Overview

Dataset statistics

Number of variables17
Number of observations10000
Missing cells19208
Missing cells (%)11.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 MiB
Average record size in memory148.0 B

Variable types

Text9
Categorical2
Numeric4
DateTime1
Unsupported1

Dataset

Description공공데이터 제공 표준데이터 속성정보(허용값, 표현형식/단위 등)는 [공공데이터 제공 표준] 전문을 참고하시기 바랍니다.(공공데이터포털>정보공유>자료실) 각 기관에서 등록한 표준데이터를 취합하여 제공하기 때문에 갱신주기는 개별 파일마다 다릅니다.(기관에서 등록한 데이터를 취합한 것으로 개별 파일별 갱신시점이 다름)
Author지방자치단체
URLhttps://www.data.go.kr/data/15013192/standard.do

Alerts

위반과태료 is highly overall correlated with 금연구역지정근거명High correlation
위도 is highly overall correlated with 시도명High correlation
경도 is highly overall correlated with 시도명High correlation
시도명 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
금연구역지정근거명 is highly overall correlated with 위반과태료 and 1 other fieldsHigh correlation
금연구역지정근거명 is highly imbalanced (64.6%)Imbalance
금연구역면적 has 9378 (93.8%) missing valuesMissing
위반과태료 has 1688 (16.9%) missing valuesMissing
위반신고전화번호 has 1540 (15.4%) missing valuesMissing
소재지도로명주소 has 240 (2.4%) missing valuesMissing
소재지지번주소 has 6362 (63.6%) missing valuesMissing
제공기관코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-04 07:44:43.577911
Analysis finished2024-05-04 07:45:02.778694
Duration19.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

금연구역명
Text

Distinct9427
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T07:45:03.326621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length31
Mean length7.6471
Min length1

Characters and Unicode

Total characters76471
Distinct characters1066
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9196 ?
Unique (%)92.0%

Sample

1st row들머리 고향순대
2nd row성주관광주유소
3rd row아지매시락국밥
4th row비비추어린이공원
5th row상대당구장
ValueCountFrequency (%)
및 274
 
2.1%
사무용건축물 272
 
2.0%
공장 272
 
2.0%
복합건축물 272
 
2.0%
놀이터 138
 
1.0%
10미터 117
 
0.9%
시설 116
 
0.9%
경계 116
 
0.9%
어린이집 60
 
0.5%
어린이 46
 
0.3%
Other values (10147) 11594
87.3%
2024-05-04T07:45:04.795284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3279
 
4.3%
이 2183
 
2.9%
원 1770
 
2.3%
어 1249
 
1.6%
점 1212
 
1.6%
학 1100
 
1.4%
아 1009
 
1.3%
린 931
 
1.2%
집 909
 
1.2%
스 902
 
1.2%
Other values (1056) 61927
81.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67711
88.5%
Space Separator 3279
 
4.3%
Decimal Number 1918
 
2.5%
Uppercase Letter 1071
 
1.4%
Close Punctuation 718
 
0.9%
Open Punctuation 716
 
0.9%
Lowercase Letter 564
 
0.7%
Other Punctuation 387
 
0.5%
Other Symbol 75
 
0.1%
Dash Punctuation 22
 
< 0.1%
Other values (4) 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 2183
 
3.2%
원 1770
 
2.6%
어 1249
 
1.8%
점 1212
 
1.8%
학 1100
 
1.6%
아 1009
 
1.5%
린 931
 
1.4%
집 909
 
1.3%
스 902
 
1.3%
산 892
 
1.3%
Other values (974) 55554
82.0%
Uppercase Letter
ValueCountFrequency (%)
C 169
15.8%
P 122
 
11.4%
S 109
 
10.2%
G 89
 
8.3%
A 55
 
5.1%
T 49
 
4.6%
E 46
 
4.3%
L 44
 
4.1%
O 43
 
4.0%
M 39
 
3.6%
Other values (16) 306
28.6%
Lowercase Letter
ValueCountFrequency (%)
e 100
17.7%
a 51
 
9.0%
o 45
 
8.0%
t 33
 
5.9%
i 32
 
5.7%
s 32
 
5.7%
c 31
 
5.5%
n 30
 
5.3%
r 28
 
5.0%
f 27
 
4.8%
Other values (15) 155
27.5%
Decimal Number
ValueCountFrequency (%)
1 486
25.3%
2 398
20.8%
0 280
14.6%
5 175
 
9.1%
3 159
 
8.3%
4 127
 
6.6%
7 100
 
5.2%
6 79
 
4.1%
9 65
 
3.4%
8 49
 
2.6%
Other Punctuation
ValueCountFrequency (%)
, 306
79.1%
& 36
 
9.3%
. 30
 
7.8%
· 8
 
2.1%
: 3
 
0.8%
/ 2
 
0.5%
? 2
 
0.5%
Other Number
ValueCountFrequency (%)
② 1
33.3%
④ 1
33.3%
① 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 717
99.9%
] 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 715
99.9%
[ 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
+ 3
75.0%
× 1
 
25.0%
Space Separator
ValueCountFrequency (%)
3279
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 75
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67768
88.6%
Common 7049
 
9.2%
Latin 1636
 
2.1%
Han 18
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 2183
 
3.2%
원 1770
 
2.6%
어 1249
 
1.8%
점 1212
 
1.8%
학 1100
 
1.6%
아 1009
 
1.5%
린 931
 
1.4%
집 909
 
1.3%
스 902
 
1.3%
산 892
 
1.3%
Other values (961) 55611
82.1%
Latin
ValueCountFrequency (%)
C 169
 
10.3%
P 122
 
7.5%
S 109
 
6.7%
e 100
 
6.1%
G 89
 
5.4%
A 55
 
3.4%
a 51
 
3.1%
T 49
 
3.0%
E 46
 
2.8%
o 45
 
2.8%
Other values (42) 801
49.0%
Common
ValueCountFrequency (%)
3279
46.5%
) 717
 
10.2%
( 715
 
10.1%
1 486
 
6.9%
2 398
 
5.6%
, 306
 
4.3%
0 280
 
4.0%
5 175
 
2.5%
3 159
 
2.3%
4 127
 
1.8%
Other values (19) 407
 
5.8%
Han
ValueCountFrequency (%)
孝 3
16.7%
安 2
11.1%
酒 2
11.1%
否 1
 
5.6%
休 1
 
5.6%
秀 1
 
5.6%
才 1
 
5.6%
府 1
 
5.6%
鉉 1
 
5.6%
太 1
 
5.6%
Other values (4) 4
22.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67692
88.5%
ASCII 8672
 
11.3%
None 84
 
0.1%
CJK 18
 
< 0.1%
Enclosed Alphanum 3
 
< 0.1%
Compat Jamo 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3279
37.8%
) 717
 
8.3%
( 715
 
8.2%
1 486
 
5.6%
2 398
 
4.6%
, 306
 
3.5%
0 280
 
3.2%
5 175
 
2.0%
C 169
 
1.9%
3 159
 
1.8%
Other values (65) 1988
22.9%
Hangul
ValueCountFrequency (%)
이 2183
 
3.2%
원 1770
 
2.6%
어 1249
 
1.8%
점 1212
 
1.8%
학 1100
 
1.6%
아 1009
 
1.5%
린 931
 
1.4%
집 909
 
1.3%
스 902
 
1.3%
산 892
 
1.3%
Other values (959) 55535
82.0%
None
ValueCountFrequency (%)
㈜ 75
89.3%
· 8
 
9.5%
× 1
 
1.2%
CJK
ValueCountFrequency (%)
孝 3
16.7%
安 2
11.1%
酒 2
11.1%
否 1
 
5.6%
休 1
 
5.6%
秀 1
 
5.6%
才 1
 
5.6%
府 1
 
5.6%
鉉 1
 
5.6%
太 1
 
5.6%
Other values (4) 4
22.2%
Compat Jamo
ValueCountFrequency (%)
ㅇ 1
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
② 1
33.3%
④ 1
33.3%
① 1
33.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

금연구역범위상세
Text

Distinct86
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T07:45:05.392162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length148
Median length4
Mean length6.4102
Min length2

Characters and Unicode

Total characters64102
Distinct characters158
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)0.2%

Sample

1st row시설전체
2nd row시설전체
3rd row시설전체
4th row공원전체
5th row시설전체
ValueCountFrequency (%)
시설전체 6948
40.3%
건물 1514
 
8.8%
내 1394
 
8.1%
시설실내 730
 
4.2%
또는 697
 
4.0%
해당부지 689
 
4.0%
흡연실 484
 
2.8%
설치 483
 
2.8%
가능 483
 
2.8%
금연(실내외 481
 
2.8%
Other values (130) 3323
19.3%
2024-05-04T07:45:06.457383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
설 8417
13.1%
시 7953
12.4%
전 7254
11.3%
체 7251
11.3%
7226
11.3%
내 3165
 
4.9%
실 1758
 
2.7%
건 1545
 
2.4%
물 1537
 
2.4%
부 1251
 
2.0%
Other values (148) 16745
26.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54602
85.2%
Space Separator 7226
 
11.3%
Decimal Number 930
 
1.5%
Close Punctuation 506
 
0.8%
Open Punctuation 506
 
0.8%
Lowercase Letter 284
 
0.4%
Other Punctuation 39
 
0.1%
Math Symbol 7
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
설 8417
15.4%
시 7953
14.6%
전 7254
13.3%
체 7251
13.3%
내 3165
 
5.8%
실 1758
 
3.2%
건 1545
 
2.8%
물 1537
 
2.8%
부 1251
 
2.3%
연 1133
 
2.1%
Other values (132) 13338
24.4%
Decimal Number
ValueCountFrequency (%)
0 472
50.8%
1 393
42.3%
5 63
 
6.8%
2 2
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 502
99.2%
」 4
 
0.8%
Open Punctuation
ValueCountFrequency (%)
( 502
99.2%
「 4
 
0.8%
Lowercase Letter
ValueCountFrequency (%)
m 282
99.3%
ｍ 2
 
0.7%
Other Punctuation
ValueCountFrequency (%)
, 35
89.7%
· 4
 
10.3%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
L 1
50.0%
Space Separator
ValueCountFrequency (%)
7226
100.0%
Math Symbol
ValueCountFrequency (%)
+ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54602
85.2%
Common 9214
 
14.4%
Latin 286
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
설 8417
15.4%
시 7953
14.6%
전 7254
13.3%
체 7251
13.3%
내 3165
 
5.8%
실 1758
 
3.2%
건 1545
 
2.8%
물 1537
 
2.8%
부 1251
 
2.3%
연 1133
 
2.1%
Other values (132) 13338
24.4%
Common
ValueCountFrequency (%)
7226
78.4%
) 502
 
5.4%
( 502
 
5.4%
0 472
 
5.1%
1 393
 
4.3%
5 63
 
0.7%
, 35
 
0.4%
+ 7
 
0.1%
」 4
 
< 0.1%
「 4
 
< 0.1%
Other values (2) 6
 
0.1%
Latin
ValueCountFrequency (%)
m 282
98.6%
ｍ 2
 
0.7%
G 1
 
0.3%
L 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54602
85.2%
ASCII 9486
 
14.8%
None 14
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
설 8417
15.4%
시 7953
14.6%
전 7254
13.3%
체 7251
13.3%
내 3165
 
5.8%
실 1758
 
3.2%
건 1545
 
2.8%
물 1537
 
2.8%
부 1251
 
2.3%
연 1133
 
2.1%
Other values (132) 13338
24.4%
ASCII
ValueCountFrequency (%)
7226
76.2%
) 502
 
5.3%
( 502
 
5.3%
0 472
 
5.0%
1 393
 
4.1%
m 282
 
3.0%
5 63
 
0.7%
, 35
 
0.4%
+ 7
 
0.1%
2 2
 
< 0.1%
Other values (2) 2
 
< 0.1%
None
ValueCountFrequency (%)
」 4
28.6%
「 4
28.6%
· 4
28.6%
ｍ 2
14.3%

시도명
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
충청남도
2414 
울산광역시
1830 
경상북도
1422 
전북특별자치도
1356 
경기도
1227 
Other values (12)
1751 

Length

Max length7
Median length5
Mean length4.7135
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전북특별자치도
2nd row경상북도
3rd row울산광역시
4th row대구광역시
5th row경상북도

Common Values

ValueCountFrequency (%)
충청남도 2414
24.1%
울산광역시 1830
18.3%
경상북도 1422
14.2%
전북특별자치도 1356
13.6%
경기도 1227
12.3%
제주특별자치도 749
 
7.5%
서울특별시 322
 
3.2%
강원도 279
 
2.8%
전라남도 133
 
1.3%
대구광역시 93
 
0.9%
Other values (7) 175
 
1.8%

Length

2024-05-04T07:45:06.902405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충청남도 2414
24.1%
울산광역시 1830
18.3%
경상북도 1422
14.2%
전북특별자치도 1356
13.6%
경기도 1227
12.3%
제주특별자치도 749
 
7.5%
서울특별시 322
 
3.2%
강원도 279
 
2.8%
전라남도 133
 
1.3%
대구광역시 93
 
0.9%
Other values (7) 175
 
1.8%

시군구명
Text

Distinct61
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T07:45:07.427614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length2.9213
Min length2

Characters and Unicode

Total characters29213
Distinct characters70
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row익산시
2nd row성주군
3rd row중구
4th row동구
5th row포항시
ValueCountFrequency (%)
아산시 2256
22.4%
익산시 1316
13.1%
중구 1084
10.8%
경산시 895
 
8.9%
동구 749
 
7.4%
서귀포시 749
 
7.4%
양주시 566
 
5.6%
성주군 275
 
2.7%
군포시 217
 
2.2%
마포구 189
 
1.9%
Other values (54) 1762
17.5%
2024-05-04T07:45:08.495417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 7064
24.2%
산 4647
15.9%
구 2260
 
7.7%
아 2256
 
7.7%
익 1316
 
4.5%
포 1287
 
4.4%
중 1084
 
3.7%
군 1080
 
3.7%
주 1030
 
3.5%
경 1020
 
3.5%
Other values (60) 6169
21.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29155
99.8%
Space Separator 58
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 7064
24.2%
산 4647
15.9%
구 2260
 
7.8%
아 2256
 
7.7%
익 1316
 
4.5%
포 1287
 
4.4%
중 1084
 
3.7%
군 1080
 
3.7%
주 1030
 
3.5%
경 1020
 
3.5%
Other values (59) 6111
21.0%
Space Separator
ValueCountFrequency (%)
58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29155
99.8%
Common 58
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 7064
24.2%
산 4647
15.9%
구 2260
 
7.8%
아 2256
 
7.7%
익 1316
 
4.5%
포 1287
 
4.4%
중 1084
 
3.7%
군 1080
 
3.7%
주 1030
 
3.5%
경 1020
 
3.5%
Other values (59) 6111
21.0%
Common
ValueCountFrequency (%)
58
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29155
99.8%
ASCII 58
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 7064
24.2%
산 4647
15.9%
구 2260
 
7.8%
아 2256
 
7.7%
익 1316
 
4.5%
포 1287
 
4.4%
중 1084
 
3.7%
군 1080
 
3.7%
주 1030
 
3.5%
경 1020
 
3.5%
Other values (59) 6111
21.0%
ASCII
ValueCountFrequency (%)
58
100.0%

금연구역구분
Text

Distinct165
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T07:45:08.981194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length125
Median length36
Mean length5.8359
Min length2

Characters and Unicode

Total characters58359
Distinct characters183
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)0.4%

Sample

1st row음식점
2nd row액화석유가스의안전관리및사업법에따른가스충전소,판매소및석유및석유대체연료사업법에의한주유소
3rd row일반음식점
4th row공원
5th row체육시설
ValueCountFrequency (%)
음식점 2934
24.5%
일반음식점 989
 
8.2%
공중이용시설 895
 
7.5%
학원 511
 
4.3%
공장 392
 
3.3%
및 379
 
3.2%
어린이집 354
 
3.0%
의료기관 349
 
2.9%
복합건축물 315
 
2.6%
어린이놀이시설 308
 
2.6%
Other values (191) 4573
38.1%
2024-05-04T07:45:10.157373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 5370
 
9.2%
식 5091
 
8.7%
음 4977
 
8.5%
이 2410
 
4.1%
1999
 
3.4%
시 1955
 
3.3%
설 1912
 
3.3%
공 1611
 
2.8%
일 1418
 
2.4%
반 1418
 
2.4%
Other values (173) 30198
51.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54366
93.2%
Space Separator 1999
 
3.4%
Other Punctuation 1047
 
1.8%
Decimal Number 517
 
0.9%
Dash Punctuation 122
 
0.2%
Math Symbol 90
 
0.2%
Open Punctuation 72
 
0.1%
Close Punctuation 72
 
0.1%
Lowercase Letter 54
 
0.1%
Other Symbol 17
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 5370
 
9.9%
식 5091
 
9.4%
음 4977
 
9.2%
이 2410
 
4.4%
시 1955
 
3.6%
설 1912
 
3.5%
공 1611
 
3.0%
일 1418
 
2.6%
반 1418
 
2.6%
용 1380
 
2.5%
Other values (150) 26824
49.3%
Decimal Number
ValueCountFrequency (%)
1 223
43.1%
0 192
37.1%
4 39
 
7.5%
2 34
 
6.6%
3 17
 
3.3%
5 8
 
1.5%
6 4
 
0.8%
Other Punctuation
ValueCountFrequency (%)
/ 634
60.6%
, 387
37.0%
· 16
 
1.5%
. 10
 
1.0%
Lowercase Letter
ValueCountFrequency (%)
m 18
33.3%
c 18
33.3%
p 18
33.3%
Open Punctuation
ValueCountFrequency (%)
( 68
94.4%
「 4
 
5.6%
Close Punctuation
ValueCountFrequency (%)
) 68
94.4%
」 4
 
5.6%
Space Separator
ValueCountFrequency (%)
1999
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 122
100.0%
Math Symbol
ValueCountFrequency (%)
+ 90
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 17
100.0%
Uppercase Letter
ValueCountFrequency (%)
M 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54366
93.2%
Common 3936
 
6.7%
Latin 57
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 5370
 
9.9%
식 5091
 
9.4%
음 4977
 
9.2%
이 2410
 
4.4%
시 1955
 
3.6%
설 1912
 
3.5%
공 1611
 
3.0%
일 1418
 
2.6%
반 1418
 
2.6%
용 1380
 
2.5%
Other values (150) 26824
49.3%
Common
ValueCountFrequency (%)
1999
50.8%
/ 634
 
16.1%
, 387
 
9.8%
1 223
 
5.7%
0 192
 
4.9%
- 122
 
3.1%
+ 90
 
2.3%
( 68
 
1.7%
) 68
 
1.7%
4 39
 
1.0%
Other values (9) 114
 
2.9%
Latin
ValueCountFrequency (%)
m 18
31.6%
c 18
31.6%
p 18
31.6%
M 3
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54366
93.2%
ASCII 3952
 
6.8%
None 24
 
< 0.1%
CJK Compat 17
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 5370
 
9.9%
식 5091
 
9.4%
음 4977
 
9.2%
이 2410
 
4.4%
시 1955
 
3.6%
설 1912
 
3.5%
공 1611
 
3.0%
일 1418
 
2.6%
반 1418
 
2.6%
용 1380
 
2.5%
Other values (150) 26824
49.3%
ASCII
ValueCountFrequency (%)
1999
50.6%
/ 634
 
16.0%
, 387
 
9.8%
1 223
 
5.6%
0 192
 
4.9%
- 122
 
3.1%
+ 90
 
2.3%
( 68
 
1.7%
) 68
 
1.7%
4 39
 
1.0%
Other values (9) 130
 
3.3%
CJK Compat
ValueCountFrequency (%)
㎡ 17
100.0%
None
ValueCountFrequency (%)
· 16
66.7%
「 4
 
16.7%
」 4
 
16.7%

금연구역지정근거명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct41
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
국민건강증진법 제9조
5664 
국민건강증진법제9조
2348 
국민건강증진법
1302 
서울특별시 강서구 간접흡연 피해 방지 조례 제5조
 
89
경산시 간접흡연 방지 등에 관한 조례
 
70
Other values (36)
 
527

Length

Max length46
Median length11
Mean length11.189
Min length7

Unique

Unique9 ?
Unique (%)0.1%

Sample

1st row국민건강증진법제9조
2nd row성주군금연환경조성및간접흡연피해방지조례 제4조
3rd row국민건강증진법 제9조
4th row대구광역시 동구 금연환경조성 및 간접흡연 피해방지 조례
5th row국민건강증진법 제9조

Common Values

ValueCountFrequency (%)
국민건강증진법 제9조 5664
56.6%
국민건강증진법제9조 2348
23.5%
국민건강증진법 1302
 
13.0%
서울특별시 강서구 간접흡연 피해 방지 조례 제5조 89
 
0.9%
경산시 간접흡연 방지 등에 관한 조례 70
 
0.7%
국민건강증진법 제9조제4항 65
 
0.7%
대구광역시 동구 금연환경조성 및 간접흡연 피해방지 조례 58
 
0.6%
울산광역시동구 금연 환경조성 및 간접흡연 피해방지 조례 제4조 45
 
0.4%
성주군금연환경조성및간접흡연피해방지조례 제4조 44
 
0.4%
아산시 금연환경 조성 및 간접흡연 피해방지 조례 제3조 41
 
0.4%
Other values (31) 274
 
2.7%

Length

2024-05-04T07:45:10.627695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
국민건강증진법 7112
38.0%
제9조 5719
30.6%
국민건강증진법제9조 2348
 
12.5%
조례 424
 
2.3%
간접흡연 415
 
2.2%
및 297
 
1.6%
피해방지 242
 
1.3%
방지 170
 
0.9%
서울특별시 110
 
0.6%
제5조 109
 
0.6%
Other values (62) 1769
 
9.5%

금연구역면적
Real number (ℝ)

MISSING 

Distinct441
Distinct (%)70.9%
Missing9378
Missing (%)93.8%
Infinite0
Infinite (%)0.0%
Mean1451.3843
Minimum0
Maximum85610
Zeros15
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T07:45:11.095862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q138.26
median100
Q3882.425
95-th percentile4369.338
Maximum85610
Range85610
Interquartile range (IQR)844.165

Descriptive statistics

Standard deviation6219.7669
Coefficient of variation (CV)4.2854033
Kurtosis102.88429
Mean1451.3843
Median Absolute Deviation (MAD)75.815
Skewness9.2079935
Sum902761.02
Variance38685500
MonotonicityNot monotonic
2024-05-04T07:45:11.487701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 55
 
0.5%
10.0 27
 
0.3%
1.0 27
 
0.3%
50.0 17
 
0.2%
0.0 15
 
0.1%
200.0 12
 
0.1%
30.0 10
 
0.1%
60.0 4
 
< 0.1%
75.0 3
 
< 0.1%
59.0 3
 
< 0.1%
Other values (431) 449
 
4.5%
(Missing) 9378
93.8%
ValueCountFrequency (%)
0.0 15
0.1%
1.0 27
0.3%
1.5 1
 
< 0.1%
2.36 1
 
< 0.1%
2.4 1
 
< 0.1%
2.53 2
 
< 0.1%
2.67 1
 
< 0.1%
3.0 2
 
< 0.1%
3.06 1
 
< 0.1%
3.3 1
 
< 0.1%
ValueCountFrequency (%)
85610.0 1
< 0.1%
79160.0 1
< 0.1%
46961.0 1
< 0.1%
39489.0 1
< 0.1%
37398.0 1
< 0.1%
31871.44 1
< 0.1%
31762.57 1
< 0.1%
28751.0 1
< 0.1%
21600.0 1
< 0.1%
18517.0 1
< 0.1%

위반과태료
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct11
Distinct (%)0.1%
Missing1688
Missing (%)16.9%
Infinite0
Infinite (%)0.0%
Mean97204.059
Minimum20000
Maximum100000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T07:45:11.849036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000
5-th percentile100000
Q1100000
median100000
Q3100000
95-th percentile100000
Maximum100000
Range80000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation13218.675
Coefficient of variation (CV)0.13598892
Kurtosis22.201255
Mean97204.059
Median Absolute Deviation (MAD)0
Skewness-4.7891858
Sum8.0796014 × 108
Variance1.7473338 × 108
MonotonicityNot monotonic
2024-05-04T07:45:12.143900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
100000 7936
79.4%
50000 220
 
2.2%
20000 148
 
1.5%
50019 1
 
< 0.1%
50011 1
 
< 0.1%
50023 1
 
< 0.1%
50007 1
 
< 0.1%
50022 1
 
< 0.1%
50024 1
 
< 0.1%
50005 1
 
< 0.1%
(Missing) 1688
 
16.9%
ValueCountFrequency (%)
20000 148
1.5%
50000 220
2.2%
50005 1
 
< 0.1%
50007 1
 
< 0.1%
50011 1
 
< 0.1%
50019 1
 
< 0.1%
50022 1
 
< 0.1%
50023 1
 
< 0.1%
50024 1
 
< 0.1%
50025 1
 
< 0.1%
ValueCountFrequency (%)
100000 7936
79.4%
50025 1
 
< 0.1%
50024 1
 
< 0.1%
50023 1
 
< 0.1%
50022 1
 
< 0.1%
50019 1
 
< 0.1%
50011 1
 
< 0.1%
50007 1
 
< 0.1%
50005 1
 
< 0.1%
50000 220
 
2.2%

위반신고전화번호
Text

MISSING 

Distinct74
Distinct (%)0.9%
Missing1540
Missing (%)15.4%
Memory size156.2 KiB
2024-05-04T07:45:12.620145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.069976
Min length11

Characters and Unicode

Total characters102112
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

Unique18 ?
Unique (%)0.2%

Sample

1st row054-930-8133
2nd row052-290-4300
3rd row053-662-3214
4th row054-270-4056
5th row041-537-3344
ValueCountFrequency (%)
041-537-3344 2256
26.7%
052-290-4300 1067
12.6%
053-810-6353 895
 
10.6%
052-209-6936 689
 
8.1%
031-8082-4342 566
 
6.7%
064-760-6043 432
 
5.1%
054-930-8133 275
 
3.3%
064-760-6123 249
 
2.9%
031-390-0825 217
 
2.6%
02-3153-9089 189
 
2.2%
Other values (64) 1625
19.2%
2024-05-04T07:45:13.598677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 17423
17.1%
- 16920
16.6%
3 16656
16.3%
4 12011
11.8%
5 8862
8.7%
2 7021
6.9%
6 6302
 
6.2%
1 5620
 
5.5%
9 3899
 
3.8%
7 3855
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 85192
83.4%
Dash Punctuation 16920
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17423
20.5%
3 16656
19.6%
4 12011
14.1%
5 8862
10.4%
2 7021
8.2%
6 6302
 
7.4%
1 5620
 
6.6%
9 3899
 
4.6%
7 3855
 
4.5%
8 3543
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 16920
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 102112
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 17423
17.1%
- 16920
16.6%
3 16656
16.3%
4 12011
11.8%
5 8862
8.7%
2 7021
6.9%
6 6302
 
6.2%
1 5620
 
5.5%
9 3899
 
3.8%
7 3855
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 102112
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 17423
17.1%
- 16920
16.6%
3 16656
16.3%
4 12011
11.8%
5 8862
8.7%
2 7021
6.9%
6 6302
 
6.2%
1 5620
 
5.5%
9 3899
 
3.8%
7 3855
 
3.8%

소재지도로명주소
Text

MISSING 

Distinct8911
Distinct (%)91.3%
Missing240
Missing (%)2.4%
Memory size156.2 KiB
2024-05-04T07:45:15.485656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length56
Mean length24.502971
Min length12

Characters and Unicode

Total characters239149
Distinct characters580
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

Unique8326 ?
Unique (%)85.3%

Sample

1st row전북특별자치도 익산시 하나로 1길 40-10 (영등동,(1층))
2nd row경상북도 성주군 선남면 성주로 3468
3rd row울산광역시 중구 염포로 60, 1층 (반구동)
4th row경상북도 포항시 남구 상공로 43
5th row충청남도 아산시 둔포면 아산밸리로388번길 48-8
ValueCountFrequency (%)
충청남도 2407
 
4.7%
아산시 2256
 
4.4%
울산광역시 1762
 
3.4%
경상북도 1422
 
2.8%
전북특별자치도 1356
 
2.6%
익산시 1317
 
2.6%
경기도 1133
 
2.2%
중구 1084
 
2.1%
1층 914
 
1.8%
경산시 895
 
1.7%
Other values (7438) 37029
71.8%
2024-05-04T07:45:17.228435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
41815
 
17.5%
1 9500
 
4.0%
시 9376
 
3.9%
산 8287
 
3.5%
도 7859
 
3.3%
로 7591
 
3.2%
동 6162
 
2.6%
2 5593
 
2.3%
) 4686
 
2.0%
( 4685
 
2.0%
Other values (570) 133595
55.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 144899
60.6%
Space Separator 41815
 
17.5%
Decimal Number 37602
 
15.7%
Close Punctuation 4688
 
2.0%
Open Punctuation 4687
 
2.0%
Other Punctuation 3022
 
1.3%
Dash Punctuation 2225
 
0.9%
Uppercase Letter 167
 
0.1%
Math Symbol 23
 
< 0.1%
Lowercase Letter 20
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 9376
 
6.5%
산 8287
 
5.7%
도 7859
 
5.4%
로 7591
 
5.2%
동 6162
 
4.3%
길 4638
 
3.2%
경 3855
 
2.7%
남 3731
 
2.6%
북 3151
 
2.2%
아 2781
 
1.9%
Other values (518) 87468
60.4%
Uppercase Letter
ValueCountFrequency (%)
A 55
32.9%
B 24
14.4%
S 14
 
8.4%
T 10
 
6.0%
C 9
 
5.4%
G 9
 
5.4%
D 6
 
3.6%
M 6
 
3.6%
I 5
 
3.0%
P 5
 
3.0%
Other values (10) 24
14.4%
Decimal Number
ValueCountFrequency (%)
1 9500
25.3%
2 5593
14.9%
3 4132
11.0%
4 3326
 
8.8%
5 2949
 
7.8%
0 2890
 
7.7%
6 2527
 
6.7%
7 2420
 
6.4%
8 2268
 
6.0%
9 1997
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
e 12
60.0%
b 1
 
5.0%
r 1
 
5.0%
o 1
 
5.0%
a 1
 
5.0%
d 1
 
5.0%
h 1
 
5.0%
l 1
 
5.0%
i 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 2997
99.2%
. 13
 
0.4%
， 10
 
0.3%
@ 1
 
< 0.1%
· 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 4686
> 99.9%
] 2
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 4685
> 99.9%
[ 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
41815
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2225
100.0%
Math Symbol
ValueCountFrequency (%)
~ 23
100.0%
Letter Number
ValueCountFrequency (%)
Ⅲ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 144899
60.6%
Common 94062
39.3%
Latin 188
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 9376
 
6.5%
산 8287
 
5.7%
도 7859
 
5.4%
로 7591
 
5.2%
동 6162
 
4.3%
길 4638
 
3.2%
경 3855
 
2.7%
남 3731
 
2.6%
북 3151
 
2.2%
아 2781
 
1.9%
Other values (518) 87468
60.4%
Latin
ValueCountFrequency (%)
A 55
29.3%
B 24
12.8%
S 14
 
7.4%
e 12
 
6.4%
T 10
 
5.3%
C 9
 
4.8%
G 9
 
4.8%
D 6
 
3.2%
M 6
 
3.2%
I 5
 
2.7%
Other values (20) 38
20.2%
Common
ValueCountFrequency (%)
41815
44.5%
1 9500
 
10.1%
2 5593
 
5.9%
) 4686
 
5.0%
( 4685
 
5.0%
3 4132
 
4.4%
4 3326
 
3.5%
, 2997
 
3.2%
5 2949
 
3.1%
0 2890
 
3.1%
Other values (12) 11489
 
12.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 144897
60.6%
ASCII 94238
39.4%
None 11
 
< 0.1%
Compat Jamo 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
41815
44.4%
1 9500
 
10.1%
2 5593
 
5.9%
) 4686
 
5.0%
( 4685
 
5.0%
3 4132
 
4.4%
4 3326
 
3.5%
, 2997
 
3.2%
5 2949
 
3.1%
0 2890
 
3.1%
Other values (39) 11665
 
12.4%
Hangul
ValueCountFrequency (%)
시 9376
 
6.5%
산 8287
 
5.7%
도 7859
 
5.4%
로 7591
 
5.2%
동 6162
 
4.3%
길 4638
 
3.2%
경 3855
 
2.7%
남 3731
 
2.6%
북 3151
 
2.2%
아 2781
 
1.9%
Other values (517) 87466
60.4%
None
ValueCountFrequency (%)
， 10
90.9%
· 1
 
9.1%
Compat Jamo
ValueCountFrequency (%)
ㅡ 2
100.0%
Number Forms
ValueCountFrequency (%)
Ⅲ 1
100.0%

소재지지번주소
Text

MISSING 

Distinct3079
Distinct (%)84.6%
Missing6362
Missing (%)63.6%
Memory size156.2 KiB
2024-05-04T07:45:18.385415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length40
Mean length20.489555
Min length11

Characters and Unicode

Total characters74541
Distinct characters302
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2757 ?
Unique (%)75.8%

Sample

1st row대구광역시 동구 신기동 1526번지
2nd row경상북도 포항시 남구 상도동 629
3rd row충청남도 아산시 둔포면 석곡리 1948
4th row충청남도 부여군 홍산면 북촌리 246-21
5th row충청남도 아산시 온천동 554
ValueCountFrequency (%)
충청남도 2315
 
13.5%
아산시 2256
 
13.1%
배방읍 381
 
2.2%
경상북도 369
 
2.1%
온천동 280
 
1.6%
경기도 250
 
1.5%
둔포면 246
 
1.4%
강원도 210
 
1.2%
음봉면 170
 
1.0%
탕정면 165
 
1.0%
Other values (3657) 10569
61.4%
2024-05-04T07:45:20.190534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13573
 
18.2%
도 3489
 
4.7%
시 3205
 
4.3%
1 2856
 
3.8%
산 2816
 
3.8%
남 2720
 
3.6%
청 2349
 
3.2%
충 2335
 
3.1%
아 2295
 
3.1%
- 2271
 
3.0%
Other values (292) 36632
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 44252
59.4%
Decimal Number 14387
 
19.3%
Space Separator 13573
 
18.2%
Dash Punctuation 2271
 
3.0%
Other Punctuation 38
 
0.1%
Close Punctuation 6
 
< 0.1%
Open Punctuation 6
 
< 0.1%
Uppercase Letter 5
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 3489
 
7.9%
시 3205
 
7.2%
산 2816
 
6.4%
남 2720
 
6.1%
청 2349
 
5.3%
충 2335
 
5.3%
아 2295
 
5.2%
리 2144
 
4.8%
동 1865
 
4.2%
면 1277
 
2.9%
Other values (271) 19757
44.6%
Decimal Number
ValueCountFrequency (%)
1 2856
19.9%
2 1884
13.1%
3 1522
10.6%
5 1394
9.7%
4 1387
9.6%
6 1193
8.3%
7 1131
 
7.9%
8 1065
 
7.4%
0 1009
 
7.0%
9 946
 
6.6%
Uppercase Letter
ValueCountFrequency (%)
L 1
20.0%
B 1
20.0%
J 1
20.0%
N 1
20.0%
A 1
20.0%
Space Separator
ValueCountFrequency (%)
13573
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2271
100.0%
Other Punctuation
ValueCountFrequency (%)
, 38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 44252
59.4%
Common 30284
40.6%
Latin 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 3489
 
7.9%
시 3205
 
7.2%
산 2816
 
6.4%
남 2720
 
6.1%
청 2349
 
5.3%
충 2335
 
5.3%
아 2295
 
5.2%
리 2144
 
4.8%
동 1865
 
4.2%
면 1277
 
2.9%
Other values (271) 19757
44.6%
Common
ValueCountFrequency (%)
13573
44.8%
1 2856
 
9.4%
- 2271
 
7.5%
2 1884
 
6.2%
3 1522
 
5.0%
5 1394
 
4.6%
4 1387
 
4.6%
6 1193
 
3.9%
7 1131
 
3.7%
8 1065
 
3.5%
Other values (6) 2008
 
6.6%
Latin
ValueCountFrequency (%)
L 1
20.0%
B 1
20.0%
J 1
20.0%
N 1
20.0%
A 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 44250
59.4%
ASCII 30289
40.6%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13573
44.8%
1 2856
 
9.4%
- 2271
 
7.5%
2 1884
 
6.2%
3 1522
 
5.0%
5 1394
 
4.6%
4 1387
 
4.6%
6 1193
 
3.9%
7 1131
 
3.7%
8 1065
 
3.5%
Other values (11) 2013
 
6.6%
Hangul
ValueCountFrequency (%)
도 3489
 
7.9%
시 3205
 
7.2%
산 2816
 
6.4%
남 2720
 
6.1%
청 2349
 
5.3%
충 2335
 
5.3%
아 2295
 
5.2%
리 2144
 
4.8%
동 1865
 
4.2%
면 1277
 
2.9%
Other values (270) 19755
44.6%
Compat Jamo
ValueCountFrequency (%)
ㅡ 2
100.0%

관리기관명
Text

Distinct85
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T07:45:20.901113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length9.416
Min length3

Characters and Unicode

Total characters94160
Distinct characters167
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)0.2%

Sample

1st row전북특별자치도 익산시
2nd row경상북도 성주군
3rd row울산광역시 중구보건소
4th row대구광역시 동구청
5th row포항시 남구보건소
ValueCountFrequency (%)
충청남도 2414
12.3%
아산시 2256
 
11.5%
울산광역시 1830
 
9.3%
전북특별자치도 1356
 
6.9%
익산시 1316
 
6.7%
경상북도 1305
 
6.7%
중구보건소 1067
 
5.4%
경산시청 895
 
4.6%
서귀포시 749
 
3.8%
동구청 749
 
3.8%
Other values (101) 5667
28.9%
2024-05-04T07:45:22.258280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9604
 
10.2%
시 9395
 
10.0%
산 6715
 
7.1%
도 5976
 
6.3%
청 5087
 
5.4%
건 3550
 
3.8%
보 3505
 
3.7%
소 3495
 
3.7%
경 2798
 
3.0%
북 2739
 
2.9%
Other values (157) 41296
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 84542
89.8%
Space Separator 9604
 
10.2%
Uppercase Letter 6
 
< 0.1%
Open Punctuation 4
 
< 0.1%
Close Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 9395
 
11.1%
산 6715
 
7.9%
도 5976
 
7.1%
청 5087
 
6.0%
건 3550
 
4.2%
보 3505
 
4.1%
소 3495
 
4.1%
경 2798
 
3.3%
북 2739
 
3.2%
남 2727
 
3.2%
Other values (149) 38555
45.6%
Uppercase Letter
ValueCountFrequency (%)
R 2
33.3%
O 1
16.7%
C 1
16.7%
A 1
16.7%
T 1
16.7%
Space Separator
ValueCountFrequency (%)
9604
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 84542
89.8%
Common 9612
 
10.2%
Latin 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 9395
 
11.1%
산 6715
 
7.9%
도 5976
 
7.1%
청 5087
 
6.0%
건 3550
 
4.2%
보 3505
 
4.1%
소 3495
 
4.1%
경 2798
 
3.3%
북 2739
 
3.2%
남 2727
 
3.2%
Other values (149) 38555
45.6%
Latin
ValueCountFrequency (%)
R 2
33.3%
O 1
16.7%
C 1
16.7%
A 1
16.7%
T 1
16.7%
Common
ValueCountFrequency (%)
9604
99.9%
( 4
 
< 0.1%
) 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 84542
89.8%
ASCII 9618
 
10.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9604
99.9%
( 4
 
< 0.1%
) 4
 
< 0.1%
R 2
 
< 0.1%
O 1
 
< 0.1%
C 1
 
< 0.1%
A 1
 
< 0.1%
T 1
 
< 0.1%
Hangul
ValueCountFrequency (%)
시 9395
 
11.1%
산 6715
 
7.9%
도 5976
 
7.1%
청 5087
 
6.0%
건 3550
 
4.2%
보 3505
 
4.1%
소 3495
 
4.1%
경 2798
 
3.3%
북 2739
 
3.2%
남 2727
 
3.2%
Other values (149) 38555
45.6%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct8688
Distinct (%)86.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.173341
Minimum33.222683
Maximum38.268509
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T07:45:22.808629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.222683
5-th percentile33.279284
Q135.568556
median35.960325
Q336.808419
95-th percentile37.823413
Maximum38.268509
Range5.0458256
Interquartile range (IQR)1.2398628

Descriptive statistics

Standard deviation1.1212829
Coefficient of variation (CV)0.030997492
Kurtosis1.0263788
Mean36.173341
Median Absolute Deviation (MAD)0.77156316
Skewness-0.82501343
Sum361733.41
Variance1.2572753
MonotonicityNot monotonic
2024-05-04T07:45:23.267835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.7992434403 22
 
0.2%
36.8289124607 16
 
0.2%
36.7974341806 13
 
0.1%
36.9238644899 10
 
0.1%
36.8428033467 10
 
0.1%
36.8410356275 9
 
0.1%
36.7683426903 8
 
0.1%
36.7974485914 7
 
0.1%
35.82746315 7
 
0.1%
37.600511 7
 
0.1%
Other values (8678) 9891
98.9%
ValueCountFrequency (%)
33.22268298 1
< 0.1%
33.22284782 1
< 0.1%
33.22566433 1
< 0.1%
33.22591979 1
< 0.1%
33.2259634 1
< 0.1%
33.22651574 1
< 0.1%
33.22784181 1
< 0.1%
33.22785244 2
< 0.1%
33.22792593 1
< 0.1%
33.2283676 1
< 0.1%
ValueCountFrequency (%)
38.26850861 1
< 0.1%
38.26531691 1
< 0.1%
38.2491978 1
< 0.1%
38.2485247 1
< 0.1%
38.24404542 1
< 0.1%
38.24348719 2
< 0.1%
38.24340756 1
< 0.1%
38.24131471 1
< 0.1%
38.24117602 1
< 0.1%
38.24111456 1
< 0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct8683
Distinct (%)86.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.69441
Minimum126.25118
Maximum129.55565
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T07:45:23.694988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.25118
5-th percentile126.59668
Q1126.95757
median127.05521
Q3128.75032
95-th percentile129.42173
Maximum129.55565
Range3.3044769
Interquartile range (IQR)1.7927475

Descriptive statistics

Standard deviation1.031095
Coefficient of variation (CV)0.008074707
Kurtosis-1.2621202
Mean127.69441
Median Absolute Deviation (MAD)0.16775297
Skewness0.68923902
Sum1276944.1
Variance1.0631569
MonotonicityNot monotonic
2024-05-04T07:45:24.032778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0601264087 22
 
0.2%
127.100270575 16
 
0.2%
127.1092405602 13
 
0.1%
127.0745914139 10
 
0.1%
127.0560864265 10
 
0.1%
127.085713545 9
 
0.1%
127.0833999521 8
 
0.1%
126.933571 7
 
0.1%
127.1057587933 7
 
0.1%
127.0552075097 7
 
0.1%
Other values (8673) 9891
98.9%
ValueCountFrequency (%)
126.2511773 1
< 0.1%
126.2517118 1
< 0.1%
126.2519751 1
< 0.1%
126.253001 1
< 0.1%
126.2589697 1
< 0.1%
126.2714057 1
< 0.1%
126.2803435 1
< 0.1%
126.2886195 1
< 0.1%
126.2896197 2
< 0.1%
126.2903056 1
< 0.1%
ValueCountFrequency (%)
129.5556542 1
< 0.1%
129.5555261 1
< 0.1%
129.5537136 1
< 0.1%
129.5175787 1
< 0.1%
129.4577169 1
< 0.1%
129.457616 1
< 0.1%
129.457377 1
< 0.1%
129.4572006 2
< 0.1%
129.457118 1
< 0.1%
129.4570342 1
< 0.1%

데이터기준일자
Date

Distinct57
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2019-09-19 00:00:00
Maximum2024-04-03 00:00:00
2024-05-04T07:45:24.746989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:45:25.143290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

제공기관코드
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size156.2 KiB

제공기관명
Text

Distinct64
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T07:45:25.799793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length8.6164
Min length7

Characters and Unicode

Total characters86164
Distinct characters83
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row전북특별자치도 익산시
2nd row경상북도 성주군
3rd row울산광역시 중구
4th row대구광역시 동구
5th row경상북도 포항시
ValueCountFrequency (%)
충청남도 2414
12.1%
아산시 2256
11.3%
울산광역시 1830
 
9.2%
경상북도 1422
 
7.1%
전북특별자치도 1360
 
6.8%
익산시 1316
 
6.6%
경기도 1227
 
6.1%
중구 1084
 
5.4%
경산시 895
 
4.5%
동구 749
 
3.7%
Other values (65) 5435
27.2%
2024-05-04T07:45:26.820745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9988
 
11.6%
시 9363
 
10.9%
도 7689
 
8.9%
산 6485
 
7.5%
경 3697
 
4.3%
북 2862
 
3.3%
남 2648
 
3.1%
청 2442
 
2.8%
충 2442
 
2.8%
별 2440
 
2.8%
Other values (73) 36108
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 76176
88.4%
Space Separator 9988
 
11.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 9363
 
12.3%
도 7689
 
10.1%
산 6485
 
8.5%
경 3697
 
4.9%
북 2862
 
3.8%
남 2648
 
3.5%
청 2442
 
3.2%
충 2442
 
3.2%
별 2440
 
3.2%
특 2440
 
3.2%
Other values (72) 33668
44.2%
Space Separator
ValueCountFrequency (%)
9988
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 76176
88.4%
Common 9988
 
11.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 9363
 
12.3%
도 7689
 
10.1%
산 6485
 
8.5%
경 3697
 
4.9%
북 2862
 
3.8%
남 2648
 
3.5%
청 2442
 
3.2%
충 2442
 
3.2%
별 2440
 
3.2%
특 2440
 
3.2%
Other values (72) 33668
44.2%
Common
ValueCountFrequency (%)
9988
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 76176
88.4%
ASCII 9988
 
11.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9988
100.0%
Hangul
ValueCountFrequency (%)
시 9363
 
12.3%
도 7689
 
10.1%
산 6485
 
8.5%
경 3697
 
4.9%
북 2862
 
3.8%
남 2648
 
3.5%
청 2442
 
3.2%
충 2442
 
3.2%
별 2440
 
3.2%
특 2440
 
3.2%
Other values (72) 33668
44.2%

Interactions

2024-05-04T07:44:59.260368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:44:55.326983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:44:56.662675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:44:57.858256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:44:59.661857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:44:55.695012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:44:56.949007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:44:58.111482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:45:00.171082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:44:56.041955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:44:57.271162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:44:58.548226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:45:00.640194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:44:56.348425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:44:57.572278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:44:58.912138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T07:45:27.115568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
금연구역범위상세시도명시군구명금연구역지정근거명금연구역면적위반과태료위반신고전화번호관리기관명위도경도데이터기준일자제공기관명
금연구역범위상세1.0000.9610.9940.9940.6640.9830.9940.9930.8800.8930.9940.995
시도명0.9611.0000.9970.9500.2020.3640.9991.0000.9540.8880.9961.000
시군구명0.9940.9971.0000.9860.4830.5891.0001.0000.9890.9870.9991.000
금연구역지정근거명0.9940.9500.9861.0000.5751.0000.9910.9920.8120.8270.9850.991
금연구역면적0.6640.2020.4830.5751.0000.2010.5840.4760.1970.0970.4510.476
위반과태료0.9830.3640.5891.0000.2011.0000.6000.6090.1610.2700.5480.627
위반신고전화번호0.9940.9991.0000.9910.5840.6001.0000.9990.9910.9921.0001.000
관리기관명0.9931.0001.0000.9920.4760.6090.9991.0000.9920.9931.0001.000
위도0.8800.9540.9890.8120.1970.1610.9910.9921.0000.8170.9850.991
경도0.8930.8880.9870.8270.0970.2700.9920.9930.8171.0000.9800.988
데이터기준일자0.9940.9960.9990.9850.4510.5481.0001.0000.9850.9801.0001.000
제공기관명0.9951.0001.0000.9910.4760.6271.0001.0000.9910.9881.0001.000
2024-05-04T07:45:27.506907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도명금연구역지정근거명
시도명1.0000.635
금연구역지정근거명0.6351.000
2024-05-04T07:45:27.743892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
금연구역면적위반과태료위도경도시도명금연구역지정근거명
금연구역면적1.0000.0350.322-0.1020.1000.302
위반과태료0.0351.000-0.020-0.0790.4520.972
위도0.322-0.0201.000-0.2870.7970.458
경도-0.102-0.079-0.2871.0000.6170.458
시도명0.1000.4520.7970.6171.0000.635
금연구역지정근거명0.3020.9720.4580.4580.6351.000

Missing values

2024-05-04T07:45:01.194957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T07:45:02.053832image/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.
2024-05-04T07:45:02.529087image/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

금연구역명금연구역범위상세시도명시군구명금연구역구분금연구역지정근거명금연구역면적위반과태료위반신고전화번호소재지도로명주소소재지지번주소관리기관명위도경도데이터기준일자제공기관코드제공기관명
2811들머리 고향순대시설전체전북특별자치도익산시음식점국민건강증진법제9조<NA><NA><NA>전북특별자치도 익산시 하나로 1길 40-10 (영등동,(1층))<NA>전북특별자치도 익산시35.959924126.9774232024-02-224681000전북특별자치도 익산시
26805성주관광주유소시설전체경상북도성주군액화석유가스의안전관리및사업법에따른가스충전소,판매소및석유및석유대체연료사업법에의한주유소성주군금연환경조성및간접흡연피해방지조례 제4조<NA>20000054-930-8133경상북도 성주군 선남면 성주로 3468<NA>경상북도 성주군35.916585128.3128372020-07-155210000경상북도 성주군
23289아지매시락국밥시설전체울산광역시중구일반음식점국민건강증진법 제9조<NA>100000052-290-4300울산광역시 중구 염포로 60, 1층 (반구동)<NA>울산광역시 중구보건소35.560495129.3477382024-01-053690000울산광역시 중구
30759비비추어린이공원공원전체대구광역시동구공원대구광역시 동구 금연환경조성 및 간접흡연 피해방지 조례1514.020000053-662-3214<NA>대구광역시 동구 신기동 1526번지대구광역시 동구청35.869596128.7046482023-04-053420000대구광역시 동구
944상대당구장시설전체경상북도포항시체육시설국민건강증진법 제9조<NA>100000054-270-4056경상북도 포항시 남구 상공로 43경상북도 포항시 남구 상도동 629포항시 남구보건소36.012627129.3561432023-03-295020000경상북도 포항시
38793사무용건축물, 공장 및 복합건축물시설전체충청남도아산시사무용건축물, 공장 및 복합건축물국민건강증진법 제9조<NA>100000041-537-3344충청남도 아산시 둔포면 아산밸리로388번길 48-8충청남도 아산시 둔포면 석곡리 1948충청남도 아산시36.906765127.0568512023-03-214520000충청남도 아산시
33094새별어린이집 놀이터시설전체충청남도부여군어린이놀이시설국민건강증진법 제9조<NA>100000041-830-8642충청남도 부여군 홍산면 태봉산길 38충청남도 부여군 홍산면 북촌리 246-21충청남도 부여군청36.219344126.7581242022-12-144570000충청남도 부여군
9810아이숲어린이집시설전체전북특별자치도익산시어린이집국민건강증진법제9조<NA><NA><NA>전북특별자치도 익산시 오산면 선화로 42-12 장신휴먼시아2단지 내 관리동<NA>전북특별자치도 익산시35.948516126.9320152024-02-224681000전북특별자치도 익산시
35353프리카페(free카페)시설전체충청남도아산시음식점국민건강증진법 제9조<NA>100000041-537-3344충청남도 아산시 시민로 308충청남도 아산시 온천동 554충청남도 아산시36.777214126.99642023-03-214520000충청남도 아산시
42629동그라미어린이집시설의 경계선으로부터 10미터 이내의 구역제주특별자치도서귀포시어린이집국민건강증진법제9조<NA>100000064-760-6043제주특별자치도 서귀포시 홍중로 92<NA>서귀포시 서귀포보건소33.260709126.5558642023-01-016520000제주특별자치도 서귀포시
금연구역명금연구역범위상세시도명시군구명금연구역구분금연구역지정근거명금연구역면적위반과태료위반신고전화번호소재지도로명주소소재지지번주소관리기관명위도경도데이터기준일자제공기관코드제공기관명
23512이안서가수미술학원시설전체울산광역시중구학원국민건강증진법 제9조<NA>100000052-290-4300울산광역시 중구 종가4길 9 , 201호 (유곡동)<NA>울산광역시 중구보건소35.560338129.2955792024-01-053690000울산광역시 중구
23509동원시설전체울산광역시중구일반음식점국민건강증진법 제9조<NA>100000052-290-4300울산광역시 중구 해오름2길 6, 1층 (남외동)<NA>울산광역시 중구보건소35.5603129.3445312024-01-053690000울산광역시 중구
25795관서피아노교습소시설전체서울특별시마포구학교교과보습학원국민건강증진법제9조<NA>10000002-3153-9089서울특별시 마포구 마포대로19길12 4층 (아현동)<NA>서울특별시 마포구청37.54982126.9352672023-09-063130000서울특별시 마포구
33152연세정이비인후과의원시설전체경기도평택시의료기관국민건강증진법 제9조<NA>100000031-8024-4413경기도 평택시 평남로 937, 폴리프라자 5층 504호 (비전동)<NA>경기도 평택시청37.004394127.1044592024-02-163910000경기도 평택시
8916꽃바위 동해반점시설실내 또는 해당부지울산광역시동구음식점국민건강증진법 제9조<NA>100000052-209-6936울산광역시 동구 꽃바위3길 63 (방어동)<NA>울산광역시 동구청35.483811129.4132212024-02-063710000울산광역시 동구
42611동카름엔황금농장시설전체제주특별자치도서귀포시일반음식점/휴게음식점/제과점국민건강증진법제9조<NA>100000064-760-6043제주특별자치도 서귀포시 월평하원로 12<NA>서귀포시 서귀포보건소33.243389126.460522023-01-016520000제주특별자치도 서귀포시
10361비엠에스음악학원시설전체서울특별시마포구학교교과보습학원국민건강증진법제9조<NA>10000002-3153-9089서울특별시 마포구 상암산로1길 77 상암타워클리닉5층 (상암동)<NA>서울특별시 마포구청37.55459126.9307172023-09-063130000서울특별시 마포구
24114할리스 시화점시설전체경기도시흥시음식점국민건강증진법 제9조<NA><NA><NA>경기도 시흥시 중심상가4길 10, 104,105,106호 (정왕동)<NA>경기도 시흥시청37.344476126.7382512023-12-084010000경기도 시흥시
39054지에스25성산신양점시설전체제주특별자치도서귀포시휴게음식점국민건강증진법제9조<NA>100000064-760-6123제주특별자치도 서귀포시 성산읍 섭지코지로 26번길 6<NA>서귀포시 동부보건소33.438584126.9194052023-01-016520000제주특별자치도 서귀포시
3578스타PC방시설전체전북특별자치도익산시게임제공업소국민건강증진법제9조<NA><NA><NA>전북특별자치도 익산시 서동로 145 (마동)<NA>전북특별자치도 익산시35.936165126.9666552024-02-224681000전북특별자치도 익산시