Overview

Dataset statistics

Number of variables30
Number of observations34
Missing cells291
Missing cells (%)28.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.7 KiB
Average record size in memory261.9 B

Variable types

Categorical10
Numeric6
DateTime3
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
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-18516/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
축산일련번호 is highly imbalanced (67.7%)Imbalance
총인원 is highly imbalanced (67.7%)Imbalance
인허가취소일자 has 34 (100.0%) missing valuesMissing
폐업일자 has 19 (55.9%) missing valuesMissing
휴업시작일자 has 34 (100.0%) missing valuesMissing
휴업종료일자 has 34 (100.0%) missing valuesMissing
재개업일자 has 34 (100.0%) missing valuesMissing
전화번호 has 11 (32.4%) missing valuesMissing
소재지면적 has 1 (2.9%) missing valuesMissing
소재지우편번호 has 34 (100.0%) missing valuesMissing
도로명주소 has 4 (11.8%) missing valuesMissing
도로명우편번호 has 14 (41.2%) missing valuesMissing
업태구분명 has 34 (100.0%) missing valuesMissing
좌표정보(X) has 2 (5.9%) missing valuesMissing
좌표정보(Y) has 2 (5.9%) missing valuesMissing
축산물가공업구분명 has 34 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가일자 has unique valuesUnique
사업장명 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
소재지면적 has 7 (20.6%) zerosZeros

Reproduction

Analysis started2024-05-11 05:51:57.124364
Analysis finished2024-05-11 05:51:57.693546
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
3140000
34 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3140000
2nd row3140000
3rd row3140000
4th row3140000
5th row3140000

Common Values

ValueCountFrequency (%)
3140000 34
100.0%

Length

2024-05-11T14:51:57.849373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:51:58.019023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 34
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.14 × 1017
Minimum3.14 × 1017
Maximum3.14 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2024-05-11T14:51:58.185776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.14 × 1017
5-th percentile3.14 × 1017
Q13.14 × 1017
median3.14 × 1017
Q33.14 × 1017
95-th percentile3.14 × 1017
Maximum3.14 × 1017
Range330002
Interquartile range (IQR)84992

Descriptive statistics

Standard deviation73002.091
Coefficient of variation (CV)2.3249074 × 10-13
Kurtosis1.0264095
Mean3.14 × 1017
Median Absolute Deviation (MAD)35008
Skewness-0.48962476
Sum-7.770744 × 1018
Variance5.3293054 × 109
MonotonicityStrictly increasing
2024-05-11T14:51:58.395044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
314000000819900001 1
 
2.9%
314000000820180001 1
 
2.9%
314000000820120002 1
 
2.9%
314000000820140001 1
 
2.9%
314000000820140002 1
 
2.9%
314000000820140003 1
 
2.9%
314000000820150001 1
 
2.9%
314000000820170001 1
 
2.9%
314000000820180002 1
 
2.9%
314000000820110003 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
314000000819900001 1
2.9%
314000000820000001 1
2.9%
314000000820000002 1
2.9%
314000000820050001 1
2.9%
314000000820050002 1
2.9%
314000000820050003 1
2.9%
314000000820060001 1
2.9%
314000000820080001 1
2.9%
314000000820080002 1
2.9%
314000000820080003 1
2.9%
ValueCountFrequency (%)
314000000820230003 1
2.9%
314000000820230002 1
2.9%
314000000820230001 1
2.9%
314000000820220002 1
2.9%
314000000820220001 1
2.9%
314000000820180003 1
2.9%
314000000820180002 1
2.9%
314000000820180001 1
2.9%
314000000820170001 1
2.9%
314000000820150001 1
2.9%

인허가일자
Date

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size404.0 B
Minimum1990-12-13 00:00:00
Maximum2023-08-14 00:00:00
2024-05-11T14:51:58.594389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:51:58.802150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing34
Missing (%)100.0%
Memory size438.0 B

영업상태코드
Categorical

Distinct3
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size404.0 B
1
19 
3
11 
4
4 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 19
55.9%
3 11
32.4%
4 4
 
11.8%

Length

2024-05-11T14:51:58.980877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:51:59.142852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 19
55.9%
3 11
32.4%
4 4
 
11.8%

영업상태명
Categorical

Distinct3
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size404.0 B
영업/정상
19 
폐업
11 
취소/말소/만료/정지/중지
4 

Length

Max length14
Median length5
Mean length5.0882353
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 19
55.9%
폐업 11
32.4%
취소/말소/만료/정지/중지 4
 
11.8%

Length

2024-05-11T14:51:59.323547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:51:59.510222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 19
55.9%
폐업 11
32.4%
취소/말소/만료/정지/중지 4
 
11.8%

상세영업상태코드
Categorical

Distinct3
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size404.0 B
0
19 
2
11 
4
4 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 19
55.9%
2 11
32.4%
4 4
 
11.8%

Length

2024-05-11T14:51:59.697595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:51:59.898042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 19
55.9%
2 11
32.4%
4 4
 
11.8%

상세영업상태명
Categorical

Distinct3
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size404.0 B
정상
19 
폐업
11 
말소
4 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정상 19
55.9%
폐업 11
32.4%
말소 4
 
11.8%

Length

2024-05-11T14:52:00.121404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:52:00.281689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상 19
55.9%
폐업 11
32.4%
말소 4
 
11.8%

폐업일자
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)73.3%
Missing19
Missing (%)55.9%
Infinite0
Infinite (%)0.0%
Mean20184878
Minimum20130219
Maximum20210408
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2024-05-11T14:52:00.432978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20130219
5-th percentile20137358
Q120180820
median20201203
Q320201231
95-th percentile20203984
Maximum20210408
Range80189
Interquartile range (IQR)20410.5

Descriptive statistics

Standard deviation24995.671
Coefficient of variation (CV)0.0012383365
Kurtosis0.49665696
Mean20184878
Median Absolute Deviation (MAD)9205
Skewness-1.2907899
Sum3.0277317 × 108
Variance6.2478356 × 108
MonotonicityNot monotonic
2024-05-11T14:52:00.622341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
20201231 4
 
11.8%
20180911 2
 
5.9%
20180730 1
 
2.9%
20201204 1
 
2.9%
20140418 1
 
2.9%
20201211 1
 
2.9%
20130219 1
 
2.9%
20150513 1
 
2.9%
20190514 1
 
2.9%
20210408 1
 
2.9%
(Missing) 19
55.9%
ValueCountFrequency (%)
20130219 1
 
2.9%
20140418 1
 
2.9%
20150513 1
 
2.9%
20180730 1
 
2.9%
20180911 2
5.9%
20190514 1
 
2.9%
20201203 1
 
2.9%
20201204 1
 
2.9%
20201211 1
 
2.9%
20201231 4
11.8%
ValueCountFrequency (%)
20210408 1
 
2.9%
20201231 4
11.8%
20201211 1
 
2.9%
20201204 1
 
2.9%
20201203 1
 
2.9%
20190514 1
 
2.9%
20180911 2
5.9%
20180730 1
 
2.9%
20150513 1
 
2.9%
20140418 1
 
2.9%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing34
Missing (%)100.0%
Memory size438.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing34
Missing (%)100.0%
Memory size438.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing34
Missing (%)100.0%
Memory size438.0 B

전화번호
Text

MISSING 

Distinct22
Distinct (%)95.7%
Missing11
Missing (%)32.4%
Memory size404.0 B
2024-05-11T14:52:00.889214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length8.7826087
Min length7

Characters and Unicode

Total characters202
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

Unique21 ?
Unique (%)91.3%

Sample

1st row26948607
2nd row2026-3131
3rd row2691-2301
4th row26156500
5th row26421218
ValueCountFrequency (%)
1566-3057 2
 
8.7%
2659-7066 1
 
4.3%
26948607 1
 
4.3%
02-412-2980 1
 
4.3%
26431221 1
 
4.3%
4122980 1
 
4.3%
2647-5522 1
 
4.3%
2644-7997 1
 
4.3%
2163-2114 1
 
4.3%
26447997 1
 
4.3%
Other values (12) 12
52.2%
2024-05-11T14:52:01.366616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 38
18.8%
6 31
15.3%
4 20
9.9%
1 18
8.9%
0 17
8.4%
- 16
7.9%
5 14
 
6.9%
3 14
 
6.9%
7 14
 
6.9%
9 12
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 186
92.1%
Dash Punctuation 16
 
7.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 38
20.4%
6 31
16.7%
4 20
10.8%
1 18
9.7%
0 17
9.1%
5 14
 
7.5%
3 14
 
7.5%
7 14
 
7.5%
9 12
 
6.5%
8 8
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 202
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 38
18.8%
6 31
15.3%
4 20
9.9%
1 18
8.9%
0 17
8.4%
- 16
7.9%
5 14
 
6.9%
3 14
 
6.9%
7 14
 
6.9%
9 12
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 202
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 38
18.8%
6 31
15.3%
4 20
9.9%
1 18
8.9%
0 17
8.4%
- 16
7.9%
5 14
 
6.9%
3 14
 
6.9%
7 14
 
6.9%
9 12
 
5.9%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct27
Distinct (%)81.8%
Missing1
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean179.78091
Minimum0
Maximum2508.5
Zeros7
Zeros (%)20.6%
Negative0
Negative (%)0.0%
Memory size438.0 B
2024-05-11T14:52:01.590723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q113.75
median40
Q385
95-th percentile785.48
Maximum2508.5
Range2508.5
Interquartile range (IQR)71.25

Descriptive statistics

Standard deviation469.48918
Coefficient of variation (CV)2.6114518
Kurtosis19.896906
Mean179.78091
Median Absolute Deviation (MAD)35.05
Skewness4.2479089
Sum5932.77
Variance220420.09
MonotonicityNot monotonic
2024-05-11T14:52:01.794880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0.0 7
20.6%
2508.5 1
 
2.9%
30.62 1
 
2.9%
33.0 1
 
2.9%
48.0 1
 
2.9%
65.0 1
 
2.9%
30.0 1
 
2.9%
599.05 1
 
2.9%
54.75 1
 
2.9%
125.7 1
 
2.9%
Other values (17) 17
50.0%
ValueCountFrequency (%)
0.0 7
20.6%
4.95 1
 
2.9%
13.75 1
 
2.9%
22.79 1
 
2.9%
24.8 1
 
2.9%
25.0 1
 
2.9%
30.0 1
 
2.9%
30.62 1
 
2.9%
33.0 1
 
2.9%
34.0 1
 
2.9%
ValueCountFrequency (%)
2508.5 1
2.9%
969.5 1
2.9%
662.8 1
2.9%
599.05 1
2.9%
125.7 1
2.9%
117.0 1
2.9%
110.0 1
2.9%
99.0 1
2.9%
85.0 1
2.9%
72.0 1
2.9%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing34
Missing (%)100.0%
Memory size438.0 B

지번주소
Text

Distinct30
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Memory size404.0 B
2024-05-11T14:52:02.033647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length32
Mean length24.558824
Min length18

Characters and Unicode

Total characters835
Distinct characters44
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)82.4%

Sample

1st row서울특별시 양천구 신월동 **-*번지
2nd row서울특별시 양천구 목동 ***-***
3rd row서울특별시 양천구 신월동 ***-**번지
4th row서울특별시 양천구 신정동 ***-**번지
5th row서울특별시 양천구 신월동 ***-*번지 하성빌딩 *층
ValueCountFrequency (%)
서울특별시 34
20.9%
양천구 34
20.9%
19
11.7%
번지 15
9.2%
신정동 12
 
7.4%
목동 12
 
7.4%
신월동 10
 
6.1%
호 10
 
6.1%
층 6
 
3.7%
서부트럭터미널 3
 
1.8%
Other values (7) 8
 
4.9%
2024-05-11T14:52:02.546588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 198
23.7%
151
18.1%
서 37
 
4.4%
동 36
 
4.3%
특 34
 
4.1%
별 34
 
4.1%
시 34
 
4.1%
양 34
 
4.1%
천 34
 
4.1%
구 34
 
4.1%
Other values (34) 209
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 455
54.5%
Other Punctuation 198
23.7%
Space Separator 151
 
18.1%
Dash Punctuation 30
 
3.6%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 37
 
8.1%
동 36
 
7.9%
특 34
 
7.5%
별 34
 
7.5%
시 34
 
7.5%
양 34
 
7.5%
천 34
 
7.5%
구 34
 
7.5%
울 34
 
7.5%
신 22
 
4.8%
Other values (30) 122
26.8%
Other Punctuation
ValueCountFrequency (%)
* 198
100.0%
Space Separator
ValueCountFrequency (%)
151
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 455
54.5%
Common 379
45.4%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 37
 
8.1%
동 36
 
7.9%
특 34
 
7.5%
별 34
 
7.5%
시 34
 
7.5%
양 34
 
7.5%
천 34
 
7.5%
구 34
 
7.5%
울 34
 
7.5%
신 22
 
4.8%
Other values (30) 122
26.8%
Common
ValueCountFrequency (%)
* 198
52.2%
151
39.8%
- 30
 
7.9%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 455
54.5%
ASCII 380
45.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 198
52.1%
151
39.7%
- 30
 
7.9%
B 1
 
0.3%
Hangul
ValueCountFrequency (%)
서 37
 
8.1%
동 36
 
7.9%
특 34
 
7.5%
별 34
 
7.5%
시 34
 
7.5%
양 34
 
7.5%
천 34
 
7.5%
구 34
 
7.5%
울 34
 
7.5%
신 22
 
4.8%
Other values (30) 122
26.8%

도로명주소
Text

MISSING 

Distinct24
Distinct (%)80.0%
Missing4
Missing (%)11.8%
Memory size404.0 B
2024-05-11T14:52:02.834350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length37
Mean length30.3
Min length23

Characters and Unicode

Total characters909
Distinct characters60
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

Unique19 ?
Unique (%)63.3%

Sample

1st row서울특별시 양천구 가로공원로 ** (신월동)
2nd row서울특별시 양천구 남부순환로**길 * (신월동)
3rd row서울특별시 양천구 오목로**길 ** (신정동)
4th row서울특별시 양천구 신월로 *** (신월동,하성빌딩 *층)
5th row서울특별시 양천구 신월로 *** (신정동)
ValueCountFrequency (%)
서울특별시 30
16.9%
30
16.9%
양천구 30
16.9%
호 12
 
6.7%
목동 9
 
5.1%
신정동 8
 
4.5%
신월로 7
 
3.9%
신월동 7
 
3.9%
목동동로 5
 
2.8%
층 5
 
2.8%
Other values (26) 35
19.7%
2024-05-11T14:52:03.361933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 150
16.5%
148
16.3%
동 49
 
5.4%
서 33
 
3.6%
로 31
 
3.4%
신 31
 
3.4%
시 30
 
3.3%
) 30
 
3.3%
특 30
 
3.3%
( 30
 
3.3%
Other values (50) 347
38.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 524
57.6%
Other Punctuation 176
 
19.4%
Space Separator 148
 
16.3%
Close Punctuation 30
 
3.3%
Open Punctuation 30
 
3.3%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 49
 
9.4%
서 33
 
6.3%
로 31
 
5.9%
신 31
 
5.9%
시 30
 
5.7%
특 30
 
5.7%
별 30
 
5.7%
울 30
 
5.7%
구 30
 
5.7%
천 30
 
5.7%
Other values (44) 200
38.2%
Other Punctuation
ValueCountFrequency (%)
* 150
85.2%
, 26
 
14.8%
Space Separator
ValueCountFrequency (%)
148
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 524
57.6%
Common 385
42.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 49
 
9.4%
서 33
 
6.3%
로 31
 
5.9%
신 31
 
5.9%
시 30
 
5.7%
특 30
 
5.7%
별 30
 
5.7%
울 30
 
5.7%
구 30
 
5.7%
천 30
 
5.7%
Other values (44) 200
38.2%
Common
ValueCountFrequency (%)
* 150
39.0%
148
38.4%
) 30
 
7.8%
( 30
 
7.8%
, 26
 
6.8%
- 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 524
57.6%
ASCII 385
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 150
39.0%
148
38.4%
) 30
 
7.8%
( 30
 
7.8%
, 26
 
6.8%
- 1
 
0.3%
Hangul
ValueCountFrequency (%)
동 49
 
9.4%
서 33
 
6.3%
로 31
 
5.9%
신 31
 
5.9%
시 30
 
5.7%
특 30
 
5.7%
별 30
 
5.7%
울 30
 
5.7%
구 30
 
5.7%
천 30
 
5.7%
Other values (44) 200
38.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)70.0%
Missing14
Missing (%)41.2%
Infinite0
Infinite (%)0.0%
Mean8004.45
Minimum7900
Maximum8082
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2024-05-11T14:52:03.569628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7900
5-th percentile7908.55
Q17990.25
median8006
Q38047
95-th percentile8056.35
Maximum8082
Range182
Interquartile range (IQR)56.75

Descriptive statistics

Standard deviation48.226958
Coefficient of variation (CV)0.0060250183
Kurtosis0.16383637
Mean8004.45
Median Absolute Deviation (MAD)38.5
Skewness-0.6989686
Sum160089
Variance2325.8395
MonotonicityNot monotonic
2024-05-11T14:52:03.739458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
7997 4
 
11.8%
8047 3
 
8.8%
8055 2
 
5.9%
7909 1
 
2.9%
8082 1
 
2.9%
8022 1
 
2.9%
7900 1
 
2.9%
7998 1
 
2.9%
8014 1
 
2.9%
8028 1
 
2.9%
Other values (4) 4
 
11.8%
(Missing) 14
41.2%
ValueCountFrequency (%)
7900 1
 
2.9%
7909 1
 
2.9%
7946 1
 
2.9%
7964 1
 
2.9%
7970 1
 
2.9%
7997 4
11.8%
7998 1
 
2.9%
8014 1
 
2.9%
8017 1
 
2.9%
8022 1
 
2.9%
ValueCountFrequency (%)
8082 1
 
2.9%
8055 2
5.9%
8047 3
8.8%
8028 1
 
2.9%
8022 1
 
2.9%
8017 1
 
2.9%
8014 1
 
2.9%
7998 1
 
2.9%
7997 4
11.8%
7970 1
 
2.9%

사업장명
Text

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size404.0 B
2024-05-11T14:52:04.050754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length7.2352941
Min length2

Characters and Unicode

Total characters246
Distinct characters82
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

Unique34 ?
Unique (%)100.0%

Sample

1st row한국냉동운수(주)
2nd row대원냉동주식회사
3rd row새한유조(주)
4th row유신우(주)
5th row(주)이편한물류
ValueCountFrequency (%)
주식회사 2
 
5.3%
한국냉동운수(주 1
 
2.6%
대원냉동주식회사 1
 
2.6%
택수물류(주 1
 
2.6%
주)케이에이치종합물류 1
 
2.6%
상석운수 1
 
2.6%
제이오물류 1
 
2.6%
주)우경로지스틱 1
 
2.6%
주)강동물류 1
 
2.6%
부광상운(주 1
 
2.6%
Other values (27) 27
71.1%
2024-05-11T14:52:04.539494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 27
 
11.0%
( 24
 
9.8%
) 24
 
9.8%
운 12
 
4.9%
물 9
 
3.7%
류 8
 
3.3%
수 8
 
3.3%
통 6
 
2.4%
유 6
 
2.4%
이 5
 
2.0%
Other values (72) 117
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 194
78.9%
Open Punctuation 24
 
9.8%
Close Punctuation 24
 
9.8%
Space Separator 4
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 27
 
13.9%
운 12
 
6.2%
물 9
 
4.6%
류 8
 
4.1%
수 8
 
4.1%
통 6
 
3.1%
유 6
 
3.1%
이 5
 
2.6%
동 5
 
2.6%
스 4
 
2.1%
Other values (69) 104
53.6%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 194
78.9%
Common 52
 
21.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 27
 
13.9%
운 12
 
6.2%
물 9
 
4.6%
류 8
 
4.1%
수 8
 
4.1%
통 6
 
3.1%
유 6
 
3.1%
이 5
 
2.6%
동 5
 
2.6%
스 4
 
2.1%
Other values (69) 104
53.6%
Common
ValueCountFrequency (%)
( 24
46.2%
) 24
46.2%
4
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 194
78.9%
ASCII 52
 
21.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 27
 
13.9%
운 12
 
6.2%
물 9
 
4.6%
류 8
 
4.1%
수 8
 
4.1%
통 6
 
3.1%
유 6
 
3.1%
이 5
 
2.6%
동 5
 
2.6%
스 4
 
2.1%
Other values (69) 104
53.6%
ASCII
ValueCountFrequency (%)
( 24
46.2%
) 24
46.2%
4
 
7.7%

최종수정일자
Date

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size404.0 B
Minimum2005-08-01 09:35:02
Maximum2024-05-03 11:46:12
2024-05-11T14:52:05.078633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:52:05.339109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)

데이터갱신구분
Categorical

Distinct2
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
U
20 
I
14 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 20
58.8%
I 14
41.2%

Length

2024-05-11T14:52:05.598348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:52:05.833389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 20
58.8%
i 14
41.2%

데이터갱신일자
Date

Distinct18
Distinct (%)52.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T14:52:05.994365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:52:06.181143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing34
Missing (%)100.0%
Memory size438.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)71.9%
Missing2
Missing (%)5.9%
Infinite0
Infinite (%)0.0%
Mean187279.93
Minimum184325.62
Maximum189412.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2024-05-11T14:52:06.449896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184325.62
5-th percentile185104.34
Q1185675.94
median187637.3
Q3188786.55
95-th percentile189209.06
Maximum189412.76
Range5087.1433
Interquartile range (IQR)3110.6124

Descriptive statistics

Standard deviation1557.1961
Coefficient of variation (CV)0.0083148048
Kurtosis-1.3200942
Mean187279.93
Median Absolute Deviation (MAD)1315.7656
Skewness-0.27972491
Sum5992957.8
Variance2424859.6
MonotonicityNot monotonic
2024-05-11T14:52:06.662865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
188953.066831076 4
 
11.8%
185621.535095905 3
 
8.8%
185566.058732924 3
 
8.8%
189412.75948153 2
 
5.9%
185716.749050511 2
 
5.9%
187501.773031293 1
 
2.9%
187061.887641094 1
 
2.9%
189042.400273025 1
 
2.9%
188227.336977959 1
 
2.9%
188051.138558242 1
 
2.9%
Other values (13) 13
38.2%
(Missing) 2
 
5.9%
ValueCountFrequency (%)
184325.616204517 1
 
2.9%
184540.012734091 1
 
2.9%
185566.058732924 3
8.8%
185621.535095905 3
8.8%
185694.070392445 1
 
2.9%
185716.749050511 2
5.9%
186525.996950856 1
 
2.9%
187030.28019681 1
 
2.9%
187058.203490236 1
 
2.9%
187061.887641094 1
 
2.9%
ValueCountFrequency (%)
189412.75948153 2
5.9%
189042.400273025 1
 
2.9%
188953.066831076 4
11.8%
188884.075622342 1
 
2.9%
188754.040095027 1
 
2.9%
188599.819584745 1
 
2.9%
188281.881518096 1
 
2.9%
188227.336977959 1
 
2.9%
188169.180124964 1
 
2.9%
188051.138558242 1
 
2.9%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)71.9%
Missing2
Missing (%)5.9%
Infinite0
Infinite (%)0.0%
Mean447152.4
Minimum445264.23
Maximum449789.61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2024-05-11T14:52:06.863993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum445264.23
5-th percentile445686.88
Q1446175.04
median446889.99
Q3447468.87
95-th percentile449488.44
Maximum449789.61
Range4525.3785
Interquartile range (IQR)1293.8289

Descriptive statistics

Standard deviation1250.1243
Coefficient of variation (CV)0.0027957455
Kurtosis-0.22801117
Mean447152.4
Median Absolute Deviation (MAD)749.87658
Skewness0.77525974
Sum14308877
Variance1562810.8
MonotonicityNot monotonic
2024-05-11T14:52:07.137857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
447333.569187997 4
 
11.8%
446032.687979646 3
 
8.8%
446070.262510721 3
 
8.8%
449232.318702848 2
 
5.9%
445264.23483344 2
 
5.9%
447215.681564812 1
 
2.9%
446549.057387399 1
 
2.9%
449313.867697582 1
 
2.9%
447874.771386911 1
 
2.9%
449789.613381329 1
 
2.9%
Other values (13) 13
38.2%
(Missing) 2
 
5.9%
ValueCountFrequency (%)
445264.23483344 2
5.9%
446032.687979646 3
8.8%
446070.262510721 3
8.8%
446209.966949064 1
 
2.9%
446367.547334782 1
 
2.9%
446411.414327066 1
 
2.9%
446522.898418369 1
 
2.9%
446549.057387399 1
 
2.9%
446745.233545657 1
 
2.9%
446755.021580644 1
 
2.9%
ValueCountFrequency (%)
449789.613381329 1
 
2.9%
449701.802558519 1
 
2.9%
449313.867697582 1
 
2.9%
449232.318702848 2
5.9%
448667.450918409 1
 
2.9%
448149.635864725 1
 
2.9%
447874.771386911 1
 
2.9%
447333.569187997 4
11.8%
447215.681564812 1
 
2.9%
447186.888604306 1
 
2.9%

축산업무구분명
Categorical

Distinct2
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
축산물운반업
26 
<NA>
8 

Length

Max length6
Median length6
Mean length5.5294118
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
축산물운반업 26
76.5%
<NA> 8
 
23.5%

Length

2024-05-11T14:52:07.354757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:52:07.558207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
축산물운반업 26
76.5%
na 8
 
23.5%

축산물가공업구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing34
Missing (%)100.0%
Memory size438.0 B

축산일련번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
<NA>
32 
0
 
2

Length

Max length4
Median length4
Mean length3.8235294
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> 32
94.1%
0 2
 
5.9%

Length

2024-05-11T14:52:07.740402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:52:07.903971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 32
94.1%
0 2
 
5.9%

권리주체일련번호
Categorical

Distinct3
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size404.0 B
L00
19 
<NA>
8 
000
7 

Length

Max length4
Median length3
Mean length3.2352941
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowL00
2nd rowL00
3rd rowL00
4th rowL00
5th rowL00

Common Values

ValueCountFrequency (%)
L00 19
55.9%
<NA> 8
23.5%
000 7
 
20.6%

Length

2024-05-11T14:52:08.067267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:52:08.200440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
l00 19
55.9%
na 8
23.5%
000 7
 
20.6%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
<NA>
32 
0
 
2

Length

Max length4
Median length4
Mean length3.8235294
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> 32
94.1%
0 2
 
5.9%

Length

2024-05-11T14:52:08.387892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:52:08.543762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 32
94.1%
0 2
 
5.9%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
0314000031400000081990000119901213<NA>3폐업2폐업20180730<NA><NA><NA>269486072508.5<NA>서울특별시 양천구 신월동 **-*번지서울특별시 양천구 가로공원로 ** (신월동)7909한국냉동운수(주)2018-07-30 11:10:06I2018-08-31 23:59:59.0<NA>184325.616205448149.635865축산물운반업<NA><NA>L00<NA>
1314000031400000082000000120000715<NA>3폐업2폐업20201204<NA><NA><NA>2026-3131662.8<NA>서울특별시 양천구 목동 ***-***<NA><NA>대원냉동주식회사2020-12-04 18:03:47U2020-12-06 02:40:00.0<NA>188281.881518446999.721549축산물운반업<NA><NA>L00<NA>
2314000031400000082000000220001007<NA>1영업/정상0정상<NA><NA><NA><NA>2691-2301969.5<NA>서울특별시 양천구 신월동 ***-**번지서울특별시 양천구 남부순환로**길 * (신월동)<NA>새한유조(주)2005-08-02 18:04:35I2018-08-31 23:59:59.0<NA>185694.070392446411.414327축산물운반업<NA><NA>L00<NA>
3314000031400000082005000120050124<NA>3폐업2폐업20140418<NA><NA><NA><NA>0.0<NA>서울특별시 양천구 신정동 ***-**번지서울특별시 양천구 오목로**길 ** (신정동)<NA>유신우(주)2014-04-18 17:23:02I2018-08-31 23:59:59.0<NA>187058.20349446755.021581축산물운반업<NA><NA>L00<NA>
4314000031400000082005000220050801<NA>1영업/정상0정상<NA><NA><NA><NA><NA>72.0<NA>서울특별시 양천구 신월동 ***-*번지 하성빌딩 *층서울특별시 양천구 신월로 *** (신월동,하성빌딩 *층)<NA>(주)이편한물류2005-08-01 09:35:02I2018-08-31 23:59:59.0<NA>185566.058733446070.262511축산물운반업<NA><NA>L00<NA>
5314000031400000082005000320050831<NA>4취소/말소/만료/정지/중지4말소20201231<NA><NA><NA>2615650034.0<NA>서울특별시 양천구 신정동 ***<NA><NA>선진통운(주)2020-12-31 14:20:26U2021-01-02 02:40:00.0<NA><NA><NA>축산물운반업<NA><NA>L00<NA>
6314000031400000082006000120060510<NA>3폐업2폐업20201211<NA><NA><NA>26421218<NA><NA>서울특별시 양천구 신정동 ****-*서울특별시 양천구 신월로 *** (신정동)8082경성유통2020-12-11 13:07:07U2020-12-13 02:40:00.0<NA>187061.887641446549.057387축산물운반업<NA><NA>000<NA>
7314000031400000082008000120080416<NA>4취소/말소/만료/정지/중지4말소20201231<NA><NA><NA>2699-337240.0<NA>서울특별시 양천구 신정동 ***-**서울특별시 양천구 신정중앙로 ** (신정동,*층)<NA>(주)삼강월드2020-12-31 14:20:50U2021-01-02 02:40:00.0<NA>187501.773031447215.681565축산물운반업<NA><NA>L00<NA>
8314000031400000082008000220080519<NA>1영업/정상0정상<NA><NA><NA><NA>02-2644-235325.0<NA>서울특별시 양천구 목동 ***-****번지 *층<NA><NA>(주)목동물류2008-05-19 14:15:22I2018-08-31 23:59:59.0<NA>189412.759482449232.318703축산물운반업<NA><NA>L00<NA>
9314000031400000082008000320080820<NA>1영업/정상0정상<NA><NA><NA><NA>2604-267499.0<NA>서울특별시 양천구 신정동 ****-*번지 *층서울특별시 양천구 목동로*길 ** (신정동,*층)<NA>(주)엉터리2008-08-20 20:11:27I2018-08-31 23:59:59.0<NA>187772.829452446745.233546축산물운반업<NA><NA>L00<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
24314000031400000082015000120150127<NA>1영업/정상0정상<NA><NA><NA><NA>2647-552213.75<NA>서울특별시 양천구 신정동 ***-**번지서울특별시 양천구 목동동로**길 ** (신정동)8014팬지아2015-01-27 17:34:45I2018-08-31 23:59:59.0<NA>188599.819585446367.547335축산물운반업<NA><NA>000<NA>
25314000031400000082017000120170116<NA>3폐업2폐업20201203<NA><NA><NA><NA>22.79<NA>서울특별시 양천구 신월동 ***-* 오진오피스텔 ***호서울특별시 양천구 오목로 **, ***호 (신월동, 오진오피스텔)8028(주)신원물류2020-12-04 10:03:01U2020-12-06 02:40:00.0<NA>186525.996951446796.069116축산물운반업<NA><NA>L00<NA>
2631400003140000008201800012018-05-15<NA>1영업/정상0정상<NA><NA><NA><NA>4122980125.7<NA>서울특별시 양천구 목동 ***-* ****호서울특별시 양천구 목동동로 ***, 현대**타워 ****호 (목동)7997(주)월드비전종합물류2023-07-17 14:28:52U2022-12-06 23:09:00.0<NA>188953.066831447333.569188<NA><NA><NA><NA><NA>
27314000031400000082018000220100323<NA>1영업/정상0정상<NA><NA><NA><NA><NA>54.75<NA>서울특별시 양천구 신정동 ***-** *층서울특별시 양천구 신목로*길 *, *층 (신정동)8017부광상운(주)2021-05-31 16:47:41U2021-06-02 02:40:00.0<NA>188754.040095446209.966949축산물운반업<NA><NA>L00<NA>
2831400003140000008201800032018-11-15<NA>1영업/정상0정상<NA><NA><NA><NA>26431221599.05<NA>서울특별시 양천구 목동 ***-* *층서울특별시 양천구 공항대로 ***, *층 (목동)7946(주)강동물류2024-04-29 16:20:50U2023-12-05 00:01:00.0<NA>188051.138558449789.613381<NA><NA><NA><NA><NA>
2931400003140000008202200012022-07-26<NA>1영업/정상0정상<NA><NA><NA><NA><NA>30.0<NA>서울특별시 양천구 목동 ***-**서울특별시 양천구 목동중앙서로 **, *층 (목동)7964(주)우경로지스틱2023-08-18 10:27:48U2022-12-07 22:00:00.0<NA>188227.336978447874.771387<NA><NA><NA><NA><NA>
3031400003140000008202200022022-12-19<NA>1영업/정상0정상<NA><NA><NA><NA><NA>65.0<NA>서울특별시 양천구 목동 ***-** ***호서울특별시 양천구 목동중앙북로**길 *, *층 ***호 (목동)7970제이오물류 주식회사2024-05-03 11:46:12U2023-12-05 00:05:00.0<NA>189042.400273449313.867698<NA><NA><NA><NA><NA>
3131400003140000008202300012023-05-04<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 양천구 신월동 ****-* ***호서울특별시 양천구 신월로 ***, ***호 (신월동)8047상석운수2023-05-04 11:28:11I2022-12-05 00:07:00.0<NA>185621.535096446032.68798<NA><NA><NA><NA><NA>
3231400003140000008202300022023-08-02<NA>1영업/정상0정상<NA><NA><NA><NA>02-412-298048.0<NA>서울특별시 양천구 목동 ***-* 현대**타워서울특별시 양천구 목동동로 ***, 현대**타워 ****호 (목동)7997(주)케이에이치종합물류2023-08-02 11:00:24I2022-12-08 00:04:00.0<NA>188953.066831447333.569188<NA><NA><NA><NA><NA>
3331400003140000008202300032023-08-14<NA>1영업/정상0정상<NA><NA><NA><NA>1566305733.0<NA>서울특별시 양천구 신월동 ****-* ***호서울특별시 양천구 신월로 ***, ***호 (신월동)8047유일상운(주)2023-12-01 13:34:20U2022-11-02 00:03:00.0<NA>185621.535096446032.68798<NA><NA><NA><NA><NA>