Overview

Dataset statistics

Number of variables44
Number of observations10000
Missing cells99248
Missing cells (%)22.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 MiB
Average record size in memory384.0 B

Variable types

Categorical19
Text7
DateTime4
Unsupported7
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
Author관악구
URLhttps://data.seoul.go.kr/dataList/OA-18672/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
총인원 is highly imbalanced (83.5%)Imbalance
본사종업원수 is highly imbalanced (83.5%)Imbalance
공장사무직종업원수 is highly imbalanced (83.5%)Imbalance
공장판매직종업원수 is highly imbalanced (83.5%)Imbalance
공장생산직종업원수 is highly imbalanced (83.5%)Imbalance
보증액 is highly imbalanced (83.5%)Imbalance
월세액 is highly imbalanced (83.5%)Imbalance
다중이용업소여부 is highly imbalanced (87.7%)Imbalance
전통업소지정번호 is highly imbalanced (99.9%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 2224 (22.2%) 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 3955 (39.6%) missing valuesMissing
도로명주소 has 5156 (51.6%) missing valuesMissing
도로명우편번호 has 5207 (52.1%) missing valuesMissing
좌표정보(X) has 244 (2.4%) missing valuesMissing
좌표정보(Y) has 244 (2.4%) missing valuesMissing
남성종사자수 has 4413 (44.1%) missing valuesMissing
여성종사자수 has 4401 (44.0%) missing valuesMissing
건물소유구분명 has 10000 (100.0%) missing valuesMissing
다중이용업소여부 has 1654 (16.5%) missing valuesMissing
시설총규모 has 1654 (16.5%) missing valuesMissing
전통업소주된음식 has 10000 (100.0%) missing valuesMissing
홈페이지 has 10000 (100.0%) missing valuesMissing
남성종사자수 is highly skewed (γ1 = 28.48329921)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
건물소유구분명 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
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
남성종사자수 has 4452 (44.5%) zerosZeros
여성종사자수 has 3939 (39.4%) zerosZeros
시설총규모 has 146 (1.5%) zerosZeros

Reproduction

Analysis started2024-05-11 04:32:07.247867
Analysis finished2024-05-11 04:32:12.347717
Duration5.1 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
3200000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3200000
2nd row3200000
3rd row3200000
4th row3200000
5th row3200000

Common Values

ValueCountFrequency (%)
3200000 10000
100.0%

Length

2024-05-11T04:32:12.692098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:13.121066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3200000 10000
100.0%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T04:32:13.732291image/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 row3200000-101-2006-00190
2nd row3200000-101-1997-01608
3rd row3200000-101-2002-00185
4th row3200000-101-2005-00295
5th row3200000-101-2020-00207
ValueCountFrequency (%)
3200000-101-2006-00190 1
 
< 0.1%
3200000-101-1992-04446 1
 
< 0.1%
3200000-101-2005-00221 1
 
< 0.1%
3200000-101-2008-00054 1
 
< 0.1%
3200000-101-1996-02136 1
 
< 0.1%
3200000-101-2001-11040 1
 
< 0.1%
3200000-101-1986-07213 1
 
< 0.1%
3200000-101-2004-00117 1
 
< 0.1%
3200000-101-1996-01902 1
 
< 0.1%
3200000-101-2001-11174 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-05-11T04:32:15.167631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 89852
40.8%
1 32017
 
14.6%
- 30000
 
13.6%
2 22885
 
10.4%
3 15205
 
6.9%
9 9492
 
4.3%
4 4818
 
2.2%
5 4172
 
1.9%
8 4064
 
1.8%
6 3938
 
1.8%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 89852
47.3%
1 32017
 
16.9%
2 22885
 
12.0%
3 15205
 
8.0%
9 9492
 
5.0%
4 4818
 
2.5%
5 4172
 
2.2%
8 4064
 
2.1%
6 3938
 
2.1%
7 3557
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 89852
40.8%
1 32017
 
14.6%
- 30000
 
13.6%
2 22885
 
10.4%
3 15205
 
6.9%
9 9492
 
4.3%
4 4818
 
2.2%
5 4172
 
1.9%
8 4064
 
1.8%
6 3938
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 89852
40.8%
1 32017
 
14.6%
- 30000
 
13.6%
2 22885
 
10.4%
3 15205
 
6.9%
9 9492
 
4.3%
4 4818
 
2.2%
5 4172
 
1.9%
8 4064
 
1.8%
6 3938
 
1.8%
Distinct6237
Distinct (%)62.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1969-06-17 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T04:32:15.652303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:32:16.226165image/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
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
7776 
1
2224 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 7776
77.8%
1 2224
 
22.2%

Length

2024-05-11T04:32:16.744832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:17.140703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 7776
77.8%
1 2224
 
22.2%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7776 
영업/정상
2224 

Length

Max length5
Median length2
Mean length2.6672
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7776
77.8%
영업/정상 2224
 
22.2%

Length

2024-05-11T04:32:17.610298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:17.977814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7776
77.8%
영업/정상 2224
 
22.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
7776 
1
2224 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 7776
77.8%
1 2224
 
22.2%

Length

2024-05-11T04:32:18.446061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:18.863382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 7776
77.8%
1 2224
 
22.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7776 
영업
2224 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7776
77.8%
영업 2224
 
22.2%

Length

2024-05-11T04:32:19.345955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:19.689700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7776
77.8%
영업 2224
 
22.2%

폐업일자
Date

MISSING 

Distinct4594
Distinct (%)59.1%
Missing2224
Missing (%)22.2%
Memory size156.2 KiB
Minimum1985-01-26 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T04:32:20.128284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:32:20.777731image/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
Text

MISSING 

Distinct4813
Distinct (%)79.6%
Missing3955
Missing (%)39.6%
Memory size156.2 KiB
2024-05-11T04:32:21.286994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.3215881
Min length2

Characters and Unicode

Total characters56349
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

Unique4693 ?
Unique (%)77.6%

Sample

1st row02 8780203
2nd row02 8681666
3rd row02 8836388
4th row02 8883336
5th row02 8307413
ValueCountFrequency (%)
02 4971
44.7%
0200000000 260
 
2.3%
00000 126
 
1.1%
877 62
 
0.6%
882 46
 
0.4%
875 38
 
0.3%
070 36
 
0.3%
871 35
 
0.3%
883 34
 
0.3%
888 32
 
0.3%
Other values (4857) 5470
49.2%
2024-05-11T04:32:22.458828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11693
20.8%
8 9183
16.3%
2 8780
15.6%
6002
10.7%
7 4261
 
7.6%
5 3413
 
6.1%
6 2856
 
5.1%
3 2847
 
5.1%
9 2471
 
4.4%
4 2469
 
4.4%
Other values (2) 2374
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50346
89.3%
Space Separator 6002
 
10.7%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11693
23.2%
8 9183
18.2%
2 8780
17.4%
7 4261
 
8.5%
5 3413
 
6.8%
6 2856
 
5.7%
3 2847
 
5.7%
9 2471
 
4.9%
4 2469
 
4.9%
1 2373
 
4.7%
Space Separator
ValueCountFrequency (%)
6002
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 56349
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11693
20.8%
8 9183
16.3%
2 8780
15.6%
6002
10.7%
7 4261
 
7.6%
5 3413
 
6.1%
6 2856
 
5.1%
3 2847
 
5.1%
9 2471
 
4.4%
4 2469
 
4.4%
Other values (2) 2374
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56349
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11693
20.8%
8 9183
16.3%
2 8780
15.6%
6002
10.7%
7 4261
 
7.6%
5 3413
 
6.1%
6 2856
 
5.1%
3 2847
 
5.1%
9 2471
 
4.4%
4 2469
 
4.4%
Other values (2) 2374
 
4.2%
Distinct4551
Distinct (%)45.9%
Missing90
Missing (%)0.9%
Memory size156.2 KiB
2024-05-11T04:32:23.508512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.093441
Min length3

Characters and Unicode

Total characters50476
Distinct characters12
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

Unique2985 ?
Unique (%)30.1%

Sample

1st row87.27
2nd row95.02
3rd row28.69
4th row21.96
5th row61.86
ValueCountFrequency (%)
33.00 193
 
1.9%
30.00 135
 
1.4%
26.40 109
 
1.1%
20.00 66
 
0.7%
00 65
 
0.7%
23.10 64
 
0.6%
24.00 62
 
0.6%
49.50 61
 
0.6%
66.00 58
 
0.6%
16.50 55
 
0.6%
Other values (4541) 9042
91.2%
2024-05-11T04:32:25.507914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9910
19.6%
0 8137
16.1%
2 5295
10.5%
1 4719
9.3%
3 3920
 
7.8%
4 3543
 
7.0%
5 3417
 
6.8%
6 3340
 
6.6%
8 2983
 
5.9%
9 2659
 
5.3%
Other values (2) 2553
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40560
80.4%
Other Punctuation 9916
 
19.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8137
20.1%
2 5295
13.1%
1 4719
11.6%
3 3920
9.7%
4 3543
8.7%
5 3417
8.4%
6 3340
8.2%
8 2983
 
7.4%
9 2659
 
6.6%
7 2547
 
6.3%
Other Punctuation
ValueCountFrequency (%)
. 9910
99.9%
, 6
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 50476
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9910
19.6%
0 8137
16.1%
2 5295
10.5%
1 4719
9.3%
3 3920
 
7.8%
4 3543
 
7.0%
5 3417
 
6.8%
6 3340
 
6.6%
8 2983
 
5.9%
9 2659
 
5.3%
Other values (2) 2553
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50476
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9910
19.6%
0 8137
16.1%
2 5295
10.5%
1 4719
9.3%
3 3920
 
7.8%
4 3543
 
7.0%
5 3417
 
6.8%
6 3340
 
6.6%
8 2983
 
5.9%
9 2659
 
5.3%
Other values (2) 2553
 
5.1%
Distinct226
Distinct (%)2.3%
Missing3
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-11T04:32:26.475569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1124337
Min length6

Characters and Unicode

Total characters61106
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

Unique18 ?
Unique (%)0.2%

Sample

1st row151811
2nd row151876
3rd row151842
4th row151848
5th row151875
ValueCountFrequency (%)
151930 454
 
4.5%
151895 301
 
3.0%
151890 296
 
3.0%
151830 271
 
2.7%
151892 268
 
2.7%
151843 244
 
2.4%
151832 231
 
2.3%
151800 225
 
2.3%
151876 217
 
2.2%
151848 216
 
2.2%
Other values (216) 7274
72.8%
2024-05-11T04:32:28.324079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 21649
35.4%
5 11914
19.5%
8 9679
15.8%
9 3686
 
6.0%
0 3666
 
6.0%
3 2821
 
4.6%
4 2183
 
3.6%
2 1686
 
2.8%
7 1533
 
2.5%
6 1165
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59982
98.2%
Dash Punctuation 1124
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 21649
36.1%
5 11914
19.9%
8 9679
16.1%
9 3686
 
6.1%
0 3666
 
6.1%
3 2821
 
4.7%
4 2183
 
3.6%
2 1686
 
2.8%
7 1533
 
2.6%
6 1165
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 1124
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61106
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 21649
35.4%
5 11914
19.5%
8 9679
15.8%
9 3686
 
6.0%
0 3666
 
6.0%
3 2821
 
4.6%
4 2183
 
3.6%
2 1686
 
2.8%
7 1533
 
2.5%
6 1165
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61106
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 21649
35.4%
5 11914
19.5%
8 9679
15.8%
9 3686
 
6.0%
0 3666
 
6.0%
3 2821
 
4.6%
4 2183
 
3.6%
2 1686
 
2.8%
7 1533
 
2.5%
6 1165
 
1.9%
Distinct6786
Distinct (%)67.9%
Missing3
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-11T04:32:29.279097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length50
Mean length23.952186
Min length17

Characters and Unicode

Total characters239450
Distinct characters297
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4978 ?
Unique (%)49.8%

Sample

1st row서울특별시 관악구 봉천동 859-31번지 2층
2nd row서울특별시 관악구 신림동 543-6번지
3rd row서울특별시 관악구 봉천동 922-1번지
4th row서울특별시 관악구 봉천동 1611-1번지 지상1층
5th row서울특별시 관악구 신림동 527-4번지
ValueCountFrequency (%)
서울특별시 9997
23.3%
관악구 9997
23.3%
신림동 5445
12.7%
봉천동 4222
 
9.8%
지상1층 1118
 
2.6%
남현동 329
 
0.8%
지하1층 179
 
0.4%
지상2층 166
 
0.4%
1층 60
 
0.1%
729-32번지 48
 
0.1%
Other values (5866) 11400
26.5%
2024-05-11T04:32:30.740024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
41236
 
17.2%
1 13199
 
5.5%
10127
 
4.2%
10065
 
4.2%
10063
 
4.2%
10021
 
4.2%
10016
 
4.2%
10007
 
4.2%
10006
 
4.2%
9997
 
4.2%
Other values (287) 104713
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 134170
56.0%
Decimal Number 53585
 
22.4%
Space Separator 41236
 
17.2%
Dash Punctuation 9927
 
4.1%
Other Punctuation 215
 
0.1%
Open Punctuation 107
 
< 0.1%
Close Punctuation 107
 
< 0.1%
Uppercase Letter 88
 
< 0.1%
Math Symbol 9
 
< 0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10127
 
7.5%
10065
 
7.5%
10063
 
7.5%
10021
 
7.5%
10016
 
7.5%
10007
 
7.5%
10006
 
7.5%
9997
 
7.5%
9997
 
7.5%
9295
 
6.9%
Other values (251) 34576
25.8%
Uppercase Letter
ValueCountFrequency (%)
B 28
31.8%
A 20
22.7%
S 10
 
11.4%
K 7
 
8.0%
T 4
 
4.5%
L 3
 
3.4%
E 3
 
3.4%
I 2
 
2.3%
G 2
 
2.3%
H 2
 
2.3%
Other values (5) 7
 
8.0%
Decimal Number
ValueCountFrequency (%)
1 13199
24.6%
2 6136
11.5%
6 6061
11.3%
5 5073
 
9.5%
4 4947
 
9.2%
3 4850
 
9.1%
0 3347
 
6.2%
8 3338
 
6.2%
9 3332
 
6.2%
7 3302
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 189
87.9%
. 13
 
6.0%
@ 13
 
6.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
50.0%
s 2
33.3%
c 1
 
16.7%
Space Separator
ValueCountFrequency (%)
41236
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9927
100.0%
Open Punctuation
ValueCountFrequency (%)
( 107
100.0%
Close Punctuation
ValueCountFrequency (%)
) 107
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 134170
56.0%
Common 105186
43.9%
Latin 94
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10127
 
7.5%
10065
 
7.5%
10063
 
7.5%
10021
 
7.5%
10016
 
7.5%
10007
 
7.5%
10006
 
7.5%
9997
 
7.5%
9997
 
7.5%
9295
 
6.9%
Other values (251) 34576
25.8%
Common
ValueCountFrequency (%)
41236
39.2%
1 13199
 
12.5%
- 9927
 
9.4%
2 6136
 
5.8%
6 6061
 
5.8%
5 5073
 
4.8%
4 4947
 
4.7%
3 4850
 
4.6%
0 3347
 
3.2%
8 3338
 
3.2%
Other values (8) 7072
 
6.7%
Latin
ValueCountFrequency (%)
B 28
29.8%
A 20
21.3%
S 10
 
10.6%
K 7
 
7.4%
T 4
 
4.3%
L 3
 
3.2%
E 3
 
3.2%
e 3
 
3.2%
I 2
 
2.1%
G 2
 
2.1%
Other values (8) 12
12.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 134168
56.0%
ASCII 105280
44.0%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
41236
39.2%
1 13199
 
12.5%
- 9927
 
9.4%
2 6136
 
5.8%
6 6061
 
5.8%
5 5073
 
4.8%
4 4947
 
4.7%
3 4850
 
4.6%
0 3347
 
3.2%
8 3338
 
3.2%
Other values (26) 7166
 
6.8%
Hangul
ValueCountFrequency (%)
10127
 
7.5%
10065
 
7.5%
10063
 
7.5%
10021
 
7.5%
10016
 
7.5%
10007
 
7.5%
10006
 
7.5%
9997
 
7.5%
9997
 
7.5%
9295
 
6.9%
Other values (249) 34574
25.8%
Compat Jamo
ValueCountFrequency (%)
1
50.0%
1
50.0%

도로명주소
Text

MISSING 

Distinct4136
Distinct (%)85.4%
Missing5156
Missing (%)51.6%
Memory size156.2 KiB
2024-05-11T04:32:31.806416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length56
Mean length30.179397
Min length21

Characters and Unicode

Total characters146189
Distinct characters321
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3596 ?
Unique (%)74.2%

Sample

1st row서울특별시 관악구 관악로16길 42 (봉천동,지상1층)
2nd row서울특별시 관악구 난곡로66길 8, 1층 (신림동)
3rd row서울특별시 관악구 봉천로 237-6, 지하1층 (봉천동)
4th row서울특별시 관악구 남부순환로 1904, 지1층 11호 (봉천동)
5th row서울특별시 관악구 관악로 268, 2층 (봉천동)
ValueCountFrequency (%)
서울특별시 4844
16.3%
관악구 4843
16.3%
1층 2436
 
8.2%
신림동 2341
 
7.9%
봉천동 1982
 
6.7%
남부순환로 451
 
1.5%
지하1층 447
 
1.5%
2층 407
 
1.4%
봉천로 307
 
1.0%
신림로 272
 
0.9%
Other values (2009) 11473
38.5%
2024-05-11T04:32:33.800666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24963
 
17.1%
1 8119
 
5.6%
5416
 
3.7%
5318
 
3.6%
5116
 
3.5%
) 4927
 
3.4%
( 4927
 
3.4%
4908
 
3.4%
4886
 
3.3%
4864
 
3.3%
Other values (311) 72745
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 83090
56.8%
Space Separator 24963
 
17.1%
Decimal Number 22850
 
15.6%
Close Punctuation 4928
 
3.4%
Open Punctuation 4928
 
3.4%
Other Punctuation 4698
 
3.2%
Dash Punctuation 594
 
0.4%
Uppercase Letter 110
 
0.1%
Math Symbol 22
 
< 0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5416
 
6.5%
5318
 
6.4%
5116
 
6.2%
4908
 
5.9%
4886
 
5.9%
4864
 
5.9%
4863
 
5.9%
4844
 
5.8%
4844
 
5.8%
4265
 
5.1%
Other values (275) 33766
40.6%
Uppercase Letter
ValueCountFrequency (%)
B 62
56.4%
A 23
 
20.9%
S 4
 
3.6%
C 3
 
2.7%
T 3
 
2.7%
E 3
 
2.7%
H 2
 
1.8%
I 2
 
1.8%
G 2
 
1.8%
R 2
 
1.8%
Other values (4) 4
 
3.6%
Decimal Number
ValueCountFrequency (%)
1 8119
35.5%
2 3376
14.8%
3 2017
 
8.8%
0 1616
 
7.1%
4 1564
 
6.8%
6 1545
 
6.8%
5 1445
 
6.3%
7 1150
 
5.0%
8 1021
 
4.5%
9 997
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 4690
99.8%
. 7
 
0.1%
@ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 4927
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 4927
> 99.9%
[ 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
b 3
50.0%
e 3
50.0%
Space Separator
ValueCountFrequency (%)
24963
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 594
100.0%
Math Symbol
ValueCountFrequency (%)
~ 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 83090
56.8%
Common 62983
43.1%
Latin 116
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5416
 
6.5%
5318
 
6.4%
5116
 
6.2%
4908
 
5.9%
4886
 
5.9%
4864
 
5.9%
4863
 
5.9%
4844
 
5.8%
4844
 
5.8%
4265
 
5.1%
Other values (275) 33766
40.6%
Common
ValueCountFrequency (%)
24963
39.6%
1 8119
 
12.9%
) 4927
 
7.8%
( 4927
 
7.8%
, 4690
 
7.4%
2 3376
 
5.4%
3 2017
 
3.2%
0 1616
 
2.6%
4 1564
 
2.5%
6 1545
 
2.5%
Other values (10) 5239
 
8.3%
Latin
ValueCountFrequency (%)
B 62
53.4%
A 23
 
19.8%
S 4
 
3.4%
b 3
 
2.6%
e 3
 
2.6%
C 3
 
2.6%
T 3
 
2.6%
E 3
 
2.6%
H 2
 
1.7%
I 2
 
1.7%
Other values (6) 8
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 83090
56.8%
ASCII 63099
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24963
39.6%
1 8119
 
12.9%
) 4927
 
7.8%
( 4927
 
7.8%
, 4690
 
7.4%
2 3376
 
5.4%
3 2017
 
3.2%
0 1616
 
2.6%
4 1564
 
2.5%
6 1545
 
2.4%
Other values (26) 5355
 
8.5%
Hangul
ValueCountFrequency (%)
5416
 
6.5%
5318
 
6.4%
5116
 
6.2%
4908
 
5.9%
4886
 
5.9%
4864
 
5.9%
4863
 
5.9%
4844
 
5.8%
4844
 
5.8%
4265
 
5.1%
Other values (275) 33766
40.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct154
Distinct (%)3.2%
Missing5207
Missing (%)52.1%
Infinite0
Infinite (%)0.0%
Mean8776.3939
Minimum6995
Maximum8866
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T04:32:34.421936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6995
5-th percentile8708
Q18751
median8776
Q38804
95-th percentile8850
Maximum8866
Range1871
Interquartile range (IQR)53

Descriptive statistics

Standard deviation47.276992
Coefficient of variation (CV)0.0053868357
Kurtosis419.44166
Mean8776.3939
Median Absolute Deviation (MAD)26
Skewness-11.056622
Sum42065256
Variance2235.114
MonotonicityNot monotonic
2024-05-11T04:32:34.887362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8776 222
 
2.2%
8788 144
 
1.4%
8789 136
 
1.4%
8793 123
 
1.2%
8813 120
 
1.2%
8785 116
 
1.2%
8774 109
 
1.1%
8814 107
 
1.1%
8754 95
 
0.9%
8708 92
 
0.9%
Other values (144) 3529
35.3%
(Missing) 5207
52.1%
ValueCountFrequency (%)
6995 1
 
< 0.1%
8700 10
 
0.1%
8701 35
 
0.4%
8702 46
0.5%
8703 3
 
< 0.1%
8704 12
 
0.1%
8705 33
 
0.3%
8706 30
 
0.3%
8707 57
0.6%
8708 92
0.9%
ValueCountFrequency (%)
8866 1
 
< 0.1%
8865 19
0.2%
8864 31
0.3%
8863 4
 
< 0.1%
8861 6
 
0.1%
8860 13
0.1%
8859 22
0.2%
8858 30
0.3%
8857 17
0.2%
8856 24
0.2%
Distinct8782
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T04:32:35.997855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length31
Mean length5.5131
Min length1

Characters and Unicode

Total characters55131
Distinct characters1133
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

Unique8009 ?
Unique (%)80.1%

Sample

1st row양평해장국
2nd row해오름
3rd row정동진식당
4th row풍경
5th row역전할머니맥주 난곡사거리점
ValueCountFrequency (%)
신림점 156
 
1.3%
봉천점 74
 
0.6%
관악점 60
 
0.5%
서울대입구역점 37
 
0.3%
전주식당 30
 
0.3%
낙성대점 25
 
0.2%
서울대입구점 22
 
0.2%
서울대점 21
 
0.2%
난곡점 19
 
0.2%
cafe 19
 
0.2%
Other values (9349) 11429
96.1%
2024-05-11T04:32:37.803257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1898
 
3.4%
1131
 
2.1%
1100
 
2.0%
1005
 
1.8%
834
 
1.5%
790
 
1.4%
762
 
1.4%
642
 
1.2%
621
 
1.1%
565
 
1.0%
Other values (1123) 45783
83.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49219
89.3%
Space Separator 1898
 
3.4%
Uppercase Letter 1139
 
2.1%
Lowercase Letter 1096
 
2.0%
Decimal Number 636
 
1.2%
Open Punctuation 435
 
0.8%
Close Punctuation 435
 
0.8%
Other Punctuation 252
 
0.5%
Dash Punctuation 9
 
< 0.1%
Math Symbol 6
 
< 0.1%
Other values (3) 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1131
 
2.3%
1100
 
2.2%
1005
 
2.0%
834
 
1.7%
790
 
1.6%
762
 
1.5%
642
 
1.3%
621
 
1.3%
565
 
1.1%
537
 
1.1%
Other values (1036) 41232
83.8%
Uppercase Letter
ValueCountFrequency (%)
B 107
 
9.4%
E 90
 
7.9%
A 87
 
7.6%
C 79
 
6.9%
O 77
 
6.8%
T 62
 
5.4%
S 54
 
4.7%
L 52
 
4.6%
F 51
 
4.5%
R 48
 
4.2%
Other values (17) 432
37.9%
Lowercase Letter
ValueCountFrequency (%)
e 161
14.7%
o 107
 
9.8%
a 106
 
9.7%
i 68
 
6.2%
r 68
 
6.2%
n 62
 
5.7%
l 57
 
5.2%
f 55
 
5.0%
s 51
 
4.7%
c 50
 
4.6%
Other values (15) 311
28.4%
Other Punctuation
ValueCountFrequency (%)
& 96
38.1%
. 72
28.6%
, 33
 
13.1%
? 17
 
6.7%
' 12
 
4.8%
! 7
 
2.8%
/ 3
 
1.2%
# 3
 
1.2%
: 2
 
0.8%
* 2
 
0.8%
Other values (3) 5
 
2.0%
Decimal Number
ValueCountFrequency (%)
2 144
22.6%
1 98
15.4%
0 79
12.4%
9 63
9.9%
5 54
 
8.5%
8 53
 
8.3%
3 46
 
7.2%
4 43
 
6.8%
6 29
 
4.6%
7 27
 
4.2%
Math Symbol
ValueCountFrequency (%)
+ 3
50.0%
< 1
 
16.7%
> 1
 
16.7%
= 1
 
16.7%
Letter Number
ValueCountFrequency (%)
2
66.7%
1
33.3%
Space Separator
ValueCountFrequency (%)
1898
100.0%
Open Punctuation
ValueCountFrequency (%)
( 435
100.0%
Close Punctuation
ValueCountFrequency (%)
) 435
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Modifier Symbol
ValueCountFrequency (%)
^ 2
100.0%
Other Symbol
ValueCountFrequency (%)
° 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49164
89.2%
Common 3674
 
6.7%
Latin 2238
 
4.1%
Han 46
 
0.1%
Hiragana 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1131
 
2.3%
1100
 
2.2%
1005
 
2.0%
834
 
1.7%
790
 
1.6%
762
 
1.5%
642
 
1.3%
621
 
1.3%
565
 
1.1%
537
 
1.1%
Other values (987) 41177
83.8%
Latin
ValueCountFrequency (%)
e 161
 
7.2%
B 107
 
4.8%
o 107
 
4.8%
a 106
 
4.7%
E 90
 
4.0%
A 87
 
3.9%
C 79
 
3.5%
O 77
 
3.4%
i 68
 
3.0%
r 68
 
3.0%
Other values (44) 1288
57.6%
Han
ValueCountFrequency (%)
3
 
6.5%
2
 
4.3%
2
 
4.3%
2
 
4.3%
1
 
2.2%
1
 
2.2%
1
 
2.2%
1
 
2.2%
1
 
2.2%
1
 
2.2%
Other values (31) 31
67.4%
Common
ValueCountFrequency (%)
1898
51.7%
( 435
 
11.8%
) 435
 
11.8%
2 144
 
3.9%
1 98
 
2.7%
& 96
 
2.6%
0 79
 
2.2%
. 72
 
2.0%
9 63
 
1.7%
5 54
 
1.5%
Other values (23) 300
 
8.2%
Hiragana
ValueCountFrequency (%)
2
22.2%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 49157
89.2%
ASCII 5903
 
10.7%
CJK 43
 
0.1%
Hiragana 9
 
< 0.1%
Compat Jamo 7
 
< 0.1%
None 6
 
< 0.1%
Number Forms 3
 
< 0.1%
CJK Compat Ideographs 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1898
32.2%
( 435
 
7.4%
) 435
 
7.4%
e 161
 
2.7%
2 144
 
2.4%
B 107
 
1.8%
o 107
 
1.8%
a 106
 
1.8%
1 98
 
1.7%
& 96
 
1.6%
Other values (71) 2316
39.2%
Hangul
ValueCountFrequency (%)
1131
 
2.3%
1100
 
2.2%
1005
 
2.0%
834
 
1.7%
790
 
1.6%
762
 
1.6%
642
 
1.3%
621
 
1.3%
565
 
1.1%
537
 
1.1%
Other values (982) 41170
83.8%
CJK
ValueCountFrequency (%)
3
 
7.0%
2
 
4.7%
2
 
4.7%
2
 
4.7%
1
 
2.3%
1
 
2.3%
1
 
2.3%
1
 
2.3%
1
 
2.3%
1
 
2.3%
Other values (28) 28
65.1%
Compat Jamo
ValueCountFrequency (%)
3
42.9%
1
 
14.3%
1
 
14.3%
1
 
14.3%
1
 
14.3%
Number Forms
ValueCountFrequency (%)
2
66.7%
1
33.3%
None
ValueCountFrequency (%)
2
33.3%
2
33.3%
1
16.7%
° 1
16.7%
Hiragana
ValueCountFrequency (%)
2
22.2%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
CJK Compat Ideographs
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Distinct6885
Distinct (%)68.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1999-01-05 00:00:00
Maximum2024-05-09 16:31:29
2024-05-11T04:32:38.426927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:32:39.325103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
7439 
U
2559 
D
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 7439
74.4%
U 2559
 
25.6%
D 2
 
< 0.1%

Length

2024-05-11T04:32:39.866073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:40.219900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 7439
74.4%
u 2559
 
25.6%
d 2
 
< 0.1%
Distinct1318
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T04:32:40.562537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:32:41.028272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct23
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
3954 
분식
2141 
호프/통닭
879 
경양식
794 
기타
787 
Other values (18)
1445 

Length

Max length15
Median length2
Mean length2.7688
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row한식
2nd row분식
3rd row한식
4th row호프/통닭
5th row호프/통닭

Common Values

ValueCountFrequency (%)
한식 3954
39.5%
분식 2141
21.4%
호프/통닭 879
 
8.8%
경양식 794
 
7.9%
기타 787
 
7.9%
일식 360
 
3.6%
중국식 292
 
2.9%
정종/대포집/소주방 221
 
2.2%
통닭(치킨) 185
 
1.8%
까페 73
 
0.7%
Other values (13) 314
 
3.1%

Length

2024-05-11T04:32:41.484371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 3954
39.5%
분식 2141
21.4%
호프/통닭 879
 
8.8%
경양식 794
 
7.9%
기타 787
 
7.9%
일식 360
 
3.6%
중국식 292
 
2.9%
정종/대포집/소주방 221
 
2.2%
통닭(치킨 185
 
1.8%
까페 73
 
0.7%
Other values (13) 314
 
3.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct4041
Distinct (%)41.4%
Missing244
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean194357.4
Minimum191131.26
Maximum198374.47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T04:32:41.888634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191131.26
5-th percentile191975.13
Q1193417.65
median194265.13
Q3195582.25
95-th percentile196924.08
Maximum198374.47
Range7243.2099
Interquartile range (IQR)2164.6011

Descriptive statistics

Standard deviation1558.1148
Coefficient of variation (CV)0.0080167508
Kurtosis-0.3586547
Mean194357.4
Median Absolute Deviation (MAD)1037.8566
Skewness0.24517205
Sum1.8961508 × 109
Variance2427721.8
MonotonicityNot monotonic
2024-05-11T04:32:42.344912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193306.240555398 52
 
0.5%
193630.488645251 48
 
0.5%
194899.891834822 44
 
0.4%
196384.544308046 37
 
0.4%
193654.690899311 36
 
0.4%
195703.043681259 32
 
0.3%
195999.663232701 24
 
0.2%
195537.269534163 21
 
0.2%
193735.829747067 20
 
0.2%
193746.833837509 20
 
0.2%
Other values (4031) 9422
94.2%
(Missing) 244
 
2.4%
ValueCountFrequency (%)
191131.263415395 1
 
< 0.1%
191139.258430167 1
 
< 0.1%
191152.411064668 1
 
< 0.1%
191176.573074128 1
 
< 0.1%
191182.000480527 4
< 0.1%
191185.163772161 1
 
< 0.1%
191191.448323925 9
0.1%
191193.948424131 1
 
< 0.1%
191196.893533157 3
 
< 0.1%
191204.884621244 4
< 0.1%
ValueCountFrequency (%)
198374.473281221 1
 
< 0.1%
198364.235287192 1
 
< 0.1%
198297.240031378 4
 
< 0.1%
198287.460384612 4
 
< 0.1%
198284.487350496 5
0.1%
198284.078546351 12
0.1%
198282.196473514 9
0.1%
198280.308333613 2
 
< 0.1%
198278.931088754 5
0.1%
198278.438025281 9
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct4042
Distinct (%)41.4%
Missing244
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean442005.04
Minimum439023.17
Maximum443553.83
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T04:32:42.857237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum439023.17
5-th percentile440723.87
Q1441533.11
median442151.98
Q3442509.39
95-th percentile442988.89
Maximum443553.83
Range4530.66
Interquartile range (IQR)976.28186

Descriptive statistics

Standard deviation702.804
Coefficient of variation (CV)0.0015900362
Kurtosis0.06424336
Mean442005.04
Median Absolute Deviation (MAD)437.87999
Skewness-0.65285438
Sum4.3122011 × 109
Variance493933.47
MonotonicityNot monotonic
2024-05-11T04:32:43.163694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443221.321009043 52
 
0.5%
442347.332984944 48
 
0.5%
442135.938022991 44
 
0.4%
442822.980265735 37
 
0.4%
442350.522803581 36
 
0.4%
442094.085759338 32
 
0.3%
442420.839863745 24
 
0.2%
442122.202180318 21
 
0.2%
442552.922888015 20
 
0.2%
442510.775085572 20
 
0.2%
Other values (4032) 9422
94.2%
(Missing) 244
 
2.4%
ValueCountFrequency (%)
439023.167125842 12
0.1%
439724.746607732 1
 
< 0.1%
439787.715563055 2
 
< 0.1%
439809.669640911 2
 
< 0.1%
439825.822160271 4
 
< 0.1%
439852.868058712 5
0.1%
439853.488919065 1
 
< 0.1%
439885.315238411 2
 
< 0.1%
439898.027808319 3
 
< 0.1%
439909.959333333 3
 
< 0.1%
ValueCountFrequency (%)
443553.827131144 1
 
< 0.1%
443547.049696825 11
0.1%
443510.752138921 2
 
< 0.1%
443475.946930007 1
 
< 0.1%
443468.517449537 1
 
< 0.1%
443399.27423614 1
 
< 0.1%
443347.669199144 11
0.1%
443341.379446435 15
0.1%
443336.744163369 3
 
< 0.1%
443329.926285288 1
 
< 0.1%

위생업태명
Categorical

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
3237 
분식
2033 
<NA>
1654 
호프/통닭
734 
경양식
654 
Other values (19)
1688 

Length

Max length15
Median length2
Mean length2.9465
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row한식
2nd row분식
3rd row한식
4th row호프/통닭
5th row호프/통닭

Common Values

ValueCountFrequency (%)
한식 3237
32.4%
분식 2033
20.3%
<NA> 1654
16.5%
호프/통닭 734
 
7.3%
경양식 654
 
6.5%
기타 558
 
5.6%
일식 259
 
2.6%
중국식 229
 
2.3%
정종/대포집/소주방 185
 
1.8%
통닭(치킨) 174
 
1.7%
Other values (14) 283
 
2.8%

Length

2024-05-11T04:32:43.526100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 3237
32.4%
분식 2033
20.3%
na 1654
16.5%
호프/통닭 734
 
7.3%
경양식 654
 
6.5%
기타 558
 
5.6%
일식 259
 
2.6%
중국식 229
 
2.3%
정종/대포집/소주방 185
 
1.8%
통닭(치킨 174
 
1.7%
Other values (14) 283
 
2.8%

남성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct9
Distinct (%)0.2%
Missing4413
Missing (%)44.1%
Infinite0
Infinite (%)0.0%
Mean0.37784142
Minimum0
Maximum94
Zeros4452
Zeros (%)44.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T04:32:43.842230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum94
Range94
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.1243869
Coefficient of variation (CV)8.2690428
Kurtosis845.73393
Mean0.37784142
Median Absolute Deviation (MAD)0
Skewness28.483299
Sum2111
Variance9.7617932
MonotonicityNot monotonic
2024-05-11T04:32:44.118902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 4452
44.5%
1 848
 
8.5%
2 191
 
1.9%
3 60
 
0.6%
4 20
 
0.2%
5 8
 
0.1%
94 3
 
< 0.1%
93 3
 
< 0.1%
10 2
 
< 0.1%
(Missing) 4413
44.1%
ValueCountFrequency (%)
0 4452
44.5%
1 848
 
8.5%
2 191
 
1.9%
3 60
 
0.6%
4 20
 
0.2%
5 8
 
0.1%
10 2
 
< 0.1%
93 3
 
< 0.1%
94 3
 
< 0.1%
ValueCountFrequency (%)
94 3
 
< 0.1%
93 3
 
< 0.1%
10 2
 
< 0.1%
5 8
 
0.1%
4 20
 
0.2%
3 60
 
0.6%
2 191
 
1.9%
1 848
 
8.5%
0 4452
44.5%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.1%
Missing4401
Missing (%)44.0%
Infinite0
Infinite (%)0.0%
Mean0.44954456
Minimum0
Maximum15
Zeros3939
Zeros (%)39.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T04:32:44.524827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum15
Range15
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.83973919
Coefficient of variation (CV)1.8679776
Kurtosis37.329648
Mean0.44954456
Median Absolute Deviation (MAD)0
Skewness3.6547283
Sum2517
Variance0.7051619
MonotonicityNot monotonic
2024-05-11T04:32:44.872988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 3939
39.4%
1 997
 
10.0%
2 538
 
5.4%
3 92
 
0.9%
4 22
 
0.2%
5 8
 
0.1%
15 2
 
< 0.1%
10 1
 
< 0.1%
(Missing) 4401
44.0%
ValueCountFrequency (%)
0 3939
39.4%
1 997
 
10.0%
2 538
 
5.4%
3 92
 
0.9%
4 22
 
0.2%
5 8
 
0.1%
10 1
 
< 0.1%
15 2
 
< 0.1%
ValueCountFrequency (%)
15 2
 
< 0.1%
10 1
 
< 0.1%
5 8
 
0.1%
4 22
 
0.2%
3 92
 
0.9%
2 538
 
5.4%
1 997
 
10.0%
0 3939
39.4%
Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5396 
주택가주변
2815 
기타
923 
유흥업소밀집지역
747 
아파트지역
 
80
Other values (3)
 
39

Length

Max length8
Median length4
Mean length4.4182
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5396
54.0%
주택가주변 2815
28.1%
기타 923
 
9.2%
유흥업소밀집지역 747
 
7.5%
아파트지역 80
 
0.8%
학교정화(상대) 21
 
0.2%
결혼예식장주변 11
 
0.1%
학교정화(절대) 7
 
0.1%

Length

2024-05-11T04:32:45.295144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:45.620335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5396
54.0%
주택가주변 2815
28.1%
기타 923
 
9.2%
유흥업소밀집지역 747
 
7.5%
아파트지역 80
 
0.8%
학교정화(상대 21
 
0.2%
결혼예식장주변 11
 
0.1%
학교정화(절대 7
 
0.1%

등급구분명
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5674 
기타
3162 
지도
712 
 
300
자율
 
141
Other values (2)
 
11

Length

Max length4
Median length4
Mean length3.1038
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5674
56.7%
기타 3162
31.6%
지도 712
 
7.1%
300
 
3.0%
자율 141
 
1.4%
10
 
0.1%
관리 1
 
< 0.1%

Length

2024-05-11T04:32:46.054983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:46.684791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5674
56.7%
기타 3162
31.6%
지도 712
 
7.1%
300
 
3.0%
자율 141
 
1.4%
10
 
0.1%
관리 1
 
< 0.1%
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
상수도전용
5922 
<NA>
4047 
상수도(음용)지하수(주방용)겸용
 
30
간이상수도
 
1

Length

Max length17
Median length5
Mean length4.6313
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 5922
59.2%
<NA> 4047
40.5%
상수도(음용)지하수(주방용)겸용 30
 
0.3%
간이상수도 1
 
< 0.1%

Length

2024-05-11T04:32:47.307991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:47.764534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 5922
59.2%
na 4047
40.5%
상수도(음용)지하수(주방용)겸용 30
 
0.3%
간이상수도 1
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9757 
0
 
243

Length

Max length4
Median length4
Mean length3.9271
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> 9757
97.6%
0 243
 
2.4%

Length

2024-05-11T04:32:48.331675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:48.682018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9757
97.6%
0 243
 
2.4%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9757 
0
 
243

Length

Max length4
Median length4
Mean length3.9271
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> 9757
97.6%
0 243
 
2.4%

Length

2024-05-11T04:32:49.122478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:49.488562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9757
97.6%
0 243
 
2.4%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9757 
0
 
243

Length

Max length4
Median length4
Mean length3.9271
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> 9757
97.6%
0 243
 
2.4%

Length

2024-05-11T04:32:49.913058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:50.266472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9757
97.6%
0 243
 
2.4%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9757 
0
 
243

Length

Max length4
Median length4
Mean length3.9271
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> 9757
97.6%
0 243
 
2.4%

Length

2024-05-11T04:32:50.743239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:51.110704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9757
97.6%
0 243
 
2.4%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9757 
0
 
243

Length

Max length4
Median length4
Mean length3.9271
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> 9757
97.6%
0 243
 
2.4%

Length

2024-05-11T04:32:51.432736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:51.739745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9757
97.6%
0 243
 
2.4%

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>
9757 
0
 
243

Length

Max length4
Median length4
Mean length3.9271
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> 9757
97.6%
0 243
 
2.4%

Length

2024-05-11T04:32:52.099395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:52.450989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9757
97.6%
0 243
 
2.4%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9757 
0
 
243

Length

Max length4
Median length4
Mean length3.9271
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> 9757
97.6%
0 243
 
2.4%

Length

2024-05-11T04:32:52.978657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:53.386436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9757
97.6%
0 243
 
2.4%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1654
Missing (%)16.5%
Memory size97.7 KiB
False
8206 
True
 
140
(Missing)
1654 
ValueCountFrequency (%)
False 8206
82.1%
True 140
 
1.4%
(Missing) 1654
 
16.5%
2024-05-11T04:32:53.748846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct4129
Distinct (%)49.5%
Missing1654
Missing (%)16.5%
Infinite0
Infinite (%)0.0%
Mean55.427971
Minimum0
Maximum1389.76
Zeros146
Zeros (%)1.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T04:32:54.241489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13.2
Q123
median33
Q366.1575
95-th percentile150
Maximum1389.76
Range1389.76
Interquartile range (IQR)43.1575

Descriptive statistics

Standard deviation70.375373
Coefficient of variation (CV)1.2696725
Kurtosis92.922538
Mean55.427971
Median Absolute Deviation (MAD)14.8
Skewness7.4550579
Sum462601.85
Variance4952.6931
MonotonicityNot monotonic
2024-05-11T04:32:54.912675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 146
 
1.5%
33.0 142
 
1.4%
30.0 84
 
0.8%
26.4 81
 
0.8%
23.1 51
 
0.5%
24.0 51
 
0.5%
49.5 50
 
0.5%
20.0 48
 
0.5%
16.5 46
 
0.5%
66.0 42
 
0.4%
Other values (4119) 7605
76.0%
(Missing) 1654
 
16.5%
ValueCountFrequency (%)
0.0 146
1.5%
3.3 1
 
< 0.1%
3.67 1
 
< 0.1%
3.97 1
 
< 0.1%
4.4 1
 
< 0.1%
4.5 1
 
< 0.1%
4.95 1
 
< 0.1%
4.97 1
 
< 0.1%
5.0 3
 
< 0.1%
5.21 1
 
< 0.1%
ValueCountFrequency (%)
1389.76 1
< 0.1%
1339.43 1
< 0.1%
1253.96 1
< 0.1%
1248.75 1
< 0.1%
1077.91 1
< 0.1%
1046.34 1
< 0.1%
968.56 1
< 0.1%
967.54 1
< 0.1%
955.35 1
< 0.1%
953.8 1
< 0.1%

전통업소지정번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9999 
8
 
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%
8 1
 
< 0.1%

Length

2024-05-11T04:32:55.485582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:32:55.859326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9999
> 99.9%
8 1
 
< 0.1%

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
1238032000003200000-101-2006-0019020060605<NA>3폐업2폐업20090122<NA><NA><NA>02 878020387.27151811서울특별시 관악구 봉천동 859-31번지 2층<NA><NA>양평해장국2006-06-05 00:00:00I2018-08-31 23:59:59.0한식<NA><NA>한식00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N87.27<NA><NA><NA>
621032000003200000-101-1997-0160819970516<NA>3폐업2폐업19981105<NA><NA><NA>02 868166695.02151876서울특별시 관악구 신림동 543-6번지<NA><NA>해오름2001-09-29 00:00:00I2018-08-31 23:59:59.0분식192162.315637442178.515906분식<NA><NA>주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N95.02<NA><NA><NA>
986232000003200000-101-2002-0018520020412<NA>3폐업2폐업20110726<NA><NA><NA>02 883638828.69151842서울특별시 관악구 봉천동 922-1번지<NA><NA>정동진식당2002-04-12 00:00:00I2018-08-31 23:59:59.0한식195036.685646442184.214938한식00주택가주변<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N28.69<NA><NA><NA>
1192832000003200000-101-2005-0029520050704<NA>3폐업2폐업20140415<NA><NA><NA>02 888333621.96151848서울특별시 관악구 봉천동 1611-1번지 지상1층서울특별시 관악구 관악로16길 42 (봉천동,지상1층)8788풍경2006-02-20 00:00:00I2018-08-31 23:59:59.0호프/통닭195947.727117441939.539151호프/통닭00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N21.96<NA><NA><NA>
1926132000003200000-101-2020-0020720200508<NA>1영업/정상1영업<NA><NA><NA><NA><NA>61.86151875서울특별시 관악구 신림동 527-4번지서울특별시 관악구 난곡로66길 8, 1층 (신림동)8761역전할머니맥주 난곡사거리점2020-05-14 17:37:00U2020-05-16 02:40:00.0호프/통닭192404.069803442253.439088호프/통닭<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N61.86<NA><NA><NA>
1119132000003200000-101-2004-0016920040428<NA>3폐업2폐업20070405<NA><NA><NA>02 830741324.57151899서울특별시 관악구 신림동 1567-6번지 지상1층<NA><NA>금화2006-07-31 00:00:00I2018-08-31 23:59:59.0호프/통닭192432.470024441912.140792호프/통닭00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N24.57<NA><NA><NA>
1703432000003200000-101-2015-004892015-12-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>65.00151-830서울특별시 관악구 봉천동 971-11서울특별시 관악구 봉천로 237-6, 지하1층 (봉천동)8722파운드밀2024-05-09 14:34:46U2023-12-04 23:01:00.0한식193593.626113443058.96566<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
178032000003200000-101-1988-0463119880818<NA>3폐업2폐업19930812<NA><NA><NA>020856851227.63151875서울특별시 관악구 신림동 529-20번지<NA><NA>마돈나2002-01-09 00:00:00I2018-08-31 23:59:59.0경양식192368.666966442337.167697경양식21주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N27.63<NA><NA><NA>
370032000003200000-101-1993-0387919931208<NA>3폐업2폐업19950223<NA><NA><NA>02 5212395121.18151926서울특별시 관악구 남현동 1054-9번지<NA><NA>흙미리방2001-09-29 00:00:00I2018-08-31 23:59:59.0분식197546.64111441501.213353분식00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N121.18<NA><NA><NA>
2099132000003200000-101-2023-000312023-01-18<NA>3폐업2폐업2024-05-03<NA><NA><NA><NA>12.76151-818서울특별시 관악구 봉천동 1661-4서울특별시 관악구 남부순환로 1904, 지1층 11호 (봉천동)8792인생BBQ 양키고기 관악점2024-05-03 11:45:40U2023-12-05 00:05:00.0식육(숯불구이)196461.877883441740.147865<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
474032000003200000-101-1995-0236319951226<NA>3폐업2폐업20020514<NA><NA><NA>02 867977417.60151893서울특별시 관악구 신림동 481-8번지<NA><NA>신림반점2000-03-24 00:00:00I2018-08-31 23:59:59.0중국식192826.226966442622.350327중국식00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N17.6<NA><NA><NA>
1154032000003200000-101-2004-0052320041101<NA>3폐업2폐업20100115<NA><NA><NA><NA>126.70151904서울특별시 관악구 신림동 1659-1번지 지상1층<NA><NA>토속촌2009-06-03 10:29:22I2018-08-31 23:59:59.0한식191548.707029442176.703717한식00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N126.7<NA><NA><NA>
1065632000003200000-101-2003-0032220030626<NA>1영업/정상1영업<NA><NA><NA><NA><NA>37.95151892서울특별시 관악구 신림동 1433-139번지서울특별시 관악구 남부순환로 1585-3, 1층 (신림동)8759미나리생삼겹2014-11-13 14:24:23I2018-08-31 23:59:59.0한식193448.05291442470.317753한식12기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N37.95<NA><NA><NA>
1643432000003200000-101-2014-0038220141010<NA>1영업/정상1영업<NA><NA><NA><NA><NA>85.59151832서울특별시 관악구 봉천동 1637-34서울특별시 관악구 인헌4길 8, 1층 (봉천동)8793오래와라2020-11-25 17:37:07U2020-11-27 02:40:00.0호프/통닭196965.625656441389.086201호프/통닭<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N85.59<NA><NA><NA>
233932000003200000-101-1990-0321619901227<NA>3폐업2폐업19960722<NA><NA><NA>02 863802323.75151872서울특별시 관악구 신림동 504-22번지<NA><NA>맛나식당2001-09-29 00:00:00I2018-08-31 23:59:59.0분식192538.405972442522.185478분식01주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N23.75<NA><NA><NA>
197232000003200000-101-1989-0213219890626<NA>3폐업2폐업19930716<NA><NA><NA>02 0000034.18151862서울특별시 관악구 신림동 1526-2번지<NA><NA>다림방2002-01-10 00:00:00I2018-08-31 23:59:59.0분식194038.868491440972.429852분식22기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N34.18<NA><NA><NA>
324732000003200000-101-1992-0489619921121<NA>3폐업2폐업20130405<NA><NA><NA>02190.97151892서울특별시 관악구 신림동 1432-73번지 지상8층서울특별시 관악구 신림로 353, 8층 (신림동)8760올 댓 째즈2013-02-01 13:41:11I2018-08-31 23:59:59.0기타193667.814824442621.679865기타00유흥업소밀집지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N190.97<NA><NA><NA>
1773132000003200000-101-2017-0022220170609<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.30151889서울특별시 관악구 신림동 703-5번지서울특별시 관악구 난곡로24길 10, 1층 (신림동)8857공주식당2019-09-18 10:40:33U2019-09-20 02:40:00.0한식192899.440965440834.491985한식<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N33.3<NA><NA><NA>
1232732000003200000-101-2006-0013720060428<NA>3폐업2폐업20160325<NA><NA><NA>02 887772025.30151827서울특별시 관악구 봉천동 943-14번지서울특별시 관악구 봉천로31길 49, 1층 (봉천동)8749로드포차2013-12-27 11:29:35I2018-08-31 23:59:59.0분식194581.258406442531.352997분식00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N25.3<NA><NA><NA>
716632000003200000-101-1999-0928319991203<NA>3폐업2폐업20010305<NA><NA><NA>0281.73151847서울특별시 관악구 봉천동 1578-5번지<NA><NA>라스칼라2001-03-05 00:00:00I2018-08-31 23:59:59.0분식195123.103902441681.122232분식01기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N81.73<NA><NA><NA>