Overview

Dataset statistics

Number of variables51
Number of observations2601
Missing cells31426
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

Description2021-03-01
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 (93.8%)Imbalance
위생업태명 is highly imbalanced (93.8%)Imbalance
발한실여부 is highly imbalanced (99.5%)Imbalance
의자수 is highly imbalanced (53.2%)Imbalance
조건부허가시작일자 is highly imbalanced (98.9%)Imbalance
다중이용업소여부 is highly imbalanced (99.5%)Imbalance
인허가취소일자 has 2601 (100.0%) missing valuesMissing
폐업일자 has 945 (36.3%) missing valuesMissing
휴업시작일자 has 2601 (100.0%) missing valuesMissing
휴업종료일자 has 2601 (100.0%) missing valuesMissing
재개업일자 has 2601 (100.0%) missing valuesMissing
소재지전화 has 617 (23.7%) missing valuesMissing
소재지우편번호 has 34 (1.3%) missing valuesMissing
도로명전체주소 has 783 (30.1%) missing valuesMissing
도로명우편번호 has 827 (31.8%) missing valuesMissing
좌표정보(x) has 70 (2.7%) missing valuesMissing
좌표정보(y) has 70 (2.7%) missing valuesMissing
건물지상층수 has 430 (16.5%) missing valuesMissing
건물지하층수 has 588 (22.6%) missing valuesMissing
사용시작지상층 has 681 (26.2%) missing valuesMissing
사용끝지상층 has 942 (36.2%) missing valuesMissing
사용시작지하층 has 1391 (53.5%) missing valuesMissing
사용끝지하층 has 1567 (60.2%) missing valuesMissing
발한실여부 has 72 (2.8%) missing valuesMissing
조건부허가신고사유 has 2595 (99.8%) missing valuesMissing
조건부허가종료일자 has 2594 (99.7%) missing valuesMissing
여성종사자수 has 2111 (81.2%) missing valuesMissing
남성종사자수 has 2066 (79.4%) missing valuesMissing
Unnamed: 50 has 2601 (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 619 (23.8%) zerosZeros
건물지하층수 has 1147 (44.1%) zerosZeros
사용시작지상층 has 352 (13.5%) zerosZeros
사용끝지상층 has 345 (13.3%) zerosZeros
사용시작지하층 has 1037 (39.9%) zerosZeros
사용끝지하층 has 877 (33.7%) zerosZeros
여성종사자수 has 428 (16.5%) zerosZeros
남성종사자수 has 361 (13.9%) zerosZeros

Reproduction

Analysis started2024-04-20 15:07:35.388446
Analysis finished2024-04-20 15:07:37.850542
Duration2.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct2601
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1301
Minimum1
Maximum2601
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.0 KiB
2024-04-21T00:07:38.059879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile131
Q1651
median1301
Q31951
95-th percentile2471
Maximum2601
Range2600
Interquartile range (IQR)1300

Descriptive statistics

Standard deviation750.98835
Coefficient of variation (CV)0.57723931
Kurtosis-1.2
Mean1301
Median Absolute Deviation (MAD)650
Skewness0
Sum3383901
Variance563983.5
MonotonicityStrictly increasing
2024-04-21T00:07:38.505190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1748 1
 
< 0.1%
1730 1
 
< 0.1%
1731 1
 
< 0.1%
1732 1
 
< 0.1%
1733 1
 
< 0.1%
1734 1
 
< 0.1%
1735 1
 
< 0.1%
1736 1
 
< 0.1%
1737 1
 
< 0.1%
Other values (2591) 2591
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 (%)
2601 1
< 0.1%
2600 1
< 0.1%
2599 1
< 0.1%
2598 1
< 0.1%
2597 1
< 0.1%
2596 1
< 0.1%
2595 1
< 0.1%
2594 1
< 0.1%
2593 1
< 0.1%
2592 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size20.4 KiB
건물위생관리업
2601 

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 2601
100.0%

Length

2024-04-21T00:07:38.919055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:07:39.262145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 2601
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size20.4 KiB
09_30_04_P
2601 

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 2601
100.0%

Length

2024-04-21T00:07:39.613783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:07:40.039299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_30_04_p 2601
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3325232.6
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.0 KiB
2024-04-21T00:07:40.347662image/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 deviation44513.111
Coefficient of variation (CV)0.013386465
Kurtosis-1.1227266
Mean3325232.6
Median Absolute Deviation (MAD)30000
Skewness0.20684281
Sum8.64893 × 109
Variance1.981417 × 109
MonotonicityNot monotonic
2024-04-21T00:07:40.790047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 355
13.6%
3300000 294
11.3%
3270000 238
9.2%
3400000 226
8.7%
3330000 203
7.8%
3370000 198
 
7.6%
3310000 161
 
6.2%
3350000 150
 
5.8%
3380000 138
 
5.3%
3320000 132
 
5.1%
Other values (6) 506
19.5%
ValueCountFrequency (%)
3250000 102
 
3.9%
3260000 75
 
2.9%
3270000 238
9.2%
3280000 27
 
1.0%
3290000 355
13.6%
3300000 294
11.3%
3310000 161
6.2%
3320000 132
 
5.1%
3330000 203
7.8%
3340000 120
 
4.6%
ValueCountFrequency (%)
3400000 226
8.7%
3390000 130
5.0%
3380000 138
5.3%
3370000 198
7.6%
3360000 52
 
2.0%
3350000 150
5.8%
3340000 120
4.6%
3330000 203
7.8%
3320000 132
5.1%
3310000 161
6.2%

관리번호
Text

UNIQUE 

Distinct2601
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size20.4 KiB
2024-04-21T00:07:41.591175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters57222
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

Unique2601 ?
Unique (%)100.0%

Sample

1st row3350000-206-2021-00001
2nd row3260000-206-2011-00003
3rd row3380000-206-2019-00001
4th row3320000-206-2005-00002
5th row3320000-206-2013-00002
ValueCountFrequency (%)
3350000-206-2021-00001 1
 
< 0.1%
3400000-206-2008-00001 1
 
< 0.1%
3320000-206-2014-00006 1
 
< 0.1%
3320000-206-2011-00009 1
 
< 0.1%
3320000-206-2015-00003 1
 
< 0.1%
3320000-206-2013-00005 1
 
< 0.1%
3320000-206-2016-00003 1
 
< 0.1%
3320000-206-2005-00001 1
 
< 0.1%
3320000-206-2011-00007 1
 
< 0.1%
3320000-206-2014-00001 1
 
< 0.1%
Other values (2591) 2591
99.6%
2024-04-21T00:07:42.799046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 26561
46.4%
- 7803
 
13.6%
2 6679
 
11.7%
3 5094
 
8.9%
6 3256
 
5.7%
1 2812
 
4.9%
9 1503
 
2.6%
4 998
 
1.7%
7 984
 
1.7%
5 806
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49419
86.4%
Dash Punctuation 7803
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 26561
53.7%
2 6679
 
13.5%
3 5094
 
10.3%
6 3256
 
6.6%
1 2812
 
5.7%
9 1503
 
3.0%
4 998
 
2.0%
7 984
 
2.0%
5 806
 
1.6%
8 726
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 7803
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 57222
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 26561
46.4%
- 7803
 
13.6%
2 6679
 
11.7%
3 5094
 
8.9%
6 3256
 
5.7%
1 2812
 
4.9%
9 1503
 
2.6%
4 998
 
1.7%
7 984
 
1.7%
5 806
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57222
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 26561
46.4%
- 7803
 
13.6%
2 6679
 
11.7%
3 5094
 
8.9%
6 3256
 
5.7%
1 2812
 
4.9%
9 1503
 
2.6%
4 998
 
1.7%
7 984
 
1.7%
5 806
 
1.4%

인허가일자
Real number (ℝ)

Distinct1945
Distinct (%)74.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20087305
Minimum19870507
Maximum20210126
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.0 KiB
2024-04-21T00:07:43.061652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19870507
5-th percentile19960620
Q120040820
median20091021
Q320140715
95-th percentile20190920
Maximum20210126
Range339619
Interquartile range (IQR)99895

Descriptive statistics

Standard deviation71418.1
Coefficient of variation (CV)0.0035553849
Kurtosis-0.11605489
Mean20087305
Median Absolute Deviation (MAD)49989
Skewness-0.5012069
Sum5.224708 × 1010
Variance5.100545 × 109
MonotonicityNot monotonic
2024-04-21T00:07:43.495672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20120622 6
 
0.2%
20100603 6
 
0.2%
20081209 6
 
0.2%
20140327 5
 
0.2%
20110726 5
 
0.2%
20140219 5
 
0.2%
20070614 5
 
0.2%
20000706 5
 
0.2%
20101217 5
 
0.2%
20020403 5
 
0.2%
Other values (1935) 2548
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 (%)
20210126 1
 
< 0.1%
20210118 1
 
< 0.1%
20210112 1
 
< 0.1%
20210111 1
 
< 0.1%
20210108 1
 
< 0.1%
20210106 2
0.1%
20210105 1
 
< 0.1%
20210104 4
0.2%
20201230 1
 
< 0.1%
20201221 1
 
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2601
Missing (%)100.0%
Memory size23.0 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.4 KiB
3
1656 
1
945 

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 1656
63.7%
1 945
36.3%

Length

2024-04-21T00:07:43.917618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:07:44.117445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1656
63.7%
1 945
36.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.4 KiB
폐업
1656 
영업/정상
945 

Length

Max length5
Median length2
Mean length3.0899654
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1656
63.7%
영업/정상 945
36.3%

Length

2024-04-21T00:07:44.319108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:07:44.517213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1656
63.7%
영업/정상 945
36.3%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.4 KiB
2
1656 
1
945 

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 1656
63.7%
1 945
36.3%

Length

2024-04-21T00:07:44.850091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:07:45.088809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1656
63.7%
1 945
36.3%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.4 KiB
폐업
1656 
영업
945 

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 1656
63.7%
영업 945
36.3%

Length

2024-04-21T00:07:45.261257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:07:45.423362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1656
63.7%
영업 945
36.3%

폐업일자
Real number (ℝ)

MISSING 

Distinct1211
Distinct (%)73.1%
Missing945
Missing (%)36.3%
Infinite0
Infinite (%)0.0%
Mean20115811
Minimum19880329
Maximum20210126
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.0 KiB
2024-04-21T00:07:45.706113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19880329
5-th percentile20020822
Q120070128
median20120926
Q320170308
95-th percentile20200325
Maximum20210126
Range329797
Interquartile range (IQR)100179.5

Descriptive statistics

Standard deviation59603.478
Coefficient of variation (CV)0.0029630164
Kurtosis-0.4674801
Mean20115811
Median Absolute Deviation (MAD)49998.5
Skewness-0.4589974
Sum3.3311784 × 1010
Variance3.5525746 × 109
MonotonicityNot monotonic
2024-04-21T00:07:46.103777image/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%
20170831 8
 
0.3%
20041213 8
 
0.3%
20031124 8
 
0.3%
20031114 7
 
0.3%
20090318 7
 
0.3%
Other values (1201) 1551
59.6%
(Missing) 945
36.3%
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 (%)
20210126 1
< 0.1%
20210122 2
0.1%
20210112 1
< 0.1%
20210111 1
< 0.1%
20210105 1
< 0.1%
20201230 1
< 0.1%
20201228 2
0.1%
20201223 1
< 0.1%
20201221 1
< 0.1%
20201218 1
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2601
Missing (%)100.0%
Memory size23.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2601
Missing (%)100.0%
Memory size23.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2601
Missing (%)100.0%
Memory size23.0 KiB

소재지전화
Text

MISSING 

Distinct1726
Distinct (%)87.0%
Missing617
Missing (%)23.7%
Memory size20.4 KiB
2024-04-21T00:07:47.287765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.205141
Min length3

Characters and Unicode

Total characters22231
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

Unique1535 ?
Unique (%)77.4%

Sample

1st row02 4647058
2nd row051 3410086
3rd row051 342 8377
4th row051 467 8313
5th row051 343 0110
ValueCountFrequency (%)
051 1760
37.2%
727 58
 
1.2%
070 55
 
1.2%
728 17
 
0.4%
724 15
 
0.3%
502 13
 
0.3%
722 12
 
0.3%
557 12
 
0.3%
465 11
 
0.2%
342 11
 
0.2%
Other values (1926) 2764
58.5%
2024-04-21T00:07:48.766002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 3479
15.6%
0 3396
15.3%
1 3251
14.6%
2761
12.4%
2 1583
7.1%
7 1533
6.9%
6 1389
 
6.2%
4 1369
 
6.2%
3 1315
 
5.9%
8 1242
 
5.6%
Other values (2) 913
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19469
87.6%
Space Separator 2761
 
12.4%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 3479
17.9%
0 3396
17.4%
1 3251
16.7%
2 1583
8.1%
7 1533
7.9%
6 1389
 
7.1%
4 1369
 
7.0%
3 1315
 
6.8%
8 1242
 
6.4%
9 912
 
4.7%
Space Separator
ValueCountFrequency (%)
2761
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22231
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 3479
15.6%
0 3396
15.3%
1 3251
14.6%
2761
12.4%
2 1583
7.1%
7 1533
6.9%
6 1389
 
6.2%
4 1369
 
6.2%
3 1315
 
5.9%
8 1242
 
5.6%
Other values (2) 913
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22231
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 3479
15.6%
0 3396
15.3%
1 3251
14.6%
2761
12.4%
2 1583
7.1%
7 1533
6.9%
6 1389
 
6.2%
4 1369
 
6.2%
3 1315
 
5.9%
8 1242
 
5.6%
Other values (2) 913
 
4.1%
Distinct1541
Distinct (%)59.8%
Missing24
Missing (%)0.9%
Memory size20.4 KiB
2024-04-21T00:07:49.900978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.8676756
Min length3

Characters and Unicode

Total characters12544
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

Unique1245 ?
Unique (%)48.3%

Sample

1st row.00
2nd row.00
3rd row33.60
4th row91.30
5th row46.29
ValueCountFrequency (%)
00 346
 
13.4%
33.00 37
 
1.4%
66.00 21
 
0.8%
40.00 15
 
0.6%
30.00 13
 
0.5%
49.50 12
 
0.5%
36.00 12
 
0.5%
12.00 11
 
0.4%
99.00 11
 
0.4%
27.00 10
 
0.4%
Other values (1531) 2089
81.1%
2024-04-21T00:07:51.421741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2717
21.7%
. 2577
20.5%
1 1071
 
8.5%
2 989
 
7.9%
5 869
 
6.9%
3 851
 
6.8%
6 804
 
6.4%
4 778
 
6.2%
8 698
 
5.6%
7 596
 
4.8%
Other values (2) 594
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9962
79.4%
Other Punctuation 2582
 
20.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2717
27.3%
1 1071
 
10.8%
2 989
 
9.9%
5 869
 
8.7%
3 851
 
8.5%
6 804
 
8.1%
4 778
 
7.8%
8 698
 
7.0%
7 596
 
6.0%
9 589
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 2577
99.8%
, 5
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 12544
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2717
21.7%
. 2577
20.5%
1 1071
 
8.5%
2 989
 
7.9%
5 869
 
6.9%
3 851
 
6.8%
6 804
 
6.4%
4 778
 
6.2%
8 698
 
5.6%
7 596
 
4.8%
Other values (2) 594
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12544
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2717
21.7%
. 2577
20.5%
1 1071
 
8.5%
2 989
 
7.9%
5 869
 
6.9%
3 851
 
6.8%
6 804
 
6.4%
4 778
 
6.2%
8 698
 
5.6%
7 596
 
4.8%
Other values (2) 594
 
4.7%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct604
Distinct (%)23.5%
Missing34
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean610888.62
Minimum400410
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.0 KiB
2024-04-21T00:07:51.743909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum400410
5-th percentile601807
Q1607810.5
median611823
Q3614854
95-th percentile619912
Maximum619953
Range219543
Interquartile range (IQR)7043.5

Descriptive statistics

Standard deviation7031.4036
Coefficient of variation (CV)0.011510124
Kurtosis311.51103
Mean610888.62
Median Absolute Deviation (MAD)3992
Skewness-10.57649
Sum1.5681511 × 109
Variance49440637
MonotonicityNot monotonic
2024-04-21T00:07:52.162236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
619951 47
 
1.8%
619952 45
 
1.7%
601837 41
 
1.6%
601839 29
 
1.1%
601836 28
 
1.1%
619953 26
 
1.0%
614844 26
 
1.0%
601838 25
 
1.0%
614865 23
 
0.9%
607804 21
 
0.8%
Other values (594) 2256
86.7%
(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 45
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
 
0.7%
619904 5
 
0.2%
Distinct2398
Distinct (%)92.7%
Missing14
Missing (%)0.5%
Memory size20.4 KiB
2024-04-21T00:07:53.327654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length45
Mean length25.442211
Min length2

Characters and Unicode

Total characters65819
Distinct characters403
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

Unique2239 ?
Unique (%)86.5%

Sample

1st row부산광역시 금정구 금사동 81-1 금사자동차운전전문학원
2nd row인천광역시 중구 덕교동 128-76번지
3rd row부산광역시 수영구 광안동 100-10
4th row부산광역시 북구 덕천동 388-1번지 대방상가 304호
5th row부산광역시 북구 구포동 1256-15번지
ValueCountFrequency (%)
부산광역시 2585
 
20.8%
부산진구 348
 
2.8%
동래구 294
 
2.4%
동구 237
 
1.9%
기장군 225
 
1.8%
해운대구 204
 
1.6%
연제구 197
 
1.6%
초량동 161
 
1.3%
남구 160
 
1.3%
금정구 150
 
1.2%
Other values (3129) 7883
63.3%
2024-04-21T00:07:55.116701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9860
 
15.0%
3196
 
4.9%
3192
 
4.8%
1 3178
 
4.8%
3147
 
4.8%
2684
 
4.1%
2613
 
4.0%
2593
 
3.9%
2500
 
3.8%
2448
 
3.7%
Other values (393) 30408
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39085
59.4%
Decimal Number 13900
 
21.1%
Space Separator 9860
 
15.0%
Dash Punctuation 2362
 
3.6%
Uppercase Letter 244
 
0.4%
Close Punctuation 142
 
0.2%
Open 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 (%)
3196
 
8.2%
3192
 
8.2%
3147
 
8.1%
2684
 
6.9%
2613
 
6.7%
2593
 
6.6%
2500
 
6.4%
2448
 
6.3%
2379
 
6.1%
530
 
1.4%
Other values (346) 13803
35.3%
Uppercase Letter
ValueCountFrequency (%)
B 98
40.2%
T 76
31.1%
O 14
 
5.7%
A 9
 
3.7%
S 8
 
3.3%
D 8
 
3.3%
K 6
 
2.5%
I 5
 
2.0%
C 5
 
2.0%
P 4
 
1.6%
Other values (8) 11
 
4.5%
Decimal Number
ValueCountFrequency (%)
1 3178
22.9%
2 1918
13.8%
3 1580
11.4%
4 1310
9.4%
0 1242
 
8.9%
5 1172
 
8.4%
6 1002
 
7.2%
7 947
 
6.8%
8 858
 
6.2%
9 693
 
5.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
15.4%
k 2
15.4%
s 2
15.4%
d 1
7.7%
h 1
7.7%
u 1
7.7%
t 1
7.7%
o 1
7.7%
y 1
7.7%
b 1
7.7%
Other Punctuation
ValueCountFrequency (%)
, 47
67.1%
/ 17
 
24.3%
@ 3
 
4.3%
. 3
 
4.3%
Space Separator
ValueCountFrequency (%)
9860
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2362
100.0%
Close Punctuation
ValueCountFrequency (%)
) 142
100.0%
Open Punctuation
ValueCountFrequency (%)
( 142
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39085
59.4%
Common 26477
40.2%
Latin 257
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3196
 
8.2%
3192
 
8.2%
3147
 
8.1%
2684
 
6.9%
2613
 
6.7%
2593
 
6.6%
2500
 
6.4%
2448
 
6.3%
2379
 
6.1%
530
 
1.4%
Other values (346) 13803
35.3%
Latin
ValueCountFrequency (%)
B 98
38.1%
T 76
29.6%
O 14
 
5.4%
A 9
 
3.5%
S 8
 
3.1%
D 8
 
3.1%
K 6
 
2.3%
I 5
 
1.9%
C 5
 
1.9%
P 4
 
1.6%
Other values (18) 24
 
9.3%
Common
ValueCountFrequency (%)
9860
37.2%
1 3178
 
12.0%
- 2362
 
8.9%
2 1918
 
7.2%
3 1580
 
6.0%
4 1310
 
4.9%
0 1242
 
4.7%
5 1172
 
4.4%
6 1002
 
3.8%
7 947
 
3.6%
Other values (9) 1906
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39085
59.4%
ASCII 26734
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9860
36.9%
1 3178
 
11.9%
- 2362
 
8.8%
2 1918
 
7.2%
3 1580
 
5.9%
4 1310
 
4.9%
0 1242
 
4.6%
5 1172
 
4.4%
6 1002
 
3.7%
7 947
 
3.5%
Other values (37) 2163
 
8.1%
Hangul
ValueCountFrequency (%)
3196
 
8.2%
3192
 
8.2%
3147
 
8.1%
2684
 
6.9%
2613
 
6.7%
2593
 
6.6%
2500
 
6.4%
2448
 
6.3%
2379
 
6.1%
530
 
1.4%
Other values (346) 13803
35.3%

도로명전체주소
Text

MISSING 

Distinct1741
Distinct (%)95.8%
Missing783
Missing (%)30.1%
Memory size20.4 KiB
2024-04-21T00:07:56.829767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length49
Mean length31.679318
Min length20

Characters and Unicode

Total characters57593
Distinct characters420
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

Unique1674 ?
Unique (%)92.1%

Sample

1st row부산광역시 금정구 공단서로8번길 49, 금사자동차운전전문학원 A동 307호 (금사동)
2nd row인천광역시 중구 마시란로 51-33 (덕교동)
3rd row부산광역시 수영구 무학로9번길 46, 1층 (광안동)
4th row부산광역시 북구 시랑로118번길 56 (구포동)
5th row부산광역시 북구 만덕3로16번길 45, 상가동 101호 (덕천동, 벽산아파트)
ValueCountFrequency (%)
부산광역시 1817
 
16.3%
부산진구 247
 
2.2%
2층 224
 
2.0%
1층 222
 
2.0%
동래구 203
 
1.8%
기장군 193
 
1.7%
해운대구 158
 
1.4%
연제구 143
 
1.3%
동구 130
 
1.2%
3층 129
 
1.2%
Other values (2414) 7698
69.0%
2024-04-21T00:07:58.800517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9348
 
16.2%
2351
 
4.1%
2285
 
4.0%
2268
 
3.9%
1 2206
 
3.8%
1922
 
3.3%
1902
 
3.3%
1824
 
3.2%
1722
 
3.0%
1710
 
3.0%
Other values (410) 30055
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33316
57.8%
Decimal Number 9494
 
16.5%
Space Separator 9348
 
16.2%
Close Punctuation 1701
 
3.0%
Open Punctuation 1701
 
3.0%
Other Punctuation 1600
 
2.8%
Dash Punctuation 309
 
0.5%
Uppercase Letter 110
 
0.2%
Lowercase Letter 11
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2351
 
7.1%
2285
 
6.9%
2268
 
6.8%
1922
 
5.8%
1902
 
5.7%
1824
 
5.5%
1722
 
5.2%
1710
 
5.1%
946
 
2.8%
911
 
2.7%
Other values (367) 15475
46.4%
Uppercase Letter
ValueCountFrequency (%)
B 35
31.8%
A 21
19.1%
C 10
 
9.1%
E 9
 
8.2%
S 7
 
6.4%
P 7
 
6.4%
O 4
 
3.6%
T 4
 
3.6%
I 4
 
3.6%
K 2
 
1.8%
Other values (6) 7
 
6.4%
Decimal Number
ValueCountFrequency (%)
1 2206
23.2%
2 1581
16.7%
3 1153
12.1%
0 873
 
9.2%
4 797
 
8.4%
5 703
 
7.4%
6 599
 
6.3%
7 558
 
5.9%
8 528
 
5.6%
9 496
 
5.2%
Lowercase Letter
ValueCountFrequency (%)
e 2
18.2%
s 2
18.2%
k 2
18.2%
y 1
9.1%
b 1
9.1%
u 1
9.1%
h 1
9.1%
d 1
9.1%
Other Punctuation
ValueCountFrequency (%)
, 1590
99.4%
/ 6
 
0.4%
@ 2
 
0.1%
. 2
 
0.1%
Space Separator
ValueCountFrequency (%)
9348
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1701
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1701
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 309
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33316
57.8%
Common 24156
41.9%
Latin 121
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2351
 
7.1%
2285
 
6.9%
2268
 
6.8%
1922
 
5.8%
1902
 
5.7%
1824
 
5.5%
1722
 
5.2%
1710
 
5.1%
946
 
2.8%
911
 
2.7%
Other values (367) 15475
46.4%
Latin
ValueCountFrequency (%)
B 35
28.9%
A 21
17.4%
C 10
 
8.3%
E 9
 
7.4%
S 7
 
5.8%
P 7
 
5.8%
O 4
 
3.3%
T 4
 
3.3%
I 4
 
3.3%
e 2
 
1.7%
Other values (14) 18
14.9%
Common
ValueCountFrequency (%)
9348
38.7%
1 2206
 
9.1%
) 1701
 
7.0%
( 1701
 
7.0%
, 1590
 
6.6%
2 1581
 
6.5%
3 1153
 
4.8%
0 873
 
3.6%
4 797
 
3.3%
5 703
 
2.9%
Other values (9) 2503
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33316
57.8%
ASCII 24277
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9348
38.5%
1 2206
 
9.1%
) 1701
 
7.0%
( 1701
 
7.0%
, 1590
 
6.5%
2 1581
 
6.5%
3 1153
 
4.7%
0 873
 
3.6%
4 797
 
3.3%
5 703
 
2.9%
Other values (33) 2624
 
10.8%
Hangul
ValueCountFrequency (%)
2351
 
7.1%
2285
 
6.9%
2268
 
6.8%
1922
 
5.8%
1902
 
5.7%
1824
 
5.5%
1722
 
5.2%
1710
 
5.1%
946
 
2.8%
911
 
2.7%
Other values (367) 15475
46.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct852
Distinct (%)48.0%
Missing827
Missing (%)31.8%
Infinite0
Infinite (%)0.0%
Mean47614.542
Minimum22385
Maximum49524
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.0 KiB
2024-04-21T00:07:59.055161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22385
5-th percentile46037
Q146957.75
median47709
Q348402.75
95-th percentile49262.05
Maximum49524
Range27139
Interquartile range (IQR)1445

Descriptive statistics

Standard deviation1144.6425
Coefficient of variation (CV)0.024039767
Kurtosis131.66173
Mean47614.542
Median Absolute Deviation (MAD)724.5
Skewness-6.0363703
Sum84468198
Variance1310206.4
MonotonicityNot monotonic
2024-04-21T00:07:59.380155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46036 30
 
1.2%
46037 23
 
0.9%
46033 19
 
0.7%
48729 18
 
0.7%
47247 14
 
0.5%
48093 14
 
0.5%
48059 13
 
0.5%
48060 13
 
0.5%
47243 11
 
0.4%
47246 11
 
0.4%
Other values (842) 1608
61.8%
(Missing) 827
31.8%
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%
Distinct2215
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Memory size20.4 KiB
2024-04-21T00:08:00.309881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length22
Mean length7.194925
Min length2

Characters and Unicode

Total characters18714
Distinct characters538
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

Unique1911 ?
Unique (%)73.5%

Sample

1st row고클린
2nd row(주)성수인력
3rd row청소협동조합 청소하는사람들 부산경남본점
4th row(주)천우이엔지
5th row신흥
ValueCountFrequency (%)
주식회사 165
 
5.5%
16
 
0.5%
주)만비종합관리 7
 
0.2%
시스템 7
 
0.2%
주)만송 7
 
0.2%
주)금강종합개발 6
 
0.2%
청소나라 6
 
0.2%
그린산업 6
 
0.2%
청소 5
 
0.2%
클린 5
 
0.2%
Other values (2327) 2776
92.3%
2024-04-21T00:08:01.617891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1471
 
7.9%
) 1308
 
7.0%
( 1272
 
6.8%
552
 
2.9%
447
 
2.4%
408
 
2.2%
375
 
2.0%
329
 
1.8%
327
 
1.7%
314
 
1.7%
Other values (528) 11911
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15343
82.0%
Close Punctuation 1308
 
7.0%
Open Punctuation 1272
 
6.8%
Space Separator 408
 
2.2%
Uppercase Letter 238
 
1.3%
Lowercase Letter 54
 
0.3%
Other Punctuation 38
 
0.2%
Decimal Number 36
 
0.2%
Other Symbol 15
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1471
 
9.6%
552
 
3.6%
447
 
2.9%
375
 
2.4%
329
 
2.1%
327
 
2.1%
314
 
2.0%
297
 
1.9%
292
 
1.9%
243
 
1.6%
Other values (476) 10696
69.7%
Uppercase Letter
ValueCountFrequency (%)
C 40
16.8%
E 22
9.2%
S 22
9.2%
B 18
 
7.6%
G 17
 
7.1%
M 16
 
6.7%
H 16
 
6.7%
N 15
 
6.3%
T 13
 
5.5%
J 8
 
3.4%
Other values (10) 51
21.4%
Lowercase Letter
ValueCountFrequency (%)
e 13
24.1%
o 6
11.1%
a 5
 
9.3%
s 5
 
9.3%
n 4
 
7.4%
l 4
 
7.4%
r 4
 
7.4%
i 3
 
5.6%
c 3
 
5.6%
t 3
 
5.6%
Other values (4) 4
 
7.4%
Decimal Number
ValueCountFrequency (%)
1 16
44.4%
2 8
22.2%
4 3
 
8.3%
0 3
 
8.3%
9 3
 
8.3%
8 2
 
5.6%
6 1
 
2.8%
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 (%)
) 1308
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1272
100.0%
Space Separator
ValueCountFrequency (%)
408
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15358
82.1%
Common 3064
 
16.4%
Latin 292
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1471
 
9.6%
552
 
3.6%
447
 
2.9%
375
 
2.4%
329
 
2.1%
327
 
2.1%
314
 
2.0%
297
 
1.9%
292
 
1.9%
243
 
1.6%
Other values (478) 10711
69.7%
Latin
ValueCountFrequency (%)
C 40
 
13.7%
E 22
 
7.5%
S 22
 
7.5%
B 18
 
6.2%
G 17
 
5.8%
M 16
 
5.5%
H 16
 
5.5%
N 15
 
5.1%
T 13
 
4.5%
e 13
 
4.5%
Other values (24) 100
34.2%
Common
ValueCountFrequency (%)
) 1308
42.7%
( 1272
41.5%
408
 
13.3%
& 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 (6) 13
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15343
82.0%
ASCII 3350
 
17.9%
None 21
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1471
 
9.6%
552
 
3.6%
447
 
2.9%
375
 
2.4%
329
 
2.1%
327
 
2.1%
314
 
2.0%
297
 
1.9%
292
 
1.9%
243
 
1.6%
Other values (476) 10696
69.7%
ASCII
ValueCountFrequency (%)
) 1308
39.0%
( 1272
38.0%
408
 
12.2%
C 40
 
1.2%
E 22
 
0.7%
S 22
 
0.7%
B 18
 
0.5%
G 17
 
0.5%
M 16
 
0.5%
H 16
 
0.5%
Other values (38) 211
 
6.3%
None
ValueCountFrequency (%)
14
66.7%
· 4
 
19.0%
2
 
9.5%
1
 
4.8%

최종수정시점
Real number (ℝ)

Distinct2346
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0130021 × 1013
Minimum1.9990201 × 1013
Maximum2.0210127 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.0 KiB
2024-04-21T00:08:01.930513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990201 × 1013
5-th percentile2.0030212 × 1013
Q12.0080623 × 1013
median2.0140611 × 1013
Q32.0181128 × 1013
95-th percentile2.0201007 × 1013
Maximum2.0210127 × 1013
Range2.1992613 × 1011
Interquartile range (IQR)1.0050498 × 1011

Descriptive statistics

Standard deviation6.0840769 × 1010
Coefficient of variation (CV)0.0030223898
Kurtosis-0.94716746
Mean2.0130021 × 1013
Median Absolute Deviation (MAD)4.969405 × 1010
Skewness-0.54053808
Sum5.2358183 × 1016
Variance3.7015992 × 1021
MonotonicityNot monotonic
2024-04-21T00:08:02.183861image/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%
20030403000000 11
 
0.4%
19990201000000 11
 
0.4%
20030404000000 10
 
0.4%
20021112000000 10
 
0.4%
20051110000000 10
 
0.4%
20020403000000 8
 
0.3%
20030227000000 8
 
0.3%
Other values (2336) 2486
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 (%)
20210127131319 1
< 0.1%
20210126173433 1
< 0.1%
20210126163728 1
< 0.1%
20210126133258 1
< 0.1%
20210125164013 1
< 0.1%
20210122142224 1
< 0.1%
20210122142157 1
< 0.1%
20210121154405 1
< 0.1%
20210121142114 1
< 0.1%
20210121094753 1
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.4 KiB
I
2016 
U
585 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 2016
77.5%
U 585
 
22.5%

Length

2024-04-21T00:08:02.420605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:08:02.582885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2016
77.5%
u 585
 
22.5%
Distinct452
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size20.4 KiB
Minimum2018-08-31 23:59:59
Maximum2021-01-29 02:40:00
2024-04-21T00:08:02.780980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T00:08:03.042749image/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 size20.4 KiB
건물위생관리업
2572 
건물위생관리업 기타
 
21
<NA>
 
8

Length

Max length10
Median length7
Mean length7.0149942
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 2572
98.9%
건물위생관리업 기타 21
 
0.8%
<NA> 8
 
0.3%

Length

2024-04-21T00:08:03.288329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:08:03.476761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 2593
98.9%
기타 21
 
0.8%
na 8
 
0.3%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct1940
Distinct (%)76.6%
Missing70
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean389105.31
Minimum148671.32
Maximum408081.98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.0 KiB
2024-04-21T00:08:03.696761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum148671.32
5-th percentile380059.42
Q1385773.89
median388601.81
Q3391459.83
95-th percentile403721.73
Maximum408081.98
Range259410.66
Interquartile range (IQR)5685.9372

Descriptive statistics

Standard deviation8016.7894
Coefficient of variation (CV)0.020603135
Kurtosis319.42423
Mean389105.31
Median Absolute Deviation (MAD)2832.2384
Skewness-10.283709
Sum9.8482555 × 108
Variance64268913
MonotonicityNot monotonic
2024-04-21T00:08:03.960527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
395615.201853958 13
 
0.5%
396180.621244719 9
 
0.3%
380482.767624189 9
 
0.3%
387927.951172724 9
 
0.3%
391411.212179843 9
 
0.3%
388310.086924943 9
 
0.3%
386351.941329364 8
 
0.3%
387869.134317928 8
 
0.3%
387225.613588405 8
 
0.3%
407871.508884898 8
 
0.3%
Other values (1930) 2441
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 

Distinct1940
Distinct (%)76.6%
Missing70
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean188406.47
Minimum174156.62
Maximum436093.42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.0 KiB
2024-04-21T00:08:04.212407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174156.62
5-th percentile179713.87
Q1183987.07
median187522.89
Q3191384.87
95-th percentile203507.3
Maximum436093.42
Range261936.8
Interquartile range (IQR)7397.7941

Descriptive statistics

Standard deviation8102.1101
Coefficient of variation (CV)0.043003354
Kurtosis344.5637
Mean188406.47
Median Absolute Deviation (MAD)3719.4766
Skewness11.707161
Sum4.7685678 × 108
Variance65644189
MonotonicityNot monotonic
2024-04-21T00:08:04.470010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
186406.750870936 13
 
0.5%
186522.35047527 9
 
0.3%
185582.274947583 9
 
0.3%
186582.791097672 9
 
0.3%
184052.409245407 9
 
0.3%
183883.854898063 9
 
0.3%
182468.78681462 8
 
0.3%
186381.28184674 8
 
0.3%
186408.726533861 8
 
0.3%
205389.277197702 8
 
0.3%
Other values (1930) 2441
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 size20.4 KiB
건물위생관리업
2572 
건물위생관리업 기타
 
21
<NA>
 
8

Length

Max length10
Median length7
Mean length7.0149942
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 2572
98.9%
건물위생관리업 기타 21
 
0.8%
<NA> 8
 
0.3%

Length

2024-04-21T00:08:04.702614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:08:04.904219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 2593
98.9%
기타 21
 
0.8%
na 8
 
0.3%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct30
Distinct (%)1.4%
Missing430
Missing (%)16.5%
Infinite0
Infinite (%)0.0%
Mean3.748503
Minimum0
Maximum51
Zeros619
Zeros (%)23.8%
Negative0
Negative (%)0.0%
Memory size23.0 KiB
2024-04-21T00:08:05.087725image/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 deviation4.5927554
Coefficient of variation (CV)1.2252239
Kurtosis14.613901
Mean3.748503
Median Absolute Deviation (MAD)2
Skewness2.9118141
Sum8138
Variance21.093402
MonotonicityNot monotonic
2024-04-21T00:08:05.314844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 619
23.8%
4 349
13.4%
3 250
9.6%
5 233
 
9.0%
2 229
 
8.8%
1 111
 
4.3%
6 87
 
3.3%
7 50
 
1.9%
10 40
 
1.5%
8 35
 
1.3%
Other values (20) 168
 
6.5%
(Missing) 430
16.5%
ValueCountFrequency (%)
0 619
23.8%
1 111
 
4.3%
2 229
 
8.8%
3 250
9.6%
4 349
13.4%
5 233
 
9.0%
6 87
 
3.3%
7 50
 
1.9%
8 35
 
1.3%
9 24
 
0.9%
ValueCountFrequency (%)
51 1
 
< 0.1%
49 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%
20 23
0.9%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.4%
Missing588
Missing (%)22.6%
Infinite0
Infinite (%)0.0%
Mean0.6130154
Minimum0
Maximum8
Zeros1147
Zeros (%)44.1%
Negative0
Negative (%)0.0%
Memory size23.0 KiB
2024-04-21T00:08:05.525158image/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 deviation0.96343152
Coefficient of variation (CV)1.5716269
Kurtosis9.514996
Mean0.6130154
Median Absolute Deviation (MAD)0
Skewness2.6436147
Sum1234
Variance0.9282003
MonotonicityNot monotonic
2024-04-21T00:08:05.722435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 1147
44.1%
1 681
26.2%
2 93
 
3.6%
3 41
 
1.6%
5 22
 
0.8%
4 21
 
0.8%
6 7
 
0.3%
8 1
 
< 0.1%
(Missing) 588
22.6%
ValueCountFrequency (%)
0 1147
44.1%
1 681
26.2%
2 93
 
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 93
 
3.6%
1 681
26.2%
0 1147
44.1%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct26
Distinct (%)1.4%
Missing681
Missing (%)26.2%
Infinite0
Infinite (%)0.0%
Mean2.65625
Minimum0
Maximum48
Zeros352
Zeros (%)13.5%
Negative0
Negative (%)0.0%
Memory size23.0 KiB
2024-04-21T00:08:05.965678image/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 deviation3.2804572
Coefficient of variation (CV)1.2349956
Kurtosis28.378412
Mean2.65625
Median Absolute Deviation (MAD)1
Skewness3.9107229
Sum5100
Variance10.761399
MonotonicityNot monotonic
2024-04-21T00:08:06.180574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
2 456
17.5%
1 419
16.1%
0 352
13.5%
3 280
10.8%
4 147
 
5.7%
5 70
 
2.7%
6 44
 
1.7%
7 35
 
1.3%
9 19
 
0.7%
8 19
 
0.7%
Other values (16) 79
 
3.0%
(Missing) 681
26.2%
ValueCountFrequency (%)
0 352
13.5%
1 419
16.1%
2 456
17.5%
3 280
10.8%
4 147
 
5.7%
5 70
 
2.7%
6 44
 
1.7%
7 35
 
1.3%
8 19
 
0.7%
9 19
 
0.7%
ValueCountFrequency (%)
48 1
 
< 0.1%
26 1
 
< 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%
Missing942
Missing (%)36.2%
Infinite0
Infinite (%)0.0%
Mean2.5382761
Minimum0
Maximum48
Zeros345
Zeros (%)13.3%
Negative0
Negative (%)0.0%
Memory size23.0 KiB
2024-04-21T00:08:06.396239image/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 deviation3.2879793
Coefficient of variation (CV)1.2953592
Kurtosis31.642899
Mean2.5382761
Median Absolute Deviation (MAD)1
Skewness4.1576963
Sum4211
Variance10.810808
MonotonicityNot monotonic
2024-04-21T00:08:06.617214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
2 382
14.7%
1 364
 
14.0%
0 345
 
13.3%
3 233
 
9.0%
4 127
 
4.9%
5 49
 
1.9%
6 41
 
1.6%
7 29
 
1.1%
8 12
 
0.5%
9 10
 
0.4%
Other values (15) 67
 
2.6%
(Missing) 942
36.2%
ValueCountFrequency (%)
0 345
13.3%
1 364
14.0%
2 382
14.7%
3 233
9.0%
4 127
 
4.9%
5 49
 
1.9%
6 41
 
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%
Missing1391
Missing (%)53.5%
Infinite0
Infinite (%)0.0%
Mean0.1553719
Minimum0
Maximum5
Zeros1037
Zeros (%)39.9%
Negative0
Negative (%)0.0%
Memory size23.0 KiB
2024-04-21T00:08:06.951099image/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 deviation0.42149649
Coefficient of variation (CV)2.7128232
Kurtosis27.888252
Mean0.1553719
Median Absolute Deviation (MAD)0
Skewness4.0421545
Sum188
Variance0.17765929
MonotonicityNot monotonic
2024-04-21T00:08:07.636200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 1037
39.9%
1 166
 
6.4%
2 3
 
0.1%
4 2
 
0.1%
3 1
 
< 0.1%
5 1
 
< 0.1%
(Missing) 1391
53.5%
ValueCountFrequency (%)
0 1037
39.9%
1 166
 
6.4%
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%
1 166
 
6.4%
0 1037
39.9%

사용끝지하층
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.7%
Missing1567
Missing (%)60.2%
Infinite0
Infinite (%)0.0%
Mean0.17601547
Minimum0
Maximum10
Zeros877
Zeros (%)33.7%
Negative0
Negative (%)0.0%
Memory size23.0 KiB
2024-04-21T00:08:07.956669image/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 deviation0.533455
Coefficient of variation (CV)3.0307278
Kurtosis121.08361
Mean0.17601547
Median Absolute Deviation (MAD)0
Skewness8.1087643
Sum182
Variance0.28457423
MonotonicityNot monotonic
2024-04-21T00:08:08.150912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 877
33.7%
1 147
 
5.7%
2 5
 
0.2%
3 2
 
0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
10 1
 
< 0.1%
(Missing) 1567
60.2%
ValueCountFrequency (%)
0 877
33.7%
1 147
 
5.7%
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%
1 147
 
5.7%
0 877
33.7%

한실수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.4 KiB
0
1721 
<NA>
879 
1
 
1

Length

Max length4
Median length1
Mean length2.0138408
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1721
66.2%
<NA> 879
33.8%
1 1
 
< 0.1%

Length

2024-04-21T00:08:08.485722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:08:08.850960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1721
66.2%
na 879
33.8%
1 1
 
< 0.1%

양실수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.4 KiB
0
1721 
<NA>
879 
29
 
1

Length

Max length4
Median length1
Mean length2.0142253
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1721
66.2%
<NA> 879
33.8%
29 1
 
< 0.1%

Length

2024-04-21T00:08:09.246523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:08:09.598857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1721
66.2%
na 879
33.8%
29 1
 
< 0.1%

욕실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.4 KiB
0
1722 
<NA>
879 

Length

Max length4
Median length1
Mean length2.0138408
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1722
66.2%
<NA> 879
33.8%

Length

2024-04-21T00:08:09.993235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:08:10.332526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1722
66.2%
na 879
33.8%

발한실여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing72
Missing (%)2.8%
Memory size5.2 KiB
False
2528 
True
 
1
(Missing)
 
72
ValueCountFrequency (%)
False 2528
97.2%
True 1
 
< 0.1%
(Missing) 72
 
2.8%
2024-04-21T00:08:10.595472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

의자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size20.4 KiB
0
1721 
<NA>
877 
9
 
2
1
 
1

Length

Max length4
Median length1
Mean length2.011534
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1721
66.2%
<NA> 877
33.7%
9 2
 
0.1%
1 1
 
< 0.1%

Length

2024-04-21T00:08:10.942847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:08:11.206692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1721
66.2%
na 877
33.7%
9 2
 
0.1%
1 1
 
< 0.1%
Distinct5
Distinct (%)83.3%
Missing2595
Missing (%)99.8%
Memory size20.4 KiB
2024-04-21T00:08:11.788651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length15.5
Mean length16.333333
Min length4

Characters and Unicode

Total characters98
Distinct characters53
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

Unique4 ?
Unique (%)66.7%

Sample

1st row계약기간연장
2nd row가설건축물
3rd row공중위생관리법시행령 제3조제1호의 규정에 의한 건축물규모 이하의 건축물을 청소하는 경우에 한함
4th row계약기간연장
5th row산학협력
ValueCountFrequency (%)
계약기간연장 2
 
11.8%
가설건축물 1
 
5.9%
공중위생관리법시행령 1
 
5.9%
제3조제1호의 1
 
5.9%
규정에 1
 
5.9%
의한 1
 
5.9%
건축물규모 1
 
5.9%
이하의 1
 
5.9%
건축물을 1
 
5.9%
청소하는 1
 
5.9%
Other values (6) 6
35.3%
2024-04-21T00:08:12.838155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11
 
11.2%
0 6
 
6.1%
3 4
 
4.1%
3
 
3.1%
3
 
3.1%
3
 
3.1%
3
 
3.1%
3
 
3.1%
3
 
3.1%
2 3
 
3.1%
Other values (43) 56
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68
69.4%
Decimal Number 15
 
15.3%
Space Separator 11
 
11.2%
Other Punctuation 2
 
2.0%
Open Punctuation 1
 
1.0%
Close Punctuation 1
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3
 
4.4%
3
 
4.4%
3
 
4.4%
3
 
4.4%
3
 
4.4%
3
 
4.4%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
Other values (34) 42
61.8%
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 68
69.4%
Common 30
30.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3
 
4.4%
3
 
4.4%
3
 
4.4%
3
 
4.4%
3
 
4.4%
3
 
4.4%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
Other values (34) 42
61.8%
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 68
69.4%
ASCII 30
30.6%

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
 
4.4%
3
 
4.4%
3
 
4.4%
3
 
4.4%
3
 
4.4%
3
 
4.4%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
Other values (34) 42
61.8%

조건부허가시작일자
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size20.4 KiB
<NA>
2595 
20140301
 
2
20140212
 
1
20060825
 
1
20060106
 
1

Length

Max length8
Median length4
Mean length4.0092272
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> 2595
99.8%
20140301 2
 
0.1%
20140212 1
 
< 0.1%
20060825 1
 
< 0.1%
20060106 1
 
< 0.1%
20100210 1
 
< 0.1%

Length

2024-04-21T00:08:13.308892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:08:13.707083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2595
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%
Missing2594
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean20126313
Minimum20061231
Maximum20200415
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.0 KiB
2024-04-21T00:08:14.085476image/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
2024-04-21T00:08:14.542366image/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) 2594
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 size20.4 KiB
<NA>
1726 
임대
833 
자가
 
42

Length

Max length4
Median length4
Mean length3.3271819
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1726
66.4%
임대 833
32.0%
자가 42
 
1.6%

Length

2024-04-21T00:08:15.125961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:08:15.515725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1726
66.4%
임대 833
32.0%
자가 42
 
1.6%

세탁기수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.4 KiB
0
1546 
<NA>
1055 

Length

Max length4
Median length1
Mean length2.2168397
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1546
59.4%
<NA> 1055
40.6%

Length

2024-04-21T00:08:15.898933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:08:16.247071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1546
59.4%
na 1055
40.6%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct19
Distinct (%)3.9%
Missing2111
Missing (%)81.2%
Infinite0
Infinite (%)0.0%
Mean2.2959184
Minimum0
Maximum340
Zeros428
Zeros (%)16.5%
Negative0
Negative (%)0.0%
Memory size23.0 KiB
2024-04-21T00:08:16.561752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3.55
Maximum340
Range340
Interquartile range (IQR)0

Descriptive statistics

Standard deviation18.346812
Coefficient of variation (CV)7.9910558
Kurtosis241.88499
Mean2.2959184
Median Absolute Deviation (MAD)0
Skewness14.227457
Sum1125
Variance336.6055
MonotonicityNot monotonic
2024-04-21T00:08:16.981292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 428
 
16.5%
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) 2111
81.2%
ValueCountFrequency (%)
0 428
16.5%
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 

Distinct26
Distinct (%)4.9%
Missing2066
Missing (%)79.4%
Infinite0
Infinite (%)0.0%
Mean4.5158879
Minimum0
Maximum560
Zeros361
Zeros (%)13.9%
Negative0
Negative (%)0.0%
Memory size23.0 KiB
2024-04-21T00:08:17.291990image/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 deviation30.121341
Coefficient of variation (CV)6.6700816
Kurtosis226.00913
Mean4.5158879
Median Absolute Deviation (MAD)0
Skewness13.571795
Sum2416
Variance907.29516
MonotonicityNot monotonic
2024-04-21T00:08:17.500267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 361
 
13.9%
2 44
 
1.7%
1 41
 
1.6%
3 25
 
1.0%
4 17
 
0.7%
5 15
 
0.6%
8 7
 
0.3%
183 4
 
0.2%
30 2
 
0.1%
7 2
 
0.1%
Other values (16) 17
 
0.7%
(Missing) 2066
79.4%
ValueCountFrequency (%)
0 361
13.9%
1 41
 
1.6%
2 44
 
1.7%
3 25
 
1.0%
4 17
 
0.7%
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 size20.4 KiB
0
1406 
<NA>
1195 

Length

Max length4
Median length1
Mean length2.378316
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1406
54.1%
<NA> 1195
45.9%

Length

2024-04-21T00:08:17.848965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:08:18.140139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1406
54.1%
na 1195
45.9%

침대수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.4 KiB
0
1345 
<NA>
1256 

Length

Max length4
Median length1
Mean length2.4486736
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1345
51.7%
<NA> 1256
48.3%

Length

2024-04-21T00:08:18.326219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:08:18.505467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1345
51.7%
na 1256
48.3%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
False
2600 
True
 
1
ValueCountFrequency (%)
False 2600
> 99.9%
True 1
 
< 0.1%
2024-04-21T00:08:18.705873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Unnamed: 50
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2601
Missing (%)100.0%
Memory size23.0 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_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>
34건물위생관리업09_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>
45건물위생관리업09_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>
56건물위생관리업09_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>
67건물위생관리업09_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>
78건물위생관리업09_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>
89건물위생관리업09_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>
910건물위생관리업09_30_04_P33200003320000-206-2000-0000320000706<NA>3폐업2폐업20161130<NA><NA><NA>051 467831283.14616826부산광역시 북구 만덕동 296번지 신만덕상가 3층부산광역시 북구 만덕2로 13 (만덕동, 신만덕상가 3층)46607세호종합관리(주)20130717140653I2018-08-31 23:59:59.0건물위생관리업385432.214042192215.717721건물위생관리업003000000N0<NA><NA><NA>임대0<NA><NA>00N<NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부Unnamed: 50
25912592건물위생관리업09_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>
25922593건물위생관리업09_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>
25932594건물위생관리업09_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>
25942595건물위생관리업09_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>
25952596건물위생관리업09_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>
25962597건물위생관리업09_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>
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25982599건물위생관리업09_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>
25992600건물위생관리업09_30_04_P33600003360000-206-2013-0000120130204<NA>1영업/정상1영업<NA><NA><NA><NA>051 971 166354.00618807부산광역시 강서구 대저2동 2440-3번지부산광역시 강서구 공항앞길221번길 56 (대저2동)46720(주)이레환경20170814143318I2018-08-31 23:59:59.0건물위생관리업377875.274835187827.464522건물위생관리업001100000N0<NA><NA><NA><NA>0<NA><NA>00Y<NA>
26002601건물위생관리업09_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>