방생위도방생경도발견장소상세발견주소발견장소특징발생원인발생원인 세부사항TM구조위도TM구조경도TM방생위도TM방생경도등록체중현재체중임상적최종진단
02019-1377멧비둘기조강(Aves)비둘기목비둘기과해당없음해당없음해당없음2019-09-032019-09-03안락사<NA>기타UnknownJuvenile36.397778126.8602558<NA><NA><NA>충청남도 청양군 대치면 작천리 8-6도로변차량과의 충돌차량충돌 추정36 23 52.0126 51 36.9<NA><NA>162162충돌에 의한 우측 완전골 근위부 개방골절
12019-1158제비조강(Aves)참새목제비과해당없음해당없음해당없음2019-07-262019-07-27방생충청남도 청양군 정산면 백곡리 76-1<NA>UnknownNestling36.412389126.9710833636.412389126.971038<NA>충청남도 청양군 정산면 백곡리 76-1건물옆추락둥지째로 추락함36 24 44.6126 58 15.936 24 44.7126 58 15.800둥지 추락으로 인한 가벼운 부상
22019-1159제비조강(Aves)참새목제비과해당없음해당없음해당없음2019-07-262019-07-27방생충청남도 청양군 정산면 백곡리 76-1<NA>UnknownNestling36.412389126.9710833636.412389126.971038<NA>충청남도 청양군 정산면 백곡리 76-1건물옆추락둥지째로 추락함36 24 44.6126 58 15.936 24 44.7126 58 15.800둥지 추락으로 인한 가벼운 부상
32019-1160제비조강(Aves)참새목제비과해당없음해당없음해당없음2019-07-262019-07-26폐사체<NA>기타UnknownNestling36.412389126.97108336<NA><NA><NA>충청남도 청양군 정산면 백곡리 76-1건물옆추락둥지째로 추락함36 24 44.6126 58 15.9<NA><NA>00둥지 추락 후 폐사
42019-1471황로조강(Aves)황새목왜가리과해당없음해당없음해당없음2019-09-282019-09-28안락사<NA>기타UnknownAdult36.451222126.7922595<NA><NA>청양소방서(가지점)충청남도 청양군 청양읍 송방리 348건물옆전선/건물과의 충돌충돌 추정36 27 04.4126 47 32.1<NA><NA>424424척추골절 및 좌측 요척골 골절
52019-1163집박쥐포유강(Mammalia)박쥐목애기박쥐과해당없음해당없음해당없음2019-07-272019-09-11방생충청남도 청양군 청양읍 읍내리 3-15<NA>Unknown0년0월0일36.453833126.8045289636.454893126.80774부전빌라 내충청남도 청양군 청양읍 읍내리 236-2건물옆인공구조물 침입·고립자택 내에서 발견36 27 13.8126 48 16.336 27 18.3126 48 26.034인가 침입
62019-0626고라니포유강(Mammalia)소목사슴과해당없음해당없음해당없음2019-05-312019-05-31안락사<NA>기타Male0년11월0일36.358056126.86877851<NA><NA><NA>충청남도 청양군 장평면 화산리 23-1도로변차량과의 충돌차량충돌36 21 29.0126 52 07.6<NA><NA>1436014360충돌에 의한 천추 골절 및 좌측 대퇴골 개방골절
72019-1235너구리포유강(Mammalia)식육목개과해당없음해당없음해당없음2019-07-312019-09-10방생충청남도 아산시 송악면 동화리 734<NA>Male0년3월0일36.434583126.85080614836.732338126.966415광대리 이하 세부 주소 누락충청남도 청양군 대치면 광대리건물옆덫원인 파악 필요덫으로 추정함36 26 04.5126 51 02.936 43 56.2126 57 59.016602560우측 전지 부종
82019-1693너구리포유강(Mammalia)식육목개과해당없음해당없음해당없음2019-12-042019-12-04폐사체<NA>기타Unknown0년0월0일36.39075126.774194123<NA><NA><NA>충청남도 청양군 남양면 대봉리 산 58-1농경지인공구조물에 얽힘밭그물에 얽힘36 23 26.7126 46 27.1<NA><NA>00승저증
92020-0916큰오색딱다구리조강(Aves)딱다구리목딱다구리과해당없음해당없음해당없음2020-06-182020-06-18폐사체<NA>기타UnknownUnknown36.494083126.78883367<NA><NA>주소지 도로 방음벽충청남도 청양군 비봉면 사점리 374-1도로변전선/건물과의 충돌방음벽 충돌36 29 38.7126 47 19.8<NA><NA>00방음벽에 충돌하여 폐사
접수번호동물국문명강목과천연기념물멸종위기등급야생동물보호협약구조일시구조결과일자구조결과이첩 방생 위치사체처리동물성별동물연령구조위도구조경도구조고도방생위도방생경도발견장소상세발견주소발견장소특징발생원인발생원인 세부사항TM구조위도TM구조경도TM방생위도TM방생경도등록체중현재체중임상적최종진단
472022-0865까치조강(Aves)참새목까마귀과해당없음해당없음해당없음2022-05-182022-05-30폐사<NA>냉동(신냉동창고)(투입박스(일반))UnknownJuvenile36.27.010126.48.16092<NA><NA>골목길충남 청양군 청양읍 칠갑산로열길 6건물옆- 어미를 잃음(미아)어미를 잃음(미아)<NA><NA><NA><NA>126110단순 미아
482022-1791박새조강(Aves)참새목박새과해당없음해당없음해당없음2022-07-292022-08-27방생충남 예산군 예산읍 대학로 54<NA>UnknownNestling36.24.142126.56.27387<NA><NA>법륜사 경내 돌계단 위충남 청양군 정산면 충의로 1273건물옆- 어미를 잃음(미아)어미를 잃음(미아)/<NA><NA><NA><NA>13.0713.54단순 미아
492022-2524직박구리조강(Aves)참새목직박구리과해당없음해당없음해당없음2022-12-302023-01-02방생충남 청양군 청양읍 교월리 57-2<NA>UnknownUnknown36.27.047126.48.1680<NA><NA>건물옆충남 청양군 청양읍 읍내리 204-13건물옆- 전선/건물과의 충돌유리 구조물 충돌<NA><NA><NA><NA>8270.9뇌진탕
502022-0303대백로조강(Aves)황새목왜가리과해당없음해당없음해당없음2022-03-072022-03-07안락사<NA>폐기UnknownUnknown36.27.090126.47.456104<NA><NA><NA>충남 청양군 청양읍 칠갑산로 179건물옆- 전선/건물과의 충돌유리 구조물 충돌<NA><NA><NA><NA>1,5361,536유리창 충돌에 의한 우측 상완골 개방골절 및 우측 안구 손상
512022-1555왜가리조강(Aves)황새목왜가리과해당없음해당없음해당없음2022-07-072022-07-07안락사<NA>기타UnknownJuvenile36.28.422126.50.136132<NA><NA>인근 가택 뒷마당충남 청양군 대치면 수석리 273-6건물옆- 전선/건물과의 충돌전선과의 충돌<NA><NA><NA><NA>1,1301,130우측 상완골 개방골절(grade3)
522022-1370고라니포유강(Mammalia)소목사슴과해당없음해당없음해당없음2022-06-122022-06-25폐사<NA>폐기Unknown0년0월0일36.31.033126.46.29041<NA><NA>농경지충남 청양군 비봉면 강정리 248-1농경지- 어미를 잃음(미아)어미를 잃음(미아)<NA><NA><NA><NA>1,1781,116미아, 식이성설사
532022-1663고라니포유강(Mammalia)소목사슴과해당없음해당없음해당없음2022-07-172022-07-17폐사체<NA>냉동(구냉동창고)(성체고라니, 개선충너구리)Female0년0월0일36.24.099126.56.29075<NA><NA>도로변충남 청양군 정산면 서정리 산18-2도로변- 차량과의 충돌차량과의 충돌<NA><NA><NA><NA>16,10016,100양측 경비 개방골절
542022-0337너구리포유강(Mammalia)식육목개과해당없음해당없음해당없음2022-03-182022-03-19DOA<NA>기타(협조)Male0년0월0일36.21.264126.51.42837<NA><NA>보건진료소 차고충남 청양군 장평면 화산로 335건물옆- 기생충 중감염기생충 중감염<NA><NA><NA><NA>3,5803,580개선충 중감염, 심한 탈수 빈혈
552022-2071너구리포유강(Mammalia)식육목개과해당없음해당없음해당없음2022-09-172022-09-17폐사체<NA>폐기Male0년0월0일36.23.266126.54.182102<NA><NA>주소지 부근 풀숲충남 청양군 장평면 적곡리 569숲- 알 수 없는 사고알 수 없는 사고<NA><NA><NA><NA>00알 수 없는 사고
562022-2362너구리포유강(Mammalia)식육목개과해당없음해당없음해당없음2022-11-232022-11-23계류<NA><NA>Female0년0월0일36.26.116126.53.3210<NA><NA>주소지 인근 휴게시설 변충남 청양군 정산면 마치리 523-6건물옆- 기생충 중감염기생충 중감염/개선충 중감염<NA><NA><NA><NA>4,6203,840개선충 중감염