Overview

Dataset statistics

Number of variables17
Number of observations10000
Missing cells28217
Missing cells (%)16.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 MiB
Average record size in memory141.0 B

Variable types

Text5
Categorical6
Numeric3
DateTime2
Unsupported1

Dataset

Description금연구역명,금연구역범위상세,시도명,시군구명,금연구역구분,금연구역지정근거명,금연구역면적,위반과태료,위반신고전화번호,소재지도로명주소,소재지지번주소,관리기관명,위도,경도,데이터기준일자,제공기관코드,작업일시
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-20339/S/1/datasetView.do

Alerts

시도명 has constant value ""Constant
시군구명 is highly overall correlated with 위도 and 5 other fieldsHigh correlation
금연구역지정근거명 is highly overall correlated with 위도 and 5 other fieldsHigh correlation
위반과태료 is highly overall correlated with 시군구명 and 3 other fieldsHigh correlation
위반신고전화번호 is highly overall correlated with 위도 and 5 other fieldsHigh correlation
관리기관명 is highly overall correlated with 위도 and 5 other fieldsHigh correlation
금연구역면적 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 금연구역면적 and 4 other fieldsHigh correlation
경도 is highly overall correlated with 금연구역면적 and 4 other fieldsHigh correlation
시군구명 is highly imbalanced (54.5%)Imbalance
금연구역지정근거명 is highly imbalanced (68.4%)Imbalance
위반과태료 is highly imbalanced (89.3%)Imbalance
위반신고전화번호 is highly imbalanced (57.0%)Imbalance
관리기관명 is highly imbalanced (54.5%)Imbalance
금연구역면적 has 9652 (96.5%) missing valuesMissing
소재지도로명주소 has 210 (2.1%) missing valuesMissing
소재지지번주소 has 8355 (83.5%) missing valuesMissing
제공기관코드 has 10000 (100.0%) missing valuesMissing
제공기관코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-20 23:05:51.973839
Analysis finished2024-04-20 23:05:56.667326
Duration4.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

금연구역명
Text

Distinct9728
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size78.3 KiB
2024-04-21T08:05:56.852173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length37
Mean length8.425
Min length1

Characters and Unicode

Total characters84250
Distinct characters1101
Distinct categories12 ?
Distinct scripts6 ?
Distinct blocks9 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9601 ?
Unique (%)96.0%

Sample

1st row모정한의원
2nd row풍림아이원 108동 놀이터
3rd row대치상상학원
4th row대치써미트영어학원
5th row대치써미트영어학원제2관(고등관)학원
ValueCountFrequency (%)
놀이터 98
 
0.8%
구립 86
 
0.7%
앞 85
 
0.7%
근린생활시설 77
 
0.6%
어린이놀이터 46
 
0.4%
상가 42
 
0.3%
어린이집 35
 
0.3%
통학로 30
 
0.2%
세븐일레븐 27
 
0.2%
마포 27
 
0.2%
Other values (10791) 12501
95.8%
2024-04-21T08:05:57.259043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3060
 
3.6%
이 2448
 
2.9%
원 1459
 
1.7%
( 1347
 
1.6%
) 1346
 
1.6%
어 1333
 
1.6%
스 1327
 
1.6%
린 1298
 
1.5%
아 1142
 
1.4%
1 1133
 
1.3%
Other values (1091) 68357
81.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67957
80.7%
Decimal Number 3965
 
4.7%
Uppercase Letter 3251
 
3.9%
Space Separator 3060
 
3.6%
Lowercase Letter 2247
 
2.7%
Open Punctuation 1352
 
1.6%
Close Punctuation 1351
 
1.6%
Other Punctuation 957
 
1.1%
Dash Punctuation 75
 
0.1%
Other Symbol 24
 
< 0.1%
Other values (2) 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 2448
 
3.6%
원 1459
 
2.1%
어 1333
 
2.0%
스 1327
 
2.0%
린 1298
 
1.9%
아 1142
 
1.7%
학 1120
 
1.6%
동 1023
 
1.5%
교 1003
 
1.5%
점 928
 
1.4%
Other values (1009) 54876
80.8%
Uppercase Letter
ValueCountFrequency (%)
I 383
 
11.8%
D 380
 
11.7%
C 265
 
8.2%
S 223
 
6.9%
A 194
 
6.0%
E 183
 
5.6%
M 161
 
5.0%
T 160
 
4.9%
O 147
 
4.5%
P 140
 
4.3%
Other values (16) 1015
31.2%
Lowercase Letter
ValueCountFrequency (%)
e 304
13.5%
a 266
11.8%
o 175
 
7.8%
i 156
 
6.9%
n 149
 
6.6%
r 126
 
5.6%
m 119
 
5.3%
t 108
 
4.8%
s 107
 
4.8%
l 92
 
4.1%
Other values (16) 645
28.7%
Decimal Number
ValueCountFrequency (%)
1 1133
28.6%
2 697
17.6%
6 428
 
10.8%
0 412
 
10.4%
3 339
 
8.5%
5 288
 
7.3%
4 224
 
5.6%
9 177
 
4.5%
7 144
 
3.6%
8 123
 
3.1%
Other Punctuation
ValueCountFrequency (%)
. 444
46.4%
, 390
40.8%
; 40
 
4.2%
& 38
 
4.0%
/ 21
 
2.2%
? 13
 
1.4%
@ 7
 
0.7%
＆ 2
 
0.2%
: 2
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 1347
99.6%
[ 5
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 1346
99.6%
] 5
 
0.4%
Other Symbol
ValueCountFrequency (%)
㈜ 21
87.5%
° 3
 
12.5%
Math Symbol
ValueCountFrequency (%)
+ 3
50.0%
~ 3
50.0%
Space Separator
ValueCountFrequency (%)
3060
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 75
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67931
80.6%
Common 10769
 
12.8%
Latin 5503
 
6.5%
Han 44
 
0.1%
Hiragana 2
 
< 0.1%
Katakana 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 2448
 
3.6%
원 1459
 
2.1%
어 1333
 
2.0%
스 1327
 
2.0%
린 1298
 
1.9%
아 1142
 
1.7%
학 1120
 
1.6%
동 1023
 
1.5%
교 1003
 
1.5%
점 928
 
1.4%
Other values (974) 54850
80.7%
Latin
ValueCountFrequency (%)
I 383
 
7.0%
D 380
 
6.9%
e 304
 
5.5%
a 266
 
4.8%
C 265
 
4.8%
S 223
 
4.1%
A 194
 
3.5%
E 183
 
3.3%
o 175
 
3.2%
M 161
 
2.9%
Other values (43) 2969
54.0%
Han
ValueCountFrequency (%)
食 4
 
9.1%
堂 3
 
6.8%
津 2
 
4.5%
生 2
 
4.5%
茶 2
 
4.5%
愛 2
 
4.5%
讀 2
 
4.5%
香 2
 
4.5%
人 1
 
2.3%
同 1
 
2.3%
Other values (23) 23
52.3%
Common
ValueCountFrequency (%)
3060
28.4%
( 1347
12.5%
) 1346
12.5%
1 1133
 
10.5%
2 697
 
6.5%
. 444
 
4.1%
6 428
 
4.0%
0 412
 
3.8%
, 390
 
3.6%
3 339
 
3.1%
Other values (18) 1173
 
10.9%
Hiragana
ValueCountFrequency (%)
く 1
50.0%
ん 1
50.0%
Katakana
ValueCountFrequency (%)
ホ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67906
80.6%
ASCII 16262
 
19.3%
CJK 42
 
< 0.1%
None 26
 
< 0.1%
Number Forms 5
 
< 0.1%
Compat Jamo 4
 
< 0.1%
CJK Compat Ideographs 2
 
< 0.1%
Hiragana 2
 
< 0.1%
Katakana 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3060
18.8%
( 1347
 
8.3%
) 1346
 
8.3%
1 1133
 
7.0%
2 697
 
4.3%
. 444
 
2.7%
6 428
 
2.6%
0 412
 
2.5%
, 390
 
2.4%
I 383
 
2.4%
Other values (68) 6622
40.7%
Hangul
ValueCountFrequency (%)
이 2448
 
3.6%
원 1459
 
2.1%
어 1333
 
2.0%
스 1327
 
2.0%
린 1298
 
1.9%
아 1142
 
1.7%
학 1120
 
1.6%
동 1023
 
1.5%
교 1003
 
1.5%
점 928
 
1.4%
Other values (970) 54825
80.7%
None
ValueCountFrequency (%)
㈜ 21
80.8%
° 3
 
11.5%
＆ 2
 
7.7%
Number Forms
ValueCountFrequency (%)
Ⅱ 5
100.0%
CJK
ValueCountFrequency (%)
食 4
 
9.5%
堂 3
 
7.1%
津 2
 
4.8%
生 2
 
4.8%
茶 2
 
4.8%
愛 2
 
4.8%
讀 2
 
4.8%
香 2
 
4.8%
人 1
 
2.4%
同 1
 
2.4%
Other values (21) 21
50.0%
Compat Jamo
ValueCountFrequency (%)
ㅋ 2
50.0%
ㅂ 1
25.0%
ㆍ 1
25.0%
CJK Compat Ideographs
ValueCountFrequency (%)
金 1
50.0%
樂 1
50.0%
Katakana
ValueCountFrequency (%)
ホ 1
100.0%
Hiragana
ValueCountFrequency (%)
く 1
50.0%
ん 1
50.0%

금연구역범위상세
Text

Distinct121
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size78.3 KiB
2024-04-21T08:05:57.473372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length4
Mean length6.6443
Min length3

Characters and Unicode

Total characters66443
Distinct characters206
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

Unique80 ?
Unique (%)0.8%

Sample

1st row시설전체
2nd row시설부지
3rd row시설전체
4th row시설전체
5th row시설전체
ValueCountFrequency (%)
시설전체 6846
45.4%
이내 779
 
5.2%
10m 764
 
5.1%
및 444
 
2.9%
경계로부터 352
 
2.3%
건축물 342
 
2.3%
10m이내 323
 
2.1%
1,000제곱미터이상 320
 
2.1%
지역 307
 
2.0%
어린이집 307
 
2.0%
Other values (251) 4296
28.5%
2024-04-21T08:05:57.810618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 7979
 
12.0%
설 7974
 
12.0%
전 7710
 
11.6%
체 7702
 
11.6%
5080
 
7.6%
0 2323
 
3.5%
이 2079
 
3.1%
부 1486
 
2.2%
터 1451
 
2.2%
1 1441
 
2.2%
Other values (196) 21218
31.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 55412
83.4%
Space Separator 5080
 
7.6%
Decimal Number 4156
 
6.3%
Lowercase Letter 1283
 
1.9%
Other Punctuation 475
 
0.7%
Math Symbol 18
 
< 0.1%
Close Punctuation 9
 
< 0.1%
Open Punctuation 8
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 7979
14.4%
설 7974
14.4%
전 7710
13.9%
체 7702
13.9%
이 2079
 
3.8%
부 1486
 
2.7%
터 1451
 
2.6%
로 1402
 
2.5%
내 1282
 
2.3%
지 1177
 
2.1%
Other values (176) 15170
27.4%
Decimal Number
ValueCountFrequency (%)
0 2323
55.9%
1 1441
34.7%
5 253
 
6.1%
2 36
 
0.9%
3 26
 
0.6%
4 25
 
0.6%
6 15
 
0.4%
7 14
 
0.3%
9 12
 
0.3%
8 11
 
0.3%
Other Punctuation
ValueCountFrequency (%)
, 471
99.2%
: 2
 
0.4%
. 2
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
m 1282
99.9%
k 1
 
0.1%
Space Separator
ValueCountFrequency (%)
5080
100.0%
Math Symbol
ValueCountFrequency (%)
~ 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55412
83.4%
Common 9748
 
14.7%
Latin 1283
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 7979
14.4%
설 7974
14.4%
전 7710
13.9%
체 7702
13.9%
이 2079
 
3.8%
부 1486
 
2.7%
터 1451
 
2.6%
로 1402
 
2.5%
내 1282
 
2.3%
지 1177
 
2.1%
Other values (176) 15170
27.4%
Common
ValueCountFrequency (%)
5080
52.1%
0 2323
23.8%
1 1441
 
14.8%
, 471
 
4.8%
5 253
 
2.6%
2 36
 
0.4%
3 26
 
0.3%
4 25
 
0.3%
~ 18
 
0.2%
6 15
 
0.2%
Other values (8) 60
 
0.6%
Latin
ValueCountFrequency (%)
m 1282
99.9%
k 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55412
83.4%
ASCII 11031
 
16.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 7979
14.4%
설 7974
14.4%
전 7710
13.9%
체 7702
13.9%
이 2079
 
3.8%
부 1486
 
2.7%
터 1451
 
2.6%
로 1402
 
2.5%
내 1282
 
2.3%
지 1177
 
2.1%
Other values (176) 15170
27.4%
ASCII
ValueCountFrequency (%)
5080
46.1%
0 2323
21.1%
1 1441
 
13.1%
m 1282
 
11.6%
, 471
 
4.3%
5 253
 
2.3%
2 36
 
0.3%
3 26
 
0.2%
4 25
 
0.2%
~ 18
 
0.2%
Other values (10) 76
 
0.7%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.3 KiB
서울특별시
10000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 10000
100.0%

Length

2024-04-21T08:05:57.952373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T08:05:58.038583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 10000
100.0%

시군구명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size78.3 KiB
마포구
6838 
은평구
1079 
강서구
 
642
노원구
 
440
금천구
 
333
Other values (10)
 
668

Length

Max length4
Median length3
Mean length3.0354
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row송파구
2nd row노원구
3rd row마포구
4th row마포구
5th row마포구

Common Values

ValueCountFrequency (%)
마포구 6838
68.4%
은평구 1079
 
10.8%
강서구 642
 
6.4%
노원구 440
 
4.4%
금천구 333
 
3.3%
서대문구 200
 
2.0%
동대문구 154
 
1.5%
강동구 97
 
1.0%
용산구 89
 
0.9%
종로구 46
 
0.5%
Other values (5) 82
 
0.8%

Length

2024-04-21T08:05:58.119990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
마포구 6838
68.4%
은평구 1079
 
10.8%
강서구 642
 
6.4%
노원구 440
 
4.4%
금천구 333
 
3.3%
서대문구 200
 
2.0%
동대문구 154
 
1.5%
강동구 97
 
1.0%
용산구 89
 
0.9%
종로구 46
 
0.5%
Other values (5) 82
 
0.8%

금연구역구분
Text

Distinct68
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size78.3 KiB
2024-04-21T08:05:58.269740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length100
Median length100
Mean length100
Min length100

Characters and Unicode

Total characters1000000
Distinct characters135
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

Unique5 ?
Unique (%)< 0.1%

Sample

1st row의료기관
2nd row어린이 놀이시설
3rd row학교교과보습학원
4th row학교교과보습학원
5th row학교교과보습학원
ValueCountFrequency (%)
음식점 3881
29.1%
복합건축물 995
 
7.5%
사무용건축물,공장 995
 
7.5%
및 995
 
7.5%
학교교과보습학원 874
 
6.5%
어린이집 511
 
3.8%
실내체육시설 374
 
2.8%
어린이놀이시설 329
 
2.5%
사무용건축물,공장및복합용도의건축물 320
 
2.4%
식품위생법에따른 292
 
2.2%
Other values (71) 3789
28.4%
2024-04-21T08:05:58.709706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
926606
92.7%
식 5049
 
0.5%
점 4786
 
0.5%
음 4465
 
0.4%
건 2630
 
0.3%
축 2630
 
0.3%
물 2630
 
0.3%
, 2166
 
0.2%
교 1970
 
0.2%
학 1960
 
0.2%
Other values (125) 45108
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Space Separator 926606
92.7%
Other Letter 70337
 
7.0%
Other Punctuation 2264
 
0.2%
Decimal Number 289
 
< 0.1%
Close Punctuation 185
 
< 0.1%
Open Punctuation 185
 
< 0.1%
Lowercase Letter 134
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 5049
 
7.2%
점 4786
 
6.8%
음 4465
 
6.3%
건 2630
 
3.7%
축 2630
 
3.7%
물 2630
 
3.7%
교 1970
 
2.8%
학 1960
 
2.8%
이 1943
 
2.8%
사 1865
 
2.7%
Other values (116) 40409
57.5%
Decimal Number
ValueCountFrequency (%)
0 148
51.2%
1 134
46.4%
5 7
 
2.4%
Other Punctuation
ValueCountFrequency (%)
, 2166
95.7%
. 98
 
4.3%
Space Separator
ValueCountFrequency (%)
926606
100.0%
Close Punctuation
ValueCountFrequency (%)
) 185
100.0%
Open Punctuation
ValueCountFrequency (%)
( 185
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 134
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 929529
93.0%
Hangul 70337
 
7.0%
Latin 134
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 5049
 
7.2%
점 4786
 
6.8%
음 4465
 
6.3%
건 2630
 
3.7%
축 2630
 
3.7%
물 2630
 
3.7%
교 1970
 
2.8%
학 1960
 
2.8%
이 1943
 
2.8%
사 1865
 
2.7%
Other values (116) 40409
57.5%
Common
ValueCountFrequency (%)
926606
99.7%
, 2166
 
0.2%
) 185
 
< 0.1%
( 185
 
< 0.1%
0 148
 
< 0.1%
1 134
 
< 0.1%
. 98
 
< 0.1%
5 7
 
< 0.1%
Latin
ValueCountFrequency (%)
m 134
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 929663
93.0%
Hangul 70337
 
7.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
926606
99.7%
, 2166
 
0.2%
) 185
 
< 0.1%
( 185
 
< 0.1%
0 148
 
< 0.1%
m 134
 
< 0.1%
1 134
 
< 0.1%
. 98
 
< 0.1%
5 7
 
< 0.1%
Hangul
ValueCountFrequency (%)
식 5049
 
7.2%
점 4786
 
6.8%
음 4465
 
6.3%
건 2630
 
3.7%
축 2630
 
3.7%
물 2630
 
3.7%
교 1970
 
2.8%
학 1960
 
2.8%
이 1943
 
2.8%
사 1865
 
2.7%
Other values (116) 40409
57.5%

금연구역지정근거명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size78.3 KiB
국민건강증진법제9조
7927 
서울특별시 강서구 간접흡연 피해 방지 조례 제5조
 
631
국민건강증진법
 
334
금천구 간접흡연 피해방지 조례
 
333
국민건강 증진법
 
200
Other values (15)
 
575

Length

Max length39
Median length10
Mean length11.998
Min length7

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row국민건강증진법 제9조
2nd row국민건강증진법
3rd row국민건강증진법제9조
4th row국민건강증진법제9조
5th row국민건강증진법제9조

Common Values

ValueCountFrequency (%)
국민건강증진법제9조 7927
79.3%
서울특별시 강서구 간접흡연 피해 방지 조례 제5조 631
 
6.3%
국민건강증진법 334
 
3.3%
금천구 간접흡연 피해방지 조례 333
 
3.3%
국민건강 증진법 200
 
2.0%
서울특별시 동대문구 간접흡연 피해방지 조례 154
 
1.5%
노원구금연구역지정및간접흡연피해방지에관한조례 106
 
1.1%
서울특별시은평구간접흡연피해방지조례제5조 87
 
0.9%
서울특별시 용산구 금연구역 지정 및 간접흡연 피해방지 조례 86
 
0.9%
서울특별시 종로구 금연환경조성 및 간접흡연 피해방지 조례 46
 
0.5%
Other values (10) 96
 
1.0%

Length

2024-04-21T08:05:58.851014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
국민건강증진법제9조 7947
47.2%
조례 1285
 
7.6%
간접흡연 1282
 
7.6%
서울특별시 952
 
5.7%
제5조 685
 
4.1%
피해방지 651
 
3.9%
강서구 642
 
3.8%
피해 631
 
3.7%
방지 631
 
3.7%
국민건강증진법 374
 
2.2%
Other values (21) 1767
 
10.5%

금연구역면적
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct195
Distinct (%)56.0%
Missing9652
Missing (%)96.5%
Infinite0
Infinite (%)0.0%
Mean9361.2046
Minimum1
Maximum649709
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size88.0 KiB
2024-04-21T08:05:59.002976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10
Q110
median345.65
Q31646.5
95-th percentile27609.9
Maximum649709
Range649708
Interquartile range (IQR)1636.5

Descriptive statistics

Standard deviation53839.058
Coefficient of variation (CV)5.751296
Kurtosis111.15041
Mean9361.2046
Median Absolute Deviation (MAD)335.65
Skewness10.039213
Sum3257699.2
Variance2.8986442 × 109
MonotonicityNot monotonic
2024-04-21T08:05:59.127623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.0 133
 
1.3%
992.0 6
 
0.1%
1500.0 5
 
0.1%
1653.0 3
 
< 0.1%
240.0 2
 
< 0.1%
150.0 2
 
< 0.1%
1617.0 2
 
< 0.1%
410.0 2
 
< 0.1%
190.0 2
 
< 0.1%
225.0 2
 
< 0.1%
Other values (185) 189
 
1.9%
(Missing) 9652
96.5%
ValueCountFrequency (%)
1.0 1
 
< 0.1%
10.0 133
1.3%
70.0 1
 
< 0.1%
110.0 1
 
< 0.1%
112.0 1
 
< 0.1%
136.0 1
 
< 0.1%
150.0 2
 
< 0.1%
152.0 1
 
< 0.1%
166.0 1
 
< 0.1%
170.0 1
 
< 0.1%
ValueCountFrequency (%)
649709.0 1
< 0.1%
632733.0 1
< 0.1%
265582.0 1
< 0.1%
242864.0 1
< 0.1%
160419.0 1
< 0.1%
102920.0 1
< 0.1%
99599.0 1
< 0.1%
87748.0 1
< 0.1%
86205.0 1
< 0.1%
59752.0 1
< 0.1%

위반과태료
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.3 KiB
100000
9859 
50000
 
141

Length

Max length6
Median length6
Mean length5.9859
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row100000
2nd row100000
3rd row100000
4th row100000
5th row100000

Common Values

ValueCountFrequency (%)
100000 9859
98.6%
50000 141
 
1.4%

Length

2024-04-21T08:05:59.252890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T08:05:59.338159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
100000 9859
98.6%
50000 141
 
1.4%

위반신고전화번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size78.3 KiB
02-3153-9089
6838 
02-351-8243
1079 
02-2600-5846
 
642
02-2116-4381
 
440
02-2627-2617
 
332
Other values (13)
 
669

Length

Max length12
Median length12
Mean length11.8683
Min length11

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row02-2147-3498
2nd row02-2116-4381
3rd row02-3153-9089
4th row02-3153-9089
5th row02-3153-9089

Common Values

ValueCountFrequency (%)
02-3153-9089 6838
68.4%
02-351-8243 1079
 
10.8%
02-2600-5846 642
 
6.4%
02-2116-4381 440
 
4.4%
02-2627-2617 332
 
3.3%
02-330-8590 200
 
2.0%
02-2127-5204 154
 
1.5%
02-2199-8363 89
 
0.9%
02-2148-3541 46
 
0.5%
02-3425-6704 46
 
0.5%
Other values (8) 134
 
1.3%

Length

2024-04-21T08:05:59.428570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
02-3153-9089 6838
68.4%
02-351-8243 1079
 
10.8%
02-2600-5846 642
 
6.4%
02-2116-4381 440
 
4.4%
02-2627-2617 332
 
3.3%
02-330-8590 200
 
2.0%
02-2127-5204 154
 
1.5%
02-2199-8363 89
 
0.9%
02-3425-6704 46
 
0.5%
02-2148-3541 46
 
0.5%
Other values (8) 134
 
1.3%

소재지도로명주소
Text

MISSING 

Distinct9508
Distinct (%)97.1%
Missing210
Missing (%)2.1%
Memory size78.3 KiB
2024-04-21T08:05:59.761194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length62
Mean length29.251992
Min length13

Characters and Unicode

Total characters286377
Distinct characters543
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9326 ?
Unique (%)95.3%

Sample

1st row서울특별시 송파구 새말로 120, 2층 201호 (문정동, 화애빌딩)
2nd row서울특별시 노원구 화랑로47길 38 (월계동)
3rd row서울특별시 마포구 신촌로 222-1 , 2,3,4,5,7,8층 (아현동)
4th row서울특별시 마포구 독막로 278-4 , 202호, 301~302호 (대흥동, LS building)
5th row서울특별시 마포구 백범로 102 , 2,3,4층 (대흥동, 원흥빌딩)
ValueCountFrequency (%)
서울특별시 9790
 
17.3%
마포구 6837
 
12.1%
1층 1505
 
2.7%
서교동 1090
 
1.9%
은평구 1080
 
1.9%
762
 
1.3%
2층 697
 
1.2%
강서구 640
 
1.1%
상암동 546
 
1.0%
성산동 465
 
0.8%
Other values (6547) 33075
58.6%
2024-04-21T08:06:00.239248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46697
 
16.3%
1 12451
 
4.3%
서 12432
 
4.3%
동 10303
 
3.6%
시 10088
 
3.5%
울 10070
 
3.5%
구 9975
 
3.5%
별 9794
 
3.4%
특 9791
 
3.4%
로 8943
 
3.1%
Other values (533) 145833
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 169838
59.3%
Space Separator 46697
 
16.3%
Decimal Number 43685
 
15.3%
Open Punctuation 8188
 
2.9%
Close Punctuation 8186
 
2.9%
Other Punctuation 7075
 
2.5%
Dash Punctuation 1596
 
0.6%
Uppercase Letter 882
 
0.3%
Lowercase Letter 146
 
0.1%
Math Symbol 76
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 12432
 
7.3%
동 10303
 
6.1%
시 10088
 
5.9%
울 10070
 
5.9%
구 9975
 
5.9%
별 9794
 
5.8%
특 9791
 
5.8%
로 8943
 
5.3%
마 7884
 
4.6%
포 7668
 
4.5%
Other values (468) 72890
42.9%
Uppercase Letter
ValueCountFrequency (%)
B 233
26.4%
C 93
 
10.5%
D 72
 
8.2%
M 64
 
7.3%
T 54
 
6.1%
K 54
 
6.1%
A 52
 
5.9%
I 42
 
4.8%
S 39
 
4.4%
G 36
 
4.1%
Other values (13) 143
16.2%
Lowercase Letter
ValueCountFrequency (%)
e 24
16.4%
o 19
13.0%
i 16
11.0%
t 15
10.3%
r 14
9.6%
y 12
8.2%
w 9
 
6.2%
n 7
 
4.8%
a 4
 
2.7%
l 4
 
2.7%
Other values (11) 22
15.1%
Decimal Number
ValueCountFrequency (%)
1 12451
28.5%
2 6999
16.0%
3 4647
 
10.6%
4 3716
 
8.5%
0 3589
 
8.2%
5 2999
 
6.9%
6 2641
 
6.0%
7 2392
 
5.5%
8 2160
 
4.9%
9 2091
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 7035
99.4%
. 30
 
0.4%
@ 6
 
0.1%
， 4
 
0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 7
87.5%
Ⅰ 1
 
12.5%
Space Separator
ValueCountFrequency (%)
46697
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8188
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8186
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1596
100.0%
Math Symbol
ValueCountFrequency (%)
~ 76
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 169838
59.3%
Common 115503
40.3%
Latin 1036
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 12432
 
7.3%
동 10303
 
6.1%
시 10088
 
5.9%
울 10070
 
5.9%
구 9975
 
5.9%
별 9794
 
5.8%
특 9791
 
5.8%
로 8943
 
5.3%
마 7884
 
4.6%
포 7668
 
4.5%
Other values (468) 72890
42.9%
Latin
ValueCountFrequency (%)
B 233
22.5%
C 93
 
9.0%
D 72
 
6.9%
M 64
 
6.2%
T 54
 
5.2%
K 54
 
5.2%
A 52
 
5.0%
I 42
 
4.1%
S 39
 
3.8%
G 36
 
3.5%
Other values (36) 297
28.7%
Common
ValueCountFrequency (%)
46697
40.4%
1 12451
 
10.8%
( 8188
 
7.1%
) 8186
 
7.1%
, 7035
 
6.1%
2 6999
 
6.1%
3 4647
 
4.0%
4 3716
 
3.2%
0 3589
 
3.1%
5 2999
 
2.6%
Other values (9) 10996
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 169564
59.2%
ASCII 116526
40.7%
Compat Jamo 274
 
0.1%
Number Forms 8
 
< 0.1%
None 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46697
40.1%
1 12451
 
10.7%
( 8188
 
7.0%
) 8186
 
7.0%
, 7035
 
6.0%
2 6999
 
6.0%
3 4647
 
4.0%
4 3716
 
3.2%
0 3589
 
3.1%
5 2999
 
2.6%
Other values (51) 12019
 
10.3%
Hangul
ValueCountFrequency (%)
서 12432
 
7.3%
동 10303
 
6.1%
시 10088
 
5.9%
울 10070
 
5.9%
구 9975
 
5.9%
별 9794
 
5.8%
특 9791
 
5.8%
로 8943
 
5.3%
마 7884
 
4.6%
포 7668
 
4.5%
Other values (467) 72616
42.8%
Compat Jamo
ValueCountFrequency (%)
ㅡ 274
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 7
87.5%
Ⅰ 1
 
12.5%
None
ValueCountFrequency (%)
， 4
80.0%
ｌ 1
 
20.0%

소재지지번주소
Text

MISSING 

Distinct1380
Distinct (%)83.9%
Missing8355
Missing (%)83.5%
Memory size78.3 KiB
2024-04-21T08:06:00.579777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length44
Mean length19.907599
Min length13

Characters and Unicode

Total characters32748
Distinct characters263
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1305 ?
Unique (%)79.3%

Sample

1st row서울특별시 은평구 진관동67ㅡ1
2nd row서울특별시 은평구 진관동68ㅡ0
3rd row서울특별시 은평구 진관동69ㅡ0
4th row서울특별시 은평구 진관동69ㅡ1
5th row서울특별시 은평구 진관동70ㅡ0
ValueCountFrequency (%)
서울특별시 1644
24.4%
은평구 1220
18.1%
1층 162
 
2.4%
동대문구 145
 
2.2%
노원구 103
 
1.5%
강동구 97
 
1.4%
용산구 85
 
1.3%
갈현동 76
 
1.1%
응암동 74
 
1.1%
불광동 73
 
1.1%
Other values (1652) 3047
45.3%
2024-04-21T08:06:01.049053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5081
 
15.5%
구 1847
 
5.6%
동 1773
 
5.4%
서 1732
 
5.3%
시 1651
 
5.0%
울 1648
 
5.0%
특 1645
 
5.0%
별 1645
 
5.0%
1 1608
 
4.9%
은 1254
 
3.8%
Other values (253) 12864
39.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20297
62.0%
Decimal Number 6510
 
19.9%
Space Separator 5081
 
15.5%
Dash Punctuation 746
 
2.3%
Other Punctuation 47
 
0.1%
Uppercase Letter 24
 
0.1%
Open Punctuation 20
 
0.1%
Close Punctuation 20
 
0.1%
Math Symbol 2
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1847
 
9.1%
동 1773
 
8.7%
서 1732
 
8.5%
시 1651
 
8.1%
울 1648
 
8.1%
특 1645
 
8.1%
별 1645
 
8.1%
은 1254
 
6.2%
평 1251
 
6.2%
ㅡ 274
 
1.3%
Other values (226) 5577
27.5%
Decimal Number
ValueCountFrequency (%)
1 1608
24.7%
2 902
13.9%
3 692
10.6%
4 587
 
9.0%
6 512
 
7.9%
5 497
 
7.6%
0 496
 
7.6%
7 441
 
6.8%
8 388
 
6.0%
9 387
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
C 5
20.8%
B 4
16.7%
D 4
16.7%
A 4
16.7%
M 3
12.5%
H 1
 
4.2%
S 1
 
4.2%
N 1
 
4.2%
E 1
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 42
89.4%
. 5
 
10.6%
Space Separator
ValueCountFrequency (%)
5081
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 746
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
ｌ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20297
62.0%
Common 12426
37.9%
Latin 25
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1847
 
9.1%
동 1773
 
8.7%
서 1732
 
8.5%
시 1651
 
8.1%
울 1648
 
8.1%
특 1645
 
8.1%
별 1645
 
8.1%
은 1254
 
6.2%
평 1251
 
6.2%
ㅡ 274
 
1.3%
Other values (226) 5577
27.5%
Common
ValueCountFrequency (%)
5081
40.9%
1 1608
 
12.9%
2 902
 
7.3%
- 746
 
6.0%
3 692
 
5.6%
4 587
 
4.7%
6 512
 
4.1%
5 497
 
4.0%
0 496
 
4.0%
7 441
 
3.5%
Other values (7) 864
 
7.0%
Latin
ValueCountFrequency (%)
C 5
20.0%
B 4
16.0%
D 4
16.0%
A 4
16.0%
M 3
12.0%
H 1
 
4.0%
S 1
 
4.0%
N 1
 
4.0%
E 1
 
4.0%
ｌ 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20023
61.1%
ASCII 12450
38.0%
Compat Jamo 274
 
0.8%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5081
40.8%
1 1608
 
12.9%
2 902
 
7.2%
- 746
 
6.0%
3 692
 
5.6%
4 587
 
4.7%
6 512
 
4.1%
5 497
 
4.0%
0 496
 
4.0%
7 441
 
3.5%
Other values (16) 888
 
7.1%
Hangul
ValueCountFrequency (%)
구 1847
 
9.2%
동 1773
 
8.9%
서 1732
 
8.7%
시 1651
 
8.2%
울 1648
 
8.2%
특 1645
 
8.2%
별 1645
 
8.2%
은 1254
 
6.3%
평 1251
 
6.2%
대 269
 
1.3%
Other values (225) 5308
26.5%
Compat Jamo
ValueCountFrequency (%)
ㅡ 274
100.0%
None
ValueCountFrequency (%)
ｌ 1
100.0%

관리기관명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size78.3 KiB
서울특별시 마포구청
6838 
서울특별시 은평구청
1079 
서울특별시 강서구보건소
 
642
서울특별시 노원구청
 
440
서울특별시 금천구청
 
333
Other values (10)
 
668

Length

Max length18
Median length10
Mean length10.1893
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시 송파구청
2nd row서울특별시 노원구청
3rd row서울특별시 마포구청
4th row서울특별시 마포구청
5th row서울특별시 마포구청

Common Values

ValueCountFrequency (%)
서울특별시 마포구청 6838
68.4%
서울특별시 은평구청 1079
 
10.8%
서울특별시 강서구보건소 642
 
6.4%
서울특별시 노원구청 440
 
4.4%
서울특별시 금천구청 333
 
3.3%
서울특별시 서대문구청 200
 
2.0%
서울특별시 동대문구청 154
 
1.5%
서울특별시 강동구청 97
 
1.0%
서울특별시용산보건소 89
 
0.9%
서울특별시 종로구청 46
 
0.5%
Other values (5) 82
 
0.8%

Length

2024-04-21T08:06:01.182328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 9911
49.7%
마포구청 6838
34.3%
은평구청 1079
 
5.4%
강서구보건소 642
 
3.2%
노원구청 440
 
2.2%
금천구청 333
 
1.7%
서대문구청 200
 
1.0%
동대문구청 154
 
0.8%
강동구청 97
 
0.5%
서울특별시용산보건소 89
 
0.4%
Other values (7) 148
 
0.7%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct6267
Distinct (%)62.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.561883
Minimum37.434878
Maximum37.738061
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size88.0 KiB
2024-04-21T08:06:01.301562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.434878
5-th percentile37.535575
Q137.548204
median37.555535
Q337.572103
95-th percentile37.625819
Maximum37.738061
Range0.303183
Interquartile range (IQR)0.02389925

Descriptive statistics

Standard deviation0.032683628
Coefficient of variation (CV)0.0008701275
Kurtosis3.2974958
Mean37.561883
Median Absolute Deviation (MAD)0.009292
Skewness0.10488522
Sum375618.83
Variance0.0010682195
MonotonicityNot monotonic
2024-04-21T08:06:01.429809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.600511 340
 
3.4%
37.580261 35
 
0.4%
37.568288 29
 
0.3%
37.551501 28
 
0.3%
37.579442 27
 
0.3%
37.580108 26
 
0.3%
37.581324 23
 
0.2%
37.585044 22
 
0.2%
37.581622 20
 
0.2%
37.539985 17
 
0.2%
Other values (6257) 9433
94.3%
ValueCountFrequency (%)
37.434878 1
< 0.1%
37.437777 2
< 0.1%
37.439347 1
< 0.1%
37.439645 1
< 0.1%
37.440267 1
< 0.1%
37.441154 1
< 0.1%
37.441311 1
< 0.1%
37.441443 1
< 0.1%
37.441704 1
< 0.1%
37.442723 1
< 0.1%
ValueCountFrequency (%)
37.738061 1
< 0.1%
37.6881795 1
< 0.1%
37.68621485 1
< 0.1%
37.685971 1
< 0.1%
37.68450193 1
< 0.1%
37.682986 1
< 0.1%
37.681574 1
< 0.1%
37.68082279 1
< 0.1%
37.680731 1
< 0.1%
37.680524 1
< 0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct6418
Distinct (%)64.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.9301
Minimum126.76837
Maximum127.1803
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size88.0 KiB
2024-04-21T08:06:01.565948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.76837
5-th percentile126.85482
Q1126.90856
median126.92317
Q3126.9436
95-th percentile127.06022
Maximum127.1803
Range0.411928
Interquartile range (IQR)0.03504425

Descriptive statistics

Standard deviation0.050366697
Coefficient of variation (CV)0.00039680658
Kurtosis4.7373981
Mean126.9301
Median Absolute Deviation (MAD)0.016890009
Skewness1.5434297
Sum1269301
Variance0.0025368042
MonotonicityNot monotonic
2024-04-21T08:06:01.706327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.933571 340
 
3.4%
126.880735 35
 
0.4%
126.897273 30
 
0.3%
126.91395 28
 
0.3%
126.890323 27
 
0.3%
126.888982 26
 
0.3%
126.888548 24
 
0.2%
126.87987 22
 
0.2%
126.88605 20
 
0.2%
126.947816 17
 
0.2%
Other values (6408) 9431
94.3%
ValueCountFrequency (%)
126.768373 2
< 0.1%
126.798211 1
 
< 0.1%
126.798792 2
< 0.1%
126.799 1
 
< 0.1%
126.800471 1
 
< 0.1%
126.801785 1
 
< 0.1%
126.802746 1
 
< 0.1%
126.80296 3
< 0.1%
126.803355 2
< 0.1%
126.804526 1
 
< 0.1%
ValueCountFrequency (%)
127.180301 1
< 0.1%
127.177562 1
< 0.1%
127.177198 1
< 0.1%
127.175773 1
< 0.1%
127.175697 1
< 0.1%
127.174715 1
< 0.1%
127.174671 1
< 0.1%
127.1744407427 1
< 0.1%
127.1739072 1
< 0.1%
127.1714755 1
< 0.1%

데이터기준일자
Date

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size78.3 KiB
Minimum2021-02-17 00:00:00
Maximum2024-02-22 00:00:00
2024-04-21T08:06:01.834196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:06:01.948963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)

제공기관코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size88.0 KiB

작업일시
Date

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size78.3 KiB
Minimum2024-04-17 11:51:52
Maximum2024-04-17 11:51:59
2024-04-21T08:06:02.035787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:06:02.127074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)

Interactions

2024-04-21T08:05:55.925013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:05:55.359263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:05:55.643557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:05:56.021909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:05:55.485586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:05:55.735280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:05:56.109017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:05:55.559695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:05:55.823183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T08:06:02.217811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명금연구역구분금연구역지정근거명금연구역면적위반과태료위반신고전화번호관리기관명위도경도데이터기준일자작업일시
시군구명1.0000.9970.9940.0000.6071.0001.0000.8840.9081.0000.593
금연구역구분0.9971.0000.9930.0000.9950.9930.9970.9140.9180.9970.908
금연구역지정근거명0.9940.9931.0000.0000.9960.9820.9940.8910.9060.9940.588
금연구역면적0.0000.0000.0001.0000.0000.0940.0000.3480.1770.0000.000
위반과태료0.6070.9950.9960.0001.0000.6950.6070.5360.4950.6070.264
위반신고전화번호1.0000.9930.9820.0940.6951.0001.0000.8740.9011.0000.600
관리기관명1.0000.9970.9940.0000.6071.0001.0000.8840.9081.0000.593
위도0.8840.9140.8910.3480.5360.8740.8841.0000.7390.8840.376
경도0.9080.9180.9060.1770.4950.9010.9080.7391.0000.9080.391
데이터기준일자1.0000.9970.9940.0000.6071.0001.0000.8840.9081.0000.593
작업일시0.5930.9080.5880.0000.2640.6000.5930.3760.3910.5931.000
2024-04-21T08:06:02.345044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명금연구역지정근거명위반과태료위반신고전화번호관리기관명
시군구명1.0000.9280.5591.0001.000
금연구역지정근거명0.9281.0000.9440.8420.928
위반과태료0.5590.9441.0000.5580.559
위반신고전화번호1.0000.8420.5581.0001.000
관리기관명1.0000.9280.5591.0001.000
2024-04-21T08:06:02.442170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
금연구역면적위도경도시군구명금연구역지정근거명위반과태료위반신고전화번호관리기관명
금연구역면적1.0000.7660.8560.0000.0000.0000.0480.000
위도0.7661.000-0.1360.5810.5150.4130.5810.581
경도0.856-0.1361.0000.6310.5430.3810.6390.631
시군구명0.0000.5810.6311.0000.9280.5591.0001.000
금연구역지정근거명0.0000.5150.5430.9281.0000.9440.8420.928
위반과태료0.0000.4130.3810.5590.9441.0000.5580.559
위반신고전화번호0.0480.5810.6391.0000.8420.5581.0001.000
관리기관명0.0000.5810.6311.0000.9280.5591.0001.000

Missing values

2024-04-21T08:05:56.253185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T08:05:56.459116image/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.
2024-04-21T08:05:56.600122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

금연구역명금연구역범위상세시도명시군구명금연구역구분금연구역지정근거명금연구역면적위반과태료위반신고전화번호소재지도로명주소소재지지번주소관리기관명위도경도데이터기준일자제공기관코드작업일시
0모정한의원시설전체서울특별시송파구의료기관국민건강증진법 제9조<NA>10000002-2147-3498서울특별시 송파구 새말로 120, 2층 201호 (문정동, 화애빌딩)<NA>서울특별시 송파구청37.482739127.1275212021-02-17<NA>2024-04-17 11:51:52.0
1풍림아이원 108동 놀이터시설부지서울특별시노원구어린이 놀이시설국민건강증진법<NA>10000002-2116-4381서울특별시 노원구 화랑로47길 38 (월계동)<NA>서울특별시 노원구청37.616512127.065742023-08-01<NA>2024-04-17 11:51:52.0
2대치상상학원시설전체서울특별시마포구학교교과보습학원국민건강증진법제9조<NA>10000002-3153-9089서울특별시 마포구 신촌로 222-1 , 2,3,4,5,7,8층 (아현동)<NA>서울특별시 마포구청37.556802126.950412023-09-06<NA>2024-04-17 11:51:52.0
3대치써미트영어학원시설전체서울특별시마포구학교교과보습학원국민건강증진법제9조<NA>10000002-3153-9089서울특별시 마포구 독막로 278-4 , 202호, 301~302호 (대흥동, LS building)<NA>서울특별시 마포구청37.5452126.9437692023-09-06<NA>2024-04-17 11:51:52.0
4대치써미트영어학원제2관(고등관)학원시설전체서울특별시마포구학교교과보습학원국민건강증진법제9조<NA>10000002-3153-9089서울특별시 마포구 백범로 102 , 2,3,4층 (대흥동, 원흥빌딩)<NA>서울특별시 마포구청37.547395126.9424542023-09-06<NA>2024-04-17 11:51:52.0
5대치영재수학학원시설전체서울특별시마포구학교교과보습학원국민건강증진법제9조<NA>10000002-3153-9089서울특별시 마포구 독막로 268 , 종합상가동 3층 302,303,304호 (대흥동, 대흥동태영아파트)<NA>서울특별시 마포구청37.545662126.9428792023-09-06<NA>2024-04-17 11:51:52.0
6대치이강학원신촌캠퍼스학원시설전체서울특별시마포구학교교과보습학원국민건강증진법제9조<NA>10000002-3153-9089서울특별시 마포구 성미산로 121 , 경성문화회관 4층(연남동 369-1) (연남동)<NA>서울특별시 마포구청37.562962126.9202492023-09-06<NA>2024-04-17 11:51:52.0
7대치학원시설전체서울특별시마포구학교교과보습학원국민건강증진법제9조<NA>10000002-3153-9089서울특별시 마포구 굴레방로 27 , 보성상가 2층 201호, 6층 602호 (아현동)<NA>서울특별시 마포구청37.556477126.9553232023-09-06<NA>2024-04-17 11:51:52.0
8대치학원광흥창영어직영관학원시설전체서울특별시마포구학교교과보습학원국민건강증진법제9조<NA>10000002-3153-9089서울특별시 마포구 독막로 153 , 2층 (창전동)<NA>서울특별시 마포구청37.547724126.930392023-09-06<NA>2024-04-17 11:51:52.0
9대치학원광흥창직영관학원시설전체서울특별시마포구학교교과보습학원국민건강증진법제9조<NA>10000002-3153-9089서울특별시 마포구 독막로 153 , 3층 (창전동)<NA>서울특별시 마포구청37.547721126.9303852023-09-06<NA>2024-04-17 11:51:52.0
금연구역명금연구역범위상세시도명시군구명금연구역구분금연구역지정근거명금연구역면적위반과태료위반신고전화번호소재지도로명주소소재지지번주소관리기관명위도경도데이터기준일자제공기관코드작업일시
9990미니스톱상암센트럴점시설전체서울특별시마포구음식점국민건강증진법제9조<NA>10000002-3153-9089서울특별시 마포구 월드컵북로 375 (상암동, DMC 이안상암1단지 1층 113호 일부)<NA>서울특별시 마포구청37.577574126.8907232023-09-06<NA>2024-04-17 11:51:59.0
9991미니스톱동교스텔라점시설전체서울특별시마포구음식점국민건강증진법제9조<NA>10000002-3153-9089서울특별시 마포구 월드컵북로 20 (동교동, 1층)<NA>서울특별시 마포구청37.556719126.9201322023-09-06<NA>2024-04-17 11:51:59.0
9992캐리피시카페(CARRY PC CAFE)시설전체서울특별시마포구음식점국민건강증진법제9조<NA>10000002-3153-9089서울특별시 마포구 포은로2가길 65, 지1층일부 (합정동)<NA>서울특별시 마포구청37.549446126.9103462023-09-06<NA>2024-04-17 11:51:59.0
9993먹거리장터시설전체서울특별시마포구음식점국민건강증진법제9조<NA>10000002-3153-9089서울특별시 마포구 양화로 45 (서교동, 메세나폴리스 지하2층 홈플러스내)<NA>서울특별시 마포구청37.551501126.913952023-09-06<NA>2024-04-17 11:51:59.0
9994지엠피씨클럽(GM PC CLUB)시설전체서울특별시마포구음식점국민건강증진법제9조<NA>10000002-3153-9089서울특별시 마포구 월드컵북로7길 11, 2층 (서교동)<NA>서울특별시 마포구청37.558077126.9172372023-09-06<NA>2024-04-17 11:51:59.0
9995이마트24 디지털큐브점시설전체서울특별시마포구음식점국민건강증진법제9조<NA>10000002-3153-9089서울특별시 마포구 상암산로 34 (상암동, 디지털큐브 지1층일부)<NA>서울특별시 마포구청37.57621126.889242023-09-06<NA>2024-04-17 11:51:59.0
9996빽다방상암KGIT점시설전체서울특별시마포구음식점국민건강증진법제9조<NA>10000002-3153-9089서울특별시 마포구 월드컵북로 402 (상암동, KGIT센터 105호, 106호)<NA>서울특별시 마포구청37.580108126.8889822023-09-06<NA>2024-04-17 11:51:59.0
9997카페코나퀸즈마포점(cafe konaqueens)시설전체서울특별시마포구음식점국민건강증진법제9조<NA>10000002-3153-9089서울특별시 마포구 마포대로 34 (도화동, 1층일부)<NA>서울특별시 마포구청37.53926126.9461522023-09-06<NA>2024-04-17 11:51:59.0
9998씨유마포성산점시설전체서울특별시마포구음식점국민건강증진법제9조<NA>10000002-3153-9089서울특별시 마포구 월드컵북로 171, 1층 (성산동)<NA>서울특별시 마포구청37.567241126.9094982023-09-06<NA>2024-04-17 11:51:59.0
9999코코부코(COCOBUKO)시설전체서울특별시마포구음식점국민건강증진법제9조<NA>10000002-3153-9089서울특별시 마포구 희우정로 72 (망원동, 1층일부)<NA>서울특별시 마포구청37.552615126.9043412023-09-06<NA>2024-04-17 11:51:59.0