Overview

Dataset statistics

Number of variables39
Number of observations10000
Missing cells103127
Missing cells (%)26.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 MiB
Average record size in memory343.0 B

Variable types

Categorical15
Text5
Numeric8
Unsupported9
DateTime1
Boolean1

Alerts

영업장주변구분명 is highly imbalanced (74.3%)Imbalance
등급구분명 is highly imbalanced (94.8%)Imbalance
급수시설구분명 is highly imbalanced (57.6%)Imbalance
다중이용업소여부 is highly imbalanced (82.7%)Imbalance
소재지도로명주소 has 473 (4.7%) missing valuesMissing
소재지우편번호 has 267 (2.7%) missing valuesMissing
위도 has 131 (1.3%) missing valuesMissing
경도 has 131 (1.3%) missing valuesMissing
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 3725 (37.2%) missing valuesMissing
휴업시작일자 has 10000 (100.0%) missing valuesMissing
휴업종료일자 has 10000 (100.0%) missing valuesMissing
재개업일자 has 10000 (100.0%) missing valuesMissing
소재지시설전화번호 has 6090 (60.9%) missing valuesMissing
소재지면적정보 has 693 (6.9%) missing valuesMissing
X좌표값 has 476 (4.8%) missing valuesMissing
Y좌표값 has 476 (4.8%) missing valuesMissing
남성종사자수 has 5201 (52.0%) missing valuesMissing
여성종사자수 has 5168 (51.7%) missing valuesMissing
건물소유구분명 has 10000 (100.0%) missing valuesMissing
다중이용업소여부 has 123 (1.2%) missing valuesMissing
시설총규모정보 has 123 (1.2%) missing valuesMissing
전통업소지정번호 has 10000 (100.0%) missing valuesMissing
전통업소주된음식 has 10000 (100.0%) missing valuesMissing
홈페이지URL has 10000 (100.0%) missing valuesMissing
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적정보 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물소유구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지URL is an unsupported type, check if it needs cleaning or further analysisUnsupported
남성종사자수 has 4566 (45.7%) zerosZeros
여성종사자수 has 4528 (45.3%) zerosZeros
시설총규모정보 has 793 (7.9%) zerosZeros

Reproduction

Analysis started2024-05-03 18:53:23.222723
Analysis finished2024-05-03 18:53:28.076826
Duration4.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
고양시
3216 
남양주시
1416 
부천시
1130 
김포시
1104 
광주시
764 
Other values (6)
2370 

Length

Max length4
Median length3
Mean length3.1638
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row고양시
2nd row고양시
3rd row구리시
4th row구리시
5th row고양시

Common Values

ValueCountFrequency (%)
고양시 3216
32.2%
남양주시 1416
14.2%
부천시 1130
 
11.3%
김포시 1104
 
11.0%
광주시 764
 
7.6%
광명시 600
 
6.0%
구리시 578
 
5.8%
군포시 510
 
5.1%
가평군 257
 
2.6%
동두천시 222
 
2.2%

Length

2024-05-03T18:53:28.225534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고양시 3216
32.2%
남양주시 1416
14.2%
부천시 1130
 
11.3%
김포시 1104
 
11.0%
광주시 764
 
7.6%
광명시 600
 
6.0%
구리시 578
 
5.8%
군포시 510
 
5.1%
가평군 257
 
2.6%
동두천시 222
 
2.2%

사업장명
Text

Distinct9083
Distinct (%)90.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-03T18:53:28.655439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length33
Mean length7.873
Min length1

Characters and Unicode

Total characters78730
Distinct characters1079
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8499 ?
Unique (%)85.0%

Sample

1st row미르투스(Myrtus)
2nd row연이만두
3rd row카페마하나임
4th row명랑핫도그
5th row아이센스리그행신본점
ValueCountFrequency (%)
세븐일레븐 212
 
1.6%
씨유 174
 
1.3%
gs25 93
 
0.7%
카페 83
 
0.6%
coffee 60
 
0.4%
지에스25 52
 
0.4%
이마트24 43
 
0.3%
cafe 41
 
0.3%
메가엠지씨커피 39
 
0.3%
지에스(gs)25 37
 
0.3%
Other values (9796) 12571
93.8%
2024-05-03T18:53:29.526884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3408
 
4.3%
점 3279
 
4.2%
스 2232
 
2.8%
이 1696
 
2.2%
) 1485
 
1.9%
( 1477
 
1.9%
피 1386
 
1.8%
리 1317
 
1.7%
커 1058
 
1.3%
페 871
 
1.1%
Other values (1069) 60521
76.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63401
80.5%
Uppercase Letter 3768
 
4.8%
Space Separator 3408
 
4.3%
Lowercase Letter 3107
 
3.9%
Decimal Number 1784
 
2.3%
Close Punctuation 1494
 
1.9%
Open Punctuation 1486
 
1.9%
Other Punctuation 249
 
0.3%
Dash Punctuation 19
 
< 0.1%
Math Symbol 6
 
< 0.1%
Other values (3) 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 3279
 
5.2%
스 2232
 
3.5%
이 1696
 
2.7%
피 1386
 
2.2%
리 1317
 
2.1%
커 1058
 
1.7%
페 871
 
1.4%
카 865
 
1.4%
다 837
 
1.3%
마 780
 
1.2%
Other values (980) 49080
77.4%
Uppercase Letter
ValueCountFrequency (%)
C 456
12.1%
S 437
11.6%
G 408
 
10.8%
E 310
 
8.2%
A 228
 
6.1%
O 206
 
5.5%
F 187
 
5.0%
P 170
 
4.5%
U 153
 
4.1%
T 142
 
3.8%
Other values (16) 1071
28.4%
Lowercase Letter
ValueCountFrequency (%)
e 547
17.6%
a 311
10.0%
o 300
 
9.7%
f 256
 
8.2%
c 180
 
5.8%
r 162
 
5.2%
n 154
 
5.0%
i 148
 
4.8%
t 148
 
4.8%
s 141
 
4.5%
Other values (15) 760
24.5%
Other Punctuation
ValueCountFrequency (%)
& 101
40.6%
, 55
22.1%
. 44
17.7%
' 23
 
9.2%
# 5
 
2.0%
% 4
 
1.6%
: 4
 
1.6%
/ 4
 
1.6%
! 2
 
0.8%
* 2
 
0.8%
Other values (3) 5
 
2.0%
Decimal Number
ValueCountFrequency (%)
2 677
37.9%
5 491
27.5%
1 167
 
9.4%
4 128
 
7.2%
3 93
 
5.2%
0 61
 
3.4%
9 57
 
3.2%
8 55
 
3.1%
6 29
 
1.6%
7 26
 
1.5%
Math Symbol
ValueCountFrequency (%)
= 2
33.3%
+ 2
33.3%
< 1
16.7%
> 1
16.7%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
33.3%
Ⅰ 1
33.3%
Ⅲ 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 1485
99.4%
] 9
 
0.6%
Open Punctuation
ValueCountFrequency (%)
( 1477
99.4%
[ 9
 
0.6%
Space Separator
ValueCountFrequency (%)
3408
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%
Other Symbol
ValueCountFrequency (%)
° 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63388
80.5%
Common 8451
 
10.7%
Latin 6878
 
8.7%
Han 13
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 3279
 
5.2%
스 2232
 
3.5%
이 1696
 
2.7%
피 1386
 
2.2%
리 1317
 
2.1%
커 1058
 
1.7%
페 871
 
1.4%
카 865
 
1.4%
다 837
 
1.3%
마 780
 
1.2%
Other values (968) 49067
77.4%
Latin
ValueCountFrequency (%)
e 547
 
8.0%
C 456
 
6.6%
S 437
 
6.4%
G 408
 
5.9%
a 311
 
4.5%
E 310
 
4.5%
o 300
 
4.4%
f 256
 
3.7%
A 228
 
3.3%
O 206
 
3.0%
Other values (44) 3419
49.7%
Common
ValueCountFrequency (%)
3408
40.3%
) 1485
17.6%
( 1477
17.5%
2 677
 
8.0%
5 491
 
5.8%
1 167
 
2.0%
4 128
 
1.5%
& 101
 
1.2%
3 93
 
1.1%
0 61
 
0.7%
Other values (25) 363
 
4.3%
Han
ValueCountFrequency (%)
米 2
15.4%
李 1
7.7%
雪 1
7.7%
人 1
7.7%
旻 1
7.7%
安 1
7.7%
愛 1
7.7%
休 1
7.7%
自 1
7.7%
樂 1
7.7%
Other values (2) 2
15.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63385
80.5%
ASCII 15321
 
19.5%
CJK 12
 
< 0.1%
Compat Jamo 3
 
< 0.1%
None 3
 
< 0.1%
Number Forms 3
 
< 0.1%
Punctuation 2
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3408
22.2%
) 1485
 
9.7%
( 1477
 
9.6%
2 677
 
4.4%
e 547
 
3.6%
5 491
 
3.2%
C 456
 
3.0%
S 437
 
2.9%
G 408
 
2.7%
a 311
 
2.0%
Other values (73) 5624
36.7%
Hangul
ValueCountFrequency (%)
점 3279
 
5.2%
스 2232
 
3.5%
이 1696
 
2.7%
피 1386
 
2.2%
리 1317
 
2.1%
커 1058
 
1.7%
페 871
 
1.4%
카 865
 
1.4%
다 837
 
1.3%
마 780
 
1.2%
Other values (966) 49064
77.4%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
66.7%
ㄹ 1
33.3%
Punctuation
ValueCountFrequency (%)
′ 2
100.0%
CJK
ValueCountFrequency (%)
米 2
16.7%
雪 1
8.3%
人 1
8.3%
旻 1
8.3%
安 1
8.3%
愛 1
8.3%
休 1
8.3%
自 1
8.3%
樂 1
8.3%
光 1
8.3%
None
ValueCountFrequency (%)
· 2
66.7%
° 1
33.3%
CJK Compat Ideographs
ValueCountFrequency (%)
李 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
33.3%
Ⅰ 1
33.3%
Ⅲ 1
33.3%

인허가일자
Text

Distinct5639
Distinct (%)56.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-03T18:53:30.086496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.516
Min length8

Characters and Unicode

Total characters85160
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

Unique3220 ?
Unique (%)32.2%

Sample

1st row20181217
2nd row20151126
3rd row20150408
4th row2017-02-08
5th row20190103
ValueCountFrequency (%)
20201029 11
 
0.1%
20170829 11
 
0.1%
20140410 9
 
0.1%
20171020 9
 
0.1%
2023-06-02 9
 
0.1%
20170807 9
 
0.1%
20100412 9
 
0.1%
2023-03-24 8
 
0.1%
20190515 8
 
0.1%
2023-10-24 8
 
0.1%
Other values (5629) 9909
99.1%
2024-05-03T18:53:31.049797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 24075
28.3%
2 19367
22.7%
1 15206
17.9%
- 5160
 
6.1%
9 4043
 
4.7%
3 3656
 
4.3%
8 2946
 
3.5%
7 2797
 
3.3%
4 2699
 
3.2%
6 2693
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80000
93.9%
Dash Punctuation 5160
 
6.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 24075
30.1%
2 19367
24.2%
1 15206
19.0%
9 4043
 
5.1%
3 3656
 
4.6%
8 2946
 
3.7%
7 2797
 
3.5%
4 2699
 
3.4%
6 2693
 
3.4%
5 2518
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 5160
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 85160
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 24075
28.3%
2 19367
22.7%
1 15206
17.9%
- 5160
 
6.1%
9 4043
 
4.7%
3 3656
 
4.3%
8 2946
 
3.5%
7 2797
 
3.3%
4 2699
 
3.2%
6 2693
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 85160
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 24075
28.3%
2 19367
22.7%
1 15206
17.9%
- 5160
 
6.1%
9 4043
 
4.7%
3 3656
 
4.3%
8 2946
 
3.5%
7 2797
 
3.3%
4 2699
 
3.2%
6 2693
 
3.2%

소재지도로명주소
Text

MISSING 

Distinct8915
Distinct (%)93.6%
Missing473
Missing (%)4.7%
Memory size156.2 KiB
2024-05-03T18:53:31.761586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length74
Median length60
Mean length35.954235
Min length13

Characters and Unicode

Total characters342536
Distinct characters667
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8587 ?
Unique (%)90.1%

Sample

1st row경기도 고양시 일산서구 대화로398번길 7-9, 1층일부호 (대화동)
2nd row경기도 고양시 일산서구 강성로 268, 102호 (대화동, 성저마을 상가동)
3rd row경기도 구리시 응달말로 4, 1층 (인창동)
4th row경기도 구리시 건원대로34번길 9, 1층 106호 (인창동)
5th row경기도 고양시 덕양구 충장로 22, 탑프라자 306(일부)호 (행신동)
ValueCountFrequency (%)
경기도 9527
 
13.5%
1층 3518
 
5.0%
고양시 3117
 
4.4%
남양주시 1341
 
1.9%
일부호 1199
 
1.7%
일산서구 1140
 
1.6%
부천시 1076
 
1.5%
김포시 1054
 
1.5%
덕양구 1041
 
1.5%
일산동구 936
 
1.3%
Other values (8755) 46413
66.0%
2024-05-03T18:53:32.798098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
60939
 
17.8%
1 17673
 
5.2%
동 10987
 
3.2%
경 10215
 
3.0%
도 10091
 
2.9%
시 10009
 
2.9%
, 9947
 
2.9%
기 9762
 
2.8%
로 9358
 
2.7%
) 8975
 
2.6%
Other values (657) 184580
53.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 195191
57.0%
Space Separator 60939
 
17.8%
Decimal Number 54681
 
16.0%
Other Punctuation 9994
 
2.9%
Close Punctuation 8975
 
2.6%
Open Punctuation 8974
 
2.6%
Dash Punctuation 2188
 
0.6%
Uppercase Letter 1311
 
0.4%
Lowercase Letter 187
 
0.1%
Math Symbol 83
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 10987
 
5.6%
경 10215
 
5.2%
도 10091
 
5.2%
시 10009
 
5.1%
기 9762
 
5.0%
로 9358
 
4.8%
양 6508
 
3.3%
일 6069
 
3.1%
호 5906
 
3.0%
층 5861
 
3.0%
Other values (580) 110425
56.6%
Uppercase Letter
ValueCountFrequency (%)
B 281
21.4%
A 222
16.9%
C 123
9.4%
E 76
 
5.8%
D 54
 
4.1%
T 54
 
4.1%
I 53
 
4.0%
K 53
 
4.0%
L 51
 
3.9%
S 51
 
3.9%
Other values (15) 293
22.3%
Lowercase Letter
ValueCountFrequency (%)
e 51
27.3%
l 16
 
8.6%
a 15
 
8.0%
o 12
 
6.4%
b 10
 
5.3%
c 10
 
5.3%
s 9
 
4.8%
r 9
 
4.8%
h 7
 
3.7%
n 7
 
3.7%
Other values (13) 41
21.9%
Decimal Number
ValueCountFrequency (%)
1 17673
32.3%
2 7235
13.2%
0 6014
 
11.0%
3 4786
 
8.8%
4 3684
 
6.7%
5 3522
 
6.4%
7 3305
 
6.0%
6 3096
 
5.7%
8 2951
 
5.4%
9 2415
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 9947
99.5%
. 22
 
0.2%
/ 11
 
0.1%
& 5
 
0.1%
@ 4
 
< 0.1%
· 3
 
< 0.1%
? 1
 
< 0.1%
※ 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 80
96.4%
> 1
 
1.2%
< 1
 
1.2%
↔ 1
 
1.2%
Letter Number
ValueCountFrequency (%)
Ⅱ 6
46.2%
Ⅰ 5
38.5%
Ⅲ 2
 
15.4%
Space Separator
ValueCountFrequency (%)
60939
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8975
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8974
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2188
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 195190
57.0%
Common 145834
42.6%
Latin 1511
 
0.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 10987
 
5.6%
경 10215
 
5.2%
도 10091
 
5.2%
시 10009
 
5.1%
기 9762
 
5.0%
로 9358
 
4.8%
양 6508
 
3.3%
일 6069
 
3.1%
호 5906
 
3.0%
층 5861
 
3.0%
Other values (579) 110424
56.6%
Latin
ValueCountFrequency (%)
B 281
18.6%
A 222
14.7%
C 123
 
8.1%
E 76
 
5.0%
D 54
 
3.6%
T 54
 
3.6%
I 53
 
3.5%
K 53
 
3.5%
L 51
 
3.4%
S 51
 
3.4%
Other values (41) 493
32.6%
Common
ValueCountFrequency (%)
60939
41.8%
1 17673
 
12.1%
, 9947
 
6.8%
) 8975
 
6.2%
( 8974
 
6.2%
2 7235
 
5.0%
0 6014
 
4.1%
3 4786
 
3.3%
4 3684
 
2.5%
5 3522
 
2.4%
Other values (16) 14085
 
9.7%
Han
ValueCountFrequency (%)
美 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 195189
57.0%
ASCII 147327
43.0%
Number Forms 13
 
< 0.1%
None 3
 
< 0.1%
CJK 1
 
< 0.1%
Arrows 1
 
< 0.1%
Punctuation 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
60939
41.4%
1 17673
 
12.0%
, 9947
 
6.8%
) 8975
 
6.1%
( 8974
 
6.1%
2 7235
 
4.9%
0 6014
 
4.1%
3 4786
 
3.2%
4 3684
 
2.5%
5 3522
 
2.4%
Other values (61) 15578
 
10.6%
Hangul
ValueCountFrequency (%)
동 10987
 
5.6%
경 10215
 
5.2%
도 10091
 
5.2%
시 10009
 
5.1%
기 9762
 
5.0%
로 9358
 
4.8%
양 6508
 
3.3%
일 6069
 
3.1%
호 5906
 
3.0%
층 5861
 
3.0%
Other values (578) 110423
56.6%
Number Forms
ValueCountFrequency (%)
Ⅱ 6
46.2%
Ⅰ 5
38.5%
Ⅲ 2
 
15.4%
None
ValueCountFrequency (%)
· 3
100.0%
CJK
ValueCountFrequency (%)
美 1
100.0%
Arrows
ValueCountFrequency (%)
↔ 1
100.0%
Punctuation
ValueCountFrequency (%)
※ 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅣ 1
100.0%

소재지지번주소
Text

Distinct9170
Distinct (%)92.2%
Missing50
Missing (%)0.5%
Memory size156.2 KiB
2024-05-03T18:53:33.385555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length57
Mean length29.433467
Min length6

Characters and Unicode

Total characters292863
Distinct characters644
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8764 ?
Unique (%)88.1%

Sample

1st row경기도 고양시 일산서구 대화동 2087-3
2nd row경기도 고양시 일산서구 대화동 2215 성저마을 상가동 102호
3rd row경기도 구리시 인창동 288-20번지 1층
4th row경기도 구리시 인창동 670-9 1층 106호
5th row경기도 고양시 덕양구 행신동 761-3 탑프라자 306호일부
ValueCountFrequency (%)
경기도 9948
 
16.2%
고양시 3201
 
5.2%
1층 1853
 
3.0%
남양주시 1409
 
2.3%
일산서구 1174
 
1.9%
부천시 1123
 
1.8%
김포시 1099
 
1.8%
덕양구 1074
 
1.7%
일산동구 953
 
1.6%
광주시 760
 
1.2%
Other values (10989) 38836
63.2%
2024-05-03T18:53:34.364146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
56398
 
19.3%
1 15482
 
5.3%
동 10947
 
3.7%
도 10411
 
3.6%
시 10292
 
3.5%
기 10132
 
3.5%
경 10113
 
3.5%
지 7097
 
2.4%
2 6970
 
2.4%
- 6564
 
2.2%
Other values (634) 148457
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 169802
58.0%
Space Separator 56398
 
19.3%
Decimal Number 56238
 
19.2%
Dash Punctuation 6564
 
2.2%
Uppercase Letter 1068
 
0.4%
Other Punctuation 960
 
0.3%
Open Punctuation 786
 
0.3%
Close Punctuation 783
 
0.3%
Lowercase Letter 174
 
0.1%
Math Symbol 73
 
< 0.1%
Other values (2) 17
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 10947
 
6.4%
도 10411
 
6.1%
시 10292
 
6.1%
기 10132
 
6.0%
경 10113
 
6.0%
지 7097
 
4.2%
양 6437
 
3.8%
번 5080
 
3.0%
일 4943
 
2.9%
구 4601
 
2.7%
Other values (556) 89749
52.9%
Uppercase Letter
ValueCountFrequency (%)
B 207
19.4%
A 182
17.0%
C 96
9.0%
E 63
 
5.9%
S 61
 
5.7%
T 54
 
5.1%
G 50
 
4.7%
L 43
 
4.0%
K 43
 
4.0%
D 38
 
3.6%
Other values (15) 231
21.6%
Lowercase Letter
ValueCountFrequency (%)
e 46
26.4%
a 15
 
8.6%
l 14
 
8.0%
o 12
 
6.9%
r 9
 
5.2%
s 9
 
5.2%
c 9
 
5.2%
h 7
 
4.0%
i 6
 
3.4%
n 6
 
3.4%
Other values (14) 41
23.6%
Decimal Number
ValueCountFrequency (%)
1 15482
27.5%
2 6970
12.4%
0 6440
11.5%
3 4823
 
8.6%
6 4591
 
8.2%
4 4312
 
7.7%
7 3847
 
6.8%
5 3778
 
6.7%
8 3243
 
5.8%
9 2752
 
4.9%
Other Punctuation
ValueCountFrequency (%)
, 901
93.9%
& 23
 
2.4%
. 17
 
1.8%
/ 8
 
0.8%
@ 7
 
0.7%
· 2
 
0.2%
% 1
 
0.1%
※ 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 71
97.3%
> 1
 
1.4%
< 1
 
1.4%
Letter Number
ValueCountFrequency (%)
Ⅰ 8
50.0%
Ⅱ 5
31.2%
Ⅲ 3
 
18.8%
Space Separator
ValueCountFrequency (%)
56398
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6564
100.0%
Open Punctuation
ValueCountFrequency (%)
( 786
100.0%
Close Punctuation
ValueCountFrequency (%)
) 783
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 169800
58.0%
Common 121803
41.6%
Latin 1258
 
0.4%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 10947
 
6.4%
도 10411
 
6.1%
시 10292
 
6.1%
기 10132
 
6.0%
경 10113
 
6.0%
지 7097
 
4.2%
양 6437
 
3.8%
번 5080
 
3.0%
일 4943
 
2.9%
구 4601
 
2.7%
Other values (554) 89747
52.9%
Latin
ValueCountFrequency (%)
B 207
16.5%
A 182
14.5%
C 96
 
7.6%
E 63
 
5.0%
S 61
 
4.8%
T 54
 
4.3%
G 50
 
4.0%
e 46
 
3.7%
L 43
 
3.4%
K 43
 
3.4%
Other values (42) 413
32.8%
Common
ValueCountFrequency (%)
56398
46.3%
1 15482
 
12.7%
2 6970
 
5.7%
- 6564
 
5.4%
0 6440
 
5.3%
3 4823
 
4.0%
6 4591
 
3.8%
4 4312
 
3.5%
7 3847
 
3.2%
5 3778
 
3.1%
Other values (16) 8598
 
7.1%
Han
ValueCountFrequency (%)
內 1
50.0%
美 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 169799
58.0%
ASCII 123042
42.0%
Number Forms 16
 
< 0.1%
None 2
 
< 0.1%
CJK 2
 
< 0.1%
Punctuation 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
56398
45.8%
1 15482
 
12.6%
2 6970
 
5.7%
- 6564
 
5.3%
0 6440
 
5.2%
3 4823
 
3.9%
6 4591
 
3.7%
4 4312
 
3.5%
7 3847
 
3.1%
5 3778
 
3.1%
Other values (63) 9837
 
8.0%
Hangul
ValueCountFrequency (%)
동 10947
 
6.4%
도 10411
 
6.1%
시 10292
 
6.1%
기 10132
 
6.0%
경 10113
 
6.0%
지 7097
 
4.2%
양 6437
 
3.8%
번 5080
 
3.0%
일 4943
 
2.9%
구 4601
 
2.7%
Other values (553) 89746
52.9%
Number Forms
ValueCountFrequency (%)
Ⅰ 8
50.0%
Ⅱ 5
31.2%
Ⅲ 3
 
18.8%
None
ValueCountFrequency (%)
· 2
100.0%
CJK
ValueCountFrequency (%)
內 1
50.0%
美 1
50.0%
Punctuation
ValueCountFrequency (%)
※ 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅣ 1
100.0%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct1378
Distinct (%)14.2%
Missing267
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean12003.52
Minimum10003
Maximum15890
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:53:34.881995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10003
5-th percentile10073
Q110390
median11938
Q312805
95-th percentile15800
Maximum15890
Range5887
Interquartile range (IQR)2415

Descriptive statistics

Standard deviation1783.7582
Coefficient of variation (CV)0.14860292
Kurtosis-0.86331489
Mean12003.52
Median Absolute Deviation (MAD)1547
Skewness0.6286636
Sum1.1683026 × 108
Variance3181793.3
MonotonicityNot monotonic
2024-05-03T18:53:35.304245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10390 304
 
3.0%
10391 174
 
1.7%
10401 141
 
1.4%
14546 105
 
1.1%
15865 90
 
0.9%
10071 87
 
0.9%
10595 87
 
0.9%
10500 84
 
0.8%
14548 76
 
0.8%
11922 74
 
0.7%
Other values (1368) 8511
85.1%
(Missing) 267
 
2.7%
ValueCountFrequency (%)
10003 1
 
< 0.1%
10004 1
 
< 0.1%
10005 1
 
< 0.1%
10008 3
 
< 0.1%
10009 2
 
< 0.1%
10010 2
 
< 0.1%
10011 14
0.1%
10012 8
0.1%
10013 3
 
< 0.1%
10014 1
 
< 0.1%
ValueCountFrequency (%)
15890 1
 
< 0.1%
15889 1
 
< 0.1%
15888 4
 
< 0.1%
15887 2
 
< 0.1%
15886 3
 
< 0.1%
15885 11
0.1%
15884 1
 
< 0.1%
15881 1
 
< 0.1%
15880 15
0.1%
15878 2
 
< 0.1%

위도
Real number (ℝ)

MISSING 

Distinct7157
Distinct (%)72.5%
Missing131
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean37.592003
Minimum37.288632
Maximum37.947881
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:53:35.764071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.288632
5-th percentile37.360231
Q137.491359
median37.634306
Q337.665464
95-th percentile37.726239
Maximum37.947881
Range0.65924876
Interquartile range (IQR)0.17410411

Descriptive statistics

Standard deviation0.12116534
Coefficient of variation (CV)0.003223168
Kurtosis-0.047556451
Mean37.592003
Median Absolute Deviation (MAD)0.0427932
Skewness-0.30565599
Sum370995.48
Variance0.014681039
MonotonicityNot monotonic
2024-05-03T18:53:36.285656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6685436 103
 
1.0%
37.6679786706 87
 
0.9%
37.6649345 79
 
0.8%
37.6679645 70
 
0.7%
37.5043171668 62
 
0.6%
37.6470962619 52
 
0.5%
37.6690309166 46
 
0.5%
37.6027017 40
 
0.4%
37.5025517408 30
 
0.3%
37.6577996 28
 
0.3%
Other values (7147) 9272
92.7%
(Missing) 131
 
1.3%
ValueCountFrequency (%)
37.2886319428 1
< 0.1%
37.2911304 1
< 0.1%
37.2945416 1
< 0.1%
37.2964626747 1
< 0.1%
37.3039708155 1
< 0.1%
37.3142459628 1
< 0.1%
37.3152859216 1
< 0.1%
37.3153514104 2
< 0.1%
37.3156149651 1
< 0.1%
37.3156760154 1
< 0.1%
ValueCountFrequency (%)
37.9478807 1
< 0.1%
37.947475128 1
< 0.1%
37.9470331654 1
< 0.1%
37.9458264 1
< 0.1%
37.944593418 1
< 0.1%
37.9345797 1
< 0.1%
37.9324891862 1
< 0.1%
37.9324854666 1
< 0.1%
37.9311622932 1
< 0.1%
37.9310986 1
< 0.1%

경도
Real number (ℝ)

MISSING 

Distinct7159
Distinct (%)72.5%
Missing131
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean126.93193
Minimum126.52778
Maximum127.55484
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:53:36.798687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.52778
5-th percentile126.66832
Q1126.76681
median126.85109
Q3127.1404
95-th percentile127.30604
Maximum127.55484
Range1.0270531
Interquartile range (IQR)0.37358524

Descriptive statistics

Standard deviation0.2168104
Coefficient of variation (CV)0.001708084
Kurtosis-0.62170995
Mean126.93193
Median Absolute Deviation (MAD)0.10101225
Skewness0.67403265
Sum1252691.2
Variance0.047006751
MonotonicityNot monotonic
2024-05-03T18:53:37.284850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.7442442 103
 
1.0%
126.7516242854 87
 
0.9%
126.7418539 79
 
0.8%
126.7513867 70
 
0.7%
126.7620745903 62
 
0.6%
126.8948092677 52
 
0.5%
126.7456041294 46
 
0.5%
127.143949 40
 
0.4%
126.7753741701 30
 
0.3%
126.7634563 28
 
0.3%
Other values (7149) 9272
92.7%
(Missing) 131
 
1.3%
ValueCountFrequency (%)
126.5277844892 1
< 0.1%
126.5325401 1
< 0.1%
126.5373874904 1
< 0.1%
126.5374279 1
< 0.1%
126.5376099095 1
< 0.1%
126.5417394585 1
< 0.1%
126.5430528165 1
< 0.1%
126.5451755 1
< 0.1%
126.5460934539 1
< 0.1%
126.5519820071 1
< 0.1%
ValueCountFrequency (%)
127.5548375712 1
 
< 0.1%
127.5498818 1
 
< 0.1%
127.5488562014 1
 
< 0.1%
127.5467944736 2
 
< 0.1%
127.5464997 1
 
< 0.1%
127.5434705352 9
0.1%
127.5429810465 1
 
< 0.1%
127.5427783405 1
 
< 0.1%
127.5377534321 1
 
< 0.1%
127.5309148 2
 
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

통합영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
6275 
영업/정상
3725 

Length

Max length5
Median length2
Mean length3.1175
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 6275
62.7%
영업/정상 3725
37.2%

Length

2024-05-03T18:53:37.844586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T18:53:38.183914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 6275
62.7%
영업/정상 3725
37.2%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
6275 
영업
3725 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 6275
62.7%
영업 3725
37.2%

Length

2024-05-03T18:53:38.550071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T18:53:38.876373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 6275
62.7%
영업 3725
37.2%

폐업일자
Date

MISSING 

Distinct3482
Distinct (%)55.5%
Missing3725
Missing (%)37.2%
Memory size156.2 KiB
Minimum1994-04-22 00:00:00
Maximum2024-04-29 00:00:00
2024-05-03T18:53:39.270904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:53:39.703584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

소재지시설전화번호
Text

MISSING 

Distinct3723
Distinct (%)95.2%
Missing6090
Missing (%)60.9%
Memory size156.2 KiB
2024-05-03T18:53:40.606339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.129923
Min length3

Characters and Unicode

Total characters43518
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3570 ?
Unique (%)91.3%

Sample

1st row031 913 5838
2nd row031 988 4569
3rd row031 3958923
4th row031 5916880
5th row070 77868187
ValueCountFrequency (%)
031 2450
27.4%
02 307
 
3.4%
032 286
 
3.2%
070 154
 
1.7%
981 35
 
0.4%
584 30
 
0.3%
901 22
 
0.2%
381 20
 
0.2%
393 19
 
0.2%
908 19
 
0.2%
Other values (3901) 5590
62.6%
2024-05-03T18:53:41.862747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6499
14.9%
3 5580
12.8%
5251
12.1%
1 5227
12.0%
9 3641
8.4%
2 3413
7.8%
5 3126
7.2%
7 3050
7.0%
8 2889
6.6%
6 2775
6.4%
Other values (2) 2067
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38257
87.9%
Space Separator 5251
 
12.1%
Dash Punctuation 10
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6499
17.0%
3 5580
14.6%
1 5227
13.7%
9 3641
9.5%
2 3413
8.9%
5 3126
8.2%
7 3050
8.0%
8 2889
7.6%
6 2775
7.3%
4 2057
 
5.4%
Space Separator
ValueCountFrequency (%)
5251
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 43518
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6499
14.9%
3 5580
12.8%
5251
12.1%
1 5227
12.0%
9 3641
8.4%
2 3413
7.8%
5 3126
7.2%
7 3050
7.0%
8 2889
6.6%
6 2775
6.4%
Other values (2) 2067
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43518
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6499
14.9%
3 5580
12.8%
5251
12.1%
1 5227
12.0%
9 3641
8.4%
2 3413
7.8%
5 3126
7.2%
7 3050
7.0%
8 2889
6.6%
6 2775
6.4%
Other values (2) 2067
 
4.7%

소재지면적정보
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing693
Missing (%)6.9%
Memory size156.2 KiB

업태구분명정보
Categorical

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
커피숍
3169 
일반조리판매
1904 
기타 휴게음식점
1821 
편의점
1029 
패스트푸드
672 
Other values (16)
1405 

Length

Max length8
Median length6
Mean length4.602
Min length2

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row커피숍
2nd row일반조리판매
3rd row커피숍
4th row일반조리판매
5th row일반조리판매

Common Values

ValueCountFrequency (%)
커피숍 3169
31.7%
일반조리판매 1904
19.0%
기타 휴게음식점 1821
18.2%
편의점 1029
 
10.3%
패스트푸드 672
 
6.7%
다방 564
 
5.6%
과자점 333
 
3.3%
푸드트럭 163
 
1.6%
백화점 114
 
1.1%
아이스크림 73
 
0.7%
Other values (11) 158
 
1.6%

Length

2024-05-03T18:53:42.555827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 3169
26.8%
일반조리판매 1904
16.1%
기타 1821
15.4%
휴게음식점 1821
15.4%
편의점 1029
 
8.7%
패스트푸드 672
 
5.7%
다방 564
 
4.8%
과자점 333
 
2.8%
푸드트럭 163
 
1.4%
백화점 114
 
1.0%
Other values (12) 231
 
2.0%

X좌표값
Real number (ℝ)

MISSING 

Distinct6207
Distinct (%)65.2%
Missing476
Missing (%)4.8%
Infinite0
Infinite (%)0.0%
Mean193599.59
Minimum158281.51
Maximum248699.12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:53:43.043969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum158281.51
5-th percentile170826.72
Q1179234.9
median185971.01
Q3212038.51
95-th percentile226951.73
Maximum248699.12
Range90417.61
Interquartile range (IQR)32803.617

Descriptive statistics

Standard deviation19079.407
Coefficient of variation (CV)0.098550862
Kurtosis-0.56197644
Mean193599.59
Median Absolute Deviation (MAD)8600.191
Skewness0.71660507
Sum1.8438425 × 109
Variance3.6402375 × 108
MonotonicityNot monotonic
2024-05-03T18:53:43.791720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
178006.080301401 170
 
1.7%
177370.820174218 165
 
1.7%
177158.311187542 111
 
1.1%
212647.021160325 67
 
0.7%
178901.991280584 64
 
0.6%
190715.654303376 48
 
0.5%
179812.331183859 43
 
0.4%
178268.135568909 35
 
0.4%
180053.344972882 34
 
0.3%
178901.990959407 33
 
0.3%
Other values (6197) 8754
87.5%
(Missing) 476
 
4.8%
ValueCountFrequency (%)
158281.512813295 1
< 0.1%
158725.795348565 1
< 0.1%
159154.342925004 1
< 0.1%
159156.996079611 1
< 0.1%
159165.07829775 1
< 0.1%
159487.166025587 1
< 0.1%
159600.779001594 1
< 0.1%
159839.973514478 1
< 0.1%
159925.74385239 1
< 0.1%
160431.887800665 1
< 0.1%
ValueCountFrequency (%)
248699.122760014 1
 
< 0.1%
248308.098320321 1
 
< 0.1%
248083.742562785 3
 
< 0.1%
247996.643663801 3
 
< 0.1%
247981.087699743 6
 
0.1%
247821.826583542 1
 
< 0.1%
247808.332027237 1
 
< 0.1%
247311.113102939 1
 
< 0.1%
246687.384766675 2
 
< 0.1%
246498.753278505 16
0.2%

Y좌표값
Real number (ℝ)

MISSING 

Distinct6211
Distinct (%)65.2%
Missing476
Missing (%)4.8%
Infinite0
Infinite (%)0.0%
Mean455053.19
Minimum420788.98
Maximum560834.91
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:53:44.201120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum420788.98
5-th percentile428721.9
Q1443393.32
median459216.21
Q3462799.52
95-th percentile470566.95
Maximum560834.91
Range140045.93
Interquartile range (IQR)19406.198

Descriptive statistics

Standard deviation15425.578
Coefficient of variation (CV)0.033898407
Kurtosis10.29913
Mean455053.19
Median Absolute Deviation (MAD)4840.4996
Skewness1.4229045
Sum4.3339266 × 109
Variance2.3794847 × 108
MonotonicityNot monotonic
2024-05-03T18:53:44.705352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
462865.812502378 170
 
1.7%
462947.515785368 165
 
1.7%
462546.660972252 111
 
1.1%
455616.655198478 67
 
0.7%
444701.557193 64
 
0.6%
560834.907896845 48
 
0.5%
462059.506265122 43
 
0.4%
462480.734362689 35
 
0.4%
444507.865626959 34
 
0.3%
444701.557249589 33
 
0.3%
Other values (6201) 8754
87.5%
(Missing) 476
 
4.8%
ValueCountFrequency (%)
420788.975855547 1
< 0.1%
421076.867130329 1
< 0.1%
421453.240952218 1
< 0.1%
421658.637355512 1
< 0.1%
422491.208056651 1
< 0.1%
423547.458917674 1
< 0.1%
423702.210108406 1
< 0.1%
423706.330364949 2
< 0.1%
423745.334055661 1
< 0.1%
423798.945163094 1
< 0.1%
ValueCountFrequency (%)
560834.907896845 48
0.5%
558895.2705657 2
 
< 0.1%
493921.187077467 1
 
< 0.1%
493865.680219095 1
 
< 0.1%
493814.121634862 1
 
< 0.1%
493690.985120779 1
 
< 0.1%
493674.924324616 1
 
< 0.1%
493562.294108815 1
 
< 0.1%
492550.73385417 1
 
< 0.1%
492344.619267014 1
 
< 0.1%

위생업태명
Categorical

Distinct22
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
커피숍
3114 
일반조리판매
1898 
기타 휴게음식점
1789 
편의점
1008 
패스트푸드
670 
Other values (17)
1521 

Length

Max length8
Median length6
Mean length4.5957
Min length2

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row커피숍
2nd row일반조리판매
3rd row커피숍
4th row일반조리판매
5th row일반조리판매

Common Values

ValueCountFrequency (%)
커피숍 3114
31.1%
일반조리판매 1898
19.0%
기타 휴게음식점 1789
17.9%
편의점 1008
 
10.1%
패스트푸드 670
 
6.7%
다방 564
 
5.6%
과자점 333
 
3.3%
푸드트럭 161
 
1.6%
<NA> 123
 
1.2%
백화점 114
 
1.1%
Other values (12) 226
 
2.3%

Length

2024-05-03T18:53:45.187452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 3114
26.4%
일반조리판매 1898
16.1%
기타 1789
15.2%
휴게음식점 1789
15.2%
편의점 1008
 
8.6%
패스트푸드 670
 
5.7%
다방 564
 
4.8%
과자점 333
 
2.8%
푸드트럭 161
 
1.4%
na 123
 
1.0%
Other values (13) 340
 
2.9%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.1%
Missing5201
Missing (%)52.0%
Infinite0
Infinite (%)0.0%
Mean0.058137112
Minimum0
Maximum5
Zeros4566
Zeros (%)45.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:53:45.513199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.28973682
Coefficient of variation (CV)4.983681
Kurtosis71.346118
Mean0.058137112
Median Absolute Deviation (MAD)0
Skewness7.0792723
Sum279
Variance0.083947425
MonotonicityNot monotonic
2024-05-03T18:53:45.865688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 4566
45.7%
1 204
 
2.0%
2 17
 
0.2%
3 9
 
0.1%
5 2
 
< 0.1%
4 1
 
< 0.1%
(Missing) 5201
52.0%
ValueCountFrequency (%)
0 4566
45.7%
1 204
 
2.0%
2 17
 
0.2%
3 9
 
0.1%
4 1
 
< 0.1%
5 2
 
< 0.1%
ValueCountFrequency (%)
5 2
 
< 0.1%
4 1
 
< 0.1%
3 9
 
0.1%
2 17
 
0.2%
1 204
 
2.0%
0 4566
45.7%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.2%
Missing5168
Missing (%)51.7%
Infinite0
Infinite (%)0.0%
Mean0.095612583
Minimum0
Maximum10
Zeros4528
Zeros (%)45.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:53:46.222838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.48871068
Coefficient of variation (CV)5.1113636
Kurtosis143.84135
Mean0.095612583
Median Absolute Deviation (MAD)0
Skewness9.8798442
Sum462
Variance0.23883813
MonotonicityNot monotonic
2024-05-03T18:53:46.583093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 4528
45.3%
1 224
 
2.2%
2 49
 
0.5%
3 15
 
0.1%
4 7
 
0.1%
5 2
 
< 0.1%
8 2
 
< 0.1%
6 2
 
< 0.1%
10 2
 
< 0.1%
9 1
 
< 0.1%
(Missing) 5168
51.7%
ValueCountFrequency (%)
0 4528
45.3%
1 224
 
2.2%
2 49
 
0.5%
3 15
 
0.1%
4 7
 
0.1%
5 2
 
< 0.1%
6 2
 
< 0.1%
8 2
 
< 0.1%
9 1
 
< 0.1%
10 2
 
< 0.1%
ValueCountFrequency (%)
10 2
 
< 0.1%
9 1
 
< 0.1%
8 2
 
< 0.1%
6 2
 
< 0.1%
5 2
 
< 0.1%
4 7
 
0.1%
3 15
 
0.1%
2 49
 
0.5%
1 224
 
2.2%
0 4528
45.3%

영업장주변구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8756 
기타
 
612
주택가주변
 
349
아파트지역
 
154
유흥업소밀집지역
 
105
Other values (3)
 
24

Length

Max length8
Median length4
Mean length3.9789
Min length2

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> 8756
87.6%
기타 612
 
6.1%
주택가주변 349
 
3.5%
아파트지역 154
 
1.5%
유흥업소밀집지역 105
 
1.1%
학교정화(상대) 9
 
0.1%
학교정화(절대) 9
 
0.1%
결혼예식장주변 6
 
0.1%

Length

2024-05-03T18:53:46.952003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T18:53:47.383087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8756
87.6%
기타 612
 
6.1%
주택가주변 349
 
3.5%
아파트지역 154
 
1.5%
유흥업소밀집지역 105
 
1.1%
학교정화(상대 9
 
0.1%
학교정화(절대 9
 
0.1%
결혼예식장주변 6
 
0.1%

등급구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9836 
자율
 
57
기타
 
56
지도
 
24
관리
 
18
Other values (3)
 
9

Length

Max length4
Median length4
Mean length3.967
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9836
98.4%
자율 57
 
0.6%
기타 56
 
0.6%
지도 24
 
0.2%
관리 18
 
0.2%
우수 7
 
0.1%
갑 1
 
< 0.1%
을 1
 
< 0.1%

Length

2024-05-03T18:53:47.835967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T18:53:48.240851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9836
98.4%
자율 57
 
0.6%
기타 56
 
0.6%
지도 24
 
0.2%
관리 18
 
0.2%
우수 7
 
0.1%
갑 1
 
< 0.1%
을 1
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
상수도전용
5576 
<NA>
4284 
지하수전용
 
109
전용상수도(특정시설의 자가용 수도)
 
16
상수도(음용)지하수(주방용)겸용
 
8

Length

Max length19
Median length5
Mean length4.6036
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 5576
55.8%
<NA> 4284
42.8%
지하수전용 109
 
1.1%
전용상수도(특정시설의 자가용 수도) 16
 
0.2%
상수도(음용)지하수(주방용)겸용 8
 
0.1%
간이상수도 7
 
0.1%

Length

2024-05-03T18:53:48.628971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T18:53:48.975527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 5576
55.6%
na 4284
42.7%
지하수전용 109
 
1.1%
전용상수도(특정시설의 16
 
0.2%
자가용 16
 
0.2%
수도 16
 
0.2%
상수도(음용)지하수(주방용)겸용 8
 
0.1%
간이상수도 7
 
0.1%

총종업원수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6461 
0
3539 

Length

Max length4
Median length4
Mean length2.9383
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 6461
64.6%
0 3539
35.4%

Length

2024-05-03T18:53:49.379544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T18:53:49.715691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6461
64.6%
0 3539
35.4%

본사종업원수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6429 
0
3571 

Length

Max length4
Median length4
Mean length2.9287
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 6429
64.3%
0 3571
35.7%

Length

2024-05-03T18:53:50.080357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T18:53:50.411266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6429
64.3%
0 3571
35.7%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6429 
0
3571 

Length

Max length4
Median length4
Mean length2.9287
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 6429
64.3%
0 3571
35.7%

Length

2024-05-03T18:53:50.772728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T18:53:51.102760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6429
64.3%
0 3571
35.7%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6429 
0
3571 

Length

Max length4
Median length4
Mean length2.9287
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 6429
64.3%
0 3571
35.7%

Length

2024-05-03T18:53:51.468976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T18:53:51.843179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6429
64.3%
0 3571
35.7%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6429 
0
3571 

Length

Max length4
Median length4
Mean length2.9287
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 6429
64.3%
0 3571
35.7%

Length

2024-05-03T18:53:52.331501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T18:53:52.677277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6429
64.3%
0 3571
35.7%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

보증액
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6429 
0
3571 

Length

Max length4
Median length4
Mean length2.9287
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 6429
64.3%
0 3571
35.7%

Length

2024-05-03T18:53:53.029041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T18:53:53.406870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6429
64.3%
0 3571
35.7%

월세액
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6429 
0
3571 

Length

Max length4
Median length4
Mean length2.9287
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 6429
64.3%
0 3571
35.7%

Length

2024-05-03T18:53:53.839468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T18:53:54.211014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6429
64.3%
0 3571
35.7%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing123
Missing (%)1.2%
Memory size97.7 KiB
False
9621 
True
 
256
(Missing)
 
123
ValueCountFrequency (%)
False 9621
96.2%
True 256
 
2.6%
(Missing) 123
 
1.2%
2024-05-03T18:53:54.571699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모정보
Real number (ℝ)

MISSING  ZEROS 

Distinct4058
Distinct (%)41.1%
Missing123
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean43.213856
Minimum0
Maximum1883
Zeros793
Zeros (%)7.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:53:54.971179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19.9
median29.12
Q350.5
95-th percentile136.466
Maximum1883
Range1883
Interquartile range (IQR)40.6

Descriptive statistics

Standard deviation64.487021
Coefficient of variation (CV)1.4922765
Kurtosis169.59751
Mean43.213856
Median Absolute Deviation (MAD)20.12
Skewness8.7585028
Sum426823.26
Variance4158.5759
MonotonicityNot monotonic
2024-05-03T18:53:55.483201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 793
 
7.9%
3.3 510
 
5.1%
10.0 173
 
1.7%
6.6 161
 
1.6%
33.0 97
 
1.0%
9.0 92
 
0.9%
3.0 66
 
0.7%
18.0 60
 
0.6%
6.0 59
 
0.6%
36.0 56
 
0.6%
Other values (4048) 7810
78.1%
(Missing) 123
 
1.2%
ValueCountFrequency (%)
0.0 793
7.9%
0.44 1
 
< 0.1%
0.48 1
 
< 0.1%
0.5 1
 
< 0.1%
0.54 1
 
< 0.1%
0.59 2
 
< 0.1%
0.62 1
 
< 0.1%
0.7 1
 
< 0.1%
0.85 1
 
< 0.1%
0.98 1
 
< 0.1%
ValueCountFrequency (%)
1883.0 1
< 0.1%
1736.42 1
< 0.1%
1575.97 1
< 0.1%
992.14 1
< 0.1%
891.0 1
< 0.1%
856.11 1
< 0.1%
702.0 1
< 0.1%
672.5 1
< 0.1%
645.92 1
< 0.1%
628.78 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

홈페이지URL
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Sample

시군명사업장명인허가일자소재지도로명주소소재지지번주소소재지우편번호위도경도인허가취소일자통합영업상태명영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지시설전화번호소재지면적정보업태구분명정보X좌표값Y좌표값위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모정보전통업소지정번호전통업소주된음식홈페이지URL
4449고양시미르투스(Myrtus)20181217경기도 고양시 일산서구 대화로398번길 7-9, 1층일부호 (대화동)경기도 고양시 일산서구 대화동 2087-31036737.682318126.752955<NA>폐업폐업20221025<NA><NA><NA><NA>72.75커피숍178140.482898464461.983799커피숍00<NA><NA>상수도전용00000<NA>00N72.75<NA><NA><NA>
7320고양시연이만두20151126경기도 고양시 일산서구 강성로 268, 102호 (대화동, 성저마을 상가동)경기도 고양시 일산서구 대화동 2215 성저마을 상가동 102호1037637.677319126.747822<NA>폐업폐업20210413<NA><NA><NA>031 913 583828.38일반조리판매177695.390071464005.979322일반조리판매<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N28.38<NA><NA><NA>
18892구리시카페마하나임20150408경기도 구리시 응달말로 4, 1층 (인창동)경기도 구리시 인창동 288-20번지 1층1192637.600891127.135951<NA>폐업폐업20160523<NA><NA><NA><NA>47.85커피숍211939.327066455421.568769커피숍<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N47.85<NA><NA><NA>
17880구리시명랑핫도그2017-02-08경기도 구리시 건원대로34번길 9, 1층 106호 (인창동)경기도 구리시 인창동 670-9 1층 106호1192137.604378127.140851<NA>폐업폐업2023-07-11<NA><NA><NA><NA>18.17일반조리판매212369.212478455794.015908일반조리판매00<NA><NA>상수도전용00000<NA>00N18.17<NA><NA><NA>
6875고양시아이센스리그행신본점20190103경기도 고양시 덕양구 충장로 22, 탑프라자 306(일부)호 (행신동)경기도 고양시 덕양구 행신동 761-3 탑프라자 306호일부1052637.614801126.834452<NA>폐업폐업20220427<NA><NA><NA><NA>35.28일반조리판매185316.605456953.615일반조리판매00<NA><NA>상수도전용00000<NA>00N35.28<NA><NA><NA>
24992김포시홍짜장20090817경기도 김포시 사우중로 88 102호 (사우동,신영프라자)경기도 김포시 사우동 873번지 신영프라자 102호1011137.622083126.721468<NA>폐업폐업20121015<NA><NA><NA>031 988 456946.80일반조리판매175346.670139457793.618416일반조리판매<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N46.8<NA><NA><NA>
21133군포시행운20021122<NA>경기도 군포시 당정동 168번지1584737.356057126.956921<NA>폐업폐업20021201<NA><NA><NA>031 3958923NaN일반조리판매196117.328419428234.123565일반조리판매00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
25999남양주시뜨란20190411경기도 남양주시 오남읍 진건오남로577번길 11, 2층 일부경기도 남양주시 오남읍 오남리 538-1번지 2층 일부1204937.684665127.209642<NA>영업/정상영업<NA><NA><NA><NA>031 59168809.60커피숍218427.607134464723.782298커피숍<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N9.6<NA><NA><NA>
28964남양주시커피브레이크20090417경기도 남양주시 오남읍 진건오남로797번길 11 (107-2)경기도 남양주시 오남읍 양지리 106-3번지 107-21204537.698131127.201028<NA>폐업폐업20141127<NA><NA><NA>070 7786818745.00커피숍217665.377613466218.573256커피숍<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N45.0<NA><NA><NA>
22030김포시더그레이2022-09-07경기도 김포시 김포한강11로 442, 2층 일부호 (운양동)경기도 김포시 운양동 1264-21007437.653742126.697465<NA>영업/정상영업<NA><NA><NA><NA><NA>161.90커피숍173238.089399461302.855619커피숍00<NA><NA>상수도전용00000<NA>00Y241.92<NA><NA><NA>
시군명사업장명인허가일자소재지도로명주소소재지지번주소소재지우편번호위도경도인허가취소일자통합영업상태명영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지시설전화번호소재지면적정보업태구분명정보X좌표값Y좌표값위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모정보전통업소지정번호전통업소주된음식홈페이지URL
2380고양시나뚜루(킨텍스전시장)20161011경기도 고양시 일산서구 킨텍스로 217-60 (대화동, 킨텍스제1전시장 4~5홀 일부)경기도 고양시 일산서구 대화동 2600번지 킨텍스제1전시장 4~5홀 일부1039037.668544126.744244<NA>폐업폐업20161018<NA><NA><NA><NA>9.00아이스크림177370.820174462947.515785아이스크림<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N9.0<NA><NA><NA>
12161과천시만가리 김밥20160509경기도 과천시 별양상가2로 20, 44,48호 (별양동, 새서울쇼핑)경기도 과천시 별양동 1-18번지 새서울쇼핑 44,48호1383737.42675126.992499<NA>폐업폐업20180531<NA><NA><NA><NA>55.06일반조리판매199271.515436077.66일반조리판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N55.06<NA><NA><NA>
24461김포시커피에반하다 김포학운점20180201경기도 김포시 양촌읍 학운산단3로25번길 14-2, 1층 101호 일부호경기도 김포시 양촌읍 학운리 3308번지 101호 일부호1004937.605193126.593336<NA>영업/정상영업<NA><NA><NA><NA><NA>49.00커피숍164025.92722455961.369208커피숍<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N49.0<NA><NA><NA>
23395김포시씨유송마로드점20180709경기도 김포시 대곶면 대곶로 239, 1층 일부호경기도 김포시 대곶면 송마리 545-4번지 1층 일부호1002737.664983126.554428<NA>영업/정상영업<NA><NA><NA><NA><NA>6.60편의점160650.160606462605.146978편의점<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N6.6<NA><NA><NA>
25910남양주시동원다방19811230<NA>경기도 남양주시 다산동 3194-1번지1224937.610808127.166785<NA>폐업폐업19960120<NA><NA><NA><NA>NaN다방214662.185329456518.723048다방<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
11842고양시황금잉어20171219경기도 고양시 일산동구 숲속마을로 49-32, 103호 일부호 (풍동)경기도 고양시 일산동구 풍동 1285-11030737.665806126.79692<NA>폐업폐업20211025<NA><NA><NA><NA>6.80기타 휴게음식점182013.541681462619.565926기타 휴게음식점00<NA><NA><NA>00000<NA>00N6.8<NA><NA><NA>
20949군포시킹와플20131108경기도 군포시 산본로323번길 26-26, 1층 102호 (산본동, 씨티빌딩)경기도 군포시 산본동 1138-3번지1586537.35945126.930596<NA>폐업폐업20151120<NA><NA><NA>031 395 389530.57커피숍193785.723075428611.517088커피숍<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N30.57<NA><NA><NA>
28833남양주시카페브런치2011-11-03경기도 남양주시 진접읍 해밀예당3로 134 (진접프라자 104호)경기도 남양주시 진접읍 금곡리 973 진접프라자104호1205537.721228127.195446<NA>폐업폐업2023-02-14<NA><NA><NA>031 571 163039.11커피숍217160.589378468771.690027커피숍00<NA><NA>상수도전용00000<NA>00N39.11<NA><NA><NA>
21229김포시105 CAFE20200703경기도 김포시 김포한강1로 250, 골든타임 1층 104호 (운양동)경기도 김포시 운양동 1307-3 골든타임 104호1007837.653314126.684921<NA>폐업폐업20200706<NA><NA><NA><NA>55.61커피숍172128.333252461262.941307커피숍<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N55.61<NA><NA><NA>
32191부천시김지현베이커리19891111경기도 부천시 부흥로 185-1 (중동)경기도 부천시 중동 677-16번지1458537.496371126.763328<NA>폐업폐업20020304<NA><NA><NA>663532824.74과자점179005.815295443832.635156과자점00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N24.74<NA><NA><NA>