Overview

Dataset statistics

Number of variables44
Number of observations4236
Missing cells44968
Missing cells (%)24.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 MiB
Average record size in memory377.0 B

Variable types

Categorical19
Text6
DateTime4
Unsupported7
Numeric7
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
Author노원구
URLhttps://data.seoul.go.kr/dataList/OA-18687/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업장주변구분명 is highly imbalanced (62.1%)Imbalance
등급구분명 is highly imbalanced (63.7%)Imbalance
총인원 is highly imbalanced (74.0%)Imbalance
본사종업원수 is highly imbalanced (73.2%)Imbalance
공장사무직종업원수 is highly imbalanced (73.2%)Imbalance
공장판매직종업원수 is highly imbalanced (73.2%)Imbalance
공장생산직종업원수 is highly imbalanced (73.2%)Imbalance
보증액 is highly imbalanced (73.2%)Imbalance
월세액 is highly imbalanced (73.2%)Imbalance
다중이용업소여부 is highly imbalanced (91.4%)Imbalance
전통업소지정번호 is highly imbalanced (99.7%)Imbalance
인허가취소일자 has 4236 (100.0%) missing valuesMissing
폐업일자 has 1324 (31.3%) missing valuesMissing
휴업시작일자 has 4236 (100.0%) missing valuesMissing
휴업종료일자 has 4236 (100.0%) missing valuesMissing
재개업일자 has 4236 (100.0%) missing valuesMissing
전화번호 has 2350 (55.5%) missing valuesMissing
소재지면적 has 135 (3.2%) missing valuesMissing
도로명주소 has 1326 (31.3%) missing valuesMissing
도로명우편번호 has 1351 (31.9%) missing valuesMissing
좌표정보(X) has 120 (2.8%) missing valuesMissing
좌표정보(Y) has 120 (2.8%) missing valuesMissing
남성종사자수 has 3269 (77.2%) missing valuesMissing
여성종사자수 has 3271 (77.2%) missing valuesMissing
건물소유구분명 has 4236 (100.0%) missing valuesMissing
다중이용업소여부 has 1014 (23.9%) missing valuesMissing
시설총규모 has 1014 (23.9%) missing valuesMissing
전통업소주된음식 has 4236 (100.0%) missing valuesMissing
홈페이지 has 4236 (100.0%) missing valuesMissing
도로명우편번호 is highly skewed (γ1 = 43.14872375)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 887 (20.9%) zerosZeros
여성종사자수 has 766 (18.1%) zerosZeros
시설총규모 has 77 (1.8%) zerosZeros

Reproduction

Analysis started2024-05-11 04:03:30.310505
Analysis finished2024-05-11 04:03:34.167178
Duration3.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.2 KiB
3100000
4236 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3100000
2nd row3100000
3rd row3100000
4th row3100000
5th row3100000

Common Values

ValueCountFrequency (%)
3100000 4236
100.0%

Length

2024-05-11T04:03:34.312746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:03:34.637197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3100000 4236
100.0%

관리번호
Text

UNIQUE 

Distinct4236
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size33.2 KiB
2024-05-11T04:03:35.194975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters93192
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

Unique4236 ?
Unique (%)100.0%

Sample

1st row3100000-104-1973-05429
2nd row3100000-104-1974-05406
3rd row3100000-104-1978-05202
4th row3100000-104-1978-05413
5th row3100000-104-1979-05376
ValueCountFrequency (%)
3100000-104-1973-05429 1
 
< 0.1%
3100000-104-2017-00132 1
 
< 0.1%
3100000-104-2017-00150 1
 
< 0.1%
3100000-104-2017-00149 1
 
< 0.1%
3100000-104-2017-00120 1
 
< 0.1%
3100000-104-2017-00121 1
 
< 0.1%
3100000-104-2017-00122 1
 
< 0.1%
3100000-104-2017-00123 1
 
< 0.1%
3100000-104-2017-00124 1
 
< 0.1%
3100000-104-2017-00125 1
 
< 0.1%
Other values (4226) 4226
99.8%
2024-05-11T04:03:36.206669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 40639
43.6%
1 13697
 
14.7%
- 12708
 
13.6%
2 6043
 
6.5%
3 5787
 
6.2%
4 5633
 
6.0%
9 2541
 
2.7%
5 1959
 
2.1%
6 1491
 
1.6%
7 1392
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80484
86.4%
Dash Punctuation 12708
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 40639
50.5%
1 13697
 
17.0%
2 6043
 
7.5%
3 5787
 
7.2%
4 5633
 
7.0%
9 2541
 
3.2%
5 1959
 
2.4%
6 1491
 
1.9%
7 1392
 
1.7%
8 1302
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 12708
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 93192
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 40639
43.6%
1 13697
 
14.7%
- 12708
 
13.6%
2 6043
 
6.5%
3 5787
 
6.2%
4 5633
 
6.0%
9 2541
 
2.7%
5 1959
 
2.1%
6 1491
 
1.6%
7 1392
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 93192
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 40639
43.6%
1 13697
 
14.7%
- 12708
 
13.6%
2 6043
 
6.5%
3 5787
 
6.2%
4 5633
 
6.0%
9 2541
 
2.7%
5 1959
 
2.1%
6 1491
 
1.6%
7 1392
 
1.5%
Distinct3064
Distinct (%)72.3%
Missing0
Missing (%)0.0%
Memory size33.2 KiB
Minimum1973-09-07 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T04:03:36.856901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:03:37.537771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4236
Missing (%)100.0%
Memory size37.4 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.2 KiB
3
2912 
1
1324 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 2912
68.7%
1 1324
31.3%

Length

2024-05-11T04:03:38.221115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:03:38.652448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2912
68.7%
1 1324
31.3%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.2 KiB
폐업
2912 
영업/정상
1324 

Length

Max length5
Median length2
Mean length2.9376771
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2912
68.7%
영업/정상 1324
31.3%

Length

2024-05-11T04:03:39.249318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:03:39.714346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2912
68.7%
영업/정상 1324
31.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.2 KiB
2
2912 
1
1324 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 2912
68.7%
1 1324
31.3%

Length

2024-05-11T04:03:40.276954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:03:40.765246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2912
68.7%
1 1324
31.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.2 KiB
폐업
2912 
영업
1324 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2912
68.7%
영업 1324
31.3%

Length

2024-05-11T04:03:41.186913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:03:41.559145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2912
68.7%
영업 1324
31.3%

폐업일자
Date

MISSING 

Distinct2191
Distinct (%)75.2%
Missing1324
Missing (%)31.3%
Memory size33.2 KiB
Minimum1993-07-07 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T04:03:41.952012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:03:42.455438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4236
Missing (%)100.0%
Memory size37.4 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4236
Missing (%)100.0%
Memory size37.4 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4236
Missing (%)100.0%
Memory size37.4 KiB

전화번호
Text

MISSING 

Distinct1673
Distinct (%)88.7%
Missing2350
Missing (%)55.5%
Memory size33.2 KiB
2024-05-11T04:03:43.391027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.252916
Min length2

Characters and Unicode

Total characters19337
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

Unique1596 ?
Unique (%)84.6%

Sample

1st row02 9366698
2nd row02 9722217
3rd row02 9728893
4th row02 9729433
5th row0209722016
ValueCountFrequency (%)
02 1424
37.5%
070 58
 
1.5%
949 24
 
0.6%
9392222 24
 
0.6%
931 21
 
0.6%
9781919 21
 
0.6%
930 21
 
0.6%
933 20
 
0.5%
031 19
 
0.5%
939 18
 
0.5%
Other values (1742) 2151
56.6%
2024-05-11T04:03:45.123810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3255
16.8%
2 2874
14.9%
9 2516
13.0%
2473
12.8%
3 1732
9.0%
7 1384
7.2%
1 1221
 
6.3%
5 1092
 
5.6%
8 996
 
5.2%
4 960
 
5.0%
Other values (2) 834
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16863
87.2%
Space Separator 2473
 
12.8%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3255
19.3%
2 2874
17.0%
9 2516
14.9%
3 1732
10.3%
7 1384
8.2%
1 1221
 
7.2%
5 1092
 
6.5%
8 996
 
5.9%
4 960
 
5.7%
6 833
 
4.9%
Space Separator
ValueCountFrequency (%)
2473
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19337
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3255
16.8%
2 2874
14.9%
9 2516
13.0%
2473
12.8%
3 1732
9.0%
7 1384
7.2%
1 1221
 
6.3%
5 1092
 
5.6%
8 996
 
5.2%
4 960
 
5.0%
Other values (2) 834
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19337
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3255
16.8%
2 2874
14.9%
9 2516
13.0%
2473
12.8%
3 1732
9.0%
7 1384
7.2%
1 1221
 
6.3%
5 1092
 
5.6%
8 996
 
5.2%
4 960
 
5.0%
Other values (2) 834
 
4.3%

소재지면적
Real number (ℝ)

MISSING 

Distinct1917
Distinct (%)46.7%
Missing135
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean39.058417
Minimum0
Maximum965
Zeros14
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size37.4 KiB
2024-05-11T04:03:46.144840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q112.2
median25.48
Q344.65
95-th percentile121.36
Maximum965
Range965
Interquartile range (IQR)32.45

Descriptive statistics

Standard deviation51.158366
Coefficient of variation (CV)1.3097911
Kurtosis50.985241
Mean39.058417
Median Absolute Deviation (MAD)15.48
Skewness5.2397718
Sum160178.57
Variance2617.1784
MonotonicityNot monotonic
2024-05-11T04:03:46.949743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 225
 
5.3%
6.6 117
 
2.8%
10.0 69
 
1.6%
9.9 63
 
1.5%
30.0 60
 
1.4%
33.0 56
 
1.3%
6.0 41
 
1.0%
13.2 39
 
0.9%
20.0 36
 
0.8%
16.5 35
 
0.8%
Other values (1907) 3360
79.3%
(Missing) 135
 
3.2%
ValueCountFrequency (%)
0.0 14
0.3%
1.0 2
 
< 0.1%
1.49 1
 
< 0.1%
1.5 2
 
< 0.1%
1.68 2
 
< 0.1%
1.87 1
 
< 0.1%
1.95 2
 
< 0.1%
2.0 3
 
0.1%
2.08 1
 
< 0.1%
2.2 2
 
< 0.1%
ValueCountFrequency (%)
965.0 1
< 0.1%
660.0 1
< 0.1%
610.9 1
< 0.1%
579.48 1
< 0.1%
500.66 1
< 0.1%
470.47 1
< 0.1%
469.4 1
< 0.1%
455.19 1
< 0.1%
444.5 1
< 0.1%
422.0 1
< 0.1%
Distinct203
Distinct (%)4.8%
Missing11
Missing (%)0.3%
Memory size33.2 KiB
2024-05-11T04:03:48.153454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.164497
Min length6

Characters and Unicode

Total characters26045
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

Unique30 ?
Unique (%)0.7%

Sample

1st row139810
2nd row139808
3rd row139240
4th row139240
5th row139808
ValueCountFrequency (%)
139200 202
 
4.8%
139240 187
 
4.4%
139708 172
 
4.1%
139816 158
 
3.7%
139821 138
 
3.3%
139800 126
 
3.0%
139837 113
 
2.7%
139861 110
 
2.6%
139860 107
 
2.5%
139808 104
 
2.5%
Other values (193) 2808
66.5%
2024-05-11T04:03:49.872325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5253
20.2%
3 4985
19.1%
9 4533
17.4%
8 3457
13.3%
0 2305
8.9%
2 1571
 
6.0%
6 971
 
3.7%
4 878
 
3.4%
7 804
 
3.1%
- 695
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25350
97.3%
Dash Punctuation 695
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5253
20.7%
3 4985
19.7%
9 4533
17.9%
8 3457
13.6%
0 2305
9.1%
2 1571
 
6.2%
6 971
 
3.8%
4 878
 
3.5%
7 804
 
3.2%
5 593
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 695
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26045
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 5253
20.2%
3 4985
19.1%
9 4533
17.4%
8 3457
13.3%
0 2305
8.9%
2 1571
 
6.0%
6 971
 
3.7%
4 878
 
3.4%
7 804
 
3.1%
- 695
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26045
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5253
20.2%
3 4985
19.1%
9 4533
17.4%
8 3457
13.3%
0 2305
8.9%
2 1571
 
6.0%
6 971
 
3.7%
4 878
 
3.4%
7 804
 
3.1%
- 695
 
2.7%
Distinct3316
Distinct (%)78.5%
Missing11
Missing (%)0.3%
Memory size33.2 KiB
2024-05-11T04:03:50.852609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length47
Mean length26.804497
Min length16

Characters and Unicode

Total characters113249
Distinct characters400
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

Unique2900 ?
Unique (%)68.6%

Sample

1st row서울특별시 노원구 상계동 101-9번지
2nd row서울특별시 노원구 공릉동 661-1번지
3rd row서울특별시 노원구 공릉동 517-31번지
4th row서울특별시 노원구 공릉동 517-31번지
5th row서울특별시 노원구 공릉동 661-4번지
ValueCountFrequency (%)
노원구 4226
19.6%
서울특별시 4224
19.6%
상계동 1799
 
8.3%
중계동 918
 
4.3%
공릉동 744
 
3.4%
월계동 503
 
2.3%
1층 387
 
1.8%
하계동 265
 
1.2%
지하1층 240
 
1.1%
롯데백화점 205
 
0.9%
Other values (3482) 8068
37.4%
2024-05-11T04:03:52.336562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20069
 
17.7%
1 5276
 
4.7%
4583
 
4.0%
4412
 
3.9%
4342
 
3.8%
4339
 
3.8%
4303
 
3.8%
4282
 
3.8%
4254
 
3.8%
4225
 
3.7%
Other values (390) 53164
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67563
59.7%
Decimal Number 21950
 
19.4%
Space Separator 20069
 
17.7%
Dash Punctuation 3103
 
2.7%
Other Punctuation 214
 
0.2%
Uppercase Letter 147
 
0.1%
Open Punctuation 95
 
0.1%
Close Punctuation 94
 
0.1%
Math Symbol 8
 
< 0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4583
 
6.8%
4412
 
6.5%
4342
 
6.4%
4339
 
6.4%
4303
 
6.4%
4282
 
6.3%
4254
 
6.3%
4225
 
6.3%
4224
 
6.3%
3753
 
5.6%
Other values (345) 24846
36.8%
Uppercase Letter
ValueCountFrequency (%)
B 69
46.9%
A 28
19.0%
S 8
 
5.4%
D 7
 
4.8%
E 7
 
4.8%
C 6
 
4.1%
K 3
 
2.0%
I 2
 
1.4%
H 2
 
1.4%
T 2
 
1.4%
Other values (11) 13
 
8.8%
Decimal Number
ValueCountFrequency (%)
1 5276
24.0%
3 2731
12.4%
2 2368
10.8%
0 2302
10.5%
6 1829
 
8.3%
5 1741
 
7.9%
4 1711
 
7.8%
7 1577
 
7.2%
9 1319
 
6.0%
8 1096
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 189
88.3%
. 9
 
4.2%
@ 8
 
3.7%
/ 7
 
3.3%
? 1
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
n 2
33.3%
g 2
33.3%
i 1
16.7%
m 1
16.7%
Space Separator
ValueCountFrequency (%)
20069
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3103
100.0%
Open Punctuation
ValueCountFrequency (%)
( 95
100.0%
Close Punctuation
ValueCountFrequency (%)
) 94
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67563
59.7%
Common 45533
40.2%
Latin 153
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4583
 
6.8%
4412
 
6.5%
4342
 
6.4%
4339
 
6.4%
4303
 
6.4%
4282
 
6.3%
4254
 
6.3%
4225
 
6.3%
4224
 
6.3%
3753
 
5.6%
Other values (345) 24846
36.8%
Latin
ValueCountFrequency (%)
B 69
45.1%
A 28
18.3%
S 8
 
5.2%
D 7
 
4.6%
E 7
 
4.6%
C 6
 
3.9%
K 3
 
2.0%
I 2
 
1.3%
n 2
 
1.3%
g 2
 
1.3%
Other values (15) 19
 
12.4%
Common
ValueCountFrequency (%)
20069
44.1%
1 5276
 
11.6%
- 3103
 
6.8%
3 2731
 
6.0%
2 2368
 
5.2%
0 2302
 
5.1%
6 1829
 
4.0%
5 1741
 
3.8%
4 1711
 
3.8%
7 1577
 
3.5%
Other values (10) 2826
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67562
59.7%
ASCII 45686
40.3%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20069
43.9%
1 5276
 
11.5%
- 3103
 
6.8%
3 2731
 
6.0%
2 2368
 
5.2%
0 2302
 
5.0%
6 1829
 
4.0%
5 1741
 
3.8%
4 1711
 
3.7%
7 1577
 
3.5%
Other values (35) 2979
 
6.5%
Hangul
ValueCountFrequency (%)
4583
 
6.8%
4412
 
6.5%
4342
 
6.4%
4339
 
6.4%
4303
 
6.4%
4282
 
6.3%
4254
 
6.3%
4225
 
6.3%
4224
 
6.3%
3753
 
5.6%
Other values (344) 24845
36.8%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct2521
Distinct (%)86.6%
Missing1326
Missing (%)31.3%
Memory size33.2 KiB
2024-05-11T04:03:53.312196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length55
Mean length35.247079
Min length21

Characters and Unicode

Total characters102569
Distinct characters411
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

Unique2346 ?
Unique (%)80.6%

Sample

1st row서울특별시 노원구 덕릉로 756 (상계동)
2nd row서울특별시 노원구 동일로243길 29 (상계동,지하1층)
3rd row서울특별시 노원구 동일로174길 32 (공릉동)
4th row서울특별시 노원구 중계로6길 22 (중계동)
5th row서울특별시 노원구 동일로 1532, 1층 (상계동)
ValueCountFrequency (%)
노원구 2911
 
14.6%
서울특별시 2909
 
14.6%
상계동 1135
 
5.7%
1층 1086
 
5.5%
공릉동 562
 
2.8%
중계동 521
 
2.6%
동일로 463
 
2.3%
월계동 362
 
1.8%
지하1층 306
 
1.5%
한글비석로 262
 
1.3%
Other values (2285) 9354
47.1%
2024-05-11T04:03:54.948736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16966
 
16.5%
1 5607
 
5.5%
4238
 
4.1%
, 3505
 
3.4%
3296
 
3.2%
3281
 
3.2%
3054
 
3.0%
3003
 
2.9%
2987
 
2.9%
) 2975
 
2.9%
Other values (401) 53657
52.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 58466
57.0%
Decimal Number 17203
 
16.8%
Space Separator 16966
 
16.5%
Other Punctuation 3516
 
3.4%
Close Punctuation 2976
 
2.9%
Open Punctuation 2976
 
2.9%
Dash Punctuation 328
 
0.3%
Uppercase Letter 121
 
0.1%
Math Symbol 11
 
< 0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4238
 
7.2%
3296
 
5.6%
3281
 
5.6%
3054
 
5.2%
3003
 
5.1%
2987
 
5.1%
2953
 
5.1%
2945
 
5.0%
2933
 
5.0%
2911
 
5.0%
Other values (356) 26865
45.9%
Uppercase Letter
ValueCountFrequency (%)
B 54
44.6%
A 26
21.5%
S 7
 
5.8%
C 6
 
5.0%
E 6
 
5.0%
G 3
 
2.5%
D 3
 
2.5%
H 2
 
1.7%
K 2
 
1.7%
T 2
 
1.7%
Other values (9) 10
 
8.3%
Decimal Number
ValueCountFrequency (%)
1 5607
32.6%
2 2348
13.6%
0 1802
 
10.5%
4 1652
 
9.6%
3 1571
 
9.1%
5 1056
 
6.1%
7 893
 
5.2%
6 850
 
4.9%
8 736
 
4.3%
9 688
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 3505
99.7%
. 5
 
0.1%
@ 4
 
0.1%
* 1
 
< 0.1%
/ 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
n 2
33.3%
g 2
33.3%
m 1
16.7%
i 1
16.7%
Close Punctuation
ValueCountFrequency (%)
) 2975
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 2975
> 99.9%
[ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
16966
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 328
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 58466
57.0%
Common 43976
42.9%
Latin 127
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4238
 
7.2%
3296
 
5.6%
3281
 
5.6%
3054
 
5.2%
3003
 
5.1%
2987
 
5.1%
2953
 
5.1%
2945
 
5.0%
2933
 
5.0%
2911
 
5.0%
Other values (356) 26865
45.9%
Latin
ValueCountFrequency (%)
B 54
42.5%
A 26
20.5%
S 7
 
5.5%
C 6
 
4.7%
E 6
 
4.7%
G 3
 
2.4%
D 3
 
2.4%
n 2
 
1.6%
H 2
 
1.6%
g 2
 
1.6%
Other values (13) 16
 
12.6%
Common
ValueCountFrequency (%)
16966
38.6%
1 5607
 
12.8%
, 3505
 
8.0%
) 2975
 
6.8%
( 2975
 
6.8%
2 2348
 
5.3%
0 1802
 
4.1%
4 1652
 
3.8%
3 1571
 
3.6%
5 1056
 
2.4%
Other values (12) 3519
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 58465
57.0%
ASCII 44103
43.0%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16966
38.5%
1 5607
 
12.7%
, 3505
 
7.9%
) 2975
 
6.7%
( 2975
 
6.7%
2 2348
 
5.3%
0 1802
 
4.1%
4 1652
 
3.7%
3 1571
 
3.6%
5 1056
 
2.4%
Other values (35) 3646
 
8.3%
Hangul
ValueCountFrequency (%)
4238
 
7.2%
3296
 
5.6%
3281
 
5.6%
3054
 
5.2%
3003
 
5.1%
2987
 
5.1%
2953
 
5.1%
2945
 
5.0%
2933
 
5.0%
2911
 
5.0%
Other values (355) 26864
45.9%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct274
Distinct (%)9.5%
Missing1351
Missing (%)31.9%
Infinite0
Infinite (%)0.0%
Mean1759.0867
Minimum1600
Maximum13353
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.4 KiB
2024-05-11T04:03:55.529374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1600
5-th percentile1624
Q11693
median1746
Q31833
95-th percentile1902
Maximum13353
Range11753
Interquartile range (IQR)140

Descriptive statistics

Standard deviation232.28315
Coefficient of variation (CV)0.13204759
Kurtosis2153.5728
Mean1759.0867
Median Absolute Deviation (MAD)64
Skewness43.148724
Sum5074965
Variance53955.463
MonotonicityNot monotonic
2024-05-11T04:03:56.114350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1695 254
 
6.0%
1693 94
 
2.2%
1906 79
 
1.9%
1783 69
 
1.6%
1849 58
 
1.4%
1662 53
 
1.3%
1779 49
 
1.2%
1746 48
 
1.1%
1784 42
 
1.0%
1762 40
 
0.9%
Other values (264) 2099
49.6%
(Missing) 1351
31.9%
ValueCountFrequency (%)
1600 1
 
< 0.1%
1601 7
 
0.2%
1603 4
 
0.1%
1604 19
0.4%
1605 4
 
0.1%
1606 7
 
0.2%
1607 6
 
0.1%
1608 14
0.3%
1609 7
 
0.2%
1610 1
 
< 0.1%
ValueCountFrequency (%)
13353 1
 
< 0.1%
1914 15
 
0.4%
1913 13
 
0.3%
1912 1
 
< 0.1%
1911 6
 
0.1%
1910 5
 
0.1%
1909 6
 
0.1%
1907 1
 
< 0.1%
1906 79
1.9%
1905 3
 
0.1%
Distinct3921
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size33.2 KiB
2024-05-11T04:03:57.065744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length27
Mean length7.3925873
Min length1

Characters and Unicode

Total characters31315
Distinct characters890
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

Unique3702 ?
Unique (%)87.4%

Sample

1st row
2nd row황해
3rd row쎌레스테
4th row길다방
5th row우성
ValueCountFrequency (%)
세븐일레븐 60
 
1.1%
노원점 58
 
1.1%
카페 43
 
0.8%
씨유 42
 
0.8%
gs25 33
 
0.6%
공릉점 27
 
0.5%
중계점 26
 
0.5%
메가엠지씨커피 24
 
0.4%
노원역점 22
 
0.4%
cafe 20
 
0.4%
Other values (4110) 5111
93.5%
2024-05-11T04:03:58.455964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1355
 
4.3%
1231
 
3.9%
903
 
2.9%
691
 
2.2%
614
 
2.0%
( 582
 
1.9%
) 582
 
1.9%
570
 
1.8%
507
 
1.6%
433
 
1.4%
Other values (880) 23847
76.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25643
81.9%
Lowercase Letter 1252
 
4.0%
Space Separator 1231
 
3.9%
Uppercase Letter 1230
 
3.9%
Decimal Number 669
 
2.1%
Open Punctuation 582
 
1.9%
Close Punctuation 582
 
1.9%
Other Punctuation 103
 
0.3%
Dash Punctuation 16
 
0.1%
Letter Number 2
 
< 0.1%
Other values (3) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1355
 
5.3%
903
 
3.5%
691
 
2.7%
614
 
2.4%
570
 
2.2%
507
 
2.0%
433
 
1.7%
426
 
1.7%
378
 
1.5%
354
 
1.4%
Other values (802) 19412
75.7%
Uppercase Letter
ValueCountFrequency (%)
S 212
17.2%
C 191
15.5%
G 167
13.6%
P 96
 
7.8%
E 73
 
5.9%
U 59
 
4.8%
A 54
 
4.4%
O 47
 
3.8%
T 44
 
3.6%
F 42
 
3.4%
Other values (16) 245
19.9%
Lowercase Letter
ValueCountFrequency (%)
e 208
16.6%
o 130
10.4%
a 116
9.3%
f 112
 
8.9%
c 97
 
7.7%
s 66
 
5.3%
i 66
 
5.3%
n 62
 
5.0%
r 59
 
4.7%
t 54
 
4.3%
Other values (15) 282
22.5%
Decimal Number
ValueCountFrequency (%)
2 245
36.6%
5 191
28.6%
1 64
 
9.6%
4 40
 
6.0%
9 29
 
4.3%
0 29
 
4.3%
3 28
 
4.2%
7 17
 
2.5%
8 14
 
2.1%
6 12
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 35
34.0%
& 26
25.2%
, 13
 
12.6%
? 11
 
10.7%
' 9
 
8.7%
# 3
 
2.9%
/ 3
 
2.9%
! 2
 
1.9%
% 1
 
1.0%
Space Separator
ValueCountFrequency (%)
1231
100.0%
Open Punctuation
ValueCountFrequency (%)
( 582
100.0%
Close Punctuation
ValueCountFrequency (%)
) 582
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25630
81.8%
Common 3187
 
10.2%
Latin 2484
 
7.9%
Han 9
 
< 0.1%
Katakana 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1355
 
5.3%
903
 
3.5%
691
 
2.7%
614
 
2.4%
570
 
2.2%
507
 
2.0%
433
 
1.7%
426
 
1.7%
378
 
1.5%
354
 
1.4%
Other values (789) 19399
75.7%
Latin
ValueCountFrequency (%)
S 212
 
8.5%
e 208
 
8.4%
C 191
 
7.7%
G 167
 
6.7%
o 130
 
5.2%
a 116
 
4.7%
f 112
 
4.5%
c 97
 
3.9%
P 96
 
3.9%
E 73
 
2.9%
Other values (42) 1082
43.6%
Common
ValueCountFrequency (%)
1231
38.6%
( 582
18.3%
) 582
18.3%
2 245
 
7.7%
5 191
 
6.0%
1 64
 
2.0%
4 40
 
1.3%
. 35
 
1.1%
9 29
 
0.9%
0 29
 
0.9%
Other values (15) 159
 
5.0%
Han
ValueCountFrequency (%)
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
Katakana
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25626
81.8%
ASCII 5669
 
18.1%
CJK 8
 
< 0.1%
Katakana 5
 
< 0.1%
Compat Jamo 3
 
< 0.1%
Number Forms 2
 
< 0.1%
None 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1355
 
5.3%
903
 
3.5%
691
 
2.7%
614
 
2.4%
570
 
2.2%
507
 
2.0%
433
 
1.7%
426
 
1.7%
378
 
1.5%
354
 
1.4%
Other values (786) 19395
75.7%
ASCII
ValueCountFrequency (%)
1231
21.7%
( 582
 
10.3%
) 582
 
10.3%
2 245
 
4.3%
S 212
 
3.7%
e 208
 
3.7%
5 191
 
3.4%
C 191
 
3.4%
G 167
 
2.9%
o 130
 
2.3%
Other values (66) 1930
34.0%
Compat Jamo
ValueCountFrequency (%)
2
66.7%
1
33.3%
Number Forms
ValueCountFrequency (%)
2
100.0%
None
ValueCountFrequency (%)
1
100.0%
Katakana
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
Distinct3670
Distinct (%)86.6%
Missing0
Missing (%)0.0%
Memory size33.2 KiB
Minimum1999-04-26 00:00:00
Maximum2024-05-09 09:25:48
2024-05-11T04:03:59.100005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:03:59.566502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size33.2 KiB
I
2746 
U
1489 
D
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
I 2746
64.8%
U 1489
35.2%
D 1
 
< 0.1%

Length

2024-05-11T04:04:00.023180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:00.351177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2746
64.8%
u 1489
35.2%
d 1
 
< 0.1%
Distinct1083
Distinct (%)25.6%
Missing0
Missing (%)0.0%
Memory size33.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T04:04:00.713803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:04:01.168759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct15
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size33.2 KiB
커피숍
1116 
기타 휴게음식점
880 
일반조리판매
758 
편의점
341 
다방
301 
Other values (10)
840 

Length

Max length8
Median length6
Mean length4.6784703
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row다방
2nd row다방
3rd row과자점
4th row다방
5th row다방

Common Values

ValueCountFrequency (%)
커피숍 1116
26.3%
기타 휴게음식점 880
20.8%
일반조리판매 758
17.9%
편의점 341
 
8.1%
다방 301
 
7.1%
패스트푸드 301
 
7.1%
과자점 284
 
6.7%
백화점 155
 
3.7%
아이스크림 35
 
0.8%
푸드트럭 26
 
0.6%
Other values (5) 39
 
0.9%

Length

2024-05-11T04:04:01.466163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 1116
21.8%
기타 880
17.2%
휴게음식점 880
17.2%
일반조리판매 758
14.8%
편의점 341
 
6.7%
다방 301
 
5.9%
패스트푸드 301
 
5.9%
과자점 284
 
5.6%
백화점 155
 
3.0%
아이스크림 35
 
0.7%
Other values (6) 65
 
1.3%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1478
Distinct (%)35.9%
Missing120
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean205945.14
Minimum203721.87
Maximum212913.03
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.4 KiB
2024-05-11T04:04:01.771821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum203721.87
5-th percentile204790.42
Q1205320.28
median205931.05
Q3206564.01
95-th percentile207175.56
Maximum212913.03
Range9191.1666
Interquartile range (IQR)1243.7274

Descriptive statistics

Standard deviation782.19922
Coefficient of variation (CV)0.003798095
Kurtosis1.434762
Mean205945.14
Median Absolute Deviation (MAD)610.7685
Skewness0.53076156
Sum8.4767021 × 108
Variance611835.62
MonotonicityNot monotonic
2024-05-11T04:04:02.224101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205320.28476675 311
 
7.3%
205994.811815848 99
 
2.3%
205391.070378059 88
 
2.1%
205931.05327036 72
 
1.7%
205645.891969072 58
 
1.4%
205985.953324881 51
 
1.2%
206204.445134058 39
 
0.9%
206132.432496938 35
 
0.8%
206981.454072644 30
 
0.7%
205601.926027171 26
 
0.6%
Other values (1468) 3307
78.1%
(Missing) 120
 
2.8%
ValueCountFrequency (%)
203721.865206618 1
 
< 0.1%
203762.973030298 2
 
< 0.1%
203809.293429767 1
 
< 0.1%
203847.028134453 1
 
< 0.1%
203904.660962669 1
 
< 0.1%
203986.825383903 2
 
< 0.1%
204325.989587591 19
0.4%
204336.148709778 1
 
< 0.1%
204360.413814457 2
 
< 0.1%
204376.414367095 3
 
0.1%
ValueCountFrequency (%)
212913.03183815 1
 
< 0.1%
209288.472624641 6
0.1%
209275.59582305 1
 
< 0.1%
209234.634090964 1
 
< 0.1%
209221.801973277 1
 
< 0.1%
208532.777004106 2
 
< 0.1%
208258.296165225 2
 
< 0.1%
208233.736645124 1
 
< 0.1%
208223.756335908 1
 
< 0.1%
208149.544920696 2
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1477
Distinct (%)35.9%
Missing120
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean460371.53
Minimum437739.6
Maximum465103.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.4 KiB
2024-05-11T04:04:02.582454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum437739.6
5-th percentile457448.88
Q1458452.73
median460830.62
Q3461626.35
95-th percentile463334.27
Maximum465103.76
Range27364.152
Interquartile range (IQR)3173.618

Descriptive statistics

Standard deviation1894.489
Coefficient of variation (CV)0.0041151306
Kurtosis3.8242226
Mean460371.53
Median Absolute Deviation (MAD)1287.8026
Skewness-0.5003417
Sum1.8948892 × 109
Variance3589088.5
MonotonicityNot monotonic
2024-05-11T04:04:02.954277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
461419.881795004 311
 
7.3%
459502.645279682 99
 
2.3%
458333.989216339 88
 
2.1%
459884.197207567 72
 
1.7%
459609.012509743 58
 
1.4%
459730.43776924 51
 
1.2%
460466.440748874 39
 
0.9%
460549.311157153 35
 
0.8%
458960.471391303 30
 
0.7%
459732.128595514 26
 
0.6%
Other values (1467) 3307
78.1%
(Missing) 120
 
2.8%
ValueCountFrequency (%)
437739.603474009 1
 
< 0.1%
456954.147370611 6
0.1%
456975.436848678 2
 
< 0.1%
456990.07335337 5
0.1%
456994.517426262 4
0.1%
456996.048176249 4
0.1%
456996.92645734 1
 
< 0.1%
457008.271220657 1
 
< 0.1%
457018.943974424 1
 
< 0.1%
457023.41378919 1
 
< 0.1%
ValueCountFrequency (%)
465103.755134816 1
 
< 0.1%
464964.284423079 3
 
0.1%
464959.058464501 1
 
< 0.1%
464947.624877034 1
 
< 0.1%
464922.213107238 1
 
< 0.1%
464920.0 1
 
< 0.1%
464508.952781941 2
 
< 0.1%
464356.527197506 2
 
< 0.1%
464346.663669239 4
0.1%
464208.305428933 9
0.2%

위생업태명
Categorical

Distinct16
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size33.2 KiB
<NA>
1014 
커피숍
693 
기타 휴게음식점
653 
일반조리판매
612 
다방
291 
Other values (11)
973 

Length

Max length8
Median length6
Mean length4.516525
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row다방
2nd row다방
3rd row과자점
4th row다방
5th row다방

Common Values

ValueCountFrequency (%)
<NA> 1014
23.9%
커피숍 693
16.4%
기타 휴게음식점 653
15.4%
일반조리판매 612
14.4%
다방 291
 
6.9%
과자점 281
 
6.6%
패스트푸드 257
 
6.1%
편의점 236
 
5.6%
백화점 137
 
3.2%
아이스크림 25
 
0.6%
Other values (6) 37
 
0.9%

Length

2024-05-11T04:04:03.377506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1014
20.7%
커피숍 693
14.2%
기타 653
13.4%
휴게음식점 653
13.4%
일반조리판매 612
12.5%
다방 291
 
6.0%
과자점 281
 
5.7%
패스트푸드 257
 
5.3%
편의점 236
 
4.8%
백화점 137
 
2.8%
Other values (7) 62
 
1.3%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.6%
Missing3269
Missing (%)77.2%
Infinite0
Infinite (%)0.0%
Mean0.10444674
Minimum0
Maximum5
Zeros887
Zeros (%)20.9%
Negative0
Negative (%)0.0%
Memory size37.4 KiB
2024-05-11T04:04:03.756989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.39985877
Coefficient of variation (CV)3.8283508
Kurtosis42.502249
Mean0.10444674
Median Absolute Deviation (MAD)0
Skewness5.5086494
Sum101
Variance0.15988704
MonotonicityNot monotonic
2024-05-11T04:04:04.154250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 887
 
20.9%
1 66
 
1.6%
2 10
 
0.2%
3 2
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
(Missing) 3269
77.2%
ValueCountFrequency (%)
0 887
20.9%
1 66
 
1.6%
2 10
 
0.2%
3 2
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
5 1
 
< 0.1%
4 1
 
< 0.1%
3 2
 
< 0.1%
2 10
 
0.2%
1 66
 
1.6%
0 887
20.9%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.6%
Missing3271
Missing (%)77.2%
Infinite0
Infinite (%)0.0%
Mean0.40310881
Minimum0
Maximum5
Zeros766
Zeros (%)18.1%
Negative0
Negative (%)0.0%
Memory size37.4 KiB
2024-05-11T04:04:04.527035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.8809832
Coefficient of variation (CV)2.1854725
Kurtosis3.5748791
Mean0.40310881
Median Absolute Deviation (MAD)0
Skewness2.1481161
Sum389
Variance0.7761314
MonotonicityNot monotonic
2024-05-11T04:04:04.916903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 766
 
18.1%
1 72
 
1.7%
2 68
 
1.6%
3 56
 
1.3%
4 2
 
< 0.1%
5 1
 
< 0.1%
(Missing) 3271
77.2%
ValueCountFrequency (%)
0 766
18.1%
1 72
 
1.7%
2 68
 
1.6%
3 56
 
1.3%
4 2
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
5 1
 
< 0.1%
4 2
 
< 0.1%
3 56
 
1.3%
2 68
 
1.6%
1 72
 
1.7%
0 766
18.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size33.2 KiB
<NA>
3395 
주택가주변
412 
아파트지역
 
240
기타
 
132
유흥업소밀집지역
 
53
Other values (2)
 
4

Length

Max length8
Median length4
Mean length4.1449481
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3395
80.1%
주택가주변 412
 
9.7%
아파트지역 240
 
5.7%
기타 132
 
3.1%
유흥업소밀집지역 53
 
1.3%
학교정화(상대) 2
 
< 0.1%
결혼예식장주변 2
 
< 0.1%

Length

2024-05-11T04:04:05.513860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:06.058960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3395
80.1%
주택가주변 412
 
9.7%
아파트지역 240
 
5.7%
기타 132
 
3.1%
유흥업소밀집지역 53
 
1.3%
학교정화(상대 2
 
< 0.1%
결혼예식장주변 2
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size33.2 KiB
<NA>
3404 
448 
자율
 
166
기타
 
105
 
53
Other values (3)
 
60

Length

Max length4
Median length4
Mean length3.4889046
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row
2nd row
3rd row
4th row
5th row지도

Common Values

ValueCountFrequency (%)
<NA> 3404
80.4%
448
 
10.6%
자율 166
 
3.9%
기타 105
 
2.5%
53
 
1.3%
지도 49
 
1.2%
우수 10
 
0.2%
관리 1
 
< 0.1%

Length

2024-05-11T04:04:06.564350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:07.031483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3404
80.4%
448
 
10.6%
자율 166
 
3.9%
기타 105
 
2.5%
53
 
1.3%
지도 49
 
1.2%
우수 10
 
0.2%
관리 1
 
< 0.1%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size33.2 KiB
<NA>
2893 
상수도전용
1341 
상수도(음용)지하수(주방용)겸용
 
2

Length

Max length17
Median length4
Mean length4.3227101
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2893
68.3%
상수도전용 1341
31.7%
상수도(음용)지하수(주방용)겸용 2
 
< 0.1%

Length

2024-05-11T04:04:07.427166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:07.803849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2893
68.3%
상수도전용 1341
31.7%
상수도(음용)지하수(주방용)겸용 2
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.2 KiB
<NA>
4050 
0
 
186

Length

Max length4
Median length4
Mean length3.868272
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> 4050
95.6%
0 186
 
4.4%

Length

2024-05-11T04:04:08.181740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:08.522050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4050
95.6%
0 186
 
4.4%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.2 KiB
<NA>
4042 
0
 
194

Length

Max length4
Median length4
Mean length3.8626062
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> 4042
95.4%
0 194
 
4.6%

Length

2024-05-11T04:04:09.037015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:09.404654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4042
95.4%
0 194
 
4.6%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.2 KiB
<NA>
4042 
0
 
194

Length

Max length4
Median length4
Mean length3.8626062
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> 4042
95.4%
0 194
 
4.6%

Length

2024-05-11T04:04:10.004370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:10.497546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4042
95.4%
0 194
 
4.6%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.2 KiB
<NA>
4042 
0
 
194

Length

Max length4
Median length4
Mean length3.8626062
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> 4042
95.4%
0 194
 
4.6%

Length

2024-05-11T04:04:11.104327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:11.669422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4042
95.4%
0 194
 
4.6%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.2 KiB
<NA>
4042 
0
 
194

Length

Max length4
Median length4
Mean length3.8626062
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> 4042
95.4%
0 194
 
4.6%

Length

2024-05-11T04:04:12.124011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:12.599254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4042
95.4%
0 194
 
4.6%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4236
Missing (%)100.0%
Memory size37.4 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.2 KiB
<NA>
4042 
0
 
194

Length

Max length4
Median length4
Mean length3.8626062
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> 4042
95.4%
0 194
 
4.6%

Length

2024-05-11T04:04:13.139385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:13.558461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4042
95.4%
0 194
 
4.6%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.2 KiB
<NA>
4042 
0
 
194

Length

Max length4
Median length4
Mean length3.8626062
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> 4042
95.4%
0 194
 
4.6%

Length

2024-05-11T04:04:14.070894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:14.442485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4042
95.4%
0 194
 
4.6%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing1014
Missing (%)23.9%
Memory size8.4 KiB
False
3187 
True
 
35
(Missing)
1014 
ValueCountFrequency (%)
False 3187
75.2%
True 35
 
0.8%
(Missing) 1014
 
23.9%
2024-05-11T04:04:14.698297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct1629
Distinct (%)50.6%
Missing1014
Missing (%)23.9%
Infinite0
Infinite (%)0.0%
Mean37.263079
Minimum0
Maximum965
Zeros77
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size37.4 KiB
2024-05-11T04:04:15.101728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q110.9
median24
Q343.29
95-th percentile115.325
Maximum965
Range965
Interquartile range (IQR)32.39

Descriptive statistics

Standard deviation47.745065
Coefficient of variation (CV)1.2812968
Kurtosis63.021666
Mean37.263079
Median Absolute Deviation (MAD)14.165
Skewness5.4426503
Sum120061.64
Variance2279.5912
MonotonicityNot monotonic
2024-05-11T04:04:15.607436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 132
 
3.1%
6.6 97
 
2.3%
0.0 77
 
1.8%
10.0 51
 
1.2%
9.9 51
 
1.2%
30.0 44
 
1.0%
33.0 37
 
0.9%
6.0 36
 
0.8%
13.2 27
 
0.6%
16.5 27
 
0.6%
Other values (1619) 2643
62.4%
(Missing) 1014
 
23.9%
ValueCountFrequency (%)
0.0 77
1.8%
1.0 1
 
< 0.1%
1.49 1
 
< 0.1%
1.5 2
 
< 0.1%
1.68 2
 
< 0.1%
1.87 1
 
< 0.1%
1.95 2
 
< 0.1%
2.0 2
 
< 0.1%
2.08 1
 
< 0.1%
2.2 2
 
< 0.1%
ValueCountFrequency (%)
965.0 1
< 0.1%
610.9 1
< 0.1%
470.47 1
< 0.1%
469.4 1
< 0.1%
444.5 1
< 0.1%
405.03 1
< 0.1%
400.0 1
< 0.1%
384.66 1
< 0.1%
339.53 1
< 0.1%
337.7 1
< 0.1%

전통업소지정번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.2 KiB
<NA>
4235 
59.33
 
1

Length

Max length5
Median length4
Mean length4.0002361
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 (%)
<NA> 4235
> 99.9%
59.33 1
 
< 0.1%

Length

2024-05-11T04:04:16.156255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:16.655653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4235
> 99.9%
59.33 1
 
< 0.1%

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4236
Missing (%)100.0%
Memory size37.4 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4236
Missing (%)100.0%
Memory size37.4 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031000003100000-104-1973-0542919730907<NA>3폐업2폐업19990807<NA><NA><NA>02 936669883.44139810서울특별시 노원구 상계동 101-9번지<NA><NA>2001-09-29 00:00:00I2018-08-31 23:59:59.0다방206829.557809462716.28223다방02주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N83.44<NA><NA><NA>
131000003100000-104-1974-0540619740924<NA>3폐업2폐업19990820<NA><NA><NA>02 9722217145.85139808서울특별시 노원구 공릉동 661-1번지<NA><NA>황해1999-09-15 00:00:00I2018-08-31 23:59:59.0다방206750.451392457401.979786다방02주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N145.85<NA><NA><NA>
231000003100000-104-1978-0520219781226<NA>3폐업2폐업20001211<NA><NA><NA>02 972889349.49139240서울특별시 노원구 공릉동 517-31번지<NA><NA>쎌레스테2000-12-14 00:00:00I2018-08-31 23:59:59.0과자점206469.596994457893.222455과자점11주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N49.49<NA><NA><NA>
331000003100000-104-1978-0541319781020<NA>3폐업2폐업20070516<NA><NA><NA>02 9729433152.63139240서울특별시 노원구 공릉동 517-31번지<NA><NA>길다방2006-03-06 00:00:00I2018-08-31 23:59:59.0다방206469.596994457893.222455다방03주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N152.63<NA><NA><NA>
431000003100000-104-1979-0537619790511<NA>3폐업2폐업19940629<NA><NA><NA>020972201643.15139808서울특별시 노원구 공릉동 661-4번지<NA><NA>우성1999-05-27 00:00:00I2018-08-31 23:59:59.0다방206760.872046457359.441329다방02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N43.15<NA><NA><NA>
531000003100000-104-1980-0519719800715<NA>3폐업2폐업20000517<NA><NA><NA>02 972648240.22139810서울특별시 노원구 상계동 95-62번지<NA><NA>독일제과2000-05-30 00:00:00I2018-08-31 23:59:59.0과자점206792.913617462586.351705과자점11주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N40.22<NA><NA><NA>
631000003100000-104-1980-0542319801231<NA>3폐업2폐업20071127<NA><NA><NA>02 936002299.78139810서울특별시 노원구 상계동 82-7번지<NA><NA>아리랑커피숍2006-04-20 00:00:00I2018-08-31 23:59:59.0다방206669.15737462444.357932다방02주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N99.78<NA><NA><NA>
731000003100000-104-1980-0542619800421<NA>3폐업2폐업20020611<NA><NA><NA>02 972591189.45139810서울특별시 노원구 상계동 95-256번지<NA><NA>상록수1999-05-27 00:00:00I2018-08-31 23:59:59.0다방206807.037677462604.909285다방03주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N89.45<NA><NA><NA>
831000003100000-104-1981-0516919810416<NA>3폐업2폐업20030619<NA><NA><NA>02 973507450.4139240서울특별시 노원구 공릉동 597-17번지<NA><NA>벨가??베이커리2001-07-14 00:00:00I2018-08-31 23:59:59.0과자점206508.572524457512.040697과자점00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N50.4<NA><NA><NA>
931000003100000-104-1981-0539019810519<NA>3폐업2폐업20011009<NA><NA><NA>02 972058163.38139840서울특별시 노원구 월계동 26-18번지<NA><NA>정다방2001-10-10 00:00:00I2018-08-31 23:59:59.0다방205845.312152457018.943974다방03기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N63.38<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
422631000003100000-104-2024-000792024-04-25<NA>3폐업2폐업2024-04-28<NA><NA><NA>070 88895191<NA>139-220서울특별시 노원구 중계동 산 95-2 불암산 산림치유센터서울특별시 노원구 한글비석로12길 51-80, 불암산 산림치유센터 (중계동)1721청소년카페 마니또2024-05-02 04:15:10I2023-12-05 00:04:00.0기타 휴게음식점207104.641341461323.060857<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
422731000003100000-104-2024-000802024-05-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.0139-831서울특별시 노원구 상계동 764-1 하라프라자센타서울특별시 노원구 동일로 1323, 하라프라자센타 1층 103-5호 (상계동)1767위아원카페_메고지고 중계위너2024-05-01 15:36:46I2023-12-05 00:03:00.0커피숍205457.289886460487.443376<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
422831000003100000-104-2024-000812024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>5.0139-816서울특별시 노원구 상계동 323-22 신영빌딩 앞 도로변(노해로)서울특별시 노원구 노해로 511, 앞 도로변(노해로) (상계동)1695인생꽈배기달인2024-05-02 11:02:24I2023-12-05 00:04:00.0푸드트럭205642.632672461455.476885<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
422931000003100000-104-2024-000822024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>16.0139-842서울특별시 노원구 월계동 333-1 월계이마트 1층 일부호서울특별시 노원구 마들로3길 15, 월계이마트 1층 일부호 (월계동)1906(주)사조씨푸드(월계점)2024-05-03 09:25:52I2023-12-05 00:05:00.0일반조리판매205391.070378458333.989216<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
423031000003100000-104-2024-000832024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139-726서울특별시 노원구 중계동 509 2001아울렛서울특별시 노원구 동일로204가길 46, 2001아울렛 지하1층 (중계동)1783(주)에벤에셀2024-05-03 13:20:14I2023-12-05 00:05:00.0기타 휴게음식점205931.05327459884.197208<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
423131000003100000-104-2024-000842024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139-240서울특별시 노원구 공릉동 389-9 화랑빌딩서울특별시 노원구 동일로192길 63, 인근 축제장 (공릉동)1841포멜로우2024-05-07 11:34:06I2023-12-05 00:09:00.0기타 휴게음식점206659.512758458320.51828<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
423231000003100000-104-2024-000852024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139-240서울특별시 노원구 공릉동 389-9 화랑빌딩서울특별시 노원구 동일로192길 63, 인근 축제장 (공릉동)1841베이킹덕2024-05-07 11:37:14I2023-12-05 00:09:00.0기타 휴게음식점206659.512758458320.51828<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
423331000003100000-104-2024-000862024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139-240서울특별시 노원구 공릉동 389-9 인근 축제장서울특별시 노원구 동일로192길 63, 인근 축제장 (공릉동)1841카페콩투어(CAFE KONGTOUR)2024-05-07 11:41:49I2023-12-05 00:09:00.0커피숍206659.512758458320.51828<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
423431000003100000-104-2024-000872024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139-240서울특별시 노원구 공릉동 389-9 인근 축제장서울특별시 노원구 동일로192길 63, 인근 축제장 (공릉동)1841아너(Honor)2024-05-08 10:47:13I2023-12-04 23:00:00.0커피숍206659.512758458320.51828<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
423531000003100000-104-2024-000882024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139-240서울특별시 노원구 공릉동 389-9 인근 축제장서울특별시 노원구 동일로192길 63, 인근 축제장 (공릉동)1841카페모남2024-05-09 09:25:48I2023-12-04 23:01:00.0커피숍206659.512758458320.51828<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>