Overview

Dataset statistics

Number of variables44
Number of observations247
Missing cells2658
Missing cells (%)24.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory90.8 KiB
Average record size in memory376.5 B

Variable types

Categorical18
Text6
DateTime4
Unsupported7
Numeric8
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
Author성북구
URLhttps://data.seoul.go.kr/dataList/OA-18259/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (53.4%)Imbalance
남성종사자수 is highly imbalanced (59.7%)Imbalance
여성종사자수 is highly imbalanced (60.8%)Imbalance
영업장주변구분명 is highly imbalanced (51.5%)Imbalance
등급구분명 is highly imbalanced (62.0%)Imbalance
총인원 is highly imbalanced (83.5%)Imbalance
본사종업원수 is highly imbalanced (53.8%)Imbalance
인허가취소일자 has 247 (100.0%) missing valuesMissing
폐업일자 has 42 (17.0%) missing valuesMissing
휴업시작일자 has 247 (100.0%) missing valuesMissing
휴업종료일자 has 247 (100.0%) missing valuesMissing
재개업일자 has 247 (100.0%) missing valuesMissing
전화번호 has 66 (26.7%) missing valuesMissing
소재지면적 has 4 (1.6%) missing valuesMissing
도로명주소 has 114 (46.2%) missing valuesMissing
도로명우편번호 has 116 (47.0%) missing valuesMissing
좌표정보(X) has 14 (5.7%) missing valuesMissing
좌표정보(Y) has 14 (5.7%) missing valuesMissing
공장생산직종업원수 has 72 (29.1%) missing valuesMissing
보증액 has 217 (87.9%) missing valuesMissing
월세액 has 218 (88.3%) missing valuesMissing
다중이용업소여부 has 26 (10.5%) missing valuesMissing
시설총규모 has 26 (10.5%) missing valuesMissing
전통업소지정번호 has 247 (100.0%) missing valuesMissing
전통업소주된음식 has 247 (100.0%) missing valuesMissing
홈페이지 has 247 (100.0%) missing valuesMissing
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
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
공장생산직종업원수 has 141 (57.1%) zerosZeros
보증액 has 21 (8.5%) zerosZeros
월세액 has 21 (8.5%) zerosZeros
시설총규모 has 200 (81.0%) zerosZeros

Reproduction

Analysis started2024-05-11 06:09:26.339772
Analysis finished2024-05-11 06:09:27.391574
Duration1.05 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
3070000
247 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3070000
2nd row3070000
3rd row3070000
4th row3070000
5th row3070000

Common Values

ValueCountFrequency (%)
3070000 247
100.0%

Length

2024-05-11T15:09:27.498236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:27.672419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3070000 247
100.0%

관리번호
Text

UNIQUE 

Distinct247
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-05-11T15:09:27.951253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters5434
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

Unique247 ?
Unique (%)100.0%

Sample

1st row3070000-106-1963-00020
2nd row3070000-106-1973-00040
3rd row3070000-106-1976-00014
4th row3070000-106-1983-00038
5th row3070000-106-1986-00012
ValueCountFrequency (%)
3070000-106-1963-00020 1
 
0.4%
3070000-106-2014-00003 1
 
0.4%
3070000-106-2012-00001 1
 
0.4%
3070000-106-2012-00002 1
 
0.4%
3070000-106-2012-00003 1
 
0.4%
3070000-106-2012-00004 1
 
0.4%
3070000-106-2012-00005 1
 
0.4%
3070000-106-2012-00006 1
 
0.4%
3070000-106-2012-00007 1
 
0.4%
3070000-106-2012-00008 1
 
0.4%
Other values (237) 237
96.0%
2024-05-11T15:09:28.400591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2712
49.9%
- 741
 
13.6%
1 498
 
9.2%
3 321
 
5.9%
7 308
 
5.7%
2 298
 
5.5%
6 297
 
5.5%
9 107
 
2.0%
4 56
 
1.0%
8 49
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4693
86.4%
Dash Punctuation 741
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2712
57.8%
1 498
 
10.6%
3 321
 
6.8%
7 308
 
6.6%
2 298
 
6.3%
6 297
 
6.3%
9 107
 
2.3%
4 56
 
1.2%
8 49
 
1.0%
5 47
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 741
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5434
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2712
49.9%
- 741
 
13.6%
1 498
 
9.2%
3 321
 
5.9%
7 308
 
5.7%
2 298
 
5.5%
6 297
 
5.5%
9 107
 
2.0%
4 56
 
1.0%
8 49
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5434
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2712
49.9%
- 741
 
13.6%
1 498
 
9.2%
3 321
 
5.9%
7 308
 
5.7%
2 298
 
5.5%
6 297
 
5.5%
9 107
 
2.0%
4 56
 
1.0%
8 49
 
0.9%

인허가일자
Date

Distinct243
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum1963-02-12 00:00:00
Maximum2024-03-14 00:00:00
2024-05-11T15:09:28.584600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:09:28.792687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing247
Missing (%)100.0%
Memory size2.3 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
3
205 
1
42 

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 (%)
3 205
83.0%
1 42
 
17.0%

Length

2024-05-11T15:09:28.992935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:29.123930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 205
83.0%
1 42
 
17.0%

영업상태명
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
폐업
205 
영업/정상
42 

Length

Max length5
Median length2
Mean length2.5101215
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 205
83.0%
영업/정상 42
 
17.0%

Length

2024-05-11T15:09:29.302205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:29.451824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 205
83.0%
영업/정상 42
 
17.0%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2
205 
1
42 

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 (%)
2 205
83.0%
1 42
 
17.0%

Length

2024-05-11T15:09:29.608472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:29.803414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 205
83.0%
1 42
 
17.0%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
폐업
205 
영업
42 

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 205
83.0%
영업 42
 
17.0%

Length

2024-05-11T15:09:29.953227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:30.125015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 205
83.0%
영업 42
 
17.0%

폐업일자
Date

MISSING 

Distinct194
Distinct (%)94.6%
Missing42
Missing (%)17.0%
Memory size2.1 KiB
Minimum2000-04-04 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T15:09:30.275192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:09:30.790772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing247
Missing (%)100.0%
Memory size2.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing247
Missing (%)100.0%
Memory size2.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing247
Missing (%)100.0%
Memory size2.3 KiB

전화번호
Text

MISSING 

Distinct174
Distinct (%)96.1%
Missing66
Missing (%)26.7%
Memory size2.1 KiB
2024-05-11T15:09:31.113428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10
Min length7

Characters and Unicode

Total characters1810
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

Unique168 ?
Unique (%)92.8%

Sample

1st row02 9125374
2nd row02 9136388
3rd row02 9233933
4th row02 9120349
5th row9168235
ValueCountFrequency (%)
02 139
41.7%
9186082 3
 
0.9%
070 3
 
0.9%
744 2
 
0.6%
9428438 2
 
0.6%
9431446 2
 
0.6%
7442266 2
 
0.6%
2266 2
 
0.6%
9125374 2
 
0.6%
9131137 1
 
0.3%
Other values (175) 175
52.6%
2024-05-11T15:09:31.641328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 312
17.2%
0 272
15.0%
9 212
11.7%
162
9.0%
1 146
8.1%
4 140
7.7%
6 122
 
6.7%
7 114
 
6.3%
8 113
 
6.2%
3 111
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1648
91.0%
Space Separator 162
 
9.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 312
18.9%
0 272
16.5%
9 212
12.9%
1 146
8.9%
4 140
8.5%
6 122
 
7.4%
7 114
 
6.9%
8 113
 
6.9%
3 111
 
6.7%
5 106
 
6.4%
Space Separator
ValueCountFrequency (%)
162
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1810
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 312
17.2%
0 272
15.0%
9 212
11.7%
162
9.0%
1 146
8.1%
4 140
7.7%
6 122
 
6.7%
7 114
 
6.3%
8 113
 
6.2%
3 111
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1810
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 312
17.2%
0 272
15.0%
9 212
11.7%
162
9.0%
1 146
8.1%
4 140
7.7%
6 122
 
6.7%
7 114
 
6.3%
8 113
 
6.2%
3 111
 
6.1%

소재지면적
Real number (ℝ)

MISSING 

Distinct226
Distinct (%)93.0%
Missing4
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean74.707037
Minimum4.55
Maximum749.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T15:09:31.896528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.55
5-th percentile11.325
Q129.56
median48.4
Q392.675
95-th percentile196.288
Maximum749.1
Range744.55
Interquartile range (IQR)63.115

Descriptive statistics

Standard deviation85.430782
Coefficient of variation (CV)1.143544
Kurtosis30.172288
Mean74.707037
Median Absolute Deviation (MAD)25.69
Skewness4.4855089
Sum18153.81
Variance7298.4185
MonotonicityNot monotonic
2024-05-11T15:09:32.229546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40.0 3
 
1.2%
117.38 3
 
1.2%
23.4 2
 
0.8%
30.0 2
 
0.8%
45.8 2
 
0.8%
61.7 2
 
0.8%
14.0 2
 
0.8%
90.0 2
 
0.8%
7.0 2
 
0.8%
29.7 2
 
0.8%
Other values (216) 221
89.5%
(Missing) 4
 
1.6%
ValueCountFrequency (%)
4.55 1
0.4%
6.12 1
0.4%
6.25 1
0.4%
7.0 2
0.8%
7.2 1
0.4%
7.72 1
0.4%
8.62 1
0.4%
8.9 1
0.4%
9.1 1
0.4%
10.5 1
0.4%
ValueCountFrequency (%)
749.1 1
0.4%
739.35 1
0.4%
297.0 1
0.4%
292.79 1
0.4%
270.74 1
0.4%
270.2 1
0.4%
269.74 1
0.4%
265.37 1
0.4%
250.0 1
0.4%
234.8 1
0.4%

소재지우편번호
Text

Distinct90
Distinct (%)36.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-05-11T15:09:32.693306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0607287
Min length6

Characters and Unicode

Total characters1497
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

Unique41 ?
Unique (%)16.6%

Sample

1st row136865
2nd row136865
3rd row136035
4th row136864
5th row136865
ValueCountFrequency (%)
136865 19
 
7.7%
136858 14
 
5.7%
136849 9
 
3.6%
136075 9
 
3.6%
136817 8
 
3.2%
136836 8
 
3.2%
136060 6
 
2.4%
136856 6
 
2.4%
136832 6
 
2.4%
136827 5
 
2.0%
Other values (80) 157
63.6%
2024-05-11T15:09:33.331188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 312
20.8%
3 310
20.7%
1 309
20.6%
8 201
13.4%
0 116
 
7.7%
5 81
 
5.4%
2 50
 
3.3%
4 43
 
2.9%
7 43
 
2.9%
9 17
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1482
99.0%
Dash Punctuation 15
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 312
21.1%
3 310
20.9%
1 309
20.9%
8 201
13.6%
0 116
 
7.8%
5 81
 
5.5%
2 50
 
3.4%
4 43
 
2.9%
7 43
 
2.9%
9 17
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1497
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 312
20.8%
3 310
20.7%
1 309
20.6%
8 201
13.4%
0 116
 
7.7%
5 81
 
5.4%
2 50
 
3.3%
4 43
 
2.9%
7 43
 
2.9%
9 17
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1497
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 312
20.8%
3 310
20.7%
1 309
20.6%
8 201
13.4%
0 116
 
7.7%
5 81
 
5.4%
2 50
 
3.3%
4 43
 
2.9%
7 43
 
2.9%
9 17
 
1.1%

지번주소
Text

Distinct238
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-05-11T15:09:33.847816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length43
Mean length25.530364
Min length17

Characters and Unicode

Total characters6306
Distinct characters125
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique230 ?
Unique (%)93.1%

Sample

1st row서울특별시 성북구 하월곡동 33-46번지
2nd row서울특별시 성북구 하월곡동 53-13번지
3rd row서울특별시 성북구 동소문동5가 55-33번지
4th row서울특별시 성북구 종암동 3-996번지
5th row서울특별시 성북구 하월곡동 59-2번지
ValueCountFrequency (%)
서울특별시 247
21.5%
성북구 247
21.5%
장위동 37
 
3.2%
하월곡동 36
 
3.1%
정릉동 33
 
2.9%
석관동 30
 
2.6%
종암동 23
 
2.0%
지상1층 22
 
1.9%
길음동 14
 
1.2%
지하1층 14
 
1.2%
Other values (335) 447
38.9%
2024-05-11T15:09:34.715378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1106
 
17.5%
1 288
 
4.6%
동 288
 
4.6%
성 266
 
4.2%
북 263
 
4.2%
지 258
 
4.1%
구 249
 
3.9%
서 248
 
3.9%
시 248
 
3.9%
특 247
 
3.9%
Other values (115) 2845
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3685
58.4%
Decimal Number 1228
 
19.5%
Space Separator 1106
 
17.5%
Dash Punctuation 206
 
3.3%
Close Punctuation 28
 
0.4%
Open Punctuation 28
 
0.4%
Other Punctuation 14
 
0.2%
Uppercase Letter 10
 
0.2%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 288
 
7.8%
성 266
 
7.2%
북 263
 
7.1%
지 258
 
7.0%
구 249
 
6.8%
서 248
 
6.7%
시 248
 
6.7%
특 247
 
6.7%
울 247
 
6.7%
별 247
 
6.7%
Other values (92) 1124
30.5%
Decimal Number
ValueCountFrequency (%)
1 288
23.5%
2 171
13.9%
3 164
13.4%
0 107
 
8.7%
5 105
 
8.6%
4 94
 
7.7%
6 81
 
6.6%
9 75
 
6.1%
7 73
 
5.9%
8 70
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
B 5
50.0%
D 2
 
20.0%
A 1
 
10.0%
P 1
 
10.0%
T 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 11
78.6%
@ 2
 
14.3%
/ 1
 
7.1%
Space Separator
ValueCountFrequency (%)
1106
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 206
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3685
58.4%
Common 2610
41.4%
Latin 11
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 288
 
7.8%
성 266
 
7.2%
북 263
 
7.1%
지 258
 
7.0%
구 249
 
6.8%
서 248
 
6.7%
시 248
 
6.7%
특 247
 
6.7%
울 247
 
6.7%
별 247
 
6.7%
Other values (92) 1124
30.5%
Common
ValueCountFrequency (%)
1106
42.4%
1 288
 
11.0%
- 206
 
7.9%
2 171
 
6.6%
3 164
 
6.3%
0 107
 
4.1%
5 105
 
4.0%
4 94
 
3.6%
6 81
 
3.1%
9 75
 
2.9%
Other values (7) 213
 
8.2%
Latin
ValueCountFrequency (%)
B 5
45.5%
D 2
 
18.2%
e 1
 
9.1%
A 1
 
9.1%
P 1
 
9.1%
T 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3685
58.4%
ASCII 2621
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1106
42.2%
1 288
 
11.0%
- 206
 
7.9%
2 171
 
6.5%
3 164
 
6.3%
0 107
 
4.1%
5 105
 
4.0%
4 94
 
3.6%
6 81
 
3.1%
9 75
 
2.9%
Other values (13) 224
 
8.5%
Hangul
ValueCountFrequency (%)
동 288
 
7.8%
성 266
 
7.2%
북 263
 
7.1%
지 258
 
7.0%
구 249
 
6.8%
서 248
 
6.7%
시 248
 
6.7%
특 247
 
6.7%
울 247
 
6.7%
별 247
 
6.7%
Other values (92) 1124
30.5%

도로명주소
Text

MISSING 

Distinct131
Distinct (%)98.5%
Missing114
Missing (%)46.2%
Memory size2.1 KiB
2024-05-11T15:09:35.262149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length44
Mean length33.578947
Min length23

Characters and Unicode

Total characters4466
Distinct characters136
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

Unique129 ?
Unique (%)97.0%

Sample

1st row서울특별시 성북구 화랑로1길 54, 지상1층 (하월곡동)
2nd row서울특별시 성북구 종암로28길 9, 지상1,2층 (종암동, 및 종암로28길 11)
3rd row서울특별시 성북구 동소문로 86-15, 지하1층 (동소문동5가)
4th row서울특별시 성북구 보국문로18가길 29 (정릉동)
5th row서울특별시 성북구 오패산로3길 36-12 (하월곡동,(지상1층, 지하1층))
ValueCountFrequency (%)
서울특별시 133
 
15.5%
성북구 133
 
15.5%
지상1층 35
 
4.1%
1층 24
 
2.8%
정릉동 24
 
2.8%
지하1층 23
 
2.7%
장위동 16
 
1.9%
하월곡동 15
 
1.8%
석관동 13
 
1.5%
상가동 11
 
1.3%
Other values (263) 429
50.1%
2024-05-11T15:09:36.028852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
723
 
16.2%
1 224
 
5.0%
동 167
 
3.7%
, 163
 
3.6%
성 157
 
3.5%
북 156
 
3.5%
) 141
 
3.2%
( 141
 
3.2%
서 135
 
3.0%
시 134
 
3.0%
Other values (126) 2325
52.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2583
57.8%
Space Separator 723
 
16.2%
Decimal Number 688
 
15.4%
Other Punctuation 163
 
3.6%
Close Punctuation 141
 
3.2%
Open Punctuation 141
 
3.2%
Dash Punctuation 23
 
0.5%
Uppercase Letter 2
 
< 0.1%
Math Symbol 1
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 167
 
6.5%
성 157
 
6.1%
북 156
 
6.0%
서 135
 
5.2%
시 134
 
5.2%
구 133
 
5.1%
특 133
 
5.1%
별 133
 
5.1%
울 133
 
5.1%
로 131
 
5.1%
Other values (108) 1171
45.3%
Decimal Number
ValueCountFrequency (%)
1 224
32.6%
2 86
 
12.5%
3 60
 
8.7%
0 56
 
8.1%
5 55
 
8.0%
4 51
 
7.4%
6 50
 
7.3%
9 37
 
5.4%
7 35
 
5.1%
8 34
 
4.9%
Space Separator
ValueCountFrequency (%)
723
100.0%
Other Punctuation
ValueCountFrequency (%)
, 163
100.0%
Close Punctuation
ValueCountFrequency (%)
) 141
100.0%
Open Punctuation
ValueCountFrequency (%)
( 141
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2583
57.8%
Common 1880
42.1%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 167
 
6.5%
성 157
 
6.1%
북 156
 
6.0%
서 135
 
5.2%
시 134
 
5.2%
구 133
 
5.1%
특 133
 
5.1%
별 133
 
5.1%
울 133
 
5.1%
로 131
 
5.1%
Other values (108) 1171
45.3%
Common
ValueCountFrequency (%)
723
38.5%
1 224
 
11.9%
, 163
 
8.7%
) 141
 
7.5%
( 141
 
7.5%
2 86
 
4.6%
3 60
 
3.2%
0 56
 
3.0%
5 55
 
2.9%
4 51
 
2.7%
Other values (6) 180
 
9.6%
Latin
ValueCountFrequency (%)
B 2
66.7%
e 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2583
57.8%
ASCII 1883
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
723
38.4%
1 224
 
11.9%
, 163
 
8.7%
) 141
 
7.5%
( 141
 
7.5%
2 86
 
4.6%
3 60
 
3.2%
0 56
 
3.0%
5 55
 
2.9%
4 51
 
2.7%
Other values (8) 183
 
9.7%
Hangul
ValueCountFrequency (%)
동 167
 
6.5%
성 157
 
6.1%
북 156
 
6.0%
서 135
 
5.2%
시 134
 
5.2%
구 133
 
5.1%
특 133
 
5.1%
별 133
 
5.1%
울 133
 
5.1%
로 131
 
5.1%
Other values (108) 1171
45.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct79
Distinct (%)60.3%
Missing116
Missing (%)47.0%
Infinite0
Infinite (%)0.0%
Mean2785.6107
Minimum2701
Maximum2880
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T15:09:36.260253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2701
5-th percentile2711
Q12739.5
median2784
Q32828.5
95-th percentile2879.5
Maximum2880
Range179
Interquartile range (IQR)89

Descriptive statistics

Standard deviation51.791976
Coefficient of variation (CV)0.018592683
Kurtosis-1.0792223
Mean2785.6107
Median Absolute Deviation (MAD)45
Skewness0.1936626
Sum364915
Variance2682.4088
MonotonicityNot monotonic
2024-05-11T15:09:36.477248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2880 7
 
2.8%
2711 7
 
2.8%
2812 6
 
2.4%
2800 5
 
2.0%
2743 4
 
1.6%
2756 3
 
1.2%
2842 3
 
1.2%
2782 3
 
1.2%
2855 3
 
1.2%
2721 3
 
1.2%
Other values (69) 87
35.2%
(Missing) 116
47.0%
ValueCountFrequency (%)
2701 2
 
0.8%
2709 1
 
0.4%
2711 7
2.8%
2714 1
 
0.4%
2716 1
 
0.4%
2717 1
 
0.4%
2718 1
 
0.4%
2719 2
 
0.8%
2721 3
1.2%
2725 1
 
0.4%
ValueCountFrequency (%)
2880 7
2.8%
2879 1
 
0.4%
2873 1
 
0.4%
2864 1
 
0.4%
2862 2
 
0.8%
2861 1
 
0.4%
2859 1
 
0.4%
2855 3
1.2%
2850 1
 
0.4%
2848 1
 
0.4%

사업장명
Text

Distinct237
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-05-11T15:09:36.860290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length6.1214575
Min length2

Characters and Unicode

Total characters1512
Distinct characters354
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique227 ?
Unique (%)91.9%

Sample

1st row동보식품
2nd row태화식품
3rd row마산식품
4th row선일식품
5th row매일식품
ValueCountFrequency (%)
주식회사 9
 
3.2%
coffee 3
 
1.1%
동보식품 2
 
0.7%
국제유통 2
 
0.7%
부산형제식품 2
 
0.7%
이지산업 2
 
0.7%
우리농산 2
 
0.7%
주)왕부라더스 2
 
0.7%
우리식품 2
 
0.7%
신흥농산 2
 
0.7%
Other values (248) 250
89.9%
2024-05-11T15:09:37.539632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 81
 
5.4%
품 69
 
4.6%
( 44
 
2.9%
) 44
 
2.9%
주 36
 
2.4%
이 34
 
2.2%
31
 
2.1%
드 30
 
2.0%
스 28
 
1.9%
사 25
 
1.7%
Other values (344) 1090
72.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1265
83.7%
Lowercase Letter 82
 
5.4%
Open Punctuation 44
 
2.9%
Close Punctuation 44
 
2.9%
Uppercase Letter 35
 
2.3%
Space Separator 31
 
2.1%
Decimal Number 5
 
0.3%
Other Punctuation 4
 
0.3%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 81
 
6.4%
품 69
 
5.5%
주 36
 
2.8%
이 34
 
2.7%
드 30
 
2.4%
스 28
 
2.2%
사 25
 
2.0%
푸 23
 
1.8%
산 20
 
1.6%
리 20
 
1.6%
Other values (298) 899
71.1%
Lowercase Letter
ValueCountFrequency (%)
e 14
17.1%
o 11
13.4%
f 7
8.5%
s 6
7.3%
r 6
7.3%
a 6
7.3%
i 6
7.3%
m 5
 
6.1%
c 4
 
4.9%
k 3
 
3.7%
Other values (8) 14
17.1%
Uppercase Letter
ValueCountFrequency (%)
F 5
14.3%
M 3
8.6%
B 3
8.6%
N 3
8.6%
O 3
8.6%
D 3
8.6%
K 3
8.6%
L 2
 
5.7%
P 2
 
5.7%
S 2
 
5.7%
Other values (6) 6
17.1%
Decimal Number
ValueCountFrequency (%)
3 2
40.0%
2 1
20.0%
1 1
20.0%
4 1
20.0%
Other Punctuation
ValueCountFrequency (%)
& 1
25.0%
. 1
25.0%
/ 1
25.0%
' 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 44
100.0%
Close Punctuation
ValueCountFrequency (%)
) 44
100.0%
Space Separator
ValueCountFrequency (%)
31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1265
83.7%
Common 130
 
8.6%
Latin 117
 
7.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 81
 
6.4%
품 69
 
5.5%
주 36
 
2.8%
이 34
 
2.7%
드 30
 
2.4%
스 28
 
2.2%
사 25
 
2.0%
푸 23
 
1.8%
산 20
 
1.6%
리 20
 
1.6%
Other values (298) 899
71.1%
Latin
ValueCountFrequency (%)
e 14
 
12.0%
o 11
 
9.4%
f 7
 
6.0%
s 6
 
5.1%
r 6
 
5.1%
a 6
 
5.1%
i 6
 
5.1%
m 5
 
4.3%
F 5
 
4.3%
c 4
 
3.4%
Other values (24) 47
40.2%
Common
ValueCountFrequency (%)
( 44
33.8%
) 44
33.8%
31
23.8%
3 2
 
1.5%
- 2
 
1.5%
& 1
 
0.8%
. 1
 
0.8%
/ 1
 
0.8%
' 1
 
0.8%
2 1
 
0.8%
Other values (2) 2
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1265
83.7%
ASCII 247
 
16.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 81
 
6.4%
품 69
 
5.5%
주 36
 
2.8%
이 34
 
2.7%
드 30
 
2.4%
스 28
 
2.2%
사 25
 
2.0%
푸 23
 
1.8%
산 20
 
1.6%
리 20
 
1.6%
Other values (298) 899
71.1%
ASCII
ValueCountFrequency (%)
( 44
17.8%
) 44
17.8%
31
12.6%
e 14
 
5.7%
o 11
 
4.5%
f 7
 
2.8%
s 6
 
2.4%
r 6
 
2.4%
a 6
 
2.4%
i 6
 
2.4%
Other values (36) 72
29.1%

최종수정일자
Date

Distinct205
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum2001-12-18 00:00:00
Maximum2024-05-08 11:44:19
2024-05-11T15:09:37.801813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:09:38.037605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
I
196 
U
51 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 196
79.4%
U 51
 
20.6%

Length

2024-05-11T15:09:38.263705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:38.418875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 196
79.4%
u 51
 
20.6%

데이터갱신일자
Date

Distinct58
Distinct (%)23.5%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 23:01:00
2024-05-11T15:09:38.570545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:09:38.778517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
식품제조가공업
199 
기타 식품제조가공업
47 
도시락제조업
 
1

Length

Max length10
Median length7
Mean length7.5668016
Min length6

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 199
80.6%
기타 식품제조가공업 47
 
19.0%
도시락제조업 1
 
0.4%

Length

2024-05-11T15:09:39.050983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:39.294182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 246
83.7%
기타 47
 
16.0%
도시락제조업 1
 
0.3%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct204
Distinct (%)87.6%
Missing14
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean202738.36
Minimum199500.86
Maximum205996.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T15:09:39.568390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum199500.86
5-th percentile200013.69
Q1201394.61
median202827.56
Q3204081.32
95-th percentile205577.21
Maximum205996.72
Range6495.8604
Interquartile range (IQR)2686.7116

Descriptive statistics

Standard deviation1693.6864
Coefficient of variation (CV)0.0083540503
Kurtosis-0.97966082
Mean202738.36
Median Absolute Deviation (MAD)1335.214
Skewness0.069683254
Sum47238037
Variance2868573.7
MonotonicityNot monotonic
2024-05-11T15:09:39.845304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200771.40526517 7
 
2.8%
203708.200583224 4
 
1.6%
200384.086912862 4
 
1.6%
200841.726990037 3
 
1.2%
204204.386675127 3
 
1.2%
202890.245685637 2
 
0.8%
199881.838498431 2
 
0.8%
205725.865213454 2
 
0.8%
203513.404894064 2
 
0.8%
202403.6850049 2
 
0.8%
Other values (194) 202
81.8%
(Missing) 14
 
5.7%
ValueCountFrequency (%)
199500.857483996 1
0.4%
199636.868302673 1
0.4%
199708.315949528 1
0.4%
199787.978588928 1
0.4%
199789.510421548 1
0.4%
199833.266853437 1
0.4%
199865.854808249 1
0.4%
199881.838498431 2
0.8%
199902.061805735 1
0.4%
199906.494561058 1
0.4%
ValueCountFrequency (%)
205996.717928956 2
0.8%
205725.865213454 2
0.8%
205718.026997417 1
0.4%
205683.367579911 1
0.4%
205675.571104389 1
0.4%
205675.271916571 1
0.4%
205628.193668349 1
0.4%
205626.659611385 1
0.4%
205594.278662967 1
0.4%
205579.315116664 1
0.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct204
Distinct (%)87.6%
Missing14
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean455622.52
Minimum453013.95
Maximum457768.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T15:09:40.120237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum453013.95
5-th percentile453533.02
Q1454721.51
median455894.43
Q3456483
95-th percentile457025.41
Maximum457768.97
Range4755.0149
Interquartile range (IQR)1761.4951

Descriptive statistics

Standard deviation1127.9606
Coefficient of variation (CV)0.0024756471
Kurtosis-0.65675943
Mean455622.52
Median Absolute Deviation (MAD)766.18925
Skewness-0.48789706
Sum1.0616005 × 108
Variance1272295.1
MonotonicityNot monotonic
2024-05-11T15:09:40.378402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
456645.212754152 7
 
2.8%
456759.52104056 4
 
1.6%
454068.456692308 4
 
1.6%
454721.505180141 3
 
1.2%
457738.394259698 3
 
1.2%
456173.478791129 2
 
0.8%
456047.388052039 2
 
0.8%
456437.328199936 2
 
0.8%
455684.926919335 2
 
0.8%
454109.173789473 2
 
0.8%
Other values (194) 202
81.8%
(Missing) 14
 
5.7%
ValueCountFrequency (%)
453013.952137832 1
0.4%
453057.146732852 1
0.4%
453102.822525082 2
0.8%
453170.305690883 1
0.4%
453212.394700124 1
0.4%
453259.738160497 1
0.4%
453264.660517215 1
0.4%
453401.624548564 1
0.4%
453403.531356157 2
0.8%
453441.798592415 1
0.4%
ValueCountFrequency (%)
457768.96703203 1
 
0.4%
457738.394259698 3
1.2%
457664.961911112 2
0.8%
457436.625254021 1
 
0.4%
457297.865876295 2
0.8%
457215.545587162 1
 
0.4%
457196.673009202 1
 
0.4%
457029.426901393 1
 
0.4%
457022.736918068 1
 
0.4%
456955.503840816 1
 
0.4%

위생업태명
Categorical

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
식품제조가공업
188 
기타 식품제조가공업
33 
<NA>
26 

Length

Max length10
Median length7
Mean length7.0850202
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 188
76.1%
기타 식품제조가공업 33
 
13.4%
<NA> 26
 
10.5%

Length

2024-05-11T15:09:40.622433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:40.767581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 221
78.9%
기타 33
 
11.8%
na 26
 
9.3%

남성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
206 
0
 
19
1
 
13
3
 
5
2
 
4

Length

Max length4
Median length4
Mean length3.5020243
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row1
4th row1
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 206
83.4%
0 19
 
7.7%
1 13
 
5.3%
3 5
 
2.0%
2 4
 
1.6%

Length

2024-05-11T15:09:40.933345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:41.100730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 206
83.4%
0 19
 
7.7%
1 13
 
5.3%
3 5
 
2.0%
2 4
 
1.6%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
211 
0
23 
1
 
9
2
 
4

Length

Max length4
Median length4
Mean length3.562753
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> 211
85.4%
0 23
 
9.3%
1 9
 
3.6%
2 4
 
1.6%

Length

2024-05-11T15:09:41.263868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:41.450303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 211
85.4%
0 23
 
9.3%
1 9
 
3.6%
2 4
 
1.6%

영업장주변구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
209 
주택가주변
23 
기타
 
15

Length

Max length5
Median length4
Mean length3.9716599
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 209
84.6%
주택가주변 23
 
9.3%
기타 15
 
6.1%

Length

2024-05-11T15:09:41.723553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:41.951573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 209
84.6%
주택가주변 23
 
9.3%
기타 15
 
6.1%

등급구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
209 
기타
29 
자율
 
8
우수
 
1

Length

Max length4
Median length4
Mean length3.6923077
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 209
84.6%
기타 29
 
11.7%
자율 8
 
3.2%
우수 1
 
0.4%

Length

2024-05-11T15:09:42.149996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:42.341980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 209
84.6%
기타 29
 
11.7%
자율 8
 
3.2%
우수 1
 
0.4%

급수시설구분명
Categorical

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
상수도전용
134 
<NA>
111 
상수도(음용)지하수(주방용)겸용
 
2

Length

Max length17
Median length5
Mean length4.6477733
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 134
54.3%
<NA> 111
44.9%
상수도(음용)지하수(주방용)겸용 2
 
0.8%

Length

2024-05-11T15:09:42.488367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:42.634635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 134
54.3%
na 111
44.9%
상수도(음용)지하수(주방용)겸용 2
 
0.8%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
241 
0
 
6

Length

Max length4
Median length4
Mean length3.9271255
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> 241
97.6%
0 6
 
2.4%

Length

2024-05-11T15:09:42.779390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:42.934813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 241
97.6%
0 6
 
2.4%

본사종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
0
165 
<NA>
76 
1
 
4
15
 
1
2
 
1

Length

Max length4
Median length1
Mean length1.9271255
Min length1

Unique

Unique2 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
0 165
66.8%
<NA> 76
30.8%
1 4
 
1.6%
15 1
 
0.4%
2 1
 
0.4%

Length

2024-05-11T15:09:43.111800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:43.707649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 165
66.8%
na 76
30.8%
1 4
 
1.6%
15 1
 
0.4%
2 1
 
0.4%

공장사무직종업원수
Categorical

Distinct5
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
0
153 
<NA>
76 
1
 
13
2
 
3
3
 
2

Length

Max length4
Median length1
Mean length1.9230769
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 153
61.9%
<NA> 76
30.8%
1 13
 
5.3%
2 3
 
1.2%
3 2
 
0.8%

Length

2024-05-11T15:09:43.922091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:44.226218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 153
61.9%
na 76
30.8%
1 13
 
5.3%
2 3
 
1.2%
3 2
 
0.8%

공장판매직종업원수
Categorical

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
0
166 
<NA>
74 
1
 
5
2
 
2

Length

Max length4
Median length1
Mean length1.8987854
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 166
67.2%
<NA> 74
30.0%
1 5
 
2.0%
2 2
 
0.8%

Length

2024-05-11T15:09:44.413318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:44.596932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 166
67.2%
na 74
30.0%
1 5
 
2.0%
2 2
 
0.8%

공장생산직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)5.1%
Missing72
Missing (%)29.1%
Infinite0
Infinite (%)0.0%
Mean0.44571429
Minimum0
Maximum8
Zeros141
Zeros (%)57.1%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T15:09:44.745131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum8
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.3157627
Coefficient of variation (CV)2.9520317
Kurtosis16.198378
Mean0.44571429
Median Absolute Deviation (MAD)0
Skewness3.9551297
Sum78
Variance1.7312315
MonotonicityNot monotonic
2024-05-11T15:09:44.951991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 141
57.1%
1 23
 
9.3%
7 2
 
0.8%
3 2
 
0.8%
6 2
 
0.8%
4 2
 
0.8%
2 1
 
0.4%
8 1
 
0.4%
5 1
 
0.4%
(Missing) 72
29.1%
ValueCountFrequency (%)
0 141
57.1%
1 23
 
9.3%
2 1
 
0.4%
3 2
 
0.8%
4 2
 
0.8%
5 1
 
0.4%
6 2
 
0.8%
7 2
 
0.8%
8 1
 
0.4%
ValueCountFrequency (%)
8 1
 
0.4%
7 2
 
0.8%
6 2
 
0.8%
5 1
 
0.4%
4 2
 
0.8%
3 2
 
0.8%
2 1
 
0.4%
1 23
 
9.3%
0 141
57.1%

건물소유구분명
Categorical

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
임대
113 
<NA>
101 
자가
33 

Length

Max length4
Median length2
Mean length2.8178138
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
임대 113
45.7%
<NA> 101
40.9%
자가 33
 
13.4%

Length

2024-05-11T15:09:45.201889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:45.405063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
임대 113
45.7%
na 101
40.9%
자가 33
 
13.4%

보증액
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)20.0%
Missing217
Missing (%)87.9%
Infinite0
Infinite (%)0.0%
Mean5500150
Minimum0
Maximum40000000
Zeros21
Zeros (%)8.5%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T15:09:45.560193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33751125
95-th percentile28250000
Maximum40000000
Range40000000
Interquartile range (IQR)3751125

Descriptive statistics

Standard deviation11091237
Coefficient of variation (CV)2.0165335
Kurtosis3.3087338
Mean5500150
Median Absolute Deviation (MAD)0
Skewness2.0381695
Sum1.650045 × 108
Variance1.2301554 × 1014
MonotonicityNot monotonic
2024-05-11T15:09:45.768572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 21
 
8.5%
20000000 4
 
1.6%
5000000 2
 
0.8%
4500 1
 
0.4%
35000000 1
 
0.4%
40000000 1
 
0.4%
(Missing) 217
87.9%
ValueCountFrequency (%)
0 21
8.5%
4500 1
 
0.4%
5000000 2
 
0.8%
20000000 4
 
1.6%
35000000 1
 
0.4%
40000000 1
 
0.4%
ValueCountFrequency (%)
40000000 1
 
0.4%
35000000 1
 
0.4%
20000000 4
 
1.6%
5000000 2
 
0.8%
4500 1
 
0.4%
0 21
8.5%

월세액
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)31.0%
Missing218
Missing (%)88.3%
Infinite0
Infinite (%)0.0%
Mean315520.34
Minimum0
Maximum2000000
Zeros21
Zeros (%)8.5%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T15:09:45.959394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q390
95-th percentile1860000
Maximum2000000
Range2000000
Interquartile range (IQR)90

Descriptive statistics

Standard deviation662124.84
Coefficient of variation (CV)2.0985171
Kurtosis2.0569408
Mean315520.34
Median Absolute Deviation (MAD)0
Skewness1.9127562
Sum9150090
Variance4.384093 × 1011
MonotonicityNot monotonic
2024-05-11T15:09:46.183054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 21
 
8.5%
90 1
 
0.4%
1700000 1
 
0.4%
2000000 1
 
0.4%
350000 1
 
0.4%
1900000 1
 
0.4%
1800000 1
 
0.4%
1100000 1
 
0.4%
300000 1
 
0.4%
(Missing) 218
88.3%
ValueCountFrequency (%)
0 21
8.5%
90 1
 
0.4%
300000 1
 
0.4%
350000 1
 
0.4%
1100000 1
 
0.4%
1700000 1
 
0.4%
1800000 1
 
0.4%
1900000 1
 
0.4%
2000000 1
 
0.4%
ValueCountFrequency (%)
2000000 1
 
0.4%
1900000 1
 
0.4%
1800000 1
 
0.4%
1700000 1
 
0.4%
1100000 1
 
0.4%
350000 1
 
0.4%
300000 1
 
0.4%
90 1
 
0.4%
0 21
8.5%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing26
Missing (%)10.5%
Memory size626.0 B
False
221 
(Missing)
26 
ValueCountFrequency (%)
False 221
89.5%
(Missing) 26
 
10.5%
2024-05-11T15:09:46.413976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct22
Distinct (%)10.0%
Missing26
Missing (%)10.5%
Infinite0
Infinite (%)0.0%
Mean2.3842986
Minimum0
Maximum125.1
Zeros200
Zeros (%)81.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T15:09:46.595549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile12.7
Maximum125.1
Range125.1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation11.138117
Coefficient of variation (CV)4.6714439
Kurtosis71.605109
Mean2.3842986
Median Absolute Deviation (MAD)0
Skewness7.5629837
Sum526.93
Variance124.05766
MonotonicityNot monotonic
2024-05-11T15:09:46.784149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0.0 200
81.0%
27.5 1
 
0.4%
16.8 1
 
0.4%
2.6 1
 
0.4%
7.5 1
 
0.4%
35.84 1
 
0.4%
25.64 1
 
0.4%
12.6 1
 
0.4%
6.43 1
 
0.4%
7.64 1
 
0.4%
Other values (12) 12
 
4.9%
(Missing) 26
 
10.5%
ValueCountFrequency (%)
0.0 200
81.0%
2.2 1
 
0.4%
2.3 1
 
0.4%
2.6 1
 
0.4%
6.43 1
 
0.4%
7.5 1
 
0.4%
7.64 1
 
0.4%
9.77 1
 
0.4%
11.7 1
 
0.4%
12.6 1
 
0.4%
ValueCountFrequency (%)
125.1 1
0.4%
59.03 1
0.4%
48.3 1
0.4%
35.84 1
0.4%
33.63 1
0.4%
33.0 1
0.4%
29.15 1
0.4%
27.5 1
0.4%
25.64 1
0.4%
17.5 1
0.4%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing247
Missing (%)100.0%
Memory size2.3 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing247
Missing (%)100.0%
Memory size2.3 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing247
Missing (%)100.0%
Memory size2.3 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030700003070000-106-1963-0002019630212<NA>3폐업2폐업20041011<NA><NA><NA>02 9125374148.18136865서울특별시 성북구 하월곡동 33-46번지<NA><NA>동보식품2002-03-15 00:00:00I2018-08-31 23:59:59.0식품제조가공업<NA><NA>식품제조가공업<NA><NA>주택가주변기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
130700003070000-106-1973-0004019730119<NA>3폐업2폐업20020816<NA><NA><NA>02 9136388131.21136865서울특별시 성북구 하월곡동 53-13번지<NA><NA>태화식품2002-01-18 00:00:00I2018-08-31 23:59:59.0식품제조가공업203476.654717455842.837418식품제조가공업<NA><NA>기타기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
230700003070000-106-1976-0001419690430<NA>3폐업2폐업20020422<NA><NA><NA>02 9233933126.57136035서울특별시 성북구 동소문동5가 55-33번지<NA><NA>마산식품2002-01-18 00:00:00I2018-08-31 23:59:59.0식품제조가공업<NA><NA>식품제조가공업1<NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
330700003070000-106-1983-0003819830423<NA>3폐업2폐업20011017<NA><NA><NA>02 912034932.92136864서울특별시 성북구 종암동 3-996번지<NA><NA>선일식품2003-03-19 00:00:00I2018-08-31 23:59:59.0식품제조가공업202859.478721455577.19359식품제조가공업1<NA>주택가주변기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
430700003070000-106-1986-0001219861204<NA>3폐업2폐업20020919<NA><NA><NA>9168235156.7136865서울특별시 성북구 하월곡동 59-2번지<NA><NA>매일식품2002-01-18 00:00:00I2018-08-31 23:59:59.0식품제조가공업203319.551117455870.94094식품제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
530700003070000-106-1988-0001719691128<NA>3폐업2폐업20150416<NA><NA><NA>02 9131688131.0136874서울특별시 성북구 하월곡동 90-1326번지서울특별시 성북구 화랑로1길 54, 지상1층 (하월곡동)2739동보식품2015-02-16 15:48:01I2018-08-31 23:59:59.0식품제조가공업202924.404094456213.429601식품제조가공업10기타기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
630700003070000-106-1988-0004419670627<NA>3폐업2폐업20040512<NA><NA><NA>02 919009352.35136865서울특별시 성북구 하월곡동 46-14번지<NA><NA>삼호제과2002-01-18 00:00:00I2018-08-31 23:59:59.0식품제조가공업<NA><NA>식품제조가공업1<NA>주택가주변자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
730700003070000-106-1988-0007119750609<NA>3폐업2폐업20011017<NA><NA><NA>02 9626271104.34136820서울특별시 성북구 석관동 338-18번지<NA><NA>새시대식품공업(주)2002-01-18 00:00:00I2018-08-31 23:59:59.0식품제조가공업204582.68027456210.836258식품제조가공업1<NA>주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
830700003070000-106-1989-0001819890222<NA>3폐업2폐업20001219<NA><NA><NA>02 9144472175.7136844서울특별시 성북구 정릉동 138-2번지 3<NA><NA>아리랑식품2002-01-18 00:00:00I2018-08-31 23:59:59.0식품제조가공업<NA><NA>식품제조가공업00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
930700003070000-106-1990-0001519710529<NA>1영업/정상1영업<NA><NA><NA><NA>02 9129988161.1136864서울특별시 성북구 종암동 3-999 및 종암동 3-75 사7호, 종암동 3-75 사8호서울특별시 성북구 종암로28길 9, 지상1,2층 (종암동, 및 종암로28길 11)2797청산식품2022-06-30 09:13:17U2021-12-07 00:02:00.0식품제조가공업202869.969665455575.692338<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
23730700003070000-106-2021-0000220210422<NA>1영업/정상1영업<NA><NA><NA><NA><NA>65.12136053서울특별시 성북구 동선동3가 9서울특별시 성북구 동소문로26다길 25, 지하1층 (동선동3가)2845달콤테라피2021-05-18 13:34:13U2021-05-20 02:40:00.0기타 식품제조가공업201712.990343454748.383073기타 식품제조가공업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA>임대<NA><NA>N0.0<NA><NA><NA>
23830700003070000-106-2021-000032021-06-24<NA>1영업/정상1영업<NA><NA><NA><NA>02 744 2266269.74136-023서울특별시 성북구 성북동1가 35-5서울특별시 성북구 성북로 7, 5층 (성북동1가)2880엔파티세리2023-06-23 09:31:35U2022-12-05 22:05:00.0기타 식품제조가공업200384.086913454068.456692<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23930700003070000-106-2021-0000420210730<NA>1영업/정상1영업<NA><NA><NA><NA><NA>23.1136075서울특별시 성북구 안암동5가 101-15 만석가 빌딩서울특별시 성북구 개운사길 19, 만석가 빌딩 1층 (안암동5가)2842(주)무아2021-08-02 16:36:24I2021-08-04 00:22:52.0기타 식품제조가공업202501.044288453887.852816기타 식품제조가공업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
24030700003070000-106-2022-000012022-09-13<NA>3폐업2폐업2023-05-31<NA><NA><NA><NA>19.88136-120서울특별시 성북구 상월곡동 23-157서울특별시 성북구 화랑로 177-1, 1층 (상월곡동)2773어버드 커피2023-05-31 16:42:55U2022-12-06 00:02:00.0기타 식품제조가공업204352.691737456130.372792<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24130700003070000-106-2022-000022022-11-24<NA>3폐업2폐업2024-05-08<NA><NA><NA><NA>39.7136-801서울특별시 성북구 길음동 1089서울특별시 성북구 삼양로 36-14, 1층 (길음동)2732(주)왕부라더스2024-05-08 11:44:19U2023-12-04 23:01:00.0기타 식품제조가공업202078.107184456048.521547<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24230700003070000-106-2022-0000320221221<NA>1영업/정상1영업<NA><NA><NA><NA><NA>221.0136800서울특별시 성북구 길음동 25-7 삼주빌딩서울특별시 성북구 도봉로 11, 삼주빌딩 4층 (길음동)2729달콤한위로2022-12-26 10:25:35I2021-11-01 22:08:00.0기타 식품제조가공업202571.112399456435.426314<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24330700003070000-106-2023-000012023-03-28<NA>3폐업2폐업2023-12-22<NA><NA><NA><NA>26.59136-756서울특별시 성북구 돈암동 632 풍림아파트서울특별시 성북구 북악산로 913, 풍림아파트 상가동 408호 (돈암동, 풍림아파트)2808일타소스2023-12-22 15:28:44U2022-11-01 22:04:00.0기타 식품제조가공업201996.703358454842.350289<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24430700003070000-106-2023-000022023-09-01<NA>1영업/정상1영업<NA><NA><NA><NA>027442266191.14136-023서울특별시 성북구 성북동1가 35-5서울특별시 성북구 성북로 7, 나폴레옹과자점 4층 (성북동1가)2880엔블랑제리2023-09-04 17:29:01I2022-12-09 00:06:00.0기타 식품제조가공업200384.086913454068.456692<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24530700003070000-106-2023-000032023-11-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>74.0136-840서울특별시 성북구 정릉동 170-21 상익빌딩서울특별시 성북구 서경로 24, 상익빌딩 1층 101호 (정릉동)2719원두상담소2023-11-07 15:16:31I2022-11-01 00:09:00.0기타 식품제조가공업201263.986307455942.266678<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24630700003070000-106-2024-000012024-03-14<NA>1영업/정상1영업<NA><NA><NA><NA><NA>90.0136-829서울특별시 성북구 장위동 68-920서울특별시 성북구 장월로 60-1, 1층 (장위동)2769은영제과2024-03-14 13:28:04I2023-12-02 23:06:00.0기타 식품제조가공업204213.355959456553.099184<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>