Overview

Dataset statistics

Number of variables44
Number of observations927
Missing cells9215
Missing cells (%)22.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory339.6 KiB
Average record size in memory375.1 B

Variable types

Numeric7
Text7
DateTime4
Unsupported7
Categorical18
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
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16076/S/1/datasetView.do

Alerts

업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (69.3%)Imbalance
여성종사자수 is highly imbalanced (63.5%)Imbalance
영업장주변구분명 is highly imbalanced (88.0%)Imbalance
등급구분명 is highly imbalanced (91.2%)Imbalance
급수시설구분명 is highly imbalanced (58.3%)Imbalance
본사종업원수 is highly imbalanced (59.8%)Imbalance
보증액 is highly imbalanced (54.2%)Imbalance
월세액 is highly imbalanced (60.1%)Imbalance
인허가취소일자 has 927 (100.0%) missing valuesMissing
폐업일자 has 363 (39.2%) missing valuesMissing
휴업시작일자 has 927 (100.0%) missing valuesMissing
휴업종료일자 has 927 (100.0%) missing valuesMissing
재개업일자 has 927 (100.0%) missing valuesMissing
전화번호 has 284 (30.6%) missing valuesMissing
소재지면적 has 123 (13.3%) missing valuesMissing
도로명주소 has 238 (25.7%) missing valuesMissing
도로명우편번호 has 248 (26.8%) missing valuesMissing
좌표정보(X) has 27 (2.9%) missing valuesMissing
좌표정보(Y) has 27 (2.9%) missing valuesMissing
공장사무직종업원수 has 527 (56.9%) missing valuesMissing
공장판매직종업원수 has 531 (57.3%) missing valuesMissing
다중이용업소여부 has 177 (19.1%) missing valuesMissing
시설총규모 has 177 (19.1%) missing valuesMissing
전통업소지정번호 has 927 (100.0%) missing valuesMissing
전통업소주된음식 has 927 (100.0%) missing valuesMissing
홈페이지 has 927 (100.0%) missing valuesMissing
시설총규모 is highly skewed (γ1 = 23.98010216)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
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
공장사무직종업원수 has 386 (41.6%) zerosZeros
공장판매직종업원수 has 391 (42.2%) zerosZeros
시설총규모 has 691 (74.5%) zerosZeros

Reproduction

Analysis started2024-05-11 05:58:40.663088
Analysis finished2024-05-11 05:58:43.988772
Duration3.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct25
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3166138.1
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2024-05-11T05:58:44.257546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3040000
Q13130000
median3180000
Q33230000
95-th percentile3230000
Maximum3240000
Range240000
Interquartile range (IQR)100000

Descriptive statistics

Standard deviation66252.465
Coefficient of variation (CV)0.020925324
Kurtosis-0.49997596
Mean3166138.1
Median Absolute Deviation (MAD)50000
Skewness-0.7885368
Sum2.93501 × 109
Variance4.3893891 × 109
MonotonicityNot monotonic
2024-05-11T05:58:44.754221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3230000 224
24.2%
3150000 100
10.8%
3210000 74
 
8.0%
3180000 69
 
7.4%
3220000 60
 
6.5%
3240000 43
 
4.6%
3060000 42
 
4.5%
3140000 40
 
4.3%
3130000 34
 
3.7%
3050000 33
 
3.6%
Other values (15) 208
22.4%
ValueCountFrequency (%)
3000000 5
 
0.5%
3010000 15
 
1.6%
3020000 9
 
1.0%
3030000 10
 
1.1%
3040000 19
2.0%
3050000 33
3.6%
3060000 42
4.5%
3070000 7
 
0.8%
3080000 13
 
1.4%
3090000 11
 
1.2%
ValueCountFrequency (%)
3240000 43
 
4.6%
3230000 224
24.2%
3220000 60
 
6.5%
3210000 74
 
8.0%
3200000 11
 
1.2%
3190000 11
 
1.2%
3180000 69
 
7.4%
3170000 28
 
3.0%
3160000 26
 
2.8%
3150000 100
10.8%

관리번호
Text

UNIQUE 

Distinct927
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2024-05-11T05:58:45.219198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters20394
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

Unique927 ?
Unique (%)100.0%

Sample

1st row3100000-117-2022-00001
2nd row3140000-117-2022-00001
3rd row3140000-117-2021-00001
4th row3140000-117-2018-00001
5th row3140000-117-2011-00003
ValueCountFrequency (%)
3100000-117-2022-00001 1
 
0.1%
3230000-117-2007-00006 1
 
0.1%
3220000-117-2003-00001 1
 
0.1%
3220000-117-2003-00002 1
 
0.1%
3220000-117-2003-00003 1
 
0.1%
3220000-117-2003-00004 1
 
0.1%
3220000-117-2004-00001 1
 
0.1%
3220000-117-2004-00002 1
 
0.1%
3220000-117-2004-00003 1
 
0.1%
3220000-117-2004-00004 1
 
0.1%
Other values (917) 917
98.9%
2024-05-11T05:58:46.152256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8873
43.5%
1 3243
 
15.9%
- 2781
 
13.6%
2 1851
 
9.1%
3 1417
 
6.9%
7 1076
 
5.3%
4 292
 
1.4%
5 263
 
1.3%
6 238
 
1.2%
8 197
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17613
86.4%
Dash Punctuation 2781
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8873
50.4%
1 3243
 
18.4%
2 1851
 
10.5%
3 1417
 
8.0%
7 1076
 
6.1%
4 292
 
1.7%
5 263
 
1.5%
6 238
 
1.4%
8 197
 
1.1%
9 163
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 2781
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20394
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8873
43.5%
1 3243
 
15.9%
- 2781
 
13.6%
2 1851
 
9.1%
3 1417
 
6.9%
7 1076
 
5.3%
4 292
 
1.4%
5 263
 
1.3%
6 238
 
1.2%
8 197
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20394
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8873
43.5%
1 3243
 
15.9%
- 2781
 
13.6%
2 1851
 
9.1%
3 1417
 
6.9%
7 1076
 
5.3%
4 292
 
1.4%
5 263
 
1.3%
6 238
 
1.2%
8 197
 
1.0%
Distinct722
Distinct (%)77.9%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
Minimum1982-08-26 00:00:00
Maximum2024-04-26 00:00:00
2024-05-11T05:58:46.616095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:58:47.114860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing927
Missing (%)100.0%
Memory size8.3 KiB
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
3
564 
1
363 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 564
60.8%
1 363
39.2%

Length

2024-05-11T05:58:47.594568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:58:47.899883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 564
60.8%
1 363
39.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
폐업
564 
영업/정상
363 

Length

Max length5
Median length2
Mean length3.1747573
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 564
60.8%
영업/정상 363
39.2%

Length

2024-05-11T05:58:48.260524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:58:48.556449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 564
60.8%
영업/정상 363
39.2%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2
564 
1
363 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 564
60.8%
1 363
39.2%

Length

2024-05-11T05:58:49.001247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:58:49.291108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 564
60.8%
1 363
39.2%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
폐업
564 
영업
363 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 564
60.8%
영업 363
39.2%

Length

2024-05-11T05:58:49.612940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:58:49.895774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 564
60.8%
영업 363
39.2%

폐업일자
Date

MISSING 

Distinct476
Distinct (%)84.4%
Missing363
Missing (%)39.2%
Memory size7.4 KiB
Minimum1995-03-16 00:00:00
Maximum2024-04-09 00:00:00
2024-05-11T05:58:50.225977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:58:50.687429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing927
Missing (%)100.0%
Memory size8.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing927
Missing (%)100.0%
Memory size8.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing927
Missing (%)100.0%
Memory size8.3 KiB

전화번호
Text

MISSING 

Distinct566
Distinct (%)88.0%
Missing284
Missing (%)30.6%
Memory size7.4 KiB
2024-05-11T05:58:51.215787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.527216
Min length2

Characters and Unicode

Total characters6769
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

Unique506 ?
Unique (%)78.7%

Sample

1st row02 64092015
2nd row02 412 2980
3rd row02 583 2501
4th row0220629916
5th row070 86563588
ValueCountFrequency (%)
02 392
32.2%
031 15
 
1.2%
070 11
 
0.9%
401 6
 
0.5%
0 5
 
0.4%
16442111 4
 
0.3%
5384723 4
 
0.3%
032 4
 
0.3%
585 4
 
0.3%
0262040000 4
 
0.3%
Other values (664) 768
63.1%
2024-05-11T05:58:52.262372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1169
17.3%
2 1124
16.6%
810
12.0%
4 581
8.6%
6 506
7.5%
3 487
7.2%
1 479
7.1%
5 435
 
6.4%
8 429
 
6.3%
7 405
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5959
88.0%
Space Separator 810
 
12.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1169
19.6%
2 1124
18.9%
4 581
9.7%
6 506
8.5%
3 487
8.2%
1 479
8.0%
5 435
 
7.3%
8 429
 
7.2%
7 405
 
6.8%
9 344
 
5.8%
Space Separator
ValueCountFrequency (%)
810
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6769
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1169
17.3%
2 1124
16.6%
810
12.0%
4 581
8.6%
6 506
7.5%
3 487
7.2%
1 479
7.1%
5 435
 
6.4%
8 429
 
6.3%
7 405
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6769
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1169
17.3%
2 1124
16.6%
810
12.0%
4 581
8.6%
6 506
7.5%
3 487
7.2%
1 479
7.1%
5 435
 
6.4%
8 429
 
6.3%
7 405
 
6.0%

소재지면적
Text

MISSING 

Distinct435
Distinct (%)54.1%
Missing123
Missing (%)13.3%
Memory size7.4 KiB
2024-05-11T05:58:53.272967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length5.0559701
Min length3

Characters and Unicode

Total characters4065
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique345 ?
Unique (%)42.9%

Sample

1st row65.00
2nd row33.00
3rd row100.00
4th row12.00
5th row66.11
ValueCountFrequency (%)
33.00 42
 
5.2%
10.00 29
 
3.6%
66.00 24
 
3.0%
3.30 21
 
2.6%
30.00 17
 
2.1%
00 13
 
1.6%
8.00 13
 
1.6%
20.00 13
 
1.6%
15.00 11
 
1.4%
40.00 11
 
1.4%
Other values (425) 610
75.9%
2024-05-11T05:58:55.145422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1181
29.1%
. 804
19.8%
3 340
 
8.4%
1 321
 
7.9%
2 245
 
6.0%
6 234
 
5.8%
5 231
 
5.7%
9 212
 
5.2%
4 210
 
5.2%
8 153
 
3.8%
Other values (2) 134
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3255
80.1%
Other Punctuation 810
 
19.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1181
36.3%
3 340
 
10.4%
1 321
 
9.9%
2 245
 
7.5%
6 234
 
7.2%
5 231
 
7.1%
9 212
 
6.5%
4 210
 
6.5%
8 153
 
4.7%
7 128
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 804
99.3%
, 6
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Common 4065
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1181
29.1%
. 804
19.8%
3 340
 
8.4%
1 321
 
7.9%
2 245
 
6.0%
6 234
 
5.8%
5 231
 
5.7%
9 212
 
5.2%
4 210
 
5.2%
8 153
 
3.8%
Other values (2) 134
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4065
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1181
29.1%
. 804
19.8%
3 340
 
8.4%
1 321
 
7.9%
2 245
 
6.0%
6 234
 
5.8%
5 231
 
5.7%
9 212
 
5.2%
4 210
 
5.2%
8 153
 
3.8%
Other values (2) 134
 
3.3%
Distinct497
Distinct (%)53.7%
Missing2
Missing (%)0.2%
Memory size7.4 KiB
2024-05-11T05:58:56.122611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1145946
Min length6

Characters and Unicode

Total characters5656
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

Unique339 ?
Unique (%)36.6%

Sample

1st row139-230
2nd row158-808
3rd row158-848
4th row158-050
5th row158-852
ValueCountFrequency (%)
138881 32
 
3.5%
157816 17
 
1.8%
157210 17
 
1.8%
138200 13
 
1.4%
138888 13
 
1.4%
157290 11
 
1.2%
138806 10
 
1.1%
150866 9
 
1.0%
137862 9
 
1.0%
150803 9
 
1.0%
Other values (487) 785
84.9%
2024-05-11T05:58:57.526762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1322
23.4%
8 1120
19.8%
3 733
13.0%
0 511
 
9.0%
5 500
 
8.8%
7 350
 
6.2%
2 349
 
6.2%
4 251
 
4.4%
6 216
 
3.8%
9 198
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5550
98.1%
Dash Punctuation 106
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1322
23.8%
8 1120
20.2%
3 733
13.2%
0 511
 
9.2%
5 500
 
9.0%
7 350
 
6.3%
2 349
 
6.3%
4 251
 
4.5%
6 216
 
3.9%
9 198
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 106
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5656
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1322
23.4%
8 1120
19.8%
3 733
13.0%
0 511
 
9.0%
5 500
 
8.8%
7 350
 
6.2%
2 349
 
6.2%
4 251
 
4.4%
6 216
 
3.8%
9 198
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5656
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1322
23.4%
8 1120
19.8%
3 733
13.0%
0 511
 
9.0%
5 500
 
8.8%
7 350
 
6.2%
2 349
 
6.2%
4 251
 
4.4%
6 216
 
3.8%
9 198
 
3.5%
Distinct777
Distinct (%)84.0%
Missing2
Missing (%)0.2%
Memory size7.4 KiB
2024-05-11T05:58:58.428187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length43
Mean length27.619459
Min length16

Characters and Unicode

Total characters25548
Distinct characters350
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique675 ?
Unique (%)73.0%

Sample

1st row서울특별시 노원구 하계동 *** 청솔아파트
2nd row서울특별시 양천구 목동 ***-** *층 ***호
3rd row서울특별시 양천구 신월동 ****-*
4th row서울특별시 양천구 목동 ***-* 현대**타워 ****호
5th row서울특별시 양천구 신정동 ***-**
ValueCountFrequency (%)
서울특별시 924
19.4%
번지 624
 
13.1%
323
 
6.8%
송파구 223
 
4.7%
206
 
4.3%
182
 
3.8%
강서구 100
 
2.1%
가락동 97
 
2.0%
서초구 74
 
1.5%
영등포구 67
 
1.4%
Other values (606) 1955
40.9%
2024-05-11T05:59:00.009437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 5052
19.8%
4505
17.6%
1186
 
4.6%
1113
 
4.4%
1000
 
3.9%
954
 
3.7%
933
 
3.7%
925
 
3.6%
924
 
3.6%
- 767
 
3.0%
Other values (340) 8189
32.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14918
58.4%
Other Punctuation 5077
 
19.9%
Space Separator 4505
 
17.6%
Dash Punctuation 767
 
3.0%
Open Punctuation 73
 
0.3%
Close Punctuation 73
 
0.3%
Uppercase Letter 69
 
0.3%
Decimal Number 57
 
0.2%
Lowercase Letter 5
 
< 0.1%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1186
 
8.0%
1113
 
7.5%
1000
 
6.7%
954
 
6.4%
933
 
6.3%
925
 
6.2%
924
 
6.2%
753
 
5.0%
628
 
4.2%
311
 
2.1%
Other values (297) 6191
41.5%
Uppercase Letter
ValueCountFrequency (%)
B 15
21.7%
A 10
14.5%
C 7
10.1%
M 5
 
7.2%
D 5
 
7.2%
K 4
 
5.8%
T 4
 
5.8%
L 3
 
4.3%
R 3
 
4.3%
O 2
 
2.9%
Other values (8) 11
15.9%
Decimal Number
ValueCountFrequency (%)
3 12
21.1%
1 11
19.3%
2 9
15.8%
7 6
10.5%
4 5
8.8%
8 4
 
7.0%
5 4
 
7.0%
9 3
 
5.3%
0 2
 
3.5%
6 1
 
1.8%
Lowercase Letter
ValueCountFrequency (%)
e 2
40.0%
r 1
20.0%
w 1
20.0%
o 1
20.0%
Other Punctuation
ValueCountFrequency (%)
* 5052
99.5%
, 24
 
0.5%
/ 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 61
83.6%
[ 12
 
16.4%
Close Punctuation
ValueCountFrequency (%)
) 61
83.6%
] 12
 
16.4%
Space Separator
ValueCountFrequency (%)
4505
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 767
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14918
58.4%
Common 10554
41.3%
Latin 76
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1186
 
8.0%
1113
 
7.5%
1000
 
6.7%
954
 
6.4%
933
 
6.3%
925
 
6.2%
924
 
6.2%
753
 
5.0%
628
 
4.2%
311
 
2.1%
Other values (297) 6191
41.5%
Latin
ValueCountFrequency (%)
B 15
19.7%
A 10
13.2%
C 7
 
9.2%
M 5
 
6.6%
D 5
 
6.6%
K 4
 
5.3%
T 4
 
5.3%
L 3
 
3.9%
R 3
 
3.9%
2
 
2.6%
Other values (13) 18
23.7%
Common
ValueCountFrequency (%)
* 5052
47.9%
4505
42.7%
- 767
 
7.3%
( 61
 
0.6%
) 61
 
0.6%
, 24
 
0.2%
[ 12
 
0.1%
3 12
 
0.1%
] 12
 
0.1%
1 11
 
0.1%
Other values (10) 37
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14918
58.4%
ASCII 10628
41.6%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 5052
47.5%
4505
42.4%
- 767
 
7.2%
( 61
 
0.6%
) 61
 
0.6%
, 24
 
0.2%
B 15
 
0.1%
[ 12
 
0.1%
3 12
 
0.1%
] 12
 
0.1%
Other values (32) 107
 
1.0%
Hangul
ValueCountFrequency (%)
1186
 
8.0%
1113
 
7.5%
1000
 
6.7%
954
 
6.4%
933
 
6.3%
925
 
6.2%
924
 
6.2%
753
 
5.0%
628
 
4.2%
311
 
2.1%
Other values (297) 6191
41.5%
Number Forms
ValueCountFrequency (%)
2
100.0%

도로명주소
Text

MISSING 

Distinct634
Distinct (%)92.0%
Missing238
Missing (%)25.7%
Memory size7.4 KiB
2024-05-11T05:59:01.189085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length47
Mean length35.457184
Min length21

Characters and Unicode

Total characters24430
Distinct characters372
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique595 ?
Unique (%)86.4%

Sample

1st row서울특별시 노원구 공릉로**길 **, ***동 ***호 (하계동, 청솔아파트)
2nd row서울특별시 양천구 목동중앙북로**길 *, *층 ***호 (목동)
3rd row서울특별시 양천구 신월로 ***, ***(일부)호 (신월동)
4th row서울특별시 양천구 목동동로 ***, 현대**타워 ****호 (목동)
5th row서울특별시 양천구 신목로*길 *, *층 (신정동)
ValueCountFrequency (%)
702
 
15.3%
서울특별시 689
 
15.0%
307
 
6.7%
247
 
5.4%
송파구 169
 
3.7%
강서구 80
 
1.7%
서초구 54
 
1.2%
지상*층 51
 
1.1%
영등포구 51
 
1.1%
가락동 44
 
1.0%
Other values (889) 2193
47.8%
2024-05-11T05:59:02.669624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 4116
16.8%
3900
 
16.0%
932
 
3.8%
924
 
3.8%
, 793
 
3.2%
762
 
3.1%
753
 
3.1%
730
 
3.0%
) 713
 
2.9%
( 713
 
2.9%
Other values (362) 10094
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13871
56.8%
Other Punctuation 4909
 
20.1%
Space Separator 3900
 
16.0%
Close Punctuation 720
 
2.9%
Open Punctuation 720
 
2.9%
Dash Punctuation 147
 
0.6%
Uppercase Letter 85
 
0.3%
Decimal Number 67
 
0.3%
Lowercase Letter 5
 
< 0.1%
Letter Number 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
932
 
6.7%
924
 
6.7%
762
 
5.5%
753
 
5.4%
730
 
5.3%
699
 
5.0%
690
 
5.0%
689
 
5.0%
409
 
2.9%
381
 
2.7%
Other values (317) 6902
49.8%
Uppercase Letter
ValueCountFrequency (%)
A 21
24.7%
B 17
20.0%
C 10
11.8%
K 4
 
4.7%
M 4
 
4.7%
T 4
 
4.7%
D 3
 
3.5%
R 3
 
3.5%
I 3
 
3.5%
L 3
 
3.5%
Other values (10) 13
15.3%
Decimal Number
ValueCountFrequency (%)
2 17
25.4%
1 11
16.4%
0 8
11.9%
5 7
10.4%
3 7
10.4%
4 5
 
7.5%
7 4
 
6.0%
9 3
 
4.5%
8 3
 
4.5%
6 2
 
3.0%
Lowercase Letter
ValueCountFrequency (%)
r 1
20.0%
e 1
20.0%
w 1
20.0%
o 1
20.0%
c 1
20.0%
Other Punctuation
ValueCountFrequency (%)
* 4116
83.8%
, 793
 
16.2%
Close Punctuation
ValueCountFrequency (%)
) 713
99.0%
] 7
 
1.0%
Open Punctuation
ValueCountFrequency (%)
( 713
99.0%
[ 7
 
1.0%
Space Separator
ValueCountFrequency (%)
3900
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 147
100.0%
Letter Number
ValueCountFrequency (%)
3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13871
56.8%
Common 10466
42.8%
Latin 93
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
932
 
6.7%
924
 
6.7%
762
 
5.5%
753
 
5.4%
730
 
5.3%
699
 
5.0%
690
 
5.0%
689
 
5.0%
409
 
2.9%
381
 
2.7%
Other values (317) 6902
49.8%
Latin
ValueCountFrequency (%)
A 21
22.6%
B 17
18.3%
C 10
10.8%
K 4
 
4.3%
M 4
 
4.3%
T 4
 
4.3%
D 3
 
3.2%
3
 
3.2%
R 3
 
3.2%
I 3
 
3.2%
Other values (16) 21
22.6%
Common
ValueCountFrequency (%)
* 4116
39.3%
3900
37.3%
, 793
 
7.6%
) 713
 
6.8%
( 713
 
6.8%
- 147
 
1.4%
2 17
 
0.2%
1 11
 
0.1%
0 8
 
0.1%
5 7
 
0.1%
Other values (9) 41
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13871
56.8%
ASCII 10556
43.2%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 4116
39.0%
3900
36.9%
, 793
 
7.5%
) 713
 
6.8%
( 713
 
6.8%
- 147
 
1.4%
A 21
 
0.2%
B 17
 
0.2%
2 17
 
0.2%
1 11
 
0.1%
Other values (34) 108
 
1.0%
Hangul
ValueCountFrequency (%)
932
 
6.7%
924
 
6.7%
762
 
5.5%
753
 
5.4%
730
 
5.3%
699
 
5.0%
690
 
5.0%
689
 
5.0%
409
 
2.9%
381
 
2.7%
Other values (317) 6902
49.8%
Number Forms
ValueCountFrequency (%)
3
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct424
Distinct (%)62.4%
Missing248
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean5811.1591
Minimum1003
Maximum8789
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2024-05-11T05:59:03.132374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1003
5-th percentile2027.6
Q15045
median5810
Q37282
95-th percentile8298.4
Maximum8789
Range7786
Interquartile range (IQR)2237

Descriptive statistics

Standard deviation1861.7205
Coefficient of variation (CV)0.32036991
Kurtosis-0.14593587
Mean5811.1591
Median Absolute Deviation (MAD)1398
Skewness-0.6903243
Sum3945777
Variance3466003.3
MonotonicityNot monotonic
2024-05-11T05:59:03.833930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5699 24
 
2.6%
7644 14
 
1.5%
5854 10
 
1.1%
7645 7
 
0.8%
6732 7
 
0.8%
2018 7
 
0.8%
8212 6
 
0.6%
7788 6
 
0.6%
7654 6
 
0.6%
5719 6
 
0.6%
Other values (414) 586
63.2%
(Missing) 248
26.8%
ValueCountFrequency (%)
1003 1
0.1%
1151 1
0.1%
1158 1
0.1%
1227 1
0.1%
1306 1
0.1%
1309 2
0.2%
1314 1
0.1%
1318 1
0.1%
1327 1
0.1%
1329 1
0.1%
ValueCountFrequency (%)
8789 1
0.1%
8788 2
0.2%
8769 2
0.2%
8766 1
0.1%
8762 1
0.1%
8755 1
0.1%
8729 2
0.2%
8638 1
0.1%
8632 1
0.1%
8614 1
0.1%
Distinct820
Distinct (%)88.5%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2024-05-11T05:59:04.481109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length17
Mean length7.412082
Min length2

Characters and Unicode

Total characters6871
Distinct characters403
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

Unique736 ?
Unique (%)79.4%

Sample

1st row채순규
2nd row제이오물류 주식회사
3rd row상석운수(주)
4th row(주)월드비전종합물류
5th row부광상운(주)
ValueCountFrequency (%)
주식회사 63
 
6.0%
9
 
0.9%
개별화물 8
 
0.8%
남양로지스 5
 
0.5%
농업회사법인 5
 
0.5%
물류 5
 
0.5%
삼원엠앤에스주식회사 4
 
0.4%
개별용달 4
 
0.4%
정화로지스(주 4
 
0.4%
주)한비종합물류 3
 
0.3%
Other values (845) 942
89.5%
2024-05-11T05:59:05.882511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
591
 
8.6%
) 512
 
7.5%
( 507
 
7.4%
253
 
3.7%
149
 
2.2%
137
 
2.0%
125
 
1.8%
125
 
1.8%
124
 
1.8%
124
 
1.8%
Other values (393) 4224
61.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5659
82.4%
Close Punctuation 512
 
7.5%
Open Punctuation 507
 
7.4%
Space Separator 125
 
1.8%
Uppercase Letter 39
 
0.6%
Lowercase Letter 14
 
0.2%
Other Punctuation 9
 
0.1%
Decimal Number 5
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
591
 
10.4%
253
 
4.5%
149
 
2.6%
137
 
2.4%
125
 
2.2%
124
 
2.2%
124
 
2.2%
119
 
2.1%
117
 
2.1%
110
 
1.9%
Other values (360) 3810
67.3%
Uppercase Letter
ValueCountFrequency (%)
S 8
20.5%
F 7
17.9%
C 4
10.3%
H 4
10.3%
M 3
 
7.7%
L 2
 
5.1%
G 2
 
5.1%
N 2
 
5.1%
T 2
 
5.1%
B 1
 
2.6%
Other values (4) 4
10.3%
Lowercase Letter
ValueCountFrequency (%)
o 4
28.6%
d 2
14.3%
p 1
 
7.1%
f 1
 
7.1%
r 1
 
7.1%
i 1
 
7.1%
e 1
 
7.1%
n 1
 
7.1%
s 1
 
7.1%
k 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
1 2
40.0%
8 2
40.0%
6 1
20.0%
Other Punctuation
ValueCountFrequency (%)
. 6
66.7%
& 3
33.3%
Close Punctuation
ValueCountFrequency (%)
) 512
100.0%
Open Punctuation
ValueCountFrequency (%)
( 507
100.0%
Space Separator
ValueCountFrequency (%)
125
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5659
82.4%
Common 1159
 
16.9%
Latin 53
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
591
 
10.4%
253
 
4.5%
149
 
2.6%
137
 
2.4%
125
 
2.2%
124
 
2.2%
124
 
2.2%
119
 
2.1%
117
 
2.1%
110
 
1.9%
Other values (360) 3810
67.3%
Latin
ValueCountFrequency (%)
S 8
15.1%
F 7
13.2%
C 4
 
7.5%
o 4
 
7.5%
H 4
 
7.5%
M 3
 
5.7%
L 2
 
3.8%
G 2
 
3.8%
d 2
 
3.8%
N 2
 
3.8%
Other values (14) 15
28.3%
Common
ValueCountFrequency (%)
) 512
44.2%
( 507
43.7%
125
 
10.8%
. 6
 
0.5%
& 3
 
0.3%
1 2
 
0.2%
8 2
 
0.2%
- 1
 
0.1%
6 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5659
82.4%
ASCII 1212
 
17.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
591
 
10.4%
253
 
4.5%
149
 
2.6%
137
 
2.4%
125
 
2.2%
124
 
2.2%
124
 
2.2%
119
 
2.1%
117
 
2.1%
110
 
1.9%
Other values (360) 3810
67.3%
ASCII
ValueCountFrequency (%)
) 512
42.2%
( 507
41.8%
125
 
10.3%
S 8
 
0.7%
F 7
 
0.6%
. 6
 
0.5%
C 4
 
0.3%
o 4
 
0.3%
H 4
 
0.3%
M 3
 
0.2%
Other values (23) 32
 
2.6%
Distinct889
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
Minimum2000-08-28 00:00:00
Maximum2024-04-26 17:05:32
2024-05-11T05:59:06.365646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:59:06.937223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
I
654 
U
273 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 654
70.6%
U 273
29.4%

Length

2024-05-11T05:59:07.626888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:59:08.042113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 654
70.6%
u 273
29.4%
Distinct306
Distinct (%)33.0%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:06:00
2024-05-11T05:59:08.452107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:59:09.055308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
식품운반업
927 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품운반업 927
100.0%

Length

2024-05-11T05:59:09.651566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:59:10.063079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품운반업 927
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct679
Distinct (%)75.4%
Missing27
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean200502.19
Minimum182864.4
Maximum215984.38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2024-05-11T05:59:10.612535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182864.4
5-th percentile184148.57
Q1190985.77
median203275.9
Q3209733.03
95-th percentile211919.42
Maximum215984.38
Range33119.976
Interquartile range (IQR)18747.254

Descriptive statistics

Standard deviation9496.1565
Coefficient of variation (CV)0.047361859
Kurtosis-1.3041844
Mean200502.19
Median Absolute Deviation (MAD)7490.9939
Skewness-0.37581534
Sum1.8045197 × 108
Variance90176989
MonotonicityNot monotonic
2024-05-11T05:59:11.145808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
209790.959909032 33
 
3.6%
184148.571466974 10
 
1.1%
191900.345924872 9
 
1.0%
202508.646065919 7
 
0.8%
187020.691251664 6
 
0.6%
210558.0 6
 
0.6%
190821.206721583 5
 
0.5%
190649.039032094 5
 
0.5%
189277.761702183 5
 
0.5%
183914.938310002 5
 
0.5%
Other values (669) 809
87.3%
(Missing) 27
 
2.9%
ValueCountFrequency (%)
182864.398784135 1
0.1%
182876.367858149 1
0.1%
182897.275780238 1
0.1%
182941.05762285 1
0.1%
182996.150402015 1
0.1%
183013.81000202 2
0.2%
183267.18602689 1
0.1%
183307.197874057 1
0.1%
183366.236140415 1
0.1%
183382.861571856 1
0.1%
ValueCountFrequency (%)
215984.375136997 1
0.1%
215212.777691087 1
0.1%
215195.884311721 1
0.1%
214960.058118573 1
0.1%
214075.140422558 1
0.1%
213877.915058256 1
0.1%
213751.740241662 1
0.1%
213316.629256533 1
0.1%
213228.378235527 1
0.1%
213212.586749809 2
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct679
Distinct (%)75.4%
Missing27
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean447610.74
Minimum438307.42
Maximum464814.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2024-05-11T05:59:11.633612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum438307.42
5-th percentile441446
Q1443574.41
median446618.94
Q3450543.45
95-th percentile457251.24
Maximum464814.72
Range26507.294
Interquartile range (IQR)6969.0426

Descriptive statistics

Standard deviation5089.6499
Coefficient of variation (CV)0.011370705
Kurtosis0.76002845
Mean447610.74
Median Absolute Deviation (MAD)3284.7136
Skewness0.97736813
Sum4.0284967 × 108
Variance25904536
MonotonicityNot monotonic
2024-05-11T05:59:12.120106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443481.212174317 33
 
3.6%
450166.360534543 10
 
1.1%
452626.221252439 9
 
1.0%
442625.413940559 7
 
0.8%
450220.360286033 6
 
0.6%
442587.0 6
 
0.6%
447023.185320259 5
 
0.5%
448224.111919951 5
 
0.5%
444671.551731639 5
 
0.5%
450085.01457343 5
 
0.5%
Other values (669) 809
87.3%
(Missing) 27
 
2.9%
ValueCountFrequency (%)
438307.423372216 1
0.1%
438711.564180845 1
0.1%
439083.411970871 1
0.1%
439251.334214938 1
0.1%
439291.776424486 1
0.1%
439322.42742435 1
0.1%
439872.136912651 1
0.1%
439881.740443559 2
0.2%
439960.533113874 2
0.2%
440025.258933437 2
0.2%
ValueCountFrequency (%)
464814.717432497 1
 
0.1%
464199.048415229 1
 
0.1%
464092.187505065 1
 
0.1%
463523.566914004 2
0.2%
463464.624149153 1
 
0.1%
463290.410210672 4
0.4%
463247.302380066 1
 
0.1%
463131.123787152 1
 
0.1%
463117.539126587 1
 
0.1%
463010.156333841 1
 
0.1%

위생업태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
식품운반업
750 
<NA>
177 

Length

Max length5
Median length5
Mean length4.8090615
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품운반업 750
80.9%
<NA> 177
 
19.1%

Length

2024-05-11T05:59:12.550491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:59:12.943700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품운반업 750
80.9%
na 177
 
19.1%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
<NA>
803 
0
117 
1
 
6
2
 
1

Length

Max length4
Median length4
Mean length3.5987055
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 803
86.6%
0 117
 
12.6%
1 6
 
0.6%
2 1
 
0.1%

Length

2024-05-11T05:59:13.508920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:59:13.872728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 803
86.6%
0 117
 
12.6%
1 6
 
0.6%
2 1
 
0.1%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
<NA>
807 
0
117 
1
 
3

Length

Max length4
Median length4
Mean length3.6116505
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> 807
87.1%
0 117
 
12.6%
1 3
 
0.3%

Length

2024-05-11T05:59:14.412742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:59:14.793232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 807
87.1%
0 117
 
12.6%
1 3
 
0.3%

영업장주변구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
<NA>
904 
기타
 
16
주택가주변
 
7

Length

Max length5
Median length4
Mean length3.9730313
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 904
97.5%
기타 16
 
1.7%
주택가주변 7
 
0.8%

Length

2024-05-11T05:59:15.449219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:59:15.975015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 904
97.5%
기타 16
 
1.7%
주택가주변 7
 
0.8%

등급구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
<NA>
904 
기타
 
15
자율
 
3
 
3
우수
 
2

Length

Max length4
Median length4
Mean length3.9471413
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> 904
97.5%
기타 15
 
1.6%
자율 3
 
0.3%
3
 
0.3%
우수 2
 
0.2%

Length

2024-05-11T05:59:16.601416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:59:17.118965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 904
97.5%
기타 15
 
1.6%
자율 3
 
0.3%
3
 
0.3%
우수 2
 
0.2%

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
<NA>
849 
상수도전용
 
78

Length

Max length5
Median length4
Mean length4.0841424
Min length4

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> 849
91.6%
상수도전용 78
 
8.4%

Length

2024-05-11T05:59:17.624676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:59:17.984031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 849
91.6%
상수도전용 78
 
8.4%

총인원
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
<NA>
817 
0
110 

Length

Max length4
Median length4
Mean length3.6440129
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> 817
88.1%
0 110
 
11.9%

Length

2024-05-11T05:59:18.411253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:59:18.742070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 817
88.1%
0 110
 
11.9%

본사종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
<NA>
528 
0
394 
8
 
2
2
 
1
1
 
1

Length

Max length4
Median length4
Mean length2.7087379
Min length1

Unique

Unique3 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 528
57.0%
0 394
42.5%
8 2
 
0.2%
2 1
 
0.1%
1 1
 
0.1%
5 1
 
0.1%

Length

2024-05-11T05:59:19.187597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:59:19.711302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 528
57.0%
0 394
42.5%
8 2
 
0.2%
2 1
 
0.1%
1 1
 
0.1%
5 1
 
0.1%

공장사무직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)2.0%
Missing527
Missing (%)56.9%
Infinite0
Infinite (%)0.0%
Mean0.63
Minimum0
Maximum130
Zeros386
Zeros (%)41.6%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2024-05-11T05:59:20.116196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum130
Range130
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7.7338627
Coefficient of variation (CV)12.275972
Kurtosis227.42776
Mean0.63
Median Absolute Deviation (MAD)0
Skewness14.753224
Sum252
Variance59.812632
MonotonicityNot monotonic
2024-05-11T05:59:20.660044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 386
41.6%
1 6
 
0.6%
2 3
 
0.3%
3 1
 
0.1%
7 1
 
0.1%
18 1
 
0.1%
130 1
 
0.1%
82 1
 
0.1%
(Missing) 527
56.9%
ValueCountFrequency (%)
0 386
41.6%
1 6
 
0.6%
2 3
 
0.3%
3 1
 
0.1%
7 1
 
0.1%
18 1
 
0.1%
82 1
 
0.1%
130 1
 
0.1%
ValueCountFrequency (%)
130 1
 
0.1%
82 1
 
0.1%
18 1
 
0.1%
7 1
 
0.1%
3 1
 
0.1%
2 3
 
0.3%
1 6
 
0.6%
0 386
41.6%

공장판매직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)1.5%
Missing531
Missing (%)57.3%
Infinite0
Infinite (%)0.0%
Mean0.33585859
Minimum0
Maximum120
Zeros391
Zeros (%)42.2%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2024-05-11T05:59:21.195253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum120
Range120
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6.0391824
Coefficient of variation (CV)17.981325
Kurtosis393.20481
Mean0.33585859
Median Absolute Deviation (MAD)0
Skewness19.796974
Sum133
Variance36.471724
MonotonicityNot monotonic
2024-05-11T05:59:21.704246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 391
42.2%
120 1
 
0.1%
4 1
 
0.1%
1 1
 
0.1%
5 1
 
0.1%
3 1
 
0.1%
(Missing) 531
57.3%
ValueCountFrequency (%)
0 391
42.2%
1 1
 
0.1%
3 1
 
0.1%
4 1
 
0.1%
5 1
 
0.1%
120 1
 
0.1%
ValueCountFrequency (%)
120 1
 
0.1%
5 1
 
0.1%
4 1
 
0.1%
3 1
 
0.1%
1 1
 
0.1%
0 391
42.2%
Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
<NA>
530 
0
395 
3
 
1
2
 
1

Length

Max length4
Median length4
Mean length2.7152104
Min length1

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 530
57.2%
0 395
42.6%
3 1
 
0.1%
2 1
 
0.1%

Length

2024-05-11T05:59:22.594652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:59:22.994614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 530
57.2%
0 395
42.6%
3 1
 
0.1%
2 1
 
0.1%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
<NA>
327 
자가
305 
임대
295 

Length

Max length4
Median length2
Mean length2.7055016
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 327
35.3%
자가 305
32.9%
임대 295
31.8%

Length

2024-05-11T05:59:23.624087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:59:24.137904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 327
35.3%
자가 305
32.9%
임대 295
31.8%

보증액
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
<NA>
645 
0
279 
20000000
 
2
10000000
 
1

Length

Max length8
Median length4
Mean length3.1100324
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 645
69.6%
0 279
30.1%
20000000 2
 
0.2%
10000000 1
 
0.1%

Length

2024-05-11T05:59:24.734051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:59:25.239256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 645
69.6%
0 279
30.1%
20000000 2
 
0.2%
10000000 1
 
0.1%

월세액
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
<NA>
644 
0
279 
500000
 
2
270000
 
1
1900000
 
1

Length

Max length7
Median length4
Mean length3.1067961
Min length1

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 644
69.5%
0 279
30.1%
500000 2
 
0.2%
270000 1
 
0.1%
1900000 1
 
0.1%

Length

2024-05-11T05:59:25.563419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:59:25.922701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 644
69.5%
0 279
30.1%
500000 2
 
0.2%
270000 1
 
0.1%
1900000 1
 
0.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing177
Missing (%)19.1%
Memory size1.9 KiB
False
750 
(Missing)
177 
ValueCountFrequency (%)
False 750
80.9%
(Missing) 177
 
19.1%
2024-05-11T05:59:26.285693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct55
Distinct (%)7.3%
Missing177
Missing (%)19.1%
Infinite0
Infinite (%)0.0%
Mean12.699907
Minimum0
Maximum4017.09
Zeros691
Zeros (%)74.5%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2024-05-11T05:59:26.825244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile28.55
Maximum4017.09
Range4017.09
Interquartile range (IQR)0

Descriptive statistics

Standard deviation153.70566
Coefficient of variation (CV)12.102897
Kurtosis618.36528
Mean12.699907
Median Absolute Deviation (MAD)0
Skewness23.980102
Sum9524.93
Variance23625.431
MonotonicityNot monotonic
2024-05-11T05:59:27.411519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 691
74.5%
3.3 3
 
0.3%
20.0 2
 
0.2%
9.9 2
 
0.2%
10.6 2
 
0.2%
52.5 1
 
0.1%
88.07 1
 
0.1%
217.2 1
 
0.1%
28.0 1
 
0.1%
90.49 1
 
0.1%
Other values (45) 45
 
4.9%
(Missing) 177
 
19.1%
ValueCountFrequency (%)
0.0 691
74.5%
3.0 1
 
0.1%
3.3 3
 
0.3%
4.0 1
 
0.1%
4.2 1
 
0.1%
5.0 1
 
0.1%
9.9 2
 
0.2%
10.6 2
 
0.2%
15.99 1
 
0.1%
17.0 1
 
0.1%
ValueCountFrequency (%)
4017.09 1
0.1%
844.4 1
0.1%
495.87 1
0.1%
400.5 1
0.1%
299.87 1
0.1%
266.2 1
0.1%
217.2 1
0.1%
214.0 1
0.1%
212.73 1
0.1%
210.0 1
0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing927
Missing (%)100.0%
Memory size8.3 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing927
Missing (%)100.0%
Memory size8.3 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing927
Missing (%)100.0%
Memory size8.3 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031000003100000-117-2022-000012022-07-29<NA>3폐업2폐업2023-03-16<NA><NA><NA><NA><NA>139-230서울특별시 노원구 하계동 *** 청솔아파트서울특별시 노원구 공릉로**길 **, ***동 ***호 (하계동, 청솔아파트)1831채순규2023-03-16 14:34:37U2022-12-02 23:08:00.0식품운반업206224.106884458905.03661<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
131400003140000-117-2022-000012022-07-12<NA>1영업/정상1영업<NA><NA><NA><NA>02 6409201565.00158-808서울특별시 양천구 목동 ***-** *층 ***호서울특별시 양천구 목동중앙북로**길 *, *층 ***호 (목동)7970제이오물류 주식회사2023-07-03 17:31:56U2022-12-07 00:05:00.0식품운반업189042.400273449313.867698<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
231400003140000-117-2021-000012021-08-04<NA>3폐업2폐업2023-08-18<NA><NA><NA><NA>33.00158-848서울특별시 양천구 신월동 ****-*서울특별시 양천구 신월로 ***, ***(일부)호 (신월동)8047상석운수(주)2023-08-18 17:31:45U2022-12-07 22:00:00.0식품운반업185621.535096446032.68798<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
331400003140000-117-2018-000012018-01-05<NA>1영업/정상1영업<NA><NA><NA><NA>02 412 2980100.00158-050서울특별시 양천구 목동 ***-* 현대**타워 ****호서울특별시 양천구 목동동로 ***, 현대**타워 ****호 (목동)7997(주)월드비전종합물류2023-03-16 15:32:40U2022-12-02 23:08:00.0식품운반업188953.066831447333.569188<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
431400003140000-117-2011-000032011-10-25<NA>1영업/정상1영업<NA><NA><NA><NA>02 583 250112.00158-852서울특별시 양천구 신정동 ***-**서울특별시 양천구 신목로*길 *, *층 (신정동)8017부광상운(주)2023-03-16 15:31:57U2022-12-02 23:08:00.0식품운반업188754.040095446209.966949<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
531400003140000-117-2011-000022011-09-01<NA>1영업/정상1영업<NA><NA><NA><NA>022062991666.11158-818서울특별시 양천구 목동 ***-** 지상*층서울특별시 양천구 목동중앙서로 **, 지상*층 (목동)7964(주)우경로지스틱2023-03-16 15:31:34U2022-12-02 23:08:00.0식품운반업188227.336978447874.771387<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
632100003210000-117-2015-000052015-07-09<NA>1영업/정상1영업<NA><NA><NA><NA>070 86563588381.00137-860서울특별시 서초구 서초동 ****-** 대륭서초타워서울특별시 서초구 강남대로 ***, 대륭서초타워 **층 (서초동)6627(주)유안로지스틱스2023-07-26 15:10:36U2022-12-06 22:08:00.0식품운반업202559.861738443317.216023<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
731400003140000-117-2008-000012008-04-28<NA>1영업/정상1영업<NA><NA><NA><NA>02 2644235399.00158-801서울특별시 양천구 목동 ***-** *층서울특별시 양천구 목동중앙로**가길 ** (목동,*층)7969주식회사 목동물류2023-03-16 15:28:59U2022-12-02 23:08:00.0식품운반업189412.759482449232.318703<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
832200003220000-117-2015-000022015-07-09<NA>3폐업2폐업2023-04-06<NA><NA><NA>070 86563588247.48135-831서울특별시 강남구 논현동 ***-** KTS빌딩서울특별시 강남구 봉은사로 ***, KTS빌딩 **층 (논현동)6109(주)유안로지스틱스2023-04-06 15:24:46U2022-12-04 00:08:00.0식품운반업203074.684011445098.521749<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
932000003200000-117-2011-000012011-03-28<NA>3폐업2폐업2023-04-06<NA><NA><NA>02 826028266.00151-804서울특별시 관악구 봉천동 ***-* 하우젠빌딩*층 ***호서울특별시 관악구 은천로**길 ** (봉천동,하우젠빌딩*층 ***호)8729(주)나눔공동체2023-04-06 11:13:45U2022-12-04 00:08:00.0식품운반업195444.735051442859.116609<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
91732300003230000-117-2020-0000220200207<NA>3폐업2폐업20220927<NA><NA><NA>02 423 0525171.08138834서울특별시 송파구 방이동 ***-** 구정빌딩서울특별시 송파구 위례성대로**길 **-*, 구정빌딩 *층 (방이동)5637주식회사 팀프레시2022-09-27 17:16:19U2021-12-08 22:09:00.0식품운반업210748.374125445562.698202<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
91832200003220000-117-2020-000022020-02-07<NA>1영업/정상1영업<NA><NA><NA><NA>02 423 0525340.07135-831서울특별시 강남구 논현동 ***-**서울특별시 강남구 봉은사로**길 *-*, 지하*층 (논현동)6109주식회사 팀프레시2023-07-18 10:48:45U2022-12-06 22:00:00.0식품운반업203124.417767445144.50744<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
91931800003180000-117-2022-000032022-07-12<NA>3폐업2폐업2023-06-19<NA><NA><NA>02 85795091.50150-094서울특별시 영등포구 문래동*가 ** 리버뷰 신안인스빌서울특별시 영등포구 경인로**길 **, ***동 상가*층 (문래동*가, 리버뷰 신안인스빌)7287아워박스 주식회사2023-06-19 09:12:27U2022-12-05 22:01:00.0식품운반업190079.219797445778.895202<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
92031500003150000-117-2022-000022022-08-12<NA>1영업/정상1영업<NA><NA><NA><NA>02 53847236.60157-928서울특별시 강서구 화곡동 ****-* *층서울특별시 강서구 까치산로 ***-*, *층 (화곡동)7654(주)대한물류2024-04-16 19:46:10U2023-12-03 23:08:00.0식품운반업187020.691252450220.360286<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
92132200003220000-117-2020-0000320200330<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.00135831서울특별시 강남구 논현동 ***-**서울특별시 강남구 봉은사로**길 *-*, 지상*층 (논현동)6109주식회사 에네스푸드넷2022-10-06 16:12:34I2021-10-31 00:08:00.0식품운반업203124.417767445144.50744<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
92232100003210000-117-2021-0000420210802<NA>1영업/정상1영업<NA><NA><NA><NA>02 556 75008.00137862서울특별시 서초구 서초동 ****-* 서초월드오피스텔 ****호서울특별시 서초구 서운로 **, 서초월드오피스텔 ****호 (서초동)6732유한회사 고속화물2022-10-11 13:45:00U2021-10-30 23:03:00.0식품운반업202508.646066442625.413941<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
92332100003210000-117-2021-0000620210802<NA>1영업/정상1영업<NA><NA><NA><NA>02 808 76618.00137862서울특별시 서초구 서초동 ****-* 서초월드오피스텔 ****호서울특별시 서초구 서운로 **, 서초월드오피스텔 ****호 (서초동)6732유한회사 삼정운수2022-10-11 13:26:05U2021-10-30 23:03:00.0식품운반업202508.646066442625.413941<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
92432100003210000-117-2021-0000120210802<NA>1영업/정상1영업<NA><NA><NA><NA>02 808 76618.00137862서울특별시 서초구 서초동 ****-* 서초월드오피스텔 ****호서울특별시 서초구 서운로 **, 서초월드오피스텔 ****호 (서초동)6732한일운수 주식회사2022-10-11 13:52:33U2021-10-30 23:03:00.0식품운반업202508.646066442625.413941<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
92532100003210000-117-2021-0000320210802<NA>1영업/정상1영업<NA><NA><NA><NA>02 808 76618.00137862서울특별시 서초구 서초동 ****-* 서초월드오피스텔 ****호서울특별시 서초구 서운로 **, 서초월드오피스텔 ****호 (서초동)6732계명운수 주식회사2022-10-11 13:48:45U2021-10-30 23:03:00.0식품운반업202508.646066442625.413941<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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