Overview

Dataset statistics

Number of variables51
Number of observations2642
Missing cells31854
Missing cells (%)23.6%
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

Description2021-06-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123152

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
업태구분명 is highly imbalanced (93.7%)Imbalance
위생업태명 is highly imbalanced (93.7%)Imbalance
발한실여부 is highly imbalanced (99.5%)Imbalance
의자수 is highly imbalanced (53.2%)Imbalance
조건부허가시작일자 is highly imbalanced (98.9%)Imbalance
다중이용업소여부 is highly imbalanced (99.5%)Imbalance
인허가취소일자 has 2642 (100.0%) missing valuesMissing
폐업일자 has 965 (36.5%) missing valuesMissing
휴업시작일자 has 2642 (100.0%) missing valuesMissing
휴업종료일자 has 2642 (100.0%) missing valuesMissing
재개업일자 has 2642 (100.0%) missing valuesMissing
소재지전화 has 636 (24.1%) missing valuesMissing
소재지우편번호 has 34 (1.3%) missing valuesMissing
도로명전체주소 has 783 (29.6%) missing valuesMissing
도로명우편번호 has 827 (31.3%) missing valuesMissing
좌표정보(x) has 70 (2.6%) missing valuesMissing
좌표정보(y) has 70 (2.6%) missing valuesMissing
건물지상층수 has 434 (16.4%) missing valuesMissing
건물지하층수 has 593 (22.4%) missing valuesMissing
사용시작지상층 has 692 (26.2%) missing valuesMissing
사용끝지상층 has 955 (36.1%) missing valuesMissing
사용시작지하층 has 1408 (53.3%) missing valuesMissing
사용끝지하층 has 1584 (60.0%) missing valuesMissing
발한실여부 has 72 (2.7%) missing valuesMissing
조건부허가신고사유 has 2637 (99.8%) missing valuesMissing
조건부허가종료일자 has 2635 (99.7%) missing valuesMissing
여성종사자수 has 2128 (80.5%) missing valuesMissing
남성종사자수 has 2083 (78.8%) missing valuesMissing
Unnamed: 50 has 2642 (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 638 (24.1%) zerosZeros
건물지하층수 has 1173 (44.4%) zerosZeros
사용시작지상층 has 357 (13.5%) zerosZeros
사용끝지상층 has 351 (13.3%) zerosZeros
사용시작지하층 has 1058 (40.0%) zerosZeros
사용끝지하층 has 898 (34.0%) zerosZeros
여성종사자수 has 452 (17.1%) zerosZeros
남성종사자수 has 381 (14.4%) zerosZeros

Reproduction

Analysis started2024-04-20 15:12:25.358586
Analysis finished2024-04-20 15:12:27.521325
Duration2.16 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct2642
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1321.5
Minimum1
Maximum2642
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.3 KiB
2024-04-21T00:12:27.723157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile133.05
Q1661.25
median1321.5
Q31981.75
95-th percentile2509.95
Maximum2642
Range2641
Interquartile range (IQR)1320.5

Descriptive statistics

Standard deviation762.82403
Coefficient of variation (CV)0.57724104
Kurtosis-1.2
Mean1321.5
Median Absolute Deviation (MAD)660.5
Skewness0
Sum3491403
Variance581900.5
MonotonicityStrictly increasing
2024-04-21T00:12:28.058289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1757 1
 
< 0.1%
1759 1
 
< 0.1%
1760 1
 
< 0.1%
1761 1
 
< 0.1%
1762 1
 
< 0.1%
1763 1
 
< 0.1%
1764 1
 
< 0.1%
1765 1
 
< 0.1%
1766 1
 
< 0.1%
Other values (2632) 2632
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 (%)
2642 1
< 0.1%
2641 1
< 0.1%
2640 1
< 0.1%
2639 1
< 0.1%
2638 1
< 0.1%
2637 1
< 0.1%
2636 1
< 0.1%
2635 1
< 0.1%
2634 1
< 0.1%
2633 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size20.8 KiB
건물위생관리업
2642 

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 2642
100.0%

Length

2024-04-21T00:12:28.292372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:12:28.482822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 2642
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size20.8 KiB
09_30_04_P
2642 

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 2642
100.0%

Length

2024-04-21T00:12:28.650071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:12:28.806041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_30_04_p 2642
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3325548.8
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.3 KiB
2024-04-21T00:12:28.957139image/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 deviation44478.782
Coefficient of variation (CV)0.01337487
Kurtosis-1.1280687
Mean3325548.8
Median Absolute Deviation (MAD)30000
Skewness0.19611294
Sum8.7861 × 109
Variance1.9783621 × 109
MonotonicityNot monotonic
2024-04-21T00:12:29.193321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 357
13.5%
3300000 299
11.3%
3270000 240
9.1%
3400000 229
8.7%
3330000 211
8.0%
3370000 205
 
7.8%
3310000 162
 
6.1%
3350000 151
 
5.7%
3380000 141
 
5.3%
3390000 134
 
5.1%
Other values (6) 513
19.4%
ValueCountFrequency (%)
3250000 102
 
3.9%
3260000 75
 
2.8%
3270000 240
9.1%
3280000 27
 
1.0%
3290000 357
13.5%
3300000 299
11.3%
3310000 162
6.1%
3320000 132
 
5.0%
3330000 211
8.0%
3340000 122
 
4.6%
ValueCountFrequency (%)
3400000 229
8.7%
3390000 134
5.1%
3380000 141
5.3%
3370000 205
7.8%
3360000 55
 
2.1%
3350000 151
5.7%
3340000 122
4.6%
3330000 211
8.0%
3320000 132
5.0%
3310000 162
6.1%

관리번호
Text

UNIQUE 

Distinct2642
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size20.8 KiB
2024-04-21T00:12:29.947301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters58124
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

Unique2642 ?
Unique (%)100.0%

Sample

1st row3350000-206-2021-00001
2nd row3260000-206-2011-00003
3rd row3270000-206-2014-00014
4th row3380000-206-2019-00001
5th row3320000-206-2005-00002
ValueCountFrequency (%)
3350000-206-2021-00001 1
 
< 0.1%
3350000-206-2018-00002 1
 
< 0.1%
3320000-206-2011-00007 1
 
< 0.1%
3320000-206-2018-00003 1
 
< 0.1%
3320000-206-2014-00001 1
 
< 0.1%
3320000-206-2013-00004 1
 
< 0.1%
3320000-206-2015-00004 1
 
< 0.1%
3320000-206-2015-00003 1
 
< 0.1%
3320000-206-2015-00002 1
 
< 0.1%
3320000-206-2015-00001 1
 
< 0.1%
Other values (2632) 2632
99.6%
2024-04-21T00:12:30.815228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 26983
46.4%
- 7926
 
13.6%
2 6807
 
11.7%
3 5186
 
8.9%
6 3304
 
5.7%
1 2856
 
4.9%
9 1512
 
2.6%
4 1009
 
1.7%
7 995
 
1.7%
5 814
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50198
86.4%
Dash Punctuation 7926
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 26983
53.8%
2 6807
 
13.6%
3 5186
 
10.3%
6 3304
 
6.6%
1 2856
 
5.7%
9 1512
 
3.0%
4 1009
 
2.0%
7 995
 
2.0%
5 814
 
1.6%
8 732
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 7926
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 58124
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 26983
46.4%
- 7926
 
13.6%
2 6807
 
11.7%
3 5186
 
8.9%
6 3304
 
5.7%
1 2856
 
4.9%
9 1512
 
2.6%
4 1009
 
1.7%
7 995
 
1.7%
5 814
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58124
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 26983
46.4%
- 7926
 
13.6%
2 6807
 
11.7%
3 5186
 
8.9%
6 3304
 
5.7%
1 2856
 
4.9%
9 1512
 
2.6%
4 1009
 
1.7%
7 995
 
1.7%
5 814
 
1.4%

인허가일자
Real number (ℝ)

Distinct1967
Distinct (%)74.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20088916
Minimum19870507
Maximum20210427
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.3 KiB
2024-04-21T00:12:31.067118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19870507
5-th percentile19960716
Q120041014
median20091203
Q320141016
95-th percentile20200213
Maximum20210427
Range339920
Interquartile range (IQR)100001.75

Descriptive statistics

Standard deviation72248.324
Coefficient of variation (CV)0.0035964272
Kurtosis-0.14269717
Mean20088916
Median Absolute Deviation (MAD)49998.5
Skewness-0.48062023
Sum5.3074916 × 1010
Variance5.2198203 × 109
MonotonicityNot monotonic
2024-04-21T00:12:31.545867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20100603 6
 
0.2%
20081209 6
 
0.2%
20120622 6
 
0.2%
20031125 5
 
0.2%
20070614 5
 
0.2%
20000706 5
 
0.2%
20020403 5
 
0.2%
20101217 5
 
0.2%
20110726 5
 
0.2%
20140219 5
 
0.2%
Other values (1957) 2589
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 (%)
20210427 1
< 0.1%
20210422 2
0.1%
20210416 1
< 0.1%
20210414 1
< 0.1%
20210412 2
0.1%
20210407 1
< 0.1%
20210325 1
< 0.1%
20210324 1
< 0.1%
20210322 1
< 0.1%
20210319 1
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2642
Missing (%)100.0%
Memory size23.3 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.8 KiB
3
1677 
1
965 

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 1677
63.5%
1 965
36.5%

Length

2024-04-21T00:12:31.914062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:12:32.099471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1677
63.5%
1 965
36.5%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.8 KiB
폐업
1677 
영업/정상
965 

Length

Max length5
Median length2
Mean length3.0957608
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1677
63.5%
영업/정상 965
36.5%

Length

2024-04-21T00:12:32.291872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:12:32.471497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1677
63.5%
영업/정상 965
36.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.8 KiB
2
1677 
1
965 

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 1677
63.5%
1 965
36.5%

Length

2024-04-21T00:12:32.728176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:12:32.981235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1677
63.5%
1 965
36.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.8 KiB
폐업
1677 
영업
965 

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 1677
63.5%
영업 965
36.5%

Length

2024-04-21T00:12:33.172036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:12:33.336120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1677
63.5%
영업 965
36.5%

폐업일자
Real number (ℝ)

MISSING 

Distinct1227
Distinct (%)73.2%
Missing965
Missing (%)36.5%
Infinite0
Infinite (%)0.0%
Mean20116995
Minimum19880329
Maximum20210428
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.3 KiB
2024-04-21T00:12:33.539989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19880329
5-th percentile20020828
Q120070202
median20121119
Q320170410
95-th percentile20200428
Maximum20210428
Range330099
Interquartile range (IQR)100208

Descriptive statistics

Standard deviation60154.55
Coefficient of variation (CV)0.0029902354
Kurtosis-0.4800225
Mean20116995
Median Absolute Deviation (MAD)50011
Skewness-0.45134956
Sum3.37362 × 1010
Variance3.6185699 × 109
MonotonicityNot monotonic
2024-04-21T00:12:33.875297image/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%
20031124 8
 
0.3%
20170831 8
 
0.3%
20041213 8
 
0.3%
20160527 7
 
0.3%
20090318 7
 
0.3%
Other values (1217) 1572
59.5%
(Missing) 965
36.5%
ValueCountFrequency (%)
19880329 1
< 0.1%
19880723 1
< 0.1%
19940215 2
0.1%
19940412 1
< 0.1%
19940630 1
< 0.1%
19940808 1
< 0.1%
19941018 1
< 0.1%
19941111 2
0.1%
19941213 1
< 0.1%
19950111 1
< 0.1%
ValueCountFrequency (%)
20210428 1
< 0.1%
20210426 2
0.1%
20210421 1
< 0.1%
20210420 1
< 0.1%
20210416 1
< 0.1%
20210413 1
< 0.1%
20210331 1
< 0.1%
20210326 1
< 0.1%
20210322 1
< 0.1%
20210311 1
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2642
Missing (%)100.0%
Memory size23.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2642
Missing (%)100.0%
Memory size23.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2642
Missing (%)100.0%
Memory size23.3 KiB

소재지전화
Text

MISSING 

Distinct1739
Distinct (%)86.7%
Missing636
Missing (%)24.1%
Memory size20.8 KiB
2024-04-21T00:12:35.214329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.211366
Min length3

Characters and Unicode

Total characters22490
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

Unique1541 ?
Unique (%)76.8%

Sample

1st row02 4647058
2nd row051 503 2470
3rd row051 3410086
4th row051 342 8377
5th row051 467 8313
ValueCountFrequency (%)
051 1781
37.2%
727 58
 
1.2%
070 55
 
1.1%
728 17
 
0.4%
724 15
 
0.3%
502 15
 
0.3%
722 13
 
0.3%
557 12
 
0.3%
342 11
 
0.2%
555 11
 
0.2%
Other values (1943) 2801
58.5%
2024-04-21T00:12:36.936198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 3516
15.6%
0 3439
15.3%
1 3293
14.6%
2800
12.4%
2 1601
7.1%
7 1551
6.9%
6 1405
 
6.2%
4 1384
 
6.2%
3 1330
 
5.9%
8 1254
 
5.6%
Other values (2) 917
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19689
87.5%
Space Separator 2800
 
12.4%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 3516
17.9%
0 3439
17.5%
1 3293
16.7%
2 1601
8.1%
7 1551
7.9%
6 1405
 
7.1%
4 1384
 
7.0%
3 1330
 
6.8%
8 1254
 
6.4%
9 916
 
4.7%
Space Separator
ValueCountFrequency (%)
2800
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22490
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 3516
15.6%
0 3439
15.3%
1 3293
14.6%
2800
12.4%
2 1601
7.1%
7 1551
6.9%
6 1405
 
6.2%
4 1384
 
6.2%
3 1330
 
5.9%
8 1254
 
5.6%
Other values (2) 917
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22490
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 3516
15.6%
0 3439
15.3%
1 3293
14.6%
2800
12.4%
2 1601
7.1%
7 1551
6.9%
6 1405
 
6.2%
4 1384
 
6.2%
3 1330
 
5.9%
8 1254
 
5.6%
Other values (2) 917
 
4.1%
Distinct1568
Distinct (%)59.9%
Missing24
Missing (%)0.9%
Memory size20.8 KiB
2024-04-21T00:12:37.952876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.8712758
Min length3

Characters and Unicode

Total characters12753
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

Unique1269 ?
Unique (%)48.5%

Sample

1st row.00
2nd row.00
3rd row46.20
4th row33.60
5th row91.30
ValueCountFrequency (%)
00 348
 
13.3%
33.00 39
 
1.5%
66.00 21
 
0.8%
40.00 15
 
0.6%
30.00 13
 
0.5%
36.00 12
 
0.5%
49.50 12
 
0.5%
25.00 11
 
0.4%
99.00 11
 
0.4%
12.00 11
 
0.4%
Other values (1558) 2125
81.2%
2024-04-21T00:12:39.620102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2756
21.6%
. 2618
20.5%
1 1096
 
8.6%
2 1006
 
7.9%
5 879
 
6.9%
3 868
 
6.8%
6 816
 
6.4%
4 791
 
6.2%
8 713
 
5.6%
7 608
 
4.8%
Other values (2) 602
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10130
79.4%
Other Punctuation 2623
 
20.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2756
27.2%
1 1096
 
10.8%
2 1006
 
9.9%
5 879
 
8.7%
3 868
 
8.6%
6 816
 
8.1%
4 791
 
7.8%
8 713
 
7.0%
7 608
 
6.0%
9 597
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 2618
99.8%
, 5
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 12753
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2756
21.6%
. 2618
20.5%
1 1096
 
8.6%
2 1006
 
7.9%
5 879
 
6.9%
3 868
 
6.8%
6 816
 
6.4%
4 791
 
6.2%
8 713
 
5.6%
7 608
 
4.8%
Other values (2) 602
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12753
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2756
21.6%
. 2618
20.5%
1 1096
 
8.6%
2 1006
 
7.9%
5 879
 
6.9%
3 868
 
6.8%
6 816
 
6.4%
4 791
 
6.2%
8 713
 
5.6%
7 608
 
4.8%
Other values (2) 602
 
4.7%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct606
Distinct (%)23.2%
Missing34
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean610913.89
Minimum400410
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.3 KiB
2024-04-21T00:12:40.043245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum400410
5-th percentile601807
Q1607812.5
median611825
Q3614854
95-th percentile619912
Maximum619953
Range219543
Interquartile range (IQR)7041.5

Descriptive statistics

Standard deviation7003.0231
Coefficient of variation (CV)0.011463192
Kurtosis311.76345
Mean610913.89
Median Absolute Deviation (MAD)3992.5
Skewness-10.544598
Sum1.5932634 × 109
Variance49042332
MonotonicityNot monotonic
2024-04-21T00:12:40.509351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
619951 47
 
1.8%
619952 46
 
1.7%
601837 41
 
1.6%
601839 29
 
1.1%
601836 28
 
1.1%
619953 26
 
1.0%
614844 26
 
1.0%
601838 25
 
0.9%
614865 23
 
0.9%
607804 22
 
0.8%
Other values (596) 2295
86.9%
(Missing) 34
 
1.3%
ValueCountFrequency (%)
400410 1
 
< 0.1%
600012 4
0.2%
600013 1
 
< 0.1%
600014 2
 
0.1%
600015 4
0.2%
600016 6
0.2%
600021 3
0.1%
600022 2
 
0.1%
600024 1
 
< 0.1%
600044 1
 
< 0.1%
ValueCountFrequency (%)
619953 26
1.0%
619952 46
1.7%
619951 47
1.8%
619950 1
 
< 0.1%
619913 7
 
0.3%
619912 9
 
0.3%
619911 10
 
0.4%
619906 10
 
0.4%
619905 18
 
0.7%
619904 5
 
0.2%
Distinct2445
Distinct (%)93.0%
Missing14
Missing (%)0.5%
Memory size20.8 KiB
2024-04-21T00:12:42.185678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length45
Mean length25.365677
Min length2

Characters and Unicode

Total characters66661
Distinct characters406
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

Unique2289 ?
Unique (%)87.1%

Sample

1st row부산광역시 금정구 금사동 81-1 금사자동차운전전문학원
2nd row인천광역시 중구 덕교동 128-76번지
3rd row부산광역시 동구 수정동 425-18 1층
4th row부산광역시 수영구 광안동 100-10
5th row부산광역시 북구 덕천동 388-1번지 대방상가 304호
ValueCountFrequency (%)
부산광역시 2626
 
20.8%
부산진구 350
 
2.8%
동래구 299
 
2.4%
동구 239
 
1.9%
기장군 228
 
1.8%
해운대구 212
 
1.7%
연제구 204
 
1.6%
남구 161
 
1.3%
초량동 161
 
1.3%
금정구 151
 
1.2%
Other values (3194) 7997
63.3%
2024-04-21T00:12:43.988786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10003
 
15.0%
3243
 
4.9%
3242
 
4.9%
1 3218
 
4.8%
3195
 
4.8%
2728
 
4.1%
2654
 
4.0%
2635
 
4.0%
2487
 
3.7%
2461
 
3.7%
Other values (396) 30795
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39562
59.3%
Decimal Number 14081
 
21.1%
Space Separator 10003
 
15.0%
Dash Punctuation 2400
 
3.6%
Uppercase Letter 247
 
0.4%
Open Punctuation 142
 
0.2%
Close Punctuation 142
 
0.2%
Other Punctuation 70
 
0.1%
Lowercase Letter 13
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3243
 
8.2%
3242
 
8.2%
3195
 
8.1%
2728
 
6.9%
2654
 
6.7%
2635
 
6.7%
2487
 
6.3%
2461
 
6.2%
2339
 
5.9%
529
 
1.3%
Other values (349) 14049
35.5%
Uppercase Letter
ValueCountFrequency (%)
B 98
39.7%
T 76
30.8%
O 14
 
5.7%
A 9
 
3.6%
D 9
 
3.6%
S 9
 
3.6%
K 6
 
2.4%
I 6
 
2.4%
C 5
 
2.0%
P 4
 
1.6%
Other values (8) 11
 
4.5%
Decimal Number
ValueCountFrequency (%)
1 3218
22.9%
2 1944
13.8%
3 1602
11.4%
4 1326
9.4%
0 1254
 
8.9%
5 1188
 
8.4%
6 1008
 
7.2%
7 957
 
6.8%
8 870
 
6.2%
9 714
 
5.1%
Lowercase Letter
ValueCountFrequency (%)
s 2
15.4%
k 2
15.4%
e 2
15.4%
t 1
7.7%
o 1
7.7%
d 1
7.7%
y 1
7.7%
b 1
7.7%
u 1
7.7%
h 1
7.7%
Other Punctuation
ValueCountFrequency (%)
, 47
67.1%
/ 17
 
24.3%
@ 3
 
4.3%
. 3
 
4.3%
Space Separator
ValueCountFrequency (%)
10003
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2400
100.0%
Open Punctuation
ValueCountFrequency (%)
( 142
100.0%
Close Punctuation
ValueCountFrequency (%)
) 142
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39562
59.3%
Common 26839
40.3%
Latin 260
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3243
 
8.2%
3242
 
8.2%
3195
 
8.1%
2728
 
6.9%
2654
 
6.7%
2635
 
6.7%
2487
 
6.3%
2461
 
6.2%
2339
 
5.9%
529
 
1.3%
Other values (349) 14049
35.5%
Latin
ValueCountFrequency (%)
B 98
37.7%
T 76
29.2%
O 14
 
5.4%
A 9
 
3.5%
D 9
 
3.5%
S 9
 
3.5%
K 6
 
2.3%
I 6
 
2.3%
C 5
 
1.9%
P 4
 
1.5%
Other values (18) 24
 
9.2%
Common
ValueCountFrequency (%)
10003
37.3%
1 3218
 
12.0%
- 2400
 
8.9%
2 1944
 
7.2%
3 1602
 
6.0%
4 1326
 
4.9%
0 1254
 
4.7%
5 1188
 
4.4%
6 1008
 
3.8%
7 957
 
3.6%
Other values (9) 1939
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39562
59.3%
ASCII 27099
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10003
36.9%
1 3218
 
11.9%
- 2400
 
8.9%
2 1944
 
7.2%
3 1602
 
5.9%
4 1326
 
4.9%
0 1254
 
4.6%
5 1188
 
4.4%
6 1008
 
3.7%
7 957
 
3.5%
Other values (37) 2199
 
8.1%
Hangul
ValueCountFrequency (%)
3243
 
8.2%
3242
 
8.2%
3195
 
8.1%
2728
 
6.9%
2654
 
6.7%
2635
 
6.7%
2487
 
6.3%
2461
 
6.2%
2339
 
5.9%
529
 
1.3%
Other values (349) 14049
35.5%

도로명전체주소
Text

MISSING 

Distinct1784
Distinct (%)96.0%
Missing783
Missing (%)29.6%
Memory size20.8 KiB
2024-04-21T00:12:45.491889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length49
Mean length31.777838
Min length20

Characters and Unicode

Total characters59075
Distinct characters424
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

Unique1719 ?
Unique (%)92.5%

Sample

1st row부산광역시 금정구 공단서로8번길 49, 금사자동차운전전문학원 A동 307호 (금사동)
2nd row인천광역시 중구 마시란로 51-33 (덕교동)
3rd row부산광역시 동구 망양로 837, 1층 (수정동)
4th row부산광역시 수영구 무학로9번길 46, 1층 (광안동)
5th row부산광역시 북구 시랑로118번길 56 (구포동)
ValueCountFrequency (%)
부산광역시 1858
 
16.2%
부산진구 249
 
2.2%
1층 233
 
2.0%
2층 232
 
2.0%
동래구 208
 
1.8%
기장군 196
 
1.7%
해운대구 166
 
1.4%
연제구 150
 
1.3%
3층 137
 
1.2%
동구 132
 
1.2%
Other values (2457) 7891
68.9%
2024-04-21T00:12:47.399175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9595
 
16.2%
2410
 
4.1%
2337
 
4.0%
2316
 
3.9%
1 2271
 
3.8%
1967
 
3.3%
1943
 
3.3%
1866
 
3.2%
1761
 
3.0%
1751
 
3.0%
Other values (414) 30858
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34144
57.8%
Decimal Number 9761
 
16.5%
Space Separator 9595
 
16.2%
Close Punctuation 1740
 
2.9%
Open Punctuation 1740
 
2.9%
Other Punctuation 1648
 
2.8%
Dash Punctuation 317
 
0.5%
Uppercase Letter 115
 
0.2%
Lowercase Letter 11
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2410
 
7.1%
2337
 
6.8%
2316
 
6.8%
1967
 
5.8%
1943
 
5.7%
1866
 
5.5%
1761
 
5.2%
1751
 
5.1%
982
 
2.9%
930
 
2.7%
Other values (371) 15881
46.5%
Uppercase Letter
ValueCountFrequency (%)
B 36
31.3%
A 22
19.1%
C 11
 
9.6%
E 10
 
8.7%
P 8
 
7.0%
S 7
 
6.1%
I 4
 
3.5%
O 4
 
3.5%
T 4
 
3.5%
K 2
 
1.7%
Other values (6) 7
 
6.1%
Decimal Number
ValueCountFrequency (%)
1 2271
23.3%
2 1627
16.7%
3 1195
12.2%
0 894
 
9.2%
4 825
 
8.5%
5 722
 
7.4%
6 610
 
6.2%
7 568
 
5.8%
8 539
 
5.5%
9 510
 
5.2%
Lowercase Letter
ValueCountFrequency (%)
e 2
18.2%
s 2
18.2%
k 2
18.2%
h 1
9.1%
u 1
9.1%
b 1
9.1%
y 1
9.1%
d 1
9.1%
Other Punctuation
ValueCountFrequency (%)
, 1638
99.4%
/ 6
 
0.4%
@ 2
 
0.1%
. 2
 
0.1%
Space Separator
ValueCountFrequency (%)
9595
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1740
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1740
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 317
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34144
57.8%
Common 24805
42.0%
Latin 126
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2410
 
7.1%
2337
 
6.8%
2316
 
6.8%
1967
 
5.8%
1943
 
5.7%
1866
 
5.5%
1761
 
5.2%
1751
 
5.1%
982
 
2.9%
930
 
2.7%
Other values (371) 15881
46.5%
Latin
ValueCountFrequency (%)
B 36
28.6%
A 22
17.5%
C 11
 
8.7%
E 10
 
7.9%
P 8
 
6.3%
S 7
 
5.6%
I 4
 
3.2%
O 4
 
3.2%
T 4
 
3.2%
K 2
 
1.6%
Other values (14) 18
14.3%
Common
ValueCountFrequency (%)
9595
38.7%
1 2271
 
9.2%
) 1740
 
7.0%
( 1740
 
7.0%
, 1638
 
6.6%
2 1627
 
6.6%
3 1195
 
4.8%
0 894
 
3.6%
4 825
 
3.3%
5 722
 
2.9%
Other values (9) 2558
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34144
57.8%
ASCII 24931
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9595
38.5%
1 2271
 
9.1%
) 1740
 
7.0%
( 1740
 
7.0%
, 1638
 
6.6%
2 1627
 
6.5%
3 1195
 
4.8%
0 894
 
3.6%
4 825
 
3.3%
5 722
 
2.9%
Other values (33) 2684
 
10.8%
Hangul
ValueCountFrequency (%)
2410
 
7.1%
2337
 
6.8%
2316
 
6.8%
1967
 
5.8%
1943
 
5.7%
1866
 
5.5%
1761
 
5.2%
1751
 
5.1%
982
 
2.9%
930
 
2.7%
Other values (371) 15881
46.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct862
Distinct (%)47.5%
Missing827
Missing (%)31.3%
Infinite0
Infinite (%)0.0%
Mean47614.847
Minimum22385
Maximum49524
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.3 KiB
2024-04-21T00:12:47.817147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22385
5-th percentile46037
Q146966.5
median47709
Q348314
95-th percentile49261.9
Maximum49524
Range27139
Interquartile range (IQR)1347.5

Descriptive statistics

Standard deviation1137.8527
Coefficient of variation (CV)0.023897015
Kurtosis131.79925
Mean47614.847
Median Absolute Deviation (MAD)721
Skewness-6.0072885
Sum86420948
Variance1294708.8
MonotonicityNot monotonic
2024-04-21T00:12:48.273566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46036 30
 
1.1%
46037 23
 
0.9%
46033 19
 
0.7%
48729 18
 
0.7%
48060 14
 
0.5%
48093 14
 
0.5%
48059 14
 
0.5%
47247 14
 
0.5%
47243 12
 
0.5%
47246 11
 
0.4%
Other values (852) 1646
62.3%
(Missing) 827
31.3%
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%
Distinct2246
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Memory size20.8 KiB
2024-04-21T00:12:49.075852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length22
Mean length7.1983346
Min length2

Characters and Unicode

Total characters19018
Distinct characters542
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

Unique1935 ?
Unique (%)73.2%

Sample

1st row고클린
2nd row(주)성수인력
3rd row(주)남영산업
4th row청소협동조합 청소하는사람들 부산경남본점
5th row(주)천우이엔지
ValueCountFrequency (%)
주식회사 171
 
5.6%
16
 
0.5%
주)만비종합관리 7
 
0.2%
시스템 7
 
0.2%
주)만송 7
 
0.2%
그린산업 6
 
0.2%
청소나라 6
 
0.2%
주)금강종합개발 6
 
0.2%
유한회사 6
 
0.2%
주)청담산업 5
 
0.2%
Other values (2360) 2820
92.2%
2024-04-21T00:12:50.427870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1493
 
7.9%
) 1321
 
6.9%
( 1285
 
6.8%
563
 
3.0%
461
 
2.4%
418
 
2.2%
378
 
2.0%
332
 
1.7%
331
 
1.7%
320
 
1.7%
Other values (532) 12116
63.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15602
82.0%
Close Punctuation 1321
 
6.9%
Open Punctuation 1285
 
6.8%
Space Separator 418
 
2.2%
Uppercase Letter 244
 
1.3%
Lowercase Letter 54
 
0.3%
Decimal Number 39
 
0.2%
Other Punctuation 38
 
0.2%
Other Symbol 15
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1493
 
9.6%
563
 
3.6%
461
 
3.0%
378
 
2.4%
332
 
2.1%
331
 
2.1%
320
 
2.1%
309
 
2.0%
296
 
1.9%
247
 
1.6%
Other values (478) 10872
69.7%
Uppercase Letter
ValueCountFrequency (%)
C 41
16.8%
S 25
10.2%
E 22
9.0%
B 18
 
7.4%
G 17
 
7.0%
M 16
 
6.6%
H 16
 
6.6%
N 15
 
6.1%
T 13
 
5.3%
P 8
 
3.3%
Other values (10) 53
21.7%
Lowercase Letter
ValueCountFrequency (%)
e 13
24.1%
o 6
11.1%
a 5
 
9.3%
s 5
 
9.3%
l 4
 
7.4%
r 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
41.0%
2 8
20.5%
9 3
 
7.7%
0 3
 
7.7%
4 3
 
7.7%
8 2
 
5.1%
6 2
 
5.1%
5 1
 
2.6%
3 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
& 16
42.1%
. 11
28.9%
, 5
 
13.2%
· 4
 
10.5%
2
 
5.3%
Other Symbol
ValueCountFrequency (%)
14
93.3%
1
 
6.7%
Close Punctuation
ValueCountFrequency (%)
) 1321
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1285
100.0%
Space Separator
ValueCountFrequency (%)
418
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15617
82.1%
Common 3103
 
16.3%
Latin 298
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1493
 
9.6%
563
 
3.6%
461
 
3.0%
378
 
2.4%
332
 
2.1%
331
 
2.1%
320
 
2.0%
309
 
2.0%
296
 
1.9%
247
 
1.6%
Other values (480) 10887
69.7%
Latin
ValueCountFrequency (%)
C 41
13.8%
S 25
 
8.4%
E 22
 
7.4%
B 18
 
6.0%
G 17
 
5.7%
M 16
 
5.4%
H 16
 
5.4%
N 15
 
5.0%
T 13
 
4.4%
e 13
 
4.4%
Other values (24) 102
34.2%
Common
ValueCountFrequency (%)
) 1321
42.6%
( 1285
41.4%
418
 
13.5%
& 16
 
0.5%
1 16
 
0.5%
. 11
 
0.4%
2 8
 
0.3%
, 5
 
0.2%
· 4
 
0.1%
9 3
 
0.1%
Other values (8) 16
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15602
82.0%
ASCII 3395
 
17.9%
None 21
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1493
 
9.6%
563
 
3.6%
461
 
3.0%
378
 
2.4%
332
 
2.1%
331
 
2.1%
320
 
2.1%
309
 
2.0%
296
 
1.9%
247
 
1.6%
Other values (478) 10872
69.7%
ASCII
ValueCountFrequency (%)
) 1321
38.9%
( 1285
37.8%
418
 
12.3%
C 41
 
1.2%
S 25
 
0.7%
E 22
 
0.6%
B 18
 
0.5%
G 17
 
0.5%
& 16
 
0.5%
1 16
 
0.5%
Other values (40) 216
 
6.4%
None
ValueCountFrequency (%)
14
66.7%
· 4
 
19.0%
2
 
9.5%
1
 
4.8%

최종수정시점
Real number (ℝ)

Distinct2388
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0131988 × 1013
Minimum1.9990201 × 1013
Maximum2.0210429 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.3 KiB
2024-04-21T00:12:50.678940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990201 × 1013
5-th percentile2.0030225 × 1013
Q12.0080821 × 1013
median2.0141005 × 1013
Q32.0190184 × 1013
95-th percentile2.0201223 × 1013
Maximum2.0210429 × 1013
Range2.2022816 × 1011
Interquartile range (IQR)1.0936294 × 1011

Descriptive statistics

Standard deviation6.1666252 × 1010
Coefficient of variation (CV)0.003063098
Kurtosis-0.94226781
Mean2.0131988 × 1013
Median Absolute Deviation (MAD)4.9500503 × 1010
Skewness-0.54313248
Sum5.3188712 × 1016
Variance3.8027267 × 1021
MonotonicityNot monotonic
2024-04-21T00:12:50.944366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20060616000000 19
 
0.7%
20020419000000 16
 
0.6%
20050920000000 12
 
0.5%
19990201000000 11
 
0.4%
20030403000000 11
 
0.4%
20021112000000 10
 
0.4%
20051110000000 10
 
0.4%
20030404000000 10
 
0.4%
20030227000000 8
 
0.3%
20030521000000 8
 
0.3%
Other values (2378) 2527
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 (%)
20210429160921 1
< 0.1%
20210429151652 1
< 0.1%
20210428150649 1
< 0.1%
20210428150015 1
< 0.1%
20210428125121 1
< 0.1%
20210427152232 1
< 0.1%
20210427115611 1
< 0.1%
20210426170224 1
< 0.1%
20210426170143 1
< 0.1%
20210426145609 1
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.8 KiB
I
2008 
U
634 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 2008
76.0%
U 634
 
24.0%

Length

2024-04-21T00:12:51.173909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:12:51.355561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2008
76.0%
u 634
 
24.0%
Distinct505
Distinct (%)19.1%
Missing0
Missing (%)0.0%
Memory size20.8 KiB
Minimum2018-08-31 23:59:59
Maximum2021-05-01 02:40:00
2024-04-21T00:12:51.763277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T00:12:52.015962image/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 size20.8 KiB
건물위생관리업
2612 
건물위생관리업 기타
 
22
<NA>
 
8

Length

Max length10
Median length7
Mean length7.015897
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 2612
98.9%
건물위생관리업 기타 22
 
0.8%
<NA> 8
 
0.3%

Length

2024-04-21T00:12:52.265589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:12:52.450345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 2634
98.9%
기타 22
 
0.8%
na 8
 
0.3%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct1970
Distinct (%)76.6%
Missing70
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean389118.25
Minimum148671.32
Maximum408081.98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.3 KiB
2024-04-21T00:12:52.651670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum148671.32
5-th percentile380054.76
Q1385779.55
median388641.53
Q3391509.28
95-th percentile403641.08
Maximum408081.98
Range259410.66
Interquartile range (IQR)5729.7355

Descriptive statistics

Standard deviation7999.4246
Coefficient of variation (CV)0.020557824
Kurtosis317.12445
Mean389118.25
Median Absolute Deviation (MAD)2863.3775
Skewness-10.187411
Sum1.0008122 × 109
Variance63990793
MonotonicityNot monotonic
2024-04-21T00:12:52.923316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
395615.201853958 13
 
0.5%
380482.767624189 10
 
0.4%
387927.951172724 10
 
0.4%
391411.212179843 9
 
0.3%
396180.621244719 9
 
0.3%
388310.086924943 9
 
0.3%
407871.508884898 8
 
0.3%
387869.134317928 8
 
0.3%
387225.613588405 8
 
0.3%
386351.941329364 8
 
0.3%
Other values (1960) 2480
93.9%
(Missing) 70
 
2.6%
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 

Distinct1970
Distinct (%)76.6%
Missing70
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean188411.27
Minimum174156.62
Maximum436093.42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.3 KiB
2024-04-21T00:12:53.176906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174156.62
5-th percentile179713.87
Q1184020.65
median187559.59
Q3191384.84
95-th percentile203500.98
Maximum436093.42
Range261936.8
Interquartile range (IQR)7364.1871

Descriptive statistics

Standard deviation8059.8575
Coefficient of variation (CV)0.042778001
Kurtosis346.22056
Mean188411.27
Median Absolute Deviation (MAD)3694.5692
Skewness11.70393
Sum4.8459379 × 108
Variance64961303
MonotonicityNot monotonic
2024-04-21T00:12:53.442963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
186406.750870936 13
 
0.5%
185582.274947583 10
 
0.4%
186582.791097672 10
 
0.4%
184052.409245407 9
 
0.3%
186522.35047527 9
 
0.3%
183883.854898063 9
 
0.3%
205389.277197702 8
 
0.3%
186381.28184674 8
 
0.3%
186408.726533861 8
 
0.3%
182468.78681462 8
 
0.3%
Other values (1960) 2480
93.9%
(Missing) 70
 
2.6%
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 size20.8 KiB
건물위생관리업
2612 
건물위생관리업 기타
 
22
<NA>
 
8

Length

Max length10
Median length7
Mean length7.015897
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 2612
98.9%
건물위생관리업 기타 22
 
0.8%
<NA> 8
 
0.3%

Length

2024-04-21T00:12:53.671902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:12:53.850569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 2634
98.9%
기타 22
 
0.8%
na 8
 
0.3%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct31
Distinct (%)1.4%
Missing434
Missing (%)16.4%
Infinite0
Infinite (%)0.0%
Mean3.7432065
Minimum0
Maximum51
Zeros638
Zeros (%)24.1%
Negative0
Negative (%)0.0%
Memory size23.3 KiB
2024-04-21T00:12:54.049748image/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 deviation4.6582042
Coefficient of variation (CV)1.2444422
Kurtosis15.927638
Mean3.7432065
Median Absolute Deviation (MAD)2
Skewness3.0423008
Sum8265
Variance21.698866
MonotonicityNot monotonic
2024-04-21T00:12:54.414759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 638
24.1%
4 352
13.3%
3 252
 
9.5%
2 234
 
8.9%
5 232
 
8.8%
1 112
 
4.2%
6 90
 
3.4%
7 51
 
1.9%
10 40
 
1.5%
8 35
 
1.3%
Other values (21) 172
 
6.5%
(Missing) 434
16.4%
ValueCountFrequency (%)
0 638
24.1%
1 112
 
4.2%
2 234
 
8.9%
3 252
 
9.5%
4 352
13.3%
5 232
 
8.8%
6 90
 
3.4%
7 51
 
1.9%
8 35
 
1.3%
9 25
 
0.9%
ValueCountFrequency (%)
51 1
 
< 0.1%
49 1
 
< 0.1%
44 1
 
< 0.1%
32 1
 
< 0.1%
28 3
0.1%
27 2
0.1%
25 4
0.2%
24 3
0.1%
22 4
0.2%
21 4
0.2%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.4%
Missing593
Missing (%)22.4%
Infinite0
Infinite (%)0.0%
Mean0.60956564
Minimum0
Maximum8
Zeros1173
Zeros (%)44.4%
Negative0
Negative (%)0.0%
Memory size23.3 KiB
2024-04-21T00:12:54.771508image/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 deviation0.96157944
Coefficient of variation (CV)1.577483
Kurtosis9.5091424
Mean0.60956564
Median Absolute Deviation (MAD)0
Skewness2.6441314
Sum1249
Variance0.92463502
MonotonicityNot monotonic
2024-04-21T00:12:55.187235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 1173
44.4%
1 688
26.0%
2 95
 
3.6%
3 41
 
1.6%
5 22
 
0.8%
4 22
 
0.8%
6 7
 
0.3%
8 1
 
< 0.1%
(Missing) 593
22.4%
ValueCountFrequency (%)
0 1173
44.4%
1 688
26.0%
2 95
 
3.6%
3 41
 
1.6%
4 22
 
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 22
 
0.8%
3 41
 
1.6%
2 95
 
3.6%
1 688
26.0%
0 1173
44.4%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct26
Distinct (%)1.3%
Missing692
Missing (%)26.2%
Infinite0
Infinite (%)0.0%
Mean2.6651282
Minimum0
Maximum48
Zeros357
Zeros (%)13.5%
Negative0
Negative (%)0.0%
Memory size23.3 KiB
2024-04-21T00:12:55.442312image/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 deviation3.3120834
Coefficient of variation (CV)1.2427483
Kurtosis27.979956
Mean2.6651282
Median Absolute Deviation (MAD)1
Skewness3.9211773
Sum5197
Variance10.969897
MonotonicityNot monotonic
2024-04-21T00:12:55.833306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
2 459
17.4%
1 429
16.2%
0 357
13.5%
3 284
10.7%
4 149
 
5.6%
5 72
 
2.7%
6 45
 
1.7%
7 35
 
1.3%
9 20
 
0.8%
8 19
 
0.7%
Other values (16) 81
 
3.1%
(Missing) 692
26.2%
ValueCountFrequency (%)
0 357
13.5%
1 429
16.2%
2 459
17.4%
3 284
10.7%
4 149
 
5.6%
5 72
 
2.7%
6 45
 
1.7%
7 35
 
1.3%
8 19
 
0.7%
9 20
 
0.8%
ValueCountFrequency (%)
48 1
 
< 0.1%
26 2
 
0.1%
24 2
 
0.1%
23 2
 
0.1%
22 1
 
< 0.1%
21 1
 
< 0.1%
20 4
0.2%
18 1
 
< 0.1%
17 3
0.1%
16 6
0.2%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct25
Distinct (%)1.5%
Missing955
Missing (%)36.1%
Infinite0
Infinite (%)0.0%
Mean2.5305276
Minimum0
Maximum48
Zeros351
Zeros (%)13.3%
Negative0
Negative (%)0.0%
Memory size23.3 KiB
2024-04-21T00:12:56.199229image/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 deviation3.2738021
Coefficient of variation (CV)1.2937232
Kurtosis31.717734
Mean2.5305276
Median Absolute Deviation (MAD)1
Skewness4.1550347
Sum4269
Variance10.71778
MonotonicityNot monotonic
2024-04-21T00:12:56.545834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
2 385
14.6%
1 374
 
14.2%
0 351
 
13.3%
3 237
 
9.0%
4 128
 
4.8%
5 51
 
1.9%
6 42
 
1.6%
7 29
 
1.1%
8 12
 
0.5%
10 11
 
0.4%
Other values (15) 67
 
2.5%
(Missing) 955
36.1%
ValueCountFrequency (%)
0 351
13.3%
1 374
14.2%
2 385
14.6%
3 237
9.0%
4 128
 
4.8%
5 51
 
1.9%
6 42
 
1.6%
7 29
 
1.1%
8 12
 
0.5%
9 10
 
0.4%
ValueCountFrequency (%)
48 1
 
< 0.1%
26 1
 
< 0.1%
24 2
 
0.1%
23 1
 
< 0.1%
21 1
 
< 0.1%
20 5
0.2%
18 1
 
< 0.1%
17 3
0.1%
16 5
0.2%
15 6
0.2%

사용시작지하층
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.5%
Missing1408
Missing (%)53.3%
Infinite0
Infinite (%)0.0%
Mean0.1547812
Minimum0
Maximum5
Zeros1058
Zeros (%)40.0%
Negative0
Negative (%)0.0%
Memory size23.3 KiB
2024-04-21T00:12:56.738833image/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 deviation0.41993781
Coefficient of variation (CV)2.713106
Kurtosis27.79941
Mean0.1547812
Median Absolute Deviation (MAD)0
Skewness4.0308356
Sum191
Variance0.17634776
MonotonicityNot monotonic
2024-04-21T00:12:56.925541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 1058
40.0%
1 169
 
6.4%
2 3
 
0.1%
4 2
 
0.1%
5 1
 
< 0.1%
3 1
 
< 0.1%
(Missing) 1408
53.3%
ValueCountFrequency (%)
0 1058
40.0%
1 169
 
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%
1 169
 
6.4%
0 1058
40.0%

사용끝지하층
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.7%
Missing1584
Missing (%)60.0%
Infinite0
Infinite (%)0.0%
Mean0.17485822
Minimum0
Maximum10
Zeros898
Zeros (%)34.0%
Negative0
Negative (%)0.0%
Memory size23.3 KiB
2024-04-21T00:12:57.137064image/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 deviation0.52976783
Coefficient of variation (CV)3.0296993
Kurtosis121.74947
Mean0.17485822
Median Absolute Deviation (MAD)0
Skewness8.1074484
Sum185
Variance0.28065395
MonotonicityNot monotonic
2024-04-21T00:12:57.347181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 898
34.0%
1 150
 
5.7%
2 5
 
0.2%
3 2
 
0.1%
5 1
 
< 0.1%
4 1
 
< 0.1%
10 1
 
< 0.1%
(Missing) 1584
60.0%
ValueCountFrequency (%)
0 898
34.0%
1 150
 
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%
1 150
 
5.7%
0 898
34.0%

한실수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.8 KiB
0
1757 
<NA>
884 
1
 
1

Length

Max length4
Median length1
Mean length2.003785
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1757
66.5%
<NA> 884
33.5%
1 1
 
< 0.1%

Length

2024-04-21T00:12:57.563719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:12:57.921193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1757
66.5%
na 884
33.5%
1 1
 
< 0.1%

양실수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.8 KiB
0
1757 
<NA>
884 
29
 
1

Length

Max length4
Median length1
Mean length2.0041635
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1757
66.5%
<NA> 884
33.5%
29 1
 
< 0.1%

Length

2024-04-21T00:12:58.340411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:12:58.692125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1757
66.5%
na 884
33.5%
29 1
 
< 0.1%

욕실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.8 KiB
0
1758 
<NA>
884 

Length

Max length4
Median length1
Mean length2.003785
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1758
66.5%
<NA> 884
33.5%

Length

2024-04-21T00:12:59.084771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:12:59.434311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1758
66.5%
na 884
33.5%

발한실여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing72
Missing (%)2.7%
Memory size5.3 KiB
False
2569 
True
 
1
(Missing)
 
72
ValueCountFrequency (%)
False 2569
97.2%
True 1
 
< 0.1%
(Missing) 72
 
2.7%
2024-04-21T00:12:59.727067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

의자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size20.8 KiB
0
1756 
<NA>
882 
9
 
2
1
 
2

Length

Max length4
Median length1
Mean length2.001514
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1756
66.5%
<NA> 882
33.4%
9 2
 
0.1%
1 2
 
0.1%

Length

2024-04-21T00:13:00.135483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:13:00.485909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1756
66.5%
na 882
33.4%
9 2
 
0.1%
1 2
 
0.1%
Distinct4
Distinct (%)80.0%
Missing2637
Missing (%)99.8%
Memory size20.8 KiB
2024-04-21T00:13:01.158301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length25
Mean length18.8
Min length5

Characters and Unicode

Total characters94
Distinct characters49
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)60.0%

Sample

1st row계약기간연장
2nd row가설건축물
3rd row공중위생관리법시행령 제3조제1호의 규정에 의한 건축물규모 이하의 건축물을 청소하는 경우에 한함
4th row계약기간연장
5th row2003 가설허가 제2호(2003.03.08)
ValueCountFrequency (%)
계약기간연장 2
 
12.5%
가설건축물 1
 
6.2%
공중위생관리법시행령 1
 
6.2%
제3조제1호의 1
 
6.2%
규정에 1
 
6.2%
의한 1
 
6.2%
건축물규모 1
 
6.2%
이하의 1
 
6.2%
건축물을 1
 
6.2%
청소하는 1
 
6.2%
Other values (5) 5
31.2%
2024-04-21T00:13:02.240506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

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

Most occurring scripts

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

Most frequent character per script

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

Most occurring blocks

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

Most frequent character per block

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

조건부허가시작일자
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size20.8 KiB
<NA>
2636 
20140301
 
2
20140212
 
1
20060825
 
1
20060106
 
1

Length

Max length8
Median length4
Mean length4.009084
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> 2636
99.8%
20140301 2
 
0.1%
20140212 1
 
< 0.1%
20060825 1
 
< 0.1%
20060106 1
 
< 0.1%
20100210 1
 
< 0.1%

Length

2024-04-21T00:13:02.679285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:13:02.981441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2636
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%
Missing2635
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean20126313
Minimum20061231
Maximum20200415
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.3 KiB
2024-04-21T00:13:03.158806image/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
2024-04-21T00:13:03.361250image/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) 2635
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 size20.8 KiB
<NA>
1758 
임대
842 
자가
 
42

Length

Max length4
Median length4
Mean length3.33081
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1758
66.5%
임대 842
31.9%
자가 42
 
1.6%

Length

2024-04-21T00:13:03.806182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:13:04.148860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1758
66.5%
임대 842
31.9%
자가 42
 
1.6%

세탁기수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.8 KiB
0
1582 
<NA>
1060 

Length

Max length4
Median length1
Mean length2.2036336
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1582
59.9%
<NA> 1060
40.1%

Length

2024-04-21T00:13:04.354876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:13:04.676773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1582
59.9%
na 1060
40.1%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct19
Distinct (%)3.7%
Missing2128
Missing (%)80.5%
Infinite0
Infinite (%)0.0%
Mean2.188716
Minimum0
Maximum340
Zeros452
Zeros (%)17.1%
Negative0
Negative (%)0.0%
Memory size23.3 KiB
2024-04-21T00:13:05.240604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation17.919067
Coefficient of variation (CV)8.1870227
Kurtosis253.73358
Mean2.188716
Median Absolute Deviation (MAD)0
Skewness14.571548
Sum1125
Variance321.09297
MonotonicityNot monotonic
2024-04-21T00:13:05.530962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 452
 
17.1%
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) 2128
80.5%
ValueCountFrequency (%)
0 452
17.1%
1 22
 
0.8%
2 11
 
0.4%
3 4
 
0.2%
4 1
 
< 0.1%
5 4
 
0.2%
7 1
 
< 0.1%
8 2
 
0.1%
9 2
 
0.1%
10 2
 
0.1%
ValueCountFrequency (%)
340 1
 
< 0.1%
102 1
 
< 0.1%
95 4
0.2%
40 1
 
< 0.1%
30 1
 
< 0.1%
26 1
 
< 0.1%
20 2
0.1%
15 1
 
< 0.1%
11 1
 
< 0.1%
10 2
0.1%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct27
Distinct (%)4.8%
Missing2083
Missing (%)78.8%
Infinite0
Infinite (%)0.0%
Mean4.3649374
Minimum0
Maximum560
Zeros381
Zeros (%)14.4%
Negative0
Negative (%)0.0%
Memory size23.3 KiB
2024-04-21T00:13:05.892616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation29.484628
Coefficient of variation (CV)6.7548799
Kurtosis235.88404
Mean4.3649374
Median Absolute Deviation (MAD)0
Skewness13.861006
Sum2440
Variance869.34328
MonotonicityNot monotonic
2024-04-21T00:13:06.216470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 381
 
14.4%
2 45
 
1.7%
1 42
 
1.6%
3 26
 
1.0%
4 17
 
0.6%
5 15
 
0.6%
8 7
 
0.3%
183 4
 
0.2%
30 2
 
0.1%
7 2
 
0.1%
Other values (17) 18
 
0.7%
(Missing) 2083
78.8%
ValueCountFrequency (%)
0 381
14.4%
1 42
 
1.6%
2 45
 
1.7%
3 26
 
1.0%
4 17
 
0.6%
5 15
 
0.6%
6 2
 
0.1%
7 2
 
0.1%
8 7
 
0.3%
9 1
 
< 0.1%
ValueCountFrequency (%)
560 1
 
< 0.1%
183 4
0.2%
101 1
 
< 0.1%
100 1
 
< 0.1%
97 1
 
< 0.1%
76 1
 
< 0.1%
51 1
 
< 0.1%
48 1
 
< 0.1%
36 1
 
< 0.1%
34 1
 
< 0.1%

회수건조수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.8 KiB
0
1443 
<NA>
1199 

Length

Max length4
Median length1
Mean length2.3614686
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1443
54.6%
<NA> 1199
45.4%

Length

2024-04-21T00:13:06.650237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:13:06.985926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1443
54.6%
na 1199
45.4%

침대수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.8 KiB
0
1383 
<NA>
1259 

Length

Max length4
Median length1
Mean length2.4295988
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1383
52.3%
<NA> 1259
47.7%

Length

2024-04-21T00:13:07.359403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:13:07.715094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1383
52.3%
na 1259
47.7%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
False
2641 
True
 
1
ValueCountFrequency (%)
False 2641
> 99.9%
True 1
 
< 0.1%
2024-04-21T00:13:07.989896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Unnamed: 50
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2642
Missing (%)100.0%
Memory size23.3 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부Unnamed: 50
01건물위생관리업09_30_04_P33500003350000-206-2021-0000120210104<NA>3폐업2폐업20210112<NA><NA><NA><NA>.00609809부산광역시 금정구 금사동 81-1 금사자동차운전전문학원부산광역시 금정구 공단서로8번길 49, 금사자동차운전전문학원 A동 307호 (금사동)46332고클린20210112173128U2021-01-14 02:40:00.0건물위생관리업392346.245721192844.636332건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
12건물위생관리업09_30_04_P32600003260000-206-2011-0000320111219<NA>3폐업2폐업20181114<NA><NA><NA>02 4647058.00400410인천광역시 중구 덕교동 128-76번지인천광역시 중구 마시란로 51-33 (덕교동)22385(주)성수인력20181114111110I2018-11-16 02:37:41.0건물위생관리업148671.318965436093.419887건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
23건물위생관리업09_30_04_P32700003270000-206-2014-0001420140327<NA>3폐업2폐업20210225<NA><NA><NA>051 503 247046.20601815부산광역시 동구 수정동 425-18 1층부산광역시 동구 망양로 837, 1층 (수정동)48705(주)남영산업20210225124248U2021-02-27 02:40:00.0건물위생관리업386389.025083183804.135721건물위생관리업717700000N0<NA><NA><NA>임대0<NA><NA>00N<NA>
34건물위생관리업09_30_04_P33800003380000-206-2019-0000120190103<NA>3폐업2폐업20201008<NA><NA><NA><NA>33.60613801부산광역시 수영구 광안동 100-10부산광역시 수영구 무학로9번길 46, 1층 (광안동)48269청소협동조합 청소하는사람들 부산경남본점20201008134352U2020-10-10 02:40:00.0건물위생관리업392665.857369186997.207472건물위생관리업201100000N0<NA><NA><NA><NA>00000N<NA>
45건물위생관리업09_30_04_P33200003320000-206-2005-0000220051103<NA>3폐업2폐업20060918<NA><NA><NA>051 341008691.30616819부산광역시 북구 덕천동 388-1번지 대방상가 304호<NA><NA>(주)천우이엔지20060629000000I2018-08-31 23:59:59.0건물위생관리업383443.264424192181.296405건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N<NA>
56건물위생관리업09_30_04_P33200003320000-206-2013-0000220130904<NA>3폐업2폐업20171116<NA><NA><NA>051 342 837746.29616809부산광역시 북구 구포동 1256-15번지부산광역시 북구 시랑로118번길 56 (구포동)46643신흥20171124142705I2018-08-31 23:59:59.0건물위생관리업382931.486707190108.209442건물위생관리업310011000N0<NA><NA><NA>자가0<NA><NA>00N<NA>
67건물위생관리업09_30_04_P33200003320000-206-2011-0000820110726<NA>3폐업2폐업20161129<NA><NA><NA>051 467 831313.80616815부산광역시 북구 덕천동 128-3번지 벽산아파트 상가동 101호부산광역시 북구 만덕3로16번길 45, 상가동 101호 (덕천동, 벽산아파트)46572신항엘엠에스(주)20130902145708I2018-08-31 23:59:59.0건물위생관리업384149.846541192152.635373건물위생관리업601100000N0<NA><NA><NA>임대0<NA><NA>00N<NA>
78건물위생관리업09_30_04_P33200003320000-206-2013-0000120130530<NA>3폐업2폐업20151104<NA><NA><NA>051 343 011028.05616827부산광역시 북구 만덕동 835-7번지부산광역시 북구 덕천로276번길 28 (만덕동)46611좋은크린용역20130530103430I2018-08-31 23:59:59.0건물위생관리업385138.67522191793.713154건물위생관리업2111<NA><NA>000N0<NA><NA><NA>임대0<NA><NA>00N<NA>
89건물위생관리업09_30_04_P33200003320000-206-2012-0000420120525<NA>3폐업2폐업20141006<NA><NA><NA>051 342 211232.18616820부산광역시 북구 덕천동 417-28번지부산광역시 북구 만덕대로40번길 33 (덕천동)46578(주)대한안전공사20130418094931I2018-08-31 23:59:59.0건물위생관리업382968.706137191893.259359건물위생관리업000011000N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
910건물위생관리업09_30_04_P33200003320000-206-2012-0000520120601<NA>3폐업2폐업20150324<NA><NA><NA>070 76450552<NA>616801부산광역시 북구 구포동 1060-313번지부산광역시 북구 구포만세길 28-1, 1층 (구포동)46502킹스환경개발20120618100433I2018-08-31 23:59:59.0건물위생관리업381624.584142191221.308437건물위생관리업101100000N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부Unnamed: 50
26322633건물위생관리업09_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>
26332634건물위생관리업09_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>
26342635건물위생관리업09_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>
26352636건물위생관리업09_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>
26362637건물위생관리업09_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>
26372638건물위생관리업09_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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26392640건물위생관리업09_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>
26402641건물위생관리업09_30_04_P33600003360000-206-2013-0000120130204<NA>1영업/정상1영업<NA><NA><NA><NA>051 971 166354.00618807부산광역시 강서구 대저2동 2440-3부산광역시 강서구 공항앞길221번길 56 (대저2동)46720(주)이레환경20210202152609U2021-02-04 02:40:00.0건물위생관리업377875.274835187827.464522건물위생관리업001100000N0<NA><NA><NA><NA>0<NA><NA>00Y<NA>
26412642건물위생관리업09_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>