Overview

Dataset statistics

Number of variables14
Number of observations4060
Missing cells11645
Missing cells (%)20.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory464.0 KiB
Average record size in memory117.0 B

Variable types

Categorical4
Text3
DateTime2
Unsupported2
Numeric3

Dataset

Description유흥주점 영업(고고(디스코) 클럽) 현황_인허가
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=HAKHY1F8KCLZ4YKFWT2R14188025&infSeq=1

Alerts

위생업태명 is highly overall correlated with 영업상태명 and 1 other fieldsHigh correlation
시군명 is highly overall correlated with 소재지우편번호 and 3 other fieldsHigh correlation
영업상태명 is highly overall correlated with 위생업종명 and 1 other fieldsHigh correlation
위생업종명 is highly overall correlated with 소재지우편번호 and 5 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 (59.2%)Imbalance
위생업종명 is highly imbalanced (76.0%)Imbalance
폐업일자 has 3464 (85.3%) missing valuesMissing
다중이용업소여부 has 4060 (100.0%) missing valuesMissing
총시설규모(㎡) has 4060 (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 21:52:22.757413
Analysis finished2023-12-10 21:52:25.065199
Duration2.31 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size31.8 KiB
부천시
474 
평택시
398 
수원시
340 
안산시
322 
성남시
315 
Other values (25)
2211 

Length

Max length4
Median length3
Mean length3.0793103
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부천시 474
 
11.7%
평택시 398
 
9.8%
수원시 340
 
8.4%
안산시 322
 
7.9%
성남시 315
 
7.8%
시흥시 196
 
4.8%
화성시 183
 
4.5%
안양시 181
 
4.5%
의정부시 151
 
3.7%
용인시 131
 
3.2%
Other values (20) 1369
33.7%

Length

2023-12-11T06:52:25.117978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부천시 474
 
11.7%
평택시 398
 
9.8%
수원시 340
 
8.4%
안산시 322
 
7.9%
성남시 315
 
7.8%
시흥시 196
 
4.8%
화성시 183
 
4.5%
안양시 181
 
4.5%
의정부시 151
 
3.7%
용인시 131
 
3.2%
Other values (20) 1369
33.7%

사업장명
Text

Distinct3449
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Memory size31.8 KiB
2023-12-11T06:52:25.396774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length5.6263547
Min length1

Characters and Unicode

Total characters22843
Distinct characters761
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

Unique3070 ?
Unique (%)75.6%

Sample

1st row대부 or 보스
2nd row오아시스노래주점
3rd row원타임
4th row술마시는1박2일노래장
5th row장녹수
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%
노래주점 13
 
0.3%
노래장 13
 
0.3%
황진이 12
 
0.3%
Other values (3453) 4302
95.9%
2023-12-11T06:52:25.777721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
노 1596
 
7.0%
래 1594
 
7.0%
이 783
 
3.4%
0 601
 
2.6%
장 514
 
2.3%
점 490
 
2.1%
라 480
 
2.1%
주 469
 
2.1%
스 462
 
2.0%
430
 
1.9%
Other values (751) 15424
67.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19686
86.2%
Decimal Number 1390
 
6.1%
Uppercase Letter 670
 
2.9%
Space Separator 430
 
1.9%
Lowercase Letter 236
 
1.0%
Open Punctuation 194
 
0.8%
Close Punctuation 193
 
0.8%
Other Punctuation 34
 
0.1%
Letter Number 6
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
노 1596
 
8.1%
래 1594
 
8.1%
이 783
 
4.0%
장 514
 
2.6%
점 490
 
2.5%
라 480
 
2.4%
주 469
 
2.4%
스 462
 
2.3%
광 394
 
2.0%
브 356
 
1.8%
Other values (675) 12548
63.7%
Uppercase Letter
ValueCountFrequency (%)
O 58
 
8.7%
E 48
 
7.2%
S 48
 
7.2%
A 45
 
6.7%
N 42
 
6.3%
I 39
 
5.8%
K 35
 
5.2%
T 34
 
5.1%
B 32
 
4.8%
H 30
 
4.5%
Other values (16) 259
38.7%
Lowercase Letter
ValueCountFrequency (%)
e 25
 
10.6%
a 22
 
9.3%
r 19
 
8.1%
s 17
 
7.2%
l 17
 
7.2%
i 17
 
7.2%
u 15
 
6.4%
o 15
 
6.4%
y 13
 
5.5%
t 10
 
4.2%
Other values (14) 66
28.0%
Decimal Number
ValueCountFrequency (%)
0 601
43.2%
7 297
21.4%
8 287
20.6%
2 60
 
4.3%
9 47
 
3.4%
1 47
 
3.4%
3 24
 
1.7%
4 13
 
0.9%
6 8
 
0.6%
5 6
 
0.4%
Other Punctuation
ValueCountFrequency (%)
. 20
58.8%
& 5
 
14.7%
, 3
 
8.8%
% 2
 
5.9%
! 1
 
2.9%
' 1
 
2.9%
/ 1
 
2.9%
· 1
 
2.9%
Open Punctuation
ValueCountFrequency (%)
( 192
99.0%
[ 2
 
1.0%
Close Punctuation
ValueCountFrequency (%)
) 191
99.0%
] 2
 
1.0%
Space Separator
ValueCountFrequency (%)
430
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19682
86.2%
Common 2245
 
9.8%
Latin 912
 
4.0%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
노 1596
 
8.1%
래 1594
 
8.1%
이 783
 
4.0%
장 514
 
2.6%
점 490
 
2.5%
라 480
 
2.4%
주 469
 
2.4%
스 462
 
2.3%
광 394
 
2.0%
브 356
 
1.8%
Other values (671) 12544
63.7%
Latin
ValueCountFrequency (%)
O 58
 
6.4%
E 48
 
5.3%
S 48
 
5.3%
A 45
 
4.9%
N 42
 
4.6%
I 39
 
4.3%
K 35
 
3.8%
T 34
 
3.7%
B 32
 
3.5%
H 30
 
3.3%
Other values (41) 501
54.9%
Common
ValueCountFrequency (%)
0 601
26.8%
430
19.2%
7 297
13.2%
8 287
12.8%
( 192
 
8.6%
) 191
 
8.5%
2 60
 
2.7%
9 47
 
2.1%
1 47
 
2.1%
3 24
 
1.1%
Other values (15) 69
 
3.1%
Han
ValueCountFrequency (%)
家 1
25.0%
大 1
25.0%
宮 1
25.0%
酌 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19680
86.2%
ASCII 3150
 
13.8%
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 (%)
노 1596
 
8.1%
래 1594
 
8.1%
이 783
 
4.0%
장 514
 
2.6%
점 490
 
2.5%
라 480
 
2.4%
주 469
 
2.4%
스 462
 
2.3%
광 394
 
2.0%
브 356
 
1.8%
Other values (669) 12542
63.7%
ASCII
ValueCountFrequency (%)
0 601
19.1%
430
13.7%
7 297
 
9.4%
8 287
 
9.1%
( 192
 
6.1%
) 191
 
6.1%
2 60
 
1.9%
O 58
 
1.8%
E 48
 
1.5%
S 48
 
1.5%
Other values (64) 938
29.8%
Number Forms
ValueCountFrequency (%)
Ⅱ 6
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅋ 1
50.0%
ㅇ 1
50.0%
CJK
ValueCountFrequency (%)
家 1
25.0%
大 1
25.0%
宮 1
25.0%
酌 1
25.0%
None
ValueCountFrequency (%)
· 1
100.0%

인허가일자
Date

Distinct3048
Distinct (%)75.1%
Missing0
Missing (%)0.0%
Memory size31.8 KiB
Minimum1964-07-30 00:00:00
Maximum2023-11-28 00:00:00
2023-12-11T06:52:25.886805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:52:26.002447image/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 size31.8 KiB
영업
3407 
폐업
466 
폐업 등
 
130
운영중
 
57

Length

Max length4
Median length2
Mean length2.0780788
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 3407
83.9%
폐업 466
 
11.5%
폐업 등 130
 
3.2%
운영중 57
 
1.4%

Length

2023-12-11T06:52:26.125536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:52:26.213315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 3407
81.3%
폐업 596
 
14.2%
등 130
 
3.1%
운영중 57
 
1.4%

폐업일자
Date

MISSING 

Distinct410
Distinct (%)68.8%
Missing3464
Missing (%)85.3%
Memory size31.8 KiB
Minimum1995-01-03 00:00:00
Maximum2023-11-28 00:00:00
2023-12-11T06:52:26.328189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:52:26.438470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

다중이용업소여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4060
Missing (%)100.0%
Memory size35.8 KiB

총시설규모(㎡)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4060
Missing (%)100.0%
Memory size35.8 KiB

위생업종명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.8 KiB
<NA>
3900 
유흥주점영업
 
160

Length

Max length6
Median length4
Mean length4.0788177
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> 3900
96.1%
유흥주점영업 160
 
3.9%

Length

2023-12-11T06:52:26.554130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:52:26.638010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3900
96.1%
유흥주점영업 160
 
3.9%

위생업태명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size31.8 KiB
룸살롱
1818 
단란주점
1036 
간이주점
325 
기타
290 
노래클럽
194 
Other values (8)
397 

Length

Max length12
Median length9
Mean length3.6261084
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
룸살롱 1818
44.8%
단란주점 1036
25.5%
간이주점 325
 
8.0%
기타 290
 
7.1%
노래클럽 194
 
4.8%
고고(디스코)클럽 180
 
4.4%
카바레 110
 
2.7%
스텐드바 49
 
1.2%
<NA> 27
 
0.7%
비어(바)살롱 26
 
0.6%
Other values (3) 5
 
0.1%

Length

2023-12-11T06:52:26.718645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
룸살롱 1818
44.8%
단란주점 1036
25.5%
간이주점 325
 
8.0%
기타 290
 
7.1%
노래클럽 194
 
4.8%
고고(디스코)클럽 180
 
4.4%
카바레 110
 
2.7%
스텐드바 49
 
1.2%
na 27
 
0.7%
비어(바)살롱 26
 
0.6%
Other values (3) 5
 
0.1%

소재지도로명주소
Text

Distinct3901
Distinct (%)96.8%
Missing31
Missing (%)0.8%
Memory size31.8 KiB
2023-12-11T06:52:26.916392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length78
Median length51
Mean length31.390171
Min length13

Characters and Unicode

Total characters126471
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

Unique3783 ?
Unique (%)93.9%

Sample

1st row경기도 가평군 가평읍 오리나무길 12
2nd row경기도 가평군 조종면 조종희망로5번길 7, 1층
3rd row경기도 가평군 설악면 신천중앙로 136-1, 지하1층
4th row경기도 가평군 가평읍 장터2길 6-14
5th row경기도 가평군 가평읍 굴다리길 2, 가동 2층
ValueCountFrequency (%)
경기도 4029
 
15.4%
지하1층 475
 
1.8%
부천시 469
 
1.8%
2층 427
 
1.6%
평택시 397
 
1.5%
수원시 338
 
1.3%
안산시 321
 
1.2%
성남시 315
 
1.2%
단원구 216
 
0.8%
지층 210
 
0.8%
Other values (3790) 18921
72.4%
2023-12-11T06:52:27.288023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
22153
 
17.5%
1 5027
 
4.0%
시 4242
 
3.4%
경 4149
 
3.3%
기 4094
 
3.2%
도 4073
 
3.2%
동 3899
 
3.1%
2 3828
 
3.0%
로 3673
 
2.9%
) 3597
 
2.8%
Other values (440) 67736
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 70084
55.4%
Decimal Number 22174
 
17.5%
Space Separator 22153
 
17.5%
Close Punctuation 3597
 
2.8%
Open Punctuation 3597
 
2.8%
Other Punctuation 3582
 
2.8%
Dash Punctuation 1002
 
0.8%
Uppercase Letter 240
 
0.2%
Math Symbol 30
 
< 0.1%
Letter Number 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 4242
 
6.1%
경 4149
 
5.9%
기 4094
 
5.8%
도 4073
 
5.8%
동 3899
 
5.6%
로 3673
 
5.2%
층 2179
 
3.1%
길 2150
 
3.1%
구 1664
 
2.4%
번 1659
 
2.4%
Other values (395) 38302
54.7%
Uppercase Letter
ValueCountFrequency (%)
B 155
64.6%
A 18
 
7.5%
C 9
 
3.8%
M 7
 
2.9%
S 6
 
2.5%
I 5
 
2.1%
H 5
 
2.1%
E 5
 
2.1%
K 4
 
1.7%
G 4
 
1.7%
Other values (9) 22
 
9.2%
Decimal Number
ValueCountFrequency (%)
1 5027
22.7%
2 3828
17.3%
3 2598
11.7%
0 2404
10.8%
4 1788
 
8.1%
5 1715
 
7.7%
6 1326
 
6.0%
7 1264
 
5.7%
9 1231
 
5.6%
8 993
 
4.5%
Letter Number
ValueCountFrequency (%)
Ⅱ 5
55.6%
Ⅳ 1
 
11.1%
Ⅲ 1
 
11.1%
ⅵ 1
 
11.1%
Ⅴ 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
, 3567
99.6%
. 14
 
0.4%
' 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 29
96.7%
> 1
 
3.3%
Lowercase Letter
ValueCountFrequency (%)
l 2
66.7%
a 1
33.3%
Space Separator
ValueCountFrequency (%)
22153
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3597
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3597
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1002
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 70084
55.4%
Common 56135
44.4%
Latin 252
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 4242
 
6.1%
경 4149
 
5.9%
기 4094
 
5.8%
도 4073
 
5.8%
동 3899
 
5.6%
로 3673
 
5.2%
층 2179
 
3.1%
길 2150
 
3.1%
구 1664
 
2.4%
번 1659
 
2.4%
Other values (395) 38302
54.7%
Latin
ValueCountFrequency (%)
B 155
61.5%
A 18
 
7.1%
C 9
 
3.6%
M 7
 
2.8%
S 6
 
2.4%
Ⅱ 5
 
2.0%
I 5
 
2.0%
H 5
 
2.0%
E 5
 
2.0%
K 4
 
1.6%
Other values (16) 33
 
13.1%
Common
ValueCountFrequency (%)
22153
39.5%
1 5027
 
9.0%
2 3828
 
6.8%
) 3597
 
6.4%
( 3597
 
6.4%
, 3567
 
6.4%
3 2598
 
4.6%
0 2404
 
4.3%
4 1788
 
3.2%
5 1715
 
3.1%
Other values (9) 5861
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 70084
55.4%
ASCII 56378
44.6%
Number Forms 9
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
22153
39.3%
1 5027
 
8.9%
2 3828
 
6.8%
) 3597
 
6.4%
( 3597
 
6.4%
, 3567
 
6.3%
3 2598
 
4.6%
0 2404
 
4.3%
4 1788
 
3.2%
5 1715
 
3.0%
Other values (30) 6104
 
10.8%
Hangul
ValueCountFrequency (%)
시 4242
 
6.1%
경 4149
 
5.9%
기 4094
 
5.8%
도 4073
 
5.8%
동 3899
 
5.6%
로 3673
 
5.2%
층 2179
 
3.1%
길 2150
 
3.1%
구 1664
 
2.4%
번 1659
 
2.4%
Other values (395) 38302
54.7%
Number Forms
ValueCountFrequency (%)
Ⅱ 5
55.6%
Ⅳ 1
 
11.1%
Ⅲ 1
 
11.1%
ⅵ 1
 
11.1%
Ⅴ 1
 
11.1%

소재지지번주소
Text

Distinct3827
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size31.8 KiB
2023-12-11T06:52:27.565257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length45
Mean length25.536207
Min length15

Characters and Unicode

Total characters103677
Distinct characters404
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

Unique3653 ?
Unique (%)90.0%

Sample

1st row경기도 가평군 가평읍 대곡리 234-10
2nd row경기도 가평군 조종면 현리 264-19 1층
3rd row경기도 가평군 설악면 신천리 464-4 지하1층
4th row경기도 가평군 가평읍 읍내리 474-6
5th row경기도 가평군 가평읍 대곡리 232-1 외 1필지 , 2층 가동
ValueCountFrequency (%)
경기도 4060
 
18.1%
부천시 474
 
2.1%
지하1층 446
 
2.0%
평택시 398
 
1.8%
수원시 340
 
1.5%
안산시 322
 
1.4%
성남시 315
 
1.4%
2층 285
 
1.3%
중동 223
 
1.0%
지층 221
 
1.0%
Other values (4552) 15343
68.4%
2023-12-11T06:52:27.962917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21740
21.0%
1 5563
 
5.4%
시 4146
 
4.0%
도 4136
 
4.0%
기 4105
 
4.0%
경 4081
 
3.9%
동 3790
 
3.7%
- 3667
 
3.5%
2 3033
 
2.9%
3 2548
 
2.5%
Other values (394) 46868
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 53710
51.8%
Decimal Number 23357
22.5%
Space Separator 21740
21.0%
Dash Punctuation 3667
 
3.5%
Other Punctuation 395
 
0.4%
Open Punctuation 302
 
0.3%
Close Punctuation 299
 
0.3%
Uppercase Letter 174
 
0.2%
Math Symbol 25
 
< 0.1%
Letter Number 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 4146
 
7.7%
도 4136
 
7.7%
기 4105
 
7.6%
경 4081
 
7.6%
동 3790
 
7.1%
구 1566
 
2.9%
지 1543
 
2.9%
층 1497
 
2.8%
호 1216
 
2.3%
부 1012
 
1.9%
Other values (348) 26618
49.6%
Uppercase Letter
ValueCountFrequency (%)
B 110
63.2%
A 13
 
7.5%
C 12
 
6.9%
S 6
 
3.4%
H 5
 
2.9%
I 5
 
2.9%
G 4
 
2.3%
M 3
 
1.7%
E 3
 
1.7%
J 2
 
1.1%
Other values (9) 11
 
6.3%
Decimal Number
ValueCountFrequency (%)
1 5563
23.8%
2 3033
13.0%
3 2548
10.9%
0 2449
10.5%
4 2153
 
9.2%
5 1746
 
7.5%
7 1732
 
7.4%
8 1507
 
6.5%
6 1506
 
6.4%
9 1120
 
4.8%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
40.0%
Ⅴ 1
20.0%
Ⅲ 1
20.0%
Ⅳ 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 377
95.4%
. 17
 
4.3%
' 1
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 301
99.7%
[ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 298
99.7%
] 1
 
0.3%
Math Symbol
ValueCountFrequency (%)
~ 24
96.0%
> 1
 
4.0%
Lowercase Letter
ValueCountFrequency (%)
b 2
66.7%
s 1
33.3%
Space Separator
ValueCountFrequency (%)
21740
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3667
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 53710
51.8%
Common 49785
48.0%
Latin 182
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 4146
 
7.7%
도 4136
 
7.7%
기 4105
 
7.6%
경 4081
 
7.6%
동 3790
 
7.1%
구 1566
 
2.9%
지 1543
 
2.9%
층 1497
 
2.8%
호 1216
 
2.3%
부 1012
 
1.9%
Other values (348) 26618
49.6%
Latin
ValueCountFrequency (%)
B 110
60.4%
A 13
 
7.1%
C 12
 
6.6%
S 6
 
3.3%
H 5
 
2.7%
I 5
 
2.7%
G 4
 
2.2%
M 3
 
1.6%
E 3
 
1.6%
b 2
 
1.1%
Other values (15) 19
 
10.4%
Common
ValueCountFrequency (%)
21740
43.7%
1 5563
 
11.2%
- 3667
 
7.4%
2 3033
 
6.1%
3 2548
 
5.1%
0 2449
 
4.9%
4 2153
 
4.3%
5 1746
 
3.5%
7 1732
 
3.5%
8 1507
 
3.0%
Other values (11) 3647
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 53710
51.8%
ASCII 49962
48.2%
Number Forms 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21740
43.5%
1 5563
 
11.1%
- 3667
 
7.3%
2 3033
 
6.1%
3 2548
 
5.1%
0 2449
 
4.9%
4 2153
 
4.3%
5 1746
 
3.5%
7 1732
 
3.5%
8 1507
 
3.0%
Other values (32) 3824
 
7.7%
Hangul
ValueCountFrequency (%)
시 4146
 
7.7%
도 4136
 
7.7%
기 4105
 
7.6%
경 4081
 
7.6%
동 3790
 
7.1%
구 1566
 
2.9%
지 1543
 
2.9%
층 1497
 
2.8%
호 1216
 
2.3%
부 1012
 
1.9%
Other values (348) 26618
49.6%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
40.0%
Ⅴ 1
20.0%
Ⅲ 1
20.0%
Ⅳ 1
20.0%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct636
Distinct (%)15.7%
Missing14
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean14589.159
Minimum10018
Maximum18623
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.8 KiB
2023-12-11T06:52:28.077203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10018
5-th percentile10511.75
Q112556
median14623
Q316490
95-th percentile18141
Maximum18623
Range8605
Interquartile range (IQR)3934

Descriptive statistics

Standard deviation2430.5055
Coefficient of variation (CV)0.16659668
Kurtosis-1.0605584
Mean14589.159
Median Absolute Deviation (MAD)1961
Skewness-0.10268474
Sum59027739
Variance5907356.9
MonotonicityNot monotonic
2023-12-11T06:52:28.202101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14548 89
 
2.2%
14580 73
 
1.8%
15361 69
 
1.7%
10071 67
 
1.7%
17774 60
 
1.5%
16489 56
 
1.4%
17758 48
 
1.2%
15062 44
 
1.1%
14066 44
 
1.1%
16490 39
 
1.0%
Other values (626) 3457
85.1%
ValueCountFrequency (%)
10018 14
 
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
 
0.1%
10129 3
 
0.1%
ValueCountFrequency (%)
18623 3
 
0.1%
18611 5
 
0.1%
18606 22
0.5%
18600 2
 
< 0.1%
18593 20
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 

Distinct2996
Distinct (%)73.9%
Missing8
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean37.418428
Minimum36.92055
Maximum38.185409
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.8 KiB
2023-12-11T06:52:28.331252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.92055
5-th percentile37.00115
Q137.26799
median37.394255
Q337.536619
95-th percentile37.886324
Maximum38.185409
Range1.2648594
Interquartile range (IQR)0.2686285

Descriptive statistics

Standard deviation0.2423226
Coefficient of variation (CV)0.0064760228
Kurtosis-0.33444071
Mean37.418428
Median Absolute Deviation (MAD)0.12802719
Skewness0.32581818
Sum151619.47
Variance0.05872024
MonotonicityNot monotonic
2023-12-11T06:52:28.436407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.7148553223 14
 
0.3%
37.0458281259 13
 
0.3%
37.0474611388 11
 
0.3%
37.5614176573 11
 
0.3%
37.2741372443 11
 
0.3%
37.1484696706 10
 
0.2%
37.317162652 9
 
0.2%
37.1158099993 9
 
0.2%
37.2062782615 8
 
0.2%
37.2005247567 7
 
0.2%
Other values (2986) 3949
97.3%
(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%
36.9598955481 1
 
< 0.1%
36.9601292292 1
 
< 0.1%
36.9602259744 1
 
< 0.1%
36.9605436675 5
0.1%
36.9605461615 1
 
< 0.1%
36.9606437702 2
 
< 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 

Distinct2996
Distinct (%)73.9%
Missing8
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean126.99018
Minimum126.55416
Maximum127.6506
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.8 KiB
2023-12-11T06:52:28.546579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.55416
5-th percentile126.73583
Q1126.82813
median127.01961
Q3127.09619
95-th percentile127.37242
Maximum127.6506
Range1.0964451
Interquartile range (IQR)0.26806504

Descriptive statistics

Standard deviation0.19813322
Coefficient of variation (CV)0.0015602247
Kurtosis0.70628149
Mean126.99018
Median Absolute Deviation (MAD)0.12683856
Skewness0.65421196
Sum514564.23
Variance0.039256775
MonotonicityNot monotonic
2023-12-11T06:52:28.653421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.7614890719 14
 
0.3%
127.0450553425 13
 
0.3%
127.0454279562 11
 
0.3%
127.1912058889 11
 
0.3%
126.9514301863 11
 
0.3%
127.0757913493 10
 
0.2%
126.8389926577 9
 
0.2%
126.9127510897 9
 
0.2%
127.0736198125 8
 
0.2%
126.8280665927 7
 
0.2%
Other values (2986) 3949
97.3%
(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

2023-12-11T06:52:24.285503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:52:23.808427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:52:24.017550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:52:24.354913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:52:23.873230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:52:24.103350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:52:24.429911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:52:23.946034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:52:24.202271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:52:28.722455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명영업상태명위생업태명소재지우편번호WGS84위도WGS84경도
시군명1.0000.2190.4740.9990.9810.979
영업상태명0.2191.0000.8470.1470.1010.106
위생업태명0.4740.8471.0000.3100.2380.208
소재지우편번호0.9990.1470.3101.0000.9390.898
WGS84위도0.9810.1010.2380.9391.0000.752
WGS84경도0.9790.1060.2080.8980.7521.000
2023-12-11T06:52:28.800800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위생업태명시군명영업상태명위생업종명
위생업태명1.0000.1700.5451.000
시군명0.1701.0000.1151.000
영업상태명0.5450.1151.0001.000
위생업종명1.0001.0001.0001.000
2023-12-11T06:52:28.873725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도시군명영업상태명위생업종명위생업태명
소재지우편번호1.000-0.9220.0340.9360.0891.0000.135
WGS84위도-0.9221.000-0.1390.7840.0601.0000.102
WGS84경도0.034-0.1391.0000.7730.0641.0000.089
시군명0.9360.7840.7731.0000.1151.0000.170
영업상태명0.0890.0600.0640.1151.0001.0000.545
위생업종명1.0001.0001.0001.0001.0001.0001.000
위생업태명0.1350.1020.0890.1700.5451.0001.000

Missing values

2023-12-11T06:52:24.535822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:52:24.687761image/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.
2023-12-11T06:52:24.993009image/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
0가평군대부 or 보스2002-01-12영업<NA><NA><NA><NA>룸살롱경기도 가평군 가평읍 오리나무길 12경기도 가평군 가평읍 대곡리 234-101242037.826633127.514181
1가평군오아시스노래주점1988-04-15영업<NA><NA><NA><NA>룸살롱경기도 가평군 조종면 조종희망로5번길 7, 1층경기도 가평군 조종면 현리 264-19 1층1243737.818903127.349079
2가평군원타임2003-02-08영업<NA><NA><NA><NA>룸살롱경기도 가평군 설악면 신천중앙로 136-1, 지하1층경기도 가평군 설악면 신천리 464-4 지하1층1246537.677879127.488671
3가평군술마시는1박2일노래장2001-06-13영업<NA><NA><NA><NA>룸살롱경기도 가평군 가평읍 장터2길 6-14경기도 가평군 가평읍 읍내리 474-61241937.82931127.514443
4가평군장녹수20051216영업<NA><NA><NA><NA>룸살롱경기도 가평군 가평읍 굴다리길 2, 가동 2층경기도 가평군 가평읍 대곡리 232-1 외 1필지 , 2층 가동1242037.826219127.514965
5가평군개미와베짱이1982-05-15영업<NA><NA><NA><NA>스텐드바경기도 가평군 가평읍 가화로 129, 지하1층경기도 가평군 가평읍 읍내리 449-1 지하1층1241337.83114127.512818
6가평군퍼스트2010-05-17영업<NA><NA><NA><NA>룸살롱경기도 가평군 조종면 조종새싹로4번길 14, 2층경기도 가평군 조종면 현리 263-19 외 2필지, 2층1243737.818958127.349783
7가평군호반에 도시2023-06-23영업<NA><NA><NA><NA>단란주점경기도 가평군 청평면 청평중앙로 30, 지하1층경기도 가평군 청평면 청평리 434-59 지하1층1245337.736816127.418205
8가평군참새노래타운2011-04-15영업<NA><NA><NA><NA>룸살롱경기도 가평군 조종면 조종새싹로4번길 14, 지하1층경기도 가평군 조종면 현리 263-19 외 2필지, 지하1층1243737.818958127.349783
9가평군무지개노래장20041122영업<NA><NA><NA><NA>룸살롱경기도 가평군 가평읍 가화로 125, 지하1층경기도 가평군 가평읍 읍내리 470-1 지하1층1241837.830662127.513057
시군명사업장명인허가일자영업상태명폐업일자다중이용업소여부총시설규모(㎡)위생업종명위생업태명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
4050화성시카카오20201029폐업20220225<NA><NA><NA>단란주점경기도 화성시 노작로 193, 삼성프라자 3층 302호 (반송동)경기도 화성시 반송동 90-8 삼성프라자1845337.205226127.074246
4051화성시상상20180410폐업20220905<NA><NA><NA>노래클럽경기도 화성시 동탄중심상가2길 15, 수성프라자 503호 (반송동)경기도 화성시 반송동 88-8 수성프라자 503호1845337.205674127.073556
4052화성시풀하우스20151216폐업20221226<NA><NA><NA>룸살롱경기도 화성시 메타폴리스로 44, 701호 (반송동)경기도 화성시 반송동 103-5 701호1845537.201712127.072271
4053화성시콜로세움20201224폐업20211118<NA><NA><NA>단란주점경기도 화성시 병점1로 218, 씨네샤르망 B동 203호 (병점동)경기도 화성시 병점동 844-1 씨네샤르망 B동 203호1840537.213663127.042697
4054화성시스테이132022-08-18폐업2023-03-29<NA><NA><NA>단란주점경기도 화성시 향남읍 평4길 13, 지하 1층경기도 화성시 향남읍 평리 131-3 지하 1층1859337.130283126.908463
4055화성시각설이노래빠2014-02-20폐업2023-06-14<NA><NA><NA>룸살롱경기도 화성시 노작로 143, 601, 603호 (반송동, 유정프라자)경기도 화성시 반송동 106-5 유정프라자 601, 603호1845537.20068127.073539
4056화성시킹 노래주점2011-01-11폐업2023-06-13<NA><NA><NA>단란주점경기도 화성시 팔탄면 온천로 318경기도 화성시 팔탄면 덕천리 117-11857737.147026126.872366
4057화성시에스에이치 단란주점20100402폐업20221118<NA><NA><NA>단란주점경기도 화성시 병점1로 216-13 (병점동)경기도 화성시 병점동 846 태안프라자1840537.214108127.043607
4058화성시탈랜트20131111폐업20210610<NA><NA><NA>룸살롱경기도 화성시 노작로 195 (반송동, 502호)경기도 화성시 반송동 90-7 502호1845337.205388127.074335
4059화성시S나이트클럽20080911폐업 등20121210<NA><NA>유흥주점영업고고(디스코)클럽경기도 화성시 메타폴리스로 47-25 (반송동)경기도 화성시 반송동 93-6번지 센트럴 s타운 9,10층1845437.202912127.072388