Overview

Dataset statistics

Number of variables32
Number of observations181
Missing cells865
Missing cells (%)14.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory45.9 KiB
Average record size in memory259.7 B

Variable types

Text14
Categorical13
DateTime2
Numeric3

Dataset

Description충남 야생동물 구조센터에서 구조한 야생동물의 종, 구조시점, 위치 자료 및 구조 이후 조치결과에 대한 자료 중, 보령시 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=15109263

Alerts

천연기념물 has constant value ""Constant
멸종위기등급 has constant value ""Constant
야생동물보호협약 has constant value ""Constant
이첩 방생 위치 has 145 (80.1%) missing valuesMissing
방생위도 has 152 (84.0%) missing valuesMissing
방생경도 has 152 (84.0%) missing valuesMissing
발견장소상세 has 11 (6.1%) missing valuesMissing
TM구조위도 has 49 (27.1%) missing valuesMissing
TM구조경도 has 49 (27.1%) missing valuesMissing
TM방생위도 has 152 (84.0%) missing valuesMissing
TM방생경도 has 152 (84.0%) missing valuesMissing
임상적최종진단 has 2 (1.1%) missing valuesMissing
접수번호 has unique valuesUnique
구조고도 has 7 (3.9%) zerosZeros

Reproduction

Analysis started2024-01-09 21:49:22.419416
Analysis finished2024-01-09 21:49:23.120967
Duration0.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

접수번호
Text

UNIQUE 

Distinct181
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-01-10T06:49:23.329593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters1629
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

Unique181 ?
Unique (%)100.0%

Sample

1st row2019-1266
2nd row2019-1054
3rd row2019-1125
4th row2019-1141
5th row2019-1339
ValueCountFrequency (%)
2019-1266 1
 
0.6%
2021-1770 1
 
0.6%
2021-0585 1
 
0.6%
2021-1055 1
 
0.6%
2021-1203 1
 
0.6%
2021-1222 1
 
0.6%
2021-1636 1
 
0.6%
2021-1821 1
 
0.6%
2021-1960 1
 
0.6%
2021-2026 1
 
0.6%
Other values (171) 171
94.5%
2024-01-10T06:49:23.695373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 443
27.2%
0 360
22.1%
1 234
14.4%
- 181
11.1%
9 83
 
5.1%
3 62
 
3.8%
5 59
 
3.6%
4 57
 
3.5%
6 53
 
3.3%
7 52
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1448
88.9%
Dash Punctuation 181
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 443
30.6%
0 360
24.9%
1 234
16.2%
9 83
 
5.7%
3 62
 
4.3%
5 59
 
4.1%
4 57
 
3.9%
6 53
 
3.7%
7 52
 
3.6%
8 45
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 181
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1629
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 443
27.2%
0 360
22.1%
1 234
14.4%
- 181
11.1%
9 83
 
5.1%
3 62
 
3.8%
5 59
 
3.6%
4 57
 
3.5%
6 53
 
3.3%
7 52
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1629
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 443
27.2%
0 360
22.1%
1 234
14.4%
- 181
11.1%
9 83
 
5.1%
3 62
 
3.8%
5 59
 
3.6%
4 57
 
3.5%
6 53
 
3.3%
7 52
 
3.2%

동물국문명
Categorical

Distinct42
Distinct (%)23.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
고라니
56 
괭이갈매기
20 
너구리
15 
멧비둘기
8 
흰뺨검둥오리
8 
Other values (37)
74 

Length

Max length8
Median length3
Mean length3.6132597
Min length1

Unique

Unique20 ?
Unique (%)11.0%

Sample

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

Common Values

ValueCountFrequency (%)
고라니 56
30.9%
괭이갈매기 20
 
11.0%
너구리 15
 
8.3%
멧비둘기 8
 
4.4%
흰뺨검둥오리 8
 
4.4%
물총새 7
 
3.9%
중대백로㉵ 6
 
3.3%
까치 6
 
3.3%
왜가리 4
 
2.2%
파랑새 4
 
2.2%
Other values (32) 47
26.0%

Length

2024-01-10T06:49:23.821787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고라니 56
30.9%
괭이갈매기 20
 
11.0%
너구리 15
 
8.3%
멧비둘기 8
 
4.4%
흰뺨검둥오리 8
 
4.4%
물총새 7
 
3.9%
중대백로㉵ 6
 
3.3%
까치 6
 
3.3%
파랑새 4
 
2.2%
왜가리 4
 
2.2%
Other values (32) 47
26.0%

강
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
조강(Aves)
104 
포유강(Mammalia)
77 

Length

Max length13
Median length8
Mean length10.127072
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) 104
57.5%
포유강(Mammalia) 77
42.5%

Length

2024-01-10T06:49:23.919813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:49:24.001177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
조강(aves 104
57.5%
포유강(mammalia 77
42.5%

목
Categorical

Distinct14
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
소목
56 
도요목
23 
참새목
23 
황새목
18 
식육목
17 
Other values (9)
44 

Length

Max length5
Median length4
Mean length2.9005525
Min length2

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
소목 56
30.9%
도요목 23
12.7%
참새목 23
12.7%
황새목 18
 
9.9%
식육목 17
 
9.4%
파랑새목 11
 
6.1%
기러기목 11
 
6.1%
비둘기목 9
 
5.0%
사다새목 3
 
1.7%
딱다구리목 3
 
1.7%
Other values (4) 7
 
3.9%

Length

2024-01-10T06:49:24.086371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
소목 56
30.9%
도요목 23
12.7%
참새목 23
12.7%
황새목 18
 
9.9%
식육목 17
 
9.4%
파랑새목 11
 
6.1%
기러기목 11
 
6.1%
비둘기목 9
 
5.0%
사다새목 3
 
1.7%
딱다구리목 3
 
1.7%
Other values (4) 7
 
3.9%

과
Categorical

Distinct27
Distinct (%)14.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
사슴과
56 
갈매기과
21 
왜가리과
18 
개과
15 
오리과
11 
Other values (22)
60 

Length

Max length5
Median length4
Mean length3.4696133
Min length2

Unique

Unique8 ?
Unique (%)4.4%

Sample

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

Common Values

ValueCountFrequency (%)
사슴과 56
30.9%
갈매기과 21
 
11.6%
왜가리과 18
 
9.9%
개과 15
 
8.3%
오리과 11
 
6.1%
비둘기과 9
 
5.0%
까마귀과 8
 
4.4%
물총새과 7
 
3.9%
파랑새과 4
 
2.2%
직박구리과 3
 
1.7%
Other values (17) 29
16.0%

Length

2024-01-10T06:49:24.188084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
사슴과 56
30.9%
갈매기과 21
 
11.6%
왜가리과 18
 
9.9%
개과 15
 
8.3%
오리과 11
 
6.1%
비둘기과 9
 
5.0%
까마귀과 8
 
4.4%
물총새과 7
 
3.9%
파랑새과 4
 
2.2%
직박구리과 3
 
1.7%
Other values (17) 29
16.0%

천연기념물
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
해당없음
181 

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 181
100.0%

Length

2024-01-10T06:49:24.284181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:49:24.364990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 181
100.0%

멸종위기등급
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
해당없음
181 

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 181
100.0%

Length

2024-01-10T06:49:24.448394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:49:24.528198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 181
100.0%

야생동물보호협약
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
해당없음
181 

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 181
100.0%

Length

2024-01-10T06:49:24.614653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:49:24.694833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 181
100.0%

구조일시
Date

Distinct154
Distinct (%)85.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum2019-01-14 00:00:00
Maximum2022-12-26 00:00:00
2024-01-10T06:49:24.789797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:49:24.899402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

구조결과일자
Date

Distinct155
Distinct (%)85.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum2019-02-16 00:00:00
Maximum2022-12-26 00:00:00
2024-01-10T06:49:25.272503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:49:25.386833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

구조결과
Categorical

Distinct5
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
안락사
62 
DOA
37 
방생
36 
폐사
31 
폐사체
15 

Length

Max length3
Median length3
Mean length2.6298343
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안락사 62
34.3%
DOA 37
20.4%
방생 36
19.9%
폐사 31
17.1%
폐사체 15
 
8.3%

Length

2024-01-10T06:49:25.488414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:49:25.582359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안락사 62
34.3%
doa 37
20.4%
방생 36
19.9%
폐사 31
17.1%
폐사체 15
 
8.3%

이첩 방생 위치
Text

MISSING 

Distinct29
Distinct (%)80.6%
Missing145
Missing (%)80.1%
Memory size1.5 KiB
2024-01-10T06:49:25.785349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length20.416667
Min length12

Characters and Unicode

Total characters735
Distinct characters97
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

Unique24 ?
Unique (%)66.7%

Sample

1st row충청남도 서산시 고북면 사기리 1109
2nd row충청남도 예산군 예산읍 주교리 488-7
3rd row충청남도 서산시 인지면 산동리 939
4th row충청남도 보령시 남포면 봉덕리 437-61
5th row충청남도 예산군 대흥면 손지리 577
ValueCountFrequency (%)
충청남도 28
 
15.5%
예산군 13
 
7.2%
보령시 9
 
5.0%
산 7
 
3.9%
예산읍 7
 
3.9%
충남 6
 
3.3%
1 4
 
2.2%
서산시 4
 
2.2%
대회리 4
 
2.2%
손지리 4
 
2.2%
Other values (73) 95
52.5%
2024-01-10T06:49:26.100156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
148
20.1%
산 38
 
5.2%
남 35
 
4.8%
충 34
 
4.6%
청 31
 
4.2%
리 31
 
4.2%
도 29
 
3.9%
1 23
 
3.1%
면 21
 
2.9%
예 20
 
2.7%
Other values (87) 325
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 458
62.3%
Space Separator 148
 
20.1%
Decimal Number 110
 
15.0%
Dash Punctuation 19
 
2.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 38
 
8.3%
남 35
 
7.6%
충 34
 
7.4%
청 31
 
6.8%
리 31
 
6.8%
도 29
 
6.3%
면 21
 
4.6%
예 20
 
4.4%
시 19
 
4.1%
군 18
 
3.9%
Other values (75) 182
39.7%
Decimal Number
ValueCountFrequency (%)
1 23
20.9%
4 15
13.6%
3 13
11.8%
5 12
10.9%
9 11
10.0%
7 10
9.1%
2 9
 
8.2%
0 8
 
7.3%
8 5
 
4.5%
6 4
 
3.6%
Space Separator
ValueCountFrequency (%)
148
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 458
62.3%
Common 277
37.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 38
 
8.3%
남 35
 
7.6%
충 34
 
7.4%
청 31
 
6.8%
리 31
 
6.8%
도 29
 
6.3%
면 21
 
4.6%
예 20
 
4.4%
시 19
 
4.1%
군 18
 
3.9%
Other values (75) 182
39.7%
Common
ValueCountFrequency (%)
148
53.4%
1 23
 
8.3%
- 19
 
6.9%
4 15
 
5.4%
3 13
 
4.7%
5 12
 
4.3%
9 11
 
4.0%
7 10
 
3.6%
2 9
 
3.2%
0 8
 
2.9%
Other values (2) 9
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 458
62.3%
ASCII 277
37.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
148
53.4%
1 23
 
8.3%
- 19
 
6.9%
4 15
 
5.4%
3 13
 
4.7%
5 12
 
4.3%
9 11
 
4.0%
7 10
 
3.6%
2 9
 
3.2%
0 8
 
2.9%
Other values (2) 9
 
3.2%
Hangul
ValueCountFrequency (%)
산 38
 
8.3%
남 35
 
7.6%
충 34
 
7.4%
청 31
 
6.8%
리 31
 
6.8%
도 29
 
6.3%
면 21
 
4.6%
예 20
 
4.4%
시 19
 
4.1%
군 18
 
3.9%
Other values (75) 182
39.7%

사체처리
Categorical

Distinct8
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
기타
105 
<NA>
39 
폐기
18 
냉동(신냉동창고)(투입박스(일반))
 
10
기타(협조)
 
4
Other values (3)
 
5

Length

Max length24
Median length2
Mean length3.961326
Min length2

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
기타 105
58.0%
<NA> 39
 
21.5%
폐기 18
 
9.9%
냉동(신냉동창고)(투입박스(일반)) 10
 
5.5%
기타(협조) 4
 
2.2%
냉동(표본제작실)(중소형조류 2) 2
 
1.1%
냉동(구냉동창고)(성체고라니, 개선충너구리) 2
 
1.1%
냉동(표본제작실)(소형조류 1) 1
 
0.6%

Length

2024-01-10T06:49:26.219235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:49:26.320306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 105
56.5%
na 39
 
21.0%
폐기 18
 
9.7%
냉동(신냉동창고)(투입박스(일반 10
 
5.4%
기타(협조 4
 
2.2%
냉동(표본제작실)(중소형조류 2
 
1.1%
2 2
 
1.1%
냉동(구냉동창고)(성체고라니 2
 
1.1%
개선충너구리 2
 
1.1%
냉동(표본제작실)(소형조류 1
 
0.5%

동물성별
Categorical

Distinct3
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Unknown
116 
Male
33 
Female
32 

Length

Max length7
Median length7
Mean length6.2762431
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
Unknown 116
64.1%
Male 33
 
18.2%
Female 32
 
17.7%

Length

2024-01-10T06:49:26.437708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:49:26.523838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
unknown 116
64.1%
male 33
 
18.2%
female 32
 
17.7%

동물연령
Categorical

Distinct21
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0년0월0일
41 
Adult
35 
Juvenile
30 
Unknown
24 
Nestling
15 
Other values (16)
36 

Length

Max length8
Median length7
Mean length6.4530387
Min length5

Unique

Unique9 ?
Unique (%)5.0%

Sample

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

Common Values

ValueCountFrequency (%)
0년0월0일 41
22.7%
Adult 35
19.3%
Juvenile 30
16.6%
Unknown 24
13.3%
Nestling 15
 
8.3%
0년2월0일 6
 
3.3%
0년6월0일 5
 
2.8%
0년1월0일 5
 
2.8%
0년7월0일 4
 
2.2%
0년11월0일 3
 
1.7%
Other values (11) 13
 
7.2%

Length

2024-01-10T06:49:26.618696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0년0월0일 41
22.7%
adult 35
19.3%
juvenile 30
16.6%
unknown 24
13.3%
nestling 15
 
8.3%
0년2월0일 6
 
3.3%
0년6월0일 5
 
2.8%
0년1월0일 5
 
2.8%
0년7월0일 4
 
2.2%
0년11월0일 3
 
1.7%
Other values (11) 13
 
7.2%

구조위도
Text

Distinct165
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-01-10T06:49:26.869587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.839779
Min length6

Characters and Unicode

Total characters1600
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

Unique156 ?
Unique (%)86.2%

Sample

1st row36.244056
2nd row36.315111
3rd row36.322278
4th row36.327083
5th row36.305611
ValueCountFrequency (%)
36.36575 6
 
3.3%
36.437944 5
 
2.8%
36.354639 2
 
1.1%
36.322278 2
 
1.1%
36.341889 2
 
1.1%
36.329028 2
 
1.1%
36.377778 2
 
1.1%
36.233639 2
 
1.1%
36.384389 2
 
1.1%
36.18.524 1
 
0.6%
Other values (155) 155
85.6%
2024-01-10T06:49:27.230505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 356
22.2%
6 270
16.9%
. 230
14.4%
2 134
 
8.4%
4 116
 
7.2%
1 115
 
7.2%
7 86
 
5.4%
9 77
 
4.8%
8 77
 
4.8%
5 75
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1370
85.6%
Other Punctuation 230
 
14.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 356
26.0%
6 270
19.7%
2 134
 
9.8%
4 116
 
8.5%
1 115
 
8.4%
7 86
 
6.3%
9 77
 
5.6%
8 77
 
5.6%
5 75
 
5.5%
0 64
 
4.7%
Other Punctuation
ValueCountFrequency (%)
. 230
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1600
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 356
22.2%
6 270
16.9%
. 230
14.4%
2 134
 
8.4%
4 116
 
7.2%
1 115
 
7.2%
7 86
 
5.4%
9 77
 
4.8%
8 77
 
4.8%
5 75
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 356
22.2%
6 270
16.9%
. 230
14.4%
2 134
 
8.4%
4 116
 
7.2%
1 115
 
7.2%
7 86
 
5.4%
9 77
 
4.8%
8 77
 
4.8%
5 75
 
4.7%

구조경도
Text

Distinct165
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-01-10T06:49:27.476713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.8563536
Min length7

Characters and Unicode

Total characters1784
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

Unique156 ?
Unique (%)86.2%

Sample

1st row126.583083
2nd row126.512083
3rd row126.526389
4th row126.511472
5th row126.516111
ValueCountFrequency (%)
126.611194 6
 
3.3%
126.588944 5
 
2.8%
126.593139 2
 
1.1%
126.526389 2
 
1.1%
126.607528 2
 
1.1%
126.602 2
 
1.1%
126.598639 2
 
1.1%
126.530444 2
 
1.1%
126.492056 2
 
1.1%
126.30.386 1
 
0.6%
Other values (155) 155
85.6%
2024-01-10T06:49:27.826463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 309
17.3%
1 282
15.8%
2 275
15.4%
. 230
12.9%
5 152
8.5%
3 136
7.6%
8 91
 
5.1%
9 89
 
5.0%
4 89
 
5.0%
0 69
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1554
87.1%
Other Punctuation 230
 
12.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 309
19.9%
1 282
18.1%
2 275
17.7%
5 152
9.8%
3 136
8.8%
8 91
 
5.9%
9 89
 
5.7%
4 89
 
5.7%
0 69
 
4.4%
7 62
 
4.0%
Other Punctuation
ValueCountFrequency (%)
. 230
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1784
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 309
17.3%
1 282
15.8%
2 275
15.4%
. 230
12.9%
5 152
8.5%
3 136
7.6%
8 91
 
5.1%
9 89
 
5.0%
4 89
 
5.0%
0 69
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1784
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 309
17.3%
1 282
15.8%
2 275
15.4%
. 230
12.9%
5 152
8.5%
3 136
7.6%
8 91
 
5.1%
9 89
 
5.0%
4 89
 
5.0%
0 69
 
3.9%

구조고도
Real number (ℝ)

ZEROS 

Distinct68
Distinct (%)37.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.375691
Minimum0
Maximum307
Zeros7
Zeros (%)3.9%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-01-10T06:49:27.953200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q18
median16
Q337
95-th percentile197
Maximum307
Range307
Interquartile range (IQR)29

Descriptive statistics

Standard deviation57.682486
Coefficient of variation (CV)1.5030996
Kurtosis6.6893737
Mean38.375691
Median Absolute Deviation (MAD)10
Skewness2.6359615
Sum6946
Variance3327.2692
MonotonicityNot monotonic
2024-01-10T06:49:28.062727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7 13
 
7.2%
16 10
 
5.5%
8 7
 
3.9%
0 7
 
3.9%
5 7
 
3.9%
22 7
 
3.9%
10 6
 
3.3%
9 6
 
3.3%
14 5
 
2.8%
17 5
 
2.8%
Other values (58) 108
59.7%
ValueCountFrequency (%)
0 7
3.9%
1 2
 
1.1%
2 5
 
2.8%
3 3
 
1.7%
4 4
 
2.2%
5 7
3.9%
6 4
 
2.2%
7 13
7.2%
8 7
3.9%
9 6
3.3%
ValueCountFrequency (%)
307 1
0.6%
256 1
0.6%
252 2
1.1%
234 1
0.6%
214 2
1.1%
213 1
0.6%
206 1
0.6%
197 1
0.6%
181 1
0.6%
179 1
0.6%

방생위도
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)79.3%
Missing152
Missing (%)84.0%
Infinite0
Infinite (%)0.0%
Mean36.544794
Minimum36.240162
Maximum36.7327
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-01-10T06:49:28.167066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.240162
5-th percentile36.241938
Q136.393112
median36.657386
Q336.670081
95-th percentile36.718424
Maximum36.7327
Range0.49253746
Interquartile range (IQR)0.27696969

Descriptive statistics

Standard deviation0.1708107
Coefficient of variation (CV)0.0046740091
Kurtosis-1.2618232
Mean36.544794
Median Absolute Deviation (MAD)0.05871089
Skewness-0.64791374
Sum1059.799
Variance0.029176295
MonotonicityNot monotonic
2024-01-10T06:49:28.259727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
36.67008139 3
 
1.7%
36.65913757 3
 
1.7%
36.24016249 2
 
1.1%
36.3931117 2
 
1.1%
36.69009433 1
 
0.6%
36.56895558 1
 
0.6%
36.61268678 1
 
0.6%
36.71997529 1
 
0.6%
36.36345959 1
 
0.6%
36.71609726 1
 
0.6%
Other values (13) 13
 
7.2%
(Missing) 152
84.0%
ValueCountFrequency (%)
36.24016249 2
1.1%
36.24460094 1
0.6%
36.32291504 1
0.6%
36.32801755 1
0.6%
36.35990872 1
0.6%
36.36345959 1
0.6%
36.3931117 2
1.1%
36.40192496 1
0.6%
36.46003141 1
0.6%
36.56895558 1
0.6%
ValueCountFrequency (%)
36.73269995 1
 
0.6%
36.71997529 1
 
0.6%
36.71609726 1
 
0.6%
36.69863217 1
 
0.6%
36.69009433 1
 
0.6%
36.68204499 1
 
0.6%
36.67008139 3
1.7%
36.66980758 1
 
0.6%
36.66022951 1
 
0.6%
36.65913757 3
1.7%

방생경도
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)79.3%
Missing152
Missing (%)84.0%
Infinite0
Infinite (%)0.0%
Mean126.72631
Minimum126.45155
Maximum127.25954
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-01-10T06:49:28.356487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.45155
5-th percentile126.48658
Q1126.53658
median126.70699
Q3126.85967
95-th percentile127.13454
Maximum127.25954
Range0.8079935
Interquartile range (IQR)0.3230866

Descriptive statistics

Standard deviation0.21300431
Coefficient of variation (CV)0.0016808215
Kurtosis0.5979717
Mean126.72631
Median Absolute Deviation (MAD)0.1526796
Skewness0.91292922
Sum3675.063
Variance0.045370836
MonotonicityNot monotonic
2024-01-10T06:49:28.453818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
126.8596661 3
 
1.7%
126.8125091 3
 
1.7%
126.531602 2
 
1.1%
126.5715732 2
 
1.1%
126.8626875 1
 
0.6%
126.6156838 1
 
0.6%
127.2470079 1
 
0.6%
126.5784814 1
 
0.6%
127.2595397 1
 
0.6%
126.5296801 1
 
0.6%
Other values (13) 13
 
7.2%
(Missing) 152
84.0%
ValueCountFrequency (%)
126.4515462 1
0.6%
126.4599809 1
0.6%
126.5264689 1
0.6%
126.5277281 1
0.6%
126.5296801 1
0.6%
126.531602 2
1.1%
126.5365795 1
0.6%
126.5715732 2
1.1%
126.5784814 1
0.6%
126.591606 1
0.6%
ValueCountFrequency (%)
127.2595397 1
 
0.6%
127.2470079 1
 
0.6%
126.9658272 1
 
0.6%
126.9494448 1
 
0.6%
126.8626875 1
 
0.6%
126.8596661 3
1.7%
126.8204893 1
 
0.6%
126.812534 1
 
0.6%
126.8125091 3
1.7%
126.7962737 1
 
0.6%

발견장소상세
Text

MISSING 

Distinct141
Distinct (%)82.9%
Missing11
Missing (%)6.1%
Memory size1.5 KiB
2024-01-10T06:49:28.707481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length20
Mean length9.8882353
Min length2

Characters and Unicode

Total characters1681
Distinct characters260
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

Unique133 ?
Unique (%)78.2%

Sample

1st row주소지 확실치 않음
2nd row대천해수욕장 부근 건물 옆
3rd row대천해수욕장
4th row(대천항중앙길 46) 유람선터미널 부근
5th row대천해수욕장
ValueCountFrequency (%)
주소지 47
 
9.9%
부근 33
 
6.9%
도로변 17
 
3.6%
인근 17
 
3.6%
앞 15
 
3.1%
옆 15
 
3.1%
도로 13
 
2.7%
농수로 12
 
2.5%
안 10
 
2.1%
내 9
 
1.9%
Other values (207) 289
60.6%
2024-01-10T06:49:29.092617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
315
 
18.7%
지 70
 
4.2%
주 68
 
4.0%
로 63
 
3.7%
소 61
 
3.6%
근 52
 
3.1%
부 48
 
2.9%
도 45
 
2.7%
변 34
 
2.0%
수 32
 
1.9%
Other values (250) 893
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1294
77.0%
Space Separator 315
 
18.7%
Decimal Number 30
 
1.8%
Lowercase Letter 20
 
1.2%
Open Punctuation 10
 
0.6%
Close Punctuation 9
 
0.5%
Dash Punctuation 2
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 70
 
5.4%
주 68
 
5.3%
로 63
 
4.9%
소 61
 
4.7%
근 52
 
4.0%
부 48
 
3.7%
도 45
 
3.5%
변 34
 
2.6%
수 32
 
2.5%
장 30
 
2.3%
Other values (221) 791
61.1%
Lowercase Letter
ValueCountFrequency (%)
h 3
15.0%
q 2
10.0%
n 2
10.0%
w 2
10.0%
s 2
10.0%
f 1
 
5.0%
e 1
 
5.0%
m 1
 
5.0%
r 1
 
5.0%
l 1
 
5.0%
Other values (4) 4
20.0%
Decimal Number
ValueCountFrequency (%)
1 7
23.3%
2 6
20.0%
6 5
16.7%
3 4
13.3%
0 3
10.0%
4 1
 
3.3%
9 1
 
3.3%
8 1
 
3.3%
5 1
 
3.3%
7 1
 
3.3%
Space Separator
ValueCountFrequency (%)
315
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1294
77.0%
Common 367
 
21.8%
Latin 20
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 70
 
5.4%
주 68
 
5.3%
로 63
 
4.9%
소 61
 
4.7%
근 52
 
4.0%
부 48
 
3.7%
도 45
 
3.5%
변 34
 
2.6%
수 32
 
2.5%
장 30
 
2.3%
Other values (221) 791
61.1%
Common
ValueCountFrequency (%)
315
85.8%
( 10
 
2.7%
) 9
 
2.5%
1 7
 
1.9%
2 6
 
1.6%
6 5
 
1.4%
3 4
 
1.1%
0 3
 
0.8%
- 2
 
0.5%
4 1
 
0.3%
Other values (5) 5
 
1.4%
Latin
ValueCountFrequency (%)
h 3
15.0%
q 2
10.0%
n 2
10.0%
w 2
10.0%
s 2
10.0%
f 1
 
5.0%
e 1
 
5.0%
m 1
 
5.0%
r 1
 
5.0%
l 1
 
5.0%
Other values (4) 4
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1294
77.0%
ASCII 387
 
23.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
315
81.4%
( 10
 
2.6%
) 9
 
2.3%
1 7
 
1.8%
2 6
 
1.6%
6 5
 
1.3%
3 4
 
1.0%
0 3
 
0.8%
h 3
 
0.8%
q 2
 
0.5%
Other values (19) 23
 
5.9%
Hangul
ValueCountFrequency (%)
지 70
 
5.4%
주 68
 
5.3%
로 63
 
4.9%
소 61
 
4.7%
근 52
 
4.0%
부 48
 
3.7%
도 45
 
3.5%
변 34
 
2.6%
수 32
 
2.5%
장 30
 
2.3%
Other values (221) 791
61.1%

발견주소
Text

Distinct167
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-01-10T06:49:29.379456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length19.458564
Min length13

Characters and Unicode

Total characters3522
Distinct characters122
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

Unique160 ?
Unique (%)88.4%

Sample

1st row충청남도 보령시 웅천읍 두룡리 539-2
2nd row충청남도 보령시 신흑동 2284-4
3rd row충청남도 보령시 신흑동 2107
4th row충청남도 보령시 신흑동 2240-12
5th row충청남도 보령시 신흑동 2267-3
ValueCountFrequency (%)
보령시 181
21.8%
충청남도 132
 
15.9%
충남 49
 
5.9%
웅천읍 22
 
2.7%
주교면 20
 
2.4%
신흑동 18
 
2.2%
죽정동 13
 
1.6%
청소면 12
 
1.4%
남포면 12
 
1.4%
오천면 12
 
1.4%
Other values (241) 358
43.2%
2024-01-10T06:49:29.787368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
658
18.7%
남 194
 
5.5%
보 185
 
5.3%
령 182
 
5.2%
시 182
 
5.2%
충 181
 
5.1%
청 151
 
4.3%
도 138
 
3.9%
1 128
 
3.6%
- 120
 
3.4%
Other values (112) 1403
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2061
58.5%
Decimal Number 683
 
19.4%
Space Separator 658
 
18.7%
Dash Punctuation 120
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 194
 
9.4%
보 185
 
9.0%
령 182
 
8.8%
시 182
 
8.8%
충 181
 
8.8%
청 151
 
7.3%
도 138
 
6.7%
리 87
 
4.2%
면 79
 
3.8%
동 74
 
3.6%
Other values (100) 608
29.5%
Decimal Number
ValueCountFrequency (%)
1 128
18.7%
2 96
14.1%
3 74
10.8%
6 74
10.8%
4 62
9.1%
5 60
8.8%
7 58
8.5%
8 49
 
7.2%
0 46
 
6.7%
9 36
 
5.3%
Space Separator
ValueCountFrequency (%)
658
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 120
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2061
58.5%
Common 1461
41.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 194
 
9.4%
보 185
 
9.0%
령 182
 
8.8%
시 182
 
8.8%
충 181
 
8.8%
청 151
 
7.3%
도 138
 
6.7%
리 87
 
4.2%
면 79
 
3.8%
동 74
 
3.6%
Other values (100) 608
29.5%
Common
ValueCountFrequency (%)
658
45.0%
1 128
 
8.8%
- 120
 
8.2%
2 96
 
6.6%
3 74
 
5.1%
6 74
 
5.1%
4 62
 
4.2%
5 60
 
4.1%
7 58
 
4.0%
8 49
 
3.4%
Other values (2) 82
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2061
58.5%
ASCII 1461
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
658
45.0%
1 128
 
8.8%
- 120
 
8.2%
2 96
 
6.6%
3 74
 
5.1%
6 74
 
5.1%
4 62
 
4.2%
5 60
 
4.1%
7 58
 
4.0%
8 49
 
3.4%
Other values (2) 82
 
5.6%
Hangul
ValueCountFrequency (%)
남 194
 
9.4%
보 185
 
9.0%
령 182
 
8.8%
시 182
 
8.8%
충 181
 
8.8%
청 151
 
7.3%
도 138
 
6.7%
리 87
 
4.2%
면 79
 
3.8%
동 74
 
3.6%
Other values (100) 608
29.5%

발견장소특징
Categorical

Distinct7
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
건물옆
63 
도로변
51 
강, 바다
28 
농경지
20 
숲
14 
Other values (2)
 
5

Length

Max length5
Median length3
Mean length3.1270718
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row숲
2nd row건물옆
3rd row강, 바다
4th row건물옆
5th row강, 바다

Common Values

ValueCountFrequency (%)
건물옆 63
34.8%
도로변 51
28.2%
강, 바다 28
15.5%
농경지 20
 
11.0%
숲 14
 
7.7%
기타 3
 
1.7%
전선 2
 
1.1%

Length

2024-01-10T06:49:29.907381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:49:30.010928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물옆 63
30.1%
도로변 51
24.4%
강 28
13.4%
바다 28
13.4%
농경지 20
 
9.6%
숲 14
 
6.7%
기타 3
 
1.4%
전선 2
 
1.0%

발생원인
Categorical

Distinct26
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
전선/건물과의 충돌
31 
차량과의 충돌
30 
어미를 잃음(미아)
18 
- 차량과의 충돌
17 
- 어미를 잃음(미아)
12 
Other values (21)
73 

Length

Max length13
Median length12
Mean length9.0662983
Min length1

Unique

Unique10 ?
Unique (%)5.5%

Sample

1st row어미를 잃음(미아)
2nd row전선/건물과의 충돌
3rd row전선/건물과의 충돌
4th row전선/건물과의 충돌
5th row전선/건물과의 충돌

Common Values

ValueCountFrequency (%)
전선/건물과의 충돌 31
17.1%
차량과의 충돌 30
16.6%
어미를 잃음(미아) 18
9.9%
- 차량과의 충돌 17
9.4%
- 어미를 잃음(미아) 12
 
6.6%
- 전선/건물과의 충돌 12
 
6.6%
기생충 중감염 11
 
6.1%
농수로 고립 10
 
5.5%
알 수 없는 사고 8
 
4.4%
인공구조물 침입·고립 5
 
2.8%
Other values (16) 27
14.9%

Length

2024-01-10T06:49:30.120060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충돌 90
20.9%
49
11.4%
차량과의 47
10.9%
전선/건물과의 43
10.0%
어미를 30
 
7.0%
잃음(미아 30
 
7.0%
사고 12
 
2.8%
기생충 11
 
2.6%
중감염 11
 
2.6%
농수로 10
 
2.3%
Other values (23) 98
22.7%

발생원인 세부사항
Text

Distinct85
Distinct (%)47.2%
Missing1
Missing (%)0.6%
Memory size1.5 KiB
2024-01-10T06:49:30.381199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length31
Mean length10.538889
Min length1

Characters and Unicode

Total characters1897
Distinct characters177
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

Unique64 ?
Unique (%)35.6%

Sample

1st row어미를 잃음
2nd row전선/또는 건물과의 충돌 후 시간이 경과한 것으로 보임
3rd row추후 기재
4th row전선 충돌 추정
5th row전선 충돌 추정
ValueCountFrequency (%)
충돌 71
 
13.7%
차량과의 33
 
6.4%
추정 27
 
5.2%
어미를 25
 
4.8%
잃음(미아 19
 
3.7%
유리 15
 
2.9%
구조물 15
 
2.9%
차량충돌 13
 
2.5%
농수로 11
 
2.1%
없는 11
 
2.1%
Other values (139) 278
53.7%
2024-01-10T06:49:30.760328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
354
 
18.7%
충 112
 
5.9%
돌 94
 
5.0%
미 56
 
3.0%
차 51
 
2.7%
량 51
 
2.7%
의 50
 
2.6%
과 48
 
2.5%
고 39
 
2.1%
추 38
 
2.0%
Other values (167) 1004
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1450
76.4%
Space Separator 354
 
18.7%
Other Punctuation 35
 
1.8%
Close Punctuation 28
 
1.5%
Open Punctuation 28
 
1.5%
Lowercase Letter 1
 
0.1%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
충 112
 
7.7%
돌 94
 
6.5%
미 56
 
3.9%
차 51
 
3.5%
량 51
 
3.5%
의 50
 
3.4%
과 48
 
3.3%
고 39
 
2.7%
추 38
 
2.6%
아 35
 
2.4%
Other values (159) 876
60.4%
Other Punctuation
ValueCountFrequency (%)
/ 28
80.0%
, 6
 
17.1%
. 1
 
2.9%
Space Separator
ValueCountFrequency (%)
354
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Lowercase Letter
ValueCountFrequency (%)
t 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
L 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1450
76.4%
Common 445
 
23.5%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
충 112
 
7.7%
돌 94
 
6.5%
미 56
 
3.9%
차 51
 
3.5%
량 51
 
3.5%
의 50
 
3.4%
과 48
 
3.3%
고 39
 
2.7%
추 38
 
2.6%
아 35
 
2.4%
Other values (159) 876
60.4%
Common
ValueCountFrequency (%)
354
79.6%
/ 28
 
6.3%
) 28
 
6.3%
( 28
 
6.3%
, 6
 
1.3%
. 1
 
0.2%
Latin
ValueCountFrequency (%)
t 1
50.0%
L 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1450
76.4%
ASCII 447
 
23.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
354
79.2%
/ 28
 
6.3%
) 28
 
6.3%
( 28
 
6.3%
, 6
 
1.3%
. 1
 
0.2%
t 1
 
0.2%
L 1
 
0.2%
Hangul
ValueCountFrequency (%)
충 112
 
7.7%
돌 94
 
6.5%
미 56
 
3.9%
차 51
 
3.5%
량 51
 
3.5%
의 50
 
3.4%
과 48
 
3.3%
고 39
 
2.7%
추 38
 
2.6%
아 35
 
2.4%
Other values (159) 876
60.4%

TM구조위도
Text

MISSING 

Distinct116
Distinct (%)87.9%
Missing49
Missing (%)27.1%
Memory size1.5 KiB
2024-01-10T06:49:30.997854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1320
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

Unique107 ?
Unique (%)81.1%

Sample

1st row36 14 38.6
2nd row36 18 54.4
3rd row36 19 20.2
4th row36 19 37.5
5th row36 18 20.2
ValueCountFrequency (%)
36 132
33.3%
21 23
 
5.8%
20 21
 
5.3%
19 13
 
3.3%
18 12
 
3.0%
14 11
 
2.8%
22 9
 
2.3%
26 8
 
2.0%
23 8
 
2.0%
16 7
 
1.8%
Other values (114) 152
38.4%
2024-01-10T06:49:31.331813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
264
20.0%
3 196
14.8%
6 195
14.8%
. 132
10.0%
2 127
9.6%
1 120
9.1%
0 79
 
6.0%
4 61
 
4.6%
5 51
 
3.9%
8 37
 
2.8%
Other values (2) 58
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 924
70.0%
Space Separator 264
 
20.0%
Other Punctuation 132
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 196
21.2%
6 195
21.1%
2 127
13.7%
1 120
13.0%
0 79
8.5%
4 61
 
6.6%
5 51
 
5.5%
8 37
 
4.0%
7 29
 
3.1%
9 29
 
3.1%
Space Separator
ValueCountFrequency (%)
264
100.0%
Other Punctuation
ValueCountFrequency (%)
. 132
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1320
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
264
20.0%
3 196
14.8%
6 195
14.8%
. 132
10.0%
2 127
9.6%
1 120
9.1%
0 79
 
6.0%
4 61
 
4.6%
5 51
 
3.9%
8 37
 
2.8%
Other values (2) 58
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1320
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
264
20.0%
3 196
14.8%
6 195
14.8%
. 132
10.0%
2 127
9.6%
1 120
9.1%
0 79
 
6.0%
4 61
 
4.6%
5 51
 
3.9%
8 37
 
2.8%
Other values (2) 58
 
4.4%

TM구조경도
Text

MISSING 

Distinct116
Distinct (%)87.9%
Missing49
Missing (%)27.1%
Memory size1.5 KiB
2024-01-10T06:49:31.563598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters1452
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

Unique107 ?
Unique (%)81.1%

Sample

1st row126 34 59.1
2nd row126 30 43.5
3rd row126 31 35.0
4th row126 30 41.3
5th row126 30 58.0
ValueCountFrequency (%)
126 132
33.3%
35 28
 
7.1%
36 25
 
6.3%
31 16
 
4.0%
30 12
 
3.0%
32 11
 
2.8%
34 9
 
2.3%
40.3 6
 
1.5%
38 5
 
1.3%
33 5
 
1.3%
Other values (113) 147
37.1%
2024-01-10T06:49:31.882807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
264
18.2%
2 195
13.4%
1 193
13.3%
6 181
12.5%
3 176
12.1%
. 132
9.1%
5 72
 
5.0%
4 70
 
4.8%
0 65
 
4.5%
8 39
 
2.7%
Other values (2) 65
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1056
72.7%
Space Separator 264
 
18.2%
Other Punctuation 132
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 195
18.5%
1 193
18.3%
6 181
17.1%
3 176
16.7%
5 72
 
6.8%
4 70
 
6.6%
0 65
 
6.2%
8 39
 
3.7%
9 37
 
3.5%
7 28
 
2.7%
Space Separator
ValueCountFrequency (%)
264
100.0%
Other Punctuation
ValueCountFrequency (%)
. 132
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1452
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
264
18.2%
2 195
13.4%
1 193
13.3%
6 181
12.5%
3 176
12.1%
. 132
9.1%
5 72
 
5.0%
4 70
 
4.8%
0 65
 
4.5%
8 39
 
2.7%
Other values (2) 65
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1452
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
264
18.2%
2 195
13.4%
1 193
13.3%
6 181
12.5%
3 176
12.1%
. 132
9.1%
5 72
 
5.0%
4 70
 
4.8%
0 65
 
4.5%
8 39
 
2.7%
Other values (2) 65
 
4.5%

TM방생위도
Text

MISSING 

Distinct27
Distinct (%)93.1%
Missing152
Missing (%)84.0%
Memory size1.5 KiB
2024-01-10T06:49:32.022333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters290
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

Unique25 ?
Unique (%)86.2%

Sample

1st row36 39 23.1
2nd row36 40 59.7
3rd row36 41 54.9
4th row36 19 42.3
5th row36 39 36.6
ValueCountFrequency (%)
36 30
34.5%
39 6
 
6.9%
40 5
 
5.7%
14 3
 
3.4%
24.4 2
 
2.3%
23 2
 
2.3%
34.8 2
 
2.3%
21 2
 
2.3%
41 2
 
2.3%
19 2
 
2.3%
Other values (30) 31
35.6%
2024-01-10T06:49:32.242021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
58
20.0%
3 52
17.9%
6 36
12.4%
4 32
11.0%
. 29
10.0%
2 21
 
7.2%
1 19
 
6.6%
9 12
 
4.1%
0 11
 
3.8%
5 9
 
3.1%
Other values (2) 11
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 203
70.0%
Space Separator 58
 
20.0%
Other Punctuation 29
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 52
25.6%
6 36
17.7%
4 32
15.8%
2 21
10.3%
1 19
 
9.4%
9 12
 
5.9%
0 11
 
5.4%
5 9
 
4.4%
7 6
 
3.0%
8 5
 
2.5%
Space Separator
ValueCountFrequency (%)
58
100.0%
Other Punctuation
ValueCountFrequency (%)
. 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 290
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
58
20.0%
3 52
17.9%
6 36
12.4%
4 32
11.0%
. 29
10.0%
2 21
 
7.2%
1 19
 
6.6%
9 12
 
4.1%
0 11
 
3.8%
5 9
 
3.1%
Other values (2) 11
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 290
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
58
20.0%
3 52
17.9%
6 36
12.4%
4 32
11.0%
. 29
10.0%
2 21
 
7.2%
1 19
 
6.6%
9 12
 
4.1%
0 11
 
3.8%
5 9
 
3.1%
Other values (2) 11
 
3.8%

TM방생경도
Text

MISSING 

Distinct28
Distinct (%)96.6%
Missing152
Missing (%)84.0%
Memory size1.5 KiB
2024-01-10T06:49:32.386074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters319
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

Unique27 ?
Unique (%)93.1%

Sample

1st row126 27 04.3
2nd row126 49 13.3
3rd row126 27 05.3
4th row126 35 28.7
5th row126 48 45.0
ValueCountFrequency (%)
126 27
31.0%
31 5
 
5.7%
51 4
 
4.6%
48 4
 
4.6%
34 3
 
3.4%
16.5 2
 
2.3%
50.5 2
 
2.3%
36 2
 
2.3%
27 2
 
2.3%
127 2
 
2.3%
Other values (34) 34
39.1%
2024-01-10T06:49:32.614462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
58
18.2%
1 46
14.4%
2 39
12.2%
6 39
12.2%
. 29
9.1%
3 26
8.2%
4 23
 
7.2%
5 23
 
7.2%
7 14
 
4.4%
0 9
 
2.8%
Other values (2) 13
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 232
72.7%
Space Separator 58
 
18.2%
Other Punctuation 29
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 46
19.8%
2 39
16.8%
6 39
16.8%
3 26
11.2%
4 23
9.9%
5 23
9.9%
7 14
 
6.0%
0 9
 
3.9%
8 9
 
3.9%
9 4
 
1.7%
Space Separator
ValueCountFrequency (%)
58
100.0%
Other Punctuation
ValueCountFrequency (%)
. 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
58
18.2%
1 46
14.4%
2 39
12.2%
6 39
12.2%
. 29
9.1%
3 26
8.2%
4 23
 
7.2%
5 23
 
7.2%
7 14
 
4.4%
0 9
 
2.8%
Other values (2) 13
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
58
18.2%
1 46
14.4%
2 39
12.2%
6 39
12.2%
. 29
9.1%
3 26
8.2%
4 23
 
7.2%
5 23
 
7.2%
7 14
 
4.4%
0 9
 
2.8%
Other values (2) 13
 
4.1%

등록체중
Text

Distinct152
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-01-10T06:49:32.870441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.4033149
Min length1

Characters and Unicode

Total characters616
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

Unique138 ?
Unique (%)76.2%

Sample

1st row14
2nd row232
3rd row524
4th row408
5th row468
ValueCountFrequency (%)
0 12
 
6.6%
103 6
 
3.3%
14 3
 
1.7%
124 2
 
1.1%
94 2
 
1.1%
186 2
 
1.1%
490 2
 
1.1%
586 2
 
1.1%
692 2
 
1.1%
17,180 2
 
1.1%
Other values (142) 146
80.7%
2024-01-10T06:49:33.234178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 120
19.5%
1 97
15.7%
4 70
11.4%
2 65
10.6%
8 61
9.9%
3 48
 
7.8%
6 45
 
7.3%
5 40
 
6.5%
7 23
 
3.7%
9 22
 
3.6%
Other values (2) 25
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 591
95.9%
Other Punctuation 25
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 120
20.3%
1 97
16.4%
4 70
11.8%
2 65
11.0%
8 61
10.3%
3 48
 
8.1%
6 45
 
7.6%
5 40
 
6.8%
7 23
 
3.9%
9 22
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 20
80.0%
. 5
 
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 616
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 120
19.5%
1 97
15.7%
4 70
11.4%
2 65
10.6%
8 61
9.9%
3 48
 
7.8%
6 45
 
7.3%
5 40
 
6.5%
7 23
 
3.7%
9 22
 
3.6%
Other values (2) 25
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 616
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 120
19.5%
1 97
15.7%
4 70
11.4%
2 65
10.6%
8 61
9.9%
3 48
 
7.8%
6 45
 
7.3%
5 40
 
6.5%
7 23
 
3.7%
9 22
 
3.6%
Other values (2) 25
 
4.1%

현재체중
Text

Distinct155
Distinct (%)85.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-01-10T06:49:33.493278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.4143646
Min length1

Characters and Unicode

Total characters618
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

Unique142 ?
Unique (%)78.5%

Sample

1st row14
2nd row232
3rd row504
4th row444
5th row386
ValueCountFrequency (%)
0 13
 
7.2%
206 4
 
2.2%
17,180 2
 
1.1%
14 2
 
1.1%
112 2
 
1.1%
4600 2
 
1.1%
15100 2
 
1.1%
13 2
 
1.1%
20 2
 
1.1%
452 2
 
1.1%
Other values (145) 148
81.8%
2024-01-10T06:49:33.856761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 124
20.1%
1 89
14.4%
2 73
11.8%
6 64
10.4%
4 63
10.2%
8 49
 
7.9%
5 45
 
7.3%
3 39
 
6.3%
7 26
 
4.2%
9 21
 
3.4%
Other values (2) 25
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 593
96.0%
Other Punctuation 25
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 124
20.9%
1 89
15.0%
2 73
12.3%
6 64
10.8%
4 63
10.6%
8 49
 
8.3%
5 45
 
7.6%
3 39
 
6.6%
7 26
 
4.4%
9 21
 
3.5%
Other Punctuation
ValueCountFrequency (%)
, 19
76.0%
. 6
 
24.0%

Most occurring scripts

ValueCountFrequency (%)
Common 618
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 124
20.1%
1 89
14.4%
2 73
11.8%
6 64
10.4%
4 63
10.2%
8 49
 
7.9%
5 45
 
7.3%
3 39
 
6.3%
7 26
 
4.2%
9 21
 
3.4%
Other values (2) 25
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 618
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 124
20.1%
1 89
14.4%
2 73
11.8%
6 64
10.4%
4 63
10.2%
8 49
 
7.9%
5 45
 
7.3%
3 39
 
6.3%
7 26
 
4.2%
9 21
 
3.4%
Other values (2) 25
 
4.0%

임상적최종진단
Text

MISSING 

Distinct160
Distinct (%)89.4%
Missing2
Missing (%)1.1%
Memory size1.5 KiB
2024-01-10T06:49:34.129161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length29
Mean length15.312849
Min length2

Characters and Unicode

Total characters2741
Distinct characters257
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

Unique153 ?
Unique (%)85.5%

Sample

1st row기력 쇠약
2nd row좌측 견관절 탈구
3rd row충돌에 의한 좌측 상완골 개방골절
4th row충돌에 의한 우측 요척골 원위부 폐쇄골절
5th row기아 및 탈진
ValueCountFrequency (%)
의한 49
 
6.3%
및 41
 
5.3%
골절 34
 
4.4%
충돌에 32
 
4.1%
좌측 28
 
3.6%
우측 26
 
3.4%
미아 25
 
3.2%
뇌진탕 20
 
2.6%
개방골절 17
 
2.2%
탈진 14
 
1.8%
Other values (281) 489
63.1%
2024-01-10T06:49:34.505604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
602
 
22.0%
골 138
 
5.0%
절 90
 
3.3%
한 66
 
2.4%
측 65
 
2.4%
의 56
 
2.0%
충 56
 
2.0%
에 54
 
2.0%
상 51
 
1.9%
돌 46
 
1.7%
Other values (247) 1517
55.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1980
72.2%
Space Separator 602
 
22.0%
Other Punctuation 53
 
1.9%
Lowercase Letter 44
 
1.6%
Open Punctuation 16
 
0.6%
Close Punctuation 16
 
0.6%
Decimal Number 14
 
0.5%
Uppercase Letter 13
 
0.5%
Math Symbol 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
골 138
 
7.0%
절 90
 
4.5%
한 66
 
3.3%
측 65
 
3.3%
의 56
 
2.8%
충 56
 
2.8%
에 54
 
2.7%
상 51
 
2.6%
돌 46
 
2.3%
개 45
 
2.3%
Other values (215) 1313
66.3%
Lowercase Letter
ValueCountFrequency (%)
e 5
11.4%
n 5
11.4%
r 4
9.1%
o 4
9.1%
i 4
9.1%
t 4
9.1%
p 3
6.8%
u 3
6.8%
c 3
6.8%
a 3
6.8%
Other values (5) 6
13.6%
Decimal Number
ValueCountFrequency (%)
6 4
28.6%
2 3
21.4%
3 3
21.4%
4 2
14.3%
1 1
 
7.1%
5 1
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
L 9
69.2%
O 1
 
7.7%
D 1
 
7.7%
T 1
 
7.7%
A 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
, 42
79.2%
/ 11
 
20.8%
Space Separator
ValueCountFrequency (%)
602
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1980
72.2%
Common 704
 
25.7%
Latin 57
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
골 138
 
7.0%
절 90
 
4.5%
한 66
 
3.3%
측 65
 
3.3%
의 56
 
2.8%
충 56
 
2.8%
에 54
 
2.7%
상 51
 
2.6%
돌 46
 
2.3%
개 45
 
2.3%
Other values (215) 1313
66.3%
Latin
ValueCountFrequency (%)
L 9
15.8%
e 5
 
8.8%
n 5
 
8.8%
r 4
 
7.0%
o 4
 
7.0%
i 4
 
7.0%
t 4
 
7.0%
p 3
 
5.3%
u 3
 
5.3%
c 3
 
5.3%
Other values (10) 13
22.8%
Common
ValueCountFrequency (%)
602
85.5%
, 42
 
6.0%
( 16
 
2.3%
) 16
 
2.3%
/ 11
 
1.6%
6 4
 
0.6%
2 3
 
0.4%
~ 3
 
0.4%
3 3
 
0.4%
4 2
 
0.3%
Other values (2) 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1980
72.2%
ASCII 761
 
27.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
602
79.1%
, 42
 
5.5%
( 16
 
2.1%
) 16
 
2.1%
/ 11
 
1.4%
L 9
 
1.2%
e 5
 
0.7%
n 5
 
0.7%
r 4
 
0.5%
o 4
 
0.5%
Other values (22) 47
 
6.2%
Hangul
ValueCountFrequency (%)
골 138
 
7.0%
절 90
 
4.5%
한 66
 
3.3%
측 65
 
3.3%
의 56
 
2.8%
충 56
 
2.8%
에 54
 
2.7%
상 51
 
2.6%
돌 46
 
2.3%
개 45
 
2.3%
Other values (215) 1313
66.3%

Sample

접수번호동물국문명강목과천연기념물멸종위기등급야생동물보호협약구조일시구조결과일자구조결과이첩 방생 위치사체처리동물성별동물연령구조위도구조경도구조고도방생위도방생경도발견장소상세발견주소발견장소특징발생원인발생원인 세부사항TM구조위도TM구조경도TM방생위도TM방생경도등록체중현재체중임상적최종진단
02019-1266꿩조강(Aves)닭목꿩과해당없음해당없음해당없음2019-08-032019-08-05폐사<NA>기타UnknownNestling36.244056126.58308335<NA><NA>주소지 확실치 않음충청남도 보령시 웅천읍 두룡리 539-2숲어미를 잃음(미아)어미를 잃음36 14 38.6126 34 59.1<NA><NA>1414기력 쇠약
12019-1054괭이갈매기조강(Aves)도요목갈매기과해당없음해당없음해당없음2019-07-152019-07-15안락사<NA>기타UnknownJuvenile36.315111126.5120838<NA><NA>대천해수욕장 부근 건물 옆충청남도 보령시 신흑동 2284-4건물옆전선/건물과의 충돌전선/또는 건물과의 충돌 후 시간이 경과한 것으로 보임36 18 54.4126 30 43.5<NA><NA>232232좌측 견관절 탈구
22019-1125괭이갈매기조강(Aves)도요목갈매기과해당없음해당없음해당없음2019-07-232019-08-13안락사<NA>기타UnknownAdult36.322278126.52638931<NA><NA>대천해수욕장충청남도 보령시 신흑동 2107강, 바다전선/건물과의 충돌추후 기재36 19 20.2126 31 35.0<NA><NA>524504충돌에 의한 좌측 상완골 개방골절
32019-1141괭이갈매기조강(Aves)도요목갈매기과해당없음해당없음해당없음2019-07-252019-09-10방생충청남도 서산시 고북면 사기리 1109<NA>UnknownJuvenile36.327083126.511472036.657386126.459981(대천항중앙길 46) 유람선터미널 부근충청남도 보령시 신흑동 2240-12건물옆전선/건물과의 충돌전선 충돌 추정36 19 37.5126 30 41.336 39 23.1126 27 04.3408444충돌에 의한 우측 요척골 원위부 폐쇄골절
42019-1339괭이갈매기조강(Aves)도요목갈매기과해당없음해당없음해당없음2019-08-242019-09-01폐사<NA>기타UnknownJuvenile36.305611126.5161119<NA><NA>대천해수욕장충청남도 보령시 신흑동 2267-3강, 바다전선/건물과의 충돌전선 충돌 추정36 18 20.2126 30 58.0<NA><NA>468386기아 및 탈진
52019-1359괭이갈매기조강(Aves)도요목갈매기과해당없음해당없음해당없음2019-08-302019-09-02안락사<NA>기타UnknownUnknown36.311611126.5128338<NA><NA><NA>충청남도 보령시 신흑동 2107강, 바다전선/건물과의 충돌전선충돌 추정36 18 41.8126 30 46.2<NA><NA>530454충돌에 의한 우측 날개 신경 손상(추정) 및 흉근 피부 열상, 좌측 견갑골 골절
62019-0804멧비둘기조강(Aves)비둘기목비둘기과해당없음해당없음해당없음2019-06-182019-07-23방생충청남도 예산군 예산읍 주교리 488-7<NA>UnknownJuvenile36.342917126.589722336.682045126.820489보령 시외버스터미널 인근 택시승강장충청남도 보령시 궁촌동 347-1건물옆알 수 없는 사고알 수 없는 사고36 20 34.5126 35 23.036 40 59.7126 49 13.3144196충돌 추정
72019-0740가마우지조강(Aves)사다새목가마우지과해당없음해당없음해당없음2019-06-122019-09-10방생충청남도 서산시 인지면 산동리 939<NA>UnknownUnknown36.347444126.595222736.698632126.451546<NA>충청남도 보령시 대천동 260-3건물옆전선/건물과의 충돌전선 충돌 추정36 20 50.8126 35 42.836 41 54.9126 27 05.313141692좌측 경비골 폐쇄골절
82019-1228가마우지조강(Aves)사다새목가마우지과해당없음해당없음해당없음2019-07-302019-07-30안락사<NA>기타UnknownUnknown36.384389126.4920565<NA><NA>신보령화력사업소충청남도 보령시 주교면 송도길 201기타전선/건물과의 충돌전선충돌로 추정36 23 03.8126 29 31.4<NA><NA>11541154좌측 요척골 진구성 개방골절 후 부정유합
92019-0354까치조강(Aves)참새목까마귀과해당없음해당없음해당없음2019-05-052019-05-06DOA<NA>기타UnknownNestling36.346639126.6001399<NA><NA>(희망2길 96-12) 희망공원 내충청남도 보령시 동대동 1341건물옆어미를 잃음(미아)성장 과정에서 자연스럽게 나타난 장애에 의한 도태 (추정)36 20 47.9126 36 00.5<NA><NA>110110성장 과정에서 자연스럽게 나타난 장애에 의한 도태
접수번호동물국문명강목과천연기념물멸종위기등급야생동물보호협약구조일시구조결과일자구조결과이첩 방생 위치사체처리동물성별동물연령구조위도구조경도구조고도방생위도방생경도발견장소상세발견주소발견장소특징발생원인발생원인 세부사항TM구조위도TM구조경도TM방생위도TM방생경도등록체중현재체중임상적최종진단
1712022-1438고라니포유강(Mammalia)소목사슴과해당없음해당없음해당없음2022-06-282022-09-20방생충남 청양군 청양읍 군량리 산15-2<NA>Female0년0월0일36.21.236126.39.459206<NA><NA>주소지 인근 텃밭과 숲 경계부충남 보령시 성주면 먹방계곡길 107숲- 어미를 잃음(미아)어미를 잃음(미아)<NA><NA><NA><NA>2,1147,160단순 미아
1722022-1692고라니포유강(Mammalia)소목사슴과해당없음해당없음해당없음2022-07-202022-08-24폐사<NA>냉동(신냉동창고)(투입박스(일반))Male0년2월0일36.20.579126.40.486214<NA><NA>주소지 인근 하천변 풀숲충남 보령시 성주면 성주리 20-66도로변- 알 수 없는 사고알 수 없는 사고<NA><NA><NA><NA>4,1743,060외상성 기립불능(Ataxia)
1732022-1708고라니포유강(Mammalia)소목사슴과해당없음해당없음해당없음2022-07-212022-10-26방생충남 예산군 예산읍 대학로 54<NA>Female0년3월0일36.16.101126.36.57764<NA><NA>밭(상세주소미상)충남 보령시 웅천읍 부당길 63-43농경지- 어미를 잃음(미아)어미를 잃음(미아)<NA><NA><NA><NA>1,2904,220미아, 탈진
1742022-1734고라니포유강(Mammalia)소목사슴과해당없음해당없음해당없음2022-07-222022-07-22폐사체<NA>냉동(구냉동창고)(성체고라니, 개선충너구리)Male0년0월0일36.18.203126.36.50174<NA><NA>도로 2차선충남 보령시 남포면 옥동리 69도로변- 차량과의 충돌차량과의 충돌<NA><NA><NA><NA>12,32012,320차량 충돌에 의한 천추, 좌측 골반, 좌우측 경비골 폐쇄골절, 우측 발목 개방 골절 및 뒷꿈치뼈 소실
1752022-1735고라니포유강(Mammalia)소목사슴과해당없음해당없음해당없음2022-07-222022-07-22안락사<NA><NA>Female0년0월0일36.23.576126.41.27889<NA><NA>도로 옆 농경지충남 보령시 청라면 소양리 521-4농경지- 차량과의 충돌차량과의 충돌<NA><NA><NA><NA>17,18017,180차량충돌에 의한 우측 발목 개방골절 및 오염, 우측 고관절 탈구, 좌측 골반 골절
1762022-2235고라니포유강(Mammalia)소목사슴과해당없음해당없음해당없음2022-10-282022-10-28DOA<NA>냉동(구냉동창고)(성체고라니, 개선충너구리)Male0년0월0일36.26.284126.35.16110<NA><NA>주소지 주택 출입구 인근 인도상충남 보령시 청소면 청소큰길 117도로변- 차량과의 충돌차량과의 충돌<NA><NA><NA><NA>20,44020,440차량 충돌에 의한 척추 및 우측 경비골 골절, 좌측 고관절 탈구
1772022-2325고라니포유강(Mammalia)소목사슴과해당없음해당없음해당없음2022-11-162022-11-16안락사<NA><NA>Male0년0월0일36.22.384126.37.55060<NA><NA>주소지 인근 청양방향 도로변충남 보령시 청라면 대청로 488도로변- 차량과의 충돌차량과의 충돌<NA><NA><NA><NA>15,84015,840<NA>
1782022-2164너구리포유강(Mammalia)식육목개과해당없음해당없음해당없음2022-10-132022-10-13폐사체<NA>냉동(신냉동창고)(투입박스(일반))Female0년6월0일36.26.504126.33.4920<NA><NA>도로변충남 보령시 오천면 교성리 1265-2건물옆- 차량과의 충돌차량과의 충돌/<NA><NA><NA><NA>3,4003,400차량충돌에 의한 골반 골절
1792022-1547오소리포유강(Mammalia)식육목족제비과해당없음해당없음해당없음2022-07-062022-10-07방생충남 공주시 계룡면 구왕리 산 31-1<NA>Male0년2월0일36.21.325126.36.00323<NA><NA><NA>충남 보령시 죽정동 658-29건물옆- 어미를 잃음(미아)어미를 잃음(미아)<NA><NA><NA><NA>1,7147,420기력이 조금 떨어져보이는 미아 개체
1802022-1844청설모포유강(Mammalia)쥐목청서과해당없음해당없음해당없음2022-08-072022-08-07DOA<NA><NA>Unknown0년0월0일36.23.038126.29.3145<NA><NA>화력발전소 내부충남 보령시 주교면 송도길 201도로변- 기아 및 탈진기아 및 탈진<NA><NA><NA><NA>288288기아 탈진 추정