Overview

Dataset statistics

Number of variables30
Number of observations60
Missing cells511
Missing cells (%)28.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.2 KiB
Average record size in memory260.2 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
Author송파구
URLhttps://data.seoul.go.kr/dataList/OA-18525/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 has 60 (100.0%) missing valuesMissing
폐업일자 has 40 (66.7%) missing valuesMissing
휴업시작일자 has 60 (100.0%) missing valuesMissing
휴업종료일자 has 60 (100.0%) missing valuesMissing
재개업일자 has 60 (100.0%) missing valuesMissing
전화번호 has 15 (25.0%) missing valuesMissing
소재지우편번호 has 60 (100.0%) missing valuesMissing
도로명주소 has 12 (20.0%) missing valuesMissing
도로명우편번호 has 12 (20.0%) missing valuesMissing
업태구분명 has 60 (100.0%) missing valuesMissing
좌표정보(X) has 6 (10.0%) missing valuesMissing
좌표정보(Y) has 6 (10.0%) missing valuesMissing
축산물가공업구분명 has 60 (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
소재지면적 has 3 (5.0%) zerosZeros

Reproduction

Analysis started2024-05-11 02:55:36.182447
Analysis finished2024-05-11 02:55:36.892623
Duration0.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
3230000
60 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3230000
2nd row3230000
3rd row3230000
4th row3230000
5th row3230000

Common Values

ValueCountFrequency (%)
3230000 60
100.0%

Length

2024-05-11T02:55:37.078908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:55:37.609463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3230000 60
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.23 × 1017
Minimum3.23 × 1017
Maximum3.23 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-05-11T02:55:37.928977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.23 × 1017
5-th percentile3.23 × 1017
Q13.23 × 1017
median3.23 × 1017
Q33.23 × 1017
95-th percentile3.23 × 1017
Maximum3.23 × 1017
Range330000
Interquartile range (IQR)139968

Descriptive statistics

Standard deviation85497.679
Coefficient of variation (CV)2.646987 × 10-13
Kurtosis0.56496812
Mean3.23 × 1017
Median Absolute Deviation (MAD)60000
Skewness-1.038401
Sum9.3325598 × 1017
Variance7.3098531 × 109
MonotonicityStrictly increasing
2024-05-11T02:55:38.371656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
323000000819910001 1
 
1.7%
323000000820180001 1
 
1.7%
323000000820180003 1
 
1.7%
323000000820190001 1
 
1.7%
323000000820190002 1
 
1.7%
323000000820200001 1
 
1.7%
323000000820200002 1
 
1.7%
323000000820200003 1
 
1.7%
323000000820200004 1
 
1.7%
323000000820200005 1
 
1.7%
Other values (50) 50
83.3%
ValueCountFrequency (%)
323000000819910001 1
1.7%
323000000819910002 1
1.7%
323000000819920001 1
1.7%
323000000819970001 1
1.7%
323000000820000001 1
1.7%
323000000820050001 1
1.7%
323000000820060001 1
1.7%
323000000820060002 1
1.7%
323000000820060003 1
1.7%
323000000820060004 1
1.7%
ValueCountFrequency (%)
323000000820240001 1
1.7%
323000000820230005 1
1.7%
323000000820230004 1
1.7%
323000000820230003 1
1.7%
323000000820230002 1
1.7%
323000000820230001 1
1.7%
323000000820220007 1
1.7%
323000000820220006 1
1.7%
323000000820220005 1
1.7%
323000000820220004 1
1.7%

인허가일자
Date

Distinct55
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
Minimum1991-12-24 00:00:00
Maximum2024-04-03 00:00:00
2024-05-11T02:55:38.809745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:55:39.262002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing60
Missing (%)100.0%
Memory size672.0 B

영업상태코드
Categorical

Distinct3
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
1
40 
3
19 
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
1 40
66.7%
3 19
31.7%
4 1
 
1.7%

Length

2024-05-11T02:55:39.641979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:55:40.052630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 40
66.7%
3 19
31.7%
4 1
 
1.7%

영업상태명
Categorical

Distinct3
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
영업/정상
40 
폐업
19 
취소/말소/만료/정지/중지
 
1

Length

Max length14
Median length5
Mean length4.2
Min length2

Unique

Unique1 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 40
66.7%
폐업 19
31.7%
취소/말소/만료/정지/중지 1
 
1.7%

Length

2024-05-11T02:55:40.433305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:55:40.791500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 40
66.7%
폐업 19
31.7%
취소/말소/만료/정지/중지 1
 
1.7%

상세영업상태코드
Categorical

Distinct3
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
0
40 
2
19 
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
0 40
66.7%
2 19
31.7%
4 1
 
1.7%

Length

2024-05-11T02:55:41.153590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:55:41.467926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 40
66.7%
2 19
31.7%
4 1
 
1.7%

상세영업상태명
Categorical

Distinct3
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
정상
40 
폐업
19 
말소
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
정상 40
66.7%
폐업 19
31.7%
말소 1
 
1.7%

Length

2024-05-11T02:55:41.842170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:55:42.160760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상 40
66.7%
폐업 19
31.7%
말소 1
 
1.7%

폐업일자
Real number (ℝ)

MISSING 

Distinct19
Distinct (%)95.0%
Missing40
Missing (%)66.7%
Infinite0
Infinite (%)0.0%
Mean20121557
Minimum20030211
Maximum20220324
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-05-11T02:55:42.476382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030211
5-th percentile20059657
Q120100758
median20115964
Q320140919
95-th percentile20191628
Maximum20220324
Range190113
Interquartile range (IQR)40161.5

Descriptive statistics

Standard deviation44540.041
Coefficient of variation (CV)0.0022135484
Kurtosis0.5643043
Mean20121557
Median Absolute Deviation (MAD)24808.5
Skewness0.21641237
Sum4.0243114 × 108
Variance1.9838152 × 109
MonotonicityNot monotonic
2024-05-11T02:55:42.896965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
20140919 2
 
3.3%
20100902 1
 
1.7%
20150123 1
 
1.7%
20180528 1
 
1.7%
20140625 1
 
1.7%
20130514 1
 
1.7%
20190118 1
 
1.7%
20080703 1
 
1.7%
20121206 1
 
1.7%
20110228 1
 
1.7%
Other values (9) 9
 
15.0%
(Missing) 40
66.7%
ValueCountFrequency (%)
20030211 1
1.7%
20061207 1
1.7%
20070130 1
1.7%
20080703 1
1.7%
20100324 1
1.7%
20100902 1
1.7%
20110215 1
1.7%
20110228 1
1.7%
20110711 1
1.7%
20110721 1
1.7%
ValueCountFrequency (%)
20220324 1
1.7%
20190118 1
1.7%
20180528 1
1.7%
20150123 1
1.7%
20140919 2
3.3%
20140625 1
1.7%
20130514 1
1.7%
20130509 1
1.7%
20121206 1
1.7%
20110721 1
1.7%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing60
Missing (%)100.0%
Memory size672.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing60
Missing (%)100.0%
Memory size672.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing60
Missing (%)100.0%
Memory size672.0 B

전화번호
Text

MISSING 

Distinct39
Distinct (%)86.7%
Missing15
Missing (%)25.0%
Memory size612.0 B
2024-05-11T02:55:43.368768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length9
Min length7

Characters and Unicode

Total characters405
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

Unique36 ?
Unique (%)80.0%

Sample

1st row483-5661
2nd row408-2142
3rd row2202-6579
4th row3401-6650
5th row4439006
ValueCountFrequency (%)
02-2631-0160 4
 
8.9%
5544599 3
 
6.7%
4150014 2
 
4.4%
02-406-7106 1
 
2.2%
02-406-6750 1
 
2.2%
02-456-7722 1
 
2.2%
22014000 1
 
2.2%
9662600 1
 
2.2%
02-6959-2252 1
 
2.2%
34632246 1
 
2.2%
Other values (29) 29
64.4%
2024-05-11T02:55:44.263874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 68
16.8%
2 50
12.3%
4 47
11.6%
- 43
10.6%
1 38
9.4%
6 36
8.9%
3 32
7.9%
5 31
7.7%
9 23
 
5.7%
7 23
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 362
89.4%
Dash Punctuation 43
 
10.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 68
18.8%
2 50
13.8%
4 47
13.0%
1 38
10.5%
6 36
9.9%
3 32
8.8%
5 31
8.6%
9 23
 
6.4%
7 23
 
6.4%
8 14
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 43
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 405
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 68
16.8%
2 50
12.3%
4 47
11.6%
- 43
10.6%
1 38
9.4%
6 36
8.9%
3 32
7.9%
5 31
7.7%
9 23
 
5.7%
7 23
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 405
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 68
16.8%
2 50
12.3%
4 47
11.6%
- 43
10.6%
1 38
9.4%
6 36
8.9%
3 32
7.9%
5 31
7.7%
9 23
 
5.7%
7 23
 
5.7%

소재지면적
Real number (ℝ)

ZEROS 

Distinct54
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.350167
Minimum0
Maximum393.16
Zeros3
Zeros (%)5.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-05-11T02:55:44.711902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.8
Q115.975
median34.5
Q362.01
95-th percentile164.331
Maximum393.16
Range393.16
Interquartile range (IQR)46.035

Descriptive statistics

Standard deviation60.806756
Coefficient of variation (CV)1.2076773
Kurtosis16.902574
Mean50.350167
Median Absolute Deviation (MAD)21.78
Skewness3.5327863
Sum3021.01
Variance3697.4615
MonotonicityNot monotonic
2024-05-11T02:55:45.167512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3
 
5.0%
34.5 3
 
5.0%
8.0 2
 
3.3%
66.0 2
 
3.3%
12.6 1
 
1.7%
16.5 1
 
1.7%
96.13 1
 
1.7%
39.76 1
 
1.7%
42.0 1
 
1.7%
6.0 1
 
1.7%
Other values (44) 44
73.3%
ValueCountFrequency (%)
0.0 3
5.0%
4.0 1
 
1.7%
6.0 1
 
1.7%
7.2 1
 
1.7%
7.84 1
 
1.7%
8.0 2
3.3%
10.0 1
 
1.7%
10.6 1
 
1.7%
12.6 1
 
1.7%
12.96 1
 
1.7%
ValueCountFrequency (%)
393.16 1
1.7%
181.8 1
1.7%
171.0 1
1.7%
163.98 1
1.7%
129.6 1
1.7%
117.68 1
1.7%
96.13 1
1.7%
83.6 1
1.7%
78.44 1
1.7%
75.68 1
1.7%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing60
Missing (%)100.0%
Memory size672.0 B

지번주소
Text

Distinct53
Distinct (%)88.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-05-11T02:55:45.748106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length30
Mean length24.716667
Min length17

Characters and Unicode

Total characters1483
Distinct characters87
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

Unique49 ?
Unique (%)81.7%

Sample

1st row서울특별시 송파구 풍납동 ***-****번지
2nd row서울특별시 송파구 풍납동 ***-****번지
3rd row서울특별시 송파구 가락동 ***번지 축산시장 *층 *-*호
4th row서울특별시 송파구 가락동 ***번지 축산협동조합건물내
5th row서울특별시 송파구 석촌동 ***-****번지
ValueCountFrequency (%)
서울특별시 60
20.8%
송파구 60
20.8%
번지 31
10.8%
28
9.7%
문정동 20
 
6.9%
가락동 16
 
5.6%
호 13
 
4.5%
지상*층 7
 
2.4%
엠스테이트 6
 
2.1%
오금동 6
 
2.1%
Other values (26) 41
14.2%
2024-05-11T02:55:46.671210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 281
18.9%
256
17.3%
파 65
 
4.4%
동 65
 
4.4%
송 63
 
4.2%
시 61
 
4.1%
서 60
 
4.0%
울 60
 
4.0%
특 60
 
4.0%
별 60
 
4.0%
Other values (77) 452
30.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 883
59.5%
Other Punctuation 281
 
18.9%
Space Separator 256
 
17.3%
Dash Punctuation 53
 
3.6%
Uppercase Letter 7
 
0.5%
Decimal Number 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 65
 
7.4%
동 65
 
7.4%
송 63
 
7.1%
시 61
 
6.9%
서 60
 
6.8%
울 60
 
6.8%
특 60
 
6.8%
별 60
 
6.8%
구 60
 
6.8%
지 41
 
4.6%
Other values (66) 288
32.6%
Uppercase Letter
ValueCountFrequency (%)
A 3
42.9%
S 1
 
14.3%
K 1
 
14.3%
V 1
 
14.3%
B 1
 
14.3%
Decimal Number
ValueCountFrequency (%)
4 1
33.3%
1 1
33.3%
7 1
33.3%
Other Punctuation
ValueCountFrequency (%)
* 281
100.0%
Space Separator
ValueCountFrequency (%)
256
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 53
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 883
59.5%
Common 593
40.0%
Latin 7
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 65
 
7.4%
동 65
 
7.4%
송 63
 
7.1%
시 61
 
6.9%
서 60
 
6.8%
울 60
 
6.8%
특 60
 
6.8%
별 60
 
6.8%
구 60
 
6.8%
지 41
 
4.6%
Other values (66) 288
32.6%
Common
ValueCountFrequency (%)
* 281
47.4%
256
43.2%
- 53
 
8.9%
4 1
 
0.2%
1 1
 
0.2%
7 1
 
0.2%
Latin
ValueCountFrequency (%)
A 3
42.9%
S 1
 
14.3%
K 1
 
14.3%
V 1
 
14.3%
B 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 883
59.5%
ASCII 600
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 281
46.8%
256
42.7%
- 53
 
8.8%
A 3
 
0.5%
4 1
 
0.2%
1 1
 
0.2%
7 1
 
0.2%
S 1
 
0.2%
K 1
 
0.2%
V 1
 
0.2%
Hangul
ValueCountFrequency (%)
파 65
 
7.4%
동 65
 
7.4%
송 63
 
7.1%
시 61
 
6.9%
서 60
 
6.8%
울 60
 
6.8%
특 60
 
6.8%
별 60
 
6.8%
구 60
 
6.8%
지 41
 
4.6%
Other values (66) 288
32.6%

도로명주소
Text

MISSING 

Distinct44
Distinct (%)91.7%
Missing12
Missing (%)20.0%
Memory size612.0 B
2024-05-11T02:55:47.188402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length42
Mean length37.458333
Min length24

Characters and Unicode

Total characters1798
Distinct characters124
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

Unique42 ?
Unique (%)87.5%

Sample

1st row서울특별시 송파구 새말로*길 ** (문정동, ***호)
2nd row서울특별시 송파구 양산로 **, ***호 (거여동, 세신거여종합상가)
3rd row서울특별시 송파구 마천로 ***, 지상*층 (오금동, 영풍아파트상가)
4th row서울특별시 송파구 백제고분로**길 **-**, 지상*층 (석촌동, 트레비타워)
5th row서울특별시 송파구 충민로 *, A동 **층 ****호 (문정동, 한화오벨리스크)
ValueCountFrequency (%)
서울특별시 48
13.6%
송파구 48
13.6%
47
13.3%
호 33
 
9.3%
층 21
 
5.9%
문정동 19
 
5.4%
가락동 10
 
2.8%
법원로 10
 
2.8%
엠스테이트 8
 
2.3%
a동 7
 
2.0%
Other values (62) 103
29.1%
2024-05-11T02:55:48.157960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 306
17.0%
306
17.0%
동 65
 
3.6%
파 64
 
3.6%
송 62
 
3.4%
, 57
 
3.2%
서 49
 
2.7%
울 49
 
2.7%
) 49
 
2.7%
( 49
 
2.7%
Other values (114) 742
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1002
55.7%
Other Punctuation 363
 
20.2%
Space Separator 306
 
17.0%
Close Punctuation 49
 
2.7%
Open Punctuation 49
 
2.7%
Uppercase Letter 15
 
0.8%
Dash Punctuation 10
 
0.6%
Decimal Number 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 65
 
6.5%
파 64
 
6.4%
송 62
 
6.2%
서 49
 
4.9%
울 49
 
4.9%
시 49
 
4.9%
특 48
 
4.8%
구 48
 
4.8%
로 48
 
4.8%
별 48
 
4.8%
Other values (99) 472
47.1%
Uppercase Letter
ValueCountFrequency (%)
A 7
46.7%
C 4
26.7%
S 1
 
6.7%
K 1
 
6.7%
V 1
 
6.7%
B 1
 
6.7%
Decimal Number
ValueCountFrequency (%)
7 2
50.0%
2 1
25.0%
5 1
25.0%
Other Punctuation
ValueCountFrequency (%)
* 306
84.3%
, 57
 
15.7%
Space Separator
ValueCountFrequency (%)
306
100.0%
Close Punctuation
ValueCountFrequency (%)
) 49
100.0%
Open Punctuation
ValueCountFrequency (%)
( 49
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1002
55.7%
Common 781
43.4%
Latin 15
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 65
 
6.5%
파 64
 
6.4%
송 62
 
6.2%
서 49
 
4.9%
울 49
 
4.9%
시 49
 
4.9%
특 48
 
4.8%
구 48
 
4.8%
로 48
 
4.8%
별 48
 
4.8%
Other values (99) 472
47.1%
Common
ValueCountFrequency (%)
* 306
39.2%
306
39.2%
, 57
 
7.3%
) 49
 
6.3%
( 49
 
6.3%
- 10
 
1.3%
7 2
 
0.3%
2 1
 
0.1%
5 1
 
0.1%
Latin
ValueCountFrequency (%)
A 7
46.7%
C 4
26.7%
S 1
 
6.7%
K 1
 
6.7%
V 1
 
6.7%
B 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1002
55.7%
ASCII 796
44.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 306
38.4%
306
38.4%
, 57
 
7.2%
) 49
 
6.2%
( 49
 
6.2%
- 10
 
1.3%
A 7
 
0.9%
C 4
 
0.5%
7 2
 
0.3%
2 1
 
0.1%
Other values (5) 5
 
0.6%
Hangul
ValueCountFrequency (%)
동 65
 
6.5%
파 64
 
6.4%
송 62
 
6.2%
서 49
 
4.9%
울 49
 
4.9%
시 49
 
4.9%
특 48
 
4.8%
구 48
 
4.8%
로 48
 
4.8%
별 48
 
4.8%
Other values (99) 472
47.1%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct30
Distinct (%)62.5%
Missing12
Missing (%)20.0%
Infinite0
Infinite (%)0.0%
Mean5755.875
Minimum5548
Maximum5855
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-05-11T02:55:48.550375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5548
5-th percentile5617.55
Q15697.25
median5774.5
Q35845
95-th percentile5854
Maximum5855
Range307
Interquartile range (IQR)147.75

Descriptive statistics

Standard deviation90.507699
Coefficient of variation (CV)0.015724403
Kurtosis-0.9473807
Mean5755.875
Median Absolute Deviation (MAD)77
Skewness-0.46970428
Sum276282
Variance8191.6436
MonotonicityNot monotonic
2024-05-11T02:55:48.939882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
5854 11
18.3%
5719 3
 
5.0%
5841 2
 
3.3%
5722 2
 
3.3%
5626 2
 
3.3%
5836 2
 
3.3%
5661 2
 
3.3%
5779 2
 
3.3%
5711 1
 
1.7%
5613 1
 
1.7%
Other values (20) 20
33.3%
(Missing) 12
20.0%
ValueCountFrequency (%)
5548 1
1.7%
5573 1
1.7%
5613 1
1.7%
5626 2
3.3%
5628 1
1.7%
5637 1
1.7%
5642 1
1.7%
5661 2
3.3%
5686 1
1.7%
5689 1
1.7%
ValueCountFrequency (%)
5855 1
 
1.7%
5854 11
18.3%
5842 1
 
1.7%
5841 2
 
3.3%
5836 2
 
3.3%
5826 1
 
1.7%
5817 1
 
1.7%
5806 1
 
1.7%
5798 1
 
1.7%
5785 1
 
1.7%

사업장명
Text

Distinct57
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-05-11T02:55:49.413503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length7.8
Min length2

Characters and Unicode

Total characters468
Distinct characters114
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

Unique54 ?
Unique (%)90.0%

Sample

1st row평안화물
2nd row평안화물
3rd row우주특수산업(주)
4th row한국축산유통
5th row삼솔물류
ValueCountFrequency (%)
주식회사 6
 
9.0%
평안화물 2
 
3.0%
주)조은운수 2
 
3.0%
주)남양로지스 2
 
3.0%
문정축산 1
 
1.5%
도민종합물류 1
 
1.5%
제이와이로지스(주 1
 
1.5%
휴먼로지엠 1
 
1.5%
주)서원종합물류 1
 
1.5%
에이치디코퍼레이션 1
 
1.5%
Other values (49) 49
73.1%
2024-05-11T02:55:50.438233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 47
 
10.0%
( 40
 
8.5%
) 40
 
8.5%
스 20
 
4.3%
지 17
 
3.6%
로 15
 
3.2%
이 14
 
3.0%
물 13
 
2.8%
수 10
 
2.1%
에 9
 
1.9%
Other values (104) 243
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 381
81.4%
Open Punctuation 40
 
8.5%
Close Punctuation 40
 
8.5%
Space Separator 7
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 47
 
12.3%
스 20
 
5.2%
지 17
 
4.5%
로 15
 
3.9%
이 14
 
3.7%
물 13
 
3.4%
수 10
 
2.6%
에 9
 
2.4%
류 9
 
2.4%
사 8
 
2.1%
Other values (101) 219
57.5%
Open Punctuation
ValueCountFrequency (%)
( 40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 40
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 381
81.4%
Common 87
 
18.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 47
 
12.3%
스 20
 
5.2%
지 17
 
4.5%
로 15
 
3.9%
이 14
 
3.7%
물 13
 
3.4%
수 10
 
2.6%
에 9
 
2.4%
류 9
 
2.4%
사 8
 
2.1%
Other values (101) 219
57.5%
Common
ValueCountFrequency (%)
( 40
46.0%
) 40
46.0%
7
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 381
81.4%
ASCII 87
 
18.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 47
 
12.3%
스 20
 
5.2%
지 17
 
4.5%
로 15
 
3.9%
이 14
 
3.7%
물 13
 
3.4%
수 10
 
2.6%
에 9
 
2.4%
류 9
 
2.4%
사 8
 
2.1%
Other values (101) 219
57.5%
ASCII
ValueCountFrequency (%)
( 40
46.0%
) 40
46.0%
7
 
8.0%

최종수정일자
Date

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
Minimum2003-03-03 19:22:05
Maximum2024-04-04 16:21:10
2024-05-11T02:55:50.850274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:55:51.421313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
I
41 
U
19 

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 41
68.3%
U 19
31.7%

Length

2024-05-11T02:55:51.909382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:55:52.325548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 41
68.3%
u 19
31.7%

데이터갱신일자
Date

Distinct31
Distinct (%)51.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:06:00
2024-05-11T02:55:52.755619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:55:53.256397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing60
Missing (%)100.0%
Memory size672.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct43
Distinct (%)79.6%
Missing6
Missing (%)10.0%
Infinite0
Infinite (%)0.0%
Mean210678.08
Minimum206835.85
Maximum213073.79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-05-11T02:55:53.723332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum206835.85
5-th percentile209400.8
Q1210325.75
median210558
Q3211141.34
95-th percentile212484.7
Maximum213073.79
Range6237.938
Interquartile range (IQR)815.59158

Descriptive statistics

Standard deviation1048.6903
Coefficient of variation (CV)0.0049776905
Kurtosis2.7650898
Mean210678.08
Median Absolute Deviation (MAD)443.23033
Skewness-0.54407901
Sum11376616
Variance1099751.3
MonotonicityNot monotonic
2024-05-11T02:55:54.129343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
210558.0 6
 
10.0%
210414.919309988 2
 
3.3%
210491.321883503 2
 
3.3%
209790.959909032 2
 
3.3%
210516.191915095 2
 
3.3%
210318.6433383 2
 
3.3%
212645.539631084 2
 
3.3%
210889.367141803 1
 
1.7%
210491.688890281 1
 
1.7%
210909.651611943 1
 
1.7%
Other values (33) 33
55.0%
(Missing) 6
 
10.0%
ValueCountFrequency (%)
206835.849181736 1
1.7%
208538.456869611 1
1.7%
209305.071099687 1
1.7%
209452.341133051 1
1.7%
209486.793951821 1
1.7%
209505.564014084 1
1.7%
209509.155143836 1
1.7%
209733.324912029 1
1.7%
209790.959909032 2
3.3%
210092.736422553 1
1.7%
ValueCountFrequency (%)
213073.787217832 1
1.7%
212645.539631084 2
3.3%
212398.096434974 1
1.7%
212126.605168251 1
1.7%
212123.802310515 1
1.7%
212001.060130824 1
1.7%
211760.769832689 1
1.7%
211741.048550472 1
1.7%
211588.003347445 1
1.7%
211314.381455567 1
1.7%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct43
Distinct (%)79.6%
Missing6
Missing (%)10.0%
Infinite0
Infinite (%)0.0%
Mean443933.39
Minimum441446
Maximum447967.68
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-05-11T02:55:54.662057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441446
5-th percentile442067.68
Q1442746.28
median443862.66
Q3444593.24
95-th percentile446276.17
Maximum447967.68
Range6521.68
Interquartile range (IQR)1846.9592

Descriptive statistics

Standard deviation1382.7011
Coefficient of variation (CV)0.0031146588
Kurtosis1.5197954
Mean443933.39
Median Absolute Deviation (MAD)775.68198
Skewness0.95643148
Sum23972403
Variance1911862.2
MonotonicityNot monotonic
2024-05-11T02:55:55.154077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
442587.0 6
 
10.0%
444081.432070039 2
 
3.3%
443569.763243482 2
 
3.3%
443481.212174317 2
 
3.3%
441996.227705236 2
 
3.3%
447967.680010779 2
 
3.3%
443127.535494347 2
 
3.3%
442530.872722442 1
 
1.7%
443508.221246366 1
 
1.7%
444385.960146534 1
 
1.7%
Other values (33) 33
55.0%
(Missing) 6
 
10.0%
ValueCountFrequency (%)
441446.0 1
 
1.7%
441996.227705236 2
 
3.3%
442106.154785377 1
 
1.7%
442395.0 1
 
1.7%
442530.872722442 1
 
1.7%
442586.0 1
 
1.7%
442587.0 6
10.0%
442695.543740081 1
 
1.7%
442898.489441704 1
 
1.7%
443127.535494347 2
 
3.3%
ValueCountFrequency (%)
447967.680010779 2
3.3%
447341.670834952 1
1.7%
445702.432655116 1
1.7%
445693.164482588 1
1.7%
445562.698201787 1
1.7%
445214.179933705 1
1.7%
444895.395901482 1
1.7%
444866.77298564 1
1.7%
444757.635763389 1
1.7%
444718.676192051 1
1.7%

축산업무구분명
Categorical

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
축산물운반업
40 
<NA>
20 

Length

Max length6
Median length6
Mean length5.3333333
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
축산물운반업 40
66.7%
<NA> 20
33.3%

Length

2024-05-11T02:55:55.797986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:55:56.153469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
축산물운반업 40
66.7%
na 20
33.3%

축산물가공업구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing60
Missing (%)100.0%
Memory size672.0 B

축산일련번호
Categorical

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
<NA>
53 
0
7 

Length

Max length4
Median length4
Mean length3.65
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> 53
88.3%
0 7
 
11.7%

Length

2024-05-11T02:55:56.490153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:55:56.834573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 53
88.3%
0 7
 
11.7%

권리주체일련번호
Categorical

Distinct3
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
L00
29 
<NA>
20 
000
11 

Length

Max length4
Median length3
Mean length3.3333333
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row000
2nd row000
3rd rowL00
4th row000
5th row000

Common Values

ValueCountFrequency (%)
L00 29
48.3%
<NA> 20
33.3%
000 11
 
18.3%

Length

2024-05-11T02:55:57.144877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:55:57.734493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
l00 29
48.3%
na 20
33.3%
000 11
 
18.3%

총인원
Categorical

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
<NA>
53 
0
7 

Length

Max length4
Median length4
Mean length3.65
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> 53
88.3%
0 7
 
11.7%

Length

2024-05-11T02:55:58.141304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:55:58.519110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 53
88.3%
0 7
 
11.7%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
0323000032300000081991000119911224<NA>3폐업2폐업20110228<NA><NA><NA>483-566112.6<NA>서울특별시 송파구 풍납동 ***-****번지<NA><NA>평안화물2011-02-28 14:25:38I2018-08-31 23:59:59.0<NA>210318.643338447967.680011축산물운반업<NA><NA>000<NA>
1323000032300000081991000219911224<NA>3폐업2폐업20110215<NA><NA><NA><NA>27.3<NA>서울특별시 송파구 풍납동 ***-****번지<NA><NA>평안화물2011-02-15 09:09:01I2018-08-31 23:59:59.0<NA>210318.643338447967.680011축산물운반업<NA><NA>000<NA>
2323000032300000081992000119921208<NA>3폐업2폐업20110721<NA><NA><NA>408-214212.98<NA>서울특별시 송파구 가락동 ***번지 축산시장 *층 *-*호<NA><NA>우주특수산업(주)2011-07-21 14:25:23I2018-08-31 23:59:59.0<NA>209790.959909443481.212174축산물운반업<NA><NA>L00<NA>
3323000032300000081997000119970804<NA>3폐업2폐업20030211<NA><NA><NA><NA>10.0<NA>서울특별시 송파구 가락동 ***번지 축산협동조합건물내<NA><NA>한국축산유통2003-03-03 19:22:05I2018-08-31 23:59:59.0<NA>209790.959909443481.212174축산물운반업<NA><NA>000<NA>
4323000032300000082000000120000107<NA>3폐업2폐업20130509<NA><NA><NA>2202-657925.74<NA>서울특별시 송파구 석촌동 ***-****번지<NA><NA>삼솔물류2013-05-09 15:29:24I2018-08-31 23:59:59.0<NA>209733.324912444276.304902축산물운반업<NA><NA>000<NA>
5323000032300000082005000120051117<NA>3폐업2폐업20061207<NA><NA><NA>3401-665078.44<NA>서울특별시 송파구 가락동 **-*번지 지상*층<NA><NA>(주)남양로지스2006-12-07 10:41:52I2018-08-31 23:59:59.0<NA>210909.651612444385.960147축산물운반업<NA><NA>L00<NA>
6323000032300000082006000120060512<NA>3폐업2폐업20140919<NA><NA><NA>443900662.64<NA>서울특별시 송파구 문정동 **-*번지서울특별시 송파구 새말로*길 ** (문정동, ***호)5817(주)케이에스로지텍2014-09-19 16:58:45I2018-08-31 23:59:59.0<NA>211111.99047442106.154785축산물운반업<NA><NA>L00<NA>
7323000032300000082006000220060517<NA>4취소/말소/만료/정지/중지4말소20220324<NA><NA><NA>470-921121.46<NA>서울특별시 송파구 거여동 ***-* ***호서울특별시 송파구 양산로 **, ***호 (거여동, 세신거여종합상가)5779(주)세상유통2022-03-24 17:17:25U2022-03-26 02:40:00.0<NA>212645.539631443127.535494축산물운반업<NA>0L000
8323000032300000082006000320060630<NA>3폐업2폐업20070130<NA><NA><NA>790-17177.2<NA>서울특별시 송파구 풍납동 ***-*번지 지상*층<NA><NA>구르메에프앤드비코리아(주)2007-01-30 16:32:03I2018-08-31 23:59:59.0<NA>210136.802919447341.670835축산물운반업<NA><NA>L00<NA>
9323000032300000082006000420060710<NA>3폐업2폐업20110711<NA><NA><NA>404-490333.75<NA>서울특별시 송파구 문정동 **-**번지 지상*층<NA><NA>택수물류(주)2011-07-11 14:54:49I2018-08-31 23:59:59.0<NA>210889.367142442530.872722축산물운반업<NA><NA>L00<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
50323000032300000082022000420220527<NA>1영업/정상0정상<NA><NA><NA><NA>02-2631-016034.74<NA>서울특별시 송파구 문정동 ***-* 엠스테이트서울특별시 송파구 법원로 ***, 엠스테이트 A동 ***호 (문정동)5854(주)서현운수2022-10-28 16:14:33U2021-10-30 21:00:00.0<NA>210558.0442587.0<NA><NA><NA><NA><NA>
51323000032300000082022000520220916<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 송파구 가락동 *** 프라자아파트서울특별시 송파구 문정로 ***, **동 ***호 (가락동, 프라자아파트)5785정태성2022-09-16 16:07:57I2021-12-08 23:08:00.0<NA>211741.04855443318.264543<NA><NA><NA><NA><NA>
52323000032300000082022000620221125<NA>1영업/정상0정상<NA><NA><NA><NA>02-6925-0515129.6<NA>서울특별시 송파구 잠실동 ***-** 애드버스서울특별시 송파구 도곡로**길 **, 애드버스 *층 (잠실동)5573주식회사 히어로지스틱2022-11-25 16:37:26I2021-10-31 22:07:00.0<NA>206835.849182444653.645158<NA><NA><NA><NA><NA>
53323000032300000082022000720221214<NA>1영업/정상0정상<NA><NA><NA><NA>1588-3372393.16<NA>서울특별시 송파구 석촌동 14-7서울특별시 송파구 백제고분로 275, 7층 (석촌동)5613(주)고고밴코리아2022-12-14 16:29:41I2021-11-01 23:06:00.0<NA>208538.45687444516.687666<NA><NA><NA><NA><NA>
5432300003230000008202300012023-03-30<NA>1영업/정상0정상<NA><NA><NA><NA>031-753-87588.0<NA>서울특별시 송파구 문정동 *** 송파 테라타워*서울특별시 송파구 송파대로 ***, 송파 테라타워* 제비동 ***-**호 (문정동)5854(주)디에이치운수2023-03-30 15:49:29I2022-12-04 00:01:00.0<NA><NA><NA><NA><NA><NA><NA><NA>
5532300003230000008202300022023-04-19<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 송파구 오금동 ***서울특별시 송파구 마천로**길 *, ***호 (오금동)5722성수화물2023-04-19 13:09:24I2022-12-03 22:01:00.0<NA>212123.802311444718.676192<NA><NA><NA><NA><NA>
5632300003230000008202300032023-05-31<NA>1영업/정상0정상<NA><NA><NA><NA>02-406-710674.52<NA>서울특별시 송파구 문정동 ***-* 엠스테이트서울특별시 송파구 법원로 ***, 엠스테이트 에이동 *층 ***호 (문정동)5854(주)엘제이 로지스틱스2023-05-31 16:44:45I2022-12-06 00:02:00.0<NA><NA><NA><NA><NA><NA><NA><NA>
5732300003230000008202300042023-07-21<NA>1영업/정상0정상<NA><NA><NA><NA><NA>61.8<NA>서울특별시 송파구 문정동 ***-* 문정역SKV*서울특별시 송파구 법원로 ***, 문정역SKV* 제지하*층 제씨지 ***호 (문정동)5854문정축산2023-07-21 09:44:44I2022-12-06 22:03:00.0<NA><NA><NA><NA><NA><NA><NA><NA>
5832300003230000008202300052023-07-26<NA>1영업/정상0정상<NA><NA><NA><NA>02-406-675017.21<NA>서울특별시 송파구 가락동 **-* 가락우성아파트서울특별시 송파구 송파대로**길 *, *층 **호 (가락동, 가락우성아파트)5711그린농수산2023-07-26 14:13:31I2022-12-06 22:08:00.0<NA>210347.070744443830.404153<NA><NA><NA><NA><NA>
5932300003230000008202400012024-04-03<NA>1영업/정상0정상<NA><NA><NA><NA>029729460181.8<NA>서울특별시 송파구 방이동 ***-* 금천빌딩서울특별시 송파구 오금로 ***, 금천빌딩 *층 (방이동)5642주식회사 태성상사2024-04-03 10:18:26I2023-12-04 00:05:00.0<NA>210092.736423445214.179934<NA><NA><NA><NA><NA>