Overview

Dataset statistics

Number of variables30
Number of observations38
Missing cells320
Missing cells (%)28.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.7 KiB
Average record size in memory261.5 B

Variable types

Categorical12
Numeric5
DateTime2
Unsupported7
Text4

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),축산업무구분명,축산물가공업구분명,축산일련번호,권리주체일련번호,총인원
Author중랑구
URLhttps://data.seoul.go.kr/dataList/OA-18508/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
소재지면적 is highly imbalanced (73.8%)Imbalance
인허가취소일자 has 38 (100.0%) missing valuesMissing
폐업일자 has 19 (50.0%) missing valuesMissing
휴업시작일자 has 38 (100.0%) missing valuesMissing
휴업종료일자 has 38 (100.0%) missing valuesMissing
재개업일자 has 38 (100.0%) missing valuesMissing
전화번호 has 20 (52.6%) missing valuesMissing
소재지우편번호 has 38 (100.0%) missing valuesMissing
도로명주소 has 1 (2.6%) missing valuesMissing
도로명우편번호 has 14 (36.8%) missing valuesMissing
업태구분명 has 38 (100.0%) missing valuesMissing
축산물가공업구분명 has 38 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 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
소재지우편번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
축산물가공업구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-06 13:01:49.709781
Analysis finished2024-04-06 13:01:50.164655
Duration0.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
3060000
38 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3060000
2nd row3060000
3rd row3060000
4th row3060000
5th row3060000

Common Values

ValueCountFrequency (%)
3060000 38
100.0%

Length

2024-04-06T22:01:50.272279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:01:50.412095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3060000 38
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.06 × 1017
Minimum3.06 × 1017
Maximum3.06 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2024-04-06T22:01:50.571094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.06 × 1017
5-th percentile3.06 × 1017
Q13.06 × 1017
median3.06 × 1017
Q33.06 × 1017
95-th percentile3.06 × 1017
Maximum3.06 × 1017
Range190001
Interquartile range (IQR)100032

Descriptive statistics

Standard deviation59298.083
Coefficient of variation (CV)1.9378459 × 10-13
Kurtosis-1.1666952
Mean3.06 × 1017
Median Absolute Deviation (MAD)49984
Skewness0.33761056
Sum-6.818744 × 1018
Variance3.5162627 × 109
MonotonicityStrictly increasing
2024-04-06T22:01:50.848957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
306000000820040001 1
 
2.6%
306000000820180004 1
 
2.6%
306000000820120005 1
 
2.6%
306000000820120006 1
 
2.6%
306000000820150001 1
 
2.6%
306000000820160001 1
 
2.6%
306000000820180001 1
 
2.6%
306000000820180002 1
 
2.6%
306000000820180003 1
 
2.6%
306000000820190001 1
 
2.6%
Other values (28) 28
73.7%
ValueCountFrequency (%)
306000000820040001 1
2.6%
306000000820040002 1
2.6%
306000000820050001 1
2.6%
306000000820050002 1
2.6%
306000000820060001 1
2.6%
306000000820060002 1
2.6%
306000000820060003 1
2.6%
306000000820070001 1
2.6%
306000000820080001 1
2.6%
306000000820080002 1
2.6%
ValueCountFrequency (%)
306000000820230002 1
2.6%
306000000820230001 1
2.6%
306000000820220002 1
2.6%
306000000820220001 1
2.6%
306000000820210001 1
2.6%
306000000820200002 1
2.6%
306000000820200001 1
2.6%
306000000820190001 1
2.6%
306000000820180004 1
2.6%
306000000820180003 1
2.6%

인허가일자
Date

Distinct34
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Memory size436.0 B
Minimum2004-09-15 00:00:00
Maximum2023-08-16 00:00:00
2024-04-06T22:01:51.041815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:01:51.234881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing38
Missing (%)100.0%
Memory size474.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
3
19 
1
19 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 19
50.0%
1 19
50.0%

Length

2024-04-06T22:01:51.462022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:01:51.620431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 19
50.0%
1 19
50.0%

영업상태명
Categorical

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
폐업
19 
영업/정상
19 

Length

Max length5
Median length3.5
Mean length3.5
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 19
50.0%
영업/정상 19
50.0%

Length

2024-04-06T22:01:52.158723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:01:52.367187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 19
50.0%
영업/정상 19
50.0%

상세영업상태코드
Categorical

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
2
19 
0
19 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row0

Common Values

ValueCountFrequency (%)
2 19
50.0%
0 19
50.0%

Length

2024-04-06T22:01:52.536669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:01:52.664989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 19
50.0%
0 19
50.0%

상세영업상태명
Categorical

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
폐업
19 
정상
19 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 19
50.0%
정상 19
50.0%

Length

2024-04-06T22:01:52.850701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:01:53.037784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 19
50.0%
정상 19
50.0%

폐업일자
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)89.5%
Missing19
Missing (%)50.0%
Infinite0
Infinite (%)0.0%
Mean20148500
Minimum20050810
Maximum20220114
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2024-04-06T22:01:53.218508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20050810
5-th percentile20059174
Q120130671
median20141112
Q320180258
95-th percentile20220107
Maximum20220114
Range169304
Interquartile range (IQR)49587.5

Descriptive statistics

Standard deviation45911.169
Coefficient of variation (CV)0.0022786396
Kurtosis0.35013709
Mean20148500
Median Absolute Deviation (MAD)20595
Skewness-0.38813477
Sum3.828215 × 108
Variance2.1078355 × 109
MonotonicityNot monotonic
2024-04-06T22:01:53.407722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
20130819 2
 
5.3%
20141112 2
 
5.3%
20131101 1
 
2.6%
20220114 1
 
2.6%
20150325 1
 
2.6%
20150331 1
 
2.6%
20210623 1
 
2.6%
20130523 1
 
2.6%
20050810 1
 
2.6%
20180212 1
 
2.6%
Other values (7) 7
 
18.4%
(Missing) 19
50.0%
ValueCountFrequency (%)
20050810 1
2.6%
20060103 1
2.6%
20120517 1
2.6%
20121026 1
2.6%
20130523 1
2.6%
20130819 2
5.3%
20131101 1
2.6%
20141112 2
5.3%
20150325 1
2.6%
20150331 1
2.6%
ValueCountFrequency (%)
20220114 1
2.6%
20220106 1
2.6%
20210623 1
2.6%
20181210 1
2.6%
20180305 1
2.6%
20180212 1
2.6%
20170327 1
2.6%
20150331 1
2.6%
20150325 1
2.6%
20141112 2
5.3%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing38
Missing (%)100.0%
Memory size474.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing38
Missing (%)100.0%
Memory size474.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing38
Missing (%)100.0%
Memory size474.0 B

전화번호
Text

MISSING 

Distinct15
Distinct (%)83.3%
Missing20
Missing (%)52.6%
Memory size436.0 B
2024-04-06T22:01:53.687672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length9.3888889
Min length7

Characters and Unicode

Total characters169
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

Unique12 ?
Unique (%)66.7%

Sample

1st row973-9944
2nd row2207-7455
3rd row452-0301
4th row34231454
5th row34223888
ValueCountFrequency (%)
973-9944 2
 
11.1%
22073151 2
 
11.1%
02-438-6700 2
 
11.1%
2207-7455 1
 
5.6%
452-0301 1
 
5.6%
34231454 1
 
5.6%
34223888 1
 
5.6%
9572837 1
 
5.6%
3422-3888 1
 
5.6%
070-8828-6606 1
 
5.6%
Other values (5) 5
27.8%
2024-04-06T22:01:54.240525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 27
16.0%
0 20
11.8%
- 19
11.2%
3 18
10.7%
4 17
10.1%
8 14
8.3%
7 12
7.1%
1 12
7.1%
6 12
7.1%
9 9
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 150
88.8%
Dash Punctuation 19
 
11.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 27
18.0%
0 20
13.3%
3 18
12.0%
4 17
11.3%
8 14
9.3%
7 12
8.0%
1 12
8.0%
6 12
8.0%
9 9
 
6.0%
5 9
 
6.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 169
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 27
16.0%
0 20
11.8%
- 19
11.2%
3 18
10.7%
4 17
10.1%
8 14
8.3%
7 12
7.1%
1 12
7.1%
6 12
7.1%
9 9
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 169
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 27
16.0%
0 20
11.8%
- 19
11.2%
3 18
10.7%
4 17
10.1%
8 14
8.3%
7 12
7.1%
1 12
7.1%
6 12
7.1%
9 9
 
5.3%

소재지면적
Categorical

IMBALANCE 

Distinct4
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Memory size436.0 B
0.0
35 
16.5
 
1
44.88
 
1
15.15
 
1

Length

Max length5
Median length3
Mean length3.1315789
Min length3

Unique

Unique3 ?
Unique (%)7.9%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 35
92.1%
16.5 1
 
2.6%
44.88 1
 
2.6%
15.15 1
 
2.6%

Length

2024-04-06T22:01:54.467048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:01:54.668453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 35
92.1%
16.5 1
 
2.6%
44.88 1
 
2.6%
15.15 1
 
2.6%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing38
Missing (%)100.0%
Memory size474.0 B

지번주소
Text

Distinct28
Distinct (%)73.7%
Missing0
Missing (%)0.0%
Memory size436.0 B
2024-04-06T22:01:54.921661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length30
Mean length24.105263
Min length18

Characters and Unicode

Total characters916
Distinct characters55
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)55.3%

Sample

1st row서울특별시 중랑구 묵동 ***-**번지 원창빌딩 *층
2nd row서울특별시 중랑구 망우동 ***-*번지
3rd row서울특별시 중랑구 면목동 ****번지
4th row서울특별시 중랑구 면목동 ****번지 두원@***
5th row서울특별시 중랑구 면목동 ****번지 두원@***
ValueCountFrequency (%)
서울특별시 38
21.6%
중랑구 38
21.6%
번지 24
13.6%
14
 
8.0%
묵동 13
 
7.4%
면목동 12
 
6.8%
신내동 5
 
2.8%
호 5
 
2.8%
층 5
 
2.8%
망우동 4
 
2.3%
Other values (14) 18
10.2%
2024-04-06T22:01:55.405320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 203
22.2%
165
18.0%
동 41
 
4.5%
시 39
 
4.3%
중 39
 
4.3%
서 38
 
4.1%
특 38
 
4.1%
별 38
 
4.1%
랑 38
 
4.1%
구 38
 
4.1%
Other values (45) 239
26.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 516
56.3%
Other Punctuation 205
 
22.4%
Space Separator 165
 
18.0%
Dash Punctuation 30
 
3.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 41
 
7.9%
시 39
 
7.6%
중 39
 
7.6%
서 38
 
7.4%
특 38
 
7.4%
별 38
 
7.4%
랑 38
 
7.4%
구 38
 
7.4%
울 38
 
7.4%
지 26
 
5.0%
Other values (41) 143
27.7%
Other Punctuation
ValueCountFrequency (%)
* 203
99.0%
@ 2
 
1.0%
Space Separator
ValueCountFrequency (%)
165
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 516
56.3%
Common 400
43.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 41
 
7.9%
시 39
 
7.6%
중 39
 
7.6%
서 38
 
7.4%
특 38
 
7.4%
별 38
 
7.4%
랑 38
 
7.4%
구 38
 
7.4%
울 38
 
7.4%
지 26
 
5.0%
Other values (41) 143
27.7%
Common
ValueCountFrequency (%)
* 203
50.7%
165
41.2%
- 30
 
7.5%
@ 2
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 516
56.3%
ASCII 400
43.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 203
50.7%
165
41.2%
- 30
 
7.5%
@ 2
 
0.5%
Hangul
ValueCountFrequency (%)
동 41
 
7.9%
시 39
 
7.6%
중 39
 
7.6%
서 38
 
7.4%
특 38
 
7.4%
별 38
 
7.4%
랑 38
 
7.4%
구 38
 
7.4%
울 38
 
7.4%
지 26
 
5.0%
Other values (41) 143
27.7%

도로명주소
Text

MISSING 

Distinct30
Distinct (%)81.1%
Missing1
Missing (%)2.6%
Memory size436.0 B
2024-04-06T22:01:55.754979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length42
Mean length29.567568
Min length21

Characters and Unicode

Total characters1094
Distinct characters69
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)67.6%

Sample

1st row서울특별시 중랑구 동일로***길 ** (묵동,원창빌딩 *층)
2nd row서울특별시 중랑구 동일로 *** (면목동)
3rd row서울특별시 중랑구 동일로 *** (면목동,두원@***)
4th row서울특별시 중랑구 동일로 *** (면목동,두원@***)
5th row서울특별시 중랑구 공릉로 ** (묵동)
ValueCountFrequency (%)
서울특별시 37
17.5%
중랑구 37
17.5%
36
17.1%
면목동 10
 
4.7%
호 9
 
4.3%
묵동 8
 
3.8%
동일로***길 6
 
2.8%
층 6
 
2.8%
중랑역로 5
 
2.4%
신내동 4
 
1.9%
Other values (32) 53
25.1%
2024-04-06T22:01:56.357806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 196
17.9%
174
15.9%
동 55
 
5.0%
중 44
 
4.0%
랑 43
 
3.9%
시 38
 
3.5%
서 37
 
3.4%
( 37
 
3.4%
특 37
 
3.4%
별 37
 
3.4%
Other values (59) 396
36.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 615
56.2%
Other Punctuation 226
 
20.7%
Space Separator 174
 
15.9%
Open Punctuation 37
 
3.4%
Close Punctuation 37
 
3.4%
Dash Punctuation 5
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 55
 
8.9%
중 44
 
7.2%
랑 43
 
7.0%
시 38
 
6.2%
서 37
 
6.0%
특 37
 
6.0%
별 37
 
6.0%
구 37
 
6.0%
울 37
 
6.0%
로 37
 
6.0%
Other values (52) 213
34.6%
Other Punctuation
ValueCountFrequency (%)
* 196
86.7%
, 28
 
12.4%
@ 2
 
0.9%
Space Separator
ValueCountFrequency (%)
174
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 615
56.2%
Common 479
43.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 55
 
8.9%
중 44
 
7.2%
랑 43
 
7.0%
시 38
 
6.2%
서 37
 
6.0%
특 37
 
6.0%
별 37
 
6.0%
구 37
 
6.0%
울 37
 
6.0%
로 37
 
6.0%
Other values (52) 213
34.6%
Common
ValueCountFrequency (%)
* 196
40.9%
174
36.3%
( 37
 
7.7%
) 37
 
7.7%
, 28
 
5.8%
- 5
 
1.0%
@ 2
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 615
56.2%
ASCII 479
43.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 196
40.9%
174
36.3%
( 37
 
7.7%
) 37
 
7.7%
, 28
 
5.8%
- 5
 
1.0%
@ 2
 
0.4%
Hangul
ValueCountFrequency (%)
동 55
 
8.9%
중 44
 
7.2%
랑 43
 
7.0%
시 38
 
6.2%
서 37
 
6.0%
특 37
 
6.0%
별 37
 
6.0%
구 37
 
6.0%
울 37
 
6.0%
로 37
 
6.0%
Other values (52) 213
34.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)70.8%
Missing14
Missing (%)36.8%
Infinite0
Infinite (%)0.0%
Mean2105.9167
Minimum2009
Maximum2256
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2024-04-06T22:01:56.572967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2009
5-th percentile2010
Q12018
median2096
Q32181
95-th percentile2233
Maximum2256
Range247
Interquartile range (IQR)163

Descriptive statistics

Standard deviation81.912953
Coefficient of variation (CV)0.038896579
Kurtosis-1.172683
Mean2105.9167
Median Absolute Deviation (MAD)78
Skewness0.36964964
Sum50542
Variance6709.7319
MonotonicityNot monotonic
2024-04-06T22:01:56.781154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
2010 3
 
7.9%
2018 3
 
7.9%
2233 2
 
5.3%
2187 2
 
5.3%
2067 2
 
5.3%
2211 1
 
2.6%
2009 1
 
2.6%
2119 1
 
2.6%
2098 1
 
2.6%
2068 1
 
2.6%
Other values (7) 7
18.4%
(Missing) 14
36.8%
ValueCountFrequency (%)
2009 1
 
2.6%
2010 3
7.9%
2018 3
7.9%
2055 1
 
2.6%
2067 2
5.3%
2068 1
 
2.6%
2094 1
 
2.6%
2098 1
 
2.6%
2119 1
 
2.6%
2122 1
 
2.6%
ValueCountFrequency (%)
2256 1
2.6%
2233 2
5.3%
2211 1
2.6%
2187 2
5.3%
2179 1
2.6%
2147 1
2.6%
2126 1
2.6%
2122 1
2.6%
2119 1
2.6%
2098 1
2.6%

사업장명
Text

Distinct34
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Memory size436.0 B
2024-04-06T22:01:57.116658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.5
Min length2

Characters and Unicode

Total characters209
Distinct characters86
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)81.6%

Sample

1st row사랑운수
2nd row동명축산
3rd row남양주급식영업점
4th row동부급식영업점
5th row남양주급식영업점
ValueCountFrequency (%)
개별화물 3
 
7.7%
남양주급식영업점 2
 
5.1%
선진c&f 2
 
5.1%
서울우유 1
 
2.6%
상진축산 1
 
2.6%
드림개별화물 1
 
2.6%
주)인하지엘에스 1
 
2.6%
주)청명물류 1
 
2.6%
동아운수 1
 
2.6%
정수남 1
 
2.6%
Other values (25) 25
64.1%
2024-04-06T22:01:57.740024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 11
 
5.3%
) 9
 
4.3%
( 9
 
4.3%
물 8
 
3.8%
스 6
 
2.9%
우 5
 
2.4%
화 5
 
2.4%
드 5
 
2.4%
통 5
 
2.4%
유 5
 
2.4%
Other values (76) 141
67.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 182
87.1%
Close Punctuation 9
 
4.3%
Open Punctuation 9
 
4.3%
Uppercase Letter 6
 
2.9%
Other Punctuation 2
 
1.0%
Space Separator 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 11
 
6.0%
물 8
 
4.4%
스 6
 
3.3%
우 5
 
2.7%
화 5
 
2.7%
드 5
 
2.7%
통 5
 
2.7%
유 5
 
2.7%
식 4
 
2.2%
상 4
 
2.2%
Other values (68) 124
68.1%
Uppercase Letter
ValueCountFrequency (%)
C 2
33.3%
F 2
33.3%
H 1
16.7%
Y 1
16.7%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 182
87.1%
Common 21
 
10.0%
Latin 6
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 11
 
6.0%
물 8
 
4.4%
스 6
 
3.3%
우 5
 
2.7%
화 5
 
2.7%
드 5
 
2.7%
통 5
 
2.7%
유 5
 
2.7%
식 4
 
2.2%
상 4
 
2.2%
Other values (68) 124
68.1%
Common
ValueCountFrequency (%)
) 9
42.9%
( 9
42.9%
& 2
 
9.5%
1
 
4.8%
Latin
ValueCountFrequency (%)
C 2
33.3%
F 2
33.3%
H 1
16.7%
Y 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 182
87.1%
ASCII 27
 
12.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 11
 
6.0%
물 8
 
4.4%
스 6
 
3.3%
우 5
 
2.7%
화 5
 
2.7%
드 5
 
2.7%
통 5
 
2.7%
유 5
 
2.7%
식 4
 
2.2%
상 4
 
2.2%
Other values (68) 124
68.1%
ASCII
ValueCountFrequency (%)
) 9
33.3%
( 9
33.3%
C 2
 
7.4%
& 2
 
7.4%
F 2
 
7.4%
1
 
3.7%
H 1
 
3.7%
Y 1
 
3.7%

최종수정일자
Date

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
Minimum2005-08-10 17:24:07
Maximum2024-04-03 20:12:29
2024-04-06T22:01:57.954775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:01:58.144886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)

데이터갱신구분
Categorical

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
I
26 
U
12 

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 26
68.4%
U 12
31.6%

Length

2024-04-06T22:01:58.328809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:01:58.508906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 26
68.4%
u 12
31.6%

데이터갱신일자
Categorical

Distinct17
Distinct (%)44.7%
Missing0
Missing (%)0.0%
Memory size436.0 B
2018-08-31 23:59:59.0
21 
2022-01-07 02:40:00.0
 
2
2021-05-22 02:40:00.0
 
1
2022-01-08 02:40:00.0
 
1
2022-11-30 22:09:00.0
 
1
Other values (12)
12 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique15 ?
Unique (%)39.5%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 21
55.3%
2022-01-07 02:40:00.0 2
 
5.3%
2021-05-22 02:40:00.0 1
 
2.6%
2022-01-08 02:40:00.0 1
 
2.6%
2022-11-30 22:09:00.0 1
 
2.6%
2022-11-30 22:02:00.0 1
 
2.6%
2023-12-04 00:05:00.0 1
 
2.6%
2021-06-25 02:40:00.0 1
 
2.6%
2018-12-12 02:40:00.0 1
 
2.6%
2020-03-27 00:23:21.0 1
 
2.6%
Other values (7) 7
 
18.4%

Length

2024-04-06T22:01:58.681288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
23:59:59.0 22
28.9%
2018-08-31 21
27.6%
02:40:00.0 7
 
9.2%
2022-01-07 2
 
2.6%
23:08:00.0 2
 
2.6%
2022-11-30 2
 
2.6%
2020-11-22 1
 
1.3%
2018-09-18 1
 
1.3%
2022-12-05 1
 
1.3%
21:01:00.0 1
 
1.3%
Other values (16) 16
21.1%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing38
Missing (%)100.0%
Memory size474.0 B

좌표정보(X)
Real number (ℝ)

Distinct28
Distinct (%)73.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean207372.11
Minimum206459.71
Maximum209646.14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2024-04-06T22:01:58.873524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum206459.71
5-th percentile206498.17
Q1206756.12
median206901.74
Q3207918.51
95-th percentile209030.34
Maximum209646.14
Range3186.4312
Interquartile range (IQR)1162.3918

Descriptive statistics

Standard deviation905.94294
Coefficient of variation (CV)0.0043686827
Kurtosis-0.087746966
Mean207372.11
Median Absolute Deviation (MAD)221.33612
Skewness1.1165174
Sum7880140.1
Variance820732.62
MonotonicityNot monotonic
2024-04-06T22:01:59.040541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
206756.119639205 4
 
10.5%
206979.383643338 3
 
7.9%
206699.691110426 2
 
5.3%
206719.70562841 2
 
5.3%
208446.504307378 2
 
5.3%
206854.785745041 2
 
5.3%
206901.742619683 2
 
5.3%
206787.260836106 1
 
2.6%
208943.875735407 1
 
2.6%
207539.91324528 1
 
2.6%
Other values (18) 18
47.4%
ValueCountFrequency (%)
206459.711379355 1
 
2.6%
206492.087474895 1
 
2.6%
206499.240717749 1
 
2.6%
206658.172408801 1
 
2.6%
206661.121885737 1
 
2.6%
206699.691110426 2
5.3%
206719.70562841 2
5.3%
206756.119639205 4
10.5%
206787.260836106 1
 
2.6%
206791.432825 1
 
2.6%
ValueCountFrequency (%)
209646.142554388 1
2.6%
209187.412590441 1
2.6%
209002.623003889 1
2.6%
208946.061006488 1
2.6%
208943.875735407 1
2.6%
208657.879148925 1
2.6%
208446.504307378 2
5.3%
208161.194053026 1
2.6%
207990.479257211 1
2.6%
207702.608098093 1
2.6%

좌표정보(Y)
Real number (ℝ)

Distinct28
Distinct (%)73.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean455155.69
Minimum452075.95
Maximum457240.39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2024-04-06T22:01:59.239253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum452075.95
5-th percentile452350.91
Q1453943.25
median455319.05
Q3456210.16
95-th percentile457236.32
Maximum457240.39
Range5164.4417
Interquartile range (IQR)2266.9111

Descriptive statistics

Standard deviation1595.2915
Coefficient of variation (CV)0.0035049358
Kurtosis-1.0314114
Mean455155.69
Median Absolute Deviation (MAD)1289.866
Skewness-0.34891265
Sum17295916
Variance2544954.9
MonotonicityNot monotonic
2024-04-06T22:01:59.451596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
456184.929130937 4
 
10.5%
452350.907653737 3
 
7.9%
456210.158404317 2
 
5.3%
453614.377409231 2
 
5.3%
456048.562552443 2
 
5.3%
457127.125369398 2
 
5.3%
457236.317706626 2
 
5.3%
454645.570410455 1
 
2.6%
454101.765182163 1
 
2.6%
454951.719136925 1
 
2.6%
Other values (18) 18
47.4%
ValueCountFrequency (%)
452075.948613979 1
 
2.6%
452350.907653737 3
7.9%
453342.721236556 1
 
2.6%
453563.525593799 1
 
2.6%
453601.225753212 1
 
2.6%
453614.377409231 2
5.3%
453938.79366 1
 
2.6%
453956.608125762 1
 
2.6%
454101.765182163 1
 
2.6%
454183.448277214 1
 
2.6%
ValueCountFrequency (%)
457240.390322006 1
 
2.6%
457236.317706626 2
5.3%
457183.637796144 1
 
2.6%
457127.125369398 2
5.3%
457009.141589479 1
 
2.6%
456996.056603203 1
 
2.6%
456251.99918147 1
 
2.6%
456210.158404317 2
5.3%
456184.929130937 4
10.5%
456048.562552443 2
5.3%

축산업무구분명
Categorical

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
축산물운반업
32 
<NA>
6 

Length

Max length6
Median length6
Mean length5.6842105
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
축산물운반업 32
84.2%
<NA> 6
 
15.8%

Length

2024-04-06T22:01:59.707716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:01:59.909162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
축산물운반업 32
84.2%
na 6
 
15.8%

축산물가공업구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing38
Missing (%)100.0%
Memory size474.0 B

축산일련번호
Categorical

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
<NA>
33 
0
5 

Length

Max length4
Median length4
Mean length3.6052632
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> 33
86.8%
0 5
 
13.2%

Length

2024-04-06T22:02:00.097946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:02:00.256635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 33
86.8%
0 5
 
13.2%

권리주체일련번호
Categorical

Distinct3
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size436.0 B
000
27 
<NA>
6 
L00
5 

Length

Max length4
Median length3
Mean length3.1578947
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row000
2nd row000
3rd row000
4th row000
5th row000

Common Values

ValueCountFrequency (%)
000 27
71.1%
<NA> 6
 
15.8%
L00 5
 
13.2%

Length

2024-04-06T22:02:00.413851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:02:00.583576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
000 27
71.1%
na 6
 
15.8%
l00 5
 
13.2%

총인원
Categorical

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
<NA>
33 
0
5 

Length

Max length4
Median length4
Mean length3.6052632
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> 33
86.8%
0 5
 
13.2%

Length

2024-04-06T22:02:00.755803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:02:00.937414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 33
86.8%
0 5
 
13.2%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
0306000030600000082004000120040915<NA>3폐업2폐업20050810<NA><NA><NA>973-99440.0<NA>서울특별시 중랑구 묵동 ***-**번지 원창빌딩 *층서울특별시 중랑구 동일로***길 ** (묵동,원창빌딩 *층)<NA>사랑운수2005-08-10 17:24:07I2018-08-31 23:59:59.0<NA>206756.119639456184.929131축산물운반업<NA><NA>000<NA>
1306000030600000082004000220040915<NA>3폐업2폐업20180212<NA><NA><NA>2207-74550.0<NA>서울특별시 중랑구 망우동 ***-*번지<NA><NA>동명축산2018-02-12 14:08:54I2018-08-31 23:59:59.0<NA>209002.623004455427.791874축산물운반업<NA><NA>000<NA>
2306000030600000082005000120050415<NA>3폐업2폐업20060103<NA><NA><NA><NA>0.0<NA>서울특별시 중랑구 면목동 ****번지서울특별시 중랑구 동일로 *** (면목동)<NA>남양주급식영업점2006-01-03 11:45:09I2018-08-31 23:59:59.0<NA>206979.383643452350.907654축산물운반업<NA><NA>000<NA>
3306000030600000082005000220050415<NA>3폐업2폐업20170327<NA><NA><NA><NA>0.0<NA>서울특별시 중랑구 면목동 ****번지 두원@***서울특별시 중랑구 동일로 *** (면목동,두원@***)<NA>동부급식영업점2017-03-27 11:19:04I2018-08-31 23:59:59.0<NA>206979.383643452350.907654축산물운반업<NA><NA>000<NA>
4306000030600000082006000120060104<NA>1영업/정상0정상<NA><NA><NA><NA>452-03010.0<NA>서울특별시 중랑구 면목동 ****번지 두원@***서울특별시 중랑구 동일로 *** (면목동,두원@***)<NA>남양주급식영업점2006-01-04 09:46:03I2018-08-31 23:59:59.0<NA>206979.383643452350.907654축산물운반업<NA><NA>000<NA>
5306000030600000082006000220060407<NA>3폐업2폐업20181210<NA><NA><NA>342314540.0<NA>서울특별시 중랑구 묵동 ***-**번지서울특별시 중랑구 공릉로 ** (묵동)2018한소닉2018-12-10 10:49:19U2018-12-12 02:40:00.0<NA>206901.74262457236.317707축산물운반업<NA><NA>000<NA>
6306000030600000082006000320060427<NA>3폐업2폐업20220106<NA><NA><NA><NA>0.0<NA>서울특별시 중랑구 묵동 ***-** *층서울특별시 중랑구 중랑천로 *** (묵동,*층)<NA>제일유통2022-01-06 17:37:16U2022-01-08 02:40:00.0<NA>206459.711379457009.141589축산물운반업<NA>00000
7306000030600000082007000120071112<NA>3폐업2폐업20130819<NA><NA><NA>342238880.0<NA>서울특별시 중랑구 묵동 ***-**번지 *층서울특별시 중랑구 공릉로 **, *층 (묵동)2018푸드강북유통2013-08-19 11:27:12I2018-08-31 23:59:59.0<NA>206901.74262457236.317707축산물운반업<NA><NA>000<NA>
8306000030600000082008000120080124<NA>3폐업2폐업20121026<NA><NA><NA>95728370.0<NA>서울특별시 중랑구 묵동 ***-**번지 지하*층서울특별시 중랑구 중랑역로 *** (묵동,지하*층)<NA>대세축산유통2012-10-26 15:52:58I2018-08-31 23:59:59.0<NA>206699.69111456210.158404축산물운반업<NA><NA>000<NA>
9306000030600000082008000220080220<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 중랑구 면목동 ***-**번지서울특별시 중랑구 겸재로*길 ** (면목동)<NA>서준푸드2008-02-20 13:33:17I2018-08-31 23:59:59.0<NA>206791.432825453938.79366축산물운반업<NA><NA>000<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
28306000030600000082018000320180913<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 중랑구 신내동 ***서울특별시 중랑구 봉화산로 ***, ***동 ****호 (신내동, 동성아파트)2067서울우유2021-05-20 10:22:43U2021-05-22 02:40:00.0<NA>208446.504307456048.562552축산물운반업<NA><NA>000<NA>
29306000030600000082018000420180918<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 중랑구 중화동 ***-*번지서울특별시 중랑구 동일로***길 **-** (중화동)2094개별화물2018-09-18 13:54:31U2018-09-18 23:59:59.0<NA>207080.617439455210.313364축산물운반업<NA><NA>000<NA>
30306000030600000082019000120190607<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 중랑구 망우동 ***-*서울특별시 중랑구 망우로**가길 ** (망우동)2179네이쳐스2022-01-05 15:52:52U2022-01-07 02:40:00.0<NA>209187.41259455126.903044축산물운반업<NA>00000
31306000030600000082020000120200325<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 중랑구 면목동 ***-**번지 대광맨션서울특별시 중랑구 겸재로**가길 **, ***호 (면목동, 대광맨션)2147정수남2020-03-25 12:53:22I2020-03-27 00:23:21.0<NA>207250.05772453956.608126축산물운반업<NA><NA>000<NA>
32306000030600000082020000220201120<NA>1영업/정상0정상<NA><NA><NA><NA>02-438-02220.0<NA>서울특별시 중랑구 면목동 ***-**서울특별시 중랑구 망우로**길 **-** (면목동)2126주식회사 진선우유통2020-11-20 09:10:08I2020-11-22 00:23:08.0<NA>206499.240718454346.975422축산물운반업<NA><NA>L00<NA>
33306000030600000082021000120210224<NA>3폐업2폐업20220114<NA><NA><NA><NA>0.0<NA>서울특별시 중랑구 망우동 ***-**서울특별시 중랑구 용마산로**길 **-** (망우동)2187정상천2022-01-14 14:17:50U2022-01-16 02:40:00.0<NA>208946.061006454183.448277축산물운반업<NA>00000
34306000030600000082022000120220127<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 중랑구 망우동 ***-**서울특별시 중랑구 용마산로**길 **-**(망우동)2187용마화물2022-01-27 14:52:23I2022-01-29 00:22:39.0<NA>208943.875735454101.765182축산물운반업<NA>00000
35306000030600000082022000220220602<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 중랑구 상봉동 ***-**서울특별시 중랑구 망우로 ***, *층 (상봉동)2122위드물류(주)2022-08-29 17:31:55U2021-12-07 21:01:00.0<NA>206787.260836454645.57041<NA><NA><NA><NA><NA>
3630600003060000008202300012023-06-16<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 중랑구 신내동 *** 동성아파트서울특별시 중랑구 봉화산로 ***, ***동 ***호 (신내동, 동성아파트)2067YH물류(해윤)2023-06-16 15:19:28I2022-12-05 23:08:00.0<NA>208446.504307456048.562552<NA><NA><NA><NA><NA>
3730600003060000008202300022023-08-16<NA>1영업/정상0정상<NA><NA><NA><NA><NA>15.15<NA>서울특별시 중랑구 신내동 *** 신내 데시앙포레서울특별시 중랑구 신내역로 ***, ***동 **층 *호 (신내동, 신내 데시앙포레)2055제이엔알2023-08-16 15:07:04I2022-12-07 23:08:00.0<NA>209646.142554456996.056603<NA><NA><NA><NA><NA>