Overview

Dataset statistics

Number of variables51
Number of observations2631
Missing cells31750
Missing cells (%)23.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 MiB
Average record size in memory441.0 B

Variable types

Numeric18
Categorical18
Text7
Unsupported5
DateTime1
Boolean2

Dataset

Description2021-05-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123152

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
업태구분명 is highly imbalanced (93.7%)Imbalance
위생업태명 is highly imbalanced (93.7%)Imbalance
발한실여부 is highly imbalanced (99.5%)Imbalance
의자수 is highly imbalanced (53.3%)Imbalance
조건부허가시작일자 is highly imbalanced (98.9%)Imbalance
다중이용업소여부 is highly imbalanced (99.5%)Imbalance
인허가취소일자 has 2631 (100.0%) missing valuesMissing
폐업일자 has 961 (36.5%) missing valuesMissing
휴업시작일자 has 2631 (100.0%) missing valuesMissing
휴업종료일자 has 2631 (100.0%) missing valuesMissing
재개업일자 has 2631 (100.0%) missing valuesMissing
소재지전화 has 629 (23.9%) missing valuesMissing
소재지우편번호 has 34 (1.3%) missing valuesMissing
도로명전체주소 has 783 (29.8%) missing valuesMissing
도로명우편번호 has 827 (31.4%) missing valuesMissing
좌표정보(x) has 70 (2.7%) missing valuesMissing
좌표정보(y) has 70 (2.7%) missing valuesMissing
건물지상층수 has 435 (16.5%) missing valuesMissing
건물지하층수 has 593 (22.5%) missing valuesMissing
사용시작지상층 has 688 (26.1%) missing valuesMissing
사용끝지상층 has 950 (36.1%) missing valuesMissing
사용시작지하층 has 1409 (53.6%) missing valuesMissing
사용끝지하층 has 1585 (60.2%) missing valuesMissing
발한실여부 has 72 (2.7%) missing valuesMissing
조건부허가신고사유 has 2626 (99.8%) missing valuesMissing
조건부허가종료일자 has 2624 (99.7%) missing valuesMissing
여성종사자수 has 2123 (80.7%) missing valuesMissing
남성종사자수 has 2078 (79.0%) missing valuesMissing
Unnamed: 50 has 2631 (100.0%) 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
Unnamed: 50 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 630 (23.9%) zerosZeros
건물지하층수 has 1165 (44.3%) zerosZeros
사용시작지상층 has 355 (13.5%) zerosZeros
사용끝지상층 has 349 (13.3%) zerosZeros
사용시작지하층 has 1048 (39.8%) zerosZeros
사용끝지하층 has 888 (33.8%) zerosZeros
여성종사자수 has 446 (17.0%) zerosZeros
남성종사자수 has 376 (14.3%) zerosZeros

Reproduction

Analysis started2024-04-20 15:19:19.423633
Analysis finished2024-04-20 15:19:21.608138
Duration2.18 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct2631
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1316
Minimum1
Maximum2631
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.2 KiB
2024-04-21T00:19:21.763657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile132.5
Q1658.5
median1316
Q31973.5
95-th percentile2499.5
Maximum2631
Range2630
Interquartile range (IQR)1315

Descriptive statistics

Standard deviation759.6486
Coefficient of variation (CV)0.57724058
Kurtosis-1.2
Mean1316
Median Absolute Deviation (MAD)658
Skewness0
Sum3462396
Variance577066
MonotonicityStrictly increasing
2024-04-21T00:19:22.169851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1749 1
 
< 0.1%
1751 1
 
< 0.1%
1752 1
 
< 0.1%
1753 1
 
< 0.1%
1754 1
 
< 0.1%
1755 1
 
< 0.1%
1756 1
 
< 0.1%
1757 1
 
< 0.1%
1758 1
 
< 0.1%
Other values (2621) 2621
99.6%
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 (%)
2631 1
< 0.1%
2630 1
< 0.1%
2629 1
< 0.1%
2628 1
< 0.1%
2627 1
< 0.1%
2626 1
< 0.1%
2625 1
< 0.1%
2624 1
< 0.1%
2623 1
< 0.1%
2622 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size20.7 KiB
건물위생관리업
2631 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 2631
100.0%

Length

2024-04-21T00:19:22.588165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:19:22.886609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 2631
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size20.7 KiB
09_30_04_P
2631 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09_30_04_P
2nd row09_30_04_P
3rd row09_30_04_P
4th row09_30_04_P
5th row09_30_04_P

Common Values

ValueCountFrequency (%)
09_30_04_P 2631
100.0%

Length

2024-04-21T00:19:23.302839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:19:23.699369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_30_04_p 2631
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3325541.6
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.2 KiB
2024-04-21T00:19:24.002779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3260000
Q13290000
median3320000
Q33370000
95-th percentile3400000
Maximum3400000
Range150000
Interquartile range (IQR)80000

Descriptive statistics

Standard deviation44495.496
Coefficient of variation (CV)0.013379924
Kurtosis-1.1287208
Mean3325541.6
Median Absolute Deviation (MAD)30000
Skewness0.19638963
Sum8.7495 × 109
Variance1.9798491 × 109
MonotonicityNot monotonic
2024-04-21T00:19:24.411592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 356
13.5%
3300000 298
11.3%
3270000 238
9.0%
3400000 228
8.7%
3330000 208
7.9%
3370000 203
 
7.7%
3310000 162
 
6.2%
3350000 151
 
5.7%
3380000 141
 
5.4%
3390000 134
 
5.1%
Other values (6) 512
19.5%
ValueCountFrequency (%)
3250000 102
 
3.9%
3260000 75
 
2.9%
3270000 238
9.0%
3280000 27
 
1.0%
3290000 356
13.5%
3300000 298
11.3%
3310000 162
6.2%
3320000 132
 
5.0%
3330000 208
7.9%
3340000 121
 
4.6%
ValueCountFrequency (%)
3400000 228
8.7%
3390000 134
5.1%
3380000 141
5.4%
3370000 203
7.7%
3360000 55
 
2.1%
3350000 151
5.7%
3340000 121
4.6%
3330000 208
7.9%
3320000 132
5.0%
3310000 162
6.2%

관리번호
Text

UNIQUE 

Distinct2631
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size20.7 KiB
2024-04-21T00:19:25.222349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters57882
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

Unique2631 ?
Unique (%)100.0%

Sample

1st row3350000-206-2021-00001
2nd row3260000-206-2011-00003
3rd row3270000-206-2014-00014
4th row3380000-206-2019-00001
5th row3320000-206-2005-00002
ValueCountFrequency (%)
3350000-206-2021-00001 1
 
< 0.1%
3320000-206-2016-00003 1
 
< 0.1%
3320000-206-2018-00003 1
 
< 0.1%
3320000-206-2014-00001 1
 
< 0.1%
3320000-206-2013-00004 1
 
< 0.1%
3320000-206-2015-00004 1
 
< 0.1%
3320000-206-2015-00003 1
 
< 0.1%
3320000-206-2015-00002 1
 
< 0.1%
3320000-206-2015-00001 1
 
< 0.1%
3320000-206-2012-00006 1
 
< 0.1%
Other values (2621) 2621
99.6%
2024-04-21T00:19:26.434453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 26869
46.4%
- 7893
 
13.6%
2 6772
 
11.7%
3 5163
 
8.9%
6 3290
 
5.7%
1 2846
 
4.9%
9 1510
 
2.6%
4 1006
 
1.7%
7 990
 
1.7%
5 813
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49989
86.4%
Dash Punctuation 7893
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 26869
53.7%
2 6772
 
13.5%
3 5163
 
10.3%
6 3290
 
6.6%
1 2846
 
5.7%
9 1510
 
3.0%
4 1006
 
2.0%
7 990
 
2.0%
5 813
 
1.6%
8 730
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 7893
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 57882
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 26869
46.4%
- 7893
 
13.6%
2 6772
 
11.7%
3 5163
 
8.9%
6 3290
 
5.7%
1 2846
 
4.9%
9 1510
 
2.6%
4 1006
 
1.7%
7 990
 
1.7%
5 813
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57882
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 26869
46.4%
- 7893
 
13.6%
2 6772
 
11.7%
3 5163
 
8.9%
6 3290
 
5.7%
1 2846
 
4.9%
9 1510
 
2.6%
4 1006
 
1.7%
7 990
 
1.7%
5 813
 
1.4%

인허가일자
Real number (ℝ)

Distinct1961
Distinct (%)74.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20088545
Minimum19870507
Maximum20210325
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.2 KiB
2024-04-21T00:19:26.866440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19870507
5-th percentile19960716
Q120041006
median20091130
Q320141009
95-th percentile20200119
Maximum20210325
Range339818
Interquartile range (IQR)100003.5

Descriptive statistics

Standard deviation72061.544
Coefficient of variation (CV)0.0035871959
Kurtosis-0.13637574
Mean20088545
Median Absolute Deviation (MAD)49995
Skewness-0.48593412
Sum5.2852961 × 1010
Variance5.1928662 × 109
MonotonicityNot monotonic
2024-04-21T00:19:27.323111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20100603 6
 
0.2%
20081209 6
 
0.2%
20120622 6
 
0.2%
20031125 5
 
0.2%
20020403 5
 
0.2%
20070614 5
 
0.2%
20000706 5
 
0.2%
20101217 5
 
0.2%
20110726 5
 
0.2%
20140219 5
 
0.2%
Other values (1951) 2578
98.0%
ValueCountFrequency (%)
19870507 1
 
< 0.1%
19870520 1
 
< 0.1%
19870601 2
0.1%
19870612 1
 
< 0.1%
19870709 3
0.1%
19870821 1
 
< 0.1%
19871006 1
 
< 0.1%
19871110 1
 
< 0.1%
19871123 1
 
< 0.1%
19871203 1
 
< 0.1%
ValueCountFrequency (%)
20210325 1
< 0.1%
20210324 1
< 0.1%
20210322 1
< 0.1%
20210319 1
< 0.1%
20210318 1
< 0.1%
20210316 1
< 0.1%
20210312 1
< 0.1%
20210305 1
< 0.1%
20210223 2
0.1%
20210218 2
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2631
Missing (%)100.0%
Memory size23.2 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.7 KiB
3
1670 
1
961 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 1670
63.5%
1 961
36.5%

Length

2024-04-21T00:19:27.663332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:19:27.828808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1670
63.5%
1 961
36.5%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.7 KiB
폐업
1670 
영업/정상
961 

Length

Max length5
Median length2
Mean length3.0957811
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1670
63.5%
영업/정상 961
36.5%

Length

2024-04-21T00:19:28.018043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:19:28.346509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1670
63.5%
영업/정상 961
36.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.7 KiB
2
1670 
1
961 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 1670
63.5%
1 961
36.5%

Length

2024-04-21T00:19:28.685071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:19:28.985462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1670
63.5%
1 961
36.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.7 KiB
폐업
1670 
영업
961 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1670
63.5%
영업 961
36.5%

Length

2024-04-21T00:19:29.300908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:19:29.608959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1670
63.5%
영업 961
36.5%

폐업일자
Real number (ℝ)

MISSING 

Distinct1221
Distinct (%)73.1%
Missing961
Missing (%)36.5%
Infinite0
Infinite (%)0.0%
Mean20116603
Minimum19880329
Maximum20210331
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.2 KiB
2024-04-21T00:19:29.952375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19880329
5-th percentile20020825
Q120070130
median20121103
Q320170406
95-th percentile20200428
Maximum20210331
Range330002
Interquartile range (IQR)100276

Descriptive statistics

Standard deviation59974.867
Coefficient of variation (CV)0.0029813615
Kurtosis-0.47580569
Mean20116603
Median Absolute Deviation (MAD)50012.5
Skewness-0.45359163
Sum3.3594727 × 1010
Variance3.5969847 × 109
MonotonicityNot monotonic
2024-04-21T00:19:30.358151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20180525 23
 
0.9%
20200428 15
 
0.6%
20110217 10
 
0.4%
20030227 10
 
0.4%
20180808 9
 
0.3%
20041213 8
 
0.3%
20031124 8
 
0.3%
20170831 8
 
0.3%
20090318 7
 
0.3%
20031114 7
 
0.3%
Other values (1211) 1565
59.5%
(Missing) 961
36.5%
ValueCountFrequency (%)
19880329 1
< 0.1%
19880723 1
< 0.1%
19940215 2
0.1%
19940412 1
< 0.1%
19940630 1
< 0.1%
19940808 1
< 0.1%
19941018 1
< 0.1%
19941111 2
0.1%
19941213 1
< 0.1%
19950111 1
< 0.1%
ValueCountFrequency (%)
20210331 1
 
< 0.1%
20210326 1
 
< 0.1%
20210322 1
 
< 0.1%
20210311 1
 
< 0.1%
20210309 2
0.1%
20210304 1
 
< 0.1%
20210225 3
0.1%
20210216 1
 
< 0.1%
20210210 2
0.1%
20210202 1
 
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2631
Missing (%)100.0%
Memory size23.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2631
Missing (%)100.0%
Memory size23.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2631
Missing (%)100.0%
Memory size23.2 KiB

소재지전화
Text

MISSING 

Distinct1738
Distinct (%)86.8%
Missing629
Missing (%)23.9%
Memory size20.7 KiB
2024-04-21T00:19:31.637638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.210789
Min length3

Characters and Unicode

Total characters22444
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1543 ?
Unique (%)77.1%

Sample

1st row02 4647058
2nd row051 503 2470
3rd row051 3410086
4th row051 342 8377
5th row051 467 8313
ValueCountFrequency (%)
051 1777
37.2%
727 58
 
1.2%
070 55
 
1.2%
728 17
 
0.4%
502 15
 
0.3%
724 15
 
0.3%
722 13
 
0.3%
557 12
 
0.3%
851 11
 
0.2%
555 11
 
0.2%
Other values (1942) 2795
58.5%
2024-04-21T00:19:33.295754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 3511
15.6%
0 3430
15.3%
1 3283
14.6%
2794
12.4%
2 1598
7.1%
7 1549
6.9%
6 1400
 
6.2%
4 1382
 
6.2%
3 1326
 
5.9%
8 1254
 
5.6%
Other values (2) 917
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19649
87.5%
Space Separator 2794
 
12.4%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 3511
17.9%
0 3430
17.5%
1 3283
16.7%
2 1598
8.1%
7 1549
7.9%
6 1400
 
7.1%
4 1382
 
7.0%
3 1326
 
6.7%
8 1254
 
6.4%
9 916
 
4.7%
Space Separator
ValueCountFrequency (%)
2794
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22444
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 3511
15.6%
0 3430
15.3%
1 3283
14.6%
2794
12.4%
2 1598
7.1%
7 1549
6.9%
6 1400
 
6.2%
4 1382
 
6.2%
3 1326
 
5.9%
8 1254
 
5.6%
Other values (2) 917
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22444
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 3511
15.6%
0 3430
15.3%
1 3283
14.6%
2794
12.4%
2 1598
7.1%
7 1549
6.9%
6 1400
 
6.2%
4 1382
 
6.2%
3 1326
 
5.9%
8 1254
 
5.6%
Other values (2) 917
 
4.1%
Distinct1557
Distinct (%)59.7%
Missing24
Missing (%)0.9%
Memory size20.7 KiB
2024-04-21T00:19:34.341724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.8665132
Min length3

Characters and Unicode

Total characters12687
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

Unique1258 ?
Unique (%)48.3%

Sample

1st row.00
2nd row.00
3rd row46.20
4th row33.60
5th row91.30
ValueCountFrequency (%)
00 351
 
13.5%
33.00 38
 
1.5%
66.00 21
 
0.8%
40.00 15
 
0.6%
30.00 13
 
0.5%
36.00 12
 
0.5%
49.50 12
 
0.5%
99.00 11
 
0.4%
25.00 11
 
0.4%
12.00 11
 
0.4%
Other values (1547) 2112
81.0%
2024-04-21T00:19:35.715976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2753
21.7%
. 2607
20.5%
1 1083
 
8.5%
2 998
 
7.9%
5 878
 
6.9%
3 857
 
6.8%
6 812
 
6.4%
4 787
 
6.2%
8 707
 
5.6%
7 604
 
4.8%
Other values (2) 601
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10075
79.4%
Other Punctuation 2612
 
20.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2753
27.3%
1 1083
 
10.7%
2 998
 
9.9%
5 878
 
8.7%
3 857
 
8.5%
6 812
 
8.1%
4 787
 
7.8%
8 707
 
7.0%
7 604
 
6.0%
9 596
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 2607
99.8%
, 5
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 12687
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2753
21.7%
. 2607
20.5%
1 1083
 
8.5%
2 998
 
7.9%
5 878
 
6.9%
3 857
 
6.8%
6 812
 
6.4%
4 787
 
6.2%
8 707
 
5.6%
7 604
 
4.8%
Other values (2) 601
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12687
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2753
21.7%
. 2607
20.5%
1 1083
 
8.5%
2 998
 
7.9%
5 878
 
6.9%
3 857
 
6.8%
6 812
 
6.4%
4 787
 
6.2%
8 707
 
5.6%
7 604
 
4.8%
Other values (2) 601
 
4.7%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct605
Distinct (%)23.3%
Missing34
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean610916.66
Minimum400410
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.2 KiB
2024-04-21T00:19:36.131980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum400410
5-th percentile601807
Q1607813
median611825
Q3614854
95-th percentile619912
Maximum619953
Range219543
Interquartile range (IQR)7041

Descriptive statistics

Standard deviation7009.0692
Coefficient of variation (CV)0.011473037
Kurtosis312.02425
Mean610916.66
Median Absolute Deviation (MAD)3993
Skewness-10.561976
Sum1.5865506 × 109
Variance49127051
MonotonicityNot monotonic
2024-04-21T00:19:36.547220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
619951 47
 
1.8%
619952 46
 
1.7%
601837 40
 
1.5%
601839 29
 
1.1%
601836 28
 
1.1%
614844 26
 
1.0%
619953 26
 
1.0%
601838 25
 
1.0%
614865 23
 
0.9%
607804 21
 
0.8%
Other values (595) 2286
86.9%
(Missing) 34
 
1.3%
ValueCountFrequency (%)
400410 1
 
< 0.1%
600012 4
0.2%
600013 1
 
< 0.1%
600014 2
 
0.1%
600015 4
0.2%
600016 6
0.2%
600021 3
0.1%
600022 2
 
0.1%
600024 1
 
< 0.1%
600044 1
 
< 0.1%
ValueCountFrequency (%)
619953 26
1.0%
619952 46
1.7%
619951 47
1.8%
619950 1
 
< 0.1%
619913 7
 
0.3%
619912 9
 
0.3%
619911 10
 
0.4%
619906 10
 
0.4%
619905 17
 
0.6%
619904 5
 
0.2%
Distinct2430
Distinct (%)92.9%
Missing14
Missing (%)0.5%
Memory size20.7 KiB
2024-04-21T00:19:38.029829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length45
Mean length25.38632
Min length2

Characters and Unicode

Total characters66436
Distinct characters405
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2271 ?
Unique (%)86.8%

Sample

1st row부산광역시 금정구 금사동 81-1 금사자동차운전전문학원
2nd row인천광역시 중구 덕교동 128-76번지
3rd row부산광역시 동구 수정동 425-18 1층
4th row부산광역시 수영구 광안동 100-10
5th row부산광역시 북구 덕천동 388-1번지 대방상가 304호
ValueCountFrequency (%)
부산광역시 2615
 
20.8%
부산진구 349
 
2.8%
동래구 298
 
2.4%
동구 237
 
1.9%
기장군 227
 
1.8%
해운대구 209
 
1.7%
연제구 202
 
1.6%
남구 161
 
1.3%
초량동 160
 
1.3%
금정구 151
 
1.2%
Other values (3171) 7969
63.4%
2024-04-21T00:19:39.624097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9964
 
15.0%
3229
 
4.9%
3228
 
4.9%
1 3206
 
4.8%
3180
 
4.8%
2716
 
4.1%
2643
 
4.0%
2624
 
3.9%
2477
 
3.7%
2475
 
3.7%
Other values (395) 30694
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39441
59.4%
Decimal Number 14027
 
21.1%
Space Separator 9964
 
15.0%
Dash Punctuation 2389
 
3.6%
Uppercase Letter 247
 
0.4%
Open Punctuation 142
 
0.2%
Close Punctuation 142
 
0.2%
Other Punctuation 70
 
0.1%
Lowercase Letter 13
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3229
 
8.2%
3228
 
8.2%
3180
 
8.1%
2716
 
6.9%
2643
 
6.7%
2624
 
6.7%
2477
 
6.3%
2475
 
6.3%
2354
 
6.0%
529
 
1.3%
Other values (348) 13986
35.5%
Uppercase Letter
ValueCountFrequency (%)
B 98
39.7%
T 76
30.8%
O 14
 
5.7%
D 9
 
3.6%
A 9
 
3.6%
S 9
 
3.6%
K 6
 
2.4%
I 6
 
2.4%
C 5
 
2.0%
P 4
 
1.6%
Other values (8) 11
 
4.5%
Decimal Number
ValueCountFrequency (%)
1 3206
22.9%
2 1936
13.8%
3 1597
11.4%
4 1323
9.4%
0 1248
 
8.9%
5 1181
 
8.4%
6 1007
 
7.2%
7 955
 
6.8%
8 865
 
6.2%
9 709
 
5.1%
Lowercase Letter
ValueCountFrequency (%)
e 2
15.4%
k 2
15.4%
s 2
15.4%
o 1
7.7%
t 1
7.7%
d 1
7.7%
y 1
7.7%
b 1
7.7%
u 1
7.7%
h 1
7.7%
Other Punctuation
ValueCountFrequency (%)
, 47
67.1%
/ 17
 
24.3%
. 3
 
4.3%
@ 3
 
4.3%
Space Separator
ValueCountFrequency (%)
9964
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2389
100.0%
Open Punctuation
ValueCountFrequency (%)
( 142
100.0%
Close Punctuation
ValueCountFrequency (%)
) 142
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39441
59.4%
Common 26735
40.2%
Latin 260
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3229
 
8.2%
3228
 
8.2%
3180
 
8.1%
2716
 
6.9%
2643
 
6.7%
2624
 
6.7%
2477
 
6.3%
2475
 
6.3%
2354
 
6.0%
529
 
1.3%
Other values (348) 13986
35.5%
Latin
ValueCountFrequency (%)
B 98
37.7%
T 76
29.2%
O 14
 
5.4%
D 9
 
3.5%
A 9
 
3.5%
S 9
 
3.5%
K 6
 
2.3%
I 6
 
2.3%
C 5
 
1.9%
P 4
 
1.5%
Other values (18) 24
 
9.2%
Common
ValueCountFrequency (%)
9964
37.3%
1 3206
 
12.0%
- 2389
 
8.9%
2 1936
 
7.2%
3 1597
 
6.0%
4 1323
 
4.9%
0 1248
 
4.7%
5 1181
 
4.4%
6 1007
 
3.8%
7 955
 
3.6%
Other values (9) 1929
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39441
59.4%
ASCII 26995
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9964
36.9%
1 3206
 
11.9%
- 2389
 
8.8%
2 1936
 
7.2%
3 1597
 
5.9%
4 1323
 
4.9%
0 1248
 
4.6%
5 1181
 
4.4%
6 1007
 
3.7%
7 955
 
3.5%
Other values (37) 2189
 
8.1%
Hangul
ValueCountFrequency (%)
3229
 
8.2%
3228
 
8.2%
3180
 
8.1%
2716
 
6.9%
2643
 
6.7%
2624
 
6.7%
2477
 
6.3%
2475
 
6.3%
2354
 
6.0%
529
 
1.3%
Other values (348) 13986
35.5%

도로명전체주소
Text

MISSING 

Distinct1772
Distinct (%)95.9%
Missing783
Missing (%)29.8%
Memory size20.7 KiB
2024-04-21T00:19:41.260616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length49
Mean length31.755952
Min length20

Characters and Unicode

Total characters58685
Distinct characters423
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1707 ?
Unique (%)92.4%

Sample

1st row부산광역시 금정구 공단서로8번길 49, 금사자동차운전전문학원 A동 307호 (금사동)
2nd row인천광역시 중구 마시란로 51-33 (덕교동)
3rd row부산광역시 동구 망양로 837, 1층 (수정동)
4th row부산광역시 수영구 무학로9번길 46, 1층 (광안동)
5th row부산광역시 북구 시랑로118번길 56 (구포동)
ValueCountFrequency (%)
부산광역시 1847
 
16.2%
부산진구 248
 
2.2%
1층 233
 
2.0%
2층 232
 
2.0%
동래구 207
 
1.8%
기장군 195
 
1.7%
해운대구 163
 
1.4%
연제구 148
 
1.3%
3층 134
 
1.2%
동구 130
 
1.1%
Other values (2444) 7843
68.9%
2024-04-21T00:19:43.429532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9534
 
16.2%
2393
 
4.1%
2323
 
4.0%
2303
 
3.9%
1 2256
 
3.8%
1955
 
3.3%
1932
 
3.3%
1855
 
3.2%
1751
 
3.0%
1740
 
3.0%
Other values (413) 30643
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33917
57.8%
Decimal Number 9697
 
16.5%
Space Separator 9534
 
16.2%
Close Punctuation 1729
 
2.9%
Open Punctuation 1729
 
2.9%
Other Punctuation 1636
 
2.8%
Dash Punctuation 314
 
0.5%
Uppercase Letter 115
 
0.2%
Lowercase Letter 11
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2393
 
7.1%
2323
 
6.8%
2303
 
6.8%
1955
 
5.8%
1932
 
5.7%
1855
 
5.5%
1751
 
5.2%
1740
 
5.1%
975
 
2.9%
923
 
2.7%
Other values (370) 15767
46.5%
Uppercase Letter
ValueCountFrequency (%)
B 36
31.3%
A 22
19.1%
C 11
 
9.6%
E 10
 
8.7%
P 8
 
7.0%
S 7
 
6.1%
O 4
 
3.5%
I 4
 
3.5%
T 4
 
3.5%
K 2
 
1.7%
Other values (6) 7
 
6.1%
Decimal Number
ValueCountFrequency (%)
1 2256
23.3%
2 1624
16.7%
3 1178
12.1%
0 890
 
9.2%
4 814
 
8.4%
5 715
 
7.4%
6 609
 
6.3%
7 563
 
5.8%
8 542
 
5.6%
9 506
 
5.2%
Lowercase Letter
ValueCountFrequency (%)
e 2
18.2%
s 2
18.2%
k 2
18.2%
u 1
9.1%
h 1
9.1%
b 1
9.1%
d 1
9.1%
y 1
9.1%
Other Punctuation
ValueCountFrequency (%)
, 1626
99.4%
/ 6
 
0.4%
@ 2
 
0.1%
. 2
 
0.1%
Space Separator
ValueCountFrequency (%)
9534
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1729
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1729
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 314
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33917
57.8%
Common 24642
42.0%
Latin 126
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2393
 
7.1%
2323
 
6.8%
2303
 
6.8%
1955
 
5.8%
1932
 
5.7%
1855
 
5.5%
1751
 
5.2%
1740
 
5.1%
975
 
2.9%
923
 
2.7%
Other values (370) 15767
46.5%
Latin
ValueCountFrequency (%)
B 36
28.6%
A 22
17.5%
C 11
 
8.7%
E 10
 
7.9%
P 8
 
6.3%
S 7
 
5.6%
O 4
 
3.2%
I 4
 
3.2%
T 4
 
3.2%
K 2
 
1.6%
Other values (14) 18
14.3%
Common
ValueCountFrequency (%)
9534
38.7%
1 2256
 
9.2%
) 1729
 
7.0%
( 1729
 
7.0%
, 1626
 
6.6%
2 1624
 
6.6%
3 1178
 
4.8%
0 890
 
3.6%
4 814
 
3.3%
5 715
 
2.9%
Other values (9) 2547
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33917
57.8%
ASCII 24768
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9534
38.5%
1 2256
 
9.1%
) 1729
 
7.0%
( 1729
 
7.0%
, 1626
 
6.6%
2 1624
 
6.6%
3 1178
 
4.8%
0 890
 
3.6%
4 814
 
3.3%
5 715
 
2.9%
Other values (33) 2673
 
10.8%
Hangul
ValueCountFrequency (%)
2393
 
7.1%
2323
 
6.8%
2303
 
6.8%
1955
 
5.8%
1932
 
5.7%
1855
 
5.5%
1751
 
5.2%
1740
 
5.1%
975
 
2.9%
923
 
2.7%
Other values (370) 15767
46.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct860
Distinct (%)47.7%
Missing827
Missing (%)31.4%
Infinite0
Infinite (%)0.0%
Mean47612.938
Minimum22385
Maximum49524
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.2 KiB
2024-04-21T00:19:43.949114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22385
5-th percentile46037
Q146965.75
median47709
Q348314
95-th percentile49260.85
Maximum49524
Range27139
Interquartile range (IQR)1348.25

Descriptive statistics

Standard deviation1139.1513
Coefficient of variation (CV)0.023925247
Kurtosis131.96033
Mean47612.938
Median Absolute Deviation (MAD)721
Skewness-6.0200949
Sum85893741
Variance1297665.7
MonotonicityNot monotonic
2024-04-21T00:19:44.227404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46036 30
 
1.1%
46037 23
 
0.9%
46033 19
 
0.7%
48729 18
 
0.7%
47247 14
 
0.5%
48060 14
 
0.5%
48093 14
 
0.5%
48059 14
 
0.5%
47243 12
 
0.5%
47246 11
 
0.4%
Other values (850) 1635
62.1%
(Missing) 827
31.4%
ValueCountFrequency (%)
22385 1
 
< 0.1%
46004 1
 
< 0.1%
46008 1
 
< 0.1%
46013 1
 
< 0.1%
46015 3
0.1%
46017 1
 
< 0.1%
46019 1
 
< 0.1%
46020 5
0.2%
46022 1
 
< 0.1%
46023 2
 
0.1%
ValueCountFrequency (%)
49524 2
0.1%
49522 1
 
< 0.1%
49514 1
 
< 0.1%
49511 3
0.1%
49504 4
0.2%
49502 1
 
< 0.1%
49497 1
 
< 0.1%
49495 1
 
< 0.1%
49490 1
 
< 0.1%
49483 1
 
< 0.1%
Distinct2238
Distinct (%)85.1%
Missing0
Missing (%)0.0%
Memory size20.7 KiB
2024-04-21T00:19:45.057700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length22
Mean length7.1980236
Min length2

Characters and Unicode

Total characters18938
Distinct characters540
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1929 ?
Unique (%)73.3%

Sample

1st row고클린
2nd row(주)성수인력
3rd row(주)남영산업
4th row청소협동조합 청소하는사람들 부산경남본점
5th row(주)천우이엔지
ValueCountFrequency (%)
주식회사 170
 
5.6%
16
 
0.5%
주)만비종합관리 7
 
0.2%
시스템 7
 
0.2%
주)만송 7
 
0.2%
주)금강종합개발 6
 
0.2%
유한회사 6
 
0.2%
청소나라 6
 
0.2%
그린산업 6
 
0.2%
환경 5
 
0.2%
Other values (2351) 2808
92.2%
2024-04-21T00:19:46.230959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1485
 
7.8%
) 1315
 
6.9%
( 1279
 
6.8%
562
 
3.0%
458
 
2.4%
416
 
2.2%
377
 
2.0%
331
 
1.7%
330
 
1.7%
321
 
1.7%
Other values (530) 12064
63.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15536
82.0%
Close Punctuation 1315
 
6.9%
Open Punctuation 1279
 
6.8%
Space Separator 416
 
2.2%
Uppercase Letter 244
 
1.3%
Lowercase Letter 54
 
0.3%
Decimal Number 39
 
0.2%
Other Punctuation 38
 
0.2%
Other Symbol 15
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1485
 
9.6%
562
 
3.6%
458
 
2.9%
377
 
2.4%
331
 
2.1%
330
 
2.1%
321
 
2.1%
307
 
2.0%
295
 
1.9%
247
 
1.6%
Other values (476) 10823
69.7%
Uppercase Letter
ValueCountFrequency (%)
C 41
16.8%
S 25
10.2%
E 22
9.0%
B 18
 
7.4%
G 17
 
7.0%
H 16
 
6.6%
M 16
 
6.6%
N 15
 
6.1%
T 13
 
5.3%
J 8
 
3.3%
Other values (10) 53
21.7%
Lowercase Letter
ValueCountFrequency (%)
e 13
24.1%
o 6
11.1%
s 5
 
9.3%
a 5
 
9.3%
r 4
 
7.4%
l 4
 
7.4%
n 4
 
7.4%
c 3
 
5.6%
t 3
 
5.6%
i 3
 
5.6%
Other values (4) 4
 
7.4%
Decimal Number
ValueCountFrequency (%)
1 16
41.0%
2 8
20.5%
4 3
 
7.7%
0 3
 
7.7%
9 3
 
7.7%
6 2
 
5.1%
8 2
 
5.1%
5 1
 
2.6%
3 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
& 16
42.1%
. 11
28.9%
, 5
 
13.2%
· 4
 
10.5%
2
 
5.3%
Other Symbol
ValueCountFrequency (%)
14
93.3%
1
 
6.7%
Close Punctuation
ValueCountFrequency (%)
) 1315
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1279
100.0%
Space Separator
ValueCountFrequency (%)
416
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15551
82.1%
Common 3089
 
16.3%
Latin 298
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1485
 
9.5%
562
 
3.6%
458
 
2.9%
377
 
2.4%
331
 
2.1%
330
 
2.1%
321
 
2.1%
307
 
2.0%
295
 
1.9%
247
 
1.6%
Other values (478) 10838
69.7%
Latin
ValueCountFrequency (%)
C 41
13.8%
S 25
 
8.4%
E 22
 
7.4%
B 18
 
6.0%
G 17
 
5.7%
H 16
 
5.4%
M 16
 
5.4%
N 15
 
5.0%
e 13
 
4.4%
T 13
 
4.4%
Other values (24) 102
34.2%
Common
ValueCountFrequency (%)
) 1315
42.6%
( 1279
41.4%
416
 
13.5%
& 16
 
0.5%
1 16
 
0.5%
. 11
 
0.4%
2 8
 
0.3%
, 5
 
0.2%
· 4
 
0.1%
4 3
 
0.1%
Other values (8) 16
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15536
82.0%
ASCII 3381
 
17.9%
None 21
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1485
 
9.6%
562
 
3.6%
458
 
2.9%
377
 
2.4%
331
 
2.1%
330
 
2.1%
321
 
2.1%
307
 
2.0%
295
 
1.9%
247
 
1.6%
Other values (476) 10823
69.7%
ASCII
ValueCountFrequency (%)
) 1315
38.9%
( 1279
37.8%
416
 
12.3%
C 41
 
1.2%
S 25
 
0.7%
E 22
 
0.7%
B 18
 
0.5%
G 17
 
0.5%
H 16
 
0.5%
& 16
 
0.5%
Other values (40) 216
 
6.4%
None
ValueCountFrequency (%)
14
66.7%
· 4
 
19.0%
2
 
9.5%
1
 
4.8%

최종수정시점
Real number (ℝ)

Distinct2376
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0131326 × 1013
Minimum1.9990201 × 1013
Maximum2.0210331 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.2 KiB
2024-04-21T00:19:46.621668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990201 × 1013
5-th percentile2.0030216 × 1013
Q12.0080804 × 1013
median2.0140828 × 1013
Q32.0190116 × 1013
95-th percentile2.0201202 × 1013
Maximum2.0210331 × 1013
Range2.2013015 × 1011
Interquartile range (IQR)1.0931199 × 1011

Descriptive statistics

Standard deviation6.1411504 × 1010
Coefficient of variation (CV)0.0030505444
Kurtosis-0.94412859
Mean2.0131326 × 1013
Median Absolute Deviation (MAD)4.9587947 × 1010
Skewness-0.54116451
Sum5.2965519 × 1016
Variance3.7713728 × 1021
MonotonicityNot monotonic
2024-04-21T00:19:47.091824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20060616000000 19
 
0.7%
20020419000000 16
 
0.6%
20050920000000 12
 
0.5%
19990201000000 11
 
0.4%
20030403000000 11
 
0.4%
20021112000000 10
 
0.4%
20051110000000 10
 
0.4%
20030404000000 10
 
0.4%
20030521000000 8
 
0.3%
20030227000000 8
 
0.3%
Other values (2366) 2516
95.6%
ValueCountFrequency (%)
19990201000000 11
0.4%
19990310000000 4
 
0.2%
19990316000000 1
 
< 0.1%
19990318000000 5
0.2%
19990330000000 6
0.2%
19990407000000 1
 
< 0.1%
19990426000000 1
 
< 0.1%
19990427000000 2
 
0.1%
19990428000000 4
 
0.2%
19990506000000 1
 
< 0.1%
ValueCountFrequency (%)
20210331154004 1
< 0.1%
20210326160703 1
< 0.1%
20210326160556 1
< 0.1%
20210326155352 1
< 0.1%
20210326103306 1
< 0.1%
20210325135858 1
< 0.1%
20210325114551 1
< 0.1%
20210325111348 1
< 0.1%
20210324172805 1
< 0.1%
20210324151002 1
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.7 KiB
I
2018 
U
613 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 2018
76.7%
U 613
 
23.3%

Length

2024-04-21T00:19:47.514912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:19:47.832253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2018
76.7%
u 613
 
23.3%
Distinct486
Distinct (%)18.5%
Missing0
Missing (%)0.0%
Memory size20.7 KiB
Minimum2018-08-31 23:59:59
Maximum2021-04-02 02:40:00
2024-04-21T00:19:48.107469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T00:19:48.476757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.7 KiB
건물위생관리업
2601 
건물위생관리업 기타
 
22
<NA>
 
8

Length

Max length10
Median length7
Mean length7.0159635
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 2601
98.9%
건물위생관리업 기타 22
 
0.8%
<NA> 8
 
0.3%

Length

2024-04-21T00:19:48.917145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:19:49.131688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 2623
98.9%
기타 22
 
0.8%
na 8
 
0.3%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct1962
Distinct (%)76.6%
Missing70
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean389108.26
Minimum148671.32
Maximum408081.98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.2 KiB
2024-04-21T00:19:49.487769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum148671.32
5-th percentile380053.98
Q1385769.57
median388630.28
Q3391501.66
95-th percentile403703.43
Maximum408081.98
Range259410.66
Interquartile range (IQR)5732.0854

Descriptive statistics

Standard deviation8006.962
Coefficient of variation (CV)0.020577723
Kurtosis317.23948
Mean389108.26
Median Absolute Deviation (MAD)2860.9895
Skewness-10.200976
Sum9.9650625 × 108
Variance64111441
MonotonicityNot monotonic
2024-04-21T00:19:49.929288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
395615.201853958 13
 
0.5%
380482.767624189 10
 
0.4%
387927.951172724 10
 
0.4%
388310.086924943 9
 
0.3%
391411.212179843 9
 
0.3%
396180.621244719 9
 
0.3%
386351.941329364 8
 
0.3%
407871.508884898 8
 
0.3%
387225.613588405 8
 
0.3%
387869.134317928 8
 
0.3%
Other values (1952) 2469
93.8%
(Missing) 70
 
2.7%
ValueCountFrequency (%)
148671.318965183 1
< 0.1%
366944.611251751 1
< 0.1%
367503.770498841 1
< 0.1%
367753.838455399 2
0.1%
367897.480797822 1
< 0.1%
367948.46831947 1
< 0.1%
368089.614964646 1
< 0.1%
369071.601644319 1
< 0.1%
369169.330139889 1
< 0.1%
371070.269343027 1
< 0.1%
ValueCountFrequency (%)
408081.981681661 1
 
< 0.1%
407919.897384557 1
 
< 0.1%
407871.508884898 8
0.3%
407829.802820519 1
 
< 0.1%
407817.876851927 1
 
< 0.1%
407739.046710947 3
 
0.1%
407709.645454165 1
 
< 0.1%
407703.086321502 3
 
0.1%
407689.600129737 1
 
< 0.1%
407663.199754951 1
 
< 0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct1962
Distinct (%)76.6%
Missing70
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean188413.89
Minimum174156.62
Maximum436093.42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.2 KiB
2024-04-21T00:19:50.260743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174156.62
5-th percentile179713.92
Q1184018.93
median187551.77
Q3191384.92
95-th percentile203500.98
Maximum436093.42
Range261936.8
Interquartile range (IQR)7365.989

Descriptive statistics

Standard deviation8071.2336
Coefficient of variation (CV)0.042837785
Kurtosis345.73488
Mean188413.89
Median Absolute Deviation (MAD)3699.6506
Skewness11.70407
Sum4.8252797 × 108
Variance65144812
MonotonicityNot monotonic
2024-04-21T00:19:50.682993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
186406.750870936 13
 
0.5%
185582.274947583 10
 
0.4%
186582.791097672 10
 
0.4%
183883.854898063 9
 
0.3%
184052.409245407 9
 
0.3%
186522.35047527 9
 
0.3%
182468.78681462 8
 
0.3%
205389.277197702 8
 
0.3%
186408.726533861 8
 
0.3%
186381.28184674 8
 
0.3%
Other values (1952) 2469
93.8%
(Missing) 70
 
2.7%
ValueCountFrequency (%)
174156.617297535 1
 
< 0.1%
174213.492106852 3
0.1%
174368.201258807 1
 
< 0.1%
174569.500346208 1
 
< 0.1%
174587.185782495 1
 
< 0.1%
174665.706660618 1
 
< 0.1%
174676.412428464 1
 
< 0.1%
174685.736751117 1
 
< 0.1%
174835.290190736 1
 
< 0.1%
175120.936107909 1
 
< 0.1%
ValueCountFrequency (%)
436093.419886508 1
< 0.1%
211676.684692594 1
< 0.1%
210934.754379078 1
< 0.1%
210528.52313338 1
< 0.1%
210316.862590787 1
< 0.1%
210315.278301031 1
< 0.1%
210312.176730581 1
< 0.1%
207754.636746297 1
< 0.1%
207714.152838506 1
< 0.1%
207360.485553669 1
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.7 KiB
건물위생관리업
2601 
건물위생관리업 기타
 
22
<NA>
 
8

Length

Max length10
Median length7
Mean length7.0159635
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 2601
98.9%
건물위생관리업 기타 22
 
0.8%
<NA> 8
 
0.3%

Length

2024-04-21T00:19:51.107400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:19:51.434673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 2623
98.9%
기타 22
 
0.8%
na 8
 
0.3%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct31
Distinct (%)1.4%
Missing435
Missing (%)16.5%
Infinite0
Infinite (%)0.0%
Mean3.753643
Minimum0
Maximum51
Zeros630
Zeros (%)23.9%
Negative0
Negative (%)0.0%
Memory size23.2 KiB
2024-04-21T00:19:51.616963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q35
95-th percentile14
Maximum51
Range51
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.6595101
Coefficient of variation (CV)1.2413301
Kurtosis15.970981
Mean3.753643
Median Absolute Deviation (MAD)2
Skewness3.0466376
Sum8243
Variance21.711035
MonotonicityNot monotonic
2024-04-21T00:19:51.991101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 630
23.9%
4 350
13.3%
3 251
 
9.5%
2 234
 
8.9%
5 233
 
8.9%
1 111
 
4.2%
6 90
 
3.4%
7 51
 
1.9%
10 41
 
1.6%
8 35
 
1.3%
Other values (21) 170
 
6.5%
(Missing) 435
16.5%
ValueCountFrequency (%)
0 630
23.9%
1 111
 
4.2%
2 234
 
8.9%
3 251
 
9.5%
4 350
13.3%
5 233
 
8.9%
6 90
 
3.4%
7 51
 
1.9%
8 35
 
1.3%
9 25
 
1.0%
ValueCountFrequency (%)
51 1
 
< 0.1%
49 1
 
< 0.1%
44 1
 
< 0.1%
32 1
 
< 0.1%
28 3
0.1%
27 2
0.1%
25 4
0.2%
24 3
0.1%
22 4
0.2%
21 4
0.2%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.4%
Missing593
Missing (%)22.5%
Infinite0
Infinite (%)0.0%
Mean0.60991168
Minimum0
Maximum8
Zeros1165
Zeros (%)44.3%
Negative0
Negative (%)0.0%
Memory size23.2 KiB
2024-04-21T00:19:52.316003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum8
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.96040405
Coefficient of variation (CV)1.5746609
Kurtosis9.5576368
Mean0.60991168
Median Absolute Deviation (MAD)0
Skewness2.6464344
Sum1243
Variance0.92237594
MonotonicityNot monotonic
2024-04-21T00:19:52.516499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 1165
44.3%
1 686
26.1%
2 95
 
3.6%
3 41
 
1.6%
5 22
 
0.8%
4 21
 
0.8%
6 7
 
0.3%
8 1
 
< 0.1%
(Missing) 593
22.5%
ValueCountFrequency (%)
0 1165
44.3%
1 686
26.1%
2 95
 
3.6%
3 41
 
1.6%
4 21
 
0.8%
5 22
 
0.8%
6 7
 
0.3%
8 1
 
< 0.1%
ValueCountFrequency (%)
8 1
 
< 0.1%
6 7
 
0.3%
5 22
 
0.8%
4 21
 
0.8%
3 41
 
1.6%
2 95
 
3.6%
1 686
26.1%
0 1165
44.3%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct26
Distinct (%)1.3%
Missing688
Missing (%)26.1%
Infinite0
Infinite (%)0.0%
Mean2.6649511
Minimum0
Maximum48
Zeros355
Zeros (%)13.5%
Negative0
Negative (%)0.0%
Memory size23.2 KiB
2024-04-21T00:19:52.974725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile9
Maximum48
Range48
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.3128097
Coefficient of variation (CV)1.2431034
Kurtosis28.058004
Mean2.6649511
Median Absolute Deviation (MAD)1
Skewness3.9297527
Sum5178
Variance10.974708
MonotonicityNot monotonic
2024-04-21T00:19:53.188999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
2 458
17.4%
1 427
16.2%
0 355
13.5%
3 285
10.8%
4 148
 
5.6%
5 71
 
2.7%
6 45
 
1.7%
7 35
 
1.3%
9 19
 
0.7%
8 19
 
0.7%
Other values (16) 81
 
3.1%
(Missing) 688
26.1%
ValueCountFrequency (%)
0 355
13.5%
1 427
16.2%
2 458
17.4%
3 285
10.8%
4 148
 
5.6%
5 71
 
2.7%
6 45
 
1.7%
7 35
 
1.3%
8 19
 
0.7%
9 19
 
0.7%
ValueCountFrequency (%)
48 1
 
< 0.1%
26 2
 
0.1%
24 2
 
0.1%
23 2
 
0.1%
22 1
 
< 0.1%
21 1
 
< 0.1%
20 4
0.2%
18 1
 
< 0.1%
17 3
0.1%
16 6
0.2%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct25
Distinct (%)1.5%
Missing950
Missing (%)36.1%
Infinite0
Infinite (%)0.0%
Mean2.5342058
Minimum0
Maximum48
Zeros349
Zeros (%)13.3%
Negative0
Negative (%)0.0%
Memory size23.2 KiB
2024-04-21T00:19:53.398244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile8
Maximum48
Range48
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.2774739
Coefficient of variation (CV)1.2932943
Kurtosis31.666903
Mean2.5342058
Median Absolute Deviation (MAD)1
Skewness4.1529396
Sum4260
Variance10.741835
MonotonicityNot monotonic
2024-04-21T00:19:53.617920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
2 384
14.6%
1 372
 
14.1%
0 349
 
13.3%
3 237
 
9.0%
4 128
 
4.9%
5 50
 
1.9%
6 42
 
1.6%
7 29
 
1.1%
8 12
 
0.5%
10 11
 
0.4%
Other values (15) 67
 
2.5%
(Missing) 950
36.1%
ValueCountFrequency (%)
0 349
13.3%
1 372
14.1%
2 384
14.6%
3 237
9.0%
4 128
 
4.9%
5 50
 
1.9%
6 42
 
1.6%
7 29
 
1.1%
8 12
 
0.5%
9 10
 
0.4%
ValueCountFrequency (%)
48 1
 
< 0.1%
26 1
 
< 0.1%
24 2
 
0.1%
23 1
 
< 0.1%
21 1
 
< 0.1%
20 5
0.2%
18 1
 
< 0.1%
17 3
0.1%
16 5
0.2%
15 6
0.2%

사용시작지하층
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.5%
Missing1409
Missing (%)53.6%
Infinite0
Infinite (%)0.0%
Mean0.15466448
Minimum0
Maximum5
Zeros1048
Zeros (%)39.8%
Negative0
Negative (%)0.0%
Memory size23.2 KiB
2024-04-21T00:19:53.943345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.42037425
Coefficient of variation (CV)2.7179753
Kurtosis27.95205
Mean0.15466448
Median Absolute Deviation (MAD)0
Skewness4.0457584
Sum189
Variance0.17671451
MonotonicityNot monotonic
2024-04-21T00:19:54.153743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 1048
39.8%
1 167
 
6.3%
2 3
 
0.1%
4 2
 
0.1%
5 1
 
< 0.1%
3 1
 
< 0.1%
(Missing) 1409
53.6%
ValueCountFrequency (%)
0 1048
39.8%
1 167
 
6.3%
2 3
 
0.1%
3 1
 
< 0.1%
4 2
 
0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
5 1
 
< 0.1%
4 2
 
0.1%
3 1
 
< 0.1%
2 3
 
0.1%
1 167
 
6.3%
0 1048
39.8%

사용끝지하층
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.7%
Missing1585
Missing (%)60.2%
Infinite0
Infinite (%)0.0%
Mean0.1749522
Minimum0
Maximum10
Zeros888
Zeros (%)33.8%
Negative0
Negative (%)0.0%
Memory size23.2 KiB
2024-04-21T00:19:54.337031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.53130133
Coefficient of variation (CV)3.0368371
Kurtosis121.72245
Mean0.1749522
Median Absolute Deviation (MAD)0
Skewness8.122549
Sum183
Variance0.2822811
MonotonicityNot monotonic
2024-04-21T00:19:54.524917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 888
33.8%
1 148
 
5.6%
2 5
 
0.2%
3 2
 
0.1%
5 1
 
< 0.1%
4 1
 
< 0.1%
10 1
 
< 0.1%
(Missing) 1585
60.2%
ValueCountFrequency (%)
0 888
33.8%
1 148
 
5.6%
2 5
 
0.2%
3 2
 
0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
10 1
 
< 0.1%
5 1
 
< 0.1%
4 1
 
< 0.1%
3 2
 
0.1%
2 5
 
0.2%
1 148
 
5.6%
0 888
33.8%

한실수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.7 KiB
0
1746 
<NA>
884 
1
 
1

Length

Max length4
Median length1
Mean length2.0079818
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1746
66.4%
<NA> 884
33.6%
1 1
 
< 0.1%

Length

2024-04-21T00:19:54.746906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:19:54.954374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1746
66.4%
na 884
33.6%
1 1
 
< 0.1%

양실수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.7 KiB
0
1746 
<NA>
884 
29
 
1

Length

Max length4
Median length1
Mean length2.0083618
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1746
66.4%
<NA> 884
33.6%
29 1
 
< 0.1%

Length

2024-04-21T00:19:55.159493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:19:55.347014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1746
66.4%
na 884
33.6%
29 1
 
< 0.1%

욕실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.7 KiB
0
1747 
<NA>
884 

Length

Max length4
Median length1
Mean length2.0079818
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1747
66.4%
<NA> 884
33.6%

Length

2024-04-21T00:19:55.547518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:19:55.739130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1747
66.4%
na 884
33.6%

발한실여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing72
Missing (%)2.7%
Memory size5.3 KiB
False
2558 
True
 
1
(Missing)
 
72
ValueCountFrequency (%)
False 2558
97.2%
True 1
 
< 0.1%
(Missing) 72
 
2.7%
2024-04-21T00:19:55.897608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

의자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size20.7 KiB
0
1746 
<NA>
882 
9
 
2
1
 
1

Length

Max length4
Median length1
Mean length2.0057013
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1746
66.4%
<NA> 882
33.5%
9 2
 
0.1%
1 1
 
< 0.1%

Length

2024-04-21T00:19:56.096030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:19:56.283362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1746
66.4%
na 882
33.5%
9 2
 
0.1%
1 1
 
< 0.1%
Distinct4
Distinct (%)80.0%
Missing2626
Missing (%)99.8%
Memory size20.7 KiB
2024-04-21T00:19:56.901379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length25
Mean length18.8
Min length5

Characters and Unicode

Total characters94
Distinct characters49
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

Unique3 ?
Unique (%)60.0%

Sample

1st row계약기간연장
2nd row가설건축물
3rd row공중위생관리법시행령 제3조제1호의 규정에 의한 건축물규모 이하의 건축물을 청소하는 경우에 한함
4th row계약기간연장
5th row2003 가설허가 제2호(2003.03.08)
ValueCountFrequency (%)
계약기간연장 2
 
12.5%
가설건축물 1
 
6.2%
공중위생관리법시행령 1
 
6.2%
제3조제1호의 1
 
6.2%
규정에 1
 
6.2%
의한 1
 
6.2%
건축물규모 1
 
6.2%
이하의 1
 
6.2%
건축물을 1
 
6.2%
청소하는 1
 
6.2%
Other values (5) 5
31.2%
2024-04-21T00:19:57.770448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11
 
11.7%
0 6
 
6.4%
3 4
 
4.3%
2 3
 
3.2%
3
 
3.2%
3
 
3.2%
3
 
3.2%
3
 
3.2%
3
 
3.2%
3
 
3.2%
Other values (39) 52
55.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 64
68.1%
Decimal Number 15
 
16.0%
Space Separator 11
 
11.7%
Other Punctuation 2
 
2.1%
Open Punctuation 1
 
1.1%
Close Punctuation 1
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3
 
4.7%
3
 
4.7%
3
 
4.7%
3
 
4.7%
3
 
4.7%
3
 
4.7%
2
 
3.1%
2
 
3.1%
2
 
3.1%
2
 
3.1%
Other values (30) 38
59.4%
Decimal Number
ValueCountFrequency (%)
0 6
40.0%
3 4
26.7%
2 3
20.0%
8 1
 
6.7%
1 1
 
6.7%
Space Separator
ValueCountFrequency (%)
11
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 64
68.1%
Common 30
31.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3
 
4.7%
3
 
4.7%
3
 
4.7%
3
 
4.7%
3
 
4.7%
3
 
4.7%
2
 
3.1%
2
 
3.1%
2
 
3.1%
2
 
3.1%
Other values (30) 38
59.4%
Common
ValueCountFrequency (%)
11
36.7%
0 6
20.0%
3 4
 
13.3%
2 3
 
10.0%
. 2
 
6.7%
( 1
 
3.3%
8 1
 
3.3%
1 1
 
3.3%
) 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 64
68.1%
ASCII 30
31.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11
36.7%
0 6
20.0%
3 4
 
13.3%
2 3
 
10.0%
. 2
 
6.7%
( 1
 
3.3%
8 1
 
3.3%
1 1
 
3.3%
) 1
 
3.3%
Hangul
ValueCountFrequency (%)
3
 
4.7%
3
 
4.7%
3
 
4.7%
3
 
4.7%
3
 
4.7%
3
 
4.7%
2
 
3.1%
2
 
3.1%
2
 
3.1%
2
 
3.1%
Other values (30) 38
59.4%

조건부허가시작일자
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size20.7 KiB
<NA>
2625 
20140301
 
2
20140212
 
1
20060825
 
1
20060106
 
1

Length

Max length8
Median length4
Mean length4.009122
Min length4

Unique

Unique4 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2625
99.8%
20140301 2
 
0.1%
20140212 1
 
< 0.1%
20060825 1
 
< 0.1%
20060106 1
 
< 0.1%
20100210 1
 
< 0.1%

Length

2024-04-21T00:19:58.245494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:19:58.619765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2625
99.8%
20140301 2
 
0.1%
20140212 1
 
< 0.1%
20060825 1
 
< 0.1%
20060106 1
 
< 0.1%
20100210 1
 
< 0.1%

조건부허가종료일자
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)85.7%
Missing2624
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean20126313
Minimum20061231
Maximum20200415
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.2 KiB
2024-04-21T00:19:58.963337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20061231
5-th percentile20067109
Q120100477
median20140430
Q320140580
95-th percentile20182510
Maximum20200415
Range139184
Interquartile range (IQR)40103

Descriptive statistics

Standard deviation45535.116
Coefficient of variation (CV)0.0022624669
Kurtosis0.29865416
Mean20126313
Median Absolute Deviation (MAD)20300
Skewness0.1124485
Sum1.4088419 × 108
Variance2.0734468 × 109
MonotonicityNot monotonic
2024-04-21T00:19:59.360564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
20140430 2
 
0.1%
20140730 1
 
< 0.1%
20080824 1
 
< 0.1%
20200415 1
 
< 0.1%
20061231 1
 
< 0.1%
20120130 1
 
< 0.1%
(Missing) 2624
99.7%
ValueCountFrequency (%)
20061231 1
< 0.1%
20080824 1
< 0.1%
20120130 1
< 0.1%
20140430 2
0.1%
20140730 1
< 0.1%
20200415 1
< 0.1%
ValueCountFrequency (%)
20200415 1
< 0.1%
20140730 1
< 0.1%
20140430 2
0.1%
20120130 1
< 0.1%
20080824 1
< 0.1%
20061231 1
< 0.1%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.7 KiB
<NA>
1748 
임대
841 
자가
 
42

Length

Max length4
Median length4
Mean length3.3287723
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1748
66.4%
임대 841
32.0%
자가 42
 
1.6%

Length

2024-04-21T00:19:59.863823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:20:00.187255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1748
66.4%
임대 841
32.0%
자가 42
 
1.6%

세탁기수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.7 KiB
0
1571 
<NA>
1060 

Length

Max length4
Median length1
Mean length2.2086659
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1571
59.7%
<NA> 1060
40.3%

Length

2024-04-21T00:20:00.560073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:20:00.884067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1571
59.7%
na 1060
40.3%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct19
Distinct (%)3.7%
Missing2123
Missing (%)80.7%
Infinite0
Infinite (%)0.0%
Mean2.2145669
Minimum0
Maximum340
Zeros446
Zeros (%)17.0%
Negative0
Negative (%)0.0%
Memory size23.2 KiB
2024-04-21T00:20:01.180111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum340
Range340
Interquartile range (IQR)0

Descriptive statistics

Standard deviation18.023194
Coefficient of variation (CV)8.1384734
Kurtosis250.77141
Mean2.2145669
Median Absolute Deviation (MAD)0
Skewness14.486291
Sum1125
Variance324.83553
MonotonicityNot monotonic
2024-04-21T00:20:01.530490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 446
 
17.0%
1 22
 
0.8%
2 11
 
0.4%
95 4
 
0.2%
5 4
 
0.2%
3 4
 
0.2%
20 2
 
0.1%
10 2
 
0.1%
8 2
 
0.1%
9 2
 
0.1%
Other values (9) 9
 
0.3%
(Missing) 2123
80.7%
ValueCountFrequency (%)
0 446
17.0%
1 22
 
0.8%
2 11
 
0.4%
3 4
 
0.2%
4 1
 
< 0.1%
5 4
 
0.2%
7 1
 
< 0.1%
8 2
 
0.1%
9 2
 
0.1%
10 2
 
0.1%
ValueCountFrequency (%)
340 1
 
< 0.1%
102 1
 
< 0.1%
95 4
0.2%
40 1
 
< 0.1%
30 1
 
< 0.1%
26 1
 
< 0.1%
20 2
0.1%
15 1
 
< 0.1%
11 1
 
< 0.1%
10 2
0.1%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct27
Distinct (%)4.9%
Missing2078
Missing (%)79.0%
Infinite0
Infinite (%)0.0%
Mean4.4068716
Minimum0
Maximum560
Zeros376
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size23.2 KiB
2024-04-21T00:20:01.891546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile8
Maximum560
Range560
Interquartile range (IQR)1

Descriptive statistics

Standard deviation29.64144
Coefficient of variation (CV)6.7261864
Kurtosis233.35969
Mean4.4068716
Median Absolute Deviation (MAD)0
Skewness13.786773
Sum2437
Variance878.61495
MonotonicityNot monotonic
2024-04-21T00:20:02.229666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 376
 
14.3%
2 45
 
1.7%
1 42
 
1.6%
3 25
 
1.0%
4 17
 
0.6%
5 15
 
0.6%
8 7
 
0.3%
183 4
 
0.2%
30 2
 
0.1%
7 2
 
0.1%
Other values (17) 18
 
0.7%
(Missing) 2078
79.0%
ValueCountFrequency (%)
0 376
14.3%
1 42
 
1.6%
2 45
 
1.7%
3 25
 
1.0%
4 17
 
0.6%
5 15
 
0.6%
6 2
 
0.1%
7 2
 
0.1%
8 7
 
0.3%
9 1
 
< 0.1%
ValueCountFrequency (%)
560 1
 
< 0.1%
183 4
0.2%
101 1
 
< 0.1%
100 1
 
< 0.1%
97 1
 
< 0.1%
76 1
 
< 0.1%
51 1
 
< 0.1%
48 1
 
< 0.1%
36 1
 
< 0.1%
34 1
 
< 0.1%

회수건조수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.7 KiB
0
1431 
<NA>
1200 

Length

Max length4
Median length1
Mean length2.368301
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1431
54.4%
<NA> 1200
45.6%

Length

2024-04-21T00:20:02.478876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:20:02.663709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1431
54.4%
na 1200
45.6%

침대수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.7 KiB
0
1370 
<NA>
1261 

Length

Max length4
Median length1
Mean length2.4378563
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1370
52.1%
<NA> 1261
47.9%

Length

2024-04-21T00:20:02.874670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:20:03.052486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1370
52.1%
na 1261
47.9%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
False
2630 
True
 
1
ValueCountFrequency (%)
False 2630
> 99.9%
True 1
 
< 0.1%
2024-04-21T00:20:03.203228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Unnamed: 50
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2631
Missing (%)100.0%
Memory size23.2 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부Unnamed: 50
01건물위생관리업09_30_04_P33500003350000-206-2021-0000120210104<NA>3폐업2폐업20210112<NA><NA><NA><NA>.00609809부산광역시 금정구 금사동 81-1 금사자동차운전전문학원부산광역시 금정구 공단서로8번길 49, 금사자동차운전전문학원 A동 307호 (금사동)46332고클린20210112173128U2021-01-14 02:40:00.0건물위생관리업392346.245721192844.636332건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
12건물위생관리업09_30_04_P32600003260000-206-2011-0000320111219<NA>3폐업2폐업20181114<NA><NA><NA>02 4647058.00400410인천광역시 중구 덕교동 128-76번지인천광역시 중구 마시란로 51-33 (덕교동)22385(주)성수인력20181114111110I2018-11-16 02:37:41.0건물위생관리업148671.318965436093.419887건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
23건물위생관리업09_30_04_P32700003270000-206-2014-0001420140327<NA>3폐업2폐업20210225<NA><NA><NA>051 503 247046.20601815부산광역시 동구 수정동 425-18 1층부산광역시 동구 망양로 837, 1층 (수정동)48705(주)남영산업20210225124248U2021-02-27 02:40:00.0건물위생관리업386389.025083183804.135721건물위생관리업717700000N0<NA><NA><NA>임대0<NA><NA>00N<NA>
34건물위생관리업09_30_04_P33800003380000-206-2019-0000120190103<NA>3폐업2폐업20201008<NA><NA><NA><NA>33.60613801부산광역시 수영구 광안동 100-10부산광역시 수영구 무학로9번길 46, 1층 (광안동)48269청소협동조합 청소하는사람들 부산경남본점20201008134352U2020-10-10 02:40:00.0건물위생관리업392665.857369186997.207472건물위생관리업201100000N0<NA><NA><NA><NA>00000N<NA>
45건물위생관리업09_30_04_P33200003320000-206-2005-0000220051103<NA>3폐업2폐업20060918<NA><NA><NA>051 341008691.30616819부산광역시 북구 덕천동 388-1번지 대방상가 304호<NA><NA>(주)천우이엔지20060629000000I2018-08-31 23:59:59.0건물위생관리업383443.264424192181.296405건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N<NA>
56건물위생관리업09_30_04_P33200003320000-206-2013-0000220130904<NA>3폐업2폐업20171116<NA><NA><NA>051 342 837746.29616809부산광역시 북구 구포동 1256-15번지부산광역시 북구 시랑로118번길 56 (구포동)46643신흥20171124142705I2018-08-31 23:59:59.0건물위생관리업382931.486707190108.209442건물위생관리업310011000N0<NA><NA><NA>자가0<NA><NA>00N<NA>
67건물위생관리업09_30_04_P33200003320000-206-2011-0000820110726<NA>3폐업2폐업20161129<NA><NA><NA>051 467 831313.80616815부산광역시 북구 덕천동 128-3번지 벽산아파트 상가동 101호부산광역시 북구 만덕3로16번길 45, 상가동 101호 (덕천동, 벽산아파트)46572신항엘엠에스(주)20130902145708I2018-08-31 23:59:59.0건물위생관리업384149.846541192152.635373건물위생관리업601100000N0<NA><NA><NA>임대0<NA><NA>00N<NA>
78건물위생관리업09_30_04_P33200003320000-206-2013-0000120130530<NA>3폐업2폐업20151104<NA><NA><NA>051 343 011028.05616827부산광역시 북구 만덕동 835-7번지부산광역시 북구 덕천로276번길 28 (만덕동)46611좋은크린용역20130530103430I2018-08-31 23:59:59.0건물위생관리업385138.67522191793.713154건물위생관리업2111<NA><NA>000N0<NA><NA><NA>임대0<NA><NA>00N<NA>
89건물위생관리업09_30_04_P33200003320000-206-2012-0000420120525<NA>3폐업2폐업20141006<NA><NA><NA>051 342 211232.18616820부산광역시 북구 덕천동 417-28번지부산광역시 북구 만덕대로40번길 33 (덕천동)46578(주)대한안전공사20130418094931I2018-08-31 23:59:59.0건물위생관리업382968.706137191893.259359건물위생관리업000011000N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
910건물위생관리업09_30_04_P33200003320000-206-2012-0000520120601<NA>3폐업2폐업20150324<NA><NA><NA>070 76450552<NA>616801부산광역시 북구 구포동 1060-313번지부산광역시 북구 구포만세길 28-1, 1층 (구포동)46502킹스환경개발20120618100433I2018-08-31 23:59:59.0건물위생관리업381624.584142191221.308437건물위생관리업101100000N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부Unnamed: 50
26212622건물위생관리업09_30_04_P32600003260000-206-2010-0000220100511<NA>1영업/정상1영업<NA><NA><NA><NA>051 257 0421102.86602091부산광역시 서구 서대신동1가 50-7번지부산광역시 서구 부용로 15-1 (서대신동1가)49235주)영인종합관리20111223172430I2018-08-31 23:59:59.0건물위생관리업 기타383858.366929180676.741592건물위생관리업 기타412<NA><NA><NA>000N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
26222623건물위생관리업09_30_04_P32600003260000-206-2010-0000120100113<NA>1영업/정상1영업<NA><NA><NA><NA>051 256 0089176.33602826부산광역시 서구 서대신동3가 448번지부산광역시 서구 구덕로327번길 61 (서대신동3가)49225주식회사 에이스20111223171637I2018-08-31 23:59:59.0건물위생관리업383476.002945181039.869631건물위생관리업4<NA>2<NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N<NA>
26232624건물위생관리업09_30_04_P32600003260000-206-2015-0000220151006<NA>1영업/정상1영업<NA><NA><NA><NA>051 231 098066.00602819부산광역시 서구 서대신동2가 253-4번지부산광역시 서구 구덕로305번길 56-2 (서대신동2가)49227주식회사 블루환경20180713150419I2018-08-31 23:59:59.0건물위생관리업383581.224313180885.702122건물위생관리업401<NA><NA><NA>000N0<NA><NA><NA><NA>00000N<NA>
26242625건물위생관리업09_30_04_P33600003360000-206-2017-0000520170607<NA>1영업/정상1영업<NA><NA><NA><NA>051 305 272715.20618200부산광역시 강서구 명지동 3440-5번지부산광역시 강서구 명지국제8로 290, 디엔씨빌딩 4층 403호 (명지동)46726(주)부성디엠씨20180614154426I2018-08-31 23:59:59.0건물위생관리업375397.641234179270.21797건물위생관리업301000000N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
26252626건물위생관리업09_30_04_P33600003360000-206-2010-0000120100104<NA>1영업/정상1영업<NA><NA><NA><NA>051 941 9196175.85618210부산광역시 강서구 녹산동 1325-2번지 1층부산광역시 강서구 화전산단4로7번길 15, 1층 (녹산동)46735(주)마스터크린시스템20180425114932I2018-08-31 23:59:59.0건물위생관리업371215.463308180776.464266건물위생관리업201100000N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
26262627건물위생관리업09_30_04_P33600003360000-206-2011-0000120110124<NA>1영업/정상1영업<NA><NA><NA><NA>051 851 88125.80618803부산광역시 강서구 대저1동 2411-1번지부산광역시 강서구 대저로299번길 42, 2층 (대저1동)46702대희산업개발(주)20180315134935I2018-08-31 23:59:59.0건물위생관리업380675.494845192241.280326건물위생관리업202200000N0<NA><NA><NA>자가0<NA><NA>00N<NA>
26272628건물위생관리업09_30_04_P33600003360000-206-2010-0000320101026<NA>1영업/정상1영업<NA><NA><NA><NA>051505 654122.34618350부산광역시 강서구 봉림동 738-1254 1층 일부부산광역시 강서구 가락대로 1132-1, 1층 일부호 (봉림동)46709(주)한성종합관리20200918101922U2020-09-20 02:40:00.0건물위생관리업372775.724086186909.681755건물위생관리업101100000N0<NA><NA><NA>자가0<NA><NA>00N<NA>
26282629건물위생관리업09_30_04_P33600003360000-206-2017-0000420171121<NA>1영업/정상1영업<NA><NA><NA><NA>051 959 4511.00618803부산광역시 강서구 대저1동 2726번지부산광역시 강서구 체육공원로52번길 79 (대저1동)46703(사)한국장애인자립협회20171121153653I2018-08-31 23:59:59.0건물위생관리업380119.062155191692.440168건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
26292630건물위생관리업09_30_04_P33600003360000-206-2013-0000120130204<NA>1영업/정상1영업<NA><NA><NA><NA>051 971 166354.00618807부산광역시 강서구 대저2동 2440-3부산광역시 강서구 공항앞길221번길 56 (대저2동)46720(주)이레환경20210202152609U2021-02-04 02:40:00.0건물위생관리업377875.274835187827.464522건물위생관리업001100000N0<NA><NA><NA><NA>0<NA><NA>00Y<NA>
26302631건물위생관리업09_30_04_P33600003360000-206-2008-0000120080131<NA>1영업/정상1영업<NA><NA><NA><NA>051 971 553452.00618803부산광역시 강서구 대저1동 3052-7번지부산광역시 강서구 경전철로188번길 138 (대저1동)46703(주)한일이티엘20170925124740I2018-08-31 23:59:59.0건물위생관리업379122.254409190794.005971건물위생관리업101100000N0<NA><NA><NA>임대0<NA><NA>00N<NA>