Overview

Dataset statistics

Number of variables14
Number of observations3913
Missing cells11295
Missing cells (%)20.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory447.2 KiB
Average record size in memory117.0 B

Variable types

Categorical4
Text3
DateTime2
Unsupported2
Numeric3

Dataset

Description유흥주점 영업(요정) 현황_인허가
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=K49KZCGQ2SSCRC6SD9KM14268792&infSeq=1

Alerts

위생업종명 is highly overall correlated with 소재지우편번호 and 5 other fieldsHigh correlation
영업상태명 is highly overall correlated with 위생업종명 and 1 other fieldsHigh correlation
위생업태명 is highly overall correlated with 영업상태명 and 1 other fieldsHigh correlation
시군명 is highly overall correlated with 소재지우편번호 and 3 other fieldsHigh correlation
소재지우편번호 is highly overall correlated with WGS84위도 and 2 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 2 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
영업상태명 is highly imbalanced (70.3%)Imbalance
위생업종명 is highly imbalanced (94.1%)Imbalance
폐업일자 has 3426 (87.6%) missing valuesMissing
다중이용업소여부 has 3913 (100.0%) missing valuesMissing
총시설규모(㎡) has 3913 (100.0%) missing valuesMissing
다중이용업소여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총시설규모(㎡) is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 21:36:59.711325
Analysis finished2023-12-10 21:37:03.100193
Duration3.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
부천시
446 
평택시
377 
수원시
332 
안산시
302 
성남시
297 
Other values (25)
2159 

Length

Max length4
Median length3
Mean length3.0789675
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부천시 446
 
11.4%
평택시 377
 
9.6%
수원시 332
 
8.5%
안산시 302
 
7.7%
성남시 297
 
7.6%
시흥시 192
 
4.9%
화성시 183
 
4.7%
안양시 163
 
4.2%
의정부시 139
 
3.6%
용인시 130
 
3.3%
Other values (20) 1352
34.6%

Length

2023-12-11T06:37:03.192759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부천시 446
 
11.4%
평택시 377
 
9.6%
수원시 332
 
8.5%
안산시 302
 
7.7%
성남시 297
 
7.6%
시흥시 192
 
4.9%
화성시 183
 
4.7%
안양시 163
 
4.2%
의정부시 139
 
3.6%
용인시 130
 
3.3%
Other values (20) 1352
34.6%

사업장명
Text

Distinct3330
Distinct (%)85.1%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
2023-12-11T06:37:03.596550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length5.5849732
Min length1

Characters and Unicode

Total characters21854
Distinct characters757
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2971 ?
Unique (%)75.9%

Sample

1st row고고노래바
2nd row별천지노래장
3rd row춘향이노래장
4th row브라보노래장
5th row리버파크단란주점
ValueCountFrequency (%)
단란주점 31
 
0.7%
라이브 25
 
0.6%
7080 22
 
0.5%
준코뮤직타운 21
 
0.5%
노래빠 18
 
0.4%
노래광장 17
 
0.4%
노래짱 14
 
0.3%
노래장 13
 
0.3%
노래주점 13
 
0.3%
황진이 13
 
0.3%
Other values (3335) 4145
95.7%
2023-12-11T06:37:04.250386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
래 1597
 
7.3%
노 1594
 
7.3%
이 683
 
3.1%
0 595
 
2.7%
장 515
 
2.4%
점 489
 
2.2%
주 467
 
2.1%
라 461
 
2.1%
스 432
 
2.0%
421
 
1.9%
Other values (747) 14600
66.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18746
85.8%
Decimal Number 1377
 
6.3%
Uppercase Letter 652
 
3.0%
Space Separator 421
 
1.9%
Lowercase Letter 233
 
1.1%
Open Punctuation 190
 
0.9%
Close Punctuation 189
 
0.9%
Other Punctuation 35
 
0.2%
Letter Number 6
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
래 1597
 
8.5%
노 1594
 
8.5%
이 683
 
3.6%
장 515
 
2.7%
점 489
 
2.6%
주 467
 
2.5%
라 461
 
2.5%
스 432
 
2.3%
광 371
 
2.0%
브 352
 
1.9%
Other values (671) 11785
62.9%
Uppercase Letter
ValueCountFrequency (%)
O 55
 
8.4%
E 48
 
7.4%
S 45
 
6.9%
A 43
 
6.6%
N 41
 
6.3%
I 39
 
6.0%
K 35
 
5.4%
T 34
 
5.2%
B 31
 
4.8%
H 30
 
4.6%
Other values (16) 251
38.5%
Lowercase Letter
ValueCountFrequency (%)
e 24
 
10.3%
a 22
 
9.4%
r 19
 
8.2%
l 17
 
7.3%
s 17
 
7.3%
i 16
 
6.9%
u 15
 
6.4%
o 15
 
6.4%
y 13
 
5.6%
b 10
 
4.3%
Other values (14) 65
27.9%
Decimal Number
ValueCountFrequency (%)
0 595
43.2%
7 296
21.5%
8 284
20.6%
2 59
 
4.3%
1 47
 
3.4%
9 45
 
3.3%
3 24
 
1.7%
4 13
 
0.9%
6 8
 
0.6%
5 6
 
0.4%
Other Punctuation
ValueCountFrequency (%)
. 20
57.1%
& 5
 
14.3%
, 3
 
8.6%
% 2
 
5.7%
! 2
 
5.7%
· 1
 
2.9%
/ 1
 
2.9%
' 1
 
2.9%
Open Punctuation
ValueCountFrequency (%)
( 188
98.9%
[ 2
 
1.1%
Close Punctuation
ValueCountFrequency (%)
) 187
98.9%
] 2
 
1.1%
Space Separator
ValueCountFrequency (%)
421
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 6
100.0%
Math Symbol
ValueCountFrequency (%)
+ 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18742
85.8%
Common 2217
 
10.1%
Latin 891
 
4.1%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
래 1597
 
8.5%
노 1594
 
8.5%
이 683
 
3.6%
장 515
 
2.7%
점 489
 
2.6%
주 467
 
2.5%
라 461
 
2.5%
스 432
 
2.3%
광 371
 
2.0%
브 352
 
1.9%
Other values (667) 11781
62.9%
Latin
ValueCountFrequency (%)
O 55
 
6.2%
E 48
 
5.4%
S 45
 
5.1%
A 43
 
4.8%
N 41
 
4.6%
I 39
 
4.4%
K 35
 
3.9%
T 34
 
3.8%
B 31
 
3.5%
H 30
 
3.4%
Other values (41) 490
55.0%
Common
ValueCountFrequency (%)
0 595
26.8%
421
19.0%
7 296
13.4%
8 284
12.8%
( 188
 
8.5%
) 187
 
8.4%
2 59
 
2.7%
1 47
 
2.1%
9 45
 
2.0%
3 24
 
1.1%
Other values (15) 71
 
3.2%
Han
ValueCountFrequency (%)
酌 1
25.0%
大 1
25.0%
宮 1
25.0%
家 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18740
85.8%
ASCII 3101
 
14.2%
Number Forms 6
 
< 0.1%
CJK 4
 
< 0.1%
Compat Jamo 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
래 1597
 
8.5%
노 1594
 
8.5%
이 683
 
3.6%
장 515
 
2.7%
점 489
 
2.6%
주 467
 
2.5%
라 461
 
2.5%
스 432
 
2.3%
광 371
 
2.0%
브 352
 
1.9%
Other values (665) 11779
62.9%
ASCII
ValueCountFrequency (%)
0 595
19.2%
421
13.6%
7 296
 
9.5%
8 284
 
9.2%
( 188
 
6.1%
) 187
 
6.0%
2 59
 
1.9%
O 55
 
1.8%
E 48
 
1.5%
1 47
 
1.5%
Other values (64) 921
29.7%
Number Forms
ValueCountFrequency (%)
Ⅱ 6
100.0%
CJK
ValueCountFrequency (%)
酌 1
25.0%
大 1
25.0%
宮 1
25.0%
家 1
25.0%
Compat Jamo
ValueCountFrequency (%)
ㅇ 1
50.0%
ㅋ 1
50.0%
None
ValueCountFrequency (%)
· 1
100.0%

인허가일자
Date

Distinct2965
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
Minimum1968-09-03 00:00:00
Maximum2023-11-28 00:00:00
2023-12-11T06:37:04.425691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:04.837604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
영업
3418 
폐업
466 
폐업 등
 
21
운영중
 
8

Length

Max length4
Median length2
Mean length2.0127779
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 3418
87.3%
폐업 466
 
11.9%
폐업 등 21
 
0.5%
운영중 8
 
0.2%

Length

2023-12-11T06:37:04.996177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:37:05.130751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 3418
86.9%
폐업 487
 
12.4%
등 21
 
0.5%
운영중 8
 
0.2%

폐업일자
Date

MISSING 

Distinct306
Distinct (%)62.8%
Missing3426
Missing (%)87.6%
Memory size30.7 KiB
Minimum1997-02-15 00:00:00
Maximum2023-11-28 00:00:00
2023-12-11T06:37:05.254414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:05.388999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

다중이용업소여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3913
Missing (%)100.0%
Memory size34.5 KiB

총시설규모(㎡)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3913
Missing (%)100.0%
Memory size34.5 KiB

위생업종명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
<NA>
3886 
유흥주점영업
 
27

Length

Max length6
Median length4
Mean length4.0138002
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3886
99.3%
유흥주점영업 27
 
0.7%

Length

2023-12-11T06:37:05.531553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:37:05.661733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3886
99.3%
유흥주점영업 27
 
0.7%

위생업태명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
룸살롱
1820 
단란주점
1036 
간이주점
326 
기타
290 
노래클럽
194 
Other values (8)
247 

Length

Max length12
Median length9
Mean length3.4042934
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row룸살롱
2nd row카바레
3rd row룸살롱
4th row룸살롱
5th row단란주점

Common Values

ValueCountFrequency (%)
룸살롱 1820
46.5%
단란주점 1036
26.5%
간이주점 326
 
8.3%
기타 290
 
7.4%
노래클럽 194
 
5.0%
카바레 110
 
2.8%
스텐드바 49
 
1.3%
요정 29
 
0.7%
고고(디스코)클럽 27
 
0.7%
비어(바)살롱 26
 
0.7%
Other values (3) 6
 
0.2%

Length

2023-12-11T06:37:05.767693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
룸살롱 1820
46.5%
단란주점 1036
26.5%
간이주점 326
 
8.3%
기타 290
 
7.4%
노래클럽 194
 
5.0%
카바레 110
 
2.8%
스텐드바 49
 
1.3%
요정 29
 
0.7%
고고(디스코)클럽 27
 
0.7%
비어(바)살롱 26
 
0.7%
Other values (3) 6
 
0.2%

소재지도로명주소
Text

Distinct3796
Distinct (%)97.5%
Missing18
Missing (%)0.5%
Memory size30.7 KiB
2023-12-11T06:37:06.015330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length78
Median length50
Mean length31.622593
Min length14

Characters and Unicode

Total characters123170
Distinct characters450
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3704 ?
Unique (%)95.1%

Sample

1st row경기도 가평군 설악면 신천중앙로 91, B동 지하1층
2nd row경기도 가평군 가평읍 오리나무길 15
3rd row경기도 가평군 가평읍 연인2길 2
4th row경기도 가평군 가평읍 오리나무길 31, 지하2층
5th row경기도 가평군 청평면 은행나무길 19 (632-1)
ValueCountFrequency (%)
경기도 3895
 
15.3%
지하1층 469
 
1.8%
부천시 446
 
1.8%
2층 423
 
1.7%
평택시 377
 
1.5%
수원시 331
 
1.3%
안산시 302
 
1.2%
성남시 297
 
1.2%
지층 205
 
0.8%
단원구 196
 
0.8%
Other values (3734) 18450
72.7%
2023-12-11T06:37:06.466585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21561
 
17.5%
1 4916
 
4.0%
시 4100
 
3.3%
경 4010
 
3.3%
기 3959
 
3.2%
도 3939
 
3.2%
동 3831
 
3.1%
2 3738
 
3.0%
로 3543
 
2.9%
( 3534
 
2.9%
Other values (440) 66039
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68142
55.3%
Decimal Number 21622
 
17.6%
Space Separator 21561
 
17.5%
Open Punctuation 3534
 
2.9%
Close Punctuation 3534
 
2.9%
Other Punctuation 3515
 
2.9%
Dash Punctuation 988
 
0.8%
Uppercase Letter 236
 
0.2%
Math Symbol 26
 
< 0.1%
Letter Number 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 4100
 
6.0%
경 4010
 
5.9%
기 3959
 
5.8%
도 3939
 
5.8%
동 3831
 
5.6%
로 3543
 
5.2%
층 2132
 
3.1%
길 2096
 
3.1%
번 1617
 
2.4%
구 1596
 
2.3%
Other values (395) 37319
54.8%
Uppercase Letter
ValueCountFrequency (%)
B 151
64.0%
A 18
 
7.6%
C 9
 
3.8%
M 7
 
3.0%
S 6
 
2.5%
H 5
 
2.1%
I 5
 
2.1%
E 5
 
2.1%
L 4
 
1.7%
G 4
 
1.7%
Other values (9) 22
 
9.3%
Decimal Number
ValueCountFrequency (%)
1 4916
22.7%
2 3738
17.3%
3 2544
11.8%
0 2347
10.9%
4 1729
 
8.0%
5 1665
 
7.7%
6 1287
 
6.0%
7 1244
 
5.8%
9 1183
 
5.5%
8 969
 
4.5%
Letter Number
ValueCountFrequency (%)
Ⅱ 5
55.6%
ⅵ 1
 
11.1%
Ⅲ 1
 
11.1%
Ⅳ 1
 
11.1%
Ⅴ 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
, 3500
99.6%
. 14
 
0.4%
' 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 25
96.2%
> 1
 
3.8%
Lowercase Letter
ValueCountFrequency (%)
l 2
66.7%
a 1
33.3%
Space Separator
ValueCountFrequency (%)
21561
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3534
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3534
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 988
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68142
55.3%
Common 54780
44.5%
Latin 248
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 4100
 
6.0%
경 4010
 
5.9%
기 3959
 
5.8%
도 3939
 
5.8%
동 3831
 
5.6%
로 3543
 
5.2%
층 2132
 
3.1%
길 2096
 
3.1%
번 1617
 
2.4%
구 1596
 
2.3%
Other values (395) 37319
54.8%
Latin
ValueCountFrequency (%)
B 151
60.9%
A 18
 
7.3%
C 9
 
3.6%
M 7
 
2.8%
S 6
 
2.4%
Ⅱ 5
 
2.0%
H 5
 
2.0%
I 5
 
2.0%
E 5
 
2.0%
L 4
 
1.6%
Other values (16) 33
 
13.3%
Common
ValueCountFrequency (%)
21561
39.4%
1 4916
 
9.0%
2 3738
 
6.8%
( 3534
 
6.5%
) 3534
 
6.5%
, 3500
 
6.4%
3 2544
 
4.6%
0 2347
 
4.3%
4 1729
 
3.2%
5 1665
 
3.0%
Other values (9) 5712
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68142
55.3%
ASCII 55019
44.7%
Number Forms 9
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21561
39.2%
1 4916
 
8.9%
2 3738
 
6.8%
( 3534
 
6.4%
) 3534
 
6.4%
, 3500
 
6.4%
3 2544
 
4.6%
0 2347
 
4.3%
4 1729
 
3.1%
5 1665
 
3.0%
Other values (30) 5951
 
10.8%
Hangul
ValueCountFrequency (%)
시 4100
 
6.0%
경 4010
 
5.9%
기 3959
 
5.8%
도 3939
 
5.8%
동 3831
 
5.6%
로 3543
 
5.2%
층 2132
 
3.1%
길 2096
 
3.1%
번 1617
 
2.4%
구 1596
 
2.3%
Other values (395) 37319
54.8%
Number Forms
ValueCountFrequency (%)
Ⅱ 5
55.6%
ⅵ 1
 
11.1%
Ⅲ 1
 
11.1%
Ⅳ 1
 
11.1%
Ⅴ 1
 
11.1%

소재지지번주소
Text

Distinct3688
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
2023-12-11T06:37:06.801642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length45
Mean length25.459494
Min length15

Characters and Unicode

Total characters99623
Distinct characters403
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3519 ?
Unique (%)89.9%

Sample

1st row경기도 가평군 설악면 신천리 408-27 외 2필지, B동 지하1층
2nd row경기도 가평군 가평읍 대곡리 239-1
3rd row경기도 가평군 가평읍 읍내리 468-8
4th row경기도 가평군 가평읍 대곡리 164-1 지하2층
5th row경기도 가평군 청평면 대성리 631-2 632-1
ValueCountFrequency (%)
경기도 3913
 
18.1%
부천시 446
 
2.1%
지하1층 436
 
2.0%
평택시 377
 
1.7%
수원시 332
 
1.5%
안산시 302
 
1.4%
성남시 297
 
1.4%
2층 282
 
1.3%
중동 223
 
1.0%
지층 211
 
1.0%
Other values (4364) 14773
68.4%
2023-12-11T06:37:07.292213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21061
21.1%
1 5363
 
5.4%
시 3996
 
4.0%
도 3987
 
4.0%
기 3957
 
4.0%
경 3933
 
3.9%
동 3644
 
3.7%
- 3550
 
3.6%
2 2913
 
2.9%
3 2467
 
2.5%
Other values (393) 44752
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 51406
51.6%
Decimal Number 22498
22.6%
Space Separator 21061
21.1%
Dash Punctuation 3550
 
3.6%
Other Punctuation 344
 
0.3%
Open Punctuation 285
 
0.3%
Close Punctuation 284
 
0.3%
Uppercase Letter 169
 
0.2%
Math Symbol 19
 
< 0.1%
Letter Number 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 3996
 
7.8%
도 3987
 
7.8%
기 3957
 
7.7%
경 3933
 
7.7%
동 3644
 
7.1%
구 1497
 
2.9%
층 1412
 
2.7%
지 1314
 
2.6%
호 1186
 
2.3%
부 954
 
1.9%
Other values (348) 25526
49.7%
Uppercase Letter
ValueCountFrequency (%)
B 106
62.7%
A 13
 
7.7%
C 11
 
6.5%
S 6
 
3.6%
H 5
 
3.0%
I 5
 
3.0%
G 4
 
2.4%
M 3
 
1.8%
E 3
 
1.8%
J 2
 
1.2%
Other values (9) 11
 
6.5%
Decimal Number
ValueCountFrequency (%)
1 5363
23.8%
2 2913
12.9%
3 2467
11.0%
0 2370
10.5%
4 2069
 
9.2%
5 1665
 
7.4%
7 1659
 
7.4%
8 1475
 
6.6%
6 1449
 
6.4%
9 1068
 
4.7%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
40.0%
Ⅲ 1
20.0%
Ⅴ 1
20.0%
Ⅳ 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 332
96.5%
. 11
 
3.2%
' 1
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 284
99.6%
[ 1
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 283
99.6%
] 1
 
0.4%
Math Symbol
ValueCountFrequency (%)
~ 18
94.7%
> 1
 
5.3%
Space Separator
ValueCountFrequency (%)
21061
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3550
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 51406
51.6%
Common 48041
48.2%
Latin 176
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 3996
 
7.8%
도 3987
 
7.8%
기 3957
 
7.7%
경 3933
 
7.7%
동 3644
 
7.1%
구 1497
 
2.9%
층 1412
 
2.7%
지 1314
 
2.6%
호 1186
 
2.3%
부 954
 
1.9%
Other values (348) 25526
49.7%
Latin
ValueCountFrequency (%)
B 106
60.2%
A 13
 
7.4%
C 11
 
6.2%
S 6
 
3.4%
H 5
 
2.8%
I 5
 
2.8%
G 4
 
2.3%
M 3
 
1.7%
E 3
 
1.7%
Ⅱ 2
 
1.1%
Other values (14) 18
 
10.2%
Common
ValueCountFrequency (%)
21061
43.8%
1 5363
 
11.2%
- 3550
 
7.4%
2 2913
 
6.1%
3 2467
 
5.1%
0 2370
 
4.9%
4 2069
 
4.3%
5 1665
 
3.5%
7 1659
 
3.5%
8 1475
 
3.1%
Other values (11) 3449
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 51406
51.6%
ASCII 48212
48.4%
Number Forms 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21061
43.7%
1 5363
 
11.1%
- 3550
 
7.4%
2 2913
 
6.0%
3 2467
 
5.1%
0 2370
 
4.9%
4 2069
 
4.3%
5 1665
 
3.5%
7 1659
 
3.4%
8 1475
 
3.1%
Other values (31) 3620
 
7.5%
Hangul
ValueCountFrequency (%)
시 3996
 
7.8%
도 3987
 
7.8%
기 3957
 
7.7%
경 3933
 
7.7%
동 3644
 
7.1%
구 1497
 
2.9%
층 1412
 
2.7%
지 1314
 
2.6%
호 1186
 
2.3%
부 954
 
1.9%
Other values (348) 25526
49.7%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
40.0%
Ⅲ 1
20.0%
Ⅴ 1
20.0%
Ⅳ 1
20.0%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct628
Distinct (%)16.1%
Missing9
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean14589.647
Minimum10018
Maximum18623
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size34.5 KiB
2023-12-11T06:37:07.442295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10018
5-th percentile10500
Q112556
median14623
Q316561
95-th percentile18141
Maximum18623
Range8605
Interquartile range (IQR)4005

Descriptive statistics

Standard deviation2452.1932
Coefficient of variation (CV)0.16807762
Kurtosis-1.0823584
Mean14589.647
Median Absolute Deviation (MAD)2003
Skewness-0.10508661
Sum56957983
Variance6013251.7
MonotonicityNot monotonic
2023-12-11T06:37:07.641152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14548 89
 
2.3%
14580 73
 
1.9%
10071 67
 
1.7%
17774 59
 
1.5%
15361 56
 
1.4%
16489 55
 
1.4%
14066 43
 
1.1%
15062 42
 
1.1%
17758 40
 
1.0%
16490 37
 
0.9%
Other values (618) 3343
85.4%
ValueCountFrequency (%)
10018 13
 
0.3%
10019 8
 
0.2%
10024 2
 
0.1%
10025 4
 
0.1%
10040 1
 
< 0.1%
10059 2
 
0.1%
10071 67
1.7%
10073 2
 
0.1%
10098 6
 
0.2%
10129 3
 
0.1%
ValueCountFrequency (%)
18623 3
 
0.1%
18611 5
 
0.1%
18606 22
0.6%
18600 2
 
0.1%
18593 21
0.5%
18591 1
 
< 0.1%
18577 1
 
< 0.1%
18567 1
 
< 0.1%
18565 4
 
0.1%
18555 1
 
< 0.1%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct2924
Distinct (%)74.9%
Missing8
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean37.418908
Minimum36.92055
Maximum38.185409
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size34.5 KiB
2023-12-11T06:37:07.806219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.92055
5-th percentile37.00125
Q137.26612
median37.393859
Q337.53896
95-th percentile37.886595
Maximum38.185409
Range1.2648594
Interquartile range (IQR)0.27283959

Descriptive statistics

Standard deviation0.24363266
Coefficient of variation (CV)0.0065109506
Kurtosis-0.36929079
Mean37.418908
Median Absolute Deviation (MAD)0.12845858
Skewness0.32615629
Sum146120.83
Variance0.059356872
MonotonicityNot monotonic
2023-12-11T06:37:07.987335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.7148553223 14
 
0.4%
37.0458281259 13
 
0.3%
37.2741372443 11
 
0.3%
37.5614176573 11
 
0.3%
37.0474611388 11
 
0.3%
37.1484696706 10
 
0.3%
37.1158099993 9
 
0.2%
37.2062782615 8
 
0.2%
37.4999597591 7
 
0.2%
37.2005247567 7
 
0.2%
Other values (2914) 3804
97.2%
(Missing) 8
 
0.2%
ValueCountFrequency (%)
36.9205495128 1
 
< 0.1%
36.9591698642 1
 
< 0.1%
36.9597125094 1
 
< 0.1%
36.9597668961 1
 
< 0.1%
36.9601292292 1
 
< 0.1%
36.9602259744 1
 
< 0.1%
36.9605436675 4
0.1%
36.9605461615 1
 
< 0.1%
36.9606437702 2
0.1%
36.9607513384 1
 
< 0.1%
ValueCountFrequency (%)
38.1854088791 1
< 0.1%
38.1019576622 1
< 0.1%
38.1012036186 1
< 0.1%
38.1001948371 1
< 0.1%
38.0914439791 1
< 0.1%
38.0910451365 1
< 0.1%
38.0908114997 1
< 0.1%
38.058140506 1
< 0.1%
38.032615034 1
< 0.1%
38.0313816443 1
< 0.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct2924
Distinct (%)74.9%
Missing8
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean126.98998
Minimum126.55416
Maximum127.6506
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size34.5 KiB
2023-12-11T06:37:08.157427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.55416
5-th percentile126.73549
Q1126.82797
median127.02127
Q3127.09606
95-th percentile127.36562
Maximum127.6506
Range1.0964451
Interquartile range (IQR)0.26808955

Descriptive statistics

Standard deviation0.1981996
Coefficient of variation (CV)0.0015607499
Kurtosis0.69826006
Mean126.98998
Median Absolute Deviation (MAD)0.12481991
Skewness0.64271651
Sum495895.88
Variance0.039283081
MonotonicityNot monotonic
2023-12-11T06:37:08.306828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.7614890719 14
 
0.4%
127.0450553425 13
 
0.3%
126.9514301863 11
 
0.3%
127.1912058889 11
 
0.3%
127.0454279562 11
 
0.3%
127.0757913493 10
 
0.3%
126.9127510897 9
 
0.2%
127.0736198125 8
 
0.2%
126.7760101349 7
 
0.2%
126.8280665927 7
 
0.2%
Other values (2914) 3804
97.2%
(Missing) 8
 
0.2%
ValueCountFrequency (%)
126.5541581093 1
< 0.1%
126.5567860205 1
< 0.1%
126.55991476 1
< 0.1%
126.5606611859 2
0.1%
126.5608313578 1
< 0.1%
126.5824929244 1
< 0.1%
126.5864818952 1
< 0.1%
126.5976057487 1
< 0.1%
126.5978179671 1
< 0.1%
126.5978810854 2
0.1%
ValueCountFrequency (%)
127.6506032269 1
< 0.1%
127.64127488 1
< 0.1%
127.6398542064 1
< 0.1%
127.6397188594 1
< 0.1%
127.6390083568 1
< 0.1%
127.6384547077 1
< 0.1%
127.6372797797 1
< 0.1%
127.63706457 1
< 0.1%
127.636962632 1
< 0.1%
127.6362086004 1
< 0.1%

Interactions

2023-12-11T06:37:02.165975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:01.356869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:01.743290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:02.251956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:01.487689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:01.866372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:02.365189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:01.624428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:02.028640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:37:08.392597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명영업상태명위생업태명소재지우편번호WGS84위도WGS84경도
시군명1.0000.2780.4900.9990.9810.978
영업상태명0.2781.0000.8580.1480.1450.101
위생업태명0.4900.8581.0000.3140.2570.213
소재지우편번호0.9990.1480.3141.0000.9380.897
WGS84위도0.9810.1450.2570.9381.0000.749
WGS84경도0.9780.1010.2130.8970.7491.000
2023-12-11T06:37:08.487263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위생업종명영업상태명위생업태명시군명
위생업종명1.0001.0001.0001.000
영업상태명1.0001.0000.5590.147
위생업태명1.0000.5591.0000.177
시군명1.0000.1470.1771.000
2023-12-11T06:37:08.572467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도시군명영업상태명위생업종명위생업태명
소재지우편번호1.000-0.9240.0460.9360.0881.0000.137
WGS84위도-0.9241.000-0.1430.7830.0871.0000.110
WGS84경도0.046-0.1431.0000.7700.0601.0000.091
시군명0.9360.7830.7701.0000.1471.0000.177
영업상태명0.0880.0870.0600.1471.0001.0000.559
위생업종명1.0001.0001.0001.0001.0001.0001.000
위생업태명0.1370.1100.0910.1770.5591.0001.000

Missing values

2023-12-11T06:37:02.523303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:37:02.772411image/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.
2023-12-11T06:37:02.968064image/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

시군명사업장명인허가일자영업상태명폐업일자다중이용업소여부총시설규모(㎡)위생업종명위생업태명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
0가평군고고노래바2008-02-26영업<NA><NA><NA><NA>룸살롱경기도 가평군 설악면 신천중앙로 91, B동 지하1층경기도 가평군 설악면 신천리 408-27 외 2필지, B동 지하1층1246737.676707127.493139
1가평군별천지노래장1983-09-15영업<NA><NA><NA><NA>카바레경기도 가평군 가평읍 오리나무길 15경기도 가평군 가평읍 대곡리 239-11242037.826228127.514329
2가평군춘향이노래장2004-09-15영업<NA><NA><NA><NA>룸살롱경기도 가평군 가평읍 연인2길 2경기도 가평군 가평읍 읍내리 468-81241837.830401127.513239
3가평군브라보노래장1999-06-25영업<NA><NA><NA><NA>룸살롱경기도 가평군 가평읍 오리나무길 31, 지하2층경기도 가평군 가평읍 대곡리 164-1 지하2층1242037.824705127.514204
4가평군리버파크단란주점1998-01-23영업<NA><NA><NA><NA>단란주점경기도 가평군 청평면 은행나무길 19 (632-1)경기도 가평군 청평면 대성리 631-2 632-11245737.679976127.375274
5가평군호반에 도시2023-06-23영업<NA><NA><NA><NA>단란주점경기도 가평군 청평면 청평중앙로 30, 지하1층경기도 가평군 청평면 청평리 434-59 지하1층1245337.736816127.418205
6가평군원타임2003-02-08영업<NA><NA><NA><NA>룸살롱경기도 가평군 설악면 신천중앙로 136-1, 지하1층경기도 가평군 설악면 신천리 464-4 지하1층1246537.677879127.488671
7가평군대부 or 보스2002-01-12영업<NA><NA><NA><NA>룸살롱경기도 가평군 가평읍 오리나무길 12경기도 가평군 가평읍 대곡리 234-101242037.826633127.514181
8가평군술마시는1박2일노래장2001-06-13영업<NA><NA><NA><NA>룸살롱경기도 가평군 가평읍 장터2길 6-14경기도 가평군 가평읍 읍내리 474-61241937.82931127.514443
9가평군금호클럽1987-02-02영업<NA><NA><NA><NA>스텐드바경기도 가평군 청평면 여울길 37 (, 423-6)경기도 가평군 청평면 청평리 419-2 , 423-61245337.736465127.419488
시군명사업장명인허가일자영업상태명폐업일자다중이용업소여부총시설규모(㎡)위생업종명위생업태명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
3903화성시풀하우스20151216폐업20221226<NA><NA><NA>룸살롱경기도 화성시 메타폴리스로 44, 701호 (반송동)경기도 화성시 반송동 103-5 701호1845537.201712127.072271
3904화성시스테이132022-08-18폐업2023-03-29<NA><NA><NA>단란주점경기도 화성시 향남읍 평4길 13, 지하 1층경기도 화성시 향남읍 평리 131-3 지하 1층1859337.130283126.908463
3905화성시마스터룸20130418폐업20220920<NA><NA><NA>룸살롱경기도 화성시 동탄중심상가2길 31 (반송동, 성진빌딩 604호)경기도 화성시 반송동 88-5 (성진빌딩 604호)1845337.206278127.07362
3906화성시아프리카20111115폐업20220920<NA><NA><NA>룸살롱경기도 화성시 동탄중심상가2길 31 (반송동, 88-5 성진빌딩 602)경기도 화성시 반송동 88-5 성진빌딩 602호1845337.206278127.07362
3907화성시19노래클럽2018-09-17폐업2023-07-10<NA><NA><NA>룸살롱경기도 화성시 남양읍 시청로 119, 206호경기도 화성시 남양읍 남양리 2072-11 206호1827137.200516126.826489
3908화성시각설이노래빠2014-02-20폐업2023-06-14<NA><NA><NA>룸살롱경기도 화성시 노작로 143, 601, 603호 (반송동, 유정프라자)경기도 화성시 반송동 106-5 유정프라자 601, 603호1845537.20068127.073539
3909화성시킹 노래주점2011-01-11폐업2023-06-13<NA><NA><NA>단란주점경기도 화성시 팔탄면 온천로 318경기도 화성시 팔탄면 덕천리 117-11857737.147026126.872366
3910화성시에스에이치 단란주점20100402폐업20221118<NA><NA><NA>단란주점경기도 화성시 병점1로 216-13 (병점동)경기도 화성시 병점동 846 태안프라자1840537.214108127.043607
3911화성시(주)라비돌 주카(ZOOKA)20030317폐업20220426<NA><NA><NA>단란주점경기도 화성시 정남면 세자로 286경기도 화성시 정남면 보통리 141-391851637.187083126.984148
3912화성시춘화정20020121폐업 등20080422<NA><NA>유흥주점영업요정<NA>경기도 화성시 향남읍 평리 81-93번지1859337.132305126.911793