Overview

Dataset statistics

Number of variables50
Number of observations3477
Missing cells37012
Missing cells (%)21.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 MiB
Average record size in memory432.0 B

Variable types

Numeric17
Categorical19
Text7
Unsupported4
DateTime1
Boolean2

Dataset

Description6270000_대구광역시_06_20_01_P_세탁업_11월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000078213&dataSetDetailId=DDI_0000078227&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스ID has constant value ""Constant
데이터갱신구분 is highly imbalanced (58.5%)Imbalance
업태구분명 is highly imbalanced (87.8%)Imbalance
위생업태명 is highly imbalanced (87.8%)Imbalance
사용시작지하층 is highly imbalanced (58.2%)Imbalance
사용끝지하층 is highly imbalanced (58.3%)Imbalance
발한실여부 is highly imbalanced (99.6%)Imbalance
조건부허가시작일자 is highly imbalanced (99.6%)Imbalance
조건부허가종료일자 is highly imbalanced (99.6%)Imbalance
다중이용업소여부 is highly imbalanced (99.6%)Imbalance
인허가취소일자 has 3477 (100.0%) missing valuesMissing
폐업일자 has 1326 (38.1%) missing valuesMissing
휴업시작일자 has 3477 (100.0%) missing valuesMissing
휴업종료일자 has 3477 (100.0%) missing valuesMissing
재개업일자 has 3477 (100.0%) missing valuesMissing
소재지전화 has 209 (6.0%) missing valuesMissing
소재지면적 has 88 (2.5%) missing valuesMissing
도로명전체주소 has 1345 (38.7%) missing valuesMissing
도로명우편번호 has 1362 (39.2%) missing valuesMissing
좌표정보(X) has 136 (3.9%) missing valuesMissing
좌표정보(Y) has 136 (3.9%) missing valuesMissing
건물지상층수 has 843 (24.2%) missing valuesMissing
건물지하층수 has 1403 (40.4%) missing valuesMissing
사용끝지상층 has 1208 (34.7%) missing valuesMissing
의자수 has 1519 (43.7%) missing valuesMissing
조건부허가신고사유 has 3475 (99.9%) missing valuesMissing
세탁기수 has 1753 (50.4%) missing valuesMissing
여성종사자수 has 3252 (93.5%) missing valuesMissing
남성종사자수 has 3166 (91.1%) missing valuesMissing
회수건조수 has 1853 (53.3%) missing valuesMissing
번호 has unique valuesUnique
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
건물지상층수 has 871 (25.1%) zerosZeros
건물지하층수 has 1626 (46.8%) zerosZeros
사용끝지상층 has 479 (13.8%) zerosZeros
의자수 has 1929 (55.5%) zerosZeros
세탁기수 has 551 (15.8%) zerosZeros
여성종사자수 has 96 (2.8%) zerosZeros
남성종사자수 has 90 (2.6%) zerosZeros
회수건조수 has 864 (24.8%) zerosZeros

Reproduction

Analysis started2023-12-10 18:58:27.061242
Analysis finished2023-12-10 18:58:29.198606
Duration2.14 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct3477
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1739
Minimum1
Maximum3477
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2023-12-11T03:58:29.290877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile174.8
Q1870
median1739
Q32608
95-th percentile3303.2
Maximum3477
Range3476
Interquartile range (IQR)1738

Descriptive statistics

Standard deviation1003.8678
Coefficient of variation (CV)0.57726726
Kurtosis-1.2
Mean1739
Median Absolute Deviation (MAD)869
Skewness0
Sum6046503
Variance1007750.5
MonotonicityStrictly increasing
2023-12-11T03:58:29.509683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2324 1
 
< 0.1%
2313 1
 
< 0.1%
2314 1
 
< 0.1%
2315 1
 
< 0.1%
2316 1
 
< 0.1%
2317 1
 
< 0.1%
2318 1
 
< 0.1%
2319 1
 
< 0.1%
2320 1
 
< 0.1%
Other values (3467) 3467
99.7%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
3477 1
< 0.1%
3476 1
< 0.1%
3475 1
< 0.1%
3474 1
< 0.1%
3473 1
< 0.1%
3472 1
< 0.1%
3471 1
< 0.1%
3470 1
< 0.1%
3469 1
< 0.1%
3468 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
세탁업
3477 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
세탁업 3477
100.0%

Length

2023-12-11T03:58:29.711392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:58:29.858922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
세탁업 3477
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
06_20_01_P
3477 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row06_20_01_P
2nd row06_20_01_P
3rd row06_20_01_P
4th row06_20_01_P
5th row06_20_01_P

Common Values

ValueCountFrequency (%)
06_20_01_P 3477
100.0%

Length

2023-12-11T03:58:30.026121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:58:30.172519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
06_20_01_p 3477
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3448191
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2023-12-11T03:58:30.296076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3420000
Q13430000
median3450000
Q33470000
95-th percentile3480000
Maximum3480000
Range70000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation20333.251
Coefficient of variation (CV)0.0058967879
Kurtosis-1.1582968
Mean3448191
Median Absolute Deviation (MAD)20000
Skewness-0.27232159
Sum1.198936 × 1010
Variance4.1344108 × 108
MonotonicityIncreasing
2023-12-11T03:58:30.470925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3470000 733
21.1%
3460000 628
18.1%
3420000 512
14.7%
3450000 499
14.4%
3430000 399
11.5%
3440000 345
9.9%
3480000 200
 
5.8%
3410000 161
 
4.6%
ValueCountFrequency (%)
3410000 161
 
4.6%
3420000 512
14.7%
3430000 399
11.5%
3440000 345
9.9%
3450000 499
14.4%
3460000 628
18.1%
3470000 733
21.1%
3480000 200
 
5.8%
ValueCountFrequency (%)
3480000 200
 
5.8%
3470000 733
21.1%
3460000 628
18.1%
3450000 499
14.4%
3440000 345
9.9%
3430000 399
11.5%
3420000 512
14.7%
3410000 161
 
4.6%

관리번호
Text

UNIQUE 

Distinct3477
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
2023-12-11T03:58:30.749287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters76494
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

Unique3477 ?
Unique (%)100.0%

Sample

1st row3410000-205-2013-00003
2nd row3410000-205-2014-00001
3rd row3410000-205-2004-00012
4th row3410000-205-1988-00005
5th row3410000-205-2016-00001
ValueCountFrequency (%)
3410000-205-2013-00003 1
 
< 0.1%
3460000-205-2003-00019 1
 
< 0.1%
3460000-205-2007-00004 1
 
< 0.1%
3460000-205-2013-00002 1
 
< 0.1%
3460000-205-2013-00003 1
 
< 0.1%
3460000-205-2012-00001 1
 
< 0.1%
3460000-205-1988-00003 1
 
< 0.1%
3460000-205-1989-00001 1
 
< 0.1%
3460000-205-2013-00005 1
 
< 0.1%
3460000-205-2004-00020 1
 
< 0.1%
Other values (3467) 3467
99.7%
2023-12-11T03:58:31.242118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 33332
43.6%
- 10431
 
13.6%
2 7076
 
9.3%
3 5189
 
6.8%
5 4709
 
6.2%
4 4603
 
6.0%
1 3746
 
4.9%
9 3232
 
4.2%
7 1580
 
2.1%
6 1344
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66063
86.4%
Dash Punctuation 10431
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 33332
50.5%
2 7076
 
10.7%
3 5189
 
7.9%
5 4709
 
7.1%
4 4603
 
7.0%
1 3746
 
5.7%
9 3232
 
4.9%
7 1580
 
2.4%
6 1344
 
2.0%
8 1252
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 10431
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 76494
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 33332
43.6%
- 10431
 
13.6%
2 7076
 
9.3%
3 5189
 
6.8%
5 4709
 
6.2%
4 4603
 
6.0%
1 3746
 
4.9%
9 3232
 
4.2%
7 1580
 
2.1%
6 1344
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76494
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 33332
43.6%
- 10431
 
13.6%
2 7076
 
9.3%
3 5189
 
6.8%
5 4709
 
6.2%
4 4603
 
6.0%
1 3746
 
4.9%
9 3232
 
4.2%
7 1580
 
2.1%
6 1344
 
1.8%

인허가일자
Real number (ℝ)

Distinct2295
Distinct (%)66.2%
Missing8
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean20002211
Minimum19710301
Maximum20191104
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2023-12-11T03:58:31.430421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19710301
5-th percentile19870822
Q119941231
median20011207
Q320050526
95-th percentile20140371
Maximum20191104
Range480803
Interquartile range (IQR)109295

Descriptive statistics

Standard deviation78033.832
Coefficient of variation (CV)0.0039012603
Kurtosis-0.51685381
Mean20002211
Median Absolute Deviation (MAD)50504
Skewness0.0514326
Sum6.938767 × 1010
Variance6.089279 × 109
MonotonicityNot monotonic
2023-12-11T03:58:31.651474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030716 217
 
6.2%
20030227 71
 
2.0%
19870720 27
 
0.8%
20030728 24
 
0.7%
20030908 17
 
0.5%
19870821 17
 
0.5%
19870703 12
 
0.3%
19870608 12
 
0.3%
19870701 11
 
0.3%
19870713 10
 
0.3%
Other values (2285) 3051
87.7%
ValueCountFrequency (%)
19710301 1
 
< 0.1%
19791231 1
 
< 0.1%
19810601 1
 
< 0.1%
19810912 1
 
< 0.1%
19820818 1
 
< 0.1%
19850821 1
 
< 0.1%
19851001 1
 
< 0.1%
19870523 1
 
< 0.1%
19870526 3
0.1%
19870528 7
0.2%
ValueCountFrequency (%)
20191104 1
< 0.1%
20191101 1
< 0.1%
20191023 1
< 0.1%
20191016 1
< 0.1%
20191008 1
< 0.1%
20190925 1
< 0.1%
20190814 1
< 0.1%
20190627 1
< 0.1%
20190625 1
< 0.1%
20190618 1
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3477
Missing (%)100.0%
Memory size30.7 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
3
2151 
1
1326 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 2151
61.9%
1 1326
38.1%

Length

2023-12-11T03:58:31.821294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:58:31.953288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2151
61.9%
1 1326
38.1%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
폐업
2151 
영업/정상
1326 

Length

Max length5
Median length2
Mean length3.1440897
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2151
61.9%
영업/정상 1326
38.1%

Length

2023-12-11T03:58:32.106213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:58:32.263689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2151
61.9%
영업/정상 1326
38.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
2
2151 
1
1326 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 2151
61.9%
1 1326
38.1%

Length

2023-12-11T03:58:32.638625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:58:32.800257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2151
61.9%
1 1326
38.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
폐업
2151 
영업
1326 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2151
61.9%
영업 1326
38.1%

Length

2023-12-11T03:58:32.964675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:58:33.128230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2151
61.9%
영업 1326
38.1%

폐업일자
Real number (ℝ)

MISSING 

Distinct1424
Distinct (%)66.2%
Missing1326
Missing (%)38.1%
Infinite0
Infinite (%)0.0%
Mean20099018
Minimum19970110
Maximum20191125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2023-12-11T03:58:33.391142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19970110
5-th percentile20030924
Q120051028
median20090619
Q320141004
95-th percentile20181116
Maximum20191125
Range221015
Interquartile range (IQR)89975.5

Descriptive statistics

Standard deviation50932.114
Coefficient of variation (CV)0.0025340598
Kurtosis-1.2003836
Mean20099018
Median Absolute Deviation (MAD)40194
Skewness0.26739917
Sum4.3232987 × 1010
Variance2.5940802 × 109
MonotonicityNot monotonic
2023-12-11T03:58:33.611084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20031128 47
 
1.4%
20050930 44
 
1.3%
20030924 31
 
0.9%
20031230 28
 
0.8%
20031229 25
 
0.7%
20041229 12
 
0.3%
20041230 10
 
0.3%
20031222 9
 
0.3%
20090119 9
 
0.3%
20031226 9
 
0.3%
Other values (1414) 1927
55.4%
(Missing) 1326
38.1%
ValueCountFrequency (%)
19970110 1
< 0.1%
20000110 1
< 0.1%
20000310 1
< 0.1%
20011102 1
< 0.1%
20011112 1
< 0.1%
20011116 1
< 0.1%
20020305 1
< 0.1%
20020306 1
< 0.1%
20020313 1
< 0.1%
20020417 1
< 0.1%
ValueCountFrequency (%)
20191125 1
< 0.1%
20191121 1
< 0.1%
20191120 2
0.1%
20191115 1
< 0.1%
20191104 1
< 0.1%
20191101 1
< 0.1%
20191031 1
< 0.1%
20191030 1
< 0.1%
20191029 1
< 0.1%
20191025 2
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3477
Missing (%)100.0%
Memory size30.7 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3477
Missing (%)100.0%
Memory size30.7 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3477
Missing (%)100.0%
Memory size30.7 KiB

소재지전화
Text

MISSING 

Distinct3095
Distinct (%)94.7%
Missing209
Missing (%)6.0%
Memory size27.3 KiB
2023-12-11T03:58:34.134746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.226438
Min length3

Characters and Unicode

Total characters36688
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

Unique2930 ?
Unique (%)89.7%

Sample

1st row053 5885391
2nd row053 4237883
3rd row053 2553002
4th row053 4220603
5th row053 4228531
ValueCountFrequency (%)
053 3006
42.2%
764 28
 
0.4%
791 25
 
0.4%
763 21
 
0.3%
754 19
 
0.3%
762 19
 
0.3%
792 18
 
0.3%
765 17
 
0.2%
781 17
 
0.2%
782 15
 
0.2%
Other values (3189) 3931
55.2%
2023-12-11T03:58:34.905929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 6593
18.0%
3 5568
15.2%
0 5025
13.7%
3883
10.6%
6 2765
7.5%
2 2644
7.2%
7 2401
 
6.5%
4 2123
 
5.8%
1 1941
 
5.3%
8 1890
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32805
89.4%
Space Separator 3883
 
10.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 6593
20.1%
3 5568
17.0%
0 5025
15.3%
6 2765
8.4%
2 2644
8.1%
7 2401
 
7.3%
4 2123
 
6.5%
1 1941
 
5.9%
8 1890
 
5.8%
9 1855
 
5.7%
Space Separator
ValueCountFrequency (%)
3883
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 36688
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 6593
18.0%
3 5568
15.2%
0 5025
13.7%
3883
10.6%
6 2765
7.5%
2 2644
7.2%
7 2401
 
6.5%
4 2123
 
5.8%
1 1941
 
5.3%
8 1890
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36688
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 6593
18.0%
3 5568
15.2%
0 5025
13.7%
3883
10.6%
6 2765
7.5%
2 2644
7.2%
7 2401
 
6.5%
4 2123
 
5.8%
1 1941
 
5.3%
8 1890
 
5.2%

소재지면적
Text

MISSING 

Distinct1255
Distinct (%)37.0%
Missing88
Missing (%)2.5%
Memory size27.3 KiB
2023-12-11T03:58:35.452835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.6287991
Min length3

Characters and Unicode

Total characters15687
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

Unique905 ?
Unique (%)26.7%

Sample

1st row342.72
2nd row244.00
3rd row50.00
4th row18.98
5th row23.10
ValueCountFrequency (%)
00 679
 
20.0%
33.00 81
 
2.4%
30.00 59
 
1.7%
26.40 48
 
1.4%
16.50 46
 
1.4%
20.00 42
 
1.2%
19.80 41
 
1.2%
23.10 37
 
1.1%
36.00 36
 
1.1%
24.00 35
 
1.0%
Other values (1245) 2285
67.4%
2023-12-11T03:58:36.164748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4239
27.0%
. 3389
21.6%
2 1451
 
9.2%
3 1288
 
8.2%
1 1015
 
6.5%
4 940
 
6.0%
5 860
 
5.5%
6 781
 
5.0%
8 649
 
4.1%
9 548
 
3.5%
Other values (2) 527
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12297
78.4%
Other Punctuation 3390
 
21.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4239
34.5%
2 1451
 
11.8%
3 1288
 
10.5%
1 1015
 
8.3%
4 940
 
7.6%
5 860
 
7.0%
6 781
 
6.4%
8 649
 
5.3%
9 548
 
4.5%
7 526
 
4.3%
Other Punctuation
ValueCountFrequency (%)
. 3389
> 99.9%
, 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 15687
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4239
27.0%
. 3389
21.6%
2 1451
 
9.2%
3 1288
 
8.2%
1 1015
 
6.5%
4 940
 
6.0%
5 860
 
5.5%
6 781
 
5.0%
8 649
 
4.1%
9 548
 
3.5%
Other values (2) 527
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15687
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4239
27.0%
. 3389
21.6%
2 1451
 
9.2%
3 1288
 
8.2%
1 1015
 
6.5%
4 940
 
6.0%
5 860
 
5.5%
6 781
 
5.0%
8 649
 
4.1%
9 548
 
3.5%
Other values (2) 527
 
3.4%

소재지우편번호
Real number (ℝ)

Distinct562
Distinct (%)16.2%
Missing11
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean704573.02
Minimum700020
Maximum711891
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2023-12-11T03:58:36.370756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700020
5-th percentile701170
Q1702831.25
median704803
Q3705832
95-th percentile711812
Maximum711891
Range11871
Interquartile range (IQR)3000.75

Descriptive statistics

Standard deviation2517.8486
Coefficient of variation (CV)0.0035735808
Kurtosis1.4492969
Mean704573.02
Median Absolute Deviation (MAD)1940.5
Skewness0.99376652
Sum2.4420501 × 109
Variance6339561.6
MonotonicityNot monotonic
2023-12-11T03:58:36.595239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
704080 48
 
1.4%
702040 39
 
1.1%
706170 36
 
1.0%
701804 30
 
0.9%
704060 30
 
0.9%
706838 23
 
0.7%
706831 22
 
0.6%
711812 22
 
0.6%
704932 22
 
0.6%
711852 20
 
0.6%
Other values (552) 3174
91.3%
ValueCountFrequency (%)
700020 3
0.1%
700081 1
 
< 0.1%
700092 2
0.1%
700093 1
 
< 0.1%
700100 1
 
< 0.1%
700113 1
 
< 0.1%
700120 1
 
< 0.1%
700150 1
 
< 0.1%
700160 3
0.1%
700180 1
 
< 0.1%
ValueCountFrequency (%)
711891 5
 
0.1%
711874 4
 
0.1%
711873 4
 
0.1%
711872 7
 
0.2%
711864 9
0.3%
711861 4
 
0.1%
711852 20
0.6%
711851 1
 
< 0.1%
711845 8
 
0.2%
711843 5
 
0.1%
Distinct3296
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
2023-12-11T03:58:37.138245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length51
Mean length25.493817
Min length17

Characters and Unicode

Total characters88642
Distinct characters346
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3129 ?
Unique (%)90.0%

Sample

1st row대구광역시 중구 남산동 0616-0037번지 지상1층
2nd row대구광역시 중구 남산동 2466-20번지
3rd row대구광역시 중구 남산동 3000번지 극동스타클래스 근린생활시설 101호
4th row대구광역시 중구 동인동4가 0272-0002번지
5th row대구광역시 중구 삼덕동3가 0264-0001번지 지상1층
ValueCountFrequency (%)
대구광역시 3477
 
21.3%
달서구 733
 
4.5%
수성구 628
 
3.8%
동구 512
 
3.1%
북구 499
 
3.1%
서구 399
 
2.4%
남구 345
 
2.1%
대명동 226
 
1.4%
달성군 200
 
1.2%
중구 161
 
1.0%
Other values (3972) 9150
56.0%
2023-12-11T03:58:37.957735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15820
17.8%
6831
 
7.7%
1 4658
 
5.3%
4451
 
5.0%
3872
 
4.4%
3863
 
4.4%
3544
 
4.0%
3490
 
3.9%
3488
 
3.9%
3481
 
3.9%
Other values (336) 35144
39.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50377
56.8%
Decimal Number 19170
 
21.6%
Space Separator 15820
 
17.8%
Dash Punctuation 2803
 
3.2%
Close Punctuation 182
 
0.2%
Open Punctuation 182
 
0.2%
Uppercase Letter 65
 
0.1%
Other Punctuation 33
 
< 0.1%
Lowercase Letter 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6831
13.6%
4451
 
8.8%
3872
 
7.7%
3863
 
7.7%
3544
 
7.0%
3490
 
6.9%
3488
 
6.9%
3481
 
6.9%
1259
 
2.5%
1176
 
2.3%
Other values (305) 14922
29.6%
Uppercase Letter
ValueCountFrequency (%)
A 20
30.8%
B 17
26.2%
T 9
13.8%
P 9
13.8%
S 2
 
3.1%
K 2
 
3.1%
L 2
 
3.1%
C 1
 
1.5%
H 1
 
1.5%
E 1
 
1.5%
Decimal Number
ValueCountFrequency (%)
1 4658
24.3%
0 2429
12.7%
2 2368
12.4%
3 1866
9.7%
4 1558
 
8.1%
5 1463
 
7.6%
6 1316
 
6.9%
7 1221
 
6.4%
9 1155
 
6.0%
8 1136
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 21
63.6%
. 8
 
24.2%
/ 3
 
9.1%
@ 1
 
3.0%
Lowercase Letter
ValueCountFrequency (%)
e 9
90.0%
s 1
 
10.0%
Space Separator
ValueCountFrequency (%)
15820
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2803
100.0%
Close Punctuation
ValueCountFrequency (%)
) 182
100.0%
Open Punctuation
ValueCountFrequency (%)
( 182
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50377
56.8%
Common 38190
43.1%
Latin 75
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6831
13.6%
4451
 
8.8%
3872
 
7.7%
3863
 
7.7%
3544
 
7.0%
3490
 
6.9%
3488
 
6.9%
3481
 
6.9%
1259
 
2.5%
1176
 
2.3%
Other values (305) 14922
29.6%
Common
ValueCountFrequency (%)
15820
41.4%
1 4658
 
12.2%
- 2803
 
7.3%
0 2429
 
6.4%
2 2368
 
6.2%
3 1866
 
4.9%
4 1558
 
4.1%
5 1463
 
3.8%
6 1316
 
3.4%
7 1221
 
3.2%
Other values (8) 2688
 
7.0%
Latin
ValueCountFrequency (%)
A 20
26.7%
B 17
22.7%
T 9
12.0%
e 9
12.0%
P 9
12.0%
S 2
 
2.7%
K 2
 
2.7%
L 2
 
2.7%
s 1
 
1.3%
C 1
 
1.3%
Other values (3) 3
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50377
56.8%
ASCII 38265
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15820
41.3%
1 4658
 
12.2%
- 2803
 
7.3%
0 2429
 
6.3%
2 2368
 
6.2%
3 1866
 
4.9%
4 1558
 
4.1%
5 1463
 
3.8%
6 1316
 
3.4%
7 1221
 
3.2%
Other values (21) 2763
 
7.2%
Hangul
ValueCountFrequency (%)
6831
13.6%
4451
 
8.8%
3872
 
7.7%
3863
 
7.7%
3544
 
7.0%
3490
 
6.9%
3488
 
6.9%
3481
 
6.9%
1259
 
2.5%
1176
 
2.3%
Other values (305) 14922
29.6%

도로명전체주소
Text

MISSING 

Distinct2108
Distinct (%)98.9%
Missing1345
Missing (%)38.7%
Memory size27.3 KiB
2023-12-11T03:58:38.552938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length50
Mean length30.311445
Min length15

Characters and Unicode

Total characters64624
Distinct characters371
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2084 ?
Unique (%)97.7%

Sample

1st row대구광역시 중구 명륜로12길 7 (남산동, 지상1층)
2nd row대구광역시 중구 남산로 29 (남산동, 지상1층)
3rd row대구광역시 중구 남산로 30 (남산동, 극동스타클래스 근린생활시설 101호)
4th row대구광역시 중구 동덕로30길 79 (동인동4가)
5th row대구광역시 중구 달구벌대로445길 44-22 (삼덕동3가, 지상1층)
ValueCountFrequency (%)
대구광역시 2132
 
17.0%
달서구 440
 
3.5%
수성구 388
 
3.1%
북구 352
 
2.8%
동구 276
 
2.2%
1층 238
 
1.9%
서구 224
 
1.8%
남구 217
 
1.7%
달성군 147
 
1.2%
대명동 143
 
1.1%
Other values (2742) 8004
63.7%
2023-12-11T03:58:39.479060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10433
 
16.1%
4369
 
6.8%
3145
 
4.9%
1 2862
 
4.4%
2715
 
4.2%
2215
 
3.4%
2156
 
3.3%
2138
 
3.3%
) 2119
 
3.3%
( 2119
 
3.3%
Other values (361) 30353
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37267
57.7%
Decimal Number 10797
 
16.7%
Space Separator 10433
 
16.1%
Close Punctuation 2119
 
3.3%
Open Punctuation 2119
 
3.3%
Other Punctuation 1431
 
2.2%
Dash Punctuation 380
 
0.6%
Uppercase Letter 69
 
0.1%
Lowercase Letter 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4369
 
11.7%
3145
 
8.4%
2715
 
7.3%
2215
 
5.9%
2156
 
5.8%
2138
 
5.7%
2019
 
5.4%
1424
 
3.8%
928
 
2.5%
920
 
2.5%
Other values (330) 15238
40.9%
Uppercase Letter
ValueCountFrequency (%)
A 25
36.2%
B 12
17.4%
T 10
 
14.5%
P 10
 
14.5%
K 3
 
4.3%
S 2
 
2.9%
D 2
 
2.9%
C 2
 
2.9%
H 1
 
1.4%
L 1
 
1.4%
Decimal Number
ValueCountFrequency (%)
1 2862
26.5%
2 1539
14.3%
0 1255
11.6%
3 1165
10.8%
4 864
 
8.0%
5 829
 
7.7%
6 686
 
6.4%
7 624
 
5.8%
8 522
 
4.8%
9 451
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 1416
99.0%
@ 10
 
0.7%
. 4
 
0.3%
/ 1
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
e 8
88.9%
s 1
 
11.1%
Space Separator
ValueCountFrequency (%)
10433
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2119
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2119
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 380
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37267
57.7%
Common 27279
42.2%
Latin 78
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4369
 
11.7%
3145
 
8.4%
2715
 
7.3%
2215
 
5.9%
2156
 
5.8%
2138
 
5.7%
2019
 
5.4%
1424
 
3.8%
928
 
2.5%
920
 
2.5%
Other values (330) 15238
40.9%
Common
ValueCountFrequency (%)
10433
38.2%
1 2862
 
10.5%
) 2119
 
7.8%
( 2119
 
7.8%
2 1539
 
5.6%
, 1416
 
5.2%
0 1255
 
4.6%
3 1165
 
4.3%
4 864
 
3.2%
5 829
 
3.0%
Other values (8) 2678
 
9.8%
Latin
ValueCountFrequency (%)
A 25
32.1%
B 12
15.4%
T 10
 
12.8%
P 10
 
12.8%
e 8
 
10.3%
K 3
 
3.8%
S 2
 
2.6%
D 2
 
2.6%
C 2
 
2.6%
s 1
 
1.3%
Other values (3) 3
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37267
57.7%
ASCII 27357
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10433
38.1%
1 2862
 
10.5%
) 2119
 
7.7%
( 2119
 
7.7%
2 1539
 
5.6%
, 1416
 
5.2%
0 1255
 
4.6%
3 1165
 
4.3%
4 864
 
3.2%
5 829
 
3.0%
Other values (21) 2756
 
10.1%
Hangul
ValueCountFrequency (%)
4369
 
11.7%
3145
 
8.4%
2715
 
7.3%
2215
 
5.9%
2156
 
5.8%
2138
 
5.7%
2019
 
5.4%
1424
 
3.8%
928
 
2.5%
920
 
2.5%
Other values (330) 15238
40.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct998
Distinct (%)47.2%
Missing1362
Missing (%)39.2%
Infinite0
Infinite (%)0.0%
Mean42072.189
Minimum41002
Maximum43018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2023-12-11T03:58:39.711553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41002
5-th percentile41136
Q141548.5
median42121
Q342623.5
95-th percentile42927.3
Maximum43018
Range2016
Interquartile range (IQR)1075

Descriptive statistics

Standard deviation575.06835
Coefficient of variation (CV)0.01366861
Kurtosis-1.1972999
Mean42072.189
Median Absolute Deviation (MAD)537
Skewness-0.13502574
Sum88982680
Variance330703.6
MonotonicityNot monotonic
2023-12-11T03:58:39.947211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41569 9
 
0.3%
42446 7
 
0.2%
42819 7
 
0.2%
42644 7
 
0.2%
42915 7
 
0.2%
42665 6
 
0.2%
42769 6
 
0.2%
42031 6
 
0.2%
42112 6
 
0.2%
42422 6
 
0.2%
Other values (988) 2048
58.9%
(Missing) 1362
39.2%
ValueCountFrequency (%)
41002 3
0.1%
41005 3
0.1%
41020 1
 
< 0.1%
41022 2
 
0.1%
41024 1
 
< 0.1%
41025 1
 
< 0.1%
41026 5
0.1%
41029 1
 
< 0.1%
41033 1
 
< 0.1%
41034 2
 
0.1%
ValueCountFrequency (%)
43018 1
< 0.1%
43014 2
0.1%
43010 2
0.1%
43009 1
< 0.1%
43008 1
< 0.1%
43005 2
0.1%
43003 2
0.1%
43002 1
< 0.1%
43000 1
< 0.1%
42999 2
0.1%
Distinct2237
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
2023-12-11T03:58:40.374912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length5.1521427
Min length2

Characters and Unicode

Total characters17914
Distinct characters487
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1724 ?
Unique (%)49.6%

Sample

1st row크린토피아
2nd row하이크리닝
3rd row극동명품세탁
4th row우리
5th row대양세탁
ValueCountFrequency (%)
현대세탁소 28
 
0.8%
세탁소 27
 
0.8%
제일세탁소 26
 
0.7%
우방세탁소 20
 
0.6%
보성세탁소 19
 
0.5%
백광세탁소 19
 
0.5%
백설세탁소 17
 
0.5%
삼성세탁소 16
 
0.4%
백조세탁소 16
 
0.4%
명성세탁소 16
 
0.4%
Other values (2237) 3378
94.3%
2023-12-11T03:58:41.066089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2504
 
14.0%
2464
 
13.8%
1639
 
9.1%
491
 
2.7%
469
 
2.6%
398
 
2.2%
381
 
2.1%
274
 
1.5%
244
 
1.4%
242
 
1.4%
Other values (477) 8808
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17584
98.2%
Space Separator 107
 
0.6%
Uppercase Letter 61
 
0.3%
Decimal Number 59
 
0.3%
Open Punctuation 33
 
0.2%
Close Punctuation 33
 
0.2%
Lowercase Letter 17
 
0.1%
Other Punctuation 15
 
0.1%
Dash Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2504
 
14.2%
2464
 
14.0%
1639
 
9.3%
491
 
2.8%
469
 
2.7%
398
 
2.3%
381
 
2.2%
274
 
1.6%
244
 
1.4%
242
 
1.4%
Other values (437) 8478
48.2%
Uppercase Letter
ValueCountFrequency (%)
A 6
9.8%
C 6
9.8%
O 6
9.8%
K 6
9.8%
E 4
 
6.6%
L 4
 
6.6%
G 4
 
6.6%
I 4
 
6.6%
D 4
 
6.6%
P 3
 
4.9%
Other values (7) 14
23.0%
Decimal Number
ValueCountFrequency (%)
2 17
28.8%
1 17
28.8%
3 9
15.3%
4 6
 
10.2%
5 3
 
5.1%
9 3
 
5.1%
8 2
 
3.4%
6 2
 
3.4%
Lowercase Letter
ValueCountFrequency (%)
e 9
52.9%
r 2
 
11.8%
k 2
 
11.8%
a 1
 
5.9%
p 1
 
5.9%
h 1
 
5.9%
t 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 11
73.3%
, 2
 
13.3%
/ 1
 
6.7%
& 1
 
6.7%
Space Separator
ValueCountFrequency (%)
107
100.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17584
98.2%
Common 252
 
1.4%
Latin 78
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2504
 
14.2%
2464
 
14.0%
1639
 
9.3%
491
 
2.8%
469
 
2.7%
398
 
2.3%
381
 
2.2%
274
 
1.6%
244
 
1.4%
242
 
1.4%
Other values (437) 8478
48.2%
Latin
ValueCountFrequency (%)
e 9
 
11.5%
A 6
 
7.7%
C 6
 
7.7%
O 6
 
7.7%
K 6
 
7.7%
E 4
 
5.1%
L 4
 
5.1%
G 4
 
5.1%
I 4
 
5.1%
D 4
 
5.1%
Other values (14) 25
32.1%
Common
ValueCountFrequency (%)
107
42.5%
( 33
 
13.1%
) 33
 
13.1%
2 17
 
6.7%
1 17
 
6.7%
. 11
 
4.4%
3 9
 
3.6%
4 6
 
2.4%
- 5
 
2.0%
5 3
 
1.2%
Other values (6) 11
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17584
98.2%
ASCII 330
 
1.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2504
 
14.2%
2464
 
14.0%
1639
 
9.3%
491
 
2.8%
469
 
2.7%
398
 
2.3%
381
 
2.2%
274
 
1.6%
244
 
1.4%
242
 
1.4%
Other values (437) 8478
48.2%
ASCII
ValueCountFrequency (%)
107
32.4%
( 33
 
10.0%
) 33
 
10.0%
2 17
 
5.2%
1 17
 
5.2%
. 11
 
3.3%
3 9
 
2.7%
e 9
 
2.7%
A 6
 
1.8%
4 6
 
1.8%
Other values (30) 82
24.8%

최종수정시점
Real number (ℝ)

Distinct2574
Distinct (%)74.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0094617 × 1013
Minimum2.001091 × 1013
Maximum2.0191125 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2023-12-11T03:58:41.308251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.001091 × 1013
5-th percentile2.0020829 × 1013
Q12.0040304 × 1013
median2.0100608 × 1013
Q32.0130905 × 1013
95-th percentile2.0190223 × 1013
Maximum2.0191125 × 1013
Range1.8021518 × 1011
Interquartile range (IQR)9.0601103 × 1010

Descriptive statistics

Standard deviation5.4810451 × 1010
Coefficient of variation (CV)0.0027276186
Kurtosis-1.1711688
Mean2.0094617 × 1013
Median Absolute Deviation (MAD)5.9381101 × 1010
Skewness0.2504445
Sum6.9868983 × 1016
Variance3.0041855 × 1021
MonotonicityNot monotonic
2023-12-11T03:58:41.542300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20041126000000 84
 
2.4%
20020410000000 48
 
1.4%
20031202000000 47
 
1.4%
20030724000000 31
 
0.9%
20030603000000 26
 
0.7%
20030325000000 24
 
0.7%
20030818000000 24
 
0.7%
20030721000000 24
 
0.7%
20020411000000 24
 
0.7%
20030122000000 22
 
0.6%
Other values (2564) 3123
89.8%
ValueCountFrequency (%)
20010910000000 1
 
< 0.1%
20011005000000 4
 
0.1%
20011006000000 2
 
0.1%
20011011000000 2
 
0.1%
20020326000000 1
 
< 0.1%
20020409000000 9
 
0.3%
20020410000000 48
1.4%
20020411000000 24
0.7%
20020418000000 1
 
< 0.1%
20020423000000 1
 
< 0.1%
ValueCountFrequency (%)
20191125180706 1
< 0.1%
20191125130144 1
< 0.1%
20191121161546 1
< 0.1%
20191120145957 1
< 0.1%
20191120144433 1
< 0.1%
20191120103928 1
< 0.1%
20191119170012 1
< 0.1%
20191115131023 1
< 0.1%
20191115110038 1
< 0.1%
20191114180011 1
< 0.1%

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
I
3186 
U
 
291

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 3186
91.6%
U 291
 
8.4%

Length

2023-12-11T03:58:41.758743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:58:41.901044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 3186
91.6%
u 291
 
8.4%
Distinct179
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
Minimum2018-08-31 23:59:59
Maximum2019-11-27 02:40:00
2023-12-11T03:58:42.075993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:58:42.279700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
일반세탁업
3364 
운동화전문세탁업
 
81
세탁업 기타
 
20
빨래방업
 
12

Length

Max length8
Median length5
Mean length5.0721887
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 3364
96.8%
운동화전문세탁업 81
 
2.3%
세탁업 기타 20
 
0.6%
빨래방업 12
 
0.3%

Length

2023-12-11T03:58:42.488388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:58:42.655534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 3364
96.2%
운동화전문세탁업 81
 
2.3%
세탁업 20
 
0.6%
기타 20
 
0.6%
빨래방업 12
 
0.3%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2908
Distinct (%)87.0%
Missing136
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean343096.81
Minimum320997.13
Maximum358060.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2023-12-11T03:58:42.841725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum320997.13
5-th percentile335134.11
Q1339811.71
median342612.16
Q3346399.43
95-th percentile353145.41
Maximum358060.65
Range37063.519
Interquartile range (IQR)6587.7172

Descriptive statistics

Standard deviation5043.8911
Coefficient of variation (CV)0.014701073
Kurtosis0.33801088
Mean343096.81
Median Absolute Deviation (MAD)3244.406
Skewness0.080851951
Sum1.1462864 × 109
Variance25440838
MonotonicityNot monotonic
2023-12-11T03:58:43.037621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
338969.480757 5
 
0.1%
338962.151491 5
 
0.1%
347296.208544 5
 
0.1%
338692.161634 5
 
0.1%
340630.056274 4
 
0.1%
354088.785458 4
 
0.1%
343505.578805 4
 
0.1%
339324.389142 4
 
0.1%
337885.924275 4
 
0.1%
333231.030913 4
 
0.1%
Other values (2898) 3297
94.8%
(Missing) 136
 
3.9%
ValueCountFrequency (%)
320997.128165505 1
< 0.1%
327557.239554 1
< 0.1%
327770.336985 1
< 0.1%
327811.761117 1
< 0.1%
327853.173809 1
< 0.1%
328223.18409 1
< 0.1%
328446.299884 1
< 0.1%
328896.964042 1
< 0.1%
329116.876 1
< 0.1%
329289.647519 1
< 0.1%
ValueCountFrequency (%)
358060.647419 1
 
< 0.1%
356610.086477 1
 
< 0.1%
356468.087524 1
 
< 0.1%
356388.525062 1
 
< 0.1%
356353.404987 1
 
< 0.1%
356310.917659 3
0.1%
356270.185688 1
 
< 0.1%
356267.166058 1
 
< 0.1%
356258.18538 1
 
< 0.1%
356175.41816 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2908
Distinct (%)87.0%
Missing136
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean263289.59
Minimum240358.72
Maximum285685.62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2023-12-11T03:58:43.231325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum240358.72
5-th percentile257529.23
Q1261176.6
median263194.92
Q3265470.66
95-th percentile270715.53
Maximum285685.62
Range45326.902
Interquartile range (IQR)4294.0656

Descriptive statistics

Standard deviation4071.4354
Coefficient of variation (CV)0.015463716
Kurtosis4.1223583
Mean263289.59
Median Absolute Deviation (MAD)2131.345
Skewness-0.60771832
Sum8.7965051 × 108
Variance16576586
MonotonicityNot monotonic
2023-12-11T03:58:43.763718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
257548.491949 5
 
0.1%
262515.182502 5
 
0.1%
261275.083084 5
 
0.1%
259135.243156 5
 
0.1%
272309.461236 4
 
0.1%
260467.894846 4
 
0.1%
261920.65367 4
 
0.1%
259405.796434 4
 
0.1%
259679.933297 4
 
0.1%
262182.395989 4
 
0.1%
Other values (2898) 3297
94.8%
(Missing) 136
 
3.9%
ValueCountFrequency (%)
240358.722944 1
< 0.1%
240622.561481 1
< 0.1%
240755.214221 1
< 0.1%
240894.621331 1
< 0.1%
240899.421415 1
< 0.1%
242492.35166 1
< 0.1%
244642.335215 1
< 0.1%
244698.0 1
< 0.1%
244716.032592 1
< 0.1%
244723.218243 1
< 0.1%
ValueCountFrequency (%)
285685.624525242 1
< 0.1%
278091.653532 1
< 0.1%
273737.60685 1
< 0.1%
273712.082489 1
< 0.1%
273593.092835 1
< 0.1%
273581.899446 1
< 0.1%
273524.079239 1
< 0.1%
273441.249973 2
0.1%
273288.3903 1
< 0.1%
273228.659246 2
0.1%

위생업태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
일반세탁업
3364 
운동화전문세탁업
 
81
세탁업 기타
 
20
빨래방업
 
12

Length

Max length8
Median length5
Mean length5.0721887
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 3364
96.8%
운동화전문세탁업 81
 
2.3%
세탁업 기타 20
 
0.6%
빨래방업 12
 
0.3%

Length

2023-12-11T03:58:43.952718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:58:44.148173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 3364
96.2%
운동화전문세탁업 81
 
2.3%
세탁업 20
 
0.6%
기타 20
 
0.6%
빨래방업 12
 
0.3%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct22
Distinct (%)0.8%
Missing843
Missing (%)24.2%
Infinite0
Infinite (%)0.0%
Mean1.6848899
Minimum0
Maximum57
Zeros871
Zeros (%)25.1%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2023-12-11T03:58:44.336372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q33
95-th percentile4
Maximum57
Range57
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.3337595
Coefficient of variation (CV)1.385111
Kurtosis183.60908
Mean1.6848899
Median Absolute Deviation (MAD)1
Skewness10.148473
Sum4438
Variance5.4464332
MonotonicityNot monotonic
2023-12-11T03:58:44.481464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 871
25.1%
2 692
19.9%
3 513
14.8%
1 361
10.4%
4 135
 
3.9%
5 32
 
0.9%
6 7
 
0.2%
20 3
 
0.1%
11 3
 
0.1%
7 3
 
0.1%
Other values (12) 14
 
0.4%
(Missing) 843
24.2%
ValueCountFrequency (%)
0 871
25.1%
1 361
10.4%
2 692
19.9%
3 513
14.8%
4 135
 
3.9%
5 32
 
0.9%
6 7
 
0.2%
7 3
 
0.1%
8 1
 
< 0.1%
9 2
 
0.1%
ValueCountFrequency (%)
57 1
 
< 0.1%
40 1
 
< 0.1%
36 1
 
< 0.1%
32 1
 
< 0.1%
24 1
 
< 0.1%
20 3
0.1%
17 1
 
< 0.1%
15 2
0.1%
14 1
 
< 0.1%
12 1
 
< 0.1%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.4%
Missing1403
Missing (%)40.4%
Infinite0
Infinite (%)0.0%
Mean0.2367406
Minimum0
Maximum7
Zeros1626
Zeros (%)46.8%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2023-12-11T03:58:44.627748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.51450751
Coefficient of variation (CV)2.1732965
Kurtosis30.145023
Mean0.2367406
Median Absolute Deviation (MAD)0
Skewness3.8350175
Sum491
Variance0.26471798
MonotonicityNot monotonic
2023-12-11T03:58:44.766752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 1626
46.8%
1 427
 
12.3%
2 11
 
0.3%
3 4
 
0.1%
4 3
 
0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%
6 1
 
< 0.1%
(Missing) 1403
40.4%
ValueCountFrequency (%)
0 1626
46.8%
1 427
 
12.3%
2 11
 
0.3%
3 4
 
0.1%
4 3
 
0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
ValueCountFrequency (%)
7 1
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
4 3
 
0.1%
3 4
 
0.1%
2 11
 
0.3%
1 427
 
12.3%
0 1626
46.8%
Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
1
1668 
<NA>
1027 
0
724 
2
 
52
3
 
5

Length

Max length4
Median length1
Mean length1.8861087
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 1668
48.0%
<NA> 1027
29.5%
0 724
20.8%
2 52
 
1.5%
3 5
 
0.1%
4 1
 
< 0.1%

Length

2023-12-11T03:58:44.948991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:58:45.109698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1668
48.0%
na 1027
29.5%
0 724
20.8%
2 52
 
1.5%
3 5
 
0.1%
4 1
 
< 0.1%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.3%
Missing1208
Missing (%)34.7%
Infinite0
Infinite (%)0.0%
Mean0.83428823
Minimum0
Maximum10
Zeros479
Zeros (%)13.8%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2023-12-11T03:58:45.275330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile1
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.58406695
Coefficient of variation (CV)0.70007814
Kurtosis82.297705
Mean0.83428823
Median Absolute Deviation (MAD)0
Skewness5.224824
Sum1893
Variance0.3411342
MonotonicityNot monotonic
2023-12-11T03:58:45.431415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 1723
49.6%
0 479
 
13.8%
2 56
 
1.6%
3 6
 
0.2%
10 3
 
0.1%
4 1
 
< 0.1%
6 1
 
< 0.1%
(Missing) 1208
34.7%
ValueCountFrequency (%)
0 479
 
13.8%
1 1723
49.6%
2 56
 
1.6%
3 6
 
0.2%
4 1
 
< 0.1%
6 1
 
< 0.1%
10 3
 
0.1%
ValueCountFrequency (%)
10 3
 
0.1%
6 1
 
< 0.1%
4 1
 
< 0.1%
3 6
 
0.2%
2 56
 
1.6%
1 1723
49.6%
0 479
 
13.8%

사용시작지하층
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
0
1829 
<NA>
1610 
1
 
34
4
 
2
6
 
1

Length

Max length4
Median length1
Mean length2.3891286
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1829
52.6%
<NA> 1610
46.3%
1 34
 
1.0%
4 2
 
0.1%
6 1
 
< 0.1%
2 1
 
< 0.1%

Length

2023-12-11T03:58:45.621240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:58:45.795334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1829
52.6%
na 1610
46.3%
1 34
 
1.0%
4 2
 
0.1%
6 1
 
< 0.1%
2 1
 
< 0.1%

사용끝지하층
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
<NA>
1890 
0
1548 
1
 
35
4
 
2
6
 
1

Length

Max length4
Median length4
Mean length2.6307161
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1890
54.4%
0 1548
44.5%
1 35
 
1.0%
4 2
 
0.1%
6 1
 
< 0.1%
2 1
 
< 0.1%

Length

2023-12-11T03:58:45.966613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:58:46.138105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1890
54.4%
0 1548
44.5%
1 35
 
1.0%
4 2
 
0.1%
6 1
 
< 0.1%
2 1
 
< 0.1%

한실수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
0
1942 
<NA>
1534 
29
 
1

Length

Max length4
Median length1
Mean length2.3238424
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1942
55.9%
<NA> 1534
44.1%
29 1
 
< 0.1%

Length

2023-12-11T03:58:46.306555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:58:46.456422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1942
55.9%
na 1534
44.1%
29 1
 
< 0.1%

양실수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
0
1942 
<NA>
1534 
2
 
1

Length

Max length4
Median length1
Mean length2.3235548
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1942
55.9%
<NA> 1534
44.1%
2 1
 
< 0.1%

Length

2023-12-11T03:58:46.583865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:58:46.709144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1942
55.9%
na 1534
44.1%
2 1
 
< 0.1%

욕실수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
0
1941 
<NA>
1535 
2
 
1

Length

Max length4
Median length1
Mean length2.3244176
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1941
55.8%
<NA> 1535
44.1%
2 1
 
< 0.1%

Length

2023-12-11T03:58:46.834789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:58:46.967783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1941
55.8%
na 1535
44.1%
2 1
 
< 0.1%

발한실여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing11
Missing (%)0.3%
Memory size6.9 KiB
False
3465 
True
 
1
(Missing)
 
11
ValueCountFrequency (%)
False 3465
99.7%
True 1
 
< 0.1%
(Missing) 11
 
0.3%
2023-12-11T03:58:47.076258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

의자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.3%
Missing1519
Missing (%)43.7%
Infinite0
Infinite (%)0.0%
Mean0.052604699
Minimum0
Maximum6
Zeros1929
Zeros (%)55.5%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2023-12-11T03:58:47.190613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4473174
Coefficient of variation (CV)8.5033734
Kurtosis88.934434
Mean0.052604699
Median Absolute Deviation (MAD)0
Skewness9.1490224
Sum103
Variance0.20009285
MonotonicityNot monotonic
2023-12-11T03:58:47.331031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 1929
55.5%
3 17
 
0.5%
4 4
 
0.1%
5 4
 
0.1%
6 2
 
0.1%
2 2
 
0.1%
(Missing) 1519
43.7%
ValueCountFrequency (%)
0 1929
55.5%
2 2
 
0.1%
3 17
 
0.5%
4 4
 
0.1%
5 4
 
0.1%
6 2
 
0.1%
ValueCountFrequency (%)
6 2
 
0.1%
5 4
 
0.1%
4 4
 
0.1%
3 17
 
0.5%
2 2
 
0.1%
0 1929
55.5%
Distinct2
Distinct (%)100.0%
Missing3475
Missing (%)99.9%
Memory size27.3 KiB
2023-12-11T03:58:47.611534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length82
Median length70
Mean length70
Min length58

Characters and Unicode

Total characters140
Distinct characters75
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row폐업,지위승계등 금지(과태료50만원체납),'05,'07년 위생교육미필 2007.05.07현재행정처분진행중
2nd row가설건축물 존치기간(2007.11.30까지)만료시 존치기간 연장, 이전 또는 자진폐업을 하여야 하며 이를 이행하지 않을시 영업신고의 효력이 소멸됨.
ValueCountFrequency (%)
폐업,지위승계등 1
 
5.3%
자진폐업을 1
 
5.3%
효력이 1
 
5.3%
영업신고의 1
 
5.3%
않을시 1
 
5.3%
이행하지 1
 
5.3%
이를 1
 
5.3%
하며 1
 
5.3%
하여야 1
 
5.3%
또는 1
 
5.3%
Other values (9) 9
47.4%
2023-12-11T03:58:48.036883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17
 
12.1%
0 10
 
7.1%
. 5
 
3.6%
7 4
 
2.9%
, 4
 
2.9%
4
 
2.9%
4
 
2.9%
3
 
2.1%
3
 
2.1%
3
 
2.1%
Other values (65) 83
59.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 86
61.4%
Decimal Number 22
 
15.7%
Space Separator 17
 
12.1%
Other Punctuation 11
 
7.9%
Close Punctuation 2
 
1.4%
Open Punctuation 2
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4
 
4.7%
4
 
4.7%
3
 
3.5%
3
 
3.5%
3
 
3.5%
2
 
2.3%
2
 
2.3%
2
 
2.3%
2
 
2.3%
2
 
2.3%
Other values (53) 59
68.6%
Decimal Number
ValueCountFrequency (%)
0 10
45.5%
7 4
 
18.2%
5 3
 
13.6%
2 2
 
9.1%
1 2
 
9.1%
3 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
. 5
45.5%
, 4
36.4%
' 2
 
18.2%
Space Separator
ValueCountFrequency (%)
17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 86
61.4%
Common 54
38.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4
 
4.7%
4
 
4.7%
3
 
3.5%
3
 
3.5%
3
 
3.5%
2
 
2.3%
2
 
2.3%
2
 
2.3%
2
 
2.3%
2
 
2.3%
Other values (53) 59
68.6%
Common
ValueCountFrequency (%)
17
31.5%
0 10
18.5%
. 5
 
9.3%
7 4
 
7.4%
, 4
 
7.4%
5 3
 
5.6%
2 2
 
3.7%
' 2
 
3.7%
1 2
 
3.7%
) 2
 
3.7%
Other values (2) 3
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 86
61.4%
ASCII 54
38.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17
31.5%
0 10
18.5%
. 5
 
9.3%
7 4
 
7.4%
, 4
 
7.4%
5 3
 
5.6%
2 2
 
3.7%
' 2
 
3.7%
1 2
 
3.7%
) 2
 
3.7%
Other values (2) 3
 
5.6%
Hangul
ValueCountFrequency (%)
4
 
4.7%
4
 
4.7%
3
 
3.5%
3
 
3.5%
3
 
3.5%
2
 
2.3%
2
 
2.3%
2
 
2.3%
2
 
2.3%
2
 
2.3%
Other values (53) 59
68.6%

조건부허가시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
<NA>
3476 
20070213
 
1

Length

Max length8
Median length4
Mean length4.0011504
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3476
> 99.9%
20070213 1
 
< 0.1%

Length

2023-12-11T03:58:48.232514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:58:48.384331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3476
> 99.9%
20070213 1
 
< 0.1%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
<NA>
3476 
20071130
 
1

Length

Max length8
Median length4
Mean length4.0011504
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3476
> 99.9%
20071130 1
 
< 0.1%

Length

2023-12-11T03:58:48.571464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:58:48.725318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3476
> 99.9%
20071130 1
 
< 0.1%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
<NA>
1834 
임대
1391 
자가
252 

Length

Max length4
Median length4
Mean length3.0549324
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1834
52.7%
임대 1391
40.0%
자가 252
 
7.2%

Length

2023-12-11T03:58:48.889130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:58:49.054867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1834
52.7%
임대 1391
40.0%
자가 252
 
7.2%

세탁기수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)0.6%
Missing1753
Missing (%)50.4%
Infinite0
Infinite (%)0.0%
Mean1.2453596
Minimum0
Maximum20
Zeros551
Zeros (%)15.8%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2023-12-11T03:58:49.203944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum20
Range20
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.1951762
Coefficient of variation (CV)0.9597037
Kurtosis36.579737
Mean1.2453596
Median Absolute Deviation (MAD)1
Skewness3.0004683
Sum2147
Variance1.4284462
MonotonicityNot monotonic
2023-12-11T03:58:49.396648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2 574
 
16.5%
0 551
 
15.8%
1 443
 
12.7%
3 111
 
3.2%
4 31
 
0.9%
5 6
 
0.2%
6 3
 
0.1%
7 2
 
0.1%
8 1
 
< 0.1%
20 1
 
< 0.1%
(Missing) 1753
50.4%
ValueCountFrequency (%)
0 551
15.8%
1 443
12.7%
2 574
16.5%
3 111
 
3.2%
4 31
 
0.9%
5 6
 
0.2%
6 3
 
0.1%
7 2
 
0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
20 1
 
< 0.1%
9 1
 
< 0.1%
8 1
 
< 0.1%
7 2
 
0.1%
6 3
 
0.1%
5 6
 
0.2%
4 31
 
0.9%
3 111
 
3.2%
2 574
16.5%
1 443
12.7%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)4.0%
Missing3252
Missing (%)93.5%
Infinite0
Infinite (%)0.0%
Mean0.8
Minimum0
Maximum20
Zeros96
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2023-12-11T03:58:49.574747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile1
Maximum20
Range20
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.677051
Coefficient of variation (CV)2.0963137
Kurtosis82.106069
Mean0.8
Median Absolute Deviation (MAD)0
Skewness8.0435419
Sum180
Variance2.8125
MonotonicityNot monotonic
2023-12-11T03:58:49.741069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 119
 
3.4%
0 96
 
2.8%
2 3
 
0.1%
3 2
 
0.1%
10 1
 
< 0.1%
20 1
 
< 0.1%
6 1
 
< 0.1%
8 1
 
< 0.1%
5 1
 
< 0.1%
(Missing) 3252
93.5%
ValueCountFrequency (%)
0 96
2.8%
1 119
3.4%
2 3
 
0.1%
3 2
 
0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
8 1
 
< 0.1%
10 1
 
< 0.1%
20 1
 
< 0.1%
ValueCountFrequency (%)
20 1
 
< 0.1%
10 1
 
< 0.1%
8 1
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
3 2
 
0.1%
2 3
 
0.1%
1 119
3.4%
0 96
2.8%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)2.3%
Missing3166
Missing (%)91.1%
Infinite0
Infinite (%)0.0%
Mean0.82636656
Minimum0
Maximum9
Zeros90
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2023-12-11T03:58:49.907419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile2
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.83978452
Coefficient of variation (CV)1.0162373
Kurtosis38.157095
Mean0.82636656
Median Absolute Deviation (MAD)0
Skewness4.5802361
Sum257
Variance0.70523805
MonotonicityNot monotonic
2023-12-11T03:58:50.083175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 203
 
5.8%
0 90
 
2.6%
2 12
 
0.3%
4 2
 
0.1%
3 2
 
0.1%
9 1
 
< 0.1%
7 1
 
< 0.1%
(Missing) 3166
91.1%
ValueCountFrequency (%)
0 90
2.6%
1 203
5.8%
2 12
 
0.3%
3 2
 
0.1%
4 2
 
0.1%
7 1
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
9 1
 
< 0.1%
7 1
 
< 0.1%
4 2
 
0.1%
3 2
 
0.1%
2 12
 
0.3%
1 203
5.8%
0 90
2.6%

회수건조수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.5%
Missing1853
Missing (%)53.3%
Infinite0
Infinite (%)0.0%
Mean0.50246305
Minimum0
Maximum10
Zeros864
Zeros (%)24.8%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2023-12-11T03:58:50.244934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum10
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.6396193
Coefficient of variation (CV)1.2729678
Kurtosis39.070479
Mean0.50246305
Median Absolute Deviation (MAD)0
Skewness3.5482606
Sum816
Variance0.40911285
MonotonicityNot monotonic
2023-12-11T03:58:50.425176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 864
24.8%
1 731
 
21.0%
2 19
 
0.5%
3 4
 
0.1%
5 2
 
0.1%
4 2
 
0.1%
7 1
 
< 0.1%
10 1
 
< 0.1%
(Missing) 1853
53.3%
ValueCountFrequency (%)
0 864
24.8%
1 731
21.0%
2 19
 
0.5%
3 4
 
0.1%
4 2
 
0.1%
5 2
 
0.1%
7 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
10 1
 
< 0.1%
7 1
 
< 0.1%
5 2
 
0.1%
4 2
 
0.1%
3 4
 
0.1%
2 19
 
0.5%
1 731
21.0%
0 864
24.8%

침대수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
<NA>
1901 
0
1576 

Length

Max length4
Median length4
Mean length2.6402071
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1901
54.7%
0 1576
45.3%

Length

2023-12-11T03:58:50.610192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:58:50.765666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1901
54.7%
0 1576
45.3%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
False
3476 
True
 
1
ValueCountFrequency (%)
False 3476
> 99.9%
True 1
 
< 0.1%
2023-12-11T03:58:50.879094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
01세탁업06_20_01_P34100003410000-205-2013-0000320131223<NA>1영업/정상1영업<NA><NA><NA><NA>053 5885391342.72700834대구광역시 중구 남산동 0616-0037번지 지상1층대구광역시 중구 명륜로12길 7 (남산동, 지상1층)41969크린토피아20170323113739I2018-08-31 23:59:59.0일반세탁업343524.92975263583.868111일반세탁업411100000N0<NA><NA><NA><NA>2<NA><NA>70N
12세탁업06_20_01_P34100003410000-205-2014-0000120140123<NA>1영업/정상1영업<NA><NA><NA><NA>053 4237883244.00700837대구광역시 중구 남산동 2466-20번지대구광역시 중구 남산로 29 (남산동, 지상1층)41978하이크리닝20170317114223I2018-08-31 23:59:59.0일반세탁업342864.46009263255.886411일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
23세탁업06_20_01_P34100003410000-205-2004-0001220040806<NA>1영업/정상1영업<NA><NA><NA><NA>053 255300250.00700440대구광역시 중구 남산동 3000번지 극동스타클래스 근린생활시설 101호대구광역시 중구 남산로 30 (남산동, 극동스타클래스 근린생활시설 101호)41971극동명품세탁20170323113944I2018-08-31 23:59:59.0일반세탁업343009.218633263321.424532일반세탁업101100000N0<NA><NA><NA>임대0<NA><NA>00N
34세탁업06_20_01_P34100003410000-205-1988-0000519880112<NA>1영업/정상1영업<NA><NA><NA><NA>053 422060318.98700847대구광역시 중구 동인동4가 0272-0002번지대구광역시 중구 동덕로30길 79 (동인동4가)41945우리20160707153157I2018-08-31 23:59:59.0일반세탁업345174.313641264135.86972일반세탁업1<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
45세탁업06_20_01_P34100003410000-205-2016-0000120161108<NA>1영업/정상1영업<NA><NA><NA><NA>053 422853123.10700413대구광역시 중구 삼덕동3가 0264-0001번지 지상1층대구광역시 중구 달구벌대로445길 44-22 (삼덕동3가, 지상1층)41948대양세탁20170921132847I2018-08-31 23:59:59.0일반세탁업345133.885687263875.819382일반세탁업001100000N0<NA><NA><NA><NA>0<NA><NA>00N
56세탁업06_20_01_P34100003410000-205-2017-0000120170308<NA>1영업/정상1영업<NA><NA><NA><NA><NA>36.70700808대구광역시 중구 남산동 2937-0001번지 101동8호대구광역시 중구 달구벌대로 1950 (남산동, 101동8호)41974남산세탁소20170320094517I2018-08-31 23:59:59.0일반세탁업342397.738481263582.562604일반세탁업001100000N0<NA><NA><NA><NA>0<NA><NA>00N
67세탁업06_20_01_P34100003410000-205-2006-0000320060413<NA>1영업/정상1영업<NA><NA><NA><NA>053 941 309356.10700837대구광역시 중구 남산동 2466-0001번지 지상1층대구광역시 중구 남산로13길 17 (남산동, 지상1층)41978황실크리닝20170921132913I2018-08-31 23:59:59.0일반세탁업342754.486268263376.49575일반세탁업311100000N0<NA><NA><NA>임대0<NA><NA>00N
78세탁업06_20_01_P34100003410000-205-2013-0000120130430<NA>1영업/정상1영업<NA><NA><NA><NA>053 9646667121.80700835대구광역시 중구 남산동 0216-0045번지대구광역시 중구 남산로8길 51 (남산동)41969(주)티에스글로벌20171221141811I2018-08-31 23:59:59.0일반세탁업343386.587953263300.654217일반세탁업101100000N0<NA><NA><NA><NA>2<NA><NA>10N
89세탁업06_20_01_P34100003410000-205-1988-0000919880129<NA>1영업/정상1영업<NA><NA><NA><NA>053 422297614.50700823대구광역시 중구 봉산동 0037-0023번지대구광역시 중구 동성로1길 46-15 (봉산동)41943경일사20120223141322I2018-08-31 23:59:59.0일반세탁업344010.318046264020.296706일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
910세탁업06_20_01_P34100003410000-205-2007-0000220070131<NA>1영업/정상1영업<NA><NA><NA><NA>053 294022048.90700818대구광역시 중구 대신동 0305-0001번지대구광역시 중구 달구벌대로 1975 (대신동)41927태왕세탁소20170323113328I2018-08-31 23:59:59.0일반세탁업342612.164106263922.517239일반세탁업101100000N0<NA><NA><NA>임대0<NA><NA>10N
번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
34673468세탁업06_20_01_P34800003480000-205-2000-0000320000127<NA>3폐업2폐업20031230<NA><NA><NA>053 615960631.50711843대구광역시 달성군 옥포면 교항리 1519번지 옥포제림뉴타운상가 401동 101호<NA><NA>백경세탁소20031231000000I2018-08-31 23:59:59.0일반세탁업330336.119714255408.050838일반세탁업1<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
34683469세탁업06_20_01_P34800003480000-205-1998-0000419980608<NA>3폐업2폐업20030722<NA><NA><NA><NA><NA>711834대구광역시 달성군 화원읍 천내리 128-10번지<NA><NA>제일세탁소20030722000000I2018-08-31 23:59:59.0일반세탁업335470.868703257270.805991일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
34693470세탁업06_20_01_P34800003480000-205-2003-0000420030808<NA>3폐업2폐업20150507<NA><NA><NA>053 615 398948.90711852대구광역시 달성군 논공읍 남리 635-3번지 논공주공아파트상가102호대구광역시 달성군 논공읍 남리길 48 (논공주공아파트상가102호)42985주공세탁하우스20140109153229I2018-08-31 23:59:59.0일반세탁업331049.71427248024.757834일반세탁업1<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
34703471세탁업06_20_01_P34800003480000-205-2000-0000420000901<NA>3폐업2폐업20050616<NA><NA><NA>053 644555044.46711832대구광역시 달성군 화원읍 명곡리 111번지 명곡미래빌 1단지상가 가동 101호<NA><NA>명곡크리닝20041104000000I2018-08-31 23:59:59.0일반세탁업335197.916723256463.132683일반세탁업2111<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
34713472세탁업06_20_01_P34800003480000-205-1995-0000819950414<NA>3폐업2폐업20140527<NA><NA><NA>053 615370823.00711852대구광역시 달성군 논공읍 북리 803-138번지대구광역시 달성군 논공읍 논공로17길 842979에덴세탁소20030818000000I2018-08-31 23:59:59.0일반세탁업330404.775353248649.853958일반세탁업3<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
34723473세탁업06_20_01_P34800003480000-205-1992-0000919920223<NA>3폐업2폐업20041012<NA><NA><NA>053 616744126.40711842대구광역시 달성군 옥포면 강림리 562-4번지<NA><NA>강림세탁소20030818000000I2018-08-31 23:59:59.0일반세탁업329289.647519254318.70007일반세탁업1<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
34733474세탁업06_20_01_P34800003480000-205-2002-0000120020528<NA>3폐업2폐업20041025<NA><NA><NA>053 641828016.50711836대구광역시 달성군 화원읍 천내리 889번지<NA><NA>아람세탁소20041029000000I2018-08-31 23:59:59.0일반세탁업335544.161184256649.86365일반세탁업2<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
34743475세탁업06_20_01_P34800003480000-205-1995-0000419951230<NA>3폐업2폐업20050107<NA><NA><NA>053 643006642.90711839대구광역시 달성군 화원읍 성산리 501번지 태왕상가 1층 106호<NA><NA>소망세탁소20050107000000I2018-08-31 23:59:59.0일반세탁업334699.779354256883.58546일반세탁업2111<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
34753476세탁업06_20_01_P34800003480000-205-2001-0000420011008<NA>3폐업2폐업20151026<NA><NA><NA>053 615354121.00711873대구광역시 달성군 현풍면 중리 335-1번지 학산상가 1층 1호대구광역시 달성군 현풍면 현풍동로 23 (학산상가 1층 1호)43005학산세탁소20030818000000I2018-08-31 23:59:59.0일반세탁업330924.217574244716.032592일반세탁업2<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
34763477세탁업06_20_01_P34800003480000-205-2001-0000920011013<NA>3폐업2폐업20011112<NA><NA><NA>053 641792042.90711839대구광역시 달성군 화원읍 성산리 55번지 삼주아파트 상가 1층동 101호<NA><NA>삼주크리링20020904000000I2018-08-31 23:59:59.0일반세탁업334485.229602257516.968663일반세탁업101<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N