Overview

Dataset statistics

Number of variables44
Number of observations7385
Missing cells109567
Missing cells (%)33.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 MiB
Average record size in memory377.0 B

Variable types

Categorical15
Text8
DateTime4
Unsupported9
Numeric7
Boolean1

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),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author서초구
URLhttps://data.seoul.go.kr/dataList/OA-18098/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
홈페이지 has constant value ""Constant
남성종사자수 is highly imbalanced (67.9%)Imbalance
여성종사자수 is highly imbalanced (67.9%)Imbalance
급수시설구분명 is highly imbalanced (97.1%)Imbalance
총인원 is highly imbalanced (68.1%)Imbalance
본사종업원수 is highly imbalanced (66.1%)Imbalance
공장사무직종업원수 is highly imbalanced (66.1%)Imbalance
인허가취소일자 has 7385 (100.0%) missing valuesMissing
폐업일자 has 2405 (32.6%) missing valuesMissing
휴업시작일자 has 7385 (100.0%) missing valuesMissing
휴업종료일자 has 7385 (100.0%) missing valuesMissing
재개업일자 has 7385 (100.0%) missing valuesMissing
전화번호 has 4057 (54.9%) missing valuesMissing
소재지면적 has 3689 (50.0%) missing valuesMissing
도로명주소 has 1508 (20.4%) missing valuesMissing
도로명우편번호 has 1555 (21.1%) missing valuesMissing
업태구분명 has 7385 (100.0%) missing valuesMissing
좌표정보(X) has 83 (1.1%) missing valuesMissing
좌표정보(Y) has 83 (1.1%) missing valuesMissing
영업장주변구분명 has 7385 (100.0%) missing valuesMissing
등급구분명 has 7385 (100.0%) missing valuesMissing
공장판매직종업원수 has 5684 (77.0%) missing valuesMissing
보증액 has 6421 (86.9%) missing valuesMissing
월세액 has 6421 (86.9%) missing valuesMissing
다중이용업소여부 has 1906 (25.8%) missing valuesMissing
시설총규모 has 1906 (25.8%) missing valuesMissing
전통업소지정번호 has 7385 (100.0%) missing valuesMissing
전통업소주된음식 has 7385 (100.0%) missing valuesMissing
홈페이지 has 7384 (> 99.9%) missing valuesMissing
도로명우편번호 is highly skewed (γ1 = 74.82479645)Skewed
공장판매직종업원수 is highly skewed (γ1 = 36.2791789)Skewed
관리번호 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
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
영업장주변구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등급구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
공장판매직종업원수 has 1694 (22.9%) zerosZeros
보증액 has 955 (12.9%) zerosZeros
월세액 has 955 (12.9%) zerosZeros
시설총규모 has 5086 (68.9%) zerosZeros

Reproduction

Analysis started2024-05-11 06:58:20.455666
Analysis finished2024-05-11 06:58:25.770300
Duration5.31 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
3210000
7385 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3210000
2nd row3210000
3rd row3210000
4th row3210000
5th row3210000

Common Values

ValueCountFrequency (%)
3210000 7385
100.0%

Length

2024-05-11T06:58:26.045666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:58:26.398867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3210000 7385
100.0%

관리번호
Text

UNIQUE 

Distinct7385
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
2024-05-11T06:58:26.818993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters162470
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

Unique7385 ?
Unique (%)100.0%

Sample

1st row3210000-134-2004-00001
2nd row3210000-134-2004-00002
3rd row3210000-134-2004-00003
4th row3210000-134-2004-00005
5th row3210000-134-2004-00006
ValueCountFrequency (%)
3210000-134-2004-00001 1
 
< 0.1%
3210000-134-2019-00013 1
 
< 0.1%
3210000-134-2019-00011 1
 
< 0.1%
3210000-134-2019-00010 1
 
< 0.1%
3210000-134-2019-00009 1
 
< 0.1%
3210000-134-2019-00008 1
 
< 0.1%
3210000-134-2019-00007 1
 
< 0.1%
3210000-134-2019-00006 1
 
< 0.1%
3210000-134-2019-00005 1
 
< 0.1%
3210000-134-2019-00004 1
 
< 0.1%
Other values (7375) 7375
99.9%
2024-05-11T06:58:27.604503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 58047
35.7%
1 22631
 
13.9%
- 22155
 
13.6%
2 20586
 
12.7%
3 17660
 
10.9%
4 11135
 
6.9%
5 2186
 
1.3%
9 2125
 
1.3%
6 2000
 
1.2%
7 1990
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 140315
86.4%
Dash Punctuation 22155
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 58047
41.4%
1 22631
 
16.1%
2 20586
 
14.7%
3 17660
 
12.6%
4 11135
 
7.9%
5 2186
 
1.6%
9 2125
 
1.5%
6 2000
 
1.4%
7 1990
 
1.4%
8 1955
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 22155
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 162470
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 58047
35.7%
1 22631
 
13.9%
- 22155
 
13.6%
2 20586
 
12.7%
3 17660
 
10.9%
4 11135
 
6.9%
5 2186
 
1.3%
9 2125
 
1.3%
6 2000
 
1.2%
7 1990
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 162470
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 58047
35.7%
1 22631
 
13.9%
- 22155
 
13.6%
2 20586
 
12.7%
3 17660
 
10.9%
4 11135
 
6.9%
5 2186
 
1.3%
9 2125
 
1.3%
6 2000
 
1.2%
7 1990
 
1.2%
Distinct3337
Distinct (%)45.2%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
Minimum2004-02-05 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T06:58:28.011088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T06:58:28.471580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7385
Missing (%)100.0%
Memory size65.0 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
3
4980 
1
2405 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 4980
67.4%
1 2405
32.6%

Length

2024-05-11T06:58:28.904158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:58:29.270616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 4980
67.4%
1 2405
32.6%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
폐업
4980 
영업/정상
2405 

Length

Max length5
Median length2
Mean length2.9769804
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 4980
67.4%
영업/정상 2405
32.6%

Length

2024-05-11T06:58:29.695619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:58:30.116177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 4980
67.4%
영업/정상 2405
32.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
2
4980 
1
2405 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 4980
67.4%
1 2405
32.6%

Length

2024-05-11T06:58:30.455873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:58:30.864280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 4980
67.4%
1 2405
32.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
폐업
4980 
영업
2405 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 4980
67.4%
영업 2405
32.6%

Length

2024-05-11T06:58:31.240407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:58:31.680454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 4980
67.4%
영업 2405
32.6%

폐업일자
Date

MISSING 

Distinct2502
Distinct (%)50.2%
Missing2405
Missing (%)32.6%
Memory size57.8 KiB
Minimum2004-04-23 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T06:58:32.285987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T06:58:32.748114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7385
Missing (%)100.0%
Memory size65.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7385
Missing (%)100.0%
Memory size65.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7385
Missing (%)100.0%
Memory size65.0 KiB

전화번호
Text

MISSING 

Distinct3106
Distinct (%)93.3%
Missing4057
Missing (%)54.9%
Memory size57.8 KiB
2024-05-11T06:58:33.406177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.426683
Min length3

Characters and Unicode

Total characters34700
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

Unique2974 ?
Unique (%)89.4%

Sample

1st row02 5168646
2nd row0220553411
3rd row0262426911
4th row02 5222180
5th row0234771250
ValueCountFrequency (%)
02 1765
27.6%
070 209
 
3.3%
031 34
 
0.5%
521 28
 
0.4%
522 27
 
0.4%
32848111 26
 
0.4%
525 26
 
0.4%
523 26
 
0.4%
588 25
 
0.4%
583 24
 
0.4%
Other values (3262) 4201
65.7%
2024-05-11T06:58:34.671162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5445
15.7%
2 4939
14.2%
4161
12.0%
5 3889
11.2%
3 2698
7.8%
7 2661
7.7%
8 2485
7.2%
1 2358
6.8%
4 2324
6.7%
6 1983
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30539
88.0%
Space Separator 4161
 
12.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5445
17.8%
2 4939
16.2%
5 3889
12.7%
3 2698
8.8%
7 2661
8.7%
8 2485
8.1%
1 2358
7.7%
4 2324
7.6%
6 1983
 
6.5%
9 1757
 
5.8%
Space Separator
ValueCountFrequency (%)
4161
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34700
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5445
15.7%
2 4939
14.2%
4161
12.0%
5 3889
11.2%
3 2698
7.8%
7 2661
7.7%
8 2485
7.2%
1 2358
6.8%
4 2324
6.7%
6 1983
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34700
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5445
15.7%
2 4939
14.2%
4161
12.0%
5 3889
11.2%
3 2698
7.8%
7 2661
7.7%
8 2485
7.2%
1 2358
6.8%
4 2324
6.7%
6 1983
 
5.7%

소재지면적
Text

MISSING 

Distinct1195
Distinct (%)32.3%
Missing3689
Missing (%)50.0%
Memory size57.8 KiB
2024-05-11T06:58:35.508180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length4.6975108
Min length3

Characters and Unicode

Total characters17362
Distinct characters12
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

Unique923 ?
Unique (%)25.0%

Sample

1st row38.00
2nd row462.00
3rd row33.00
4th row33.00
5th row205.57
ValueCountFrequency (%)
3.30 431
 
11.7%
00 223
 
6.0%
6.00 198
 
5.4%
3.00 125
 
3.4%
10.00 105
 
2.8%
33.00 87
 
2.4%
0.00 69
 
1.9%
4.00 65
 
1.8%
6.60 59
 
1.6%
16.50 47
 
1.3%
Other values (1185) 2287
61.9%
2024-05-11T06:58:37.185483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5214
30.0%
. 3696
21.3%
3 1939
 
11.2%
1 1257
 
7.2%
6 1048
 
6.0%
2 958
 
5.5%
5 785
 
4.5%
4 755
 
4.3%
9 612
 
3.5%
8 605
 
3.5%
Other values (2) 493
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13658
78.7%
Other Punctuation 3704
 
21.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5214
38.2%
3 1939
 
14.2%
1 1257
 
9.2%
6 1048
 
7.7%
2 958
 
7.0%
5 785
 
5.7%
4 755
 
5.5%
9 612
 
4.5%
8 605
 
4.4%
7 485
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 3696
99.8%
, 8
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 17362
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5214
30.0%
. 3696
21.3%
3 1939
 
11.2%
1 1257
 
7.2%
6 1048
 
6.0%
2 958
 
5.5%
5 785
 
4.5%
4 755
 
4.3%
9 612
 
3.5%
8 605
 
3.5%
Other values (2) 493
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17362
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5214
30.0%
. 3696
21.3%
3 1939
 
11.2%
1 1257
 
7.2%
6 1048
 
6.0%
2 958
 
5.5%
5 785
 
4.5%
4 755
 
4.3%
9 612
 
3.5%
8 605
 
3.5%
Other values (2) 493
 
2.8%
Distinct344
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
2024-05-11T06:58:38.263379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.160325
Min length6

Characters and Unicode

Total characters45494
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

Unique52 ?
Unique (%)0.7%

Sample

1st row137808
2nd row137850
3rd row137843
4th row137860
5th row137818
ValueCountFrequency (%)
137884 407
 
5.5%
137860 195
 
2.6%
137858 171
 
2.3%
137881 154
 
2.1%
137952 130
 
1.8%
137856 114
 
1.5%
137040 109
 
1.5%
137863 107
 
1.4%
137902 105
 
1.4%
137818 103
 
1.4%
Other values (334) 5790
78.4%
2024-05-11T06:58:39.839079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 9100
20.0%
3 8698
19.1%
1 8694
19.1%
8 7533
16.6%
0 2562
 
5.6%
9 2220
 
4.9%
4 1546
 
3.4%
5 1473
 
3.2%
6 1458
 
3.2%
- 1184
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44310
97.4%
Dash Punctuation 1184
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 9100
20.5%
3 8698
19.6%
1 8694
19.6%
8 7533
17.0%
0 2562
 
5.8%
9 2220
 
5.0%
4 1546
 
3.5%
5 1473
 
3.3%
6 1458
 
3.3%
2 1026
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 1184
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 45494
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 9100
20.0%
3 8698
19.1%
1 8694
19.1%
8 7533
16.6%
0 2562
 
5.6%
9 2220
 
4.9%
4 1546
 
3.4%
5 1473
 
3.2%
6 1458
 
3.2%
- 1184
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45494
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 9100
20.0%
3 8698
19.1%
1 8694
19.1%
8 7533
16.6%
0 2562
 
5.6%
9 2220
 
4.9%
4 1546
 
3.4%
5 1473
 
3.2%
6 1458
 
3.2%
- 1184
 
2.6%
Distinct4042
Distinct (%)54.7%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
2024-05-11T06:58:40.708688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length52
Mean length29.345159
Min length16

Characters and Unicode

Total characters216714
Distinct characters567
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3338 ?
Unique (%)45.2%

Sample

1st row서울특별시 서초구 반포동 ***-*번지 대종빌딩 ***호
2nd row서울특별시 서초구 방배동 ****-**번지 유신빌딩 *층
3rd row서울특별시 서초구 방배동 ***-**번지 호서빌딩 ***호
4th row서울특별시 서초구 서초동 ****-*번지 현대골든텔 ****호
5th row서울특별시 서초구 방배동 ***-**번지 오륜빌딩 *층
ValueCountFrequency (%)
서울특별시 7384
17.7%
서초구 7381
17.7%
번지 4415
10.6%
서초동 3215
7.7%
3043
7.3%
2945
 
7.1%
2419
 
5.8%
방배동 1494
 
3.6%
양재동 1022
 
2.4%
반포동 835
 
2.0%
Other values (2404) 7567
18.1%
2024-05-11T06:58:42.112432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 47967
22.1%
38377
17.7%
18424
 
8.5%
10930
 
5.0%
8147
 
3.8%
7507
 
3.5%
7427
 
3.4%
7415
 
3.4%
7389
 
3.4%
7385
 
3.4%
Other values (557) 55746
25.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 120841
55.8%
Other Punctuation 48337
22.3%
Space Separator 38377
 
17.7%
Dash Punctuation 6736
 
3.1%
Decimal Number 939
 
0.4%
Uppercase Letter 840
 
0.4%
Close Punctuation 248
 
0.1%
Open Punctuation 248
 
0.1%
Lowercase Letter 79
 
< 0.1%
Math Symbol 57
 
< 0.1%
Other values (2) 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
18424
15.2%
10930
 
9.0%
8147
 
6.7%
7507
 
6.2%
7427
 
6.1%
7415
 
6.1%
7389
 
6.1%
7385
 
6.1%
5452
 
4.5%
4417
 
3.7%
Other values (483) 36348
30.1%
Uppercase Letter
ValueCountFrequency (%)
B 309
36.8%
A 112
 
13.3%
D 55
 
6.5%
T 44
 
5.2%
E 32
 
3.8%
S 31
 
3.7%
L 31
 
3.7%
K 29
 
3.5%
P 29
 
3.5%
G 23
 
2.7%
Other values (16) 145
17.3%
Lowercase Letter
ValueCountFrequency (%)
a 15
19.0%
i 9
11.4%
e 7
 
8.9%
l 7
 
8.9%
o 5
 
6.3%
n 5
 
6.3%
c 3
 
3.8%
v 3
 
3.8%
r 3
 
3.8%
b 3
 
3.8%
Other values (10) 19
24.1%
Decimal Number
ValueCountFrequency (%)
1 200
21.3%
2 128
13.6%
0 101
10.8%
3 97
10.3%
4 95
10.1%
7 83
8.8%
5 81
8.6%
6 59
 
6.3%
8 52
 
5.5%
9 43
 
4.6%
Other Punctuation
ValueCountFrequency (%)
* 47967
99.2%
, 293
 
0.6%
/ 45
 
0.1%
. 12
 
< 0.1%
@ 8
 
< 0.1%
? 6
 
< 0.1%
: 3
 
< 0.1%
& 3
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 247
99.6%
] 1
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 247
99.6%
[ 1
 
0.4%
Letter Number
ValueCountFrequency (%)
5
55.6%
4
44.4%
Space Separator
ValueCountFrequency (%)
38377
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6736
100.0%
Math Symbol
ValueCountFrequency (%)
~ 57
100.0%
Other Symbol
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 120841
55.8%
Common 94945
43.8%
Latin 927
 
0.4%
Greek 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
18424
15.2%
10930
 
9.0%
8147
 
6.7%
7507
 
6.2%
7427
 
6.1%
7415
 
6.1%
7389
 
6.1%
7385
 
6.1%
5452
 
4.5%
4417
 
3.7%
Other values (483) 36348
30.1%
Latin
ValueCountFrequency (%)
B 309
33.3%
A 112
 
12.1%
D 55
 
5.9%
T 44
 
4.7%
E 32
 
3.5%
S 31
 
3.3%
L 31
 
3.3%
K 29
 
3.1%
P 29
 
3.1%
G 23
 
2.5%
Other values (37) 232
25.0%
Common
ValueCountFrequency (%)
* 47967
50.5%
38377
40.4%
- 6736
 
7.1%
, 293
 
0.3%
) 247
 
0.3%
( 247
 
0.3%
1 200
 
0.2%
2 128
 
0.1%
0 101
 
0.1%
3 97
 
0.1%
Other values (16) 552
 
0.6%
Greek
ValueCountFrequency (%)
Ι 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 120841
55.8%
ASCII 95860
44.2%
Number Forms 9
 
< 0.1%
CJK Compat 3
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 47967
50.0%
38377
40.0%
- 6736
 
7.0%
B 309
 
0.3%
, 293
 
0.3%
) 247
 
0.3%
( 247
 
0.3%
1 200
 
0.2%
2 128
 
0.1%
A 112
 
0.1%
Other values (60) 1244
 
1.3%
Hangul
ValueCountFrequency (%)
18424
15.2%
10930
 
9.0%
8147
 
6.7%
7507
 
6.2%
7427
 
6.1%
7415
 
6.1%
7389
 
6.1%
7385
 
6.1%
5452
 
4.5%
4417
 
3.7%
Other values (483) 36348
30.1%
Number Forms
ValueCountFrequency (%)
5
55.6%
4
44.4%
CJK Compat
ValueCountFrequency (%)
3
100.0%
None
ValueCountFrequency (%)
Ι 1
100.0%

도로명주소
Text

MISSING 

Distinct3894
Distinct (%)66.3%
Missing1508
Missing (%)20.4%
Memory size57.8 KiB
2024-05-11T06:58:42.857025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length54
Mean length35.52697
Min length22

Characters and Unicode

Total characters208792
Distinct characters554
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3139 ?
Unique (%)53.4%

Sample

1st row서울특별시 서초구 효령로 ** (방배동,호서빌딩 ***호)
2nd row서울특별시 서초구 효령로**길 **, *층 ***호 (방배동, 삼익상가)
3rd row서울특별시 서초구 잠원로*길 ** (잠원동,대림@상가 ***호)
4th row서울특별시 서초구 사임당로*길 ** (서초동,소담빌딩 *층)
5th row서울특별시 서초구 강남대로**길 ** (서초동,풍림아이원매직 ***호)
ValueCountFrequency (%)
서울특별시 5876
14.7%
서초구 5874
14.7%
5831
14.6%
2963
 
7.4%
2492
 
6.3%
서초동 1921
 
4.8%
방배동 1003
 
2.5%
양재동 715
 
1.8%
반포동 583
 
1.5%
452
 
1.1%
Other values (2637) 12159
30.5%
2024-05-11T06:58:44.114960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 34647
16.6%
34003
16.3%
15795
 
7.6%
9656
 
4.6%
, 7515
 
3.6%
6904
 
3.3%
5954
 
2.9%
) 5952
 
2.9%
( 5952
 
2.9%
5933
 
2.8%
Other values (544) 76481
36.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 117737
56.4%
Other Punctuation 42201
 
20.2%
Space Separator 34003
 
16.3%
Close Punctuation 5952
 
2.9%
Open Punctuation 5952
 
2.9%
Dash Punctuation 1039
 
0.5%
Decimal Number 1028
 
0.5%
Uppercase Letter 779
 
0.4%
Lowercase Letter 74
 
< 0.1%
Math Symbol 17
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
15795
 
13.4%
9656
 
8.2%
6904
 
5.9%
5954
 
5.1%
5933
 
5.0%
5909
 
5.0%
5881
 
5.0%
5877
 
5.0%
5770
 
4.9%
3521
 
3.0%
Other values (475) 46537
39.5%
Uppercase Letter
ValueCountFrequency (%)
B 276
35.4%
A 127
16.3%
T 42
 
5.4%
L 35
 
4.5%
S 31
 
4.0%
E 31
 
4.0%
D 31
 
4.0%
C 23
 
3.0%
P 22
 
2.8%
R 22
 
2.8%
Other values (16) 139
17.8%
Lowercase Letter
ValueCountFrequency (%)
a 13
17.6%
e 10
13.5%
i 9
12.2%
l 8
10.8%
v 6
8.1%
f 5
 
6.8%
o 3
 
4.1%
n 3
 
4.1%
b 3
 
4.1%
c 2
 
2.7%
Other values (9) 12
16.2%
Decimal Number
ValueCountFrequency (%)
1 243
23.6%
2 188
18.3%
0 133
12.9%
3 100
9.7%
5 88
 
8.6%
4 84
 
8.2%
7 62
 
6.0%
6 52
 
5.1%
8 43
 
4.2%
9 35
 
3.4%
Other Punctuation
ValueCountFrequency (%)
* 34647
82.1%
, 7515
 
17.8%
/ 20
 
< 0.1%
? 6
 
< 0.1%
@ 5
 
< 0.1%
. 5
 
< 0.1%
& 3
 
< 0.1%
Letter Number
ValueCountFrequency (%)
6
60.0%
4
40.0%
Space Separator
ValueCountFrequency (%)
34003
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5952
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5952
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1039
100.0%
Math Symbol
ValueCountFrequency (%)
~ 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 117737
56.4%
Common 90192
43.2%
Latin 862
 
0.4%
Greek 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
15795
 
13.4%
9656
 
8.2%
6904
 
5.9%
5954
 
5.1%
5933
 
5.0%
5909
 
5.0%
5881
 
5.0%
5877
 
5.0%
5770
 
4.9%
3521
 
3.0%
Other values (475) 46537
39.5%
Latin
ValueCountFrequency (%)
B 276
32.0%
A 127
14.7%
T 42
 
4.9%
L 35
 
4.1%
S 31
 
3.6%
E 31
 
3.6%
D 31
 
3.6%
C 23
 
2.7%
P 22
 
2.6%
R 22
 
2.6%
Other values (36) 222
25.8%
Common
ValueCountFrequency (%)
* 34647
38.4%
34003
37.7%
, 7515
 
8.3%
) 5952
 
6.6%
( 5952
 
6.6%
- 1039
 
1.2%
1 243
 
0.3%
2 188
 
0.2%
0 133
 
0.1%
3 100
 
0.1%
Other values (12) 420
 
0.5%
Greek
ValueCountFrequency (%)
Ι 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 117737
56.4%
ASCII 91044
43.6%
Number Forms 10
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 34647
38.1%
34003
37.3%
, 7515
 
8.3%
) 5952
 
6.5%
( 5952
 
6.5%
- 1039
 
1.1%
B 276
 
0.3%
1 243
 
0.3%
2 188
 
0.2%
0 133
 
0.1%
Other values (56) 1096
 
1.2%
Hangul
ValueCountFrequency (%)
15795
 
13.4%
9656
 
8.2%
6904
 
5.9%
5954
 
5.1%
5933
 
5.0%
5909
 
5.0%
5881
 
5.0%
5877
 
5.0%
5770
 
4.9%
3521
 
3.0%
Other values (475) 46537
39.5%
Number Forms
ValueCountFrequency (%)
6
60.0%
4
40.0%
None
ValueCountFrequency (%)
Ι 1
100.0%

도로명우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct294
Distinct (%)5.0%
Missing1555
Missing (%)21.1%
Infinite0
Infinite (%)0.0%
Mean6655.5098
Minimum6035
Maximum63237
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.0 KiB
2024-05-11T06:58:44.673349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6035
5-th percentile6524
Q16584
median6634
Q36719.75
95-th percentile6781
Maximum63237
Range57202
Interquartile range (IQR)135.75

Descriptive statistics

Standard deviation746.18992
Coefficient of variation (CV)0.11211612
Kurtosis5674.4525
Mean6655.5098
Median Absolute Deviation (MAD)64
Skewness74.824796
Sum38801622
Variance556799.39
MonotonicityNot monotonic
2024-05-11T06:58:45.397334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6595 230
 
3.1%
6627 134
 
1.8%
6621 121
 
1.6%
6546 108
 
1.5%
6775 84
 
1.1%
6626 76
 
1.0%
6634 72
 
1.0%
6762 70
 
0.9%
6720 69
 
0.9%
6628 62
 
0.8%
Other values (284) 4804
65.1%
(Missing) 1555
 
21.1%
ValueCountFrequency (%)
6035 1
 
< 0.1%
6500 1
 
< 0.1%
6501 9
 
0.1%
6502 25
0.3%
6503 18
0.2%
6504 1
 
< 0.1%
6505 5
 
0.1%
6506 8
 
0.1%
6508 2
 
< 0.1%
6509 26
0.4%
ValueCountFrequency (%)
63237 1
 
< 0.1%
8594 1
 
< 0.1%
6804 2
 
< 0.1%
6803 1
 
< 0.1%
6802 22
0.3%
6801 3
 
< 0.1%
6800 28
0.4%
6799 1
 
< 0.1%
6798 16
0.2%
6797 32
0.4%
Distinct6495
Distinct (%)87.9%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
2024-05-11T06:58:46.222113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length33
Mean length7.4639133
Min length1

Characters and Unicode

Total characters55121
Distinct characters885
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6251 ?
Unique (%)84.6%

Sample

1st row마리온(주)
2nd row(주)글로벌헬스케어
3rd row그루피아(주)
4th row한돌메디칼
5th row씨케이디메딕스(주)
ValueCountFrequency (%)
주식회사 580
 
6.0%
한국암웨이 396
 
4.1%
gs25 120
 
1.2%
리더스패밀리 73
 
0.8%
세븐일레븐 63
 
0.6%
60
 
0.6%
인셀덤 36
 
0.4%
서초점 34
 
0.3%
강남점 33
 
0.3%
패밀리 28
 
0.3%
Other values (6884) 8301
85.4%
2024-05-11T06:58:47.625161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2493
 
4.5%
2344
 
4.3%
2334
 
4.2%
) 1994
 
3.6%
( 1994
 
3.6%
1584
 
2.9%
1170
 
2.1%
884
 
1.6%
789
 
1.4%
749
 
1.4%
Other values (875) 38786
70.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 45189
82.0%
Space Separator 2344
 
4.3%
Close Punctuation 1994
 
3.6%
Open Punctuation 1994
 
3.6%
Uppercase Letter 1552
 
2.8%
Lowercase Letter 1270
 
2.3%
Decimal Number 652
 
1.2%
Other Punctuation 112
 
0.2%
Dash Punctuation 11
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2493
 
5.5%
2334
 
5.2%
1584
 
3.5%
1170
 
2.6%
884
 
2.0%
789
 
1.7%
749
 
1.7%
676
 
1.5%
669
 
1.5%
659
 
1.5%
Other values (800) 33182
73.4%
Uppercase Letter
ValueCountFrequency (%)
S 231
14.9%
G 187
 
12.0%
C 87
 
5.6%
N 84
 
5.4%
O 82
 
5.3%
B 81
 
5.2%
H 77
 
5.0%
T 76
 
4.9%
I 75
 
4.8%
A 73
 
4.7%
Other values (15) 499
32.2%
Lowercase Letter
ValueCountFrequency (%)
e 187
14.7%
o 116
 
9.1%
a 113
 
8.9%
t 94
 
7.4%
l 90
 
7.1%
i 85
 
6.7%
n 84
 
6.6%
r 83
 
6.5%
s 54
 
4.3%
m 45
 
3.5%
Other values (15) 319
25.1%
Decimal Number
ValueCountFrequency (%)
2 207
31.7%
5 176
27.0%
1 82
 
12.6%
3 42
 
6.4%
4 35
 
5.4%
0 34
 
5.2%
6 30
 
4.6%
7 18
 
2.8%
9 17
 
2.6%
8 11
 
1.7%
Other Punctuation
ValueCountFrequency (%)
& 44
39.3%
. 42
37.5%
, 9
 
8.0%
? 8
 
7.1%
/ 3
 
2.7%
' 3
 
2.7%
: 2
 
1.8%
# 1
 
0.9%
Math Symbol
ValueCountFrequency (%)
+ 1
50.0%
= 1
50.0%
Space Separator
ValueCountFrequency (%)
2344
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1994
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1994
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 45185
82.0%
Common 7110
 
12.9%
Latin 2822
 
5.1%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2493
 
5.5%
2334
 
5.2%
1584
 
3.5%
1170
 
2.6%
884
 
2.0%
789
 
1.7%
749
 
1.7%
676
 
1.5%
669
 
1.5%
659
 
1.5%
Other values (796) 33178
73.4%
Latin
ValueCountFrequency (%)
S 231
 
8.2%
e 187
 
6.6%
G 187
 
6.6%
o 116
 
4.1%
a 113
 
4.0%
t 94
 
3.3%
l 90
 
3.2%
C 87
 
3.1%
i 85
 
3.0%
n 84
 
3.0%
Other values (40) 1548
54.9%
Common
ValueCountFrequency (%)
2344
33.0%
) 1994
28.0%
( 1994
28.0%
2 207
 
2.9%
5 176
 
2.5%
1 82
 
1.2%
& 44
 
0.6%
. 42
 
0.6%
3 42
 
0.6%
4 35
 
0.5%
Other values (15) 150
 
2.1%
Han
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 45184
82.0%
ASCII 9932
 
18.0%
CJK 4
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2493
 
5.5%
2334
 
5.2%
1584
 
3.5%
1170
 
2.6%
884
 
2.0%
789
 
1.7%
749
 
1.7%
676
 
1.5%
669
 
1.5%
659
 
1.5%
Other values (795) 33177
73.4%
ASCII
ValueCountFrequency (%)
2344
23.6%
) 1994
20.1%
( 1994
20.1%
S 231
 
2.3%
2 207
 
2.1%
e 187
 
1.9%
G 187
 
1.9%
5 176
 
1.8%
o 116
 
1.2%
a 113
 
1.1%
Other values (65) 2383
24.0%
CJK
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Distinct6622
Distinct (%)89.7%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
Minimum2004-03-25 00:00:00
Maximum2024-05-09 16:28:15
2024-05-11T06:58:48.171121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T06:58:48.782865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
I
4593 
U
2792 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 4593
62.2%
U 2792
37.8%

Length

2024-05-11T06:58:49.359881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:58:49.969669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 4593
62.2%
u 2792
37.8%
Distinct1457
Distinct (%)19.7%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T06:58:50.464550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T06:58:51.021158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7385
Missing (%)100.0%
Memory size65.0 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2996
Distinct (%)41.0%
Missing83
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean201230.81
Minimum189920.53
Maximum207693.87
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.0 KiB
2024-05-11T06:58:51.655779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189920.53
5-th percentile198572.58
Q1200250.45
median201230.69
Q3202340.65
95-th percentile203811.37
Maximum207693.87
Range17773.342
Interquartile range (IQR)2090.2069

Descriptive statistics

Standard deviation1572.9836
Coefficient of variation (CV)0.0078168129
Kurtosis0.23327611
Mean201230.81
Median Absolute Deviation (MAD)1015.1876
Skewness0.0093435516
Sum1.4693873 × 109
Variance2474277.3
MonotonicityNot monotonic
2024-05-11T06:58:52.205096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200660.72602366 379
 
5.1%
200250.447804795 126
 
1.7%
200601.352689145 112
 
1.5%
202501.602561199 80
 
1.1%
201501.672660443 51
 
0.7%
203204.755637424 41
 
0.6%
202175.011113176 40
 
0.5%
200949.551476636 37
 
0.5%
201680.914515104 36
 
0.5%
200896.488726199 31
 
0.4%
Other values (2986) 6369
86.2%
(Missing) 83
 
1.1%
ValueCountFrequency (%)
189920.528610917 1
 
< 0.1%
190541.499138217 1
 
< 0.1%
198341.208478761 1
 
< 0.1%
198344.761390706 1
 
< 0.1%
198351.955 4
0.1%
198352.675 2
< 0.1%
198353.824006002 1
 
< 0.1%
198355.846023337 3
< 0.1%
198356.006840205 1
 
< 0.1%
198357.319178572 2
< 0.1%
ValueCountFrequency (%)
207693.870617743 2
< 0.1%
207367.089538074 3
< 0.1%
207172.190710637 1
 
< 0.1%
206964.260080589 1
 
< 0.1%
206527.143128753 1
 
< 0.1%
206291.982497443 1
 
< 0.1%
206158.477194617 1
 
< 0.1%
206023.723764186 1
 
< 0.1%
205900.29503107 1
 
< 0.1%
205819.580437692 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2997
Distinct (%)41.0%
Missing83
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean443051.39
Minimum436968.83
Maximum446681.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.0 KiB
2024-05-11T06:58:52.714683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum436968.83
5-th percentile440677.24
Q1442326.24
median443056.44
Q3443761.22
95-th percentile445457.37
Maximum446681.1
Range9712.2766
Interquartile range (IQR)1434.9866

Descriptive statistics

Standard deviation1384.9893
Coefficient of variation (CV)0.003126024
Kurtosis0.48585037
Mean443051.39
Median Absolute Deviation (MAD)718.78662
Skewness-0.20761467
Sum3.2351613 × 109
Variance1918195.4
MonotonicityNot monotonic
2024-05-11T06:58:53.494179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443448.509483173 379
 
5.1%
444683.220506107 126
 
1.7%
443052.573822557 112
 
1.5%
443226.434038556 80
 
1.1%
442505.573142545 51
 
0.7%
440136.781183797 41
 
0.6%
440963.759050916 40
 
0.5%
443483.146383375 37
 
0.5%
444584.589362916 36
 
0.5%
443317.733765416 31
 
0.4%
Other values (2987) 6369
86.2%
(Missing) 83
 
1.1%
ValueCountFrequency (%)
436968.827045316 1
 
< 0.1%
437119.595971567 1
 
< 0.1%
437983.549727893 1
 
< 0.1%
438089.937256048 1
 
< 0.1%
438125.636291897 1
 
< 0.1%
438241.0 1
 
< 0.1%
438278.235724516 1
 
< 0.1%
438293.331675201 4
0.1%
438360.612274203 1
 
< 0.1%
438416.991038311 4
0.1%
ValueCountFrequency (%)
446681.103634893 1
 
< 0.1%
446565.028672992 5
0.1%
446439.134713956 2
 
< 0.1%
446421.477235361 1
 
< 0.1%
446331.380046658 1
 
< 0.1%
446312.298040264 2
 
< 0.1%
446261.422577646 1
 
< 0.1%
446247.719636035 1
 
< 0.1%
446206.354902748 8
0.1%
446205.939573861 1
 
< 0.1%

위생업태명
Categorical

Distinct12
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
<NA>
1906 
영업장판매
1696 
전자상거래(통신판매업)
1440 
다단계판매
896 
통신판매
646 
Other values (7)
801 

Length

Max length14
Median length12
Mean length6.014218
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row영업장판매
2nd row영업장판매
3rd row영업장판매
4th row영업장판매
5th row통신판매

Common Values

ValueCountFrequency (%)
<NA> 1906
25.8%
영업장판매 1696
23.0%
전자상거래(통신판매업) 1440
19.5%
다단계판매 896
12.1%
통신판매 646
 
8.7%
방문판매 571
 
7.7%
도매업(유통) 161
 
2.2%
전화권유판매 40
 
0.5%
기타 건강기능식품일반판매업 15
 
0.2%
기타(복합 등) 10
 
0.1%
Other values (2) 4
 
0.1%

Length

2024-05-11T06:58:53.964238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1906
25.7%
영업장판매 1696
22.9%
전자상거래(통신판매업 1440
19.4%
다단계판매 896
12.1%
통신판매 646
 
8.7%
방문판매 571
 
7.7%
도매업(유통 161
 
2.2%
전화권유판매 40
 
0.5%
기타 15
 
0.2%
건강기능식품일반판매업 15
 
0.2%
Other values (4) 24
 
0.3%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
<NA>
6953 
0
 
432

Length

Max length4
Median length4
Mean length3.8245091
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> 6953
94.2%
0 432
 
5.8%

Length

2024-05-11T06:58:54.403044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:58:54.852263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6953
94.2%
0 432
 
5.8%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
<NA>
6953 
0
 
432

Length

Max length4
Median length4
Mean length3.8245091
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> 6953
94.2%
0 432
 
5.8%

Length

2024-05-11T06:58:55.357715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:58:55.759843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6953
94.2%
0 432
 
5.8%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7385
Missing (%)100.0%
Memory size65.0 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7385
Missing (%)100.0%
Memory size65.0 KiB

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
<NA>
7363 
상수도전용
 
22

Length

Max length5
Median length4
Mean length4.002979
Min length4

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> 7363
99.7%
상수도전용 22
 
0.3%

Length

2024-05-11T06:58:56.120184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:58:56.456978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7363
99.7%
상수도전용 22
 
0.3%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
<NA>
6957 
0
 
428

Length

Max length4
Median length4
Mean length3.8261341
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> 6957
94.2%
0 428
 
5.8%

Length

2024-05-11T06:58:56.781124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:58:57.051681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6957
94.2%
0 428
 
5.8%

본사종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
<NA>
5685 
0
1695 
4
 
2
6
 
2
10
 
1

Length

Max length4
Median length4
Mean length3.3095464
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5685
77.0%
0 1695
 
23.0%
4 2
 
< 0.1%
6 2
 
< 0.1%
10 1
 
< 0.1%

Length

2024-05-11T06:58:57.300676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:58:57.653280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5685
77.0%
0 1695
 
23.0%
4 2
 
< 0.1%
6 2
 
< 0.1%
10 1
 
< 0.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
<NA>
5685 
0
1694 
1
 
3
2
 
2
4
 
1

Length

Max length4
Median length4
Mean length3.309411
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5685
77.0%
0 1694
 
22.9%
1 3
 
< 0.1%
2 2
 
< 0.1%
4 1
 
< 0.1%

Length

2024-05-11T06:58:58.066682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:58:58.420063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5685
77.0%
0 1694
 
22.9%
1 3
 
< 0.1%
2 2
 
< 0.1%
4 1
 
< 0.1%

공장판매직종업원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct7
Distinct (%)0.4%
Missing5684
Missing (%)77.0%
Infinite0
Infinite (%)0.0%
Mean0.065843621
Minimum0
Maximum70
Zeros1694
Zeros (%)22.9%
Negative0
Negative (%)0.0%
Memory size65.0 KiB
2024-05-11T06:58:58.745847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum70
Range70
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.7856661
Coefficient of variation (CV)27.119803
Kurtosis1395.2683
Mean0.065843621
Median Absolute Deviation (MAD)0
Skewness36.279179
Sum112
Variance3.1886032
MonotonicityNot monotonic
2024-05-11T06:58:59.078621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 1694
 
22.9%
7 2
 
< 0.1%
20 1
 
< 0.1%
2 1
 
< 0.1%
5 1
 
< 0.1%
70 1
 
< 0.1%
1 1
 
< 0.1%
(Missing) 5684
77.0%
ValueCountFrequency (%)
0 1694
22.9%
1 1
 
< 0.1%
2 1
 
< 0.1%
5 1
 
< 0.1%
7 2
 
< 0.1%
20 1
 
< 0.1%
70 1
 
< 0.1%
ValueCountFrequency (%)
70 1
 
< 0.1%
20 1
 
< 0.1%
7 2
 
< 0.1%
5 1
 
< 0.1%
2 1
 
< 0.1%
1 1
 
< 0.1%
0 1694
22.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
<NA>
5686 
0
1699 

Length

Max length4
Median length4
Mean length3.3098172
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5686
77.0%
0 1699
 
23.0%

Length

2024-05-11T06:58:59.534274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:58:59.949611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5686
77.0%
0 1699
 
23.0%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
<NA>
4505 
임대
2099 
자가
781 

Length

Max length4
Median length4
Mean length3.2200406
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4505
61.0%
임대 2099
28.4%
자가 781
 
10.6%

Length

2024-05-11T06:59:00.480568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:59:00.906601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4505
61.0%
임대 2099
28.4%
자가 781
 
10.6%

보증액
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.7%
Missing6421
Missing (%)86.9%
Infinite0
Infinite (%)0.0%
Mean179460.58
Minimum0
Maximum50000000
Zeros955
Zeros (%)12.9%
Negative0
Negative (%)0.0%
Memory size65.0 KiB
2024-05-11T06:59:01.310067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum50000000
Range50000000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2273590.6
Coefficient of variation (CV)12.669025
Kurtosis293.67074
Mean179460.58
Median Absolute Deviation (MAD)0
Skewness16.038235
Sum1.73 × 108
Variance5.1692142 × 1012
MonotonicityNot monotonic
2024-05-11T06:59:01.806249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 955
 
12.9%
25000000 2
 
< 0.1%
10000000 2
 
< 0.1%
5000000 2
 
< 0.1%
50000000 1
 
< 0.1%
28000000 1
 
< 0.1%
15000000 1
 
< 0.1%
(Missing) 6421
86.9%
ValueCountFrequency (%)
0 955
12.9%
5000000 2
 
< 0.1%
10000000 2
 
< 0.1%
15000000 1
 
< 0.1%
25000000 2
 
< 0.1%
28000000 1
 
< 0.1%
50000000 1
 
< 0.1%
ValueCountFrequency (%)
50000000 1
 
< 0.1%
28000000 1
 
< 0.1%
25000000 2
 
< 0.1%
15000000 1
 
< 0.1%
10000000 2
 
< 0.1%
5000000 2
 
< 0.1%
0 955
12.9%

월세액
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)0.9%
Missing6421
Missing (%)86.9%
Infinite0
Infinite (%)0.0%
Mean14751.037
Minimum0
Maximum4000000
Zeros955
Zeros (%)12.9%
Negative0
Negative (%)0.0%
Memory size65.0 KiB
2024-05-11T06:59:02.359226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum4000000
Range4000000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation185075.66
Coefficient of variation (CV)12.54662
Kurtosis295.06296
Mean14751.037
Median Absolute Deviation (MAD)0
Skewness16.143392
Sum14220000
Variance3.4253001 × 1010
MonotonicityNot monotonic
2024-05-11T06:59:02.796865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 955
 
12.9%
800000 2
 
< 0.1%
1500000 1
 
< 0.1%
2000000 1
 
< 0.1%
770000 1
 
< 0.1%
2800000 1
 
< 0.1%
4000000 1
 
< 0.1%
900000 1
 
< 0.1%
650000 1
 
< 0.1%
(Missing) 6421
86.9%
ValueCountFrequency (%)
0 955
12.9%
650000 1
 
< 0.1%
770000 1
 
< 0.1%
800000 2
 
< 0.1%
900000 1
 
< 0.1%
1500000 1
 
< 0.1%
2000000 1
 
< 0.1%
2800000 1
 
< 0.1%
4000000 1
 
< 0.1%
ValueCountFrequency (%)
4000000 1
 
< 0.1%
2800000 1
 
< 0.1%
2000000 1
 
< 0.1%
1500000 1
 
< 0.1%
900000 1
 
< 0.1%
800000 2
 
< 0.1%
770000 1
 
< 0.1%
650000 1
 
< 0.1%
0 955
12.9%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing1906
Missing (%)25.8%
Memory size14.6 KiB
False
5479 
(Missing)
1906 
ValueCountFrequency (%)
False 5479
74.2%
(Missing) 1906
 
25.8%
2024-05-11T06:59:03.160867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct108
Distinct (%)2.0%
Missing1906
Missing (%)25.8%
Infinite0
Infinite (%)0.0%
Mean1.733382
Minimum0
Maximum366.99
Zeros5086
Zeros (%)68.9%
Negative0
Negative (%)0.0%
Memory size65.0 KiB
2024-05-11T06:59:03.504006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3.3
Maximum366.99
Range366.99
Interquartile range (IQR)0

Descriptive statistics

Standard deviation14.685977
Coefficient of variation (CV)8.4724409
Kurtosis268.3316
Mean1.733382
Median Absolute Deviation (MAD)0
Skewness14.859967
Sum9497.2
Variance215.67791
MonotonicityNot monotonic
2024-05-11T06:59:04.030352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 5086
68.9%
3.3 151
 
2.0%
3.0 41
 
0.6%
6.0 16
 
0.2%
5.0 11
 
0.1%
10.0 11
 
0.1%
30.0 8
 
0.1%
33.0 7
 
0.1%
6.6 6
 
0.1%
2.2 6
 
0.1%
Other values (98) 136
 
1.8%
(Missing) 1906
 
25.8%
ValueCountFrequency (%)
0.0 5086
68.9%
1.0 2
 
< 0.1%
1.44 2
 
< 0.1%
1.47 1
 
< 0.1%
2.0 1
 
< 0.1%
2.2 6
 
0.1%
3.0 41
 
0.6%
3.3 151
 
2.0%
4.0 6
 
0.1%
4.95 1
 
< 0.1%
ValueCountFrequency (%)
366.99 1
< 0.1%
322.54 1
< 0.1%
312.05 1
< 0.1%
281.74 1
< 0.1%
280.0 1
< 0.1%
260.88 1
< 0.1%
257.0 1
< 0.1%
234.72 1
< 0.1%
188.1 1
< 0.1%
181.43 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7385
Missing (%)100.0%
Memory size65.0 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7385
Missing (%)100.0%
Memory size65.0 KiB

홈페이지
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing7384
Missing (%)> 99.9%
Memory size57.8 KiB
2024-05-11T06:59:04.591737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters24
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowhttp://wwww.power365.com
ValueCountFrequency (%)
http://wwww.power365.com 1
100.0%
2024-05-11T06:59:05.669590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 5
20.8%
t 2
 
8.3%
p 2
 
8.3%
/ 2
 
8.3%
. 2
 
8.3%
o 2
 
8.3%
h 1
 
4.2%
: 1
 
4.2%
e 1
 
4.2%
r 1
 
4.2%
Other values (5) 5
20.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 16
66.7%
Other Punctuation 5
 
20.8%
Decimal Number 3
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 5
31.2%
t 2
 
12.5%
p 2
 
12.5%
o 2
 
12.5%
h 1
 
6.2%
e 1
 
6.2%
r 1
 
6.2%
c 1
 
6.2%
m 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
/ 2
40.0%
. 2
40.0%
: 1
20.0%
Decimal Number
ValueCountFrequency (%)
3 1
33.3%
6 1
33.3%
5 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 16
66.7%
Common 8
33.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 5
31.2%
t 2
 
12.5%
p 2
 
12.5%
o 2
 
12.5%
h 1
 
6.2%
e 1
 
6.2%
r 1
 
6.2%
c 1
 
6.2%
m 1
 
6.2%
Common
ValueCountFrequency (%)
/ 2
25.0%
. 2
25.0%
: 1
12.5%
3 1
12.5%
6 1
12.5%
5 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 5
20.8%
t 2
 
8.3%
p 2
 
8.3%
/ 2
 
8.3%
. 2
 
8.3%
o 2
 
8.3%
h 1
 
4.2%
: 1
 
4.2%
e 1
 
4.2%
r 1
 
4.2%
Other values (5) 5
20.8%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032100003210000-134-2004-0000120040325<NA>3폐업2폐업20041005<NA><NA><NA>02 5168646<NA>137808서울특별시 서초구 반포동 ***-*번지 대종빌딩 ***호<NA><NA>마리온(주)2004-03-25 00:00:00I2018-08-31 23:59:59.0<NA>201649.126385445308.271173영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
132100003210000-134-2004-0000220040326<NA>3폐업2폐업20041004<NA><NA><NA><NA><NA>137850서울특별시 서초구 방배동 ****-**번지 유신빌딩 *층<NA><NA>(주)글로벌헬스케어2004-03-26 00:00:00I2018-08-31 23:59:59.0<NA>200300.654224442252.336549영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
232100003210000-134-2004-0000320040331<NA>3폐업2폐업20181112<NA><NA><NA>0220553411<NA>137843서울특별시 서초구 방배동 ***-**번지 호서빌딩 ***호서울특별시 서초구 효령로 ** (방배동,호서빌딩 ***호)6687그루피아(주)2018-11-16 15:26:52U2018-11-18 02:36:47.0<NA>199486.69453442077.607925영업장판매<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
332100003210000-134-2004-0000520040331<NA>3폐업2폐업20100506<NA><NA><NA>026242691138.00137860서울특별시 서초구 서초동 ****-*번지 현대골든텔 ****호<NA><NA>한돌메디칼2004-12-30 00:00:00I2018-08-31 23:59:59.0<NA>202478.104884443306.064905영업장판매<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
432100003210000-134-2004-0000620040331<NA>3폐업2폐업20041220<NA><NA><NA><NA>462.00137818서울특별시 서초구 방배동 ***-**번지 오륜빌딩 *층<NA><NA>씨케이디메딕스(주)2004-03-31 00:00:00I2018-08-31 23:59:59.0<NA>198484.945811441665.723328통신판매<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
532100003210000-134-2004-0000720040401<NA>3폐업2폐업20221117<NA><NA><NA>02 522218033.00137850서울특별시 서초구 방배동 ****-* 삼익상가 *층***호서울특별시 서초구 효령로**길 **, *층 ***호 (방배동, 삼익상가)6705바이올가 신방배점2022-11-17 15:20:06U2021-10-31 23:09:00.0<NA>200070.821284441854.339667<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
632100003210000-134-2004-0000820040401<NA>1영업/정상1영업<NA><NA><NA><NA>023477125033.00137907서울특별시 서초구 잠원동 **번지 대림@상가 ***호서울특별시 서초구 잠원로*길 ** (잠원동,대림@상가 ***호)6518내추럴하우스2004-04-01 00:00:00I2018-08-31 23:59:59.0<NA>201016.283557446102.588876영업장판매<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
732100003210000-134-2004-0000920040401<NA>3폐업2폐업20170818<NA><NA><NA><NA>205.57137872서울특별시 서초구 서초동 ****-*번지 소담빌딩 *층서울특별시 서초구 사임당로*길 ** (서초동,소담빌딩 *층)6649주영엔에스(주)2017-08-18 14:58:28I2018-08-31 23:59:59.0<NA>200899.769015442891.960871영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
832100003210000-134-2004-0001020040401<NA>3폐업2폐업20190211<NA><NA><NA>02 586566365.00137857서울특별시 서초구 서초동 ****-*번지 풍림아이원매직 ***호서울특별시 서초구 강남대로**길 ** (서초동,풍림아이원매직 ***호)6619(주)웰스라인2019-02-11 11:03:01U2019-02-13 02:40:00.0<NA>202193.920857443717.690282전자상거래(통신판매업)<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
932100003210000-134-2004-0001120040401<NA>3폐업2폐업20190128<NA><NA><NA>02 586566350.00137857서울특별시 서초구 서초동 ****-*번지 풍림아이원매직 ***호서울특별시 서초구 강남대로**길 ** (서초동,풍림아이원매직 ***호)6619웰스라인2019-01-29 11:37:23U2019-01-31 02:40:00.0<NA>202193.920857443717.690282전자상거래(통신판매업)<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
737532100003210000-134-2024-001462024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>137-898서울특별시 서초구 양재동 ***-* *층서울특별시 서초구 동산로*길 **, *층 (양재동)6786에이스(ACE)센터2024-05-03 16:02:12I2023-12-05 00:05:00.0<NA>203751.83440674.585<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
737632100003210000-134-2024-001472024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>80.00137-881서울특별시 서초구 서초동 ****-* ***호(*층 ***호의 북측 일부분)서울특별시 서초구 서초대로**길 **, ***호(*층 ***호의 북측 일부분) (서초동)6634서초그린케어2024-05-03 17:26:51I2023-12-05 00:05:00.0<NA>201393.459943443334.048742<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
737732100003210000-134-2024-001482024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>137-893서울특별시 서초구 양재동 *** **층 ****호서울특별시 서초구 매헌로 **, **층 ****호 (양재동)6771뉴벨2024-05-03 18:02:25I2023-12-05 00:05:00.0<NA>203204.755637440136.781184<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
737832100003210000-134-2024-001492024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>137-810서울특별시 서초구 반포동 ***-**서울특별시 서초구 사평대로**길 **-*, ***호 (반포동)6540태씨네2024-05-07 10:09:19I2023-12-05 00:09:00.0<NA>201831.355139444876.977892<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
737932100003210000-134-2024-001502024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>137-892서울특별시 서초구 양재동 ***-* 단지내상가 *층 *-***호서울특별시 서초구 바우뫼로 ** (양재동, 우성아파트)6751아라바바2024-05-07 15:44:34I2023-12-05 00:09:00.0<NA>202535.840179441604.113262<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
738032100003210000-134-2024-001512024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>137-070서울특별시 서초구 서초동 **** 래미안 리더스원 ***동 ***호서울특별시 서초구 서운로 **, ***동 ***호 (서초동, 래미안 리더스원)6629쁘띠누2024-05-07 15:56:16I2023-12-05 00:09:00.0<NA>202435.53028443148.839518<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
738132100003210000-134-2024-001522024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>137-860서울특별시 서초구 서초동 **** 현대ESA아파트 ****호서울특별시 서초구 효령로**길 **, ****호 (서초동, 현대ESA아파트)6628소싱랩스2024-05-07 17:37:14I2023-12-05 00:09:00.0<NA>202537.854222443188.657701<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
738232100003210000-134-2024-001532024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.00137-880서울특별시 서초구 서초동 ****-** 지하*층 ***호서울특별시 서초구 사임당로**길 **-**, 지하*층 ***호 (서초동)6638엠제이익스프레스2024-05-08 09:29:21I2023-12-04 23:00:00.0<NA>201498.874489443254.590549<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
738332100003210000-134-2024-001542024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>137-903서울특별시 서초구 잠원동 **-** *층 **실서울특별시 서초구 강남대로**길 **-*, *층 (잠원동)6526화수분상회2024-05-08 10:29:59I2023-12-04 23:00:00.0<NA>201541.849961445841.273247<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
738432100003210000-134-2024-001552024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.00137-908서울특별시 서초구 잠원동 **-* *동 *층서울특별시 서초구 신반포로 ***, *동 *층 (잠원동)6512엠에스안과2024-05-09 14:13:21I2023-12-04 23:01:00.0<NA>200346.774648444921.730153<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>