Overview

Dataset statistics

Number of variables3
Number of observations71
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory25.9 B

Variable types

Text3

Dataset

Description서울특별시 강남구 쓰레기상습무단투기지역현황(연번, 주소, 상세위치)에 대한 정보를 제공합니다. 해당지역은 경험적으로 자주 단속하는 지역이며 관리데이터가 아님을 안내드립니다. 기타 자세한 사항은 서울특별시 강남구 자원순환과(02-3423-5999)로 주시면 자세히 안내해 드리도록 하겠습니다.
URLhttps://www.data.go.kr/data/15114860/fileData.do

Alerts

연번 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:03:55.954964
Analysis finished2023-12-12 14:03:56.278632
Duration0.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Text

UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size700.0 B
2023-12-12T23:03:56.524236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.8732394
Min length5

Characters and Unicode

Total characters417
Distinct characters35
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)100.0%

Sample

1st row신사동-1
2nd row신사동-2
3rd row신사동-3
4th row신사동-4
5th row신사동-5
ValueCountFrequency (%)
신사동-1 1
 
1.4%
도곡2동-1 1
 
1.4%
역삼2동-2 1
 
1.4%
역삼2동-1 1
 
1.4%
역삼1동-17 1
 
1.4%
역삼1동-16 1
 
1.4%
역삼1동-15 1
 
1.4%
역삼1동-14 1
 
1.4%
역삼1동-12 1
 
1.4%
역삼1동-4 1
 
1.4%
Other values (61) 61
85.9%
2023-12-12T23:03:56.935256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 71
17.0%
- 71
17.0%
1 59
14.1%
2 33
 
7.9%
삼 22
 
5.3%
역 19
 
4.6%
3 14
 
3.4%
곡 10
 
2.4%
4 9
 
2.2%
대 8
 
1.9%
Other values (25) 101
24.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 216
51.8%
Decimal Number 130
31.2%
Dash Punctuation 71
 
17.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 71
32.9%
삼 22
 
10.2%
역 19
 
8.8%
곡 10
 
4.6%
대 8
 
3.7%
치 8
 
3.7%
개 7
 
3.2%
도 7
 
3.2%
사 7
 
3.2%
신 7
 
3.2%
Other values (14) 50
23.1%
Decimal Number
ValueCountFrequency (%)
1 59
45.4%
2 33
25.4%
3 14
 
10.8%
4 9
 
6.9%
5 5
 
3.8%
6 4
 
3.1%
7 3
 
2.3%
8 1
 
0.8%
9 1
 
0.8%
0 1
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 71
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 216
51.8%
Common 201
48.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 71
32.9%
삼 22
 
10.2%
역 19
 
8.8%
곡 10
 
4.6%
대 8
 
3.7%
치 8
 
3.7%
개 7
 
3.2%
도 7
 
3.2%
사 7
 
3.2%
신 7
 
3.2%
Other values (14) 50
23.1%
Common
ValueCountFrequency (%)
- 71
35.3%
1 59
29.4%
2 33
16.4%
3 14
 
7.0%
4 9
 
4.5%
5 5
 
2.5%
6 4
 
2.0%
7 3
 
1.5%
8 1
 
0.5%
9 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 216
51.8%
ASCII 201
48.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 71
32.9%
삼 22
 
10.2%
역 19
 
8.8%
곡 10
 
4.6%
대 8
 
3.7%
치 8
 
3.7%
개 7
 
3.2%
도 7
 
3.2%
사 7
 
3.2%
신 7
 
3.2%
Other values (14) 50
23.1%
ASCII
ValueCountFrequency (%)
- 71
35.3%
1 59
29.4%
2 33
16.4%
3 14
 
7.0%
4 9
 
4.5%
5 5
 
2.5%
6 4
 
2.0%
7 3
 
1.5%
8 1
 
0.5%
9 1
 
0.5%

주소
Text

UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size700.0 B
2023-12-12T23:03:57.165918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length19.605634
Min length16

Characters and Unicode

Total characters1392
Distinct characters71
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)100.0%

Sample

1st row서울특별시 강남구 논현로159길 25
2nd row서울특별시 강남구 논현로159길 49
3rd row서울특별시 강남구 도산대로17길 22
4th row서울특별시 강남구 강남대로152길 69
5th row서울특별시 강남구 압구정로2길 15
ValueCountFrequency (%)
서울특별시 71
26.5%
강남구 71
26.5%
25 3
 
1.1%
삼성로 3
 
1.1%
15 2
 
0.7%
34 2
 
0.7%
논현로38길 2
 
0.7%
영동대로 2
 
0.7%
12 2
 
0.7%
35 2
 
0.7%
Other values (107) 108
40.3%
2023-12-12T23:03:57.529948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
203
 
14.6%
남 81
 
5.8%
강 78
 
5.6%
구 74
 
5.3%
서 72
 
5.2%
울 71
 
5.1%
특 71
 
5.1%
별 71
 
5.1%
시 71
 
5.1%
로 64
 
4.6%
Other values (61) 536
38.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 885
63.6%
Decimal Number 287
 
20.6%
Space Separator 203
 
14.6%
Dash Punctuation 11
 
0.8%
Open Punctuation 3
 
0.2%
Close Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 81
9.2%
강 78
8.8%
구 74
8.4%
서 72
8.1%
울 71
8.0%
특 71
8.0%
별 71
8.0%
시 71
8.0%
로 64
 
7.2%
길 56
 
6.3%
Other values (47) 176
19.9%
Decimal Number
ValueCountFrequency (%)
1 55
19.2%
5 37
12.9%
2 34
11.8%
6 29
10.1%
3 29
10.1%
9 26
9.1%
4 22
 
7.7%
7 21
 
7.3%
8 18
 
6.3%
0 16
 
5.6%
Space Separator
ValueCountFrequency (%)
203
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 885
63.6%
Common 507
36.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 81
9.2%
강 78
8.8%
구 74
8.4%
서 72
8.1%
울 71
8.0%
특 71
8.0%
별 71
8.0%
시 71
8.0%
로 64
 
7.2%
길 56
 
6.3%
Other values (47) 176
19.9%
Common
ValueCountFrequency (%)
203
40.0%
1 55
 
10.8%
5 37
 
7.3%
2 34
 
6.7%
6 29
 
5.7%
3 29
 
5.7%
9 26
 
5.1%
4 22
 
4.3%
7 21
 
4.1%
8 18
 
3.6%
Other values (4) 33
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 885
63.6%
ASCII 507
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
203
40.0%
1 55
 
10.8%
5 37
 
7.3%
2 34
 
6.7%
6 29
 
5.7%
3 29
 
5.7%
9 26
 
5.1%
4 22
 
4.3%
7 21
 
4.1%
8 18
 
3.6%
Other values (4) 33
 
6.5%
Hangul
ValueCountFrequency (%)
남 81
9.2%
강 78
8.8%
구 74
8.4%
서 72
8.1%
울 71
8.0%
특 71
8.0%
별 71
8.0%
시 71
8.0%
로 64
 
7.2%
길 56
 
6.3%
Other values (47) 176
19.9%

상세위치
Text

Distinct36
Distinct (%)50.7%
Missing0
Missing (%)0.0%
Memory size700.0 B
2023-12-12T23:03:57.786354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length6.3098592
Min length2

Characters and Unicode

Total characters448
Distinct characters84
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)39.4%

Sample

1st row 건물 앞 전신주 옆
2nd row 건물 앞
3rd row 건물 왼쪽 전신주 옆
4th row건물 좌측 주차장 자리
5th row전신주와 의류수거함 사이
ValueCountFrequency (%)
앞 26
16.0%
옆 23
14.1%
전신주 22
13.5%
건물 11
 
6.7%
주차장 8
 
4.9%
공원 7
 
4.3%
부근 6
 
3.7%
담벼락 5
 
3.1%
화단 4
 
2.5%
공터 3
 
1.8%
Other values (36) 48
29.4%
2023-12-12T23:03:58.267632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
98
21.9%
주 35
 
7.8%
앞 26
 
5.8%
전 24
 
5.4%
옆 24
 
5.4%
신 23
 
5.1%
장 12
 
2.7%
공 11
 
2.5%
건 11
 
2.5%
물 11
 
2.5%
Other values (74) 173
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 349
77.9%
Space Separator 98
 
21.9%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 35
 
10.0%
앞 26
 
7.4%
전 24
 
6.9%
옆 24
 
6.9%
신 23
 
6.6%
장 12
 
3.4%
공 11
 
3.2%
건 11
 
3.2%
물 11
 
3.2%
근 9
 
2.6%
Other values (72) 163
46.7%
Space Separator
ValueCountFrequency (%)
98
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 349
77.9%
Common 99
 
22.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 35
 
10.0%
앞 26
 
7.4%
전 24
 
6.9%
옆 24
 
6.9%
신 23
 
6.6%
장 12
 
3.4%
공 11
 
3.2%
건 11
 
3.2%
물 11
 
3.2%
근 9
 
2.6%
Other values (72) 163
46.7%
Common
ValueCountFrequency (%)
98
99.0%
, 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 349
77.9%
ASCII 99
 
22.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
98
99.0%
, 1
 
1.0%
Hangul
ValueCountFrequency (%)
주 35
 
10.0%
앞 26
 
7.4%
전 24
 
6.9%
옆 24
 
6.9%
신 23
 
6.6%
장 12
 
3.4%
공 11
 
3.2%
건 11
 
3.2%
물 11
 
3.2%
근 9
 
2.6%
Other values (72) 163
46.7%

Correlations

2023-12-12T23:03:58.427902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번주소상세위치
연번1.0001.0001.000
주소1.0001.0001.000
상세위치1.0001.0001.000

Missing values

2023-12-12T23:03:56.174529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:03:56.251312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

연번주소상세위치
0신사동-1서울특별시 강남구 논현로159길 25건물 앞 전신주 옆
1신사동-2서울특별시 강남구 논현로159길 49건물 앞
2신사동-3서울특별시 강남구 도산대로17길 22건물 왼쪽 전신주 옆
3신사동-4서울특별시 강남구 강남대로152길 69건물 좌측 주차장 자리
4신사동-5서울특별시 강남구 압구정로2길 15전신주와 의류수거함 사이
5신사동-6서울특별시 강남구 강남대로162길 27건물 옆쪽 화단주변
6신사동-7서울특별시 강남구 가로수길 85빈집공가, 건물 주차장 내
7논현1동-1서울특별시 강남구 논현동162-11(논현까치공원 앞)공원 앞
8논현1동-2서울특별시 강남구 논현동150-5(논현개나리공원)공원 앞
9논현1동-3서울특별시 강남구 논현동173-18(논현목련공원)공원 앞
연번주소상세위치
61개포2동-2서울특별시 강남구 선릉로18길 12전신주 옆
62개포3동-1서울특별시 강남구 일원동 716-2주차장 부근
63개포3동-2서울특별시 강남구 광평로20길 63주차장 부근
64개포3동-3서울특별시 강남구 수서동 595도서관 옆 공터
65개포4동-1서울특별시 강남구 논현로8길69전신주 옆
66일원1동-1서울특별시 강남구 양재대로 55길 12아파트 입구
67수서동-1서울특별시 강남구 광평로 280건물 뒤편
68세곡동-1서울특별시 강남구 세곡동158-2텃밭 근처
69세곡동-2서울특별시 강남구 자곡동344-7충전소 옆
70세곡동-3서울특별시 강남구 헌릉로571길 60-1공원 앞