Overview

Dataset statistics

Number of variables4
Number of observations243
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)0.4%
Total size in memory8.0 KiB
Average record size in memory33.5 B

Variable types

Categorical2
Text2

Dataset

Description서울특별시 중랑구 관내의 흡연시설 현황 제공합니다. 중랑구 흡연구역의 위치를 제공합니다. 실내흡연시설이아닌 외부 흡연가능구역의 위치를 제공합니다. 참고해주십시오.감사합니다.
Author서울특별시 중랑구
URLhttps://www.data.go.kr/data/15040636/fileData.do

Alerts

Dataset has 1 (0.4%) duplicate rowsDuplicates
업종 is highly overall correlated with 흡연실 개소수High correlation
흡연실 개소수 is highly overall correlated with 업종High correlation
업종 is highly imbalanced (50.8%)Imbalance
흡연실 개소수 is highly imbalanced (91.5%)Imbalance

Reproduction

Analysis started2023-12-12 21:03:42.351108
Analysis finished2023-12-12 21:03:42.780553
Duration0.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct7
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
게임업소
119 
체육시설업
110 
복합건축물
 
5
의료기관
 
4
공공청사
 
2
Other values (2)
 
3

Length

Max length5
Median length4
Mean length4.4691358
Min length3

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row공공청사
2nd row공공청사
3rd row의료기관
4th row의료기관
5th row의료기관

Common Values

ValueCountFrequency (%)
게임업소 119
49.0%
체육시설업 110
45.3%
복합건축물 5
 
2.1%
의료기관 4
 
1.6%
공공청사 2
 
0.8%
대형점포 2
 
0.8%
대학교 1
 
0.4%

Length

2023-12-13T06:03:42.856373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:03:42.982483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
게임업소 119
49.0%
체육시설업 110
45.3%
복합건축물 5
 
2.1%
의료기관 4
 
1.6%
공공청사 2
 
0.8%
대형점포 2
 
0.8%
대학교 1
 
0.4%

시설명(업소)
Text

Distinct237
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-13T06:03:43.263469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length19
Mean length6.6625514
Min length2

Characters and Unicode

Total characters1619
Distinct characters299
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique232 ?
Unique (%)95.5%

Sample

1st row지방자치단체 청사
2nd row면목5동
3rd row서울의료원
4th row녹색병원
5th row서울정형외과
ValueCountFrequency (%)
당구장 22
 
6.0%
pc방 11
 
3.0%
휘트니스 9
 
2.5%
pc 9
 
2.5%
스크린골프 7
 
1.9%
당구클럽 6
 
1.6%
골프스쿨 3
 
0.8%
cafe 3
 
0.8%
맥스피드pc방 3
 
0.8%
망우점 2
 
0.5%
Other values (270) 289
79.4%
2023-12-13T06:03:43.714006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
121
 
7.5%
C 112
 
6.9%
P 110
 
6.8%
스 86
 
5.3%
방 56
 
3.5%
구 37
 
2.3%
당 37
 
2.3%
이 32
 
2.0%
장 32
 
2.0%
프 30
 
1.9%
Other values (289) 966
59.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1094
67.6%
Uppercase Letter 331
 
20.4%
Space Separator 121
 
7.5%
Lowercase Letter 39
 
2.4%
Open Punctuation 11
 
0.7%
Close Punctuation 11
 
0.7%
Decimal Number 7
 
0.4%
Other Punctuation 5
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 86
 
7.9%
방 56
 
5.1%
구 37
 
3.4%
당 37
 
3.4%
이 32
 
2.9%
장 32
 
2.9%
프 30
 
2.7%
골 27
 
2.5%
아 19
 
1.7%
트 18
 
1.6%
Other values (236) 720
65.8%
Uppercase Letter
ValueCountFrequency (%)
C 112
33.8%
P 110
33.2%
A 19
 
5.7%
O 10
 
3.0%
E 8
 
2.4%
M 7
 
2.1%
G 7
 
2.1%
N 7
 
2.1%
T 6
 
1.8%
Y 5
 
1.5%
Other values (15) 40
 
12.1%
Lowercase Letter
ValueCountFrequency (%)
e 6
15.4%
c 4
10.3%
a 4
10.3%
l 3
 
7.7%
f 3
 
7.7%
i 3
 
7.7%
n 2
 
5.1%
p 2
 
5.1%
o 2
 
5.1%
u 2
 
5.1%
Other values (7) 8
20.5%
Decimal Number
ValueCountFrequency (%)
7 2
28.6%
1 1
14.3%
2 1
14.3%
4 1
14.3%
9 1
14.3%
5 1
14.3%
Other Punctuation
ValueCountFrequency (%)
& 3
60.0%
· 2
40.0%
Space Separator
ValueCountFrequency (%)
121
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1094
67.6%
Latin 370
 
22.9%
Common 155
 
9.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 86
 
7.9%
방 56
 
5.1%
구 37
 
3.4%
당 37
 
3.4%
이 32
 
2.9%
장 32
 
2.9%
프 30
 
2.7%
골 27
 
2.5%
아 19
 
1.7%
트 18
 
1.6%
Other values (236) 720
65.8%
Latin
ValueCountFrequency (%)
C 112
30.3%
P 110
29.7%
A 19
 
5.1%
O 10
 
2.7%
E 8
 
2.2%
M 7
 
1.9%
G 7
 
1.9%
N 7
 
1.9%
e 6
 
1.6%
T 6
 
1.6%
Other values (32) 78
21.1%
Common
ValueCountFrequency (%)
121
78.1%
( 11
 
7.1%
) 11
 
7.1%
& 3
 
1.9%
· 2
 
1.3%
7 2
 
1.3%
1 1
 
0.6%
2 1
 
0.6%
4 1
 
0.6%
9 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1094
67.6%
ASCII 523
32.3%
None 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
121
23.1%
C 112
21.4%
P 110
21.0%
A 19
 
3.6%
( 11
 
2.1%
) 11
 
2.1%
O 10
 
1.9%
E 8
 
1.5%
M 7
 
1.3%
G 7
 
1.3%
Other values (42) 107
20.5%
Hangul
ValueCountFrequency (%)
스 86
 
7.9%
방 56
 
5.1%
구 37
 
3.4%
당 37
 
3.4%
이 32
 
2.9%
장 32
 
2.9%
프 30
 
2.7%
골 27
 
2.5%
아 19
 
1.7%
트 18
 
1.6%
Other values (236) 720
65.8%
None
ValueCountFrequency (%)
· 2
100.0%

주소
Text

Distinct232
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-13T06:03:43.995595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length39
Mean length26.962963
Min length17

Characters and Unicode

Total characters6552
Distinct characters150
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

Unique221 ?
Unique (%)90.9%

Sample

1st row서울특별시 중랑구 봉화산로 179(신내동)
2nd row서울특별시 중랑구 동일로 619(면목동)
3rd row서울특별시 중랑구 신내로 156
4th row서울특별시 중랑구 사가정로49길 53
5th row서울특별시 중랑구 망우로 418
ValueCountFrequency (%)
서울특별시 243
19.8%
중랑구 243
19.8%
면목동 84
 
6.8%
상봉동 39
 
3.2%
망우동 32
 
2.6%
신내동 26
 
2.1%
묵동 22
 
1.8%
중화동 22
 
1.8%
2층 18
 
1.5%
망우로 17
 
1.4%
Other values (327) 482
39.3%
2023-12-13T06:03:44.485711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1329
20.3%
중 279
 
4.3%
동 257
 
3.9%
랑 252
 
3.8%
시 247
 
3.8%
울 244
 
3.7%
구 243
 
3.7%
서 243
 
3.7%
별 243
 
3.7%
특 243
 
3.7%
Other values (140) 2972
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3774
57.6%
Space Separator 1329
 
20.3%
Decimal Number 1060
 
16.2%
Close Punctuation 115
 
1.8%
Open Punctuation 115
 
1.8%
Dash Punctuation 111
 
1.7%
Other Punctuation 42
 
0.6%
Uppercase Letter 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 279
 
7.4%
동 257
 
6.8%
랑 252
 
6.7%
시 247
 
6.5%
울 244
 
6.5%
구 243
 
6.4%
서 243
 
6.4%
별 243
 
6.4%
특 243
 
6.4%
지 170
 
4.5%
Other values (122) 1353
35.9%
Decimal Number
ValueCountFrequency (%)
1 236
22.3%
2 132
12.5%
3 130
12.3%
4 111
10.5%
7 81
 
7.6%
6 80
 
7.5%
5 76
 
7.2%
0 73
 
6.9%
8 71
 
6.7%
9 70
 
6.6%
Uppercase Letter
ValueCountFrequency (%)
S 3
50.0%
B 2
33.3%
M 1
 
16.7%
Space Separator
ValueCountFrequency (%)
1329
100.0%
Close Punctuation
ValueCountFrequency (%)
) 115
100.0%
Open Punctuation
ValueCountFrequency (%)
( 115
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 111
100.0%
Other Punctuation
ValueCountFrequency (%)
, 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3774
57.6%
Common 2772
42.3%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 279
 
7.4%
동 257
 
6.8%
랑 252
 
6.7%
시 247
 
6.5%
울 244
 
6.5%
구 243
 
6.4%
서 243
 
6.4%
별 243
 
6.4%
특 243
 
6.4%
지 170
 
4.5%
Other values (122) 1353
35.9%
Common
ValueCountFrequency (%)
1329
47.9%
1 236
 
8.5%
2 132
 
4.8%
3 130
 
4.7%
) 115
 
4.1%
( 115
 
4.1%
- 111
 
4.0%
4 111
 
4.0%
7 81
 
2.9%
6 80
 
2.9%
Other values (5) 332
 
12.0%
Latin
ValueCountFrequency (%)
S 3
50.0%
B 2
33.3%
M 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3774
57.6%
ASCII 2778
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1329
47.8%
1 236
 
8.5%
2 132
 
4.8%
3 130
 
4.7%
) 115
 
4.1%
( 115
 
4.1%
- 111
 
4.0%
4 111
 
4.0%
7 81
 
2.9%
6 80
 
2.9%
Other values (8) 338
 
12.2%
Hangul
ValueCountFrequency (%)
중 279
 
7.4%
동 257
 
6.8%
랑 252
 
6.7%
시 247
 
6.5%
울 244
 
6.5%
구 243
 
6.4%
서 243
 
6.4%
별 243
 
6.4%
특 243
 
6.4%
지 170
 
4.5%
Other values (122) 1353
35.9%

흡연실 개소수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
1
239 
2
 
3
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row2
2nd row1
3rd row1
4th row2
5th row1

Common Values

ValueCountFrequency (%)
1 239
98.4%
2 3
 
1.2%
4 1
 
0.4%

Length

2023-12-13T06:03:44.622076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:03:44.725218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 239
98.4%
2 3
 
1.2%
4 1
 
0.4%

Correlations

2023-12-13T06:03:44.808845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종흡연실 개소수
업종1.0000.835
흡연실 개소수0.8351.000
2023-12-13T06:03:44.913442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종흡연실 개소수
업종1.0000.797
흡연실 개소수0.7971.000
2023-12-13T06:03:44.992429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종흡연실 개소수
업종1.0000.797
흡연실 개소수0.7971.000

Missing values

2023-12-13T06:03:42.642221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:03:42.743014image/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

업종시설명(업소)주소흡연실 개소수
0공공청사지방자치단체 청사서울특별시 중랑구 봉화산로 179(신내동)2
1공공청사면목5동서울특별시 중랑구 동일로 619(면목동)1
2의료기관서울의료원서울특별시 중랑구 신내로 1561
3의료기관녹색병원서울특별시 중랑구 사가정로49길 532
4의료기관서울정형외과서울특별시 중랑구 망우로 4181
5의료기관위너스병원서울특별시 중랑구 망우로 4031
6복합건축물서울시체육회서울특별시 중랑구 망우로 182(상봉동)1
7복합건축물한국전력서울특별시 중랑구 동일로 8621
8복합건축물서울우유서울특별시 중랑구 중랑천로 712
9복합건축물삼부빌딩서울특별시 중랑구 망우로 4181
업종시설명(업소)주소흡연실 개소수
233체육시설업B1 당구클럽서울특별시 중랑구 봉화산로56길 77 (신내동)1
234체육시설업당돌이 당구장서울특별시 중랑구 용마산로 440 (면목동)1
235체육시설업한큐당구장서울특별시 중랑구 면목로37길 5 (면목동, 중하빌딩)1
236체육시설업FUll 당구장서울특별시 중랑구 겸재로 264 (면목동, (주)그린고속관광)1
237체육시설업캐롬스팟서울특별시 중랑구 용마산로 493, 동양빌딩 지층 1호 (망우동)1
238체육시설업빌킬서울특별시 중랑구 면목로 289, 4층 (면목동)1
239체육시설업ICE PLANET(아이스 플래닛)서울특별시 중랑구 상봉중앙로 45 (상봉동)1
240체육시설업로얄스포츠센타서울특별시 중랑구 망우로 247 (중화동)1
241체육시설업중곡 스포렉스서울특별시 중랑구 면목로23길 20 (면목동)1
242체육시설업면일체육문화센터서울특별시 중랑구 용마산로100길 13, 면일체육문화센터 (망우동)1

Duplicate rows

Most frequently occurring

업종시설명(업소)주소흡연실 개소수# duplicates
0체육시설업휘트니스 놀이터서울특별시 중랑구 숙선옹주로 6-9 (묵동, 묵동자이아파트)12