Overview

Dataset statistics

Number of variables44
Number of observations10000
Missing cells97364
Missing cells (%)22.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 MiB
Average record size in memory383.0 B

Variable types

Categorical19
Text6
DateTime4
Unsupported8
Numeric6
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-18666/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
급수시설구분명 is highly imbalanced (56.6%)Imbalance
총인원 is highly imbalanced (80.9%)Imbalance
본사종업원수 is highly imbalanced (80.7%)Imbalance
공장사무직종업원수 is highly imbalanced (80.7%)Imbalance
공장판매직종업원수 is highly imbalanced (80.7%)Imbalance
공장생산직종업원수 is highly imbalanced (80.7%)Imbalance
보증액 is highly imbalanced (80.7%)Imbalance
월세액 is highly imbalanced (80.7%)Imbalance
다중이용업소여부 is highly imbalanced (88.4%)Imbalance
전통업소주된음식 is highly imbalanced (99.9%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 1871 (18.7%) missing valuesMissing
휴업시작일자 has 10000 (100.0%) missing valuesMissing
휴업종료일자 has 10000 (100.0%) missing valuesMissing
재개업일자 has 10000 (100.0%) missing valuesMissing
전화번호 has 2764 (27.6%) missing valuesMissing
도로명주소 has 5709 (57.1%) missing valuesMissing
도로명우편번호 has 5779 (57.8%) missing valuesMissing
좌표정보(X) has 310 (3.1%) missing valuesMissing
좌표정보(Y) has 310 (3.1%) missing valuesMissing
남성종사자수 has 3826 (38.3%) missing valuesMissing
여성종사자수 has 3744 (37.4%) missing valuesMissing
건물소유구분명 has 10000 (100.0%) missing valuesMissing
다중이용업소여부 has 1501 (15.0%) missing valuesMissing
시설총규모 has 1501 (15.0%) missing valuesMissing
전통업소지정번호 has 9997 (> 99.9%) missing valuesMissing
홈페이지 has 10000 (100.0%) missing valuesMissing
여성종사자수 is highly skewed (γ1 = 44.78666375)Skewed
관리번호 has unique valuesUnique
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
전화번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 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
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
남성종사자수 has 4525 (45.2%) zerosZeros
여성종사자수 has 3440 (34.4%) zerosZeros

Reproduction

Analysis started2024-05-17 22:54:19.512342
Analysis finished2024-05-17 22:54:24.178510
Duration4.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3140000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3140000
2nd row3140000
3rd row3140000
4th row3140000
5th row3140000

Common Values

ValueCountFrequency (%)
3140000 10000
100.0%

Length

2024-05-18T07:54:24.414923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:54:24.795088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 10000
100.0%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T07:54:25.486703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters220000
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

Unique10000 ?
Unique (%)100.0%

Sample

1st row3140000-101-2013-00233
2nd row3140000-101-2014-00252
3rd row3140000-101-2016-00035
4th row3140000-101-2014-00302
5th row3140000-101-2017-00024
ValueCountFrequency (%)
3140000-101-2013-00233 1
 
< 0.1%
3140000-101-1994-03768 1
 
< 0.1%
3140000-101-1997-03013 1
 
< 0.1%
3140000-101-1997-01748 1
 
< 0.1%
3140000-101-2021-00156 1
 
< 0.1%
3140000-101-1992-01249 1
 
< 0.1%
3140000-101-1993-00220 1
 
< 0.1%
3140000-101-2011-00175 1
 
< 0.1%
3140000-101-2021-00381 1
 
< 0.1%
3140000-101-2022-00054 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-05-18T07:54:26.425510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 80026
36.4%
1 41478
18.9%
- 30000
 
13.6%
3 15126
 
6.9%
4 14403
 
6.5%
2 12505
 
5.7%
9 10498
 
4.8%
8 4563
 
2.1%
5 3869
 
1.8%
7 3837
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 190000
86.4%
Dash Punctuation 30000
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 80026
42.1%
1 41478
21.8%
3 15126
 
8.0%
4 14403
 
7.6%
2 12505
 
6.6%
9 10498
 
5.5%
8 4563
 
2.4%
5 3869
 
2.0%
7 3837
 
2.0%
6 3695
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 80026
36.4%
1 41478
18.9%
- 30000
 
13.6%
3 15126
 
6.9%
4 14403
 
6.5%
2 12505
 
5.7%
9 10498
 
4.8%
8 4563
 
2.1%
5 3869
 
1.8%
7 3837
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 80026
36.4%
1 41478
18.9%
- 30000
 
13.6%
3 15126
 
6.9%
4 14403
 
6.5%
2 12505
 
5.7%
9 10498
 
4.8%
8 4563
 
2.1%
5 3869
 
1.8%
7 3837
 
1.7%

인허가일자
Date

Distinct6010
Distinct (%)60.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1976-03-09 00:00:00
Maximum2024-05-16 00:00:00
2024-05-18T07:54:26.821939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:54:27.369803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

영업상태코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
8129 
1
1871 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row1
4th row3
5th row1

Common Values

ValueCountFrequency (%)
3 8129
81.3%
1 1871
 
18.7%

Length

2024-05-18T07:54:27.967970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:54:28.350492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 8129
81.3%
1 1871
 
18.7%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
8129 
영업/정상
1871 

Length

Max length5
Median length2
Mean length2.5613
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row폐업
3rd row영업/정상
4th row폐업
5th row영업/정상

Common Values

ValueCountFrequency (%)
폐업 8129
81.3%
영업/정상 1871
 
18.7%

Length

2024-05-18T07:54:28.741843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:54:29.051512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 8129
81.3%
영업/정상 1871
 
18.7%

상세영업상태코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
8129 
1
1871 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row1
4th row2
5th row1

Common Values

ValueCountFrequency (%)
2 8129
81.3%
1 1871
 
18.7%

Length

2024-05-18T07:54:29.397451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:54:29.719178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 8129
81.3%
1 1871
 
18.7%

상세영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
8129 
영업
1871 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 8129
81.3%
영업 1871
 
18.7%

Length

2024-05-18T07:54:30.119978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:54:30.529855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 8129
81.3%
영업 1871
 
18.7%

폐업일자
Date

MISSING 

Distinct4591
Distinct (%)56.5%
Missing1871
Missing (%)18.7%
Memory size156.2 KiB
Minimum1989-03-27 00:00:00
Maximum2024-05-16 00:00:00
2024-05-18T07:54:30.933230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:54:31.566471image/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

전화번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2764
Missing (%)27.6%
Memory size156.2 KiB

소재지면적
Unsupported

REJECTED  UNSUPPORTED 

Missing52
Missing (%)0.5%
Memory size156.2 KiB

소재지우편번호
Text

Distinct207
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T07:54:32.704787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1003
Min length6

Characters and Unicode

Total characters61003
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

Unique22 ?
Unique (%)0.2%

Sample

1st row158829
2nd row158864
3rd row158857
4th row158805
5th row158791
ValueCountFrequency (%)
158860 462
 
4.6%
158861 407
 
4.1%
158811 398
 
4.0%
158806 376
 
3.8%
158050 370
 
3.7%
158827 369
 
3.7%
158070 350
 
3.5%
158857 271
 
2.7%
158819 259
 
2.6%
158849 258
 
2.6%
Other values (197) 6480
64.8%
2024-05-18T07:54:34.623769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 19756
32.4%
1 12868
21.1%
5 12222
20.0%
0 3626
 
5.9%
6 2496
 
4.1%
7 2172
 
3.6%
2 2124
 
3.5%
4 2083
 
3.4%
9 1424
 
2.3%
3 1229
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60000
98.4%
Dash Punctuation 1003
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 19756
32.9%
1 12868
21.4%
5 12222
20.4%
0 3626
 
6.0%
6 2496
 
4.2%
7 2172
 
3.6%
2 2124
 
3.5%
4 2083
 
3.5%
9 1424
 
2.4%
3 1229
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 1003
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61003
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 19756
32.4%
1 12868
21.1%
5 12222
20.0%
0 3626
 
5.9%
6 2496
 
4.1%
7 2172
 
3.6%
2 2124
 
3.5%
4 2083
 
3.4%
9 1424
 
2.3%
3 1229
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61003
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 19756
32.4%
1 12868
21.1%
5 12222
20.0%
0 3626
 
5.9%
6 2496
 
4.1%
7 2172
 
3.6%
2 2124
 
3.5%
4 2083
 
3.4%
9 1424
 
2.3%
3 1229
 
2.0%

지번주소
Text

Distinct7223
Distinct (%)72.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T07:54:36.173578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length56
Mean length25.7321
Min length16

Characters and Unicode

Total characters257321
Distinct characters391
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5802 ?
Unique (%)58.0%

Sample

1st row서울특별시 양천구 신월동 160-9번지 1층
2nd row서울특별시 양천구 신정동 1179-15번지 1층
3rd row서울특별시 양천구 신정동 900-6 지상2층
4th row서울특별시 양천구 목동 324-150 1층
5th row서울특별시 양천구 목동 709-2 성원아파트상가 102동 112일부호
ValueCountFrequency (%)
서울특별시 10000
20.8%
양천구 10000
20.8%
신정동 3535
 
7.4%
목동 3303
 
6.9%
신월동 3208
 
6.7%
1층 1420
 
3.0%
지상1층 477
 
1.0%
2층 225
 
0.5%
지하1층 202
 
0.4%
101호 125
 
0.3%
Other values (6487) 15469
32.3%
2024-05-18T07:54:37.969859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46090
17.9%
1 14879
 
5.8%
동 10892
 
4.2%
양 10112
 
3.9%
서 10094
 
3.9%
시 10052
 
3.9%
천 10046
 
3.9%
구 10027
 
3.9%
울 10004
 
3.9%
별 10001
 
3.9%
Other values (381) 115124
44.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 143801
55.9%
Decimal Number 55729
 
21.7%
Space Separator 46090
 
17.9%
Dash Punctuation 9554
 
3.7%
Close Punctuation 715
 
0.3%
Open Punctuation 714
 
0.3%
Other Punctuation 384
 
0.1%
Uppercase Letter 254
 
0.1%
Math Symbol 50
 
< 0.1%
Lowercase Letter 17
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 10892
 
7.6%
양 10112
 
7.0%
서 10094
 
7.0%
시 10052
 
7.0%
천 10046
 
7.0%
구 10027
 
7.0%
울 10004
 
7.0%
별 10001
 
7.0%
특 10000
 
7.0%
지 9026
 
6.3%
Other values (332) 43547
30.3%
Uppercase Letter
ValueCountFrequency (%)
B 112
44.1%
A 82
32.3%
C 17
 
6.7%
M 8
 
3.1%
T 7
 
2.8%
S 5
 
2.0%
P 5
 
2.0%
O 4
 
1.6%
D 3
 
1.2%
R 2
 
0.8%
Other values (7) 9
 
3.5%
Decimal Number
ValueCountFrequency (%)
1 14879
26.7%
2 6941
12.5%
0 5804
 
10.4%
9 5308
 
9.5%
3 4338
 
7.8%
4 3999
 
7.2%
5 3994
 
7.2%
7 3749
 
6.7%
6 3616
 
6.5%
8 3101
 
5.6%
Lowercase Letter
ValueCountFrequency (%)
l 8
47.1%
a 2
 
11.8%
p 2
 
11.8%
y 1
 
5.9%
e 1
 
5.9%
i 1
 
5.9%
v 1
 
5.9%
b 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 351
91.4%
. 26
 
6.8%
/ 5
 
1.3%
: 1
 
0.3%
& 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 714
99.9%
] 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 48
96.0%
| 2
 
4.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 9
69.2%
Ⅱ 4
30.8%
Space Separator
ValueCountFrequency (%)
46090
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9554
100.0%
Open Punctuation
ValueCountFrequency (%)
( 714
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 143800
55.9%
Common 113236
44.0%
Latin 284
 
0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 10892
 
7.6%
양 10112
 
7.0%
서 10094
 
7.0%
시 10052
 
7.0%
천 10046
 
7.0%
구 10027
 
7.0%
울 10004
 
7.0%
별 10001
 
7.0%
특 10000
 
7.0%
지 9026
 
6.3%
Other values (331) 43546
30.3%
Latin
ValueCountFrequency (%)
B 112
39.4%
A 82
28.9%
C 17
 
6.0%
Ⅰ 9
 
3.2%
l 8
 
2.8%
M 8
 
2.8%
T 7
 
2.5%
S 5
 
1.8%
P 5
 
1.8%
O 4
 
1.4%
Other values (17) 27
 
9.5%
Common
ValueCountFrequency (%)
46090
40.7%
1 14879
 
13.1%
- 9554
 
8.4%
2 6941
 
6.1%
0 5804
 
5.1%
9 5308
 
4.7%
3 4338
 
3.8%
4 3999
 
3.5%
5 3994
 
3.5%
7 3749
 
3.3%
Other values (12) 8580
 
7.6%
Han
ValueCountFrequency (%)
內 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 143800
55.9%
ASCII 113507
44.1%
Number Forms 13
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46090
40.6%
1 14879
 
13.1%
- 9554
 
8.4%
2 6941
 
6.1%
0 5804
 
5.1%
9 5308
 
4.7%
3 4338
 
3.8%
4 3999
 
3.5%
5 3994
 
3.5%
7 3749
 
3.3%
Other values (37) 8851
 
7.8%
Hangul
ValueCountFrequency (%)
동 10892
 
7.6%
양 10112
 
7.0%
서 10094
 
7.0%
시 10052
 
7.0%
천 10046
 
7.0%
구 10027
 
7.0%
울 10004
 
7.0%
별 10001
 
7.0%
특 10000
 
7.0%
지 9026
 
6.3%
Other values (331) 43546
30.3%
Number Forms
ValueCountFrequency (%)
Ⅰ 9
69.2%
Ⅱ 4
30.8%
CJK
ValueCountFrequency (%)
內 1
100.0%

도로명주소
Text

MISSING 

Distinct3793
Distinct (%)88.4%
Missing5709
Missing (%)57.1%
Memory size156.2 KiB
2024-05-18T07:54:38.741867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length75
Median length59
Mean length33.175251
Min length21

Characters and Unicode

Total characters142355
Distinct characters358
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

Unique3457 ?
Unique (%)80.6%

Sample

1st row서울특별시 양천구 남부순환로40길 27, 1층 (신월동)
2nd row서울특별시 양천구 중앙로29길 10, 1층 (신정동)
3rd row서울특별시 양천구 신정중앙로23길 10, 지상2층 (신정동, 지상2층)
4th row서울특별시 양천구 목동중앙남로16다길 26, 1층 (목동)
5th row서울특별시 양천구 목동중앙남로 100, 102동 지상1층 상가112(일부)호 (목동)
ValueCountFrequency (%)
서울특별시 4291
 
15.3%
양천구 4291
 
15.3%
1층 1877
 
6.7%
목동 1520
 
5.4%
신정동 1251
 
4.5%
신월동 1091
 
3.9%
지상1층 533
 
1.9%
목동동로 447
 
1.6%
오목로 300
 
1.1%
목동서로 264
 
0.9%
Other values (2235) 12092
43.3%
2024-05-18T07:54:40.044430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23669
 
16.6%
1 7541
 
5.3%
동 7203
 
5.1%
, 4884
 
3.4%
서 4721
 
3.3%
) 4548
 
3.2%
( 4548
 
3.2%
양 4494
 
3.2%
로 4486
 
3.2%
목 4356
 
3.1%
Other values (348) 71905
50.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 81754
57.4%
Space Separator 23669
 
16.6%
Decimal Number 22108
 
15.5%
Other Punctuation 4893
 
3.4%
Close Punctuation 4548
 
3.2%
Open Punctuation 4548
 
3.2%
Dash Punctuation 608
 
0.4%
Uppercase Letter 143
 
0.1%
Math Symbol 57
 
< 0.1%
Lowercase Letter 16
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 7203
 
8.8%
서 4721
 
5.8%
양 4494
 
5.5%
로 4486
 
5.5%
목 4356
 
5.3%
천 4333
 
5.3%
시 4331
 
5.3%
구 4312
 
5.3%
울 4294
 
5.3%
별 4291
 
5.2%
Other values (307) 34933
42.7%
Uppercase Letter
ValueCountFrequency (%)
B 72
50.3%
A 39
27.3%
M 7
 
4.9%
C 6
 
4.2%
O 3
 
2.1%
R 3
 
2.1%
K 3
 
2.1%
S 3
 
2.1%
E 2
 
1.4%
P 2
 
1.4%
Other values (3) 3
 
2.1%
Decimal Number
ValueCountFrequency (%)
1 7541
34.1%
2 3226
14.6%
3 2366
 
10.7%
0 2071
 
9.4%
5 1473
 
6.7%
4 1422
 
6.4%
6 1153
 
5.2%
7 1133
 
5.1%
9 920
 
4.2%
8 803
 
3.6%
Lowercase Letter
ValueCountFrequency (%)
l 8
50.0%
a 2
 
12.5%
p 2
 
12.5%
y 1
 
6.2%
v 1
 
6.2%
i 1
 
6.2%
e 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 4884
99.8%
. 6
 
0.1%
/ 2
 
< 0.1%
& 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅰ 9
81.8%
Ⅱ 2
 
18.2%
Space Separator
ValueCountFrequency (%)
23669
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4548
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4548
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 608
100.0%
Math Symbol
ValueCountFrequency (%)
~ 57
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 81754
57.4%
Common 60431
42.5%
Latin 170
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 7203
 
8.8%
서 4721
 
5.8%
양 4494
 
5.5%
로 4486
 
5.5%
목 4356
 
5.3%
천 4333
 
5.3%
시 4331
 
5.3%
구 4312
 
5.3%
울 4294
 
5.3%
별 4291
 
5.2%
Other values (307) 34933
42.7%
Latin
ValueCountFrequency (%)
B 72
42.4%
A 39
22.9%
Ⅰ 9
 
5.3%
l 8
 
4.7%
M 7
 
4.1%
C 6
 
3.5%
O 3
 
1.8%
R 3
 
1.8%
K 3
 
1.8%
S 3
 
1.8%
Other values (12) 17
 
10.0%
Common
ValueCountFrequency (%)
23669
39.2%
1 7541
 
12.5%
, 4884
 
8.1%
) 4548
 
7.5%
( 4548
 
7.5%
2 3226
 
5.3%
3 2366
 
3.9%
0 2071
 
3.4%
5 1473
 
2.4%
4 1422
 
2.4%
Other values (9) 4683
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 81754
57.4%
ASCII 60590
42.6%
Number Forms 11
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23669
39.1%
1 7541
 
12.4%
, 4884
 
8.1%
) 4548
 
7.5%
( 4548
 
7.5%
2 3226
 
5.3%
3 2366
 
3.9%
0 2071
 
3.4%
5 1473
 
2.4%
4 1422
 
2.3%
Other values (29) 4842
 
8.0%
Hangul
ValueCountFrequency (%)
동 7203
 
8.8%
서 4721
 
5.8%
양 4494
 
5.5%
로 4486
 
5.5%
목 4356
 
5.3%
천 4333
 
5.3%
시 4331
 
5.3%
구 4312
 
5.3%
울 4294
 
5.3%
별 4291
 
5.2%
Other values (307) 34933
42.7%
Number Forms
ValueCountFrequency (%)
Ⅰ 9
81.8%
Ⅱ 2
 
18.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct191
Distinct (%)4.5%
Missing5779
Missing (%)57.8%
Infinite0
Infinite (%)0.0%
Mean7992.1471
Minimum7900
Maximum8111
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T07:54:40.681883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7900
5-th percentile7910
Q17946
median7995
Q38028
95-th percentile8087
Maximum8111
Range211
Interquartile range (IQR)82

Descriptive statistics

Standard deviation54.884233
Coefficient of variation (CV)0.0068672701
Kurtosis-0.87569402
Mean7992.1471
Median Absolute Deviation (MAD)42
Skewness0.27528266
Sum33734853
Variance3012.2791
MonotonicityNot monotonic
2024-05-18T07:54:41.224952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7997 120
 
1.2%
7946 111
 
1.1%
7998 108
 
1.1%
8082 103
 
1.0%
7938 91
 
0.9%
7999 84
 
0.8%
8087 84
 
0.8%
7965 83
 
0.8%
7995 80
 
0.8%
7945 73
 
0.7%
Other values (181) 3284
32.8%
(Missing) 5779
57.8%
ValueCountFrequency (%)
7900 18
0.2%
7902 13
 
0.1%
7903 29
0.3%
7904 29
0.3%
7905 19
0.2%
7906 25
0.2%
7907 22
0.2%
7908 1
 
< 0.1%
7909 29
0.3%
7910 33
0.3%
ValueCountFrequency (%)
8111 1
 
< 0.1%
8110 1
 
< 0.1%
8108 1
 
< 0.1%
8106 14
0.1%
8105 1
 
< 0.1%
8104 26
0.3%
8103 3
 
< 0.1%
8102 2
 
< 0.1%
8101 24
0.2%
8100 6
 
0.1%

사업장명
Text

Distinct8435
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T07:54:42.093571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length28
Mean length5.4191
Min length1

Characters and Unicode

Total characters54191
Distinct characters1083
Distinct categories13 ?
Distinct scripts5 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7549 ?
Unique (%)75.5%

Sample

1st row붐버거
2nd row함향
3rd row두찜 양천 목동역점
4th row꼬끼오랑
5th row옛날통닭
ValueCountFrequency (%)
목동점 140
 
1.3%
전주식당 32
 
0.3%
신월점 30
 
0.3%
오목교점 29
 
0.3%
신정점 28
 
0.3%
양천점 19
 
0.2%
실내포장마차 19
 
0.2%
토크쇼 15
 
0.1%
고향식당 14
 
0.1%
만리장성 14
 
0.1%
Other values (8734) 10612
96.9%
2024-05-18T07:54:43.464213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 1246
 
2.3%
이 1118
 
2.1%
점 1036
 
1.9%
당 956
 
1.8%
954
 
1.8%
동 902
 
1.7%
리 841
 
1.6%
스 824
 
1.5%
치 795
 
1.5%
마 711
 
1.3%
Other values (1073) 44808
82.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50308
92.8%
Space Separator 954
 
1.8%
Lowercase Letter 742
 
1.4%
Uppercase Letter 654
 
1.2%
Decimal Number 582
 
1.1%
Close Punctuation 378
 
0.7%
Open Punctuation 377
 
0.7%
Other Punctuation 179
 
0.3%
Dash Punctuation 6
 
< 0.1%
Math Symbol 6
 
< 0.1%
Other values (3) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 1246
 
2.5%
이 1118
 
2.2%
점 1036
 
2.1%
당 956
 
1.9%
동 902
 
1.8%
리 841
 
1.7%
스 824
 
1.6%
치 795
 
1.6%
마 711
 
1.4%
목 702
 
1.4%
Other values (989) 41177
81.8%
Lowercase Letter
ValueCountFrequency (%)
e 109
14.7%
o 78
 
10.5%
a 67
 
9.0%
i 60
 
8.1%
n 52
 
7.0%
r 45
 
6.1%
s 34
 
4.6%
t 33
 
4.4%
f 30
 
4.0%
l 28
 
3.8%
Other values (16) 206
27.8%
Uppercase Letter
ValueCountFrequency (%)
B 72
 
11.0%
O 50
 
7.6%
C 43
 
6.6%
A 42
 
6.4%
S 41
 
6.3%
E 38
 
5.8%
M 36
 
5.5%
H 33
 
5.0%
F 32
 
4.9%
I 30
 
4.6%
Other values (16) 237
36.2%
Other Punctuation
ValueCountFrequency (%)
. 60
33.5%
& 58
32.4%
, 17
 
9.5%
' 15
 
8.4%
? 12
 
6.7%
! 8
 
4.5%
# 2
 
1.1%
% 2
 
1.1%
; 2
 
1.1%
@ 1
 
0.6%
Other values (2) 2
 
1.1%
Decimal Number
ValueCountFrequency (%)
1 107
18.4%
2 86
14.8%
0 84
14.4%
3 60
10.3%
9 54
9.3%
4 52
8.9%
5 48
8.2%
8 39
 
6.7%
7 30
 
5.2%
6 22
 
3.8%
Math Symbol
ValueCountFrequency (%)
× 3
50.0%
+ 2
33.3%
~ 1
 
16.7%
Space Separator
ValueCountFrequency (%)
954
100.0%
Close Punctuation
ValueCountFrequency (%)
) 378
100.0%
Open Punctuation
ValueCountFrequency (%)
( 377
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50277
92.8%
Common 2485
 
4.6%
Latin 1398
 
2.6%
Han 29
 
0.1%
Hiragana 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 1246
 
2.5%
이 1118
 
2.2%
점 1036
 
2.1%
당 956
 
1.9%
동 902
 
1.8%
리 841
 
1.7%
스 824
 
1.6%
치 795
 
1.6%
마 711
 
1.4%
목 702
 
1.4%
Other values (962) 41146
81.8%
Latin
ValueCountFrequency (%)
e 109
 
7.8%
o 78
 
5.6%
B 72
 
5.2%
a 67
 
4.8%
i 60
 
4.3%
n 52
 
3.7%
O 50
 
3.6%
r 45
 
3.2%
C 43
 
3.1%
A 42
 
3.0%
Other values (43) 780
55.8%
Common
ValueCountFrequency (%)
954
38.4%
) 378
 
15.2%
( 377
 
15.2%
1 107
 
4.3%
2 86
 
3.5%
0 84
 
3.4%
3 60
 
2.4%
. 60
 
2.4%
& 58
 
2.3%
9 54
 
2.2%
Other values (21) 267
 
10.7%
Han
ValueCountFrequency (%)
酒 2
 
6.9%
家 2
 
6.9%
火 2
 
6.9%
松 2
 
6.9%
一 1
 
3.4%
品 1
 
3.4%
木 1
 
3.4%
肉 1
 
3.4%
箕 1
 
3.4%
天 1
 
3.4%
Other values (15) 15
51.7%
Hiragana
ValueCountFrequency (%)
だ 1
50.0%
お 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50276
92.8%
ASCII 3878
 
7.2%
CJK 28
 
0.1%
None 3
 
< 0.1%
Number Forms 2
 
< 0.1%
Hiragana 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 1246
 
2.5%
이 1118
 
2.2%
점 1036
 
2.1%
당 956
 
1.9%
동 902
 
1.8%
리 841
 
1.7%
스 824
 
1.6%
치 795
 
1.6%
마 711
 
1.4%
목 702
 
1.4%
Other values (961) 41145
81.8%
ASCII
ValueCountFrequency (%)
954
24.6%
) 378
 
9.7%
( 377
 
9.7%
e 109
 
2.8%
1 107
 
2.8%
2 86
 
2.2%
0 84
 
2.2%
o 78
 
2.0%
B 72
 
1.9%
a 67
 
1.7%
Other values (72) 1566
40.4%
None
ValueCountFrequency (%)
× 3
100.0%
CJK
ValueCountFrequency (%)
酒 2
 
7.1%
家 2
 
7.1%
火 2
 
7.1%
松 2
 
7.1%
一 1
 
3.6%
品 1
 
3.6%
木 1
 
3.6%
肉 1
 
3.6%
箕 1
 
3.6%
天 1
 
3.6%
Other values (14) 14
50.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%
Compat Jamo
ValueCountFrequency (%)
ㄲ 1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
金 1
100.0%
Hiragana
ValueCountFrequency (%)
だ 1
50.0%
お 1
50.0%

최종수정일자
Date

Distinct6600
Distinct (%)66.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1999-01-19 00:00:00
Maximum2024-05-16 14:58:37
2024-05-18T07:54:43.890861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:54:44.297177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
7576 
U
2424 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowI
2nd rowI
3rd rowU
4th rowU
5th rowU

Common Values

ValueCountFrequency (%)
I 7576
75.8%
U 2424
 
24.2%

Length

2024-05-18T07:54:44.718502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:54:45.120266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 7576
75.8%
u 2424
 
24.2%

데이터갱신일자
Date

Distinct1182
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-18T07:54:45.502882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:54:45.921137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
3856 
분식
1864 
호프/통닭
1229 
기타
905 
경양식
496 
Other values (19)
1650 

Length

Max length15
Median length2
Mean length2.8084
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row패스트푸드
2nd row한식
3rd row기타
4th row통닭(치킨)
5th row분식

Common Values

ValueCountFrequency (%)
한식 3856
38.6%
분식 1864
18.6%
호프/통닭 1229
 
12.3%
기타 905
 
9.0%
경양식 496
 
5.0%
일식 355
 
3.5%
중국식 317
 
3.2%
통닭(치킨) 294
 
2.9%
까페 122
 
1.2%
정종/대포집/소주방 117
 
1.2%
Other values (14) 445
 
4.5%

Length

2024-05-18T07:54:46.354603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 3856
38.6%
분식 1864
18.6%
호프/통닭 1229
 
12.3%
기타 905
 
9.0%
경양식 496
 
5.0%
일식 355
 
3.5%
중국식 317
 
3.2%
통닭(치킨 294
 
2.9%
까페 122
 
1.2%
정종/대포집/소주방 117
 
1.2%
Other values (14) 445
 
4.5%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct3178
Distinct (%)32.8%
Missing310
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean187205.31
Minimum184242.73
Maximum189878.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T07:54:46.712488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184242.73
5-th percentile184877.28
Q1185932.44
median187561.54
Q3188335.5
95-th percentile189021.8
Maximum189878.41
Range5635.6773
Interquartile range (IQR)2403.0579

Descriptive statistics

Standard deviation1389.3805
Coefficient of variation (CV)0.0074216941
Kurtosis-1.1240212
Mean187205.31
Median Absolute Deviation (MAD)1091.9327
Skewness-0.33593432
Sum1.8140194 × 109
Variance1930378.2
MonotonicityNot monotonic
2024-05-18T07:54:47.182003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
188884.075622342 121
 
1.2%
188953.066831076 63
 
0.6%
188895.844080632 52
 
0.5%
188494.598982992 50
 
0.5%
188977.171050288 47
 
0.5%
189042.496526196 40
 
0.4%
189151.208015925 35
 
0.4%
188254.464058537 32
 
0.3%
188584.345447275 32
 
0.3%
188729.190478822 30
 
0.3%
Other values (3168) 9188
91.9%
(Missing) 310
 
3.1%
ValueCountFrequency (%)
184242.730019702 27
0.3%
184298.438528197 1
 
< 0.1%
184328.800385288 1
 
< 0.1%
184398.640381471 2
 
< 0.1%
184400.769531722 1
 
< 0.1%
184413.184233757 2
 
< 0.1%
184425.126732761 2
 
< 0.1%
184428.035362179 1
 
< 0.1%
184429.476451033 1
 
< 0.1%
184443.469766368 2
 
< 0.1%
ValueCountFrequency (%)
189878.40729119 4
 
< 0.1%
189755.541308355 15
0.1%
189749.776358917 21
0.2%
189743.464254868 11
0.1%
189709.803505321 8
 
0.1%
189676.766585898 8
 
0.1%
189643.735000001 4
 
< 0.1%
189576.475334065 1
 
< 0.1%
189519.862506193 1
 
< 0.1%
189512.045139098 4
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct3178
Distinct (%)32.8%
Missing310
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean447314.43
Minimum444842.31
Maximum449843.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T07:54:47.721179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum444842.31
5-th percentile446003.94
Q1446550.11
median447053.63
Q3448057.93
95-th percentile449389.69
Maximum449843.2
Range5000.8973
Interquartile range (IQR)1507.8175

Descriptive statistics

Standard deviation1041.048
Coefficient of variation (CV)0.0023273294
Kurtosis-0.36702199
Mean447314.43
Median Absolute Deviation (MAD)687.724
Skewness0.55993391
Sum4.3344768 × 109
Variance1083781
MonotonicityNot monotonic
2024-05-18T07:54:48.201795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447186.888604306 121
 
1.2%
447333.569187997 63
 
0.6%
447480.979609884 52
 
0.5%
447318.660520705 50
 
0.5%
447466.355031447 47
 
0.5%
447777.835760268 40
 
0.4%
448200.067716589 35
 
0.4%
449635.632611714 32
 
0.3%
447255.070457495 32
 
0.3%
447572.610039376 30
 
0.3%
Other values (3168) 9188
91.9%
(Missing) 310
 
3.1%
ValueCountFrequency (%)
444842.305705773 2
 
< 0.1%
444868.742452 1
 
< 0.1%
444888.208549896 2
 
< 0.1%
444957.421347261 1
 
< 0.1%
444965.527121198 1
 
< 0.1%
445020.49011294 5
0.1%
445039.928375227 2
 
< 0.1%
445044.714764921 1
 
< 0.1%
445070.749071939 1
 
< 0.1%
445073.76201045 2
 
< 0.1%
ValueCountFrequency (%)
449843.203005652 2
 
< 0.1%
449833.140237863 3
< 0.1%
449821.719712552 1
 
< 0.1%
449818.916783 6
0.1%
449818.743412617 2
 
< 0.1%
449806.796167471 1
 
< 0.1%
449804.270313845 3
< 0.1%
449794.496622118 3
< 0.1%
449789.729178343 2
 
< 0.1%
449785.227427003 3
< 0.1%

위생업태명
Categorical

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
3324 
분식
1761 
<NA>
1501 
호프/통닭
1069 
기타
598 
Other values (20)
1747 

Length

Max length15
Median length2
Mean length2.9725
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row패스트푸드
2nd row한식
3rd row기타
4th row통닭(치킨)
5th row분식

Common Values

ValueCountFrequency (%)
한식 3324
33.2%
분식 1761
17.6%
<NA> 1501
15.0%
호프/통닭 1069
 
10.7%
기타 598
 
6.0%
경양식 438
 
4.4%
일식 283
 
2.8%
통닭(치킨) 257
 
2.6%
중국식 256
 
2.6%
패스트푸드 110
 
1.1%
Other values (15) 403
 
4.0%

Length

2024-05-18T07:54:48.674298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 3324
33.2%
분식 1761
17.6%
na 1501
15.0%
호프/통닭 1069
 
10.7%
기타 598
 
6.0%
경양식 438
 
4.4%
일식 283
 
2.8%
통닭(치킨 257
 
2.6%
중국식 256
 
2.6%
패스트푸드 110
 
1.1%
Other values (15) 403
 
4.0%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)0.2%
Missing3826
Missing (%)38.3%
Infinite0
Infinite (%)0.0%
Mean0.35698089
Minimum0
Maximum28
Zeros4525
Zeros (%)45.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T07:54:49.013595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum28
Range28
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.92530126
Coefficient of variation (CV)2.5920191
Kurtosis328.65725
Mean0.35698089
Median Absolute Deviation (MAD)0
Skewness13.37272
Sum2204
Variance0.85618243
MonotonicityNot monotonic
2024-05-18T07:54:49.359127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 4525
45.2%
1 1339
 
13.4%
2 222
 
2.2%
3 50
 
0.5%
4 17
 
0.2%
5 10
 
0.1%
7 2
 
< 0.1%
21 2
 
< 0.1%
6 2
 
< 0.1%
12 1
 
< 0.1%
Other values (4) 4
 
< 0.1%
(Missing) 3826
38.3%
ValueCountFrequency (%)
0 4525
45.2%
1 1339
 
13.4%
2 222
 
2.2%
3 50
 
0.5%
4 17
 
0.2%
5 10
 
0.1%
6 2
 
< 0.1%
7 2
 
< 0.1%
8 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
28 1
 
< 0.1%
27 1
 
< 0.1%
21 2
 
< 0.1%
12 1
 
< 0.1%
10 1
 
< 0.1%
8 1
 
< 0.1%
7 2
 
< 0.1%
6 2
 
< 0.1%
5 10
0.1%
4 17
0.2%

여성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct11
Distinct (%)0.2%
Missing3744
Missing (%)37.4%
Infinite0
Infinite (%)0.0%
Mean0.60853581
Minimum0
Maximum93
Zeros3440
Zeros (%)34.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T07:54:49.698869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum93
Range93
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.4161512
Coefficient of variation (CV)2.3271453
Kurtosis2897.7316
Mean0.60853581
Median Absolute Deviation (MAD)0
Skewness44.786664
Sum3807
Variance2.0054843
MonotonicityNot monotonic
2024-05-18T07:54:49.916147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 3440
34.4%
1 2122
21.2%
2 553
 
5.5%
3 105
 
1.1%
4 22
 
0.2%
5 7
 
0.1%
7 2
 
< 0.1%
8 2
 
< 0.1%
6 1
 
< 0.1%
93 1
 
< 0.1%
(Missing) 3744
37.4%
ValueCountFrequency (%)
0 3440
34.4%
1 2122
21.2%
2 553
 
5.5%
3 105
 
1.1%
4 22
 
0.2%
5 7
 
0.1%
6 1
 
< 0.1%
7 2
 
< 0.1%
8 2
 
< 0.1%
12 1
 
< 0.1%
ValueCountFrequency (%)
93 1
 
< 0.1%
12 1
 
< 0.1%
8 2
 
< 0.1%
7 2
 
< 0.1%
6 1
 
< 0.1%
5 7
 
0.1%
4 22
 
0.2%
3 105
 
1.1%
2 553
 
5.5%
1 2122
21.2%

영업장주변구분명
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5446 
주택가주변
3026 
기타
1263 
아파트지역
 
224
학교정화(상대)
 
26
Other values (3)
 
15

Length

Max length8
Median length4
Mean length4.0886
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> 5446
54.5%
주택가주변 3026
30.3%
기타 1263
 
12.6%
아파트지역 224
 
2.2%
학교정화(상대) 26
 
0.3%
학교정화(절대) 9
 
0.1%
유흥업소밀집지역 4
 
< 0.1%
결혼예식장주변 2
 
< 0.1%

Length

2024-05-18T07:54:50.322335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:54:50.687999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5446
54.5%
주택가주변 3026
30.3%
기타 1263
 
12.6%
아파트지역 224
 
2.2%
학교정화(상대 26
 
0.3%
학교정화(절대 9
 
0.1%
유흥업소밀집지역 4
 
< 0.1%
결혼예식장주변 2
 
< 0.1%

등급구분명
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5605 
기타
3231 
지도
749 
자율
 
234
을
 
144
Other values (3)
 
37

Length

Max length4
Median length4
Mean length3.1043
Min length1

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> 5605
56.0%
기타 3231
32.3%
지도 749
 
7.5%
자율 234
 
2.3%
을 144
 
1.4%
갑 23
 
0.2%
우수 12
 
0.1%
관리 2
 
< 0.1%

Length

2024-05-18T07:54:51.113797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:54:51.467779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5605
56.0%
기타 3231
32.3%
지도 749
 
7.5%
자율 234
 
2.3%
을 144
 
1.4%
갑 23
 
0.2%
우수 12
 
0.1%
관리 2
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
상수도전용
5942 
<NA>
4022 
지하수전용
 
24
상수도(음용)지하수(주방용)겸용
 
11
간이상수도
 
1

Length

Max length17
Median length5
Mean length4.611
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 5942
59.4%
<NA> 4022
40.2%
지하수전용 24
 
0.2%
상수도(음용)지하수(주방용)겸용 11
 
0.1%
간이상수도 1
 
< 0.1%

Length

2024-05-18T07:54:51.882518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:54:52.210728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 5942
59.4%
na 4022
40.2%
지하수전용 24
 
0.2%
상수도(음용)지하수(주방용)겸용 11
 
0.1%
간이상수도 1
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9707 
0
 
293

Length

Max length4
Median length4
Mean length3.9121
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9707
97.1%
0 293
 
2.9%

Length

2024-05-18T07:54:52.619685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:54:52.943810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9707
97.1%
0 293
 
2.9%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9703 
0
 
297

Length

Max length4
Median length4
Mean length3.9109
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9703
97.0%
0 297
 
3.0%

Length

2024-05-18T07:54:53.292465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:54:54.030377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9703
97.0%
0 297
 
3.0%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9703 
0
 
297

Length

Max length4
Median length4
Mean length3.9109
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9703
97.0%
0 297
 
3.0%

Length

2024-05-18T07:54:54.370222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:54:54.723281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9703
97.0%
0 297
 
3.0%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9703 
0
 
297

Length

Max length4
Median length4
Mean length3.9109
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9703
97.0%
0 297
 
3.0%

Length

2024-05-18T07:54:55.135069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:54:55.454636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9703
97.0%
0 297
 
3.0%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9703 
0
 
297

Length

Max length4
Median length4
Mean length3.9109
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9703
97.0%
0 297
 
3.0%

Length

2024-05-18T07:54:55.941946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:54:56.344775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9703
97.0%
0 297
 
3.0%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9703 
0
 
297

Length

Max length4
Median length4
Mean length3.9109
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9703
97.0%
0 297
 
3.0%

Length

2024-05-18T07:54:56.820555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:54:57.251222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9703
97.0%
0 297
 
3.0%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9703 
0
 
297

Length

Max length4
Median length4
Mean length3.9109
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9703
97.0%
0 297
 
3.0%

Length

2024-05-18T07:54:57.704586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:54:58.027278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9703
97.0%
0 297
 
3.0%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1501
Missing (%)15.0%
Memory size97.7 KiB
False
8366 
True
 
133
(Missing)
1501 
ValueCountFrequency (%)
False 8366
83.7%
True 133
 
1.3%
(Missing) 1501
 
15.0%
2024-05-18T07:54:58.295788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING 

Distinct3938
Distinct (%)46.3%
Missing1501
Missing (%)15.0%
Infinite0
Infinite (%)0.0%
Mean60.748372
Minimum0
Maximum4273.96
Zeros36
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T07:54:58.633526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile16.5
Q125.39
median35.75
Q367.645
95-th percentile160.702
Maximum4273.96
Range4273.96
Interquartile range (IQR)42.255

Descriptive statistics

Standard deviation101.30394
Coefficient of variation (CV)1.6675993
Kurtosis459.15123
Mean60.748372
Median Absolute Deviation (MAD)14.25
Skewness15.868006
Sum516300.41
Variance10262.488
MonotonicityNot monotonic
2024-05-18T07:54:59.045009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26.4 293
 
2.9%
23.1 167
 
1.7%
29.7 158
 
1.6%
33.0 124
 
1.2%
30.0 96
 
1.0%
19.8 92
 
0.9%
66.0 91
 
0.9%
39.6 76
 
0.8%
16.5 61
 
0.6%
49.5 53
 
0.5%
Other values (3928) 7288
72.9%
(Missing) 1501
 
15.0%
ValueCountFrequency (%)
0.0 36
0.4%
2.64 2
 
< 0.1%
3.3 1
 
< 0.1%
3.6 1
 
< 0.1%
3.86 1
 
< 0.1%
4.93 1
 
< 0.1%
6.16 1
 
< 0.1%
6.22 1
 
< 0.1%
6.26 1
 
< 0.1%
6.6 6
 
0.1%
ValueCountFrequency (%)
4273.96 1
< 0.1%
2338.96 1
< 0.1%
2064.61 1
< 0.1%
1798.47 1
< 0.1%
1785.43 1
< 0.1%
1584.0 1
< 0.1%
1567.5 1
< 0.1%
1353.5 1
< 0.1%
1340.31 1
< 0.1%
1322.7 1
< 0.1%

전통업소지정번호
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing9997
Missing (%)> 99.9%
Memory size156.2 KiB
2024-05-18T07:54:59.531975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length2
Mean length3.6666667
Min length1

Characters and Unicode

Total characters11
Distinct characters6
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rowㅁㅁ
2nd row2009-001
3rd row0
ValueCountFrequency (%)
ㅁㅁ 1
33.3%
2009-001 1
33.3%
0 1
33.3%
2024-05-18T07:55:00.344137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5
45.5%
ㅁ 2
 
18.2%
2 1
 
9.1%
9 1
 
9.1%
- 1
 
9.1%
1 1
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8
72.7%
Other Letter 2
 
18.2%
Dash Punctuation 1
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5
62.5%
2 1
 
12.5%
9 1
 
12.5%
1 1
 
12.5%
Other Letter
ValueCountFrequency (%)
ㅁ 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9
81.8%
Hangul 2
 
18.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5
55.6%
2 1
 
11.1%
9 1
 
11.1%
- 1
 
11.1%
1 1
 
11.1%
Hangul
ValueCountFrequency (%)
ㅁ 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9
81.8%
Compat Jamo 2
 
18.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5
55.6%
2 1
 
11.1%
9 1
 
11.1%
- 1
 
11.1%
1 1
 
11.1%
Compat Jamo
ValueCountFrequency (%)
ㅁ 2
100.0%

전통업소주된음식
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9999 
1
 
1

Length

Max length4
Median length4
Mean length3.9997
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9999
> 99.9%
1 1
 
< 0.1%

Length

2024-05-18T07:55:00.800019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:55:01.126037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9999
> 99.9%
1 1
 
< 0.1%

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
1314231400003140000-101-2013-0023320130906<NA>3폐업2폐업20161212<NA><NA><NA>NaN21.48158829서울특별시 양천구 신월동 160-9번지 1층서울특별시 양천구 남부순환로40길 27, 1층 (신월동)7912붐버거2015-12-11 11:15:41I2018-08-31 23:59:59.0패스트푸드184694.128185448025.559067패스트푸드<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N21.48<NA><NA><NA>
1352131400003140000-101-2014-0025220140911<NA>3폐업2폐업20150827<NA><NA><NA>NaN46.20158864서울특별시 양천구 신정동 1179-15번지 1층서울특별시 양천구 중앙로29길 10, 1층 (신정동)<NA>함향2014-09-11 14:25:55I2018-08-31 23:59:59.0한식186918.034868446125.370032한식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N46.2<NA><NA><NA>
1403331400003140000-101-2016-0003520160215<NA>1영업/정상1영업<NA><NA><NA><NA>NaN57.08158857서울특별시 양천구 신정동 900-6 지상2층서울특별시 양천구 신정중앙로23길 10, 지상2층 (신정동, 지상2층)7938두찜 양천 목동역점2021-06-28 11:19:03U2021-06-30 02:40:00.0기타187871.040283447227.145318기타<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N57.08<NA><NA><NA>
1357131400003140000-101-2014-0030220141027<NA>3폐업2폐업20210727<NA><NA><NA>NaN30.00158805서울특별시 양천구 목동 324-150 1층서울특별시 양천구 목동중앙남로16다길 26, 1층 (목동)7951꼬끼오랑2021-07-31 12:30:10U2021-08-02 02:40:00.0통닭(치킨)187947.077966449058.1376통닭(치킨)00<NA><NA><NA>00000<NA>00N30.0<NA><NA><NA>
1435431400003140000-101-2017-0002420170213<NA>1영업/정상1영업<NA><NA><NA><NA>022642828129.70158791서울특별시 양천구 목동 709-2 성원아파트상가 102동 112일부호서울특별시 양천구 목동중앙남로 100, 102동 지상1층 상가112(일부)호 (목동)7956옛날통닭2021-09-01 09:10:16U2021-09-03 02:40:00.0분식187864.502277448953.063207분식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N29.7<NA><NA><NA>
597831400003140000-101-1999-0680319990205<NA>3폐업2폐업20000812<NA><NA><NA>02 696208822.70158838서울특별시 양천구 신월동 509-1번지<NA><NA>라미락2000-08-12 00:00:00I2018-08-31 23:59:59.0분식186202.649871446699.633449분식11주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N22.7<NA><NA><NA>
1247931400003140000-101-2011-0026120110915<NA>1영업/정상1영업<NA><NA><NA><NA>NaN69.03158825서울특별시 양천구 신월동 80-1번지 1층서울특별시 양천구 화곡로4길 31 (신월동,1층)7905대박연탄구이2011-09-15 15:34:12I2018-08-31 23:59:59.0식육(숯불구이)184796.924298448305.972006식육(숯불구이)<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N69.03<NA><NA><NA>
1540331400003140000-101-2020-0006220200317<NA>1영업/정상1영업<NA><NA><NA><NA>NaN110.58158852서울특별시 양천구 신정동 294-39번지 피앤제이테크빌딩 1층서울특별시 양천구 목동동로8길 11, 피앤제이테크빌딩 1층 (신정동)8014춘천중앙로숯불닭갈비2020-03-17 09:31:59I2020-03-19 00:23:30.0기타188515.269316446180.315568기타<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N110.58<NA><NA><NA>
464531400003140000-101-1996-0503319961223<NA>3폐업2폐업20000805<NA><NA><NA>0228.47158812서울특별시 양천구 목동 651-1번지<NA><NA>토마토2000-08-11 00:00:00I2018-08-31 23:59:59.0분식187812.328566449324.455505분식01기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N28.47<NA><NA><NA>
220931400003140000-101-1993-0005919930906<NA>3폐업2폐업20070118<NA><NA><NA>022655070581.48158819서울특별시 양천구 목동 794-18번지<NA><NA>소리도2005-03-09 00:00:00I2018-08-31 23:59:59.0한식187961.79151447763.7012한식11주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N81.48<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
1257631400003140000-101-2011-0035820111124<NA>3폐업2폐업20210727<NA><NA><NA>NaN74.61158861서울특별시 양천구 신정동 1015-2 1층서울특별시 양천구 은행정로4길 14, 1층 (신정동)8087만리장성2021-07-31 09:31:18U2021-08-02 02:40:00.0한식187685.918214446541.406692한식00<NA><NA>상수도전용00000<NA>00N74.61<NA><NA><NA>
626931400003140000-101-1999-0719619991005<NA>1영업/정상1영업<NA><NA><NA><NA>022643998268.24158070서울특별시 양천구 신정동 1296 신정동 아이파크 상가동 106호서울특별시 양천구 목동동로 180 (신정동, 신정동 아이파크 상가동 106호)8010교촌치킨오목교점2021-11-08 16:55:34U2021-11-10 02:40:00.0통닭(치킨)188629.222126446609.345448통닭(치킨)02주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N68.24<NA><NA><NA>
1166931400003140000-101-2009-0815420090803<NA>3폐업2폐업20110215<NA><NA><NA>022651211139.60158849서울특별시 양천구 신정동 127-3번지 1층(오목내길 64-6)<NA><NA>이삭식당2009-08-03 16:34:42I2018-08-31 23:59:59.0한식188970.72549446457.499206한식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N39.6<NA><NA><NA>
1491731400003140000-101-2018-0027420181023<NA>1영업/정상1영업<NA><NA><NA><NA>NaN42.90158803서울특별시 양천구 목동 315-42서울특별시 양천구 목동중앙본로 57, 1층 (목동)7954새우중독2020-07-14 10:31:06U2020-07-16 02:40:00.0한식188334.439886448773.305792한식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N42.9<NA><NA><NA>
342631400003140000-101-1995-0138219950404<NA>3폐업2폐업20220831<NA><NA><NA>022065944348.81158844서울특별시 양천구 신월동 913-1서울특별시 양천구 지양로 96, 1층 (신월동)8033신월생고기2022-08-31 09:47:58U2021-12-09 00:02:00.0한식185077.934512446815.49327<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1277631400003140000-101-2012-0019720120727<NA>3폐업2폐업20121210<NA><NA><NA>02 2616298896.33158855서울특별시 양천구 신정동 836-20번지 2층서울특별시 양천구 신정로5길 19 (신정동, 2층)8056베네치아2012-12-10 17:22:42I2018-08-31 23:59:59.0경양식185316.870386445020.490113경양식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N96.33<NA><NA><NA>
1417931400003140000-101-2016-0018120160715<NA>1영업/정상1영업<NA><NA><NA><NA>NaN92.26158808서울특별시 양천구 목동 513-10번지 지상2층서울특별시 양천구 공항대로 616, 지상2층 (목동)7968콩부자염창역점2019-01-30 15:38:06U2019-02-01 02:40:00.0한식188729.508803449390.114312한식<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N92.26<NA><NA><NA>
384331400003140000-101-1995-0453019950712<NA>3폐업2폐업19980325<NA><NA><NA>02 603969630.83158858서울특별시 양천구 신정동 922-34번지<NA><NA>그린치킨호프2001-09-28 00:00:00I2018-08-31 23:59:59.0분식187050.851648446977.248575분식01주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N30.83<NA><NA><NA>
406331400003140000-101-1996-0159619960507<NA>3폐업2폐업20050628<NA><NA><NA>02 642155099.00158807서울특별시 양천구 목동 507-2번지<NA><NA>선비마을2003-11-21 00:00:00I2018-08-31 23:59:59.0한식188563.746658449409.143622한식01주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N99.0<NA><NA><NA>
1259731400003140000-101-2012-000162012-02-08<NA>3폐업2폐업2024-05-16<NA><NA><NA>NaN82.08158-839서울특별시 양천구 신월동 514-3 해태아파트서울특별시 양천구 월정로 21, 상가동 1층 110호 (신월동, 해태아파트)8029활어회전문점2024-05-16 11:39:51U2023-12-04 23:08:00.0일식186056.530964446627.179128<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>