Overview

Dataset statistics

Number of variables31
Number of observations86
Missing cells1018
Missing cells (%)38.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.2 KiB
Average record size in memory264.5 B

Variable types

Numeric7
Categorical11
DateTime2
Unsupported7
Text4

Dataset

Description23년11월_6270000_대구광역시_08_26_01_P_다단계판매업체
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000101396&dataSetDetailId=DDI_0000101455&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
개방자치단체코드 has constant value ""Constant
업종구분명 has constant value ""Constant
데이터갱신구분 is highly imbalanced (55.4%)Imbalance
데이터갱신일자 is highly imbalanced (76.6%)Imbalance
인허가취소일자 has 86 (100.0%) missing valuesMissing
폐업일자 has 55 (64.0%) missing valuesMissing
휴업시작일자 has 86 (100.0%) missing valuesMissing
휴업종료일자 has 86 (100.0%) missing valuesMissing
재개업일자 has 86 (100.0%) missing valuesMissing
소재지전화 has 3 (3.5%) missing valuesMissing
소재지면적 has 86 (100.0%) missing valuesMissing
소재지우편번호 has 77 (89.5%) missing valuesMissing
도로명전체주소 has 69 (80.2%) missing valuesMissing
도로명우편번호 has 86 (100.0%) missing valuesMissing
업태구분명 has 86 (100.0%) missing valuesMissing
좌표정보(X) has 69 (80.2%) missing valuesMissing
좌표정보(Y) has 69 (80.2%) missing valuesMissing
사업자등록번호 has 74 (86.0%) missing valuesMissing
번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
도로명우편번호 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
자본금의규모 has 5 (5.8%) zerosZeros

Reproduction

Analysis started2023-12-16 05:33:43.547253
Analysis finished2023-12-16 05:33:45.082312
Duration1.54 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct86
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.5
Minimum1
Maximum86
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size906.0 B
2023-12-16T05:33:45.501661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.25
Q122.25
median43.5
Q364.75
95-th percentile81.75
Maximum86
Range85
Interquartile range (IQR)42.5

Descriptive statistics

Standard deviation24.969982
Coefficient of variation (CV)0.57402257
Kurtosis-1.2
Mean43.5
Median Absolute Deviation (MAD)21.5
Skewness0
Sum3741
Variance623.5
MonotonicityStrictly increasing
2023-12-16T05:33:46.651600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.2%
56 1
 
1.2%
64 1
 
1.2%
63 1
 
1.2%
62 1
 
1.2%
61 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
Other values (76) 76
88.4%
ValueCountFrequency (%)
1 1
1.2%
2 1
1.2%
3 1
1.2%
4 1
1.2%
5 1
1.2%
6 1
1.2%
7 1
1.2%
8 1
1.2%
9 1
1.2%
10 1
1.2%
ValueCountFrequency (%)
86 1
1.2%
85 1
1.2%
84 1
1.2%
83 1
1.2%
82 1
1.2%
81 1
1.2%
80 1
1.2%
79 1
1.2%
78 1
1.2%
77 1
1.2%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size820.0 B
다단계판매업체
86 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
다단계판매업체 86
100.0%

Length

2023-12-16T05:33:47.552688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T05:33:48.128203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
다단계판매업체 86
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size820.0 B
08_26_01_P
86 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row08_26_01_P
2nd row08_26_01_P
3rd row08_26_01_P
4th row08_26_01_P
5th row08_26_01_P

Common Values

ValueCountFrequency (%)
08_26_01_P 86
100.0%

Length

2023-12-16T05:33:48.729457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T05:33:49.342844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
08_26_01_p 86
100.0%

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size820.0 B
6270000
86 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6270000
2nd row6270000
3rd row6270000
4th row6270000
5th row6270000

Common Values

ValueCountFrequency (%)
6270000 86
100.0%

Length

2023-12-16T05:33:50.239029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T05:33:50.713382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6270000 86
100.0%

관리번호
Real number (ℝ)

Distinct10
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0067549 × 1019
Minimum2.004627 × 1019
Maximum2.023627 × 1019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size906.0 B
2023-12-16T05:33:51.435297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.004627 × 1019
5-th percentile2.004627 × 1019
Q12.004627 × 1019
median2.004627 × 1019
Q32.004627 × 1019
95-th percentile2.016627 × 1019
Maximum2.023627 × 1019
Range1.9 × 1017
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.6899053 × 1016
Coefficient of variation (CV)0.0023370594
Kurtosis3.0802279
Mean2.0067549 × 1019
Median Absolute Deviation (MAD)0
Skewness2.0437646
Sum1.7258092 × 1021
Variance2.1995212 × 1033
MonotonicityNot monotonic
2023-12-16T05:33:52.047033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2.0046270000041e+19 70
81.4%
2.0136270000041e+19 6
 
7.0%
2.0156270000041e+19 2
 
2.3%
2.0166270000041e+19 2
 
2.3%
2.0126270000041e+19 1
 
1.2%
2.0146270000041e+19 1
 
1.2%
2.0196270000041e+19 1
 
1.2%
2.0176270000041e+19 1
 
1.2%
2.0236270000041e+19 1
 
1.2%
2.0226270000041e+19 1
 
1.2%
ValueCountFrequency (%)
2.0046270000041e+19 70
81.4%
2.0126270000041e+19 1
 
1.2%
2.0136270000041e+19 6
 
7.0%
2.0146270000041e+19 1
 
1.2%
2.0156270000041e+19 2
 
2.3%
2.0166270000041e+19 2
 
2.3%
2.0176270000041e+19 1
 
1.2%
2.0196270000041e+19 1
 
1.2%
2.0226270000041e+19 1
 
1.2%
2.0236270000041e+19 1
 
1.2%
ValueCountFrequency (%)
2.0236270000041e+19 1
 
1.2%
2.0226270000041e+19 1
 
1.2%
2.0196270000041e+19 1
 
1.2%
2.0176270000041e+19 1
 
1.2%
2.0166270000041e+19 2
 
2.3%
2.0156270000041e+19 2
 
2.3%
2.0146270000041e+19 1
 
1.2%
2.0136270000041e+19 6
 
7.0%
2.0126270000041e+19 1
 
1.2%
2.0046270000041e+19 70
81.4%

인허가일자
Date

Distinct74
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Memory size820.0 B
Minimum1995-07-24 00:00:00
Maximum2023-02-08 00:00:00
2023-12-16T05:33:52.620120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T05:33:53.467760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing86
Missing (%)100.0%
Memory size906.0 B

영업상태구분코드
Categorical

Distinct3
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size820.0 B
3
61 
4
21 
1
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 61
70.9%
4 21
 
24.4%
1 4
 
4.7%

Length

2023-12-16T05:33:54.082584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T05:33:54.681006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 61
70.9%
4 21
 
24.4%
1 4
 
4.7%

영업상태명
Categorical

Distinct3
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size820.0 B
폐업
61 
취소/말소/만료/정지/중지
21 
영업/정상
 
4

Length

Max length14
Median length2
Mean length5.0697674
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 61
70.9%
취소/말소/만료/정지/중지 21
 
24.4%
영업/정상 4
 
4.7%

Length

2023-12-16T05:33:55.207076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T05:33:55.804988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 61
70.9%
취소/말소/만료/정지/중지 21
 
24.4%
영업/정상 4
 
4.7%

상세영업상태코드
Categorical

Distinct4
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size820.0 B
4
61 
6
21 
BBBB
 
3
2
 
1

Length

Max length4
Median length1
Mean length1.1046512
Min length1

Unique

Unique1 ?
Unique (%)1.2%

Sample

1st row2
2nd row4
3rd row4
4th row4
5th row4

Common Values

ValueCountFrequency (%)
4 61
70.9%
6 21
 
24.4%
BBBB 3
 
3.5%
2 1
 
1.2%

Length

2023-12-16T05:33:56.241000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T05:33:56.826062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 61
70.9%
6 21
 
24.4%
bbbb 3
 
3.5%
2 1
 
1.2%

상세영업상태명
Categorical

Distinct3
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size820.0 B
폐업
61 
직권말소
21 
영업
 
4

Length

Max length4
Median length2
Mean length2.4883721
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 61
70.9%
직권말소 21
 
24.4%
영업 4
 
4.7%

Length

2023-12-16T05:33:57.457765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T05:33:57.937588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 61
70.9%
직권말소 21
 
24.4%
영업 4
 
4.7%

폐업일자
Date

MISSING 

Distinct24
Distinct (%)77.4%
Missing55
Missing (%)64.0%
Memory size820.0 B
Minimum1997-03-31 00:00:00
Maximum2018-10-18 00:00:00
2023-12-16T05:33:58.331921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T05:33:58.980801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing86
Missing (%)100.0%
Memory size906.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing86
Missing (%)100.0%
Memory size906.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing86
Missing (%)100.0%
Memory size906.0 B

소재지전화
Real number (ℝ)

MISSING 

Distinct83
Distinct (%)100.0%
Missing3
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean5.7389474 × 108
Minimum15449886
Maximum5.3189979 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size906.0 B
2023-12-16T05:33:59.800097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15449886
5-th percentile5.3171264 × 108
Q15.3425306 × 108
median5.3652336 × 108
Q35.3751812 × 108
95-th percentile5.3962053 × 108
Maximum5.3189979 × 109
Range5.303548 × 109
Interquartile range (IQR)3265056.5

Descriptive statistics

Standard deviation5.4031245 × 108
Coefficient of variation (CV)0.94148352
Kurtosis74.996537
Mean5.7389474 × 108
Median Absolute Deviation (MAD)1032891
Skewness8.4102371
Sum4.7633264 × 1010
Variance2.9193754 × 1017
MonotonicityNot monotonic
2023-12-16T05:34:00.478438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
537459003 1
 
1.2%
532551017 1
 
1.2%
536560717 1
 
1.2%
15449886 1
 
1.2%
808968888 1
 
1.2%
18993121 1
 
1.2%
704760398 1
 
1.2%
531661688 1
 
1.2%
533112675 1
 
1.2%
537218550 1
 
1.2%
Other values (73) 73
84.9%
(Missing) 3
 
3.5%
ValueCountFrequency (%)
15449886 1
1.2%
16660223 1
1.2%
16668118 1
1.2%
18993121 1
1.2%
531661688 1
1.2%
532171171 1
1.2%
532471234 1
1.2%
532475660 1
1.2%
532537180 1
1.2%
532541728 1
1.2%
ValueCountFrequency (%)
5318997889 1
1.2%
808968888 1
1.2%
704760398 1
1.2%
539637779 1
1.2%
539626200 1
1.2%
539569534 1
1.2%
539431472 1
1.2%
537612109 1
1.2%
537610040 1
1.2%
537579058 1
1.2%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing86
Missing (%)100.0%
Memory size906.0 B

소재지우편번호
Text

MISSING 

Distinct9
Distinct (%)100.0%
Missing77
Missing (%)89.5%
Memory size820.0 B
2023-12-16T05:34:01.030643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.1111111
Min length5

Characters and Unicode

Total characters55
Distinct characters10
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

Unique9 ?
Unique (%)100.0%

Sample

1st row700-412
2nd row701-827
3rd row701-729
4th row701-021
5th row705-808
ValueCountFrequency (%)
700-412 1
11.1%
701-827 1
11.1%
701-729 1
11.1%
701-021 1
11.1%
705-808 1
11.1%
41166 1
11.1%
42142 1
11.1%
41058 1
11.1%
41954 1
11.1%
2023-12-16T05:34:03.313776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10
18.2%
0 9
16.4%
7 7
12.7%
4 7
12.7%
2 6
10.9%
- 5
9.1%
8 4
 
7.3%
5 3
 
5.5%
9 2
 
3.6%
6 2
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50
90.9%
Dash Punctuation 5
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 10
20.0%
0 9
18.0%
7 7
14.0%
4 7
14.0%
2 6
12.0%
8 4
 
8.0%
5 3
 
6.0%
9 2
 
4.0%
6 2
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 55
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 10
18.2%
0 9
16.4%
7 7
12.7%
4 7
12.7%
2 6
10.9%
- 5
9.1%
8 4
 
7.3%
5 3
 
5.5%
9 2
 
3.6%
6 2
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 55
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 10
18.2%
0 9
16.4%
7 7
12.7%
4 7
12.7%
2 6
10.9%
- 5
9.1%
8 4
 
7.3%
5 3
 
5.5%
9 2
 
3.6%
6 2
 
3.6%

소재지전체주소
Text

Distinct83
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size820.0 B
2023-12-16T05:34:05.490274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length32
Mean length28.209302
Min length1

Characters and Unicode

Total characters2426
Distinct characters128
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

Unique81 ?
Unique (%)94.2%

Sample

1st row대구광역시 동구 신천동 74번지 1호 74번지 1호 74번지 1호
2nd row대구광역시 동구 신천동 신천4동 335-6
3rd row대구광역시 달서구 두류동 8-7-3 한신빌딩 6층
4th row대구광역시 수성구 범어동 186-4번지
5th row대구광역시 북구 침산동 심산2동 156-50
ValueCountFrequency (%)
대구광역시 83
 
18.2%
동구 27
 
5.9%
신천동 22
 
4.8%
수성구 16
 
3.5%
중구 15
 
3.3%
남구 10
 
2.2%
서구 8
 
1.8%
대명동 8
 
1.8%
4층 7
 
1.5%
2층 7
 
1.5%
Other values (181) 254
55.6%
2023-12-16T05:34:07.438924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
620
25.6%
구 167
 
6.9%
동 148
 
6.1%
대 106
 
4.4%
1 100
 
4.1%
광 89
 
3.7%
역 83
 
3.4%
시 83
 
3.4%
3 69
 
2.8%
2 61
 
2.5%
Other values (118) 900
37.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1259
51.9%
Space Separator 620
25.6%
Decimal Number 466
 
19.2%
Dash Punctuation 60
 
2.5%
Open Punctuation 9
 
0.4%
Close Punctuation 9
 
0.4%
Uppercase Letter 2
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 167
 
13.3%
동 148
 
11.8%
대 106
 
8.4%
광 89
 
7.1%
역 83
 
6.6%
시 83
 
6.6%
층 41
 
3.3%
신 36
 
2.9%
딩 33
 
2.6%
천 33
 
2.6%
Other values (101) 440
34.9%
Decimal Number
ValueCountFrequency (%)
1 100
21.5%
3 69
14.8%
2 61
13.1%
4 43
9.2%
7 42
9.0%
0 37
 
7.9%
5 32
 
6.9%
6 31
 
6.7%
8 26
 
5.6%
9 25
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
O 1
50.0%
T 1
50.0%
Space Separator
ValueCountFrequency (%)
620
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 60
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1259
51.9%
Common 1165
48.0%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 167
 
13.3%
동 148
 
11.8%
대 106
 
8.4%
광 89
 
7.1%
역 83
 
6.6%
시 83
 
6.6%
층 41
 
3.3%
신 36
 
2.9%
딩 33
 
2.6%
천 33
 
2.6%
Other values (101) 440
34.9%
Common
ValueCountFrequency (%)
620
53.2%
1 100
 
8.6%
3 69
 
5.9%
2 61
 
5.2%
- 60
 
5.2%
4 43
 
3.7%
7 42
 
3.6%
0 37
 
3.2%
5 32
 
2.7%
6 31
 
2.7%
Other values (5) 70
 
6.0%
Latin
ValueCountFrequency (%)
O 1
50.0%
T 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1259
51.9%
ASCII 1167
48.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
620
53.1%
1 100
 
8.6%
3 69
 
5.9%
2 61
 
5.2%
- 60
 
5.1%
4 43
 
3.7%
7 42
 
3.6%
0 37
 
3.2%
5 32
 
2.7%
6 31
 
2.7%
Other values (7) 72
 
6.2%
Hangul
ValueCountFrequency (%)
구 167
 
13.3%
동 148
 
11.8%
대 106
 
8.4%
광 89
 
7.1%
역 83
 
6.6%
시 83
 
6.6%
층 41
 
3.3%
신 36
 
2.9%
딩 33
 
2.6%
천 33
 
2.6%
Other values (101) 440
34.9%

도로명전체주소
Text

MISSING 

Distinct15
Distinct (%)88.2%
Missing69
Missing (%)80.2%
Memory size820.0 B
2023-12-16T05:34:08.276573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length29
Mean length26.823529
Min length21

Characters and Unicode

Total characters456
Distinct characters70
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)76.5%

Sample

1st row대구광역시 동구 동대구로 503 (신천동)
2nd row대구광역시 동구 장등로 88 (신천동)
3rd row대구광역시 중구 공평로4길 39 (삼덕동2가)
4th row대구광역시 동구 동부로26길 66 (신천동)
5th row대구광역시 동구 동대구로 483 (신천동)
ValueCountFrequency (%)
대구광역시 17
 
18.7%
동구 9
 
9.9%
신천동 6
 
6.6%
수성구 4
 
4.4%
66 2
 
2.2%
화랑로 2
 
2.2%
471 2
 
2.2%
용계동 2
 
2.2%
동대구로 2
 
2.2%
중구 2
 
2.2%
Other values (41) 43
47.3%
2023-12-16T05:34:10.043544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
74
 
16.2%
구 37
 
8.1%
동 33
 
7.2%
대 23
 
5.0%
( 17
 
3.7%
광 17
 
3.7%
역 17
 
3.7%
시 17
 
3.7%
) 17
 
3.7%
로 17
 
3.7%
Other values (60) 187
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 265
58.1%
Space Separator 74
 
16.2%
Decimal Number 73
 
16.0%
Open Punctuation 17
 
3.7%
Close Punctuation 17
 
3.7%
Other Punctuation 9
 
2.0%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 37
14.0%
동 33
12.5%
대 23
 
8.7%
광 17
 
6.4%
역 17
 
6.4%
시 17
 
6.4%
로 17
 
6.4%
성 8
 
3.0%
수 8
 
3.0%
가 7
 
2.6%
Other values (45) 81
30.6%
Decimal Number
ValueCountFrequency (%)
2 13
17.8%
3 11
15.1%
6 10
13.7%
1 10
13.7%
0 7
9.6%
4 6
8.2%
5 6
8.2%
8 5
 
6.8%
7 3
 
4.1%
9 2
 
2.7%
Space Separator
ValueCountFrequency (%)
74
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 265
58.1%
Common 191
41.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 37
14.0%
동 33
12.5%
대 23
 
8.7%
광 17
 
6.4%
역 17
 
6.4%
시 17
 
6.4%
로 17
 
6.4%
성 8
 
3.0%
수 8
 
3.0%
가 7
 
2.6%
Other values (45) 81
30.6%
Common
ValueCountFrequency (%)
74
38.7%
( 17
 
8.9%
) 17
 
8.9%
2 13
 
6.8%
3 11
 
5.8%
6 10
 
5.2%
1 10
 
5.2%
, 9
 
4.7%
0 7
 
3.7%
4 6
 
3.1%
Other values (5) 17
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 265
58.1%
ASCII 191
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
74
38.7%
( 17
 
8.9%
) 17
 
8.9%
2 13
 
6.8%
3 11
 
5.8%
6 10
 
5.2%
1 10
 
5.2%
, 9
 
4.7%
0 7
 
3.7%
4 6
 
3.1%
Other values (5) 17
 
8.9%
Hangul
ValueCountFrequency (%)
구 37
14.0%
동 33
12.5%
대 23
 
8.7%
광 17
 
6.4%
역 17
 
6.4%
시 17
 
6.4%
로 17
 
6.4%
성 8
 
3.0%
수 8
 
3.0%
가 7
 
2.6%
Other values (45) 81
30.6%

도로명우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing86
Missing (%)100.0%
Memory size906.0 B

사업장명
Text

Distinct85
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size820.0 B
2023-12-16T05:34:10.930320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length8.3837209
Min length5

Characters and Unicode

Total characters721
Distinct characters166
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)97.7%

Sample

1st row(주)투에버
2nd row(주)세비앙몽드
3rd row케이제이엠종합유통(주)
4th row(주)제이아이씨
5th row(주)라이즈업
ValueCountFrequency (%)
주식회사 10
 
10.3%
주)그린앤센스 2
 
2.1%
주)벤처아트 1
 
1.0%
주)다와 1
 
1.0%
라라코리아인터내셔날 1
 
1.0%
위나라이트코리아 1
 
1.0%
블루그린 1
 
1.0%
컨슈머월드 1
 
1.0%
지원엔앰씨 1
 
1.0%
금보바이오닉스(주 1
 
1.0%
Other values (77) 77
79.4%
2023-12-16T05:34:12.639204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 85
 
11.8%
( 75
 
10.4%
) 75
 
10.4%
이 35
 
4.9%
아 17
 
2.4%
리 16
 
2.2%
스 14
 
1.9%
코 13
 
1.8%
11
 
1.5%
인 11
 
1.5%
Other values (156) 369
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 556
77.1%
Open Punctuation 75
 
10.4%
Close Punctuation 75
 
10.4%
Space Separator 11
 
1.5%
Other Punctuation 4
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 85
 
15.3%
이 35
 
6.3%
아 17
 
3.1%
리 16
 
2.9%
스 14
 
2.5%
코 13
 
2.3%
인 11
 
2.0%
식 10
 
1.8%
회 10
 
1.8%
라 10
 
1.8%
Other values (152) 335
60.3%
Open Punctuation
ValueCountFrequency (%)
( 75
100.0%
Close Punctuation
ValueCountFrequency (%)
) 75
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 556
77.1%
Common 165
 
22.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 85
 
15.3%
이 35
 
6.3%
아 17
 
3.1%
리 16
 
2.9%
스 14
 
2.5%
코 13
 
2.3%
인 11
 
2.0%
식 10
 
1.8%
회 10
 
1.8%
라 10
 
1.8%
Other values (152) 335
60.3%
Common
ValueCountFrequency (%)
( 75
45.5%
) 75
45.5%
11
 
6.7%
. 4
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 556
77.1%
ASCII 165
 
22.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 85
 
15.3%
이 35
 
6.3%
아 17
 
3.1%
리 16
 
2.9%
스 14
 
2.5%
코 13
 
2.3%
인 11
 
2.0%
식 10
 
1.8%
회 10
 
1.8%
라 10
 
1.8%
Other values (152) 335
60.3%
ASCII
ValueCountFrequency (%)
( 75
45.5%
) 75
45.5%
11
 
6.7%
. 4
 
2.4%

최종수정시점
Categorical

Distinct20
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Memory size820.0 B
2014-10-01 00:00:00
32 
2018-05-14 00:00:00
25 
2005-11-10 00:00:00
7 
2005-11-11 00:00:00
5 
2005-11-12 00:00:00
 
2
Other values (15)
15 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique15 ?
Unique (%)17.4%

Sample

1st row2023-07-10 00:00:00
2nd row2014-10-01 00:00:00
3rd row2018-05-14 00:00:00
4th row2018-05-14 00:00:00
5th row2018-05-14 00:00:00

Common Values

ValueCountFrequency (%)
2014-10-01 00:00:00 32
37.2%
2018-05-14 00:00:00 25
29.1%
2005-11-10 00:00:00 7
 
8.1%
2005-11-11 00:00:00 5
 
5.8%
2005-11-12 00:00:00 2
 
2.3%
2015-12-04 00:00:00 1
 
1.2%
2015-03-04 00:00:00 1
 
1.2%
2018-10-18 00:00:00 1
 
1.2%
2014-06-23 00:00:00 1
 
1.2%
2014-09-26 00:00:00 1
 
1.2%
Other values (10) 10
 
11.6%

Length

2023-12-16T05:34:13.539932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
00:00:00 86
50.0%
2014-10-01 32
 
18.6%
2018-05-14 25
 
14.5%
2005-11-10 7
 
4.1%
2005-11-11 5
 
2.9%
2005-11-12 2
 
1.2%
2019-01-10 1
 
0.6%
2023-07-10 1
 
0.6%
2018-07-11 1
 
0.6%
2023-09-07 1
 
0.6%
Other values (11) 11
 
6.4%

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size820.0 B
I
78 
U
8 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 78
90.7%
U 8
 
9.3%

Length

2023-12-16T05:34:14.386837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T05:34:14.794925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 78
90.7%
u 8
 
9.3%

데이터갱신일자
Categorical

IMBALANCE 

Distinct8
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size820.0 B
2018-08-31 23:59:59
78 
2023-05-26 08:48:36
 
2
2023-07-13 02:40:00
 
1
2018-10-20 02:37:50
 
1
2019-01-12 02:40:00
 
1
Other values (3)
 
3

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique6 ?
Unique (%)7.0%

Sample

1st row2023-07-13 02:40:00
2nd row2018-08-31 23:59:59
3rd row2018-08-31 23:59:59
4th row2018-08-31 23:59:59
5th row2018-08-31 23:59:59

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59 78
90.7%
2023-05-26 08:48:36 2
 
2.3%
2023-07-13 02:40:00 1
 
1.2%
2018-10-20 02:37:50 1
 
1.2%
2019-01-12 02:40:00 1
 
1.2%
2019-01-11 02:40:00 1
 
1.2%
2023-10-22 02:40:00 1
 
1.2%
2023-09-09 02:40:00 1
 
1.2%

Length

2023-12-16T05:34:15.611678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T05:34:15.990633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-08-31 78
45.3%
23:59:59 78
45.3%
02:40:00 5
 
2.9%
2023-05-26 2
 
1.2%
08:48:36 2
 
1.2%
2023-07-13 1
 
0.6%
2018-10-20 1
 
0.6%
02:37:50 1
 
0.6%
2019-01-12 1
 
0.6%
2019-01-11 1
 
0.6%
Other values (2) 2
 
1.2%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing86
Missing (%)100.0%
Memory size906.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct15
Distinct (%)88.2%
Missing69
Missing (%)80.2%
Infinite0
Infinite (%)0.0%
Mean346809.36
Minimum340568.71
Maximum354859.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size906.0 B
2023-12-16T05:34:16.597927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum340568.71
5-th percentile342214.03
Q1345387.06
median346671.75
Q3346954.22
95-th percentile351940.79
Maximum354859.43
Range14290.723
Interquartile range (IQR)1567.166

Descriptive statistics

Standard deviation3304.0241
Coefficient of variation (CV)0.0095269173
Kurtosis1.5573753
Mean346809.36
Median Absolute Deviation (MAD)1284.6914
Skewness0.69480955
Sum5895759.2
Variance10916575
MonotonicityNot monotonic
2023-12-16T05:34:17.243455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
346954.221838711 2
 
2.3%
351211.131307881 2
 
2.3%
346691.951910382 1
 
1.2%
346557.305781287 1
 
1.2%
344634.648244336 1
 
1.2%
346671.747220574 1
 
1.2%
346915.153894167 1
 
1.2%
345727.539482349 1
 
1.2%
342625.355314337 1
 
1.2%
348061.829691568 1
 
1.2%
Other values (5) 5
 
5.8%
(Missing) 69
80.2%
ValueCountFrequency (%)
340568.709642826 1
1.2%
342625.355314337 1
1.2%
344634.648244336 1
1.2%
344716.15441687 1
1.2%
345387.055811851 1
1.2%
345727.539482349 1
1.2%
346011.564157904 1
1.2%
346557.305781287 1
1.2%
346671.747220574 1
1.2%
346691.951910382 1
1.2%
ValueCountFrequency (%)
354859.432848577 1
1.2%
351211.131307881 2
2.3%
348061.829691568 1
1.2%
346954.221838711 2
2.3%
346915.153894167 1
1.2%
346691.951910382 1
1.2%
346671.747220574 1
1.2%
346557.305781287 1
1.2%
346011.564157904 1
1.2%
345727.539482349 1
1.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct15
Distinct (%)88.2%
Missing69
Missing (%)80.2%
Infinite0
Infinite (%)0.0%
Mean264324.58
Minimum261396.15
Maximum268828.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size906.0 B
2023-12-16T05:34:17.695164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum261396.15
5-th percentile262213.73
Q1263356.83
median264539.57
Q3265104.49
95-th percentile265970.92
Maximum268828.43
Range7432.2864
Interquartile range (IQR)1747.656

Descriptive statistics

Standard deviation1623.6728
Coefficient of variation (CV)0.0061427232
Kurtosis3.0335807
Mean264324.58
Median Absolute Deviation (MAD)716.9694
Skewness0.91092866
Sum4493517.9
Variance2636313.2
MonotonicityNot monotonic
2023-12-16T05:34:18.476204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
264539.573320203 2
 
2.3%
265256.542723342 2
 
2.3%
265138.774608058 1
 
1.2%
265104.489673016 1
 
1.2%
263978.051871396 1
 
1.2%
264917.244195841 1
 
1.2%
264572.308082542 1
 
1.2%
263045.110029152 1
 
1.2%
261396.148029265 1
 
1.2%
264922.92149464 1
 
1.2%
Other values (5) 5
 
5.8%
(Missing) 69
80.2%
ValueCountFrequency (%)
261396.148029265 1
1.2%
262418.129404355 1
1.2%
262779.774088701 1
1.2%
263045.110029152 1
1.2%
263356.833665963 1
1.2%
263467.493083226 1
1.2%
263978.051871396 1
1.2%
264539.573320203 2
2.3%
264572.308082542 1
1.2%
264917.244195841 1
1.2%
ValueCountFrequency (%)
268828.434408585 1
1.2%
265256.542723342 2
2.3%
265138.774608058 1
1.2%
265104.489673016 1
1.2%
264922.92149464 1
1.2%
264917.244195841 1
1.2%
264572.308082542 1
1.2%
264539.573320203 2
2.3%
263978.051871396 1
1.2%
263467.493083226 1
1.2%

업종구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size820.0 B
다단계판매업
86 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
다단계판매업 86
100.0%

Length

2023-12-16T05:34:19.115306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T05:34:19.591755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
다단계판매업 86
100.0%

자본금의규모
Real number (ℝ)

ZEROS 

Distinct46
Distinct (%)53.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.7807987 × 108
Minimum0
Maximum2.06 × 1010
Zeros5
Zeros (%)5.8%
Negative0
Negative (%)0.0%
Memory size906.0 B
2023-12-16T05:34:20.504496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7671475
Q13 × 108
median3.1 × 108
Q35 × 108
95-th percentile5.2870402 × 108
Maximum2.06 × 1010
Range2.06 × 1010
Interquartile range (IQR)2 × 108

Descriptive statistics

Standard deviation2.1890226 × 109
Coefficient of variation (CV)3.786713
Kurtosis85.253299
Mean5.7807987 × 108
Median Absolute Deviation (MAD)10000000
Skewness9.21368
Sum4.9714869 × 1010
Variance4.7918198 × 1018
MonotonicityNot monotonic
2023-12-16T05:34:21.244777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
300000000 18
20.9%
500000000 14
 
16.3%
310000000 5
 
5.8%
0 5
 
5.8%
505000000 2
 
2.3%
600000000 2
 
2.3%
302434208 1
 
1.2%
301872704 1
 
1.2%
307900000 1
 
1.2%
311110016 1
 
1.2%
Other values (36) 36
41.9%
ValueCountFrequency (%)
0 5
 
5.8%
30685900 1
 
1.2%
31000000 1
 
1.2%
50000000 1
 
1.2%
300000000 18
20.9%
300143808 1
 
1.2%
300325984 1
 
1.2%
300920512 1
 
1.2%
301872704 1
 
1.2%
302434208 1
 
1.2%
ValueCountFrequency (%)
20600000500 1
 
1.2%
600000000 2
 
2.3%
550000000 1
 
1.2%
530000000 1
 
1.2%
524816096 1
 
1.2%
518012576 1
 
1.2%
515000000 1
 
1.2%
505000000 2
 
2.3%
501000000 1
 
1.2%
500000000 14
16.3%

사업자등록번호
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)100.0%
Missing74
Missing (%)86.0%
Infinite0
Infinite (%)0.0%
Mean4.6885749 × 109
Minimum1.2586336 × 109
Maximum6.8086005 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size906.0 B
2023-12-16T05:34:21.840342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.2586336 × 109
5-th percentile1.7482409 × 109
Q14.8386681 × 109
median5.028625 × 109
Q35.0735049 × 109
95-th percentile6.5941008 × 109
Maximum6.8086005 × 109
Range5.5499669 × 109
Interquartile range (IQR)2.3483681 × 108

Descriptive statistics

Standard deviation1.5612118 × 109
Coefficient of variation (CV)0.33298217
Kurtosis1.519006
Mean4.6885749 × 109
Median Absolute Deviation (MAD)69776462
Skewness-1.1970107
Sum5.6262899 × 1010
Variance2.4373824 × 1018
MonotonicityNot monotonic
2023-12-16T05:34:22.578848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
5048132871 1
 
1.2%
5028623838 1
 
1.2%
5028624365 1
 
1.2%
5028625587 1
 
1.2%
5028623293 1
 
1.2%
5148194457 1
 
1.2%
2148828721 1
 
1.2%
6418601070 1
 
1.2%
6808600514 1
 
1.2%
5048608420 1
 
1.2%
Other values (2) 2
 
2.3%
(Missing) 74
86.0%
ValueCountFrequency (%)
1258633600 1
1.2%
2148828721 1
1.2%
4268802585 1
1.2%
5028623293 1
1.2%
5028623838 1
1.2%
5028624365 1
1.2%
5028625587 1
1.2%
5048132871 1
1.2%
5048608420 1
1.2%
5148194457 1
1.2%
ValueCountFrequency (%)
6808600514 1
1.2%
6418601070 1
1.2%
5148194457 1
1.2%
5048608420 1
1.2%
5048132871 1
1.2%
5028625587 1
1.2%
5028624365 1
1.2%
5028623838 1
1.2%
5028623293 1
1.2%
4268802585 1
1.2%

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)업종구분명자본금의규모사업자등록번호
01다단계판매업체08_26_01_P6270000200462700000410000432011-04-05<NA>1영업/정상2영업<NA><NA><NA><NA>537579058<NA><NA>대구광역시 동구 신천동 74번지 1호 74번지 1호 74번지 1호대구광역시 동구 동대구로 503 (신천동)<NA>(주)투에버2023-07-10 00:00:00U2023-07-13 02:40:00<NA>346691.95191265138.774608다단계판매업206000005005048132871
12다단계판매업체08_26_01_P6270000200462700000410000661995-08-05<NA>3폐업4폐업<NA><NA><NA><NA>537521030<NA><NA>대구광역시 동구 신천동 신천4동 335-6<NA><NA>(주)세비앙몽드2014-10-01 00:00:00I2018-08-31 23:59:59<NA><NA><NA>다단계판매업306000000<NA>
23다단계판매업체08_26_01_P6270000200462700000410000672000-03-08<NA>3폐업4폐업2018-05-14<NA><NA><NA>536234400<NA><NA>대구광역시 달서구 두류동 8-7-3 한신빌딩 6층<NA><NA>케이제이엠종합유통(주)2018-05-14 00:00:00I2018-08-31 23:59:59<NA><NA><NA>다단계판매업300000000<NA>
34다단계판매업체08_26_01_P6270000200462700000410000681998-03-20<NA>3폐업4폐업2018-05-14<NA><NA><NA>537517435<NA><NA>대구광역시 수성구 범어동 186-4번지<NA><NA>(주)제이아이씨2018-05-14 00:00:00I2018-08-31 23:59:59<NA><NA><NA>다단계판매업306493664<NA>
45다단계판매업체08_26_01_P6270000200462700000410000422001-04-20<NA>3폐업4폐업2018-05-14<NA><NA><NA>534220330<NA><NA>대구광역시 북구 침산동 심산2동 156-50<NA><NA>(주)라이즈업2018-05-14 00:00:00I2018-08-31 23:59:59<NA><NA><NA>다단계판매업308022976<NA>
56다단계판매업체08_26_01_P6270000200462700000410000372001-07-16<NA>3폐업4폐업2003-11-05<NA><NA><NA>539569534<NA><NA>대구광역시 북구 서변동 970번지 (2층)<NA><NA>(주)골든임페리얼2005-11-10 00:00:00I2018-08-31 23:59:59<NA><NA><NA>다단계판매업304599008<NA>
67다단계판매업체08_26_01_P6270000200462700000410000332001-11-12<NA>3폐업4폐업<NA><NA><NA><NA>536562861<NA><NA>대구광역시 남구 대명동 대명2동 1790-3 한빛은행 2층<NA><NA>(주)프리웨이2014-10-01 00:00:00I2018-08-31 23:59:59<NA><NA><NA>다단계판매업354742688<NA>
78다단계판매업체08_26_01_P6270000200462700000410000062002-10-28<NA>3폐업4폐업<NA><NA><NA><NA>537556251<NA><NA>대구광역시 동구 신천동 신천3동 194-45 목화빌딩 3층<NA><NA>(주)라이프케어코리아2014-10-01 00:00:00I2018-08-31 23:59:59<NA><NA><NA>다단계판매업31000000<NA>
89다단계판매업체08_26_01_P6270000200462700000410000022003-02-10<NA>3폐업4폐업<NA><NA><NA><NA>537543391<NA><NA>대구광역시 중구 동산동 788-5 그룹원빌딩 7층<NA><NA>다부코리아2014-10-01 00:00:00I2018-08-31 23:59:59<NA><NA><NA>다단계판매업524816096<NA>
910다단계판매업체08_26_01_P6270000200462700000410000442001-03-15<NA>3폐업4폐업2004-02-11<NA><NA><NA>534297744<NA><NA>대구광역시 중구 삼덕동2가 210-1 진석타워 5층 7호<NA><NA>(주)리치웨이인터내셔날2005-11-12 00:00:00I2018-08-31 23:59:59<NA><NA><NA>다단계판매업500000000<NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)업종구분명자본금의규모사업자등록번호
7677다단계판매업체08_26_01_P6270000200462700000410000482000-12-23<NA>4취소/말소/만료/정지/중지6직권말소<NA><NA><NA><NA>537610040<NA><NA>대구광역시 수성구 수성동3가 332 다송빌딩 2층<NA><NA>(주)지엠코리아원2018-05-14 00:00:00I2018-08-31 23:59:59<NA><NA><NA>다단계판매업310000000<NA>
7778다단계판매업체08_26_01_P6270000200462700000410000502000-11-30<NA>4취소/말소/만료/정지/중지6직권말소<NA><NA><NA><NA>536523360<NA><NA>대구광역시 남구 대명동 대명7동 1896-13 쌍마빌딩2층<NA><NA>(주)옥타코리아2018-05-14 00:00:00I2018-08-31 23:59:59<NA><NA><NA>다단계판매업302464992<NA>
7879다단계판매업체08_26_01_P6270000200462700000410000611997-12-20<NA>4취소/말소/만료/정지/중지6직권말소<NA><NA><NA><NA>534760180<NA><NA>대구광역시 남구 봉덕동 봉덕1동 606-8번지<NA><NA>코리넷(주)2018-05-14 00:00:00I2018-08-31 23:59:59<NA><NA><NA>다단계판매업492940000<NA>
7980다단계판매업체08_26_01_P6270000200462700000410000631996-11-05<NA>4취소/말소/만료/정지/중지6직권말소<NA><NA><NA><NA>536560755<NA><NA>대구광역시 동구 신천동 391-2<NA><NA>(주)아프로드2018-05-14 00:00:00I2018-08-31 23:59:59<NA><NA><NA>다단계판매업310223392<NA>
8081다단계판매업체08_26_01_P6270000200462700000410000641995-10-28<NA>4취소/말소/만료/정지/중지6직권말소<NA><NA><NA><NA>537439866<NA><NA>대구광역시 동구 신천동 323-3<NA><NA>(주)밀레니스2018-05-14 00:00:00I2018-08-31 23:59:59<NA><NA><NA>다단계판매업330984992<NA>
8182다단계판매업체08_26_01_P6270000201562700000410000022015-05-11<NA>4취소/말소/만료/정지/중지6직권말소<NA><NA><NA><NA>16660223<NA><NA>대구광역시 수성구 수성동1가 272번지 11호 한가라코아상가 202호대구광역시 수성구 명덕로 368, 202호 (수성동1가,한가라코아상가)<NA>주식회사 아이시냅스2019-01-09 00:00:00U2019-01-11 02:40:00<NA>345387.055812262779.774089다단계판매업500000000<NA>
8283다단계판매업체08_26_01_P6270000201762700000410000012016-11-22<NA>4취소/말소/만료/정지/중지6직권말소<NA><NA><NA><NA>16668118<NA><NA>대구광역시 서구 내당동 230번지 1호 301호대구광역시 서구 서대구로 38, 301호 (내당동)<NA>주식회사 예스인포2018-05-14 00:00:00I2018-08-31 23:59:59<NA>340568.709643263467.493083다단계판매업06808600514
8384다단계판매업체08_26_01_P6270000201362700000410000052013-10-22<NA>1영업/정상BBBB영업<NA><NA><NA><NA>5318997889<NA>42142대구광역시 수성구 수성동3가 391번지 2호대구광역시 수성구 들안로 236 (수성동3가)<NA>(주)채이은2023-10-20 00:00:00U2023-10-22 02:40:00<NA>346011.564158262418.129404다단계판매업5000000005048608420
8485다단계판매업체08_26_01_P6270000202362700000410000012023-02-08<NA>1영업/정상BBBB영업<NA><NA><NA><NA>532171171<NA>41058대구광역시 동구 매여동 230번지 0호대구광역시 동구 매여로2길 53(매여동)<NA>주식회사 에스엔비아이2023-09-07 00:00:00U2023-09-09 02:40:00<NA>354859.432849268828.434409다단계판매업5000000004268802585
8586다단계판매업체08_26_01_P6270000202262700000410000012022-05-06<NA>1영업/정상BBBB영업<NA><NA><NA><NA>534277077<NA>41954대구광역시 중구 대봉동 758번지 0호 대봉태왕아너스 111동 304호대구광역시 중구 동덕로 55, 111동 304호(대봉동, 대봉태왕아너스)<NA>주식회사 올네이쳐2023-03-16 00:00:00U2023-05-26 08:48:36<NA>344716.154417263356.833666다단계판매업6000000001258633600