Overview

Dataset statistics

Number of variables38
Number of observations74
Missing cells766
Missing cells (%)27.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory23.8 KiB
Average record size in memory328.8 B

Variable types

Categorical14
Text7
DateTime4
Unsupported6
Numeric7

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),일반창고_동수,일반창고_면적,냉동,냉장창고_동수,냉동,냉장창고_면적,보관장소_면적,종업원수,시설/장비현황,보관요율,법인여부명,업태_보관및창고업,업태_운송및택배업,업태_판매업,업태_제조업
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16147/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태_제조업 is highly imbalanced (50.6%)Imbalance
인허가취소일자 has 74 (100.0%) missing valuesMissing
폐업일자 has 60 (81.1%) missing valuesMissing
휴업시작일자 has 74 (100.0%) missing valuesMissing
휴업종료일자 has 74 (100.0%) missing valuesMissing
재개업일자 has 74 (100.0%) missing valuesMissing
전화번호 has 2 (2.7%) missing valuesMissing
소재지면적 has 74 (100.0%) missing valuesMissing
소재지우편번호 has 7 (9.5%) missing valuesMissing
도로명주소 has 1 (1.4%) missing valuesMissing
도로명우편번호 has 48 (64.9%) missing valuesMissing
업태구분명 has 74 (100.0%) missing valuesMissing
좌표정보(X) has 8 (10.8%) missing valuesMissing
좌표정보(Y) has 8 (10.8%) missing valuesMissing
일반창고_면적 has 36 (48.6%) missing valuesMissing
냉동,냉장창고_면적 has 36 (48.6%) missing valuesMissing
종업원수 has 36 (48.6%) missing valuesMissing
시설/장비현황 has 36 (48.6%) missing valuesMissing
보관요율 has 44 (59.5%) missing valuesMissing
관리번호 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
소재지면적 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
일반창고_면적 has 2 (2.7%) zerosZeros
냉동,냉장창고_면적 has 33 (44.6%) zerosZeros

Reproduction

Analysis started2024-04-29 18:54:12.320694
Analysis finished2024-04-29 18:54:13.124588
Duration0.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size724.0 B
6110000
74 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6110000
2nd row6110000
3rd row6110000
4th row6110000
5th row6110000

Common Values

ValueCountFrequency (%)
6110000 74
100.0%

Length

2024-04-30T03:54:13.189641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:54:13.265589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6110000 74
100.0%

관리번호
Text

UNIQUE 

Distinct74
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size724.0 B
2024-04-30T03:54:13.420376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length16
Min length16

Characters and Unicode

Total characters1184
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)100.0%

Sample

1st row2012S61100000008
2nd row2012S61100000021
3rd row2023S61100000001
4th row2022S61100000008
5th row2022S61100000005
ValueCountFrequency (%)
2012s61100000008 1
 
1.4%
2012s61100000023 1
 
1.4%
2012s61100000037 1
 
1.4%
2017s61100000002 1
 
1.4%
2014s61100000002 1
 
1.4%
2014s61100000001 1
 
1.4%
2012s61100000017 1
 
1.4%
2012s61100000015 1
 
1.4%
2012s61100000011 1
 
1.4%
2012s61100000010 1
 
1.4%
Other values (64) 64
86.5%
2024-04-30T03:54:13.706923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 561
47.4%
1 232
19.6%
2 172
 
14.5%
6 80
 
6.8%
S 74
 
6.2%
3 24
 
2.0%
4 16
 
1.4%
7 8
 
0.7%
5 7
 
0.6%
8 5
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1110
93.8%
Uppercase Letter 74
 
6.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 561
50.5%
1 232
20.9%
2 172
 
15.5%
6 80
 
7.2%
3 24
 
2.2%
4 16
 
1.4%
7 8
 
0.7%
5 7
 
0.6%
8 5
 
0.5%
9 5
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
S 74
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1110
93.8%
Latin 74
 
6.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 561
50.5%
1 232
20.9%
2 172
 
15.5%
6 80
 
7.2%
3 24
 
2.2%
4 16
 
1.4%
7 8
 
0.7%
5 7
 
0.6%
8 5
 
0.5%
9 5
 
0.5%
Latin
ValueCountFrequency (%)
S 74
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1184
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 561
47.4%
1 232
19.6%
2 172
 
14.5%
6 80
 
6.8%
S 74
 
6.2%
3 24
 
2.0%
4 16
 
1.4%
7 8
 
0.7%
5 7
 
0.6%
8 5
 
0.4%

인허가일자
Date

Distinct41
Distinct (%)55.4%
Missing0
Missing (%)0.0%
Memory size724.0 B
Minimum2012-06-18 00:00:00
Maximum2024-02-06 00:00:00
2024-04-30T03:54:13.825211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T03:54:13.934000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing74
Missing (%)100.0%
Memory size798.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size724.0 B
3
38 
1
36 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 38
51.4%
1 36
48.6%

Length

2024-04-30T03:54:14.049158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:54:14.132965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 38
51.4%
1 36
48.6%

영업상태명
Categorical

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size724.0 B
폐업
38 
영업/정상
36 

Length

Max length5
Median length2
Mean length3.4594595
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 38
51.4%
영업/정상 36
48.6%

Length

2024-04-30T03:54:14.220077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:54:14.309323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 38
51.4%
영업/정상 36
48.6%

상세영업상태코드
Categorical

Distinct3
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size724.0 B
3
37 
1
36 
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
3 37
50.0%
1 36
48.6%
4 1
 
1.4%

Length

2024-04-30T03:54:14.396157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:54:14.481495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 37
50.0%
1 36
48.6%
4 1
 
1.4%

상세영업상태명
Categorical

Distinct3
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size724.0 B
폐업
37 
등록
36 
해산
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 37
50.0%
등록 36
48.6%
해산 1
 
1.4%

Length

2024-04-30T03:54:14.574773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:54:14.680199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 37
50.0%
등록 36
48.6%
해산 1
 
1.4%

폐업일자
Date

MISSING 

Distinct13
Distinct (%)92.9%
Missing60
Missing (%)81.1%
Memory size724.0 B
Minimum2014-05-21 00:00:00
Maximum2023-08-01 00:00:00
2024-04-30T03:54:14.762431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T03:54:14.847374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing74
Missing (%)100.0%
Memory size798.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing74
Missing (%)100.0%
Memory size798.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing74
Missing (%)100.0%
Memory size798.0 B

전화번호
Real number (ℝ)

MISSING 

Distinct64
Distinct (%)88.9%
Missing2
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean4.6133934 × 108
Minimum23222508
Maximum7.0514721 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size798.0 B
2024-04-30T03:54:14.955773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23222508
5-th percentile24642641
Q128847982
median2.2251177 × 108
Q32.3662384 × 108
95-th percentile5.5278636 × 108
Maximum7.0514721 × 109
Range7.0282495 × 109
Interquartile range (IQR)2.0777586 × 108

Descriptive statistics

Standard deviation1.3885059 × 109
Coefficient of variation (CV)3.0097279
Kurtosis20.175113
Mean4.6133934 × 108
Median Absolute Deviation (MAD)38996538
Skewness4.6291927
Sum3.3216433 × 1010
Variance1.9279486 × 1018
MonotonicityNot monotonic
2024-04-30T03:54:15.074856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
261508309 6
 
8.1%
220953072 2
 
2.7%
29492566 2
 
2.7%
28670927 2
 
2.7%
7048588400 1
 
1.4%
218997659 1
 
1.4%
28606100 1
 
1.4%
28555291 1
 
1.4%
226603730 1
 
1.4%
24510640 1
 
1.4%
Other values (54) 54
73.0%
(Missing) 2
 
2.7%
ValueCountFrequency (%)
23222508 1
1.4%
24510640 1
1.4%
24543355 1
1.4%
24636264 1
1.4%
24647859 1
1.4%
24694225 1
1.4%
24980141 1
1.4%
25142675 1
1.4%
25780068 1
1.4%
25898842 1
1.4%
ValueCountFrequency (%)
7051472054 1
 
1.4%
7048588400 1
 
1.4%
7048000335 1
 
1.4%
707559099 1
 
1.4%
426154124 1
 
1.4%
269196825 1
 
1.4%
264301057 1
 
1.4%
264264306 1
 
1.4%
263001114 1
 
1.4%
261508309 6
8.1%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing74
Missing (%)100.0%
Memory size798.0 B

소재지우편번호
Text

MISSING 

Distinct46
Distinct (%)68.7%
Missing7
Missing (%)9.5%
Memory size724.0 B
2024-04-30T03:54:15.268759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.7910448
Min length5

Characters and Unicode

Total characters388
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

Unique37 ?
Unique (%)55.2%

Sample

1st row153802
2nd row07505
3rd row04508
4th row05842
5th row05842
ValueCountFrequency (%)
05842 7
 
10.4%
153803 5
 
7.5%
133120 4
 
6.0%
153802 3
 
4.5%
152895 3
 
4.5%
157-240 2
 
3.0%
132801 2
 
3.0%
157240 2
 
3.0%
137893 2
 
3.0%
157863 1
 
1.5%
Other values (36) 36
53.7%
2024-04-30T03:54:15.568510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 64
16.5%
0 61
15.7%
5 52
13.4%
8 44
11.3%
3 43
11.1%
2 40
10.3%
7 30
7.7%
4 22
 
5.7%
9 15
 
3.9%
6 9
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 380
97.9%
Dash Punctuation 8
 
2.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 64
16.8%
0 61
16.1%
5 52
13.7%
8 44
11.6%
3 43
11.3%
2 40
10.5%
7 30
7.9%
4 22
 
5.8%
9 15
 
3.9%
6 9
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 388
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 64
16.5%
0 61
15.7%
5 52
13.4%
8 44
11.3%
3 43
11.1%
2 40
10.3%
7 30
7.7%
4 22
 
5.7%
9 15
 
3.9%
6 9
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 388
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 64
16.5%
0 61
15.7%
5 52
13.4%
8 44
11.3%
3 43
11.1%
2 40
10.3%
7 30
7.7%
4 22
 
5.7%
9 15
 
3.9%
6 9
 
2.3%

지번주소
Text

Distinct68
Distinct (%)91.9%
Missing0
Missing (%)0.0%
Memory size724.0 B
2024-04-30T03:54:15.815673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length35
Mean length25.243243
Min length17

Characters and Unicode

Total characters1868
Distinct characters120
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)89.2%

Sample

1st row서울특별시 금천구 가산동 345번지 1호
2nd row서울특별시 강서구 공항동 1373-5 물류창고(ACT화물창고1층A창고)
3rd row서울특별시 중구 만리동1가 35-1 DHL강북물류센타
4th row서울특별시 송파구 장지동 875번지 서울복합물류
5th row서울특별시 송파구 장지동 875번지 서울복합물류 A동 601호
ValueCountFrequency (%)
서울특별시 74
 
20.3%
강서구 15
 
4.1%
금천구 12
 
3.3%
가산동 11
 
3.0%
장지동 10
 
2.7%
875번지 10
 
2.7%
서울복합물류 10
 
2.7%
송파구 10
 
2.7%
성동구 7
 
1.9%
영등포구 7
 
1.9%
Other values (126) 198
54.4%
2024-04-30T03:54:16.182786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
325
 
17.4%
서 106
 
5.7%
동 96
 
5.1%
울 84
 
4.5%
구 82
 
4.4%
시 76
 
4.1%
지 74
 
4.0%
별 74
 
4.0%
특 74
 
4.0%
번 64
 
3.4%
Other values (110) 813
43.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1207
64.6%
Space Separator 325
 
17.4%
Decimal Number 299
 
16.0%
Uppercase Letter 17
 
0.9%
Dash Punctuation 13
 
0.7%
Close Punctuation 3
 
0.2%
Open Punctuation 3
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 106
 
8.8%
동 96
 
8.0%
울 84
 
7.0%
구 82
 
6.8%
시 76
 
6.3%
지 74
 
6.1%
별 74
 
6.1%
특 74
 
6.1%
번 64
 
5.3%
가 34
 
2.8%
Other values (88) 443
36.7%
Decimal Number
ValueCountFrequency (%)
2 47
15.7%
1 45
15.1%
3 45
15.1%
5 35
11.7%
6 28
9.4%
7 26
8.7%
8 24
8.0%
4 21
7.0%
9 18
 
6.0%
0 10
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
C 5
29.4%
A 5
29.4%
D 2
 
11.8%
T 2
 
11.8%
L 1
 
5.9%
H 1
 
5.9%
B 1
 
5.9%
Space Separator
ValueCountFrequency (%)
325
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1207
64.6%
Common 644
34.5%
Latin 17
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 106
 
8.8%
동 96
 
8.0%
울 84
 
7.0%
구 82
 
6.8%
시 76
 
6.3%
지 74
 
6.1%
별 74
 
6.1%
특 74
 
6.1%
번 64
 
5.3%
가 34
 
2.8%
Other values (88) 443
36.7%
Common
ValueCountFrequency (%)
325
50.5%
2 47
 
7.3%
1 45
 
7.0%
3 45
 
7.0%
5 35
 
5.4%
6 28
 
4.3%
7 26
 
4.0%
8 24
 
3.7%
4 21
 
3.3%
9 18
 
2.8%
Other values (5) 30
 
4.7%
Latin
ValueCountFrequency (%)
C 5
29.4%
A 5
29.4%
D 2
 
11.8%
T 2
 
11.8%
L 1
 
5.9%
H 1
 
5.9%
B 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1207
64.6%
ASCII 661
35.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
325
49.2%
2 47
 
7.1%
1 45
 
6.8%
3 45
 
6.8%
5 35
 
5.3%
6 28
 
4.2%
7 26
 
3.9%
8 24
 
3.6%
4 21
 
3.2%
9 18
 
2.7%
Other values (12) 47
 
7.1%
Hangul
ValueCountFrequency (%)
서 106
 
8.8%
동 96
 
8.0%
울 84
 
7.0%
구 82
 
6.8%
시 76
 
6.3%
지 74
 
6.1%
별 74
 
6.1%
특 74
 
6.1%
번 64
 
5.3%
가 34
 
2.8%
Other values (88) 443
36.7%

도로명주소
Text

MISSING 

Distinct64
Distinct (%)87.7%
Missing1
Missing (%)1.4%
Memory size724.0 B
2024-04-30T03:54:16.438619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length41
Mean length29.136986
Min length21

Characters and Unicode

Total characters2127
Distinct characters146
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

Unique60 ?
Unique (%)82.2%

Sample

1st row서울특별시 금천구 디지털로 154 (가산동)
2nd row서울특별시 강서구 하늘길 247, 물류창고(ACT화물창고1층A창고) (공항동)
3rd row서울특별시 중구 만리재로37길 5, DHL강북물류센타 1동 B1,1,2층 (만리동1가)
4th row서울특별시 송파구 송파대로 55, 서울복합물류 C동 5층(장지동)
5th row서울특별시 송파구 송파대로 55, 서울복합물류 A동 601호(장지동)
ValueCountFrequency (%)
서울특별시 73
 
18.2%
강서구 15
 
3.8%
금천구 12
 
3.0%
55 10
 
2.5%
송파대로 10
 
2.5%
가산동 10
 
2.5%
송파구 10
 
2.5%
서울복합물류 7
 
1.8%
영등포구 7
 
1.8%
가산디지털2로 7
 
1.8%
Other values (158) 239
59.8%
2024-04-30T03:54:16.804129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
327
 
15.4%
서 107
 
5.0%
동 99
 
4.7%
울 83
 
3.9%
구 81
 
3.8%
( 76
 
3.6%
) 76
 
3.6%
시 75
 
3.5%
특 73
 
3.4%
별 73
 
3.4%
Other values (136) 1057
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1314
61.8%
Space Separator 327
 
15.4%
Decimal Number 281
 
13.2%
Open Punctuation 76
 
3.6%
Close Punctuation 76
 
3.6%
Other Punctuation 29
 
1.4%
Uppercase Letter 18
 
0.8%
Dash Punctuation 5
 
0.2%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 107
 
8.1%
동 99
 
7.5%
울 83
 
6.3%
구 81
 
6.2%
시 75
 
5.7%
특 73
 
5.6%
별 73
 
5.6%
로 71
 
5.4%
가 42
 
3.2%
산 38
 
2.9%
Other values (112) 572
43.5%
Decimal Number
ValueCountFrequency (%)
1 63
22.4%
5 48
17.1%
2 43
15.3%
3 27
9.6%
6 22
 
7.8%
0 19
 
6.8%
4 19
 
6.8%
7 17
 
6.0%
8 15
 
5.3%
9 8
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
A 4
22.2%
C 4
22.2%
B 3
16.7%
F 2
11.1%
D 2
11.1%
T 1
 
5.6%
L 1
 
5.6%
H 1
 
5.6%
Space Separator
ValueCountFrequency (%)
327
100.0%
Open Punctuation
ValueCountFrequency (%)
( 76
100.0%
Close Punctuation
ValueCountFrequency (%)
) 76
100.0%
Other Punctuation
ValueCountFrequency (%)
, 29
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1314
61.8%
Common 794
37.3%
Latin 19
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 107
 
8.1%
동 99
 
7.5%
울 83
 
6.3%
구 81
 
6.2%
시 75
 
5.7%
특 73
 
5.6%
별 73
 
5.6%
로 71
 
5.4%
가 42
 
3.2%
산 38
 
2.9%
Other values (112) 572
43.5%
Common
ValueCountFrequency (%)
327
41.2%
( 76
 
9.6%
) 76
 
9.6%
1 63
 
7.9%
5 48
 
6.0%
2 43
 
5.4%
, 29
 
3.7%
3 27
 
3.4%
6 22
 
2.8%
0 19
 
2.4%
Other values (5) 64
 
8.1%
Latin
ValueCountFrequency (%)
A 4
21.1%
C 4
21.1%
B 3
15.8%
F 2
10.5%
D 2
10.5%
T 1
 
5.3%
L 1
 
5.3%
H 1
 
5.3%
c 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1314
61.8%
ASCII 813
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
327
40.2%
( 76
 
9.3%
) 76
 
9.3%
1 63
 
7.7%
5 48
 
5.9%
2 43
 
5.3%
, 29
 
3.6%
3 27
 
3.3%
6 22
 
2.7%
0 19
 
2.3%
Other values (14) 83
 
10.2%
Hangul
ValueCountFrequency (%)
서 107
 
8.1%
동 99
 
7.5%
울 83
 
6.3%
구 81
 
6.2%
시 75
 
5.7%
특 73
 
5.6%
별 73
 
5.6%
로 71
 
5.4%
가 42
 
3.2%
산 38
 
2.9%
Other values (112) 572
43.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct16
Distinct (%)61.5%
Missing48
Missing (%)64.9%
Infinite0
Infinite (%)0.0%
Mean5726.8077
Minimum1014
Maximum8503
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size798.0 B
2024-04-30T03:54:16.913763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1014
5-th percentile2393.75
Q14784
median5842
Q37102.25
95-th percentile7529.5
Maximum8503
Range7489
Interquartile range (IQR)2318.25

Descriptive statistics

Standard deviation1722.0181
Coefficient of variation (CV)0.30069424
Kurtosis1.4841123
Mean5726.8077
Median Absolute Deviation (MAD)1198.5
Skewness-1.0342466
Sum148897
Variance2965346.2
MonotonicityNot monotonic
2024-04-30T03:54:17.016144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
5842 9
 
12.2%
7505 2
 
2.7%
4428 2
 
2.7%
7522 1
 
1.4%
6803 1
 
1.4%
6771 1
 
1.4%
7217 1
 
1.4%
1886 1
 
1.4%
4508 1
 
1.4%
4779 1
 
1.4%
Other values (6) 6
 
8.1%
(Missing) 48
64.9%
ValueCountFrequency (%)
1014 1
 
1.4%
1886 1
 
1.4%
3917 1
 
1.4%
4428 2
 
2.7%
4508 1
 
1.4%
4779 1
 
1.4%
4799 1
 
1.4%
5842 9
12.2%
6771 1
 
1.4%
6803 1
 
1.4%
ValueCountFrequency (%)
8503 1
 
1.4%
7532 1
 
1.4%
7522 1
 
1.4%
7505 2
 
2.7%
7217 1
 
1.4%
7202 1
 
1.4%
6803 1
 
1.4%
6771 1
 
1.4%
5842 9
12.2%
4799 1
 
1.4%

사업장명
Text

UNIQUE 

Distinct74
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size724.0 B
2024-04-30T03:54:17.219168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length17.5
Mean length13.175676
Min length4

Characters and Unicode

Total characters975
Distinct characters170
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)100.0%

Sample

1st row롯데글로벌로지스(주) 서울구로지점
2nd row(주)발렉스 특수물류
3rd row유피에스에스씨에스코리아(주)
4th row쿠팡로지스틱스서비스 유한회사 (송파 캠프)
5th row머스크컨트랙트로지스틱스코리아(주)
ValueCountFrequency (%)
주식회사 8
 
6.3%
쿠팡로지스틱스서비스 7
 
5.5%
유한회사 5
 
3.9%
롯데글로벌로지스(주 4
 
3.1%
주)한진 4
 
3.1%
씨제이대한통운(주 4
 
3.1%
씨제이지엘에스(주 3
 
2.4%
한솔로지스틱스(주 3
 
2.4%
롯데로지스틱스(주 3
 
2.4%
서울남부지점 2
 
1.6%
Other values (82) 84
66.1%
2024-04-30T03:54:17.551505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 63
 
6.5%
( 59
 
6.1%
주 59
 
6.1%
) 58
 
5.9%
54
 
5.5%
지 34
 
3.5%
로 30
 
3.1%
한 23
 
2.4%
터 23
 
2.4%
서 22
 
2.3%
Other values (160) 550
56.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 797
81.7%
Open Punctuation 59
 
6.1%
Close Punctuation 58
 
5.9%
Space Separator 54
 
5.5%
Decimal Number 7
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 63
 
7.9%
주 59
 
7.4%
지 34
 
4.3%
로 30
 
3.8%
한 23
 
2.9%
터 23
 
2.9%
서 22
 
2.8%
센 21
 
2.6%
이 20
 
2.5%
사 19
 
2.4%
Other values (154) 483
60.6%
Decimal Number
ValueCountFrequency (%)
1 5
71.4%
3 1
 
14.3%
7 1
 
14.3%
Open Punctuation
ValueCountFrequency (%)
( 59
100.0%
Close Punctuation
ValueCountFrequency (%)
) 58
100.0%
Space Separator
ValueCountFrequency (%)
54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 797
81.7%
Common 178
 
18.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 63
 
7.9%
주 59
 
7.4%
지 34
 
4.3%
로 30
 
3.8%
한 23
 
2.9%
터 23
 
2.9%
서 22
 
2.8%
센 21
 
2.6%
이 20
 
2.5%
사 19
 
2.4%
Other values (154) 483
60.6%
Common
ValueCountFrequency (%)
( 59
33.1%
) 58
32.6%
54
30.3%
1 5
 
2.8%
3 1
 
0.6%
7 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 797
81.7%
ASCII 178
 
18.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 63
 
7.9%
주 59
 
7.4%
지 34
 
4.3%
로 30
 
3.8%
한 23
 
2.9%
터 23
 
2.9%
서 22
 
2.8%
센 21
 
2.6%
이 20
 
2.5%
사 19
 
2.4%
Other values (154) 483
60.6%
ASCII
ValueCountFrequency (%)
( 59
33.1%
) 58
32.6%
54
30.3%
1 5
 
2.8%
3 1
 
0.6%
7 1
 
0.6%

최종수정일자
Date

UNIQUE 

Distinct74
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size724.0 B
Minimum2013-03-04 17:14:10
Maximum2024-03-06 14:08:21
2024-04-30T03:54:17.675654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T03:54:17.792843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size724.0 B
U
42 
I
32 

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 (%)
U 42
56.8%
I 32
43.2%

Length

2024-04-30T03:54:17.908860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:54:18.194242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 42
56.8%
i 32
43.2%

데이터갱신일자
Date

Distinct34
Distinct (%)45.9%
Missing0
Missing (%)0.0%
Memory size724.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-03 00:08:00
2024-04-30T03:54:18.283470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T03:54:18.388742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing74
Missing (%)100.0%
Memory size798.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct48
Distinct (%)72.7%
Missing8
Missing (%)10.8%
Infinite0
Infinite (%)0.0%
Mean194025.81
Minimum182974.85
Maximum210857
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size798.0 B
2024-04-30T03:54:18.494255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182974.85
5-th percentile182974.85
Q1186550.35
median190257.46
Q3203426.09
95-th percentile210096.79
Maximum210857
Range27882.15
Interquartile range (IQR)16875.735

Descriptive statistics

Standard deviation8986.8703
Coefficient of variation (CV)0.046317911
Kurtosis-1.2406418
Mean194025.81
Median Absolute Deviation (MAD)6591.927
Skewness0.46559052
Sum12805703
Variance80763838
MonotonicityNot monotonic
2024-04-30T03:54:18.600656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
182974.850127567 6
 
8.1%
210857.0 4
 
5.4%
189208.076361179 3
 
4.1%
185346.474167215 3
 
4.1%
189372.681522711 3
 
4.1%
189578.962415014 2
 
2.7%
203301.847003968 2
 
2.7%
205426.539610564 2
 
2.7%
185583.534294451 2
 
2.7%
203252.909483212 1
 
1.4%
Other values (38) 38
51.4%
(Missing) 8
 
10.8%
ValueCountFrequency (%)
182974.850127567 6
8.1%
183007.220061564 1
 
1.4%
183656.849521557 1
 
1.4%
183674.21081987 1
 
1.4%
183914.938310002 1
 
1.4%
185346.474167215 3
4.1%
185346.474170202 1
 
1.4%
185583.534294451 2
 
2.7%
186223.731478589 1
 
1.4%
187530.220523848 1
 
1.4%
ValueCountFrequency (%)
210857.0 4
5.4%
207816.150341549 1
 
1.4%
205583.478361767 1
 
1.4%
205426.852991761 1
 
1.4%
205426.539610564 2
2.7%
205388.693108378 1
 
1.4%
205131.802637307 1
 
1.4%
204871.625958952 1
 
1.4%
204506.257672262 1
 
1.4%
204199.156989282 1
 
1.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct49
Distinct (%)74.2%
Missing8
Missing (%)10.8%
Infinite0
Infinite (%)0.0%
Mean447229.8
Minimum439561.99
Maximum464598.79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size798.0 B
2024-04-30T03:54:18.725549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum439561.99
5-th percentile440116.67
Q1442193.95
median447051.18
Q3450419.68
95-th percentile457981.58
Maximum464598.79
Range25036.793
Interquartile range (IQR)8225.7329

Descriptive statistics

Standard deviation5827.0907
Coefficient of variation (CV)0.013029299
Kurtosis0.92002722
Mean447229.8
Median Absolute Deviation (MAD)4136.7891
Skewness0.92418645
Sum29517167
Variance33954986
MonotonicityNot monotonic
2024-04-30T03:54:18.850014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
450419.684560487 6
 
8.1%
441446.0 4
 
5.4%
442193.951625785 3
 
4.1%
443218.645815417 3
 
4.1%
441433.526777708 3
 
4.1%
454129.858577368 2
 
2.7%
439561.993971648 2
 
2.7%
452292.441240545 2
 
2.7%
440074.205886207 1
 
1.4%
442240.604273101 1
 
1.4%
Other values (39) 39
52.7%
(Missing) 8
 
10.8%
ValueCountFrequency (%)
439561.993971648 2
2.7%
439850.278304857 1
 
1.4%
440074.205886207 1
 
1.4%
440244.063361575 1
 
1.4%
441190.9991286 1
 
1.4%
441299.303727005 1
 
1.4%
441433.526777708 3
4.1%
441446.0 4
5.4%
441583.577484134 1
 
1.4%
441616.460710064 1
 
1.4%
ValueCountFrequency (%)
464598.787343683 1
1.4%
464552.486156478 1
1.4%
460403.858685434 1
1.4%
458009.51865216 1
1.4%
457897.781977757 1
1.4%
454129.858577368 2
2.7%
452292.441240545 2
2.7%
451794.187683343 1
1.4%
451741.544790262 1
1.4%
450756.389026636 1
1.4%

일반창고_동수
Categorical

Distinct6
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size724.0 B
<NA>
36 
1
27 
0
4 
4
 
3
3
 
2

Length

Max length4
Median length1
Mean length2.4594595
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 36
48.6%
1 27
36.5%
0 4
 
5.4%
4 3
 
4.1%
3 2
 
2.7%
2 2
 
2.7%

Length

2024-04-30T03:54:18.956255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:54:19.060021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 36
48.6%
1 27
36.5%
0 4
 
5.4%
4 3
 
4.1%
3 2
 
2.7%
2 2
 
2.7%

일반창고_면적
Real number (ℝ)

MISSING  ZEROS 

Distinct37
Distinct (%)97.4%
Missing36
Missing (%)48.6%
Infinite0
Infinite (%)0.0%
Mean8642.7713
Minimum0
Maximum107504.03
Zeros2
Zeros (%)2.7%
Negative0
Negative (%)0.0%
Memory size798.0 B
2024-04-30T03:54:19.159703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile969.425
Q11626.3975
median2469.06
Q36785.4925
95-th percentile31557.441
Maximum107504.03
Range107504.03
Interquartile range (IQR)5159.095

Descriptive statistics

Standard deviation18534.111
Coefficient of variation (CV)2.1444639
Kurtosis22.920705
Mean8642.7713
Median Absolute Deviation (MAD)1255.56
Skewness4.521034
Sum328425.31
Variance3.4351327 × 108
MonotonicityNot monotonic
2024-04-30T03:54:19.275101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0.0 2
 
2.7%
1659.17 1
 
1.4%
3557.0 1
 
1.4%
1203.0 1
 
1.4%
5228.28 1
 
1.4%
5270.79 1
 
1.4%
4653.1 1
 
1.4%
1991.4 1
 
1.4%
2380.17 1
 
1.4%
2557.95 1
 
1.4%
Other values (27) 27
36.5%
(Missing) 36
48.6%
ValueCountFrequency (%)
0.0 2
2.7%
1140.5 1
1.4%
1203.0 1
1.4%
1224.0 1
1.4%
1321.88 1
1.4%
1433.77 1
1.4%
1454.55 1
1.4%
1606.0 1
1.4%
1617.53 1
1.4%
1653.0 1
1.4%
ValueCountFrequency (%)
107504.03 1
1.4%
43072.0 1
1.4%
29525.46 1
1.4%
17078.0 1
1.4%
13968.0 1
1.4%
13516.93 1
1.4%
12584.99 1
1.4%
9695.0 1
1.4%
8362.0 1
1.4%
6984.16 1
1.4%

냉동,냉장창고_동수
Categorical

Distinct5
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size724.0 B
<NA>
36 
0
33 
1
 
2
3
 
2
2
 
1

Length

Max length4
Median length1
Mean length2.4594595
Min length1

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 36
48.6%
0 33
44.6%
1 2
 
2.7%
3 2
 
2.7%
2 1
 
1.4%

Length

2024-04-30T03:54:19.412624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:54:19.522804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 36
48.6%
0 33
44.6%
1 2
 
2.7%
3 2
 
2.7%
2 1
 
1.4%

냉동,냉장창고_면적
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)15.8%
Missing36
Missing (%)48.6%
Infinite0
Infinite (%)0.0%
Mean1131.8108
Minimum0
Maximum23371.96
Zeros33
Zeros (%)44.6%
Negative0
Negative (%)0.0%
Memory size798.0 B
2024-04-30T03:54:19.599128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5824.0275
Maximum23371.96
Range23371.96
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4091.9874
Coefficient of variation (CV)3.6154342
Kurtosis24.92539
Mean1131.8108
Median Absolute Deviation (MAD)0
Skewness4.7866091
Sum43008.81
Variance16744361
MonotonicityNot monotonic
2024-04-30T03:54:19.677203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0.0 33
44.6%
8855.85 1
 
1.4%
2251.0 1
 
1.4%
23371.96 1
 
1.4%
3241.0 1
 
1.4%
5289.0 1
 
1.4%
(Missing) 36
48.6%
ValueCountFrequency (%)
0.0 33
44.6%
2251.0 1
 
1.4%
3241.0 1
 
1.4%
5289.0 1
 
1.4%
8855.85 1
 
1.4%
23371.96 1
 
1.4%
ValueCountFrequency (%)
23371.96 1
 
1.4%
8855.85 1
 
1.4%
5289.0 1
 
1.4%
3241.0 1
 
1.4%
2251.0 1
 
1.4%
0.0 33
44.6%

보관장소_면적
Categorical

Distinct3
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size724.0 B
0
37 
<NA>
36 
5166
 
1

Length

Max length4
Median length2.5
Mean length2.5
Min length1

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 37
50.0%
<NA> 36
48.6%
5166 1
 
1.4%

Length

2024-04-30T03:54:19.768976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:54:19.856903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 37
50.0%
na 36
48.6%
5166 1
 
1.4%

종업원수
Real number (ℝ)

MISSING 

Distinct25
Distinct (%)65.8%
Missing36
Missing (%)48.6%
Infinite0
Infinite (%)0.0%
Mean81.342105
Minimum1
Maximum1300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size798.0 B
2024-04-30T03:54:19.947242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14.25
median8.5
Q330
95-th percentile384.9
Maximum1300
Range1299
Interquartile range (IQR)25.75

Descriptive statistics

Standard deviation252.67384
Coefficient of variation (CV)3.1063105
Kurtosis17.467574
Mean81.342105
Median Absolute Deviation (MAD)6.5
Skewness4.1672364
Sum3091
Variance63844.069
MonotonicityNot monotonic
2024-04-30T03:54:20.055560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
2 5
 
6.8%
8 4
 
5.4%
1 3
 
4.1%
5 3
 
4.1%
30 2
 
2.7%
9 2
 
2.7%
39 1
 
1.4%
100 1
 
1.4%
4 1
 
1.4%
7 1
 
1.4%
Other values (15) 15
20.3%
(Missing) 36
48.6%
ValueCountFrequency (%)
1 3
4.1%
2 5
6.8%
3 1
 
1.4%
4 1
 
1.4%
5 3
4.1%
6 1
 
1.4%
7 1
 
1.4%
8 4
5.4%
9 2
 
2.7%
10 1
 
1.4%
ValueCountFrequency (%)
1300 1
1.4%
900 1
1.4%
294 1
1.4%
100 1
1.4%
81 1
1.4%
47 1
1.4%
39 1
1.4%
38 1
1.4%
36 1
1.4%
30 2
2.7%

시설/장비현황
Text

MISSING 

Distinct27
Distinct (%)71.1%
Missing36
Missing (%)48.6%
Memory size724.0 B
2024-04-30T03:54:20.206720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14.5
Mean length7.2631579
Min length1

Characters and Unicode

Total characters276
Distinct characters53
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

Unique24 ?
Unique (%)63.2%

Sample

1st row컨베이어, 랙, 지게차,
2nd row컨베이어
3rd row랙설치, 지게차
4th row지게차
5th row지게차3대, 자동포장기
ValueCountFrequency (%)
지게차 14
21.9%
랙 13
20.3%
컨베이어 11
17.2%
화물용승강기 2
 
3.1%
지게차3대 2
 
3.1%
4대 2
 
3.1%
자동화창고 1
 
1.6%
파렛트 1
 
1.6%
지게차4대 1
 
1.6%
지게차2대 1
 
1.6%
Other values (16) 16
25.0%
2024-04-30T03:54:20.498244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 27
 
9.8%
27
 
9.8%
지 22
 
8.0%
게 22
 
8.0%
차 22
 
8.0%
랙 15
 
5.4%
이 13
 
4.7%
컨 12
 
4.3%
어 12
 
4.3%
베 12
 
4.3%
Other values (43) 92
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 213
77.2%
Other Punctuation 27
 
9.8%
Space Separator 27
 
9.8%
Decimal Number 9
 
3.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 22
 
10.3%
게 22
 
10.3%
차 22
 
10.3%
랙 15
 
7.0%
이 13
 
6.1%
컨 12
 
5.6%
어 12
 
5.6%
베 12
 
5.6%
대 10
 
4.7%
기 10
 
4.7%
Other values (35) 63
29.6%
Decimal Number
ValueCountFrequency (%)
4 3
33.3%
3 2
22.2%
2 1
 
11.1%
5 1
 
11.1%
7 1
 
11.1%
6 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
, 27
100.0%
Space Separator
ValueCountFrequency (%)
27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 213
77.2%
Common 63
 
22.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 22
 
10.3%
게 22
 
10.3%
차 22
 
10.3%
랙 15
 
7.0%
이 13
 
6.1%
컨 12
 
5.6%
어 12
 
5.6%
베 12
 
5.6%
대 10
 
4.7%
기 10
 
4.7%
Other values (35) 63
29.6%
Common
ValueCountFrequency (%)
, 27
42.9%
27
42.9%
4 3
 
4.8%
3 2
 
3.2%
2 1
 
1.6%
5 1
 
1.6%
7 1
 
1.6%
6 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 213
77.2%
ASCII 63
 
22.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 27
42.9%
27
42.9%
4 3
 
4.8%
3 2
 
3.2%
2 1
 
1.6%
5 1
 
1.6%
7 1
 
1.6%
6 1
 
1.6%
Hangul
ValueCountFrequency (%)
지 22
 
10.3%
게 22
 
10.3%
차 22
 
10.3%
랙 15
 
7.0%
이 13
 
6.1%
컨 12
 
5.6%
어 12
 
5.6%
베 12
 
5.6%
대 10
 
4.7%
기 10
 
4.7%
Other values (35) 63
29.6%

보관요율
Text

MISSING 

Distinct27
Distinct (%)90.0%
Missing44
Missing (%)59.5%
Memory size724.0 B
2024-04-30T03:54:20.673280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length9.4666667
Min length1

Characters and Unicode

Total characters284
Distinct characters32
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)80.0%

Sample

1st row-
2nd row4,790원/톤,월
3rd row10,000원/㎡
4th row850원/톤(일)
5th row25,000원/월,제곱미터
ValueCountFrequency (%)
4,790원/톤 2
 
5.9%
10,000원/㎡ 2
 
5.9%
2
 
5.9%
12,100원/㎡ 2
 
5.9%
30000 1
 
2.9%
7,121원/㎡ 1
 
2.9%
7936원/제곱미터 1
 
2.9%
1600원/박스 1
 
2.9%
15,000원/㎡ 1
 
2.9%
380원/박스 1
 
2.9%
Other values (20) 20
58.8%
2024-04-30T03:54:20.971541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 56
19.7%
, 29
 
10.2%
/ 27
 
9.5%
원 26
 
9.2%
1 20
 
7.0%
4 13
 
4.6%
㎡ 12
 
4.2%
2 9
 
3.2%
9 8
 
2.8%
터 7
 
2.5%
Other values (22) 77
27.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 133
46.8%
Other Letter 75
26.4%
Other Punctuation 56
19.7%
Other Symbol 12
 
4.2%
Space Separator 4
 
1.4%
Close Punctuation 1
 
0.4%
Math Symbol 1
 
0.4%
Open Punctuation 1
 
0.4%
Dash Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 26
34.7%
터 7
 
9.3%
제 7
 
9.3%
곱 7
 
9.3%
미 7
 
9.3%
월 6
 
8.0%
톤 5
 
6.7%
박 2
 
2.7%
일 2
 
2.7%
스 2
 
2.7%
Other values (4) 4
 
5.3%
Decimal Number
ValueCountFrequency (%)
0 56
42.1%
1 20
 
15.0%
4 13
 
9.8%
2 9
 
6.8%
9 8
 
6.0%
5 7
 
5.3%
3 7
 
5.3%
6 5
 
3.8%
7 5
 
3.8%
8 3
 
2.3%
Other Punctuation
ValueCountFrequency (%)
, 29
51.8%
/ 27
48.2%
Other Symbol
ValueCountFrequency (%)
㎡ 12
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 209
73.6%
Hangul 75
 
26.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 56
26.8%
, 29
13.9%
/ 27
12.9%
1 20
 
9.6%
4 13
 
6.2%
㎡ 12
 
5.7%
2 9
 
4.3%
9 8
 
3.8%
5 7
 
3.3%
3 7
 
3.3%
Other values (8) 21
 
10.0%
Hangul
ValueCountFrequency (%)
원 26
34.7%
터 7
 
9.3%
제 7
 
9.3%
곱 7
 
9.3%
미 7
 
9.3%
월 6
 
8.0%
톤 5
 
6.7%
박 2
 
2.7%
일 2
 
2.7%
스 2
 
2.7%
Other values (4) 4
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 197
69.4%
Hangul 75
 
26.4%
CJK Compat 12
 
4.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 56
28.4%
, 29
14.7%
/ 27
13.7%
1 20
 
10.2%
4 13
 
6.6%
2 9
 
4.6%
9 8
 
4.1%
5 7
 
3.6%
3 7
 
3.6%
6 5
 
2.5%
Other values (7) 16
 
8.1%
Hangul
ValueCountFrequency (%)
원 26
34.7%
터 7
 
9.3%
제 7
 
9.3%
곱 7
 
9.3%
미 7
 
9.3%
월 6
 
8.0%
톤 5
 
6.7%
박 2
 
2.7%
일 2
 
2.7%
스 2
 
2.7%
Other values (4) 4
 
5.3%
CJK Compat
ValueCountFrequency (%)
㎡ 12
100.0%

법인여부명
Categorical

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size724.0 B
개인
38 
<NA>
36 

Length

Max length4
Median length2
Mean length2.972973
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 38
51.4%
<NA> 36
48.6%

Length

2024-04-30T03:54:21.092283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:54:21.186623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 38
51.4%
na 36
48.6%

업태_보관및창고업
Categorical

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size724.0 B
<NA>
45 
1
29 

Length

Max length4
Median length4
Mean length2.8243243
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> 45
60.8%
1 29
39.2%

Length

2024-04-30T03:54:21.271007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:54:21.369656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 45
60.8%
1 29
39.2%

업태_운송및택배업
Categorical

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size724.0 B
<NA>
49 
1
25 

Length

Max length4
Median length4
Mean length2.9864865
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 49
66.2%
1 25
33.8%

Length

2024-04-30T03:54:21.470697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:54:21.552438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 49
66.2%
1 25
33.8%

업태_판매업
Categorical

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size724.0 B
<NA>
58 
1
16 

Length

Max length4
Median length4
Mean length3.3513514
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> 58
78.4%
1 16
 
21.6%

Length

2024-04-30T03:54:21.646742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:54:21.737243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 58
78.4%
1 16
 
21.6%

업태_제조업
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size724.0 B
<NA>
66 
1
8 

Length

Max length4
Median length4
Mean length3.6756757
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> 66
89.2%
1 8
 
10.8%

Length

2024-04-30T03:54:21.833375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:54:21.927708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 66
89.2%
1 8
 
10.8%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)일반창고_동수일반창고_면적냉동,냉장창고_동수냉동,냉장창고_면적보관장소_면적종업원수시설/장비현황보관요율법인여부명업태_보관및창고업업태_운송및택배업업태_판매업업태_제조업
061100002012S6110000000820120723<NA>1영업/정상1등록<NA><NA><NA><NA>28663355<NA>153802서울특별시 금천구 가산동 345번지 1호서울특별시 금천구 디지털로 154 (가산동)<NA>롯데글로벌로지스(주) 서울구로지점2019-03-04 16:00:28U2019-03-06 02:40:00.0<NA>189690.633211441583.577484113516.9300.0022컨베이어, 랙, 지게차,-개인<NA>1<NA><NA>
161100002012S611000000212012-08-09<NA>1영업/정상1등록<NA><NA><NA><NA>226653750<NA>07505서울특별시 강서구 공항동 1373-5 물류창고(ACT화물창고1층A창고)서울특별시 강서구 하늘길 247, 물류창고(ACT화물창고1층A창고) (공항동)7505(주)발렉스 특수물류2023-07-18 09:35:47U2022-12-06 22:00:00.0<NA>183007.220062450515.642036<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
261100002023S611000000012023-05-22<NA>1영업/정상1등록<NA><NA><NA><NA>24647859<NA>04508서울특별시 중구 만리동1가 35-1 DHL강북물류센타서울특별시 중구 만리재로37길 5, DHL강북물류센타 1동 B1,1,2층 (만리동1가)4508유피에스에스씨에스코리아(주)2023-06-12 14:07:03U2022-12-05 23:04:00.0<NA>197090.106144450448.091108<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
361100002022S611000000082022-08-18<NA>1영업/정상1등록<NA><NA><NA><NA>261508309<NA>05842서울특별시 송파구 장지동 875번지 서울복합물류서울특별시 송파구 송파대로 55, 서울복합물류 C동 5층(장지동)5842쿠팡로지스틱스서비스 유한회사 (송파 캠프)2023-06-15 15:14:54U2022-12-05 23:07:00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
461100002022S611000000052022-07-07<NA>3폐업3폐업2023-08-01<NA><NA><NA>234416211<NA>05842서울특별시 송파구 장지동 875번지 서울복합물류 A동 601호서울특별시 송파구 송파대로 55, 서울복합물류 A동 601호(장지동)5842머스크컨트랙트로지스틱스코리아(주)2023-08-24 11:12:48U2022-12-07 22:06:00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
561100002023S611000000022023-08-31<NA>1영업/정상1등록<NA><NA><NA><NA>261508309<NA>07522서울특별시 강서구 마곡동 8-1서울특별시 강서구 양천로47길 54, 1층 (마곡동)7522쿠팡로지스틱스서비스 유한회사(강서1모바일캠프(마곡동)2023-08-31 15:43:20I2022-12-09 00:02:00.0<NA>185583.534294452292.441241<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
661100002023S611000000032023-09-12<NA>1영업/정상1등록<NA><NA><NA><NA>215449898<NA>06803서울특별시 서초구 양재동 225번지서울특별시 서초구 양재대로12길 25 (양재동)6803쿠팡로지스틱스서비스 유한회사(서초1캠프)2023-09-12 17:10:22I2022-12-08 23:04:00.0<NA>203467.5021439850.278305<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
761100002012S611000000122012-08-03<NA>3폐업3폐업2023-02-28<NA><NA><NA>236613500<NA>157-210서울특별시 강서구 마곡동 8번지 1호서울특별시 강서구 양천로47길 54 (마곡동)<NA>안국물류센터2023-12-12 08:52:09U2022-11-01 23:04:00.0<NA>185583.534294452292.441241<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
861100002024S611000000012024-02-06<NA>1영업/정상1등록<NA><NA><NA><NA><NA><NA>05842서울특별시 송파구 장지동 875번지 서울복합물류 D동서울특별시 송파구 송파대로 55, 서울복합물류 D동 4층 (장지동)5842크림 주식회사 송파지점2024-02-07 10:49:59I2023-12-01 23:03:00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
961100002012S6110000001320120803<NA>1영업/정상1등록<NA><NA><NA><NA>29551039<NA>132801서울특별시 도봉구 도봉동 58번지 3호서울특별시 도봉구 도봉로180길 9 (도봉동)<NA>이화창고2018-07-04 10:42:30I2018-08-31 23:59:59.0<NA>204052.327585464598.78734432201.0600.009컨베이어4,790원/톤,월개인1<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)일반창고_동수일반창고_면적냉동,냉장창고_동수냉동,냉장창고_면적보관장소_면적종업원수시설/장비현황보관요율법인여부명업태_보관및창고업업태_운송및택배업업태_판매업업태_제조업
6461100002012S6110000002020120803<NA>3폐업3폐업<NA><NA><NA><NA>263001114<NA>156800서울특별시 동작구 노량진동 13번지 6호서울특별시 동작구 노들로 674 (노량진동)<NA>한국농수산식품유통공사2013-03-04 17:14:10I2018-08-31 23:59:59.0<NA>194346.156671445823.50089211653.015289.002지게차, 파렛트, 대형선풍기<NA>개인1<NA>1<NA>
6561100002012S6110000000120120618<NA>3폐업3폐업<NA><NA><NA><NA>234610101<NA>137893서울특별시 서초구 양재2동 224번지서울특별시 서초구 양재대로12길 56 (양재동)<NA>(주)케이씨티시 양재물류센터2022-06-07 15:48:30U2021-12-06 00:09:00.0<NA>203301.847004439561.993972<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6661100002022S6110000000420220621<NA>1영업/정상1등록<NA><NA><NA><NA>7048000335<NA>05842서울특별시 송파구 장지동 875번지 서울복합물류서울특별시 송파구 송파대로 55, 서울복합물류 F동 1층(장지동)5842주식회사 컬리넥스트마일2022-06-23 09:42:30I2021-12-05 22:05:00.0<NA>210857.0441446.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6761100002022S611000000072022-08-18<NA>1영업/정상1등록<NA><NA><NA><NA>261508309<NA>07532서울특별시 강서구 가양동 449-9 한일철강(주),한일물류센터 다동서울특별시 강서구 양천로 537, 한일철강(주),한일물류센터 다동(가양동)7532쿠팡로지스틱스서비스 유한회사 (강서1캠프)2023-08-31 15:14:57U2022-12-09 00:02:00.0<NA>187530.220524450756.389027<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6861100002012S6110000003620120810<NA>3폐업3폐업20220718<NA><NA><NA>220469402<NA>157724서울특별시 강서구 가양동 92번지 1호서울특별시 강서구 양천로 373 (가양동)<NA>씨제이대한통운(주) 가양센터2022-07-13 16:50:47U2021-12-06 23:05:00.0<NA>186223.731479451794.187683<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6961100002012S6110000000620120702<NA>3폐업3폐업20220708<NA><NA><NA>231580912<NA>121833서울특별시 마포구 상암동 508번지서울특별시 마포구 구룡길 36 (상암동)<NA>씨제이대한통운(주) 수색물류센터2022-07-13 16:46:29U2021-12-06 23:05:00.0<NA>189578.962415454129.858577<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7061100002022S611000000062022-07-21<NA>1영업/정상1등록<NA><NA><NA><NA>426154124<NA>03917서울특별시 마포구 상암동 508번지서울특별시 마포구 구룡길 36(상암동)3917한국철도공사2023-09-12 17:03:10U2022-12-08 23:04:00.0<NA>189578.962415454129.858577<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7161100002022S611000000112022-08-18<NA>1영업/정상1등록<NA><NA><NA><NA>261508309<NA>07202서울특별시 영등포구 양평동6가 12번지서울특별시 영등포구 양평로28길 19(양평동6가)7202쿠팡로지스틱스서비스 유한회사 (일산7모바일캠프)2023-06-15 15:16:36U2022-12-05 23:07:00.0<NA>190290.318903448827.040749<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7261100002022S611000000092022-08-18<NA>1영업/정상1등록<NA><NA><NA><NA>261508309<NA>01014서울특별시 강북구 수유동 565-2 고려창고서울특별시 강북구 인수봉로 305, 고려창고(수유동)1014쿠팡로지스틱스서비스 유한회사 (양주1모바일캠프)2023-06-15 15:15:31U2022-12-05 23:07:00.0<NA>200825.183179460403.858685<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7361100002022S611000000032022-05-09<NA>3폐업3폐업2023-06-30<NA><NA><NA>216441107<NA>05842서울특별시 송파구 장지동 875번지 서울복합물류 A동 B1호서울특별시 송파구 송파대로 55, 서울복합물류 A동 B1층(장지동)5842주식회사 컬리2023-07-26 13:43:13U2022-12-06 22:08:00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>