Overview

Dataset statistics

Number of variables30
Number of observations104
Missing cells966
Missing cells (%)31.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory26.0 KiB
Average record size in memory256.3 B

Variable types

Categorical10
Numeric5
DateTime5
Unsupported6
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-16505/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
휴업시작일자 has constant value ""Constant
휴업종료일자 has constant value ""Constant
총인원 is highly imbalanced (86.3%)Imbalance
인허가취소일자 has 104 (100.0%) missing valuesMissing
폐업일자 has 48 (46.2%) missing valuesMissing
휴업시작일자 has 103 (99.0%) missing valuesMissing
휴업종료일자 has 103 (99.0%) missing valuesMissing
재개업일자 has 104 (100.0%) missing valuesMissing
전화번호 has 6 (5.8%) missing valuesMissing
소재지면적 has 4 (3.8%) missing valuesMissing
소재지우편번호 has 104 (100.0%) missing valuesMissing
도로명주소 has 13 (12.5%) missing valuesMissing
도로명우편번호 has 41 (39.4%) missing valuesMissing
업태구분명 has 104 (100.0%) missing valuesMissing
좌표정보(X) has 12 (11.5%) missing valuesMissing
좌표정보(Y) has 12 (11.5%) missing valuesMissing
축산물가공업구분명 has 104 (100.0%) missing valuesMissing
축산일련번호 has 104 (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
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
축산일련번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 33 (31.7%) zerosZeros

Reproduction

Analysis started2024-04-29 19:03:22.917311
Analysis finished2024-04-29 19:03:23.570619
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size964.0 B
3140000
104 

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 104
100.0%

Length

2024-04-30T04:03:23.629550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:03:23.714438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 104
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct104
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 size1.0 KiB
2024-04-30T04:03:23.799223image/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
Range330003
Interquartile range (IQR)112512

Descriptive statistics

Standard deviation80582.318
Coefficient of variation (CV)2.5663159 × 10-13
Kurtosis-0.74381242
Mean3.14 × 1017
Median Absolute Deviation (MAD)59968
Skewness-0.013481499
Sum-4.237488 × 1018
Variance6.49351 × 109
MonotonicityStrictly increasing
2024-04-30T04:03:23.915322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
314000001019900001 1
 
1.0%
314000001020080001 1
 
1.0%
314000001020140004 1
 
1.0%
314000001020140003 1
 
1.0%
314000001020140002 1
 
1.0%
314000001020140001 1
 
1.0%
314000001020130005 1
 
1.0%
314000001020130004 1
 
1.0%
314000001020130003 1
 
1.0%
314000001020130002 1
 
1.0%
Other values (94) 94
90.4%
ValueCountFrequency (%)
314000001019900001 1
1.0%
314000001019900002 1
1.0%
314000001019940001 1
1.0%
314000001019940002 1
1.0%
314000001019940003 1
1.0%
314000001019950001 1
1.0%
314000001019950002 1
1.0%
314000001019960001 1
1.0%
314000001019960002 1
1.0%
314000001019970001 1
1.0%
ValueCountFrequency (%)
314000001020230004 1
1.0%
314000001020230003 1
1.0%
314000001020230002 1
1.0%
314000001020220001 1
1.0%
314000001020210002 1
1.0%
314000001020210001 1
1.0%
314000001020200003 1
1.0%
314000001020200002 1
1.0%
314000001020200001 1
1.0%
314000001020190004 1
1.0%

인허가일자
Date

Distinct102
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size964.0 B
Minimum1990-01-30 00:00:00
Maximum2023-09-07 00:00:00
2024-04-30T04:03:24.039852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:03:24.162959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing104
Missing (%)100.0%
Memory size1.0 KiB

영업상태코드
Categorical

Distinct3
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size964.0 B
3
56 
1
47 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 56
53.8%
1 47
45.2%
2 1
 
1.0%

Length

2024-04-30T04:03:24.273282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:03:24.360727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 56
53.8%
1 47
45.2%
2 1
 
1.0%

영업상태명
Categorical

Distinct3
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size964.0 B
폐업
56 
영업/정상
47 
휴업
 
1

Length

Max length5
Median length2
Mean length3.3557692
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 56
53.8%
영업/정상 47
45.2%
휴업 1
 
1.0%

Length

2024-04-30T04:03:24.452082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:03:24.534636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 56
53.8%
영업/정상 47
45.2%
휴업 1
 
1.0%

상세영업상태코드
Categorical

Distinct3
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size964.0 B
2
56 
0
47 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 56
53.8%
0 47
45.2%
1 1
 
1.0%

Length

2024-04-30T04:03:24.615047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:03:24.702819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 56
53.8%
0 47
45.2%
1 1
 
1.0%

상세영업상태명
Categorical

Distinct3
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size964.0 B
폐업
56 
정상
47 
휴업
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 56
53.8%
정상 47
45.2%
휴업 1
 
1.0%

Length

2024-04-30T04:03:24.789880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:03:24.889861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 56
53.8%
정상 47
45.2%
휴업 1
 
1.0%

폐업일자
Date

MISSING 

Distinct55
Distinct (%)98.2%
Missing48
Missing (%)46.2%
Memory size964.0 B
Minimum2003-04-14 00:00:00
Maximum2023-03-24 00:00:00
2024-04-30T04:03:24.991248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:03:25.127274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing103
Missing (%)99.0%
Memory size964.0 B
Minimum2023-07-12 00:00:00
Maximum2023-07-12 00:00:00
2024-04-30T04:03:25.212428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:03:25.286994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

휴업종료일자
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing103
Missing (%)99.0%
Memory size964.0 B
Minimum2024-07-12 00:00:00
Maximum2024-07-12 00:00:00
2024-04-30T04:03:25.355523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:03:25.427785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing104
Missing (%)100.0%
Memory size1.0 KiB

전화번호
Text

MISSING 

Distinct78
Distinct (%)79.6%
Missing6
Missing (%)5.8%
Memory size964.0 B
2024-04-30T04:03:25.635450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length9.744898
Min length7

Characters and Unicode

Total characters955
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)64.3%

Sample

1st row2693-8883
2nd row2642-9159
3rd row02-2651-9953
4th row2608-5886
5th row692-7283
ValueCountFrequency (%)
2643-0283 5
 
5.1%
02-2643-0283 3
 
3.1%
2651-1855 3
 
3.1%
2645-7611 2
 
2.0%
2647-1772 2
 
2.0%
2644-0069 2
 
2.0%
2694-9550 2
 
2.0%
2690-5673 2
 
2.0%
2608-5886 2
 
2.0%
2604-0156 2
 
2.0%
Other values (68) 73
74.5%
2024-04-30T04:03:25.984631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 183
19.2%
6 118
12.4%
- 117
12.3%
5 97
10.2%
0 83
8.7%
4 80
8.4%
8 73
 
7.6%
7 71
 
7.4%
9 49
 
5.1%
3 41
 
4.3%
Other values (2) 43
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 836
87.5%
Dash Punctuation 117
 
12.3%
Close Punctuation 2
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 183
21.9%
6 118
14.1%
5 97
11.6%
0 83
9.9%
4 80
9.6%
8 73
 
8.7%
7 71
 
8.5%
9 49
 
5.9%
3 41
 
4.9%
1 41
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 117
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 955
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 183
19.2%
6 118
12.4%
- 117
12.3%
5 97
10.2%
0 83
8.7%
4 80
8.4%
8 73
 
7.6%
7 71
 
7.4%
9 49
 
5.1%
3 41
 
4.3%
Other values (2) 43
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 955
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 183
19.2%
6 118
12.4%
- 117
12.3%
5 97
10.2%
0 83
8.7%
4 80
8.4%
8 73
 
7.6%
7 71
 
7.4%
9 49
 
5.1%
3 41
 
4.3%
Other values (2) 43
 
4.5%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct55
Distinct (%)55.0%
Missing4
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean57.6299
Minimum0
Maximum776
Zeros33
Zeros (%)31.7%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-30T04:03:26.123283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median40.55
Q362
95-th percentile259.64
Maximum776
Range776
Interquartile range (IQR)62

Descriptive statistics

Standard deviation98.886814
Coefficient of variation (CV)1.7158942
Kurtosis28.586872
Mean57.6299
Median Absolute Deviation (MAD)40.05
Skewness4.5912807
Sum5762.99
Variance9778.602
MonotonicityNot monotonic
2024-04-30T04:03:26.245600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 33
31.7%
1.0 4
 
3.8%
40.0 3
 
2.9%
42.6 3
 
2.9%
28.0 3
 
2.9%
62.0 3
 
2.9%
44.8 2
 
1.9%
259.64 2
 
1.9%
105.57 1
 
1.0%
47.84 1
 
1.0%
Other values (45) 45
43.3%
(Missing) 4
 
3.8%
ValueCountFrequency (%)
0.0 33
31.7%
1.0 4
 
3.8%
24.0 1
 
1.0%
25.16 1
 
1.0%
28.0 3
 
2.9%
31.5 1
 
1.0%
32.9 1
 
1.0%
33.6 1
 
1.0%
36.0 1
 
1.0%
38.0 1
 
1.0%
ValueCountFrequency (%)
776.0 1
1.0%
329.18 1
1.0%
314.0 1
1.0%
270.0 1
1.0%
259.64 2
1.9%
168.5 1
1.0%
166.0 1
1.0%
149.42 1
1.0%
128.3 1
1.0%
110.62 1
1.0%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing104
Missing (%)100.0%
Memory size1.0 KiB

지번주소
Text

Distinct96
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Memory size964.0 B
2024-04-30T04:03:26.470506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length34
Mean length26.115385
Min length18

Characters and Unicode

Total characters2716
Distinct characters110
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

Unique89 ?
Unique (%)85.6%

Sample

1st row서울특별시 양천구 신월동 501-12
2nd row서울특별시 양천구 목동 657-16
3rd row서울특별시 양천구 신정동 1020-17
4th row서울특별시 양천구 신월동 512-7번지
5th row서울특별시 양천구 신월동 64-1 번지
ValueCountFrequency (%)
서울특별시 104
19.8%
양천구 104
19.8%
목동 50
 
9.5%
신정동 35
 
6.7%
신월동 19
 
3.6%
번지 12
 
2.3%
1층 12
 
2.3%
919-7 6
 
1.1%
106호 5
 
1.0%
898-2번지 4
 
0.8%
Other values (137) 173
33.0%
2024-04-30T04:03:26.866794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
518
19.1%
1 128
 
4.7%
동 122
 
4.5%
시 106
 
3.9%
서 104
 
3.8%
천 104
 
3.8%
구 104
 
3.8%
울 104
 
3.8%
양 104
 
3.8%
별 104
 
3.8%
Other values (100) 1218
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1544
56.8%
Decimal Number 550
 
20.3%
Space Separator 518
 
19.1%
Dash Punctuation 92
 
3.4%
Other Punctuation 5
 
0.2%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%
Uppercase Letter 2
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 122
 
7.9%
시 106
 
6.9%
서 104
 
6.7%
천 104
 
6.7%
구 104
 
6.7%
울 104
 
6.7%
양 104
 
6.7%
별 104
 
6.7%
특 104
 
6.7%
지 75
 
4.9%
Other values (82) 513
33.2%
Decimal Number
ValueCountFrequency (%)
1 128
23.3%
2 71
12.9%
0 63
11.5%
9 55
10.0%
7 52
9.5%
3 46
 
8.4%
5 40
 
7.3%
6 37
 
6.7%
8 29
 
5.3%
4 29
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
M 1
50.0%
Space Separator
ValueCountFrequency (%)
518
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 92
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1544
56.8%
Common 1170
43.1%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 122
 
7.9%
시 106
 
6.9%
서 104
 
6.7%
천 104
 
6.7%
구 104
 
6.7%
울 104
 
6.7%
양 104
 
6.7%
별 104
 
6.7%
특 104
 
6.7%
지 75
 
4.9%
Other values (82) 513
33.2%
Common
ValueCountFrequency (%)
518
44.3%
1 128
 
10.9%
- 92
 
7.9%
2 71
 
6.1%
0 63
 
5.4%
9 55
 
4.7%
7 52
 
4.4%
3 46
 
3.9%
5 40
 
3.4%
6 37
 
3.2%
Other values (6) 68
 
5.8%
Latin
ValueCountFrequency (%)
B 1
50.0%
M 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1544
56.8%
ASCII 1172
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
518
44.2%
1 128
 
10.9%
- 92
 
7.8%
2 71
 
6.1%
0 63
 
5.4%
9 55
 
4.7%
7 52
 
4.4%
3 46
 
3.9%
5 40
 
3.4%
6 37
 
3.2%
Other values (8) 70
 
6.0%
Hangul
ValueCountFrequency (%)
동 122
 
7.9%
시 106
 
6.9%
서 104
 
6.7%
천 104
 
6.7%
구 104
 
6.7%
울 104
 
6.7%
양 104
 
6.7%
별 104
 
6.7%
특 104
 
6.7%
지 75
 
4.9%
Other values (82) 513
33.2%

도로명주소
Text

MISSING 

Distinct80
Distinct (%)87.9%
Missing13
Missing (%)12.5%
Memory size964.0 B
2024-04-30T04:03:27.105091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length46
Mean length28.538462
Min length21

Characters and Unicode

Total characters2597
Distinct characters112
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

Unique71 ?
Unique (%)78.0%

Sample

1st row서울특별시 양천구 중앙로 295 (신월동)
2nd row서울특별시 양천구 등촌로 160 (목동)
3rd row서울특별시 양천구 은행정로 10 (신정동)
4th row서울특별시 양천구 신월로 199 (신월동)
5th row서울특별시 양천구 등촌로 58 (목동)
ValueCountFrequency (%)
서울특별시 91
17.4%
양천구 91
17.4%
목동 29
 
5.5%
신정동 28
 
5.3%
목동서로 17
 
3.2%
신월동 16
 
3.1%
1층 14
 
2.7%
등촌로 9
 
1.7%
목동로 8
 
1.5%
신월로 7
 
1.3%
Other values (141) 214
40.8%
2024-04-30T04:03:27.456497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
433
 
16.7%
동 154
 
5.9%
서 109
 
4.2%
목 102
 
3.9%
1 100
 
3.9%
시 93
 
3.6%
양 93
 
3.6%
) 92
 
3.5%
( 92
 
3.5%
로 92
 
3.5%
Other values (102) 1237
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1567
60.3%
Space Separator 433
 
16.7%
Decimal Number 349
 
13.4%
Close Punctuation 92
 
3.5%
Open Punctuation 92
 
3.5%
Other Punctuation 59
 
2.3%
Dash Punctuation 3
 
0.1%
Uppercase Letter 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 154
 
9.8%
서 109
 
7.0%
목 102
 
6.5%
시 93
 
5.9%
양 93
 
5.9%
로 92
 
5.9%
구 91
 
5.8%
천 91
 
5.8%
별 91
 
5.8%
특 91
 
5.8%
Other values (85) 560
35.7%
Decimal Number
ValueCountFrequency (%)
1 100
28.7%
2 48
13.8%
0 45
12.9%
3 41
11.7%
7 28
 
8.0%
4 19
 
5.4%
9 18
 
5.2%
8 17
 
4.9%
5 17
 
4.9%
6 16
 
4.6%
Space Separator
ValueCountFrequency (%)
433
100.0%
Close Punctuation
ValueCountFrequency (%)
) 92
100.0%
Open Punctuation
ValueCountFrequency (%)
( 92
100.0%
Other Punctuation
ValueCountFrequency (%)
, 59
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1567
60.3%
Common 1029
39.6%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 154
 
9.8%
서 109
 
7.0%
목 102
 
6.5%
시 93
 
5.9%
양 93
 
5.9%
로 92
 
5.9%
구 91
 
5.8%
천 91
 
5.8%
별 91
 
5.8%
특 91
 
5.8%
Other values (85) 560
35.7%
Common
ValueCountFrequency (%)
433
42.1%
1 100
 
9.7%
) 92
 
8.9%
( 92
 
8.9%
, 59
 
5.7%
2 48
 
4.7%
0 45
 
4.4%
3 41
 
4.0%
7 28
 
2.7%
4 19
 
1.8%
Other values (6) 72
 
7.0%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1567
60.3%
ASCII 1030
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
433
42.0%
1 100
 
9.7%
) 92
 
8.9%
( 92
 
8.9%
, 59
 
5.7%
2 48
 
4.7%
0 45
 
4.4%
3 41
 
4.0%
7 28
 
2.7%
4 19
 
1.8%
Other values (7) 73
 
7.1%
Hangul
ValueCountFrequency (%)
동 154
 
9.8%
서 109
 
7.0%
목 102
 
6.5%
시 93
 
5.9%
양 93
 
5.9%
로 92
 
5.9%
구 91
 
5.8%
천 91
 
5.8%
별 91
 
5.8%
특 91
 
5.8%
Other values (85) 560
35.7%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct47
Distinct (%)74.6%
Missing41
Missing (%)39.4%
Infinite0
Infinite (%)0.0%
Mean8003.0476
Minimum7905
Maximum8106
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-30T04:03:27.578895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7905
5-th percentile7930.6
Q17954
median7997
Q38045.5
95-th percentile8095
Maximum8106
Range201
Interquartile range (IQR)91.5

Descriptive statistics

Standard deviation57.501593
Coefficient of variation (CV)0.007184962
Kurtosis-1.1033583
Mean8003.0476
Median Absolute Deviation (MAD)46
Skewness0.3581952
Sum504192
Variance3306.4332
MonotonicityNot monotonic
2024-04-30T04:03:27.703558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
7937 4
 
3.8%
7965 3
 
2.9%
8104 2
 
1.9%
8023 2
 
1.9%
7947 2
 
1.9%
7983 2
 
1.9%
7951 2
 
1.9%
8091 2
 
1.9%
7946 2
 
1.9%
7966 2
 
1.9%
Other values (37) 40
38.5%
(Missing) 41
39.4%
ValueCountFrequency (%)
7905 1
 
1.0%
7921 1
 
1.0%
7923 1
 
1.0%
7930 1
 
1.0%
7936 1
 
1.0%
7937 4
3.8%
7946 2
1.9%
7947 2
1.9%
7948 1
 
1.0%
7951 2
1.9%
ValueCountFrequency (%)
8106 1
1.0%
8104 2
1.9%
8095 2
1.9%
8093 1
1.0%
8092 1
1.0%
8091 2
1.9%
8087 1
1.0%
8082 1
1.0%
8073 1
1.0%
8065 1
1.0%

사업장명
Text

Distinct87
Distinct (%)83.7%
Missing0
Missing (%)0.0%
Memory size964.0 B
2024-04-30T04:03:27.892031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length7.5384615
Min length6

Characters and Unicode

Total characters784
Distinct characters135
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

Unique77 ?
Unique (%)74.0%

Sample

1st row우신동물병원
2nd row강현림 종합동물병원
3rd row해성동물병원
4th row신월동물병원
5th row강성동물병원
ValueCountFrequency (%)
동물병원 23
 
16.7%
닥터펫 5
 
3.6%
닥터펫동물병원 4
 
2.9%
대현동물병원 3
 
2.2%
하니동물병원 3
 
2.2%
신월동물병원 2
 
1.4%
우리들 2
 
1.4%
바우동물병원 2
 
1.4%
24시 2
 
1.4%
상아동물병원 2
 
1.4%
Other values (87) 90
65.2%
2024-04-30T04:03:28.210013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 107
 
13.6%
물 103
 
13.1%
원 94
 
12.0%
병 93
 
11.9%
34
 
4.3%
터 21
 
2.7%
펫 18
 
2.3%
센 11
 
1.4%
리 11
 
1.4%
합 10
 
1.3%
Other values (125) 282
36.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 738
94.1%
Space Separator 34
 
4.3%
Decimal Number 6
 
0.8%
Lowercase Letter 3
 
0.4%
Uppercase Letter 2
 
0.3%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 107
14.5%
물 103
 
14.0%
원 94
 
12.7%
병 93
 
12.6%
터 21
 
2.8%
펫 18
 
2.4%
센 11
 
1.5%
리 11
 
1.5%
합 10
 
1.4%
종 10
 
1.4%
Other values (116) 260
35.2%
Lowercase Letter
ValueCountFrequency (%)
t 1
33.3%
e 1
33.3%
r 1
33.3%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
4 3
50.0%
Uppercase Letter
ValueCountFrequency (%)
P 1
50.0%
D 1
50.0%
Space Separator
ValueCountFrequency (%)
34
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 738
94.1%
Common 41
 
5.2%
Latin 5
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 107
14.5%
물 103
 
14.0%
원 94
 
12.7%
병 93
 
12.6%
터 21
 
2.8%
펫 18
 
2.4%
센 11
 
1.5%
리 11
 
1.5%
합 10
 
1.4%
종 10
 
1.4%
Other values (116) 260
35.2%
Latin
ValueCountFrequency (%)
t 1
20.0%
e 1
20.0%
P 1
20.0%
r 1
20.0%
D 1
20.0%
Common
ValueCountFrequency (%)
34
82.9%
2 3
 
7.3%
4 3
 
7.3%
. 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 738
94.1%
ASCII 46
 
5.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 107
14.5%
물 103
 
14.0%
원 94
 
12.7%
병 93
 
12.6%
터 21
 
2.8%
펫 18
 
2.4%
센 11
 
1.5%
리 11
 
1.5%
합 10
 
1.4%
종 10
 
1.4%
Other values (116) 260
35.2%
ASCII
ValueCountFrequency (%)
34
73.9%
2 3
 
6.5%
4 3
 
6.5%
t 1
 
2.2%
e 1
 
2.2%
P 1
 
2.2%
. 1
 
2.2%
r 1
 
2.2%
D 1
 
2.2%

최종수정일자
Date

UNIQUE 

Distinct104
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size964.0 B
Minimum2003-07-02 11:04:12
Maximum2024-04-05 09:10:13
2024-04-30T04:03:28.324326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:03:28.614385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size964.0 B
I
54 
U
50 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 54
51.9%
U 50
48.1%

Length

2024-04-30T04:03:28.725981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:03:28.804116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 54
51.9%
u 50
48.1%

데이터갱신일자
Categorical

Distinct42
Distinct (%)40.4%
Missing0
Missing (%)0.0%
Memory size964.0 B
2018-08-31 23:59:59.0
50 
2020-11-12 02:40:00.0
7 
2022-12-02 22:06:00.0
 
3
2019-01-18 02:40:00.0
 
3
2022-12-03 22:09:00.0
 
2
Other values (37)
39 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique35 ?
Unique (%)33.7%

Sample

1st row2022-12-05 23:00:00.0
2nd row2020-11-12 02:40:00.0
3rd row2021-12-05 00:04:00.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 50
48.1%
2020-11-12 02:40:00.0 7
 
6.7%
2022-12-02 22:06:00.0 3
 
2.9%
2019-01-18 02:40:00.0 3
 
2.9%
2022-12-03 22:09:00.0 2
 
1.9%
2019-03-08 02:40:00.0 2
 
1.9%
2022-12-05 23:06:00.0 2
 
1.9%
2020-03-21 02:40:00.0 1
 
1.0%
2021-12-05 00:04:00.0 1
 
1.0%
2018-10-15 23:59:59.0 1
 
1.0%
Other values (32) 32
30.8%

Length

2024-04-30T04:03:28.883097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
23:59:59.0 51
24.5%
2018-08-31 50
24.0%
02:40:00.0 27
13.0%
2020-11-12 7
 
3.4%
2022-12-05 4
 
1.9%
2022-12-02 3
 
1.4%
22:06:00.0 3
 
1.4%
2019-01-18 3
 
1.4%
2022-12-03 2
 
1.0%
22:09:00.0 2
 
1.0%
Other values (52) 56
26.9%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing104
Missing (%)100.0%
Memory size1.0 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct66
Distinct (%)71.7%
Missing12
Missing (%)11.5%
Infinite0
Infinite (%)0.0%
Mean187741.84
Minimum184767.73
Maximum189512.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-30T04:03:28.991309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184767.73
5-th percentile185562.95
Q1187158.47
median187938.16
Q3188564.8
95-th percentile189055.49
Maximum189512.05
Range4744.3156
Interquartile range (IQR)1406.329

Descriptive statistics

Standard deviation1130.8303
Coefficient of variation (CV)0.0060233261
Kurtosis-0.038629413
Mean187741.84
Median Absolute Deviation (MAD)714.31313
Skewness-0.90429921
Sum17272249
Variance1278777.2
MonotonicityNot monotonic
2024-04-30T04:03:29.113231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
188729.190478822 6
 
5.8%
187866.51995498 4
 
3.8%
187079.375126738 3
 
2.9%
188977.171050288 3
 
2.9%
187158.467033065 3
 
2.9%
187646.629756578 3
 
2.9%
187890.251114546 3
 
2.9%
185992.29499381 2
 
1.9%
185562.951924004 2
 
1.9%
189151.208015925 2
 
1.9%
Other values (56) 61
58.7%
(Missing) 12
 
11.5%
ValueCountFrequency (%)
184767.729553942 1
1.0%
185117.794648334 1
1.0%
185125.957709458 1
1.0%
185337.191425189 1
1.0%
185562.951924004 2
1.9%
185585.990207369 1
1.0%
185586.445641247 1
1.0%
185810.065888388 1
1.0%
185860.979146266 1
1.0%
185992.29499381 2
1.9%
ValueCountFrequency (%)
189512.045139098 1
 
1.0%
189311.02246611 2
 
1.9%
189151.208015925 2
 
1.9%
188977.171050288 3
2.9%
188918.535367036 2
 
1.9%
188828.544788973 1
 
1.0%
188813.809498067 1
 
1.0%
188729.190478822 6
5.8%
188700.851169641 1
 
1.0%
188685.978168598 1
 
1.0%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct66
Distinct (%)71.7%
Missing12
Missing (%)11.5%
Infinite0
Infinite (%)0.0%
Mean447251.06
Minimum445073.76
Maximum449701.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-30T04:03:29.230659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum445073.76
5-th percentile445678.08
Q1446243.21
median447091.86
Q3448106.57
95-th percentile449389.21
Maximum449701.8
Range4628.0405
Interquartile range (IQR)1863.3578

Descriptive statistics

Standard deviation1153.4761
Coefficient of variation (CV)0.0025790349
Kurtosis-0.6486037
Mean447251.06
Median Absolute Deviation (MAD)921.64031
Skewness0.37082757
Sum41147098
Variance1330507.1
MonotonicityNot monotonic
2024-04-30T04:03:29.341019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447572.610039376 6
 
5.8%
447451.595714316 4
 
3.8%
446116.629313272 3
 
2.9%
447466.355031447 3
 
2.9%
445678.076325463 3
 
2.9%
445993.33256629 3
 
2.9%
448106.571502671 3
 
2.9%
446855.110008127 2
 
1.9%
447671.835790408 2
 
1.9%
448200.067716589 2
 
1.9%
Other values (56) 61
58.7%
(Missing) 12
 
11.5%
ValueCountFrequency (%)
445073.76201045 1
 
1.0%
445120.122760486 1
 
1.0%
445390.869067966 1
 
1.0%
445643.874069493 1
 
1.0%
445678.076325463 3
2.9%
445910.803771191 1
 
1.0%
445920.374891605 1
 
1.0%
445993.33256629 3
2.9%
446003.941216623 1
 
1.0%
446018.063168796 1
 
1.0%
ValueCountFrequency (%)
449701.802558519 1
1.0%
449662.909076605 1
1.0%
449540.781075325 1
1.0%
449409.143621821 1
1.0%
449389.208595744 2
1.9%
449290.733051822 2
1.9%
449204.635182585 1
1.0%
449143.102014667 1
1.0%
449099.406847977 1
1.0%
448665.257157041 1
1.0%

축산업무구분명
Categorical

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size964.0 B
동물병원
82 
<NA>
22 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
동물병원 82
78.8%
<NA> 22
 
21.2%

Length

2024-04-30T04:03:29.437790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:03:29.526770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동물병원 82
78.8%
na 22
 
21.2%

축산물가공업구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing104
Missing (%)100.0%
Memory size1.0 KiB

축산일련번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing104
Missing (%)100.0%
Memory size1.0 KiB

권리주체일련번호
Categorical

Distinct3
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size964.0 B
000
81 
<NA>
22 
L00
 
1

Length

Max length4
Median length3
Mean length3.2115385
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row<NA>
2nd row000
3rd row<NA>
4th row000
5th row000

Common Values

ValueCountFrequency (%)
000 81
77.9%
<NA> 22
 
21.2%
L00 1
 
1.0%

Length

2024-04-30T04:03:29.611264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:03:29.730262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
000 81
77.9%
na 22
 
21.2%
l00 1
 
1.0%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size964.0 B
<NA>
102 
0
 
2

Length

Max length4
Median length4
Mean length3.9423077
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> 102
98.1%
0 2
 
1.9%

Length

2024-04-30T04:03:29.855582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:03:29.968183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 102
98.1%
0 2
 
1.9%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
031400003140000010199000011990-01-30<NA>1영업/정상0정상<NA><NA><NA><NA>2693-88831.0<NA>서울특별시 양천구 신월동 501-12서울특별시 양천구 중앙로 295 (신월동)8028우신동물병원2023-06-08 09:22:00U2022-12-05 23:00:00.0<NA>186794.842143446714.275789<NA><NA><NA><NA><NA>
1314000031400000101990000219900223<NA>1영업/정상0정상<NA><NA><NA><NA>2642-91591.0<NA>서울특별시 양천구 목동 657-16서울특별시 양천구 등촌로 160 (목동)7951강현림 종합동물병원2020-11-10 20:33:45U2020-11-12 02:40:00.0<NA>187774.076185449099.406848동물병원<NA><NA>000<NA>
2314000031400000101994000119940318<NA>1영업/정상0정상<NA><NA><NA><NA>02-2651-99531.0<NA>서울특별시 양천구 신정동 1020-17서울특별시 양천구 은행정로 10 (신정동)8087해성동물병원2022-05-02 11:40:29U2021-12-05 00:04:00.0<NA>187566.108463446497.584536<NA><NA><NA><NA><NA>
3314000031400000101994000219940707<NA>3폐업2폐업20080820<NA><NA><NA>2608-58861.0<NA>서울특별시 양천구 신월동 512-7번지서울특별시 양천구 신월로 199 (신월동)<NA>신월동물병원2008-08-20 20:03:07I2018-08-31 23:59:59.0<NA>186179.736792446472.412127동물병원<NA><NA>000<NA>
4314000031400000101994000319940812<NA>3폐업2폐업20120808<NA><NA><NA>692-72830.0<NA>서울특별시 양천구 신월동 64-1 번지<NA><NA>강성동물병원2012-08-08 15:05:37I2018-08-31 23:59:59.0<NA><NA><NA>동물병원<NA><NA>000<NA>
5314000031400000101995000119950905<NA>3폐업2폐업20130527<NA><NA><NA>2647-17720.0<NA>서울특별시 양천구 목동 783-2번지서울특별시 양천구 등촌로 58 (목동)7965하니동물병원2013-05-28 10:09:27I2018-08-31 23:59:59.0<NA>187890.251115448106.571503동물병원<NA><NA>000<NA>
6314000031400000101995000219950425<NA>3폐업2폐업20120501<NA><NA><NA>2644-00690.0<NA>서울특별시 양천구 신정동 995-4 번지<NA><NA>상아동물병원2012-05-01 15:04:38I2018-08-31 23:59:59.0<NA><NA><NA>동물병원<NA><NA>000<NA>
7314000031400000101996000119950615<NA>1영업/정상0정상<NA><NA><NA><NA>022654618362.4<NA>서울특별시 양천구 신정동 294-62번지서울특별시 양천구 목동동로10길 6 (신정동)8014노아동물병원2018-10-15 17:28:21U2018-10-15 23:59:59.0<NA>188498.889562446254.470337동물병원<NA><NA>000<NA>
8314000031400000101996000219960128<NA>3폐업2폐업20081107<NA><NA><NA>2651-18550.0<NA>서울특별시 양천구 목동 506-7번지서울특별시 양천구 목동중앙본로 113 (목동)<NA>대현동물병원2008-11-07 15:59:43I2018-08-31 23:59:59.0<NA>188540.174474449290.733052동물병원<NA><NA>000<NA>
9314000031400000101997000119970110<NA>3폐업2폐업20060203<NA><NA><NA>654-73450.0<NA>서울특별시 양천구 목동 788-13 번지<NA><NA>애완동물병원2006-02-06 10:30:58I2018-08-31 23:59:59.0<NA><NA><NA>동물병원<NA><NA>000<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
94314000031400000102019000420191227<NA>3폐업2폐업20221110<NA><NA><NA>02-2642-75880.0<NA>서울특별시 양천구 신정동 1006-3 4층서울특별시 양천구 목동로 171, 4층 (신정동)8023우리들 노령동물 암센터2022-11-16 08:27:45U2021-10-31 23:08:00.0<NA>187971.403234446833.613864<NA><NA><NA><NA><NA>
9531400003140000010202000012020-04-10<NA>1영업/정상0정상<NA><NA><NA><NA>02-6949-0413106.2<NA>서울특별시 양천구 목동 753-12서울특별시 양천구 목동중앙로 89, 1층 (목동)7961봄날동물병원2023-04-27 09:55:03U2022-12-03 22:09:00.0<NA>188605.762731448342.943185<NA><NA><NA><NA><NA>
9631400003140000010202000022020-05-08<NA>1영업/정상0정상<NA><NA><NA><NA>02-2607-758261.52<NA>서울특별시 양천구 신월동 1002-3서울특별시 양천구 신월로 124, 1층 (신월동)8047신월동물병원2023-04-27 09:55:53U2022-12-03 22:09:00.0<NA>185586.445641446018.063169<NA><NA><NA><NA><NA>
97314000031400000102020000320200723<NA>1영업/정상0정상<NA><NA><NA><NA>02-2653-333587.0<NA>서울특별시 양천구 신정동 324-7 대림아크로빌 102호서울특별시 양천구 목동서로 401, 1층 102호 (신정동, 대림아크로빌)8092산책동물병원2020-07-23 16:08:35I2020-07-25 00:23:15.0<NA>187518.093591445920.374892동물병원<NA><NA>000<NA>
98314000031400000102021000120210820<NA>1영업/정상0정상<NA><NA><NA><NA>022691811962.0<NA>서울특별시 양천구 신월동 559-7 2층서울특별시 양천구 신월로10길 22, 2층층 (신월동)8065정말로동물병원2021-11-26 19:14:01U2021-11-28 02:40:00.0<NA>185860.979146445910.803771동물병원<NA><NA>0000
9931400003140000010202100022021-08-25<NA>1영업/정상0정상<NA><NA><NA><NA>02-2694-7575110.62<NA>서울특별시 양천구 신월동 536-6 1층서울특별시 양천구 신월로 179, 1층 (신월동)8030신월라온동물의료센터2024-03-28 15:39:44U2023-12-02 21:00:00.0<NA>186052.170748446339.972046<NA><NA><NA><NA><NA>
10031400003140000010202200012022-07-21<NA>1영업/정상0정상<NA><NA><NA><NA>0226987582<NA><NA>서울특별시 양천구 신월동 602-1서울특별시 양천구 신월로 208(신월동)806324시월드펫동물메디컬센터2023-06-14 17:51:08U2022-12-05 23:06:00.0<NA>186262.212836446486.385297<NA><NA><NA><NA><NA>
10131400003140000010202300022023-03-24<NA>1영업/정상0정상<NA><NA><NA><NA>02-2650-8275<NA><NA>서울특별시 양천구 신정동 321-6 센트럴프라자 203호서울특별시 양천구 목동서로 349, 센트럴프라자 203호 (신정동)8095공원옆동물의료센터2023-03-24 16:05:12I2022-12-02 22:06:00.0<NA>188039.543425446149.197185<NA><NA><NA><NA><NA>
10231400003140000010202300032023-06-01<NA>1영업/정상0정상<NA><NA><NA><NA>02)2062-798254.0<NA>서울특별시 양천구 목동 917-6 중소기업유통센터(행복한백화점)서울특별시 양천구 목동동로 309, 중소기업유통센터(행복한백화점) 지하2층 (목동)7997펫사랑동물병원2023-06-14 14:20:15U2022-12-05 23:06:00.0<NA>188977.17105447466.355031<NA><NA><NA><NA><NA>
10331400003140000010202300042023-09-07<NA>1영업/정상0정상<NA><NA><NA><NA>02)6953-7576776.0<NA>서울특별시 양천구 목동 807-1서울특별시 양천구 등촌로 10, 1~2층 (목동)796624시 로운동물의료센터2023-10-19 18:08:27U2022-10-30 22:01:00.0<NA>187932.730876447620.266191<NA><NA><NA><NA><NA>