Overview

Dataset statistics

Number of variables14
Number of observations4806
Missing cells13820
Missing cells (%)20.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory549.3 KiB
Average record size in memory117.0 B

Variable types

Categorical4
Text3
DateTime2
Unsupported2
Numeric3

Dataset

Description유흥주점 영업(기타) 현황_인허가
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=R47PBCY1P2RXLLDESFQA14209030&infSeq=1

Alerts

위생업태명 is highly overall correlated with 위생업종명High correlation
위생업종명 is highly overall correlated with 소재지우편번호 and 5 other fieldsHigh correlation
시군명 is highly overall correlated with 소재지우편번호 and 3 other fieldsHigh correlation
영업상태명 is highly overall correlated with 위생업종명High 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
폐업일자 has 4078 (84.9%) missing valuesMissing
다중이용업소여부 has 4806 (100.0%) missing valuesMissing
총시설규모(㎡) has 4806 (100.0%) missing valuesMissing
소재지도로명주소 has 62 (1.3%) 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 22:29:27.335247
Analysis finished2023-12-10 22:29:29.911472
Duration2.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size37.7 KiB
평택시
604 
부천시
474 
수원시
391 
안산시
335 
성남시
319 
Other values (25)
2683 

Length

Max length4
Median length3
Mean length3.1086142
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
평택시 604
 
12.6%
부천시 474
 
9.9%
수원시 391
 
8.1%
안산시 335
 
7.0%
성남시 319
 
6.6%
안양시 268
 
5.6%
동두천시 252
 
5.2%
시흥시 218
 
4.5%
화성시 187
 
3.9%
용인시 165
 
3.4%
Other values (20) 1593
33.1%

Length

2023-12-11T07:29:29.981468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
평택시 604
 
12.6%
부천시 474
 
9.9%
수원시 391
 
8.1%
안산시 335
 
7.0%
성남시 319
 
6.6%
안양시 268
 
5.6%
동두천시 252
 
5.2%
시흥시 218
 
4.5%
화성시 187
 
3.9%
용인시 165
 
3.4%
Other values (20) 1593
33.1%

사업장명
Text

Distinct3943
Distinct (%)82.0%
Missing0
Missing (%)0.0%
Memory size37.7 KiB
2023-12-11T07:29:30.318298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length5.4870995
Min length1

Characters and Unicode

Total characters26371
Distinct characters793
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3405 ?
Unique (%)70.8%

Sample

1st row썬노래타운
2nd row개미와베짱이
3rd row고구려
4th row브라보노래장
5th row무지개노래장
ValueCountFrequency (%)
단란주점 33
 
0.6%
라이브 27
 
0.5%
준코뮤직타운 25
 
0.5%
노래광장 23
 
0.4%
7080 21
 
0.4%
노래빠 19
 
0.4%
노래장 15
 
0.3%
노래주점 15
 
0.3%
노래타운 14
 
0.3%
노래클럽 14
 
0.3%
Other values (3940) 5078
96.1%
2023-12-11T07:29:30.788991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
노 1914
 
7.3%
래 1911
 
7.2%
이 782
 
3.0%
점 653
 
2.5%
0 649
 
2.5%
주 623
 
2.4%
장 612
 
2.3%
스 575
 
2.2%
라 536
 
2.0%
480
 
1.8%
Other values (783) 17636
66.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22870
86.7%
Decimal Number 1535
 
5.8%
Uppercase Letter 734
 
2.8%
Space Separator 480
 
1.8%
Lowercase Letter 259
 
1.0%
Open Punctuation 221
 
0.8%
Close Punctuation 220
 
0.8%
Other Punctuation 40
 
0.2%
Letter Number 8
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
노 1914
 
8.4%
래 1911
 
8.4%
이 782
 
3.4%
점 653
 
2.9%
주 623
 
2.7%
장 612
 
2.7%
스 575
 
2.5%
라 536
 
2.3%
광 437
 
1.9%
빠 410
 
1.8%
Other values (708) 14417
63.0%
Uppercase Letter
ValueCountFrequency (%)
S 64
 
8.7%
O 62
 
8.4%
E 50
 
6.8%
A 46
 
6.3%
N 42
 
5.7%
T 39
 
5.3%
I 39
 
5.3%
K 39
 
5.3%
B 38
 
5.2%
M 33
 
4.5%
Other values (16) 282
38.4%
Lowercase Letter
ValueCountFrequency (%)
e 30
11.6%
a 26
 
10.0%
s 21
 
8.1%
o 20
 
7.7%
r 20
 
7.7%
i 19
 
7.3%
l 17
 
6.6%
u 15
 
5.8%
h 12
 
4.6%
t 11
 
4.2%
Other values (14) 68
26.3%
Decimal Number
ValueCountFrequency (%)
0 649
42.3%
7 323
21.0%
8 310
20.2%
2 76
 
5.0%
1 63
 
4.1%
9 48
 
3.1%
3 30
 
2.0%
4 15
 
1.0%
5 12
 
0.8%
6 9
 
0.6%
Other Punctuation
ValueCountFrequency (%)
. 27
67.5%
& 5
 
12.5%
, 3
 
7.5%
# 2
 
5.0%
/ 1
 
2.5%
% 1
 
2.5%
' 1
 
2.5%
Open Punctuation
ValueCountFrequency (%)
( 218
98.6%
[ 3
 
1.4%
Close Punctuation
ValueCountFrequency (%)
) 217
98.6%
] 3
 
1.4%
Space Separator
ValueCountFrequency (%)
480
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 8
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22866
86.7%
Common 2500
 
9.5%
Latin 1001
 
3.8%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
노 1914
 
8.4%
래 1911
 
8.4%
이 782
 
3.4%
점 653
 
2.9%
주 623
 
2.7%
장 612
 
2.7%
스 575
 
2.5%
라 536
 
2.3%
광 437
 
1.9%
빠 410
 
1.8%
Other values (704) 14413
63.0%
Latin
ValueCountFrequency (%)
S 64
 
6.4%
O 62
 
6.2%
E 50
 
5.0%
A 46
 
4.6%
N 42
 
4.2%
T 39
 
3.9%
I 39
 
3.9%
K 39
 
3.9%
B 38
 
3.8%
M 33
 
3.3%
Other values (41) 549
54.8%
Common
ValueCountFrequency (%)
0 649
26.0%
480
19.2%
7 323
12.9%
8 310
12.4%
( 218
 
8.7%
) 217
 
8.7%
2 76
 
3.0%
1 63
 
2.5%
9 48
 
1.9%
3 30
 
1.2%
Other values (14) 86
 
3.4%
Han
ValueCountFrequency (%)
家 1
25.0%
大 1
25.0%
酌 1
25.0%
宮 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22864
86.7%
ASCII 3493
 
13.2%
Number Forms 8
 
< 0.1%
CJK 4
 
< 0.1%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
노 1914
 
8.4%
래 1911
 
8.4%
이 782
 
3.4%
점 653
 
2.9%
주 623
 
2.7%
장 612
 
2.7%
스 575
 
2.5%
라 536
 
2.3%
광 437
 
1.9%
빠 410
 
1.8%
Other values (702) 14411
63.0%
ASCII
ValueCountFrequency (%)
0 649
18.6%
480
13.7%
7 323
 
9.2%
8 310
 
8.9%
( 218
 
6.2%
) 217
 
6.2%
2 76
 
2.2%
S 64
 
1.8%
1 63
 
1.8%
O 62
 
1.8%
Other values (64) 1031
29.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 8
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅇ 1
50.0%
ㅋ 1
50.0%
CJK
ValueCountFrequency (%)
家 1
25.0%
大 1
25.0%
酌 1
25.0%
宮 1
25.0%

인허가일자
Date

Distinct3376
Distinct (%)70.2%
Missing0
Missing (%)0.0%
Memory size37.7 KiB
Minimum1967-08-12 00:00:00
Maximum2023-12-04 00:00:00
2023-12-11T07:29:30.911068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:31.026467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size37.7 KiB
영업
3442 
운영중
636 
폐업
460 
폐업 등
 
268

Length

Max length4
Median length2
Mean length2.2438618
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 3442
71.6%
운영중 636
 
13.2%
폐업 460
 
9.6%
폐업 등 268
 
5.6%

Length

2023-12-11T07:29:31.152094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:29:31.242014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 3442
67.8%
폐업 728
 
14.3%
운영중 636
 
12.5%
등 268
 
5.3%

폐업일자
Date

MISSING 

Distinct538
Distinct (%)73.9%
Missing4078
Missing (%)84.9%
Memory size37.7 KiB
Minimum1996-02-01 00:00:00
Maximum2023-12-04 00:00:00
2023-12-11T07:29:31.339595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:31.472564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

다중이용업소여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4806
Missing (%)100.0%
Memory size42.4 KiB

총시설규모(㎡)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4806
Missing (%)100.0%
Memory size42.4 KiB

위생업종명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.7 KiB
<NA>
3924 
유흥주점영업
882 

Length

Max length6
Median length4
Mean length4.3670412
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> 3924
81.6%
유흥주점영업 882
 
18.4%

Length

2023-12-11T07:29:31.814313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:29:31.898119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3924
81.6%
유흥주점영업 882
 
18.4%

위생업태명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size37.7 KiB
룸살롱
1858 
기타
1168 
단란주점
1040 
간이주점
317 
노래클럽
187 
Other values (8)
236 

Length

Max length12
Median length9
Mean length3.1458593
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
룸살롱 1858
38.7%
기타 1168
24.3%
단란주점 1040
21.6%
간이주점 317
 
6.6%
노래클럽 187
 
3.9%
카바레 113
 
2.4%
스텐드바 49
 
1.0%
비어(바)살롱 24
 
0.5%
고고(디스코)클럽 22
 
0.5%
<NA> 22
 
0.5%
Other values (3) 6
 
0.1%

Length

2023-12-11T07:29:32.004814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
룸살롱 1858
38.7%
기타 1168
24.3%
단란주점 1040
21.6%
간이주점 317
 
6.6%
노래클럽 187
 
3.9%
카바레 113
 
2.4%
스텐드바 49
 
1.0%
비어(바)살롱 24
 
0.5%
고고(디스코)클럽 22
 
0.5%
na 22
 
0.5%
Other values (3) 6
 
0.1%

소재지도로명주소
Text

MISSING 

Distinct4383
Distinct (%)92.4%
Missing62
Missing (%)1.3%
Memory size37.7 KiB
2023-12-11T07:29:32.230763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length78
Median length50
Mean length30.785624
Min length13

Characters and Unicode

Total characters146047
Distinct characters454
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

Unique4048 ?
Unique (%)85.3%

Sample

1st row경기도 가평군 조종면 조종희망로 11-1, 2층
2nd row경기도 가평군 가평읍 가화로 129, 지하1층
3rd row경기도 가평군 청평면 청평중앙로 62, 지하1층
4th row경기도 가평군 가평읍 오리나무길 31, 지하2층
5th row경기도 가평군 가평읍 가화로 125, 지하1층
ValueCountFrequency (%)
경기도 4744
 
15.7%
평택시 594
 
2.0%
지하1층 531
 
1.8%
2층 501
 
1.7%
부천시 471
 
1.6%
수원시 391
 
1.3%
안산시 335
 
1.1%
성남시 319
 
1.1%
안양시 267
 
0.9%
동두천시 235
 
0.8%
Other values (4021) 21843
72.3%
2023-12-11T07:29:32.704921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25558
 
17.5%
1 5730
 
3.9%
시 4978
 
3.4%
경 4910
 
3.4%
기 4816
 
3.3%
도 4808
 
3.3%
동 4629
 
3.2%
2 4449
 
3.0%
로 4355
 
3.0%
( 4194
 
2.9%
Other values (444) 77620
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 81204
55.6%
Space Separator 25558
 
17.5%
Decimal Number 25460
 
17.4%
Open Punctuation 4194
 
2.9%
Close Punctuation 4194
 
2.9%
Other Punctuation 3942
 
2.7%
Dash Punctuation 1180
 
0.8%
Uppercase Letter 273
 
0.2%
Math Symbol 26
 
< 0.1%
Letter Number 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 4978
 
6.1%
경 4910
 
6.0%
기 4816
 
5.9%
도 4808
 
5.9%
동 4629
 
5.7%
로 4355
 
5.4%
길 2541
 
3.1%
층 2435
 
3.0%
번 2016
 
2.5%
구 1905
 
2.3%
Other values (399) 43811
54.0%
Uppercase Letter
ValueCountFrequency (%)
B 178
65.2%
A 22
 
8.1%
C 10
 
3.7%
M 8
 
2.9%
K 6
 
2.2%
L 6
 
2.2%
S 6
 
2.2%
H 5
 
1.8%
N 5
 
1.8%
E 5
 
1.8%
Other values (9) 22
 
8.1%
Decimal Number
ValueCountFrequency (%)
1 5730
22.5%
2 4449
17.5%
3 3026
11.9%
0 2632
10.3%
4 2030
 
8.0%
5 2024
 
7.9%
6 1536
 
6.0%
7 1453
 
5.7%
9 1435
 
5.6%
8 1145
 
4.5%
Letter Number
ValueCountFrequency (%)
Ⅱ 5
50.0%
Ⅳ 2
 
20.0%
ⅵ 1
 
10.0%
Ⅲ 1
 
10.0%
Ⅴ 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 3923
99.5%
. 18
 
0.5%
' 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 25
96.2%
> 1
 
3.8%
Lowercase Letter
ValueCountFrequency (%)
l 4
66.7%
a 2
33.3%
Space Separator
ValueCountFrequency (%)
25558
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4194
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4194
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1180
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 81204
55.6%
Common 64554
44.2%
Latin 289
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 4978
 
6.1%
경 4910
 
6.0%
기 4816
 
5.9%
도 4808
 
5.9%
동 4629
 
5.7%
로 4355
 
5.4%
길 2541
 
3.1%
층 2435
 
3.0%
번 2016
 
2.5%
구 1905
 
2.3%
Other values (399) 43811
54.0%
Latin
ValueCountFrequency (%)
B 178
61.6%
A 22
 
7.6%
C 10
 
3.5%
M 8
 
2.8%
K 6
 
2.1%
L 6
 
2.1%
S 6
 
2.1%
Ⅱ 5
 
1.7%
H 5
 
1.7%
N 5
 
1.7%
Other values (16) 38
 
13.1%
Common
ValueCountFrequency (%)
25558
39.6%
1 5730
 
8.9%
2 4449
 
6.9%
( 4194
 
6.5%
) 4194
 
6.5%
, 3923
 
6.1%
3 3026
 
4.7%
0 2632
 
4.1%
4 2030
 
3.1%
5 2024
 
3.1%
Other values (9) 6794
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 81204
55.6%
ASCII 64833
44.4%
Number Forms 10
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25558
39.4%
1 5730
 
8.8%
2 4449
 
6.9%
( 4194
 
6.5%
) 4194
 
6.5%
, 3923
 
6.1%
3 3026
 
4.7%
0 2632
 
4.1%
4 2030
 
3.1%
5 2024
 
3.1%
Other values (30) 7073
 
10.9%
Hangul
ValueCountFrequency (%)
시 4978
 
6.1%
경 4910
 
6.0%
기 4816
 
5.9%
도 4808
 
5.9%
동 4629
 
5.7%
로 4355
 
5.4%
길 2541
 
3.1%
층 2435
 
3.0%
번 2016
 
2.5%
구 1905
 
2.3%
Other values (399) 43811
54.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 5
50.0%
Ⅳ 2
 
20.0%
ⅵ 1
 
10.0%
Ⅲ 1
 
10.0%
Ⅴ 1
 
10.0%

소재지지번주소
Text

Distinct4539
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size37.7 KiB
2023-12-11T07:29:33.017486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length45
Mean length25.246359
Min length15

Characters and Unicode

Total characters121334
Distinct characters405
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

Unique4334 ?
Unique (%)90.2%

Sample

1st row경기도 가평군 조종면 현리 411-4 2층
2nd row경기도 가평군 가평읍 읍내리 449-1 지하1층
3rd row경기도 가평군 청평면 청평리 432-16 지하1층
4th row경기도 가평군 가평읍 대곡리 164-1 지하2층
5th row경기도 가평군 가평읍 읍내리 470-1 지하1층
ValueCountFrequency (%)
경기도 4806
 
18.4%
평택시 604
 
2.3%
지하1층 509
 
2.0%
부천시 474
 
1.8%
수원시 391
 
1.5%
2층 347
 
1.3%
안산시 335
 
1.3%
성남시 319
 
1.2%
안양시 268
 
1.0%
동두천시 252
 
1.0%
Other values (5280) 17777
68.2%
2023-12-11T07:29:33.475996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24685
20.3%
1 6352
 
5.2%
도 4904
 
4.0%
시 4886
 
4.0%
기 4859
 
4.0%
경 4825
 
4.0%
동 4600
 
3.8%
- 4385
 
3.6%
2 3535
 
2.9%
3 2908
 
2.4%
Other values (395) 55395
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63725
52.5%
Decimal Number 27148
22.4%
Space Separator 24685
 
20.3%
Dash Punctuation 4385
 
3.6%
Other Punctuation 430
 
0.4%
Open Punctuation 379
 
0.3%
Close Punctuation 378
 
0.3%
Uppercase Letter 176
 
0.1%
Math Symbol 18
 
< 0.1%
Lowercase Letter 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 4904
 
7.7%
시 4886
 
7.7%
기 4859
 
7.6%
경 4825
 
7.6%
동 4600
 
7.2%
지 2423
 
3.8%
구 1760
 
2.8%
층 1678
 
2.6%
호 1299
 
2.0%
안 1246
 
2.0%
Other values (347) 31245
49.0%
Uppercase Letter
ValueCountFrequency (%)
B 113
64.2%
A 16
 
9.1%
C 11
 
6.2%
S 6
 
3.4%
H 5
 
2.8%
G 4
 
2.3%
I 3
 
1.7%
E 3
 
1.7%
M 2
 
1.1%
J 2
 
1.1%
Other values (9) 11
 
6.2%
Decimal Number
ValueCountFrequency (%)
1 6352
23.4%
2 3535
13.0%
3 2908
10.7%
0 2762
10.2%
4 2604
9.6%
5 2125
 
7.8%
7 2004
 
7.4%
6 1772
 
6.5%
8 1754
 
6.5%
9 1332
 
4.9%
Lowercase Letter
ValueCountFrequency (%)
b 2
40.0%
c 1
20.0%
d 1
20.0%
m 1
20.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
40.0%
Ⅲ 1
20.0%
Ⅳ 1
20.0%
Ⅴ 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 411
95.6%
. 18
 
4.2%
' 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 378
99.7%
[ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 377
99.7%
] 1
 
0.3%
Math Symbol
ValueCountFrequency (%)
~ 17
94.4%
> 1
 
5.6%
Space Separator
ValueCountFrequency (%)
24685
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4385
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63725
52.5%
Common 57423
47.3%
Latin 186
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 4904
 
7.7%
시 4886
 
7.7%
기 4859
 
7.6%
경 4825
 
7.6%
동 4600
 
7.2%
지 2423
 
3.8%
구 1760
 
2.8%
층 1678
 
2.6%
호 1299
 
2.0%
안 1246
 
2.0%
Other values (347) 31245
49.0%
Latin
ValueCountFrequency (%)
B 113
60.8%
A 16
 
8.6%
C 11
 
5.9%
S 6
 
3.2%
H 5
 
2.7%
G 4
 
2.2%
I 3
 
1.6%
E 3
 
1.6%
M 2
 
1.1%
J 2
 
1.1%
Other values (17) 21
 
11.3%
Common
ValueCountFrequency (%)
24685
43.0%
1 6352
 
11.1%
- 4385
 
7.6%
2 3535
 
6.2%
3 2908
 
5.1%
0 2762
 
4.8%
4 2604
 
4.5%
5 2125
 
3.7%
7 2004
 
3.5%
6 1772
 
3.1%
Other values (11) 4291
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63725
52.5%
ASCII 57604
47.5%
Number Forms 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24685
42.9%
1 6352
 
11.0%
- 4385
 
7.6%
2 3535
 
6.1%
3 2908
 
5.0%
0 2762
 
4.8%
4 2604
 
4.5%
5 2125
 
3.7%
7 2004
 
3.5%
6 1772
 
3.1%
Other values (34) 4472
 
7.8%
Hangul
ValueCountFrequency (%)
도 4904
 
7.7%
시 4886
 
7.7%
기 4859
 
7.6%
경 4825
 
7.6%
동 4600
 
7.2%
지 2423
 
3.8%
구 1760
 
2.8%
층 1678
 
2.6%
호 1299
 
2.0%
안 1246
 
2.0%
Other values (347) 31245
49.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
40.0%
Ⅲ 1
20.0%
Ⅳ 1
20.0%
Ⅴ 1
20.0%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct662
Distinct (%)13.8%
Missing22
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean14609.545
Minimum10018
Maximum18623
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size42.4 KiB
2023-12-11T07:29:33.649126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10018
5-th percentile10834
Q112448.25
median14598
Q316705
95-th percentile18139
Maximum18623
Range8605
Interquartile range (IQR)4256.75

Descriptive statistics

Standard deviation2469.1185
Coefficient of variation (CV)0.16900722
Kurtosis-1.1715818
Mean14609.545
Median Absolute Deviation (MAD)2107
Skewness-0.088227209
Sum69892063
Variance6096546.2
MonotonicityNot monotonic
2023-12-11T07:29:33.777792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11324 106
 
2.2%
17774 98
 
2.0%
14548 90
 
1.9%
17758 87
 
1.8%
14580 74
 
1.5%
15361 64
 
1.3%
16489 63
 
1.3%
10071 62
 
1.3%
14066 56
 
1.2%
15062 48
 
1.0%
Other values (652) 4036
84.0%
ValueCountFrequency (%)
10018 14
 
0.3%
10019 7
 
0.1%
10024 1
 
< 0.1%
10025 2
 
< 0.1%
10040 1
 
< 0.1%
10059 2
 
< 0.1%
10071 62
1.3%
10073 3
 
0.1%
10098 8
 
0.2%
10129 3
 
0.1%
ValueCountFrequency (%)
18623 3
 
0.1%
18611 5
 
0.1%
18606 20
0.4%
18600 3
 
0.1%
18593 24
0.5%
18591 1
 
< 0.1%
18577 1
 
< 0.1%
18567 1
 
< 0.1%
18565 5
 
0.1%
18555 1
 
< 0.1%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct3390
Distinct (%)70.9%
Missing23
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean37.419469
Minimum36.95917
Maximum38.185501
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size42.4 KiB
2023-12-11T07:29:33.908111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.95917
5-th percentile36.994938
Q137.264763
median37.392142
Q337.597433
95-th percentile37.905744
Maximum38.185501
Range1.2263309
Interquartile range (IQR)0.33267032

Descriptive statistics

Standard deviation0.25887209
Coefficient of variation (CV)0.0069181123
Kurtosis-0.49113903
Mean37.419469
Median Absolute Deviation (MAD)0.13374466
Skewness0.34725793
Sum178977.32
Variance0.067014759
MonotonicityNot monotonic
2023-12-11T07:29:34.050389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.7148553223 13
 
0.3%
37.0458281259 13
 
0.3%
37.1484696706 12
 
0.2%
37.5614176573 12
 
0.2%
37.6514200626 12
 
0.2%
37.2741372443 11
 
0.2%
37.1158099993 9
 
0.2%
37.0474611388 9
 
0.2%
37.6436073171 8
 
0.2%
37.2062782615 8
 
0.2%
Other values (3380) 4676
97.3%
(Missing) 23
 
0.5%
ValueCountFrequency (%)
36.9591698642 1
< 0.1%
36.9597125094 1
< 0.1%
36.9597668961 1
< 0.1%
36.9599465341 1
< 0.1%
36.9601292292 1
< 0.1%
36.9601632627 1
< 0.1%
36.9602259744 1
< 0.1%
36.9603626517 1
< 0.1%
36.960426741 1
< 0.1%
36.9604993278 2
< 0.1%
ValueCountFrequency (%)
38.1855007623 1
< 0.1%
38.1854088791 1
< 0.1%
38.185096312 2
< 0.1%
38.1019576622 2
< 0.1%
38.1012036186 1
< 0.1%
38.1001948371 1
< 0.1%
38.0914439791 1
< 0.1%
38.0910451365 1
< 0.1%
38.0909854253 1
< 0.1%
38.0908114997 2
< 0.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct3390
Distinct (%)70.9%
Missing23
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean127.00212
Minimum126.55679
Maximum127.70833
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size42.4 KiB
2023-12-11T07:29:34.246218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.55679
5-th percentile126.74743
Q1126.83953
median127.03493
Q3127.0934
95-th percentile127.36943
Maximum127.70833
Range1.1515426
Interquartile range (IQR)0.25386286

Descriptive statistics

Standard deviation0.19192551
Coefficient of variation (CV)0.0015111992
Kurtosis0.84403159
Mean127.00212
Median Absolute Deviation (MAD)0.10967529
Skewness0.61066921
Sum607451.15
Variance0.036835401
MonotonicityNot monotonic
2023-12-11T07:29:34.426743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.7614890719 13
 
0.3%
127.0450553425 13
 
0.3%
127.0757913493 12
 
0.2%
127.1912058889 12
 
0.2%
127.3069975916 12
 
0.2%
126.9514301863 11
 
0.2%
126.9127510897 9
 
0.2%
127.0454279562 9
 
0.2%
126.6234326771 8
 
0.2%
127.0736198125 8
 
0.2%
Other values (3380) 4676
97.3%
(Missing) 23
 
0.5%
ValueCountFrequency (%)
126.5567860205 1
< 0.1%
126.55991476 1
< 0.1%
126.5606611859 1
< 0.1%
126.5824929244 1
< 0.1%
126.5976057487 1
< 0.1%
126.5978179671 1
< 0.1%
126.5978810854 1
< 0.1%
126.5979449967 1
< 0.1%
126.5979460751 1
< 0.1%
126.5981167495 2
< 0.1%
ValueCountFrequency (%)
127.7083286196 2
< 0.1%
127.6980758264 1
< 0.1%
127.6506032269 1
< 0.1%
127.64127488 1
< 0.1%
127.6406999002 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%

Interactions

2023-12-11T07:29:29.203100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:28.698473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:28.968640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:29.280023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:28.778191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:29.041657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:29.382058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:28.866271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:29.123067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:29:34.521605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명영업상태명위생업태명소재지우편번호WGS84위도WGS84경도
시군명1.0000.4440.5230.9990.9920.979
영업상태명0.4441.0000.7960.2670.2580.214
위생업태명0.5230.7961.0000.3360.3060.247
소재지우편번호0.9990.2670.3361.0000.9420.918
WGS84위도0.9920.2580.3060.9421.0000.770
WGS84경도0.9790.2140.2470.9180.7701.000
2023-12-11T07:29:34.665510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위생업태명위생업종명시군명영업상태명
위생업태명1.0001.0000.1930.485
위생업종명1.0001.0001.0001.000
시군명0.1931.0001.0000.244
영업상태명0.4851.0000.2441.000
2023-12-11T07:29:34.782351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도시군명영업상태명위생업종명위생업태명
소재지우편번호1.000-0.9310.0130.9350.1631.0000.149
WGS84위도-0.9311.000-0.0950.8530.1571.0000.133
WGS84경도0.013-0.0951.0000.7740.1291.0000.106
시군명0.9350.8530.7741.0000.2441.0000.193
영업상태명0.1630.1570.1290.2441.0001.0000.485
위생업종명1.0001.0001.0001.0001.0001.0001.000
위생업태명0.1490.1330.1060.1930.4851.0001.000

Missing values

2023-12-11T07:29:29.501215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:29:29.683563image/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.
2023-12-11T07:29:29.814753image/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
0가평군썬노래타운2014-06-27영업<NA><NA><NA><NA>기타경기도 가평군 조종면 조종희망로 11-1, 2층경기도 가평군 조종면 현리 411-4 2층1243737.8184127.349796
1가평군개미와베짱이1982-05-15영업<NA><NA><NA><NA>스텐드바경기도 가평군 가평읍 가화로 129, 지하1층경기도 가평군 가평읍 읍내리 449-1 지하1층1241337.83114127.512818
2가평군고구려2011-05-12영업<NA><NA><NA><NA>룸살롱경기도 가평군 청평면 청평중앙로 62, 지하1층경기도 가평군 청평면 청평리 432-16 지하1층1245237.738494127.42112
3가평군브라보노래장1999-06-25영업<NA><NA><NA><NA>룸살롱경기도 가평군 가평읍 오리나무길 31, 지하2층경기도 가평군 가평읍 대곡리 164-1 지하2층1242037.824705127.514204
4가평군무지개노래장20041122영업<NA><NA><NA><NA>룸살롱경기도 가평군 가평읍 가화로 125, 지하1층경기도 가평군 가평읍 읍내리 470-1 지하1층1241837.830662127.513057
5가평군필(feel)노래주점1989-02-03영업<NA><NA><NA><NA>노래클럽경기도 가평군 북면 화악산로 5, A동 ,지하1층경기도 가평군 북면 목동리 840-4 외 1필지(840-12), 지하1층1240337.885975127.549276
6가평군프라하2007-10-24영업<NA><NA><NA><NA>스텐드바경기도 가평군 가평읍 굴다리길 11, 1층경기도 가평군 가평읍 대곡리 240-1 1층1242037.825903127.513715
7가평군동그라미단란주점2008-11-10영업<NA><NA><NA><NA>단란주점경기도 가평군 조종면 조종희망로5번길 12-4, 2층경기도 가평군 조종면 현리 264-66 외 1필지 (264-67), 2층1243737.819111127.349544
8가평군고고노래바2008-02-26영업<NA><NA><NA><NA>룸살롱경기도 가평군 설악면 신천중앙로 91, B동 지하1층경기도 가평군 설악면 신천리 408-27 외 2필지, B동 지하1층1246737.676707127.493139
9가평군가람노래클럽2006-12-14영업<NA><NA><NA><NA>노래클럽경기도 가평군 설악면 신천중앙로 93, 지하1층경기도 가평군 설악면 신천리 410-2 외 1필지, 지하1층1246737.676779127.492969
시군명사업장명인허가일자영업상태명폐업일자다중이용업소여부총시설규모(㎡)위생업종명위생업태명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
4796화성시마돈나20090423폐업20210609<NA><NA><NA>단란주점경기도 화성시 향남읍 행정중앙2로 63-34경기도 화성시 향남읍 행정리 486-1 명신프라자 2동1860037.130569126.922567
4797화성시카카오20201029폐업20220225<NA><NA><NA>단란주점경기도 화성시 노작로 193, 삼성프라자 3층 302호 (반송동)경기도 화성시 반송동 90-8 삼성프라자1845337.205226127.074246
4798화성시상상20180410폐업20220905<NA><NA><NA>노래클럽경기도 화성시 동탄중심상가2길 15, 수성프라자 503호 (반송동)경기도 화성시 반송동 88-8 수성프라자 503호1845337.205674127.073556
4799화성시19노래클럽2018-09-17폐업2023-07-10<NA><NA><NA>룸살롱경기도 화성시 남양읍 시청로 119, 206호경기도 화성시 남양읍 남양리 2072-11 206호1827137.200516126.826489
4800화성시마스터룸20130418폐업20220920<NA><NA><NA>룸살롱경기도 화성시 동탄중심상가2길 31 (반송동, 성진빌딩 604호)경기도 화성시 반송동 88-5 (성진빌딩 604호)1845337.206278127.07362
4801화성시아프리카20111115폐업20220920<NA><NA><NA>룸살롱경기도 화성시 동탄중심상가2길 31 (반송동, 88-5 성진빌딩 602)경기도 화성시 반송동 88-5 성진빌딩 602호1845337.206278127.07362
4802화성시킹 노래주점2011-01-11폐업2023-06-13<NA><NA><NA>단란주점경기도 화성시 팔탄면 온천로 318경기도 화성시 팔탄면 덕천리 117-11857737.147026126.872366
4803화성시노래천국20050621폐업 등20071001<NA><NA>유흥주점영업기타경기도 화성시 떡전골로 96-4경기도 화성시 병점동 382-2번지 미라클프라자 502,503호1841237.207022127.034274
4804화성시블루스키20071129폐업 등20100611<NA><NA>유흥주점영업기타경기도 화성시 동탄중심상가2길 11경기도 화성시 반송동 88-9번지 (삼성파크뷰 403호)1845337.205772127.073273
4805화성시제부노래빵20021116폐업 등20030418<NA><NA>유흥주점영업기타경기도 화성시 서신면 해안길 296-8경기도 화성시 서신면 제부리 190-192번지1855337.167358126.618376