Overview

Dataset statistics

Number of variables32
Number of observations122
Missing cells545
Missing cells (%)14.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory31.0 KiB
Average record size in memory260.1 B

Variable types

Text14
Categorical13
DateTime2
Numeric3

Dataset

Description충남 야생동물 구조센터에서 구조한 야생동물의 종, 구조시점, 위치 자료 및 구조 이후 조치결과에 대한 자료 중, 부여군 내에서 발생한 구조 건에 대한 자료임
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=68&beforeMenuCd=DOM_000000201001001000&publicdatapk=15109270

Alerts

천연기념물 has constant value ""Constant
멸종위기등급 has constant value ""Constant
야생동물보호협약 has constant value ""Constant
이첩 방생 위치 has 84 (68.9%) missing valuesMissing
방생위도 has 96 (78.7%) missing valuesMissing
방생경도 has 96 (78.7%) missing valuesMissing
발견장소상세 has 11 (9.0%) missing valuesMissing
TM구조위도 has 32 (26.2%) missing valuesMissing
TM구조경도 has 32 (26.2%) missing valuesMissing
TM방생위도 has 96 (78.7%) missing valuesMissing
TM방생경도 has 96 (78.7%) missing valuesMissing
접수번호 has unique valuesUnique

Reproduction

Analysis started2024-01-09 20:19:31.703236
Analysis finished2024-01-09 20:19:32.472568
Duration0.77 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

접수번호
Text

UNIQUE 

Distinct122
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-01-10T05:19:32.704249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters1098
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

Unique122 ?
Unique (%)100.0%

Sample

1st row2019-1491
2nd row2019-0185
3rd row2019-1492
4th row2019-1567
5th row2019-1568
ValueCountFrequency (%)
2019-1491 1
 
0.8%
2022-0271 1
 
0.8%
2021-1428 1
 
0.8%
2021-1427 1
 
0.8%
2021-1421 1
 
0.8%
2021-2048 1
 
0.8%
2021-2043 1
 
0.8%
2021-1999 1
 
0.8%
2021-1794 1
 
0.8%
2021-1301 1
 
0.8%
Other values (112) 112
91.8%
2024-01-10T05:19:33.115940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 297
27.0%
0 218
19.9%
1 178
16.2%
- 122
11.1%
9 67
 
6.1%
7 46
 
4.2%
5 40
 
3.6%
4 38
 
3.5%
8 34
 
3.1%
3 31
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 976
88.9%
Dash Punctuation 122
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 297
30.4%
0 218
22.3%
1 178
18.2%
9 67
 
6.9%
7 46
 
4.7%
5 40
 
4.1%
4 38
 
3.9%
8 34
 
3.5%
3 31
 
3.2%
6 27
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 122
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1098
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 297
27.0%
0 218
19.9%
1 178
16.2%
- 122
11.1%
9 67
 
6.1%
7 46
 
4.2%
5 40
 
3.6%
4 38
 
3.5%
8 34
 
3.1%
3 31
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1098
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 297
27.0%
0 218
19.9%
1 178
16.2%
- 122
11.1%
9 67
 
6.1%
7 46
 
4.2%
5 40
 
3.6%
4 38
 
3.5%
8 34
 
3.1%
3 31
 
2.8%

동물국문명
Categorical

Distinct22
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
고라니
36 
너구리
21 
멧비둘기
11 
물까치
10 
흰뺨검둥오리
7 
Other values (17)
37 

Length

Max length7
Median length3
Mean length3.2377049
Min length1

Unique

Unique8 ?
Unique (%)6.6%

Sample

1st row꿩
2nd row멧비둘기
3rd row멧비둘기
4th row멧비둘기
5th row멧비둘기

Common Values

ValueCountFrequency (%)
고라니 36
29.5%
너구리 21
17.2%
멧비둘기 11
 
9.0%
물까치 10
 
8.2%
흰뺨검둥오리 7
 
5.7%
참새 7
 
5.7%
까치 6
 
4.9%
왜가리 3
 
2.5%
파랑새 3
 
2.5%
딱새 2
 
1.6%
Other values (12) 16
13.1%

Length

2024-01-10T05:19:33.298899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고라니 36
29.5%
너구리 21
17.2%
멧비둘기 11
 
9.0%
물까치 10
 
8.2%
흰뺨검둥오리 7
 
5.7%
참새 7
 
5.7%
까치 6
 
4.9%
왜가리 3
 
2.5%
파랑새 3
 
2.5%
큰오색딱다구리 2
 
1.6%
Other values (12) 16
13.1%

강
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
조강(Aves)
62 
포유강(Mammalia)
60 

Length

Max length13
Median length8
Mean length10.459016
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 (%)
조강(Aves) 62
50.8%
포유강(Mammalia) 60
49.2%

Length

2024-01-10T05:19:33.501956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:19:33.647765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
조강(aves 62
50.8%
포유강(mammalia 60
49.2%

목
Categorical

Distinct11
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
소목
36 
참새목
27 
식육목
22 
비둘기목
11 
기러기목
8 
Other values (6)
18 

Length

Max length5
Median length4
Mean length2.9180328
Min length2

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row닭목
2nd row비둘기목
3rd row비둘기목
4th row비둘기목
5th row비둘기목

Common Values

ValueCountFrequency (%)
소목 36
29.5%
참새목 27
22.1%
식육목 22
18.0%
비둘기목 11
 
9.0%
기러기목 8
 
6.6%
황새목 6
 
4.9%
파랑새목 5
 
4.1%
닭목 2
 
1.6%
박쥐목 2
 
1.6%
딱다구리목 2
 
1.6%

Length

2024-01-10T05:19:33.789137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
소목 36
29.5%
참새목 27
22.1%
식육목 22
18.0%
비둘기목 11
 
9.0%
기러기목 8
 
6.6%
황새목 6
 
4.9%
파랑새목 5
 
4.1%
닭목 2
 
1.6%
박쥐목 2
 
1.6%
딱다구리목 2
 
1.6%

과
Categorical

Distinct18
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
사슴과
36 
개과
21 
까마귀과
16 
비둘기과
11 
오리과
8 
Other values (13)
30 

Length

Max length5
Median length4
Mean length3.2213115
Min length2

Unique

Unique6 ?
Unique (%)4.9%

Sample

1st row꿩과
2nd row비둘기과
3rd row비둘기과
4th row비둘기과
5th row비둘기과

Common Values

ValueCountFrequency (%)
사슴과 36
29.5%
개과 21
17.2%
까마귀과 16
13.1%
비둘기과 11
 
9.0%
오리과 8
 
6.6%
참새과 7
 
5.7%
왜가리과 6
 
4.9%
파랑새과 3
 
2.5%
애기박쥐과 2
 
1.6%
솔딱새과 2
 
1.6%
Other values (8) 10
 
8.2%

Length

2024-01-10T05:19:33.927633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
사슴과 36
29.5%
개과 21
17.2%
까마귀과 16
13.1%
비둘기과 11
 
9.0%
오리과 8
 
6.6%
참새과 7
 
5.7%
왜가리과 6
 
4.9%
파랑새과 3
 
2.5%
딱다구리과 2
 
1.6%
꿩과 2
 
1.6%
Other values (8) 10
 
8.2%

천연기념물
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
해당없음
122 

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 122
100.0%

Length

2024-01-10T05:19:34.036361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:19:34.125352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 122
100.0%

멸종위기등급
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
해당없음
122 

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 122
100.0%

Length

2024-01-10T05:19:34.234309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:19:34.341680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 122
100.0%

야생동물보호협약
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
해당없음
122 

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 122
100.0%

Length

2024-01-10T05:19:34.453155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:19:34.587980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 122
100.0%

구조일시
Date

Distinct99
Distinct (%)81.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2019-01-24 00:00:00
Maximum2022-12-19 00:00:00
2024-01-10T05:19:34.723958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:19:34.864661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

구조결과일자
Date

Distinct105
Distinct (%)86.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2019-01-24 00:00:00
Maximum2022-12-19 00:00:00
2024-01-10T05:19:34.997752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:19:35.146896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

구조결과
Categorical

Distinct5
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
방생
38 
안락사
30 
DOA
21 
폐사
18 
폐사체
15 

Length

Max length3
Median length3
Mean length2.5409836
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
방생 38
31.1%
안락사 30
24.6%
DOA 21
17.2%
폐사 18
14.8%
폐사체 15
 
12.3%

Length

2024-01-10T05:19:35.297206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:19:35.403670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
방생 38
31.1%
안락사 30
24.6%
doa 21
17.2%
폐사 18
14.8%
폐사체 15
 
12.3%

이첩 방생 위치
Text

MISSING 

Distinct24
Distinct (%)63.2%
Missing84
Missing (%)68.9%
Memory size1.1 KiB
2024-01-10T05:19:35.605649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22.5
Mean length20.763158
Min length16

Characters and Unicode

Total characters789
Distinct characters71
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

Unique19 ?
Unique (%)50.0%

Sample

1st row충청남도 예산군 예산읍 향천리 54
2nd row충청남도 예산군 예산읍 향천리 54
3rd row충청남도 예산군 예산읍 향천리 56-1
4th row충청남도 아산시 송악면 동화리 734
5th row충청남도 아산시 송악면 동화리 734
ValueCountFrequency (%)
충청남도 26
 
13.3%
예산군 14
 
7.2%
부여군 14
 
7.2%
충남 12
 
6.2%
성왕로328번길 7
 
3.6%
예산읍 7
 
3.6%
부여읍 7
 
3.6%
15 7
 
3.6%
산 6
 
3.1%
오가면 5
 
2.6%
Other values (54) 90
46.2%
2024-01-10T05:19:36.030984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
165
20.9%
충 44
 
5.6%
남 38
 
4.8%
산 35
 
4.4%
군 31
 
3.9%
리 30
 
3.8%
청 29
 
3.7%
도 27
 
3.4%
1 25
 
3.2%
부 23
 
2.9%
Other values (61) 342
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 486
61.6%
Space Separator 165
 
20.9%
Decimal Number 127
 
16.1%
Dash Punctuation 11
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
충 44
 
9.1%
남 38
 
7.8%
산 35
 
7.2%
군 31
 
6.4%
리 30
 
6.2%
청 29
 
6.0%
도 27
 
5.6%
부 23
 
4.7%
여 21
 
4.3%
면 21
 
4.3%
Other values (49) 187
38.5%
Decimal Number
ValueCountFrequency (%)
1 25
19.7%
5 19
15.0%
3 18
14.2%
2 18
14.2%
4 17
13.4%
7 10
 
7.9%
8 8
 
6.3%
9 5
 
3.9%
6 4
 
3.1%
0 3
 
2.4%
Space Separator
ValueCountFrequency (%)
165
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 486
61.6%
Common 303
38.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
충 44
 
9.1%
남 38
 
7.8%
산 35
 
7.2%
군 31
 
6.4%
리 30
 
6.2%
청 29
 
6.0%
도 27
 
5.6%
부 23
 
4.7%
여 21
 
4.3%
면 21
 
4.3%
Other values (49) 187
38.5%
Common
ValueCountFrequency (%)
165
54.5%
1 25
 
8.3%
5 19
 
6.3%
3 18
 
5.9%
2 18
 
5.9%
4 17
 
5.6%
- 11
 
3.6%
7 10
 
3.3%
8 8
 
2.6%
9 5
 
1.7%
Other values (2) 7
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 486
61.6%
ASCII 303
38.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
165
54.5%
1 25
 
8.3%
5 19
 
6.3%
3 18
 
5.9%
2 18
 
5.9%
4 17
 
5.6%
- 11
 
3.6%
7 10
 
3.3%
8 8
 
2.6%
9 5
 
1.7%
Other values (2) 7
 
2.3%
Hangul
ValueCountFrequency (%)
충 44
 
9.1%
남 38
 
7.8%
산 35
 
7.2%
군 31
 
6.4%
리 30
 
6.2%
청 29
 
6.0%
도 27
 
5.6%
부 23
 
4.7%
여 21
 
4.3%
면 21
 
4.3%
Other values (49) 187
38.5%

사체처리
Categorical

Distinct6
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
기타
66 
<NA>
38 
폐기
8 
냉동(신냉동창고)(투입박스(일반))
 
5
냉동(구냉동창고)(성체고라니, 개선충너구리)
 
4

Length

Max length24
Median length2
Mean length4.1311475
Min length2

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
기타 66
54.1%
<NA> 38
31.1%
폐기 8
 
6.6%
냉동(신냉동창고)(투입박스(일반)) 5
 
4.1%
냉동(구냉동창고)(성체고라니, 개선충너구리) 4
 
3.3%
냉동(신냉동창고)(선반) 1
 
0.8%

Length

2024-01-10T05:19:36.192019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:19:36.311528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 66
52.4%
na 38
30.2%
폐기 8
 
6.3%
냉동(신냉동창고)(투입박스(일반 5
 
4.0%
냉동(구냉동창고)(성체고라니 4
 
3.2%
개선충너구리 4
 
3.2%
냉동(신냉동창고)(선반 1
 
0.8%

동물성별
Categorical

Distinct4
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Unknown
67 
Male
27 
Female
27 
Male()
 
1

Length

Max length7
Median length7
Mean length6.1065574
Min length4

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
Unknown 67
54.9%
Male 27
22.1%
Female 27
22.1%
Male() 1
 
0.8%

Length

2024-01-10T05:19:36.513379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:19:36.686907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
unknown 67
54.9%
male 28
23.0%
female 27
22.1%

동물연령
Categorical

Distinct18
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0년0월0일
29 
Nestling
24 
Adult
17 
Juvenile
12 
0년1월0일
10 
Other values (13)
30 

Length

Max length8
Median length7
Mean length6.5409836
Min length5

Unique

Unique7 ?
Unique (%)5.7%

Sample

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

Common Values

ValueCountFrequency (%)
0년0월0일 29
23.8%
Nestling 24
19.7%
Adult 17
13.9%
Juvenile 12
9.8%
0년1월0일 10
 
8.2%
Unknown 9
 
7.4%
0년2월0일 4
 
3.3%
0년3월0일 4
 
3.3%
1년0월0일 2
 
1.6%
0년5월0일 2
 
1.6%
Other values (8) 9
 
7.4%

Length

2024-01-10T05:19:36.834266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0년0월0일 29
23.8%
nestling 24
19.7%
adult 17
13.9%
juvenile 12
9.8%
0년1월0일 10
 
8.2%
unknown 9
 
7.4%
0년2월0일 4
 
3.3%
0년3월0일 4
 
3.3%
0년11월0일 2
 
1.6%
0년5월0일 2
 
1.6%
Other values (8) 9
 
7.4%

구조위도
Text

Distinct97
Distinct (%)79.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-01-10T05:19:37.144730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.8278689
Min length5

Characters and Unicode

Total characters1077
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

Unique87 ?
Unique (%)71.3%

Sample

1st row36.266528
2nd row36.298611
3rd row36.285694
4th row36.326111
5th row36.326111
ValueCountFrequency (%)
36.281861 7
 
5.7%
36.16.389 7
 
5.7%
36.308861 4
 
3.3%
36.11.157 3
 
2.5%
36.258444 3
 
2.5%
36.286667 3
 
2.5%
36.287806 2
 
1.6%
36.326111 2
 
1.6%
36.307972 2
 
1.6%
36.18.305 2
 
1.6%
Other values (87) 87
71.3%
2024-01-10T05:19:37.597119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 196
18.2%
3 188
17.5%
. 154
14.3%
2 116
10.8%
1 113
10.5%
8 74
 
6.9%
7 62
 
5.8%
5 52
 
4.8%
4 50
 
4.6%
9 39
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 923
85.7%
Other Punctuation 154
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 196
21.2%
3 188
20.4%
2 116
12.6%
1 113
12.2%
8 74
 
8.0%
7 62
 
6.7%
5 52
 
5.6%
4 50
 
5.4%
9 39
 
4.2%
0 33
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 154
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1077
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 196
18.2%
3 188
17.5%
. 154
14.3%
2 116
10.8%
1 113
10.5%
8 74
 
6.9%
7 62
 
5.8%
5 52
 
4.8%
4 50
 
4.6%
9 39
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1077
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 196
18.2%
3 188
17.5%
. 154
14.3%
2 116
10.8%
1 113
10.5%
8 74
 
6.9%
7 62
 
5.8%
5 52
 
4.8%
4 50
 
4.6%
9 39
 
3.6%

구조경도
Text

Distinct97
Distinct (%)79.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-01-10T05:19:37.883287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9098361
Min length6

Characters and Unicode

Total characters1209
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

Unique86 ?
Unique (%)70.5%

Sample

1st row126.931222
2nd row126.936972
3rd row126.909167
4th row126.740056
5th row126.740056
ValueCountFrequency (%)
126.925222 7
 
5.7%
126.54.241 6
 
4.9%
126.902333 4
 
3.3%
126.845389 3
 
2.5%
126.921889 3
 
2.5%
126.49.416 3
 
2.5%
126.740056 2
 
1.6%
126.914056 2
 
1.6%
126.894667 2
 
1.6%
126.897306 2
 
1.6%
Other values (87) 88
72.1%
2024-01-10T05:19:38.363239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 208
17.2%
1 188
15.6%
6 172
14.2%
. 154
12.7%
8 94
7.8%
9 89
7.4%
3 72
 
6.0%
5 70
 
5.8%
4 63
 
5.2%
7 53
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1055
87.3%
Other Punctuation 154
 
12.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 208
19.7%
1 188
17.8%
6 172
16.3%
8 94
8.9%
9 89
8.4%
3 72
 
6.8%
5 70
 
6.6%
4 63
 
6.0%
7 53
 
5.0%
0 46
 
4.4%
Other Punctuation
ValueCountFrequency (%)
. 154
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1209
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 208
17.2%
1 188
15.6%
6 172
14.2%
. 154
12.7%
8 94
7.8%
9 89
7.4%
3 72
 
6.0%
5 70
 
5.8%
4 63
 
5.2%
7 53
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1209
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 208
17.2%
1 188
15.6%
6 172
14.2%
. 154
12.7%
8 94
7.8%
9 89
7.4%
3 72
 
6.0%
5 70
 
5.8%
4 63
 
5.2%
7 53
 
4.4%

구조고도
Real number (ℝ)

Distinct52
Distinct (%)42.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.442623
Minimum0
Maximum261
Zeros1
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-01-10T05:19:38.801688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7.1
Q115
median27
Q340
95-th percentile94.8
Maximum261
Range261
Interquartile range (IQR)25

Descriptive statistics

Standard deviation37.52664
Coefficient of variation (CV)1.0587998
Kurtosis13.66097
Mean35.442623
Median Absolute Deviation (MAD)12
Skewness3.2867456
Sum4324
Variance1408.2487
MonotonicityNot monotonic
2024-01-10T05:19:38.927766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15 10
 
8.2%
27 9
 
7.4%
16 8
 
6.6%
30 7
 
5.7%
10 5
 
4.1%
31 5
 
4.1%
32 5
 
4.1%
20 4
 
3.3%
14 3
 
2.5%
6 3
 
2.5%
Other values (42) 63
51.6%
ValueCountFrequency (%)
0 1
 
0.8%
5 1
 
0.8%
6 3
2.5%
7 2
 
1.6%
9 2
 
1.6%
10 5
4.1%
11 2
 
1.6%
12 1
 
0.8%
13 3
2.5%
14 3
2.5%
ValueCountFrequency (%)
261 1
0.8%
186 1
0.8%
170 1
0.8%
148 2
1.6%
95 2
1.6%
91 1
0.8%
83 1
0.8%
78 1
0.8%
77 2
1.6%
73 1
0.8%

방생위도
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)65.4%
Missing96
Missing (%)78.7%
Infinite0
Infinite (%)0.0%
Mean36.493422
Minimum36.070794
Maximum36.779105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-01-10T05:19:39.037961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.070794
5-th percentile36.24719
Q136.282088
median36.530543
Q336.690094
95-th percentile36.73261
Maximum36.779105
Range0.70831166
Interquartile range (IQR)0.40800586

Descriptive statistics

Standard deviation0.2182522
Coefficient of variation (CV)0.0059805901
Kurtosis-1.5895099
Mean36.493422
Median Absolute Deviation (MAD)0.20197647
Skewness-0.19641344
Sum948.82897
Variance0.047634023
MonotonicityNot monotonic
2024-01-10T05:19:39.149636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
36.28208847 7
 
5.7%
36.73233832 3
 
2.5%
36.69009433 2
 
1.6%
36.41195162 1
 
0.8%
36.45411247 1
 
0.8%
36.68696856 1
 
0.8%
36.67008139 1
 
0.8%
36.23555694 1
 
0.8%
36.69042881 1
 
0.8%
36.30988028 1
 
0.8%
Other values (7) 7
 
5.7%
(Missing) 96
78.7%
ValueCountFrequency (%)
36.07079358 1
 
0.8%
36.23555694 1
 
0.8%
36.28208847 7
5.7%
36.30988028 1
 
0.8%
36.31847598 1
 
0.8%
36.41195162 1
 
0.8%
36.45411247 1
 
0.8%
36.60697286 1
 
0.8%
36.63875502 1
 
0.8%
36.67008139 1
 
0.8%
ValueCountFrequency (%)
36.77910524 1
 
0.8%
36.73269995 1
 
0.8%
36.73233832 3
2.5%
36.69042881 1
 
0.8%
36.69009433 2
1.6%
36.68696856 1
 
0.8%
36.6713663 1
 
0.8%
36.67008139 1
 
0.8%
36.63875502 1
 
0.8%
36.60697286 1
 
0.8%

방생경도
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)65.4%
Missing96
Missing (%)78.7%
Infinite0
Infinite (%)0.0%
Mean126.85589
Minimum126.38737
Maximum126.98756
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-01-10T05:19:39.277317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.38737
5-th percentile126.46186
Q1126.86026
median126.90486
Q3126.9242
95-th percentile126.96642
Maximum126.98756
Range0.6001845
Interquartile range (IQR)0.063934925

Descriptive statistics

Standard deviation0.15191591
Coefficient of variation (CV)0.0011975472
Kurtosis5.8709531
Mean126.85589
Median Absolute Deviation (MAD)0.04248955
Skewness-2.4627694
Sum3298.2531
Variance0.023078445
MonotonicityNot monotonic
2024-01-10T05:19:39.408864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
126.9241976 7
 
5.7%
126.9664151 3
 
2.5%
126.8626875 2
 
1.6%
126.8364806 1
 
0.8%
126.8099568 1
 
0.8%
126.8228817 1
 
0.8%
126.8596661 1
 
0.8%
126.9875586 1
 
0.8%
126.8620524 1
 
0.8%
126.9053074 1
 
0.8%
Other values (7) 7
 
5.7%
(Missing) 96
78.7%
ValueCountFrequency (%)
126.3873741 1
0.8%
126.391016 1
0.8%
126.6743764 1
0.8%
126.8099568 1
0.8%
126.8228817 1
0.8%
126.8364806 1
0.8%
126.8596661 1
0.8%
126.8620524 1
0.8%
126.8626875 2
1.6%
126.8631409 1
0.8%
ValueCountFrequency (%)
126.9875586 1
 
0.8%
126.9664151 3
2.5%
126.9658272 1
 
0.8%
126.9241976 7
5.7%
126.9053074 1
 
0.8%
126.9044116 1
 
0.8%
126.8890182 1
 
0.8%
126.8631409 1
 
0.8%
126.8626875 2
 
1.6%
126.8620524 1
 
0.8%

발견장소상세
Text

MISSING 

Distinct83
Distinct (%)74.8%
Missing11
Missing (%)9.0%
Memory size1.1 KiB
2024-01-10T05:19:39.702551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length19
Mean length9.8288288
Min length1

Characters and Unicode

Total characters1091
Distinct characters181
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)65.8%

Sample

1st row주소지 부근 농경지
2nd row(나루터로 37) 주소지 부근
3rd row밤나무 산
4th row밤나무 산
5th row한국전통문화대학 화장실 내부
ValueCountFrequency (%)
주소지 30
 
9.5%
부근 21
 
6.7%
도로변 13
 
4.1%
도로 13
 
4.1%
건물 13
 
4.1%
내 9
 
2.9%
옆 8
 
2.5%
농경지 8
 
2.5%
실외기 7
 
2.2%
504호 7
 
2.2%
Other values (116) 186
59.0%
2024-01-10T05:19:40.107330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
211
 
19.3%
지 50
 
4.6%
소 42
 
3.8%
주 41
 
3.8%
로 38
 
3.5%
부 34
 
3.1%
도 31
 
2.8%
근 30
 
2.7%
변 17
 
1.6%
경 16
 
1.5%
Other values (171) 581
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 808
74.1%
Space Separator 211
 
19.3%
Decimal Number 56
 
5.1%
Other Punctuation 7
 
0.6%
Open Punctuation 3
 
0.3%
Close Punctuation 3
 
0.3%
Dash Punctuation 2
 
0.2%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 50
 
6.2%
소 42
 
5.2%
주 41
 
5.1%
로 38
 
4.7%
부 34
 
4.2%
도 31
 
3.8%
근 30
 
3.7%
변 17
 
2.1%
경 16
 
2.0%
건 16
 
2.0%
Other values (155) 493
61.0%
Decimal Number
ValueCountFrequency (%)
0 14
25.0%
1 11
19.6%
4 7
12.5%
5 7
12.5%
8 7
12.5%
2 4
 
7.1%
6 2
 
3.6%
9 2
 
3.6%
7 1
 
1.8%
3 1
 
1.8%
Space Separator
ValueCountFrequency (%)
211
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
k 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 808
74.1%
Common 282
 
25.8%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 50
 
6.2%
소 42
 
5.2%
주 41
 
5.1%
로 38
 
4.7%
부 34
 
4.2%
도 31
 
3.8%
근 30
 
3.7%
변 17
 
2.1%
경 16
 
2.0%
건 16
 
2.0%
Other values (155) 493
61.0%
Common
ValueCountFrequency (%)
211
74.8%
0 14
 
5.0%
1 11
 
3.9%
, 7
 
2.5%
4 7
 
2.5%
5 7
 
2.5%
8 7
 
2.5%
2 4
 
1.4%
( 3
 
1.1%
) 3
 
1.1%
Other values (5) 8
 
2.8%
Latin
ValueCountFrequency (%)
k 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 808
74.1%
ASCII 283
 
25.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
211
74.6%
0 14
 
4.9%
1 11
 
3.9%
, 7
 
2.5%
4 7
 
2.5%
5 7
 
2.5%
8 7
 
2.5%
2 4
 
1.4%
( 3
 
1.1%
) 3
 
1.1%
Other values (6) 9
 
3.2%
Hangul
ValueCountFrequency (%)
지 50
 
6.2%
소 42
 
5.2%
주 41
 
5.1%
로 38
 
4.7%
부 34
 
4.2%
도 31
 
3.8%
근 30
 
3.7%
변 17
 
2.1%
경 16
 
2.0%
건 16
 
2.0%
Other values (155) 493
61.0%

발견주소
Text

Distinct101
Distinct (%)82.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-01-10T05:19:40.487754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length21.04918
Min length17

Characters and Unicode

Total characters2568
Distinct characters110
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

Unique92 ?
Unique (%)75.4%

Sample

1st row충청남도 부여군 부여읍 중정리 106
2nd row충청남도 부여군 부여읍 정동리 440-9
3rd row충청남도 부여군 부여읍 구아리 99
4th row충청남도 부여군 외산면 화성리 652-3
5th row충청남도 부여군 외산면 화성리 652-3
ValueCountFrequency (%)
부여군 122
19.9%
충청남도 90
 
14.7%
부여읍 42
 
6.8%
충남 32
 
5.2%
규암면 32
 
5.2%
동남리 9
 
1.5%
은산면 8
 
1.3%
성왕로328번길 7
 
1.1%
15 7
 
1.1%
합정리 7
 
1.1%
Other values (181) 258
42.0%
2024-01-10T05:19:41.018037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
500
19.5%
부 169
 
6.6%
여 165
 
6.4%
충 131
 
5.1%
남 131
 
5.1%
군 123
 
4.8%
리 99
 
3.9%
도 93
 
3.6%
청 93
 
3.6%
1 91
 
3.5%
Other values (100) 973
37.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1547
60.2%
Space Separator 500
 
19.5%
Decimal Number 453
 
17.6%
Dash Punctuation 68
 
2.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 169
10.9%
여 165
 
10.7%
충 131
 
8.5%
남 131
 
8.5%
군 123
 
8.0%
리 99
 
6.4%
도 93
 
6.0%
청 93
 
6.0%
면 78
 
5.0%
암 43
 
2.8%
Other values (88) 422
27.3%
Decimal Number
ValueCountFrequency (%)
1 91
20.1%
2 65
14.3%
3 62
13.7%
5 43
9.5%
6 41
9.1%
8 40
8.8%
4 34
 
7.5%
9 29
 
6.4%
0 27
 
6.0%
7 21
 
4.6%
Space Separator
ValueCountFrequency (%)
500
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 68
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1547
60.2%
Common 1021
39.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 169
10.9%
여 165
 
10.7%
충 131
 
8.5%
남 131
 
8.5%
군 123
 
8.0%
리 99
 
6.4%
도 93
 
6.0%
청 93
 
6.0%
면 78
 
5.0%
암 43
 
2.8%
Other values (88) 422
27.3%
Common
ValueCountFrequency (%)
500
49.0%
1 91
 
8.9%
- 68
 
6.7%
2 65
 
6.4%
3 62
 
6.1%
5 43
 
4.2%
6 41
 
4.0%
8 40
 
3.9%
4 34
 
3.3%
9 29
 
2.8%
Other values (2) 48
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1547
60.2%
ASCII 1021
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
500
49.0%
1 91
 
8.9%
- 68
 
6.7%
2 65
 
6.4%
3 62
 
6.1%
5 43
 
4.2%
6 41
 
4.0%
8 40
 
3.9%
4 34
 
3.3%
9 29
 
2.8%
Other values (2) 48
 
4.7%
Hangul
ValueCountFrequency (%)
부 169
10.9%
여 165
 
10.7%
충 131
 
8.5%
남 131
 
8.5%
군 123
 
8.0%
리 99
 
6.4%
도 93
 
6.0%
청 93
 
6.0%
면 78
 
5.0%
암 43
 
2.8%
Other values (88) 422
27.3%

발견장소특징
Categorical

Distinct6
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
건물옆
48 
도로변
30 
농경지
21 
숲
14 
기타
8 

Length

Max length5
Median length3
Mean length2.7213115
Min length1

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
건물옆 48
39.3%
도로변 30
24.6%
농경지 21
17.2%
숲 14
 
11.5%
기타 8
 
6.6%
강, 바다 1
 
0.8%

Length

2024-01-10T05:19:41.197590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:19:41.316701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물옆 48
39.0%
도로변 30
24.4%
농경지 21
17.1%
숲 14
 
11.4%
기타 8
 
6.5%
강 1
 
0.8%
바다 1
 
0.8%

발생원인
Categorical

Distinct22
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
어미를 잃음(미아)
23 
기생충 중감염
17 
차량과의 충돌
15 
전선/건물과의 충돌
15 
- 어미를 잃음(미아)
10 
Other values (17)
42 

Length

Max length14
Median length13
Mean length9.4344262
Min length3

Unique

Unique9 ?
Unique (%)7.4%

Sample

1st row인공구조물 침입·고립
2nd row전선/건물과의 충돌
3rd row바이러스 감염
4th row어미를 잃음(미아)
5th row어미를 잃음(미아)

Common Values

ValueCountFrequency (%)
어미를 잃음(미아) 23
18.9%
기생충 중감염 17
13.9%
차량과의 충돌 15
12.3%
전선/건물과의 충돌 15
12.3%
- 어미를 잃음(미아) 10
8.2%
- 차량과의 충돌 7
 
5.7%
- 인공구조물 침입·고립 6
 
4.9%
- 전선/건물과의 충돌 4
 
3.3%
바이러스 감염 4
 
3.3%
개, 고양이 공격 4
 
3.3%
Other values (12) 17
13.9%

Length

2024-01-10T05:19:41.441026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충돌 41
14.3%
어미를 33
11.5%
잃음(미아 33
11.5%
32
11.2%
차량과의 22
7.7%
전선/건물과의 19
 
6.6%
기생충 18
 
6.3%
중감염 18
 
6.3%
인공구조물 9
 
3.1%
침입·고립 9
 
3.1%
Other values (19) 52
18.2%

발생원인 세부사항
Text

Distinct59
Distinct (%)48.8%
Missing1
Missing (%)0.8%
Memory size1.1 KiB
2024-01-10T05:19:41.689393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length25
Mean length10.049587
Min length2

Characters and Unicode

Total characters1216
Distinct characters141
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)34.7%

Sample

1st row인공구조물 끼임 추정
2nd row방음벽 충돌 추정
3rd row폭스 바이러스 감염
4th row미아
5th row미아
ValueCountFrequency (%)
충돌 34
 
10.8%
어미를 27
 
8.6%
잃음(미아 26
 
8.3%
차량과의 18
 
5.7%
중감염 13
 
4.1%
개선충 12
 
3.8%
추정 12
 
3.8%
고립 11
 
3.5%
감염 9
 
2.9%
인공구조물 8
 
2.5%
Other values (90) 145
46.0%
2024-01-10T05:19:42.063890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
202
 
16.6%
충 66
 
5.4%
미 58
 
4.8%
돌 44
 
3.6%
아 34
 
2.8%
음 33
 
2.7%
어 29
 
2.4%
를 29
 
2.4%
잃 28
 
2.3%
( 28
 
2.3%
Other values (131) 665
54.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 920
75.7%
Space Separator 202
 
16.6%
Open Punctuation 28
 
2.3%
Close Punctuation 28
 
2.3%
Other Punctuation 28
 
2.3%
Lowercase Letter 9
 
0.7%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
충 66
 
7.2%
미 58
 
6.3%
돌 44
 
4.8%
아 34
 
3.7%
음 33
 
3.6%
어 29
 
3.2%
를 29
 
3.2%
잃 28
 
3.0%
감 27
 
2.9%
염 26
 
2.8%
Other values (116) 546
59.3%
Lowercase Letter
ValueCountFrequency (%)
e 2
22.2%
t 1
11.1%
r 1
11.1%
m 1
11.1%
p 1
11.1%
i 1
11.1%
s 1
11.1%
d 1
11.1%
Other Punctuation
ValueCountFrequency (%)
/ 14
50.0%
, 12
42.9%
. 2
 
7.1%
Space Separator
ValueCountFrequency (%)
202
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 920
75.7%
Common 287
 
23.6%
Latin 9
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
충 66
 
7.2%
미 58
 
6.3%
돌 44
 
4.8%
아 34
 
3.7%
음 33
 
3.6%
어 29
 
3.2%
를 29
 
3.2%
잃 28
 
3.0%
감 27
 
2.9%
염 26
 
2.8%
Other values (116) 546
59.3%
Latin
ValueCountFrequency (%)
e 2
22.2%
t 1
11.1%
r 1
11.1%
m 1
11.1%
p 1
11.1%
i 1
11.1%
s 1
11.1%
d 1
11.1%
Common
ValueCountFrequency (%)
202
70.4%
( 28
 
9.8%
) 28
 
9.8%
/ 14
 
4.9%
, 12
 
4.2%
. 2
 
0.7%
- 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 920
75.7%
ASCII 296
 
24.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
202
68.2%
( 28
 
9.5%
) 28
 
9.5%
/ 14
 
4.7%
, 12
 
4.1%
. 2
 
0.7%
e 2
 
0.7%
t 1
 
0.3%
r 1
 
0.3%
m 1
 
0.3%
Other values (5) 5
 
1.7%
Hangul
ValueCountFrequency (%)
충 66
 
7.2%
미 58
 
6.3%
돌 44
 
4.8%
아 34
 
3.7%
음 33
 
3.6%
어 29
 
3.2%
를 29
 
3.2%
잃 28
 
3.0%
감 27
 
2.9%
염 26
 
2.8%
Other values (116) 546
59.3%

TM구조위도
Text

MISSING 

Distinct74
Distinct (%)82.2%
Missing32
Missing (%)26.2%
Memory size1.1 KiB
2024-01-10T05:19:42.264492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters900
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

Unique67 ?
Unique (%)74.4%

Sample

1st row36 15 59.5
2nd row36 17 55.0
3rd row36 17 08.5
4th row36 19 34.0
5th row36 19 34.0
ValueCountFrequency (%)
36 90
33.3%
16 28
 
10.4%
17 17
 
6.3%
18 9
 
3.3%
15 8
 
3.0%
14 8
 
3.0%
13 7
 
2.6%
54.7 7
 
2.6%
19 4
 
1.5%
31.9 4
 
1.5%
Other values (74) 88
32.6%
2024-01-10T05:19:42.566279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
180
20.0%
6 138
15.3%
3 132
14.7%
1 128
14.2%
. 90
10.0%
5 38
 
4.2%
4 38
 
4.2%
7 37
 
4.1%
2 37
 
4.1%
0 37
 
4.1%
Other values (2) 45
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 630
70.0%
Space Separator 180
 
20.0%
Other Punctuation 90
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 138
21.9%
3 132
21.0%
1 128
20.3%
5 38
 
6.0%
4 38
 
6.0%
7 37
 
5.9%
2 37
 
5.9%
0 37
 
5.9%
8 23
 
3.7%
9 22
 
3.5%
Space Separator
ValueCountFrequency (%)
180
100.0%
Other Punctuation
ValueCountFrequency (%)
. 90
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 900
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
180
20.0%
6 138
15.3%
3 132
14.7%
1 128
14.2%
. 90
10.0%
5 38
 
4.2%
4 38
 
4.2%
7 37
 
4.1%
2 37
 
4.1%
0 37
 
4.1%
Other values (2) 45
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
180
20.0%
6 138
15.3%
3 132
14.7%
1 128
14.2%
. 90
10.0%
5 38
 
4.2%
4 38
 
4.2%
7 37
 
4.1%
2 37
 
4.1%
0 37
 
4.1%
Other values (2) 45
 
5.0%

TM구조경도
Text

MISSING 

Distinct73
Distinct (%)81.1%
Missing32
Missing (%)26.2%
Memory size1.1 KiB
2024-01-10T05:19:42.778136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters990
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

Unique65 ?
Unique (%)72.2%

Sample

1st row126 55 52.4
2nd row126 56 13.1
3rd row126 54 33.0
4th row126 44 24.2
5th row126 44 24.2
ValueCountFrequency (%)
126 89
33.0%
55 18
 
6.7%
54 16
 
5.9%
53 11
 
4.1%
52 8
 
3.0%
50 8
 
3.0%
30.8 7
 
2.6%
49 5
 
1.9%
44 4
 
1.5%
08.4 4
 
1.5%
Other values (73) 100
37.0%
2024-01-10T05:19:43.067573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
180
18.2%
5 127
12.8%
2 124
12.5%
1 111
11.2%
6 105
10.6%
. 90
9.1%
4 80
8.1%
0 57
 
5.8%
3 43
 
4.3%
8 31
 
3.1%
Other values (2) 42
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 720
72.7%
Space Separator 180
 
18.2%
Other Punctuation 90
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 127
17.6%
2 124
17.2%
1 111
15.4%
6 105
14.6%
4 80
11.1%
0 57
7.9%
3 43
 
6.0%
8 31
 
4.3%
9 30
 
4.2%
7 12
 
1.7%
Space Separator
ValueCountFrequency (%)
180
100.0%
Other Punctuation
ValueCountFrequency (%)
. 90
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 990
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
180
18.2%
5 127
12.8%
2 124
12.5%
1 111
11.2%
6 105
10.6%
. 90
9.1%
4 80
8.1%
0 57
 
5.8%
3 43
 
4.3%
8 31
 
3.1%
Other values (2) 42
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 990
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
180
18.2%
5 127
12.8%
2 124
12.5%
1 111
11.2%
6 105
10.6%
. 90
9.1%
4 80
8.1%
0 57
 
5.8%
3 43
 
4.3%
8 31
 
3.1%
Other values (2) 42
 
4.2%

TM방생위도
Text

MISSING 

Distinct17
Distinct (%)65.4%
Missing96
Missing (%)78.7%
Memory size1.1 KiB
2024-01-10T05:19:43.196493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters260
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

Unique14 ?
Unique (%)53.8%

Sample

1st row36 41 24.0
2nd row36 41 24.0
3rd row36 41 24.8
4th row36 43 56.2
5th row36 43 56.2
ValueCountFrequency (%)
36 27
34.6%
54.7 7
 
9.0%
16 7
 
9.0%
43 4
 
5.1%
41 4
 
5.1%
56.2 3
 
3.8%
40 2
 
2.6%
14.7 2
 
2.6%
24.0 2
 
2.6%
13.4 1
 
1.3%
Other values (19) 19
24.4%
2024-01-10T05:19:43.423017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
52
20.0%
6 39
15.0%
3 35
13.5%
4 34
13.1%
. 26
10.0%
1 21
8.1%
7 16
 
6.2%
5 12
 
4.6%
2 11
 
4.2%
0 8
 
3.1%
Other values (2) 6
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 182
70.0%
Space Separator 52
 
20.0%
Other Punctuation 26
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 39
21.4%
3 35
19.2%
4 34
18.7%
1 21
11.5%
7 16
8.8%
5 12
 
6.6%
2 11
 
6.0%
0 8
 
4.4%
8 4
 
2.2%
9 2
 
1.1%
Space Separator
ValueCountFrequency (%)
52
100.0%
Other Punctuation
ValueCountFrequency (%)
. 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 260
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
52
20.0%
6 39
15.0%
3 35
13.5%
4 34
13.1%
. 26
10.0%
1 21
8.1%
7 16
 
6.2%
5 12
 
4.6%
2 11
 
4.2%
0 8
 
3.1%
Other values (2) 6
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 260
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
52
20.0%
6 39
15.0%
3 35
13.5%
4 34
13.1%
. 26
10.0%
1 21
8.1%
7 16
 
6.2%
5 12
 
4.6%
2 11
 
4.2%
0 8
 
3.1%
Other values (2) 6
 
2.3%

TM방생경도
Text

MISSING 

Distinct17
Distinct (%)65.4%
Missing96
Missing (%)78.7%
Memory size1.1 KiB
2024-01-10T05:19:43.547988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters286
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

Unique14 ?
Unique (%)53.8%

Sample

1st row126 51 46.1
2nd row126 51 46.1
3rd row126 51 43.6
4th row126 57 59.0
5th row126 57 59.0
ValueCountFrequency (%)
126 26
33.3%
30.8 7
 
9.0%
55 7
 
9.0%
51 5
 
6.4%
57 4
 
5.1%
59.0 3
 
3.8%
46.1 2
 
2.6%
54 2
 
2.6%
23 2
 
2.6%
53 1
 
1.3%
Other values (19) 19
24.4%
2024-01-10T05:19:43.780605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
52
18.2%
1 40
14.0%
2 35
12.2%
6 33
11.5%
5 33
11.5%
. 26
9.1%
0 17
 
5.9%
3 13
 
4.5%
4 13
 
4.5%
8 11
 
3.8%
Other values (2) 13
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 208
72.7%
Space Separator 52
 
18.2%
Other Punctuation 26
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 40
19.2%
2 35
16.8%
6 33
15.9%
5 33
15.9%
0 17
8.2%
3 13
 
6.2%
4 13
 
6.2%
8 11
 
5.3%
7 7
 
3.4%
9 6
 
2.9%
Space Separator
ValueCountFrequency (%)
52
100.0%
Other Punctuation
ValueCountFrequency (%)
. 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 286
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
52
18.2%
1 40
14.0%
2 35
12.2%
6 33
11.5%
5 33
11.5%
. 26
9.1%
0 17
 
5.9%
3 13
 
4.5%
4 13
 
4.5%
8 11
 
3.8%
Other values (2) 13
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 286
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
52
18.2%
1 40
14.0%
2 35
12.2%
6 33
11.5%
5 33
11.5%
. 26
9.1%
0 17
 
5.9%
3 13
 
4.5%
4 13
 
4.5%
8 11
 
3.8%
Other values (2) 13
 
4.5%

등록체중
Text

Distinct101
Distinct (%)82.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-01-10T05:19:44.058251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.295082
Min length1

Characters and Unicode

Total characters402
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

Unique92 ?
Unique (%)75.4%

Sample

1st row310
2nd row248
3rd row0
4th row66
5th row64
ValueCountFrequency (%)
0 13
 
10.7%
8 3
 
2.5%
18 2
 
1.6%
640 2
 
1.6%
6 2
 
1.6%
62 2
 
1.6%
248 2
 
1.6%
106 2
 
1.6%
118 2
 
1.6%
3880 1
 
0.8%
Other values (91) 91
74.6%
2024-01-10T05:19:44.407154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 92
22.9%
1 69
17.2%
4 41
10.2%
8 38
9.5%
2 38
9.5%
6 35
 
8.7%
3 32
 
8.0%
7 17
 
4.2%
5 12
 
3.0%
, 10
 
2.5%
Other values (2) 18
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 383
95.3%
Other Punctuation 19
 
4.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 92
24.0%
1 69
18.0%
4 41
10.7%
8 38
9.9%
2 38
9.9%
6 35
 
9.1%
3 32
 
8.4%
7 17
 
4.4%
5 12
 
3.1%
9 9
 
2.3%
Other Punctuation
ValueCountFrequency (%)
, 10
52.6%
. 9
47.4%

Most occurring scripts

ValueCountFrequency (%)
Common 402
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 92
22.9%
1 69
17.2%
4 41
10.2%
8 38
9.5%
2 38
9.5%
6 35
 
8.7%
3 32
 
8.0%
7 17
 
4.2%
5 12
 
3.0%
, 10
 
2.5%
Other values (2) 18
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 402
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 92
22.9%
1 69
17.2%
4 41
10.2%
8 38
9.5%
2 38
9.5%
6 35
 
8.7%
3 32
 
8.0%
7 17
 
4.2%
5 12
 
3.0%
, 10
 
2.5%
Other values (2) 18
 
4.5%

현재체중
Text

Distinct95
Distinct (%)77.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-01-10T05:19:44.641386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.2868852
Min length1

Characters and Unicode

Total characters401
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

Unique85 ?
Unique (%)69.7%

Sample

1st row310
2nd row248
3rd row0
4th row171
5th row168
ValueCountFrequency (%)
0 16
 
13.1%
35.8 5
 
4.1%
16 2
 
1.6%
168 2
 
1.6%
200 2
 
1.6%
18 2
 
1.6%
640 2
 
1.6%
172 2
 
1.6%
8 2
 
1.6%
6 2
 
1.6%
Other values (85) 85
69.7%
2024-01-10T05:19:45.002877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 96
23.9%
1 63
15.7%
8 39
9.7%
4 38
 
9.5%
2 37
 
9.2%
6 35
 
8.7%
3 32
 
8.0%
7 17
 
4.2%
5 14
 
3.5%
9 13
 
3.2%
Other values (2) 17
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 384
95.8%
Other Punctuation 17
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 96
25.0%
1 63
16.4%
8 39
10.2%
4 38
 
9.9%
2 37
 
9.6%
6 35
 
9.1%
3 32
 
8.3%
7 17
 
4.4%
5 14
 
3.6%
9 13
 
3.4%
Other Punctuation
ValueCountFrequency (%)
, 9
52.9%
. 8
47.1%

Most occurring scripts

ValueCountFrequency (%)
Common 401
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 96
23.9%
1 63
15.7%
8 39
9.7%
4 38
 
9.5%
2 37
 
9.2%
6 35
 
8.7%
3 32
 
8.0%
7 17
 
4.2%
5 14
 
3.5%
9 13
 
3.2%
Other values (2) 17
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 401
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 96
23.9%
1 63
15.7%
8 39
9.7%
4 38
 
9.5%
2 37
 
9.2%
6 35
 
8.7%
3 32
 
8.0%
7 17
 
4.2%
5 14
 
3.5%
9 13
 
3.2%
Other values (2) 17
 
4.2%

임상적최종진단
Text

Distinct83
Distinct (%)68.6%
Missing1
Missing (%)0.8%
Memory size1.1 KiB
2024-01-10T05:19:45.282271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length27
Mean length12.049587
Min length2

Characters and Unicode

Total characters1458
Distinct characters213
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

Unique75 ?
Unique (%)62.0%

Sample

1st row우측 슬관절 탈구 및 좌측 대퇴골 탈구
2nd row방음벽 충돌 개체
3rd row폭스바이러스 중감염
4th row미아
5th row미아
ValueCountFrequency (%)
미아 31
 
7.3%
및 22
 
5.2%
의한 18
 
4.2%
개선충 17
 
4.0%
골절 16
 
3.8%
중감염 14
 
3.3%
우측 12
 
2.8%
충돌에 12
 
2.8%
단순 9
 
2.1%
좌측 9
 
2.1%
Other values (168) 264
62.3%
2024-01-10T05:19:45.665339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
305
 
20.9%
골 47
 
3.2%
충 38
 
2.6%
절 37
 
2.5%
개 36
 
2.5%
미 35
 
2.4%
아 34
 
2.3%
상 26
 
1.8%
한 25
 
1.7%
측 24
 
1.6%
Other values (203) 851
58.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1005
68.9%
Space Separator 305
 
20.9%
Lowercase Letter 66
 
4.5%
Other Punctuation 25
 
1.7%
Decimal Number 19
 
1.3%
Uppercase Letter 17
 
1.2%
Close Punctuation 10
 
0.7%
Open Punctuation 10
 
0.7%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
골 47
 
4.7%
충 38
 
3.8%
절 37
 
3.7%
개 36
 
3.6%
미 35
 
3.5%
아 34
 
3.4%
상 26
 
2.6%
한 25
 
2.5%
측 24
 
2.4%
에 22
 
2.2%
Other values (167) 681
67.8%
Lowercase Letter
ValueCountFrequency (%)
t 8
12.1%
e 6
 
9.1%
p 6
 
9.1%
i 6
 
9.1%
n 5
 
7.6%
o 5
 
7.6%
a 5
 
7.6%
l 3
 
4.5%
s 3
 
4.5%
m 3
 
4.5%
Other values (9) 16
24.2%
Decimal Number
ValueCountFrequency (%)
5 4
21.1%
4 4
21.1%
1 4
21.1%
2 2
10.5%
3 2
10.5%
6 2
10.5%
0 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 14
56.0%
. 8
32.0%
/ 3
 
12.0%
Uppercase Letter
ValueCountFrequency (%)
L 10
58.8%
R 5
29.4%
T 2
 
11.8%
Space Separator
ValueCountFrequency (%)
305
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1005
68.9%
Common 370
 
25.4%
Latin 83
 
5.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
골 47
 
4.7%
충 38
 
3.8%
절 37
 
3.7%
개 36
 
3.6%
미 35
 
3.5%
아 34
 
3.4%
상 26
 
2.6%
한 25
 
2.5%
측 24
 
2.4%
에 22
 
2.2%
Other values (167) 681
67.8%
Latin
ValueCountFrequency (%)
L 10
12.0%
t 8
 
9.6%
e 6
 
7.2%
p 6
 
7.2%
i 6
 
7.2%
n 5
 
6.0%
R 5
 
6.0%
o 5
 
6.0%
a 5
 
6.0%
l 3
 
3.6%
Other values (12) 24
28.9%
Common
ValueCountFrequency (%)
305
82.4%
, 14
 
3.8%
) 10
 
2.7%
( 10
 
2.7%
. 8
 
2.2%
5 4
 
1.1%
4 4
 
1.1%
1 4
 
1.1%
/ 3
 
0.8%
2 2
 
0.5%
Other values (4) 6
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1005
68.9%
ASCII 453
31.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
305
67.3%
, 14
 
3.1%
) 10
 
2.2%
L 10
 
2.2%
( 10
 
2.2%
t 8
 
1.8%
. 8
 
1.8%
e 6
 
1.3%
p 6
 
1.3%
i 6
 
1.3%
Other values (26) 70
 
15.5%
Hangul
ValueCountFrequency (%)
골 47
 
4.7%
충 38
 
3.8%
절 37
 
3.7%
개 36
 
3.6%
미 35
 
3.5%
아 34
 
3.4%
상 26
 
2.6%
한 25
 
2.5%
측 24
 
2.4%
에 22
 
2.2%
Other values (167) 681
67.8%

Sample

접수번호동물국문명강목과천연기념물멸종위기등급야생동물보호협약구조일시구조결과일자구조결과이첩 방생 위치사체처리동물성별동물연령구조위도구조경도구조고도방생위도방생경도발견장소상세발견주소발견장소특징발생원인발생원인 세부사항TM구조위도TM구조경도TM방생위도TM방생경도등록체중현재체중임상적최종진단
02019-1491꿩조강(Aves)닭목꿩과해당없음해당없음해당없음2019-10-052019-10-07폐사체<NA>기타UnknownJuvenile36.266528126.93122218<NA><NA>주소지 부근 농경지충청남도 부여군 부여읍 중정리 106농경지인공구조물 침입·고립인공구조물 끼임 추정36 15 59.5126 55 52.4<NA><NA>310310우측 슬관절 탈구 및 좌측 대퇴골 탈구
12019-0185멧비둘기조강(Aves)비둘기목비둘기과해당없음해당없음해당없음2019-03-292019-03-29폐사체<NA>기타UnknownUnknown36.298611126.93697212<NA><NA><NA>충청남도 부여군 부여읍 정동리 440-9도로변전선/건물과의 충돌방음벽 충돌 추정36 17 55.0126 56 13.1<NA><NA>248248방음벽 충돌 개체
22019-1492멧비둘기조강(Aves)비둘기목비둘기과해당없음해당없음해당없음2019-10-072019-10-07안락사<NA>기타UnknownUnknown36.285694126.90916720<NA><NA>(나루터로 37) 주소지 부근충청남도 부여군 부여읍 구아리 99건물옆바이러스 감염폭스 바이러스 감염36 17 08.5126 54 33.0<NA><NA>00폭스바이러스 중감염
32019-1567멧비둘기조강(Aves)비둘기목비둘기과해당없음해당없음해당없음2019-10-262019-11-27방생충청남도 예산군 예산읍 향천리 54<NA>UnknownNestling36.326111126.74005614836.690094126.862688밤나무 산충청남도 부여군 외산면 화성리 652-3숲어미를 잃음(미아)미아36 19 34.0126 44 24.236 41 24.0126 51 46.166171미아
42019-1568멧비둘기조강(Aves)비둘기목비둘기과해당없음해당없음해당없음2019-10-262019-11-27방생충청남도 예산군 예산읍 향천리 54<NA>UnknownNestling36.326111126.74005614836.690094126.862688밤나무 산충청남도 부여군 외산면 화성리 652-3숲어미를 잃음(미아)미아36 19 34.0126 44 24.236 41 24.0126 51 46.164168미아
52019-0316물까치조강(Aves)참새목까마귀과해당없음해당없음해당없음2019-04-302019-05-05폐사<NA>기타UnknownAdult36.307972126.89730630<NA><NA>한국전통문화대학 화장실 내부충청남도 부여군 규암면 합정리 430건물옆전선/건물과의 충돌화장실 유리창 충돌36 18 28.7126 53 50.3<NA><NA>6250건물 충돌에 의한 가벼운 뇌진탕
62019-0317물까치조강(Aves)참새목까마귀과해당없음해당없음해당없음2019-04-302019-05-02폐사체<NA>기타UnknownAdult36.307972126.89730630<NA><NA>한국전통문화대학 화장실 내부충청남도 부여군 규암면 합정리 430건물옆전선/건물과의 충돌화장실 유리창 충돌36 18 28.7126 53 50.3<NA><NA>7676건물 충돌 개체
72019-0884딱새조강(Aves)참새목솔딱새과해당없음해당없음해당없음2019-06-272019-07-06방생충청남도 예산군 예산읍 향천리 56-1<NA>UnknownJuvenile36.281389126.8179444736.690429126.862052<NA>충청남도 부여군 은산면 내지리 311-3건물옆어미를 잃음(미아)다른 동배 개체들 이소 후에도 둥지에 남아있음36 16 53.0126 49 04.636 41 24.8126 51 43.61216동배 이소 후에도 둥지에 잔류
82019-1659흰배지빠귀조강(Aves)참새목지빠귀과해당없음해당없음해당없음2019-11-232019-11-23폐사체<NA>기타UnknownUnknown36.230639126.87361146<NA><NA><NA>충청남도 부여군 장암면 합곡리 66-8농경지전선/건물과의 충돌충돌 추정36 13 50.3126 52 25.0<NA><NA>5454충돌 추정 개체
92019-0858참새조강(Aves)참새목참새과해당없음해당없음해당없음2019-06-242019-06-24폐사체<NA>기타UnknownUnknown36.276806126.78694447<NA><NA><NA>충청남도 부여군 내산면 운치리 324-5도로변전선/건물과의 충돌도로 방음벽 충돌36 16 36.5126 47 13.0<NA><NA>1818방음벽 충돌 개체
접수번호동물국문명강목과천연기념물멸종위기등급야생동물보호협약구조일시구조결과일자구조결과이첩 방생 위치사체처리동물성별동물연령구조위도구조경도구조고도방생위도방생경도발견장소상세발견주소발견장소특징발생원인발생원인 세부사항TM구조위도TM구조경도TM방생위도TM방생경도등록체중현재체중임상적최종진단
1122022-0235고라니포유강(Mammalia)소목사슴과해당없음해당없음해당없음2022-02-102022-02-12폐사<NA>폐기Female0년0월0일36.17.452126.56.53322<NA><NA>농경지충남 부여군 부여읍 가증리 166-1농경지- 차량과의 충돌차량과의 충돌<NA><NA><NA><NA>19,64019,640우측 척골 골절
1132022-0331고라니포유강(Mammalia)소목사슴과해당없음해당없음해당없음2022-03-162022-03-16폐사체<NA>폐기Female0년0월0일36.16.543126.55.14725<NA><NA>주소지 도로 가운데충남 부여군 부여읍 쌍북리 583-4도로변- 차량과의 충돌차량과의 충돌<NA><NA><NA><NA>14,18014,180우측 metacarpal bone open fx. 항문부 심한열상
1142022-1284고라니포유강(Mammalia)소목사슴과해당없음해당없음해당없음2022-06-152022-06-23폐사<NA>폐기Unknown0년0월0일36.19.332126.51.28113<NA><NA>고속도로 공사현장 인근 도로변충남 부여군 은산면 회곡리 88-6도로변- 어미를 잃음(미아)어미를 잃음(미아)<NA><NA><NA><NA>1,0761,248미아, 탈진
1152022-1501고라니포유강(Mammalia)소목사슴과해당없음해당없음해당없음2022-07-012022-07-01안락사<NA>폐기Unknown0년1월0일36.10.576126.42.27383<NA><NA>주소지 인근 농로 주변 농경지충남 부여군 옥산면 대덕리 363농경지- 어미를 잃음(미아)어미를 잃음(미아)<NA><NA><NA><NA>1,2181,218선천적 안구 구조물 이상
1162022-1799고라니포유강(Mammalia)소목사슴과해당없음해당없음해당없음2022-07-312022-08-01방생충남 부여군 세도면 간대리 산 34<NA>Female0년2월0일36.10.133126.56.45211<NA><NA>우수로충남 부여군 세도면 청송리 427-2도로변- 농수로 고립농수로 고립<NA><NA><NA><NA>6,0806,080고립, 저체온증
1172022-1980고라니포유강(Mammalia)소목사슴과해당없음해당없음해당없음2022-08-292022-08-29안락사<NA>냉동(구냉동창고)(성체고라니, 개선충너구리)Male2년3월0일36.18.270126.50.32964<NA><NA>주소지 인근 29번 국도 하행선 녹지 사면 상충남 부여군 은산면 은산리 238도로변- 차량과의 충돌차량과의 충돌<NA><NA><NA><NA>15,46015,460차량 충돌에 의한 L6, 우측 골반 골절
1182022-2215고라니포유강(Mammalia)소목사슴과해당없음해당없음해당없음2022-10-232022-10-23폐사체<NA>냉동(구냉동창고)(성체고라니, 개선충너구리)Female0년0월0일36.16.389126.53.06824<NA><NA>농경지충남 부여군 규암면 규암리 65농경지- 인공구조물에 얽힘인공구조물에 얽힘<NA><NA><NA><NA>19,40019,400좌안 소실 우안 hypopyon
1192022-2461고라니포유강(Mammalia)소목사슴과해당없음해당없음해당없음2022-12-192022-12-19안락사<NA>냉동(구냉동창고)(성체고라니, 개선충너구리)Male0년0월0일36.15.244126.51.0430<NA><NA>도로변충남 부여군 규암면 노화리 130-6도로변- 차량과의 충돌차량과의 충돌<NA><NA><NA><NA>17,5000L5 골절
1202022-2159너구리포유강(Mammalia)식육목개과해당없음해당없음해당없음2022-10-112022-10-11안락사<NA>냉동(신냉동창고)(선반)Unknown0년0월0일36.21.188126.48.11195<NA><NA>주소지 내 하천변충남 부여군 은산면 장벌리 563농경지- 차량과의 충돌차량과의 충돌<NA><NA><NA><NA>4,6004,600목뼈 1번 골절, 좌측 어깨뼈 골절
1212022-2317너구리포유강(Mammalia)식육목개과해당없음해당없음해당없음2022-11-152022-11-16DOA<NA>냉동(구냉동창고)(성체고라니, 개선충너구리)Male0년0월0일36.14.250126.45.08059<NA><NA>주소지 내 농경지충남 부여군 홍산면 상천리 258-1농경지- 기생충 중감염기생충 중감염/개선충 중감염<NA><NA><NA><NA>3,4303,430개선충 중감염