Overview

Dataset statistics

Number of variables51
Number of observations2588
Missing cells31261
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

Description2021-01-04
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 (53.3%)Imbalance
조건부허가시작일자 is highly imbalanced (98.9%)Imbalance
다중이용업소여부 is highly imbalanced (99.5%)Imbalance
인허가취소일자 has 2588 (100.0%) missing valuesMissing
폐업일자 has 939 (36.3%) missing valuesMissing
휴업시작일자 has 2588 (100.0%) missing valuesMissing
휴업종료일자 has 2588 (100.0%) missing valuesMissing
재개업일자 has 2588 (100.0%) missing valuesMissing
소재지전화 has 607 (23.5%) missing valuesMissing
소재지우편번호 has 34 (1.3%) missing valuesMissing
도로명전체주소 has 783 (30.3%) missing valuesMissing
도로명우편번호 has 827 (32.0%) missing valuesMissing
좌표정보(x) has 70 (2.7%) missing valuesMissing
좌표정보(y) has 70 (2.7%) missing valuesMissing
건물지상층수 has 423 (16.3%) missing valuesMissing
건물지하층수 has 581 (22.4%) missing valuesMissing
사용시작지상층 has 674 (26.0%) missing valuesMissing
사용끝지상층 has 936 (36.2%) missing valuesMissing
사용시작지하층 has 1384 (53.5%) missing valuesMissing
사용끝지하층 has 1561 (60.3%) missing valuesMissing
발한실여부 has 72 (2.8%) missing valuesMissing
조건부허가신고사유 has 2582 (99.8%) missing valuesMissing
조건부허가종료일자 has 2581 (99.7%) missing valuesMissing
여성종사자수 has 2102 (81.2%) missing valuesMissing
남성종사자수 has 2057 (79.5%) missing valuesMissing
Unnamed: 50 has 2588 (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 617 (23.8%) zerosZeros
건물지하층수 has 1144 (44.2%) zerosZeros
사용시작지상층 has 352 (13.6%) zerosZeros
사용끝지상층 has 344 (13.3%) zerosZeros
사용시작지하층 has 1031 (39.8%) zerosZeros
사용끝지하층 has 870 (33.6%) zerosZeros
여성종사자수 has 424 (16.4%) zerosZeros
남성종사자수 has 358 (13.8%) zerosZeros

Reproduction

Analysis started2024-04-20 15:14:41.907766
Analysis finished2024-04-20 15:14:44.117376
Duration2.21 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct2588
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1294.5
Minimum1
Maximum2588
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.9 KiB
2024-04-21T00:14:44.318159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile130.35
Q1647.75
median1294.5
Q31941.25
95-th percentile2458.65
Maximum2588
Range2587
Interquartile range (IQR)1293.5

Descriptive statistics

Standard deviation747.23557
Coefficient of variation (CV)0.57723876
Kurtosis-1.2
Mean1294.5
Median Absolute Deviation (MAD)647
Skewness0
Sum3350166
Variance558361
MonotonicityStrictly increasing
2024-04-21T00:14:44.749237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1701 1
 
< 0.1%
1723 1
 
< 0.1%
1724 1
 
< 0.1%
1725 1
 
< 0.1%
1726 1
 
< 0.1%
1727 1
 
< 0.1%
1728 1
 
< 0.1%
1729 1
 
< 0.1%
1730 1
 
< 0.1%
Other values (2578) 2578
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 (%)
2588 1
< 0.1%
2587 1
< 0.1%
2586 1
< 0.1%
2585 1
< 0.1%
2584 1
< 0.1%
2583 1
< 0.1%
2582 1
< 0.1%
2581 1
< 0.1%
2580 1
< 0.1%
2579 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size20.3 KiB
건물위생관리업
2588 

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 2588
100.0%

Length

2024-04-21T00:14:45.033641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:14:45.261217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 2588
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size20.3 KiB
09_30_04_P
2588 

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 2588
100.0%

Length

2024-04-21T00:14:45.457860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:14:45.651891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_30_04_p 2588
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3325177.7
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.9 KiB
2024-04-21T00:14:45.844583image/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 deviation44550.837
Coefficient of variation (CV)0.013398032
Kurtosis-1.1231132
Mean3325177.7
Median Absolute Deviation (MAD)30000
Skewness0.20849
Sum8.60556 × 109
Variance1.9847771 × 109
MonotonicityNot monotonic
2024-04-21T00:14:46.108403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 353
13.6%
3300000 292
11.3%
3270000 238
9.2%
3400000 226
8.7%
3330000 202
7.8%
3370000 197
 
7.6%
3310000 160
 
6.2%
3350000 148
 
5.7%
3380000 138
 
5.3%
3320000 132
 
5.1%
Other values (6) 502
19.4%
ValueCountFrequency (%)
3250000 102
 
3.9%
3260000 75
 
2.9%
3270000 238
9.2%
3280000 27
 
1.0%
3290000 353
13.6%
3300000 292
11.3%
3310000 160
6.2%
3320000 132
 
5.1%
3330000 202
7.8%
3340000 119
 
4.6%
ValueCountFrequency (%)
3400000 226
8.7%
3390000 128
4.9%
3380000 138
5.3%
3370000 197
7.6%
3360000 51
 
2.0%
3350000 148
5.7%
3340000 119
4.6%
3330000 202
7.8%
3320000 132
5.1%
3310000 160
6.2%

관리번호
Text

UNIQUE 

Distinct2588
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size20.3 KiB
2024-04-21T00:14:46.897482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters56936
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

Unique2588 ?
Unique (%)100.0%

Sample

1st row3260000-206-2011-00003
2nd row3380000-206-2019-00001
3rd row3320000-206-2005-00002
4th row3320000-206-2013-00002
5th row3320000-206-2011-00008
ValueCountFrequency (%)
3260000-206-2011-00003 1
 
< 0.1%
3320000-206-2018-00007 1
 
< 0.1%
3320000-206-2012-00006 1
 
< 0.1%
3400000-206-2011-00007 1
 
< 0.1%
3320000-206-2018-00003 1
 
< 0.1%
3320000-206-2016-00006 1
 
< 0.1%
3320000-206-2016-00002 1
 
< 0.1%
3320000-206-2009-00001 1
 
< 0.1%
3400000-206-2008-00001 1
 
< 0.1%
3400000-206-2010-00021 1
 
< 0.1%
Other values (2578) 2578
99.6%
2024-04-21T00:14:48.023952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 26429
46.4%
- 7764
 
13.6%
2 6635
 
11.7%
3 5068
 
8.9%
6 3242
 
5.7%
1 2790
 
4.9%
9 1498
 
2.6%
4 997
 
1.8%
7 983
 
1.7%
5 804
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49172
86.4%
Dash Punctuation 7764
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 26429
53.7%
2 6635
 
13.5%
3 5068
 
10.3%
6 3242
 
6.6%
1 2790
 
5.7%
9 1498
 
3.0%
4 997
 
2.0%
7 983
 
2.0%
5 804
 
1.6%
8 726
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 7764
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 56936
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 26429
46.4%
- 7764
 
13.6%
2 6635
 
11.7%
3 5068
 
8.9%
6 3242
 
5.7%
1 2790
 
4.9%
9 1498
 
2.6%
4 997
 
1.8%
7 983
 
1.7%
5 804
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56936
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 26429
46.4%
- 7764
 
13.6%
2 6635
 
11.7%
3 5068
 
8.9%
6 3242
 
5.7%
1 2790
 
4.9%
9 1498
 
2.6%
4 997
 
1.8%
7 983
 
1.7%
5 804
 
1.4%

인허가일자
Real number (ℝ)

Distinct1937
Distinct (%)74.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20086696
Minimum19870507
Maximum20201230
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.9 KiB
2024-04-21T00:14:48.389350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19870507
5-th percentile19960612
Q120040803
median20090927
Q320140612
95-th percentile20190721
Maximum20201230
Range330723
Interquartile range (IQR)99808.5

Descriptive statistics

Standard deviation71075.665
Coefficient of variation (CV)0.0035384448
Kurtosis-0.10631048
Mean20086696
Median Absolute Deviation (MAD)49901
Skewness-0.51042996
Sum5.1984369 × 1010
Variance5.0517502 × 109
MonotonicityNot monotonic
2024-04-21T00:14:48.769919image/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%
20000706 5
 
0.2%
20070614 5
 
0.2%
20140327 5
 
0.2%
20020403 5
 
0.2%
20101217 5
 
0.2%
20031125 5
 
0.2%
20140219 5
 
0.2%
Other values (1927) 2535
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 (%)
20201230 1
 
< 0.1%
20201221 1
 
< 0.1%
20201215 1
 
< 0.1%
20201209 1
 
< 0.1%
20201207 1
 
< 0.1%
20201203 1
 
< 0.1%
20201201 1
 
< 0.1%
20201130 1
 
< 0.1%
20201127 3
0.1%
20201126 1
 
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2588
Missing (%)100.0%
Memory size22.9 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.3 KiB
3
1649 
1
939 

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 1649
63.7%
1 939
36.3%

Length

2024-04-21T00:14:49.197267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:14:49.404171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1649
63.7%
1 939
36.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.3 KiB
폐업
1649 
영업/정상
939 

Length

Max length5
Median length2
Mean length3.0884853
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1649
63.7%
영업/정상 939
36.3%

Length

2024-04-21T00:14:49.636777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:14:49.885274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1649
63.7%
영업/정상 939
36.3%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.3 KiB
2
1649 
1
939 

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 1649
63.7%
1 939
36.3%

Length

2024-04-21T00:14:50.117038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:14:50.342602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1649
63.7%
1 939
36.3%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.3 KiB
폐업
1649 
영업
939 

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 1649
63.7%
영업 939
36.3%

Length

2024-04-21T00:14:50.562904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:14:50.837373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1649
63.7%
영업 939
36.3%

폐업일자
Real number (ℝ)

MISSING 

Distinct1205
Distinct (%)73.1%
Missing939
Missing (%)36.3%
Infinite0
Infinite (%)0.0%
Mean20115417
Minimum19880329
Maximum20201228
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.9 KiB
2024-04-21T00:14:51.367576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19880329
5-th percentile20020821
Q120070122
median20120905
Q320170208
95-th percentile20200310
Maximum20201228
Range320899
Interquartile range (IQR)100086

Descriptive statistics

Standard deviation59419.711
Coefficient of variation (CV)0.0029539389
Kurtosis-0.46336107
Mean20115417
Median Absolute Deviation (MAD)49977
Skewness-0.46165252
Sum3.3170322 × 1010
Variance3.5307021 × 109
MonotonicityNot monotonic
2024-04-21T00:14:51.820507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20180525 23
 
0.9%
20200428 15
 
0.6%
20030227 10
 
0.4%
20110217 10
 
0.4%
20180808 9
 
0.3%
20041213 8
 
0.3%
20170831 8
 
0.3%
20031124 8
 
0.3%
20031114 7
 
0.3%
20160527 7
 
0.3%
Other values (1195) 1544
59.7%
(Missing) 939
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 (%)
20201228 2
0.1%
20201223 1
< 0.1%
20201221 1
< 0.1%
20201218 1
< 0.1%
20201216 1
< 0.1%
20201215 1
< 0.1%
20201214 2
0.1%
20201211 1
< 0.1%
20201210 1
< 0.1%
20201202 2
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2588
Missing (%)100.0%
Memory size22.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2588
Missing (%)100.0%
Memory size22.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2588
Missing (%)100.0%
Memory size22.9 KiB

소재지전화
Text

MISSING 

Distinct1724
Distinct (%)87.0%
Missing607
Missing (%)23.5%
Memory size20.3 KiB
2024-04-21T00:14:52.962599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.204947
Min length3

Characters and Unicode

Total characters22197
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

Unique1533 ?
Unique (%)77.4%

Sample

1st row02 4647058
2nd row051 3410086
3rd row051 342 8377
4th row051 467 8313
5th row051 343 0110
ValueCountFrequency (%)
051 1758
37.2%
727 58
 
1.2%
070 55
 
1.2%
728 17
 
0.4%
724 15
 
0.3%
502 13
 
0.3%
557 12
 
0.3%
722 12
 
0.3%
342 11
 
0.2%
851 11
 
0.2%
Other values (1924) 2759
58.4%
2024-04-21T00:14:54.451873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 3473
15.6%
0 3389
15.3%
1 3248
14.6%
2757
12.4%
2 1581
7.1%
7 1528
6.9%
6 1386
 
6.2%
4 1369
 
6.2%
3 1314
 
5.9%
8 1242
 
5.6%
Other values (2) 910
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19439
87.6%
Space Separator 2757
 
12.4%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 3473
17.9%
0 3389
17.4%
1 3248
16.7%
2 1581
8.1%
7 1528
7.9%
6 1386
 
7.1%
4 1369
 
7.0%
3 1314
 
6.8%
8 1242
 
6.4%
9 909
 
4.7%
Space Separator
ValueCountFrequency (%)
2757
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22197
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 3473
15.6%
0 3389
15.3%
1 3248
14.6%
2757
12.4%
2 1581
7.1%
7 1528
6.9%
6 1386
 
6.2%
4 1369
 
6.2%
3 1314
 
5.9%
8 1242
 
5.6%
Other values (2) 910
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22197
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 3473
15.6%
0 3389
15.3%
1 3248
14.6%
2757
12.4%
2 1581
7.1%
7 1528
6.9%
6 1386
 
6.2%
4 1369
 
6.2%
3 1314
 
5.9%
8 1242
 
5.6%
Other values (2) 910
 
4.1%
Distinct1533
Distinct (%)59.8%
Missing24
Missing (%)0.9%
Memory size20.3 KiB
2024-04-21T00:14:55.784653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.8697348
Min length3

Characters and Unicode

Total characters12486
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

Unique1237 ?
Unique (%)48.2%

Sample

1st row.00
2nd row33.60
3rd row91.30
4th row46.29
5th row13.80
ValueCountFrequency (%)
00 341
 
13.3%
33.00 37
 
1.4%
66.00 21
 
0.8%
40.00 15
 
0.6%
30.00 14
 
0.5%
36.00 12
 
0.5%
49.50 12
 
0.5%
99.00 11
 
0.4%
12.00 10
 
0.4%
50.00 10
 
0.4%
Other values (1523) 2081
81.2%
2024-04-21T00:14:58.053243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2708
21.7%
. 2564
20.5%
1 1064
 
8.5%
2 982
 
7.9%
5 867
 
6.9%
3 848
 
6.8%
6 804
 
6.4%
4 771
 
6.2%
8 695
 
5.6%
7 594
 
4.8%
Other values (2) 589
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9917
79.4%
Other Punctuation 2569
 
20.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2708
27.3%
1 1064
 
10.7%
2 982
 
9.9%
5 867
 
8.7%
3 848
 
8.6%
6 804
 
8.1%
4 771
 
7.8%
8 695
 
7.0%
7 594
 
6.0%
9 584
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 2564
99.8%
, 5
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 12486
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2708
21.7%
. 2564
20.5%
1 1064
 
8.5%
2 982
 
7.9%
5 867
 
6.9%
3 848
 
6.8%
6 804
 
6.4%
4 771
 
6.2%
8 695
 
5.6%
7 594
 
4.8%
Other values (2) 589
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12486
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2708
21.7%
. 2564
20.5%
1 1064
 
8.5%
2 982
 
7.9%
5 867
 
6.9%
3 848
 
6.8%
6 804
 
6.4%
4 771
 
6.2%
8 695
 
5.6%
7 594
 
4.8%
Other values (2) 589
 
4.7%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct604
Distinct (%)23.6%
Missing34
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean610882.85
Minimum400410
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.9 KiB
2024-04-21T00:14:58.522480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum400410
5-th percentile601807
Q1607809.25
median611823
Q3614854
95-th percentile619912
Maximum619953
Range219543
Interquartile range (IQR)7044.75

Descriptive statistics

Standard deviation7042.3885
Coefficient of variation (CV)0.011528215
Kurtosis311.11222
Mean610882.85
Median Absolute Deviation (MAD)3992
Skewness-10.579277
Sum1.5601948 × 109
Variance49595236
MonotonicityNot monotonic
2024-04-21T00:14:58.973026image/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%
614844 26
 
1.0%
619953 26
 
1.0%
601838 25
 
1.0%
614865 23
 
0.9%
607804 21
 
0.8%
Other values (594) 2243
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%
Distinct2385
Distinct (%)92.7%
Missing14
Missing (%)0.5%
Memory size20.3 KiB
2024-04-21T00:15:00.028378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length45
Mean length25.465035
Min length2

Characters and Unicode

Total characters65547
Distinct characters399
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

Unique2227 ?
Unique (%)86.5%

Sample

1st row인천광역시 중구 덕교동 128-76번지
2nd row부산광역시 수영구 광안동 100-10
3rd row부산광역시 북구 덕천동 388-1번지 대방상가 304호
4th row부산광역시 북구 구포동 1256-15번지
5th row부산광역시 북구 덕천동 128-3번지 벽산아파트 상가동 101호
ValueCountFrequency (%)
부산광역시 2572
 
20.8%
부산진구 346
 
2.8%
동래구 292
 
2.4%
동구 237
 
1.9%
기장군 225
 
1.8%
해운대구 203
 
1.6%
연제구 196
 
1.6%
초량동 161
 
1.3%
남구 159
 
1.3%
금정구 148
 
1.2%
Other values (3109) 7843
63.3%
2024-04-21T00:15:01.665724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9811
 
15.0%
3179
 
4.8%
3176
 
4.8%
1 3165
 
4.8%
3131
 
4.8%
2671
 
4.1%
2600
 
4.0%
2580
 
3.9%
2515
 
3.8%
2434
 
3.7%
Other values (389) 30285
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38934
59.4%
Decimal Number 13839
 
21.1%
Space Separator 9811
 
15.0%
Dash Punctuation 2351
 
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 (%)
3179
 
8.2%
3176
 
8.2%
3131
 
8.0%
2671
 
6.9%
2600
 
6.7%
2580
 
6.6%
2515
 
6.5%
2434
 
6.3%
2396
 
6.2%
526
 
1.4%
Other values (342) 13726
35.3%
Uppercase Letter
ValueCountFrequency (%)
B 98
40.2%
T 76
31.1%
O 14
 
5.7%
A 9
 
3.7%
D 8
 
3.3%
S 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 3165
22.9%
2 1909
13.8%
3 1572
11.4%
4 1311
9.5%
0 1234
 
8.9%
5 1171
 
8.5%
6 1000
 
7.2%
7 936
 
6.8%
8 856
 
6.2%
9 685
 
4.9%
Lowercase Letter
ValueCountFrequency (%)
s 2
15.4%
k 2
15.4%
e 2
15.4%
d 1
7.7%
t 1
7.7%
o 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 (%)
9811
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2351
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 38934
59.4%
Common 26356
40.2%
Latin 257
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3179
 
8.2%
3176
 
8.2%
3131
 
8.0%
2671
 
6.9%
2600
 
6.7%
2580
 
6.6%
2515
 
6.5%
2434
 
6.3%
2396
 
6.2%
526
 
1.4%
Other values (342) 13726
35.3%
Latin
ValueCountFrequency (%)
B 98
38.1%
T 76
29.6%
O 14
 
5.4%
A 9
 
3.5%
D 8
 
3.1%
S 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 (%)
9811
37.2%
1 3165
 
12.0%
- 2351
 
8.9%
2 1909
 
7.2%
3 1572
 
6.0%
4 1311
 
5.0%
0 1234
 
4.7%
5 1171
 
4.4%
6 1000
 
3.8%
7 936
 
3.6%
Other values (9) 1896
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38934
59.4%
ASCII 26613
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9811
36.9%
1 3165
 
11.9%
- 2351
 
8.8%
2 1909
 
7.2%
3 1572
 
5.9%
4 1311
 
4.9%
0 1234
 
4.6%
5 1171
 
4.4%
6 1000
 
3.8%
7 936
 
3.5%
Other values (37) 2153
 
8.1%
Hangul
ValueCountFrequency (%)
3179
 
8.2%
3176
 
8.2%
3131
 
8.0%
2671
 
6.9%
2600
 
6.7%
2580
 
6.6%
2515
 
6.5%
2434
 
6.3%
2396
 
6.2%
526
 
1.4%
Other values (342) 13726
35.3%

도로명전체주소
Text

MISSING 

Distinct1728
Distinct (%)95.7%
Missing783
Missing (%)30.3%
Memory size20.3 KiB
2024-04-21T00:15:02.975347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length49
Mean length31.647645
Min length20

Characters and Unicode

Total characters57124
Distinct characters415
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

Unique1661 ?
Unique (%)92.0%

Sample

1st row인천광역시 중구 마시란로 51-33 (덕교동)
2nd row부산광역시 수영구 무학로9번길 46, 1층 (광안동)
3rd row부산광역시 북구 시랑로118번길 56 (구포동)
4th row부산광역시 북구 만덕3로16번길 45, 상가동 101호 (덕천동, 벽산아파트)
5th row부산광역시 북구 덕천로276번길 28 (만덕동)
ValueCountFrequency (%)
부산광역시 1804
 
16.3%
부산진구 245
 
2.2%
2층 224
 
2.0%
1층 214
 
1.9%
동래구 201
 
1.8%
기장군 193
 
1.7%
해운대구 157
 
1.4%
연제구 142
 
1.3%
동구 130
 
1.2%
3층 128
 
1.2%
Other values (2400) 7635
69.0%
2024-04-21T00:15:04.816475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9270
 
16.2%
2331
 
4.1%
2269
 
4.0%
2252
 
3.9%
1 2187
 
3.8%
1909
 
3.3%
1888
 
3.3%
1811
 
3.2%
1707
 
3.0%
1699
 
3.0%
Other values (405) 29801
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33050
57.9%
Decimal Number 9410
 
16.5%
Space Separator 9270
 
16.2%
Open Punctuation 1688
 
3.0%
Close Punctuation 1688
 
3.0%
Other Punctuation 1589
 
2.8%
Dash Punctuation 307
 
0.5%
Uppercase Letter 108
 
0.2%
Lowercase Letter 11
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2331
 
7.1%
2269
 
6.9%
2252
 
6.8%
1909
 
5.8%
1888
 
5.7%
1811
 
5.5%
1707
 
5.2%
1699
 
5.1%
934
 
2.8%
897
 
2.7%
Other values (362) 15353
46.5%
Uppercase Letter
ValueCountFrequency (%)
B 35
32.4%
A 20
18.5%
C 10
 
9.3%
E 8
 
7.4%
S 7
 
6.5%
P 7
 
6.5%
O 4
 
3.7%
I 4
 
3.7%
T 4
 
3.7%
K 2
 
1.9%
Other values (6) 7
 
6.5%
Decimal Number
ValueCountFrequency (%)
1 2187
23.2%
2 1571
16.7%
3 1141
12.1%
0 868
 
9.2%
4 792
 
8.4%
5 697
 
7.4%
6 590
 
6.3%
7 552
 
5.9%
8 523
 
5.6%
9 489
 
5.2%
Lowercase Letter
ValueCountFrequency (%)
e 2
18.2%
k 2
18.2%
s 2
18.2%
u 1
9.1%
b 1
9.1%
y 1
9.1%
d 1
9.1%
h 1
9.1%
Other Punctuation
ValueCountFrequency (%)
, 1579
99.4%
/ 6
 
0.4%
. 2
 
0.1%
@ 2
 
0.1%
Space Separator
ValueCountFrequency (%)
9270
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1688
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1688
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 307
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33050
57.9%
Common 23955
41.9%
Latin 119
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2331
 
7.1%
2269
 
6.9%
2252
 
6.8%
1909
 
5.8%
1888
 
5.7%
1811
 
5.5%
1707
 
5.2%
1699
 
5.1%
934
 
2.8%
897
 
2.7%
Other values (362) 15353
46.5%
Latin
ValueCountFrequency (%)
B 35
29.4%
A 20
16.8%
C 10
 
8.4%
E 8
 
6.7%
S 7
 
5.9%
P 7
 
5.9%
O 4
 
3.4%
I 4
 
3.4%
T 4
 
3.4%
K 2
 
1.7%
Other values (14) 18
15.1%
Common
ValueCountFrequency (%)
9270
38.7%
1 2187
 
9.1%
( 1688
 
7.0%
) 1688
 
7.0%
, 1579
 
6.6%
2 1571
 
6.6%
3 1141
 
4.8%
0 868
 
3.6%
4 792
 
3.3%
5 697
 
2.9%
Other values (9) 2474
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33050
57.9%
ASCII 24074
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9270
38.5%
1 2187
 
9.1%
( 1688
 
7.0%
) 1688
 
7.0%
, 1579
 
6.6%
2 1571
 
6.5%
3 1141
 
4.7%
0 868
 
3.6%
4 792
 
3.3%
5 697
 
2.9%
Other values (33) 2593
 
10.8%
Hangul
ValueCountFrequency (%)
2331
 
7.1%
2269
 
6.9%
2252
 
6.8%
1909
 
5.8%
1888
 
5.7%
1811
 
5.5%
1707
 
5.2%
1699
 
5.1%
934
 
2.8%
897
 
2.7%
Other values (362) 15353
46.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct850
Distinct (%)48.3%
Missing827
Missing (%)32.0%
Infinite0
Infinite (%)0.0%
Mean47615.592
Minimum22385
Maximum49524
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.9 KiB
2024-04-21T00:15:05.236466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22385
5-th percentile46037
Q146966
median47709
Q348403
95-th percentile49261
Maximum49524
Range27139
Interquartile range (IQR)1437

Descriptive statistics

Standard deviation1146.3482
Coefficient of variation (CV)0.024075059
Kurtosis131.86944
Mean47615.592
Median Absolute Deviation (MAD)726
Skewness-6.0571409
Sum83851057
Variance1314114.2
MonotonicityNot monotonic
2024-04-21T00:15:05.683771image/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%
48093 14
 
0.5%
47247 14
 
0.5%
48059 13
 
0.5%
48060 12
 
0.5%
47246 11
 
0.4%
47243 11
 
0.4%
Other values (840) 1596
61.7%
(Missing) 827
32.0%
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 3
0.1%
49502 1
 
< 0.1%
49497 1
 
< 0.1%
49495 1
 
< 0.1%
49490 1
 
< 0.1%
49483 1
 
< 0.1%
Distinct2203
Distinct (%)85.1%
Missing0
Missing (%)0.0%
Memory size20.3 KiB
2024-04-21T00:15:06.569892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length22
Mean length7.1989954
Min length2

Characters and Unicode

Total characters18631
Distinct characters537
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

Unique1900 ?
Unique (%)73.4%

Sample

1st row(주)성수인력
2nd row청소협동조합 청소하는사람들 부산경남본점
3rd row(주)천우이엔지
4th row신흥
5th row신항엘엠에스(주)
ValueCountFrequency (%)
주식회사 164
 
5.5%
16
 
0.5%
주)만비종합관리 7
 
0.2%
시스템 7
 
0.2%
주)만송 7
 
0.2%
청소나라 6
 
0.2%
그린산업 6
 
0.2%
주)금강종합개발 6
 
0.2%
유한회사 5
 
0.2%
환경 5
 
0.2%
Other values (2314) 2762
92.3%
2024-04-21T00:15:07.923396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1468
 
7.9%
) 1306
 
7.0%
( 1270
 
6.8%
552
 
3.0%
443
 
2.4%
406
 
2.2%
375
 
2.0%
327
 
1.8%
326
 
1.7%
315
 
1.7%
Other values (527) 11843
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15266
81.9%
Close Punctuation 1306
 
7.0%
Open Punctuation 1270
 
6.8%
Space Separator 406
 
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 (%)
1468
 
9.6%
552
 
3.6%
443
 
2.9%
375
 
2.5%
327
 
2.1%
326
 
2.1%
315
 
2.1%
296
 
1.9%
290
 
1.9%
241
 
1.6%
Other values (475) 10633
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%
r 4
 
7.4%
l 4
 
7.4%
n 4
 
7.4%
t 3
 
5.6%
c 3
 
5.6%
i 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%
. 10
26.3%
, 6
 
15.8%
· 4
 
10.5%
2
 
5.3%
Other Symbol
ValueCountFrequency (%)
14
93.3%
1
 
6.7%
Close Punctuation
ValueCountFrequency (%)
) 1306
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1270
100.0%
Space Separator
ValueCountFrequency (%)
406
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15281
82.0%
Common 3058
 
16.4%
Latin 292
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1468
 
9.6%
552
 
3.6%
443
 
2.9%
375
 
2.5%
327
 
2.1%
326
 
2.1%
315
 
2.1%
296
 
1.9%
290
 
1.9%
241
 
1.6%
Other values (477) 10648
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%
e 13
 
4.5%
T 13
 
4.5%
Other values (24) 100
34.2%
Common
ValueCountFrequency (%)
) 1306
42.7%
( 1270
41.5%
406
 
13.3%
1 16
 
0.5%
& 16
 
0.5%
. 10
 
0.3%
2 8
 
0.3%
, 6
 
0.2%
· 4
 
0.1%
4 3
 
0.1%
Other values (6) 13
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15266
81.9%
ASCII 3344
 
17.9%
None 21
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1468
 
9.6%
552
 
3.6%
443
 
2.9%
375
 
2.5%
327
 
2.1%
326
 
2.1%
315
 
2.1%
296
 
1.9%
290
 
1.9%
241
 
1.6%
Other values (475) 10633
69.7%
ASCII
ValueCountFrequency (%)
) 1306
39.1%
( 1270
38.0%
406
 
12.1%
C 40
 
1.2%
E 22
 
0.7%
S 22
 
0.7%
B 18
 
0.5%
G 17
 
0.5%
M 16
 
0.5%
1 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)

Distinct2333
Distinct (%)90.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0129362 × 1013
Minimum1.9990201 × 1013
Maximum2.020123 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.9 KiB
2024-04-21T00:15:08.182835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990201 × 1013
5-th percentile2.0030212 × 1013
Q12.0080522 × 1013
median2.0140513 × 1013
Q32.0181103 × 1013
95-th percentile2.0200814 × 1013
Maximum2.020123 × 1013
Range2.1102914 × 1011
Interquartile range (IQR)1.005808 × 1011

Descriptive statistics

Standard deviation6.0493607 × 1010
Coefficient of variation (CV)0.0030052421
Kurtosis-0.94809328
Mean2.0129362 × 1013
Median Absolute Deviation (MAD)4.9695484 × 1010
Skewness-0.54447554
Sum5.2094788 × 1016
Variance3.6594764 × 1021
MonotonicityNot monotonic
2024-04-21T00:15:08.456160image/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%
20030404000000 10
 
0.4%
20021112000000 10
 
0.4%
20051110000000 10
 
0.4%
20030521000000 8
 
0.3%
20020403000000 8
 
0.3%
Other values (2323) 2473
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 (%)
20201230143123 1
< 0.1%
20201228183134 1
< 0.1%
20201228183116 1
< 0.1%
20201224115639 1
< 0.1%
20201224100902 1
< 0.1%
20201223163030 1
< 0.1%
20201223110700 1
< 0.1%
20201223094115 1
< 0.1%
20201223091457 1
< 0.1%
20201222103438 1
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.3 KiB
I
2021 
U
567 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 2021
78.1%
U 567
 
21.9%

Length

2024-04-21T00:15:08.693777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:15:08.872523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2021
78.1%
u 567
 
21.9%
Distinct440
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size20.3 KiB
Minimum2018-08-31 23:59:59
Maximum2021-01-01 00:23:05
2024-04-21T00:15:09.176583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T00:15:09.551323image/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 size20.3 KiB
건물위생관리업
2559 
건물위생관리업 기타
 
21
<NA>
 
8

Length

Max length10
Median length7
Mean length7.0150696
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 2559
98.9%
건물위생관리업 기타 21
 
0.8%
<NA> 8
 
0.3%

Length

2024-04-21T00:15:09.798984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:15:09.991657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 2580
98.9%
기타 21
 
0.8%
na 8
 
0.3%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct1932
Distinct (%)76.7%
Missing70
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean389113.85
Minimum148671.32
Maximum408081.98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.9 KiB
2024-04-21T00:15:10.210035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum148671.32
5-th percentile380110.72
Q1385778.65
median388599.34
Q3391427.31
95-th percentile403741.28
Maximum408081.98
Range259410.66
Interquartile range (IQR)5648.6607

Descriptive statistics

Standard deviation8026.2098
Coefficient of variation (CV)0.020626893
Kurtosis319.61395
Mean389113.85
Median Absolute Deviation (MAD)2826.3652
Skewness-10.300727
Sum9.7978866 × 108
Variance64420043
MonotonicityNot monotonic
2024-04-21T00:15:10.465785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
395615.201853958 13
 
0.5%
388310.086924943 9
 
0.3%
391411.212179843 9
 
0.3%
396180.621244719 9
 
0.3%
380482.767624189 9
 
0.3%
387927.951172724 9
 
0.3%
387225.613588405 8
 
0.3%
387869.134317928 8
 
0.3%
407871.508884898 8
 
0.3%
386351.941329364 8
 
0.3%
Other values (1922) 2428
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 

Distinct1932
Distinct (%)76.7%
Missing70
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean188411.49
Minimum174156.62
Maximum436093.42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.9 KiB
2024-04-21T00:15:10.853001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174156.62
5-th percentile179713.91
Q1183987.07
median187548.91
Q3191384.89
95-th percentile203524.77
Maximum436093.42
Range261936.8
Interquartile range (IQR)7397.8198

Descriptive statistics

Standard deviation8110.0643
Coefficient of variation (CV)0.043044426
Kurtosis344.95819
Mean188411.49
Median Absolute Deviation (MAD)3712.9372
Skewness11.731889
Sum4.7442013 × 108
Variance65773143
MonotonicityNot monotonic
2024-04-21T00:15:11.262934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
186406.750870936 13
 
0.5%
183883.854898063 9
 
0.3%
184052.409245407 9
 
0.3%
186522.35047527 9
 
0.3%
185582.274947583 9
 
0.3%
186582.791097672 9
 
0.3%
186408.726533861 8
 
0.3%
186381.28184674 8
 
0.3%
205389.277197702 8
 
0.3%
182468.78681462 8
 
0.3%
Other values (1922) 2428
93.8%
(Missing) 70
 
2.7%
ValueCountFrequency (%)
174156.617297535 1
< 0.1%
174213.492106852 2
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 size20.3 KiB
건물위생관리업
2559 
건물위생관리업 기타
 
21
<NA>
 
8

Length

Max length10
Median length7
Mean length7.0150696
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 2559
98.9%
건물위생관리업 기타 21
 
0.8%
<NA> 8
 
0.3%

Length

2024-04-21T00:15:11.976320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:15:12.313106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 2580
98.9%
기타 21
 
0.8%
na 8
 
0.3%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct30
Distinct (%)1.4%
Missing423
Missing (%)16.3%
Infinite0
Infinite (%)0.0%
Mean3.7528868
Minimum0
Maximum51
Zeros617
Zeros (%)23.8%
Negative0
Negative (%)0.0%
Memory size22.9 KiB
2024-04-21T00:15:12.667582image/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 deviation4.5963094
Coefficient of variation (CV)1.2247397
Kurtosis14.596515
Mean3.7528868
Median Absolute Deviation (MAD)2
Skewness2.9107916
Sum8125
Variance21.12606
MonotonicityNot monotonic
2024-04-21T00:15:13.102914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 617
23.8%
4 350
13.5%
3 249
9.6%
5 232
 
9.0%
2 229
 
8.8%
1 109
 
4.2%
6 87
 
3.4%
7 49
 
1.9%
10 40
 
1.5%
8 35
 
1.4%
Other values (20) 168
 
6.5%
(Missing) 423
16.3%
ValueCountFrequency (%)
0 617
23.8%
1 109
 
4.2%
2 229
 
8.8%
3 249
9.6%
4 350
13.5%
5 232
 
9.0%
6 87
 
3.4%
7 49
 
1.9%
8 35
 
1.4%
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%
Missing581
Missing (%)22.4%
Infinite0
Infinite (%)0.0%
Mean0.6118585
Minimum0
Maximum8
Zeros1144
Zeros (%)44.2%
Negative0
Negative (%)0.0%
Memory size22.9 KiB
2024-04-21T00:15:13.489137image/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 deviation0.9625691
Coefficient of variation (CV)1.5731891
Kurtosis9.5890545
Mean0.6118585
Median Absolute Deviation (MAD)0
Skewness2.6535243
Sum1228
Variance0.92653927
MonotonicityNot monotonic
2024-04-21T00:15:13.882339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 1144
44.2%
1 680
26.3%
2 92
 
3.6%
3 40
 
1.5%
5 22
 
0.9%
4 21
 
0.8%
6 7
 
0.3%
8 1
 
< 0.1%
(Missing) 581
22.4%
ValueCountFrequency (%)
0 1144
44.2%
1 680
26.3%
2 92
 
3.6%
3 40
 
1.5%
4 21
 
0.8%
5 22
 
0.9%
6 7
 
0.3%
8 1
 
< 0.1%
ValueCountFrequency (%)
8 1
 
< 0.1%
6 7
 
0.3%
5 22
 
0.9%
4 21
 
0.8%
3 40
 
1.5%
2 92
 
3.6%
1 680
26.3%
0 1144
44.2%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct25
Distinct (%)1.3%
Missing674
Missing (%)26.0%
Infinite0
Infinite (%)0.0%
Mean2.6452456
Minimum0
Maximum48
Zeros352
Zeros (%)13.6%
Negative0
Negative (%)0.0%
Memory size22.9 KiB
2024-04-21T00:15:14.299820image/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 deviation3.2413076
Coefficient of variation (CV)1.2253334
Kurtosis28.667829
Mean2.6452456
Median Absolute Deviation (MAD)1
Skewness3.8817024
Sum5063
Variance10.506075
MonotonicityNot monotonic
2024-04-21T00:15:14.699701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
2 455
17.6%
1 417
16.1%
0 352
13.6%
3 279
10.8%
4 146
 
5.6%
5 70
 
2.7%
6 44
 
1.7%
7 35
 
1.4%
9 19
 
0.7%
8 19
 
0.7%
Other values (15) 78
 
3.0%
(Missing) 674
26.0%
ValueCountFrequency (%)
0 352
13.6%
1 417
16.1%
2 455
17.6%
3 279
10.8%
4 146
 
5.6%
5 70
 
2.7%
6 44
 
1.7%
7 35
 
1.4%
8 19
 
0.7%
9 19
 
0.7%
ValueCountFrequency (%)
48 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%
15 8
0.3%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct24
Distinct (%)1.5%
Missing936
Missing (%)36.2%
Infinite0
Infinite (%)0.0%
Mean2.5266344
Minimum0
Maximum48
Zeros344
Zeros (%)13.3%
Negative0
Negative (%)0.0%
Memory size22.9 KiB
2024-04-21T00:15:15.096615image/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 deviation3.2426433
Coefficient of variation (CV)1.2833844
Kurtosis32.170578
Mean2.5266344
Median Absolute Deviation (MAD)1
Skewness4.1343839
Sum4174
Variance10.514735
MonotonicityNot monotonic
2024-04-21T00:15:15.526510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
2 381
14.7%
1 362
 
14.0%
0 344
 
13.3%
3 232
 
9.0%
4 126
 
4.9%
5 49
 
1.9%
6 41
 
1.6%
7 29
 
1.1%
8 12
 
0.5%
10 10
 
0.4%
Other values (14) 66
 
2.6%
(Missing) 936
36.2%
ValueCountFrequency (%)
0 344
13.3%
1 362
14.0%
2 381
14.7%
3 232
9.0%
4 126
 
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%
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%
14 9
0.3%

사용시작지하층
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.5%
Missing1384
Missing (%)53.5%
Infinite0
Infinite (%)0.0%
Mean0.15614618
Minimum0
Maximum5
Zeros1031
Zeros (%)39.8%
Negative0
Negative (%)0.0%
Memory size22.9 KiB
2024-04-21T00:15:15.906518image/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 deviation0.42240309
Coefficient of variation (CV)2.7051772
Kurtosis27.747593
Mean0.15614618
Median Absolute Deviation (MAD)0
Skewness4.0309878
Sum188
Variance0.17842437
MonotonicityNot monotonic
2024-04-21T00:15:16.250327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 1031
39.8%
1 166
 
6.4%
2 3
 
0.1%
4 2
 
0.1%
3 1
 
< 0.1%
5 1
 
< 0.1%
(Missing) 1384
53.5%
ValueCountFrequency (%)
0 1031
39.8%
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 1031
39.8%

사용끝지하층
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.7%
Missing1561
Missing (%)60.3%
Infinite0
Infinite (%)0.0%
Mean0.17721519
Minimum0
Maximum10
Zeros870
Zeros (%)33.6%
Negative0
Negative (%)0.0%
Memory size22.9 KiB
2024-04-21T00:15:16.589677image/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 deviation0.53507285
Coefficient of variation (CV)3.0193397
Kurtosis120.35795
Mean0.17721519
Median Absolute Deviation (MAD)0
Skewness8.0838662
Sum182
Variance0.28630296
MonotonicityNot monotonic
2024-04-21T00:15:16.943673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 870
33.6%
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) 1561
60.3%
ValueCountFrequency (%)
0 870
33.6%
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%
0 870
33.6%

한실수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.3 KiB
0
1715 
<NA>
872 
1
 
1

Length

Max length4
Median length1
Mean length2.0108192
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1715
66.3%
<NA> 872
33.7%
1 1
 
< 0.1%

Length

2024-04-21T00:15:17.419017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:15:17.740048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1715
66.3%
na 872
33.7%
1 1
 
< 0.1%

양실수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.3 KiB
0
1715 
<NA>
872 
29
 
1

Length

Max length4
Median length1
Mean length2.0112056
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1715
66.3%
<NA> 872
33.7%
29 1
 
< 0.1%

Length

2024-04-21T00:15:17.947026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:15:18.142421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1715
66.3%
na 872
33.7%
29 1
 
< 0.1%

욕실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.3 KiB
0
1716 
<NA>
872 

Length

Max length4
Median length1
Mean length2.0108192
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1716
66.3%
<NA> 872
33.7%

Length

2024-04-21T00:15:18.357526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:15:18.536329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1716
66.3%
na 872
33.7%

발한실여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing72
Missing (%)2.8%
Memory size5.2 KiB
False
2515 
True
 
1
(Missing)
 
72
ValueCountFrequency (%)
False 2515
97.2%
True 1
 
< 0.1%
(Missing) 72
 
2.8%
2024-04-21T00:15:18.807459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

의자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size20.3 KiB
0
1715 
<NA>
870 
9
 
2
1
 
1

Length

Max length4
Median length1
Mean length2.0085008
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1715
66.3%
<NA> 870
33.6%
9 2
 
0.1%
1 1
 
< 0.1%

Length

2024-04-21T00:15:19.160951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:15:19.500755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1715
66.3%
na 870
33.6%
9 2
 
0.1%
1 1
 
< 0.1%
Distinct5
Distinct (%)83.3%
Missing2582
Missing (%)99.8%
Memory size20.3 KiB
2024-04-21T00:15:20.095632image/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%
2024-04-21T00:15:21.166919image/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 size20.3 KiB
<NA>
2582 
20140301
 
2
20140212
 
1
20060825
 
1
20060106
 
1

Length

Max length8
Median length4
Mean length4.0092736
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> 2582
99.8%
20140301 2
 
0.1%
20140212 1
 
< 0.1%
20060825 1
 
< 0.1%
20060106 1
 
< 0.1%
20100210 1
 
< 0.1%

Length

2024-04-21T00:15:21.600503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:15:21.953344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2582
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%
Missing2581
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean20126313
Minimum20061231
Maximum20200415
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.9 KiB
2024-04-21T00:15:22.217882image/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
2024-04-21T00:15:22.411630image/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) 2581
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 size20.3 KiB
<NA>
1716 
임대
831 
자가
 
41

Length

Max length4
Median length4
Mean length3.3261206
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1716
66.3%
임대 831
32.1%
자가 41
 
1.6%

Length

2024-04-21T00:15:22.655771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:15:22.898798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1716
66.3%
임대 831
32.1%
자가 41
 
1.6%

세탁기수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.3 KiB
0
1539 
<NA>
1049 

Length

Max length4
Median length1
Mean length2.2159969
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1539
59.5%
<NA> 1049
40.5%

Length

2024-04-21T00:15:23.209521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:15:23.425990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1539
59.5%
na 1049
40.5%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct19
Distinct (%)3.9%
Missing2102
Missing (%)81.2%
Infinite0
Infinite (%)0.0%
Mean2.3148148
Minimum0
Maximum340
Zeros424
Zeros (%)16.4%
Negative0
Negative (%)0.0%
Memory size22.9 KiB
2024-04-21T00:15:23.712549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3.75
Maximum340
Range340
Interquartile range (IQR)0

Descriptive statistics

Standard deviation18.421124
Coefficient of variation (CV)7.9579255
Kurtosis239.91025
Mean2.3148148
Median Absolute Deviation (MAD)0
Skewness14.169297
Sum1125
Variance339.3378
MonotonicityNot monotonic
2024-04-21T00:15:24.094146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 424
 
16.4%
1 22
 
0.9%
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) 2102
81.2%
ValueCountFrequency (%)
0 424
16.4%
1 22
 
0.9%
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%
Missing2057
Missing (%)79.5%
Infinite0
Infinite (%)0.0%
Mean4.5480226
Minimum0
Maximum560
Zeros358
Zeros (%)13.8%
Negative0
Negative (%)0.0%
Memory size22.9 KiB
2024-04-21T00:15:24.401140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31.5
95-th percentile8
Maximum560
Range560
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation30.232481
Coefficient of variation (CV)6.6473901
Kurtosis224.32433
Mean4.5480226
Median Absolute Deviation (MAD)0
Skewness13.521174
Sum2415
Variance914.00288
MonotonicityNot monotonic
2024-04-21T00:15:24.598594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 358
 
13.8%
2 44
 
1.7%
1 40
 
1.5%
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) 2057
79.5%
ValueCountFrequency (%)
0 358
13.8%
1 40
 
1.5%
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 size20.3 KiB
0
1399 
<NA>
1189 

Length

Max length4
Median length1
Mean length2.3782844
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1399
54.1%
<NA> 1189
45.9%

Length

2024-04-21T00:15:24.826759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:15:25.013672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1399
54.1%
na 1189
45.9%

침대수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.3 KiB
0
1338 
<NA>
1250 

Length

Max length4
Median length1
Mean length2.4489954
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1338
51.7%
<NA> 1250
48.3%

Length

2024-04-21T00:15:25.371821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:15:25.694099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1338
51.7%
na 1250
48.3%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
False
2587 
True
 
1
ValueCountFrequency (%)
False 2587
> 99.9%
True 1
 
< 0.1%
2024-04-21T00:15:25.911715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Unnamed: 50
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2588
Missing (%)100.0%
Memory size22.9 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부Unnamed: 50
01건물위생관리업09_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>
12건물위생관리업09_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>
23건물위생관리업09_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>
34건물위생관리업09_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>
45건물위생관리업09_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>
56건물위생관리업09_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>
67건물위생관리업09_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>
78건물위생관리업09_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>
89건물위생관리업09_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>
910건물위생관리업09_30_04_P33200003320000-206-2011-0000320110517<NA>3폐업2폐업20140311<NA><NA><NA>051 334 828220.00616807부산광역시 북구 구포동 1084-3번지 협진태양프라자 상가동 128호부산광역시 북구 백양대로 1029, 상가동 128호 (구포동, 협진태양프라자 )<NA>고성환경20140224150546I2018-08-31 23:59:59.0건물위생관리업381617.539583190548.761317건물위생관리업000000000N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부Unnamed: 50
25782579건물위생관리업09_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>
25792580건물위생관리업09_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>
25802581건물위생관리업09_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>
25812582건물위생관리업09_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>
25822583건물위생관리업09_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>
25832584건물위생관리업09_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>
25842585건물위생관리업09_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>
25852586건물위생관리업09_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>
25862587건물위생관리업09_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>
25872588건물위생관리업09_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>