Overview

Dataset statistics

Number of variables51
Number of observations2618
Missing cells31613
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

Description2021-04-01
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 (93.9%)Imbalance
위생업태명 is highly imbalanced (93.9%)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 2618 (100.0%) missing valuesMissing
폐업일자 has 955 (36.5%) missing valuesMissing
휴업시작일자 has 2618 (100.0%) missing valuesMissing
휴업종료일자 has 2618 (100.0%) missing valuesMissing
재개업일자 has 2618 (100.0%) missing valuesMissing
소재지전화 has 624 (23.8%) missing valuesMissing
소재지우편번호 has 34 (1.3%) missing valuesMissing
도로명전체주소 has 783 (29.9%) missing valuesMissing
도로명우편번호 has 827 (31.6%) missing valuesMissing
좌표정보(x) has 70 (2.7%) missing valuesMissing
좌표정보(y) has 70 (2.7%) missing valuesMissing
건물지상층수 has 433 (16.5%) missing valuesMissing
건물지하층수 has 591 (22.6%) missing valuesMissing
사용시작지상층 has 685 (26.2%) missing valuesMissing
사용끝지상층 has 947 (36.2%) missing valuesMissing
사용시작지하층 has 1403 (53.6%) missing valuesMissing
사용끝지하층 has 1579 (60.3%) missing valuesMissing
발한실여부 has 72 (2.8%) missing valuesMissing
조건부허가신고사유 has 2612 (99.8%) missing valuesMissing
조건부허가종료일자 has 2611 (99.7%) missing valuesMissing
여성종사자수 has 2117 (80.9%) missing valuesMissing
남성종사자수 has 2072 (79.1%) missing valuesMissing
Unnamed: 50 has 2618 (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 626 (23.9%) zerosZeros
건물지하층수 has 1159 (44.3%) zerosZeros
사용시작지상층 has 354 (13.5%) zerosZeros
사용끝지상층 has 347 (13.3%) zerosZeros
사용시작지하층 has 1041 (39.8%) zerosZeros
사용끝지하층 has 881 (33.7%) zerosZeros
여성종사자수 has 439 (16.8%) zerosZeros
남성종사자수 has 370 (14.1%) zerosZeros

Reproduction

Analysis started2024-04-20 15:29:29.980357
Analysis finished2024-04-20 15:29:32.094764
Duration2.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct2618
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1309.5
Minimum1
Maximum2618
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2024-04-21T00:29:32.287625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile131.85
Q1655.25
median1309.5
Q31963.75
95-th percentile2487.15
Maximum2618
Range2617
Interquartile range (IQR)1308.5

Descriptive statistics

Standard deviation755.89583
Coefficient of variation (CV)0.57724004
Kurtosis-1.2
Mean1309.5
Median Absolute Deviation (MAD)654.5
Skewness0
Sum3428271
Variance571378.5
MonotonicityStrictly increasing
2024-04-21T00:29:32.722410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1760 1
 
< 0.1%
1742 1
 
< 0.1%
1743 1
 
< 0.1%
1744 1
 
< 0.1%
1745 1
 
< 0.1%
1746 1
 
< 0.1%
1747 1
 
< 0.1%
1748 1
 
< 0.1%
1749 1
 
< 0.1%
Other values (2608) 2608
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 (%)
2618 1
< 0.1%
2617 1
< 0.1%
2616 1
< 0.1%
2615 1
< 0.1%
2614 1
< 0.1%
2613 1
< 0.1%
2612 1
< 0.1%
2611 1
< 0.1%
2610 1
< 0.1%
2609 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
건물위생관리업
2618 

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 2618
100.0%

Length

2024-04-21T00:29:33.123493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:29:33.410793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 2618
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
09_30_04_P
2618 

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 2618
100.0%

Length

2024-04-21T00:29:33.724639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:29:34.020343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_30_04_p 2618
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3325397.2
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2024-04-21T00:29:34.306364image/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 deviation44481.631
Coefficient of variation (CV)0.013376336
Kurtosis-1.1245877
Mean3325397.2
Median Absolute Deviation (MAD)30000
Skewness0.20069345
Sum8.70589 × 109
Variance1.9786155 × 109
MonotonicityNot monotonic
2024-04-21T00:29:34.698140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 355
13.6%
3300000 296
11.3%
3270000 238
9.1%
3400000 227
8.7%
3330000 207
7.9%
3370000 201
 
7.7%
3310000 162
 
6.2%
3350000 151
 
5.8%
3380000 140
 
5.3%
3320000 132
 
5.0%
Other values (6) 509
19.4%
ValueCountFrequency (%)
3250000 102
 
3.9%
3260000 75
 
2.9%
3270000 238
9.1%
3280000 27
 
1.0%
3290000 355
13.6%
3300000 296
11.3%
3310000 162
6.2%
3320000 132
 
5.0%
3330000 207
7.9%
3340000 120
 
4.6%
ValueCountFrequency (%)
3400000 227
8.7%
3390000 131
5.0%
3380000 140
5.3%
3370000 201
7.7%
3360000 54
 
2.1%
3350000 151
5.8%
3340000 120
4.6%
3330000 207
7.9%
3320000 132
5.0%
3310000 162
6.2%

관리번호
Text

UNIQUE 

Distinct2618
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
2024-04-21T00:29:35.451358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters57596
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

Unique2618 ?
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%
3400000-206-2010-00021 1
 
< 0.1%
3320000-206-2011-00009 1
 
< 0.1%
3320000-206-2013-00005 1
 
< 0.1%
3320000-206-2015-00002 1
 
< 0.1%
3320000-206-2016-00003 1
 
< 0.1%
3320000-206-2005-00001 1
 
< 0.1%
3320000-206-2011-00007 1
 
< 0.1%
3320000-206-2014-00001 1
 
< 0.1%
3320000-206-2013-00004 1
 
< 0.1%
Other values (2608) 2608
99.6%
2024-04-21T00:29:36.342757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 26735
46.4%
- 7854
 
13.6%
2 6732
 
11.7%
3 5136
 
8.9%
6 3276
 
5.7%
1 2833
 
4.9%
9 1504
 
2.6%
4 1001
 
1.7%
7 988
 
1.7%
5 808
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49742
86.4%
Dash Punctuation 7854
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 26735
53.7%
2 6732
 
13.5%
3 5136
 
10.3%
6 3276
 
6.6%
1 2833
 
5.7%
9 1504
 
3.0%
4 1001
 
2.0%
7 988
 
2.0%
5 808
 
1.6%
8 729
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 7854
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 57596
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 26735
46.4%
- 7854
 
13.6%
2 6732
 
11.7%
3 5136
 
8.9%
6 3276
 
5.7%
1 2833
 
4.9%
9 1504
 
2.6%
4 1001
 
1.7%
7 988
 
1.7%
5 808
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57596
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 26735
46.4%
- 7854
 
13.6%
2 6732
 
11.7%
3 5136
 
8.9%
6 3276
 
5.7%
1 2833
 
4.9%
9 1504
 
2.6%
4 1001
 
1.7%
7 988
 
1.7%
5 808
 
1.4%

인허가일자
Real number (ℝ)

Distinct1953
Distinct (%)74.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20088043
Minimum19870507
Maximum20210223
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2024-04-21T00:29:36.588099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19870507
5-th percentile19960702
Q120040911
median20091108
Q320140829
95-th percentile20191216
Maximum20210223
Range339716
Interquartile range (IQR)99918

Descriptive statistics

Standard deviation71795.629
Coefficient of variation (CV)0.003574048
Kurtosis-0.12682319
Mean20088043
Median Absolute Deviation (MAD)49989.5
Skewness-0.49241367
Sum5.2590496 × 1010
Variance5.1546124 × 109
MonotonicityNot monotonic
2024-04-21T00:29:36.849690image/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%
20140327 5
 
0.2%
20031125 5
 
0.2%
20101217 5
 
0.2%
20110726 5
 
0.2%
20140219 5
 
0.2%
20070614 5
 
0.2%
20000706 5
 
0.2%
Other values (1943) 2565
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 (%)
20210223 2
0.1%
20210218 2
0.1%
20210217 2
0.1%
20210216 3
0.1%
20210215 1
 
< 0.1%
20210205 1
 
< 0.1%
20210204 1
 
< 0.1%
20210201 1
 
< 0.1%
20210126 1
 
< 0.1%
20210118 1
 
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2618
Missing (%)100.0%
Memory size23.1 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
3
1663 
1
955 

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 1663
63.5%
1 955
36.5%

Length

2024-04-21T00:29:37.087555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:29:37.247257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1663
63.5%
1 955
36.5%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
폐업
1663 
영업/정상
955 

Length

Max length5
Median length2
Mean length3.0943468
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1663
63.5%
영업/정상 955
36.5%

Length

2024-04-21T00:29:37.432010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:29:37.605847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1663
63.5%
영업/정상 955
36.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
2
1663 
1
955 

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 1663
63.5%
1 955
36.5%

Length

2024-04-21T00:29:37.774827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:29:38.126379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1663
63.5%
1 955
36.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
폐업
1663 
영업
955 

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 1663
63.5%
영업 955
36.5%

Length

2024-04-21T00:29:38.293712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:29:38.456364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1663
63.5%
영업 955
36.5%

폐업일자
Real number (ℝ)

MISSING 

Distinct1215
Distinct (%)73.1%
Missing955
Missing (%)36.5%
Infinite0
Infinite (%)0.0%
Mean20116209
Minimum19880329
Maximum20210225
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2024-04-21T00:29:38.649345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19880329
5-th percentile20020823
Q120070130
median20121015
Q320170310
95-th percentile20200422
Maximum20210225
Range329896
Interquartile range (IQR)100180.5

Descriptive statistics

Standard deviation59791.224
Coefficient of variation (CV)0.0029722909
Kurtosis-0.47161909
Mean20116209
Median Absolute Deviation (MAD)50008
Skewness-0.45613411
Sum3.3453255 × 1010
Variance3.5749905 × 109
MonotonicityNot monotonic
2024-04-21T00:29:38.909510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20180525 23
 
0.9%
20200428 15
 
0.6%
20110217 10
 
0.4%
20030227 10
 
0.4%
20180808 9
 
0.3%
20041213 8
 
0.3%
20170831 8
 
0.3%
20031124 8
 
0.3%
20031114 7
 
0.3%
20090318 7
 
0.3%
Other values (1205) 1558
59.5%
(Missing) 955
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 (%)
20210225 3
0.1%
20210216 1
 
< 0.1%
20210210 2
0.1%
20210202 1
 
< 0.1%
20210126 1
 
< 0.1%
20210122 2
0.1%
20210112 1
 
< 0.1%
20210111 1
 
< 0.1%
20210105 1
 
< 0.1%
20201230 1
 
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2618
Missing (%)100.0%
Memory size23.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2618
Missing (%)100.0%
Memory size23.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2618
Missing (%)100.0%
Memory size23.1 KiB

소재지전화
Text

MISSING 

Distinct1733
Distinct (%)86.9%
Missing624
Missing (%)23.8%
Memory size20.6 KiB
2024-04-21T00:29:40.107116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.208124
Min length3

Characters and Unicode

Total characters22349
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

Unique1540 ?
Unique (%)77.2%

Sample

1st row02 4647058
2nd row051 503 2470
3rd row051 3410086
4th row051 342 8377
5th row051 467 8313
ValueCountFrequency (%)
051 1769
37.2%
727 58
 
1.2%
070 55
 
1.2%
728 17
 
0.4%
724 15
 
0.3%
502 13
 
0.3%
722 13
 
0.3%
557 12
 
0.3%
465 11
 
0.2%
342 11
 
0.2%
Other values (1933) 2782
58.5%
2024-04-21T00:29:41.492545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 3496
15.6%
0 3414
15.3%
1 3271
14.6%
2779
12.4%
2 1593
7.1%
7 1544
6.9%
6 1393
 
6.2%
4 1375
 
6.2%
3 1322
 
5.9%
8 1247
 
5.6%
Other values (2) 915
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19569
87.6%
Space Separator 2779
 
12.4%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 3496
17.9%
0 3414
17.4%
1 3271
16.7%
2 1593
8.1%
7 1544
7.9%
6 1393
 
7.1%
4 1375
 
7.0%
3 1322
 
6.8%
8 1247
 
6.4%
9 914
 
4.7%
Space Separator
ValueCountFrequency (%)
2779
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22349
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 3496
15.6%
0 3414
15.3%
1 3271
14.6%
2779
12.4%
2 1593
7.1%
7 1544
6.9%
6 1393
 
6.2%
4 1375
 
6.2%
3 1322
 
5.9%
8 1247
 
5.6%
Other values (2) 915
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22349
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 3496
15.6%
0 3414
15.3%
1 3271
14.6%
2779
12.4%
2 1593
7.1%
7 1544
6.9%
6 1393
 
6.2%
4 1375
 
6.2%
3 1322
 
5.9%
8 1247
 
5.6%
Other values (2) 915
 
4.1%
Distinct1551
Distinct (%)59.8%
Missing24
Missing (%)0.9%
Memory size20.6 KiB
2024-04-21T00:29:42.475384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.8670008
Min length3

Characters and Unicode

Total characters12625
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

Unique1254 ?
Unique (%)48.3%

Sample

1st row.00
2nd row.00
3rd row46.20
4th row33.60
5th row91.30
ValueCountFrequency (%)
00 348
 
13.4%
33.00 38
 
1.5%
66.00 21
 
0.8%
40.00 15
 
0.6%
30.00 13
 
0.5%
49.50 12
 
0.5%
36.00 12
 
0.5%
12.00 11
 
0.4%
25.00 11
 
0.4%
99.00 11
 
0.4%
Other values (1541) 2102
81.0%
2024-04-21T00:29:43.671555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2735
21.7%
. 2594
20.5%
1 1074
 
8.5%
2 995
 
7.9%
5 876
 
6.9%
3 855
 
6.8%
6 810
 
6.4%
4 782
 
6.2%
8 705
 
5.6%
7 599
 
4.7%
Other values (2) 600
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10026
79.4%
Other Punctuation 2599
 
20.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2735
27.3%
1 1074
 
10.7%
2 995
 
9.9%
5 876
 
8.7%
3 855
 
8.5%
6 810
 
8.1%
4 782
 
7.8%
8 705
 
7.0%
7 599
 
6.0%
9 595
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 2594
99.8%
, 5
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 12625
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2735
21.7%
. 2594
20.5%
1 1074
 
8.5%
2 995
 
7.9%
5 876
 
6.9%
3 855
 
6.8%
6 810
 
6.4%
4 782
 
6.2%
8 705
 
5.6%
7 599
 
4.7%
Other values (2) 600
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12625
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2735
21.7%
. 2594
20.5%
1 1074
 
8.5%
2 995
 
7.9%
5 876
 
6.9%
3 855
 
6.8%
6 810
 
6.4%
4 782
 
6.2%
8 705
 
5.6%
7 599
 
4.7%
Other values (2) 600
 
4.8%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct605
Distinct (%)23.4%
Missing34
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean610902.89
Minimum400410
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2024-04-21T00:29:43.926483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum400410
5-th percentile601807
Q1607812.5
median611824
Q3614854
95-th percentile619912
Maximum619953
Range219543
Interquartile range (IQR)7041.5

Descriptive statistics

Standard deviation7016.5302
Coefficient of variation (CV)0.011485508
Kurtosis312.18264
Mean610902.89
Median Absolute Deviation (MAD)3991
Skewness-10.577672
Sum1.5785731 × 109
Variance49231696
MonotonicityNot monotonic
2024-04-21T00:29:44.165408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
619951 47
 
1.8%
619952 45
 
1.7%
601837 41
 
1.6%
601839 29
 
1.1%
601836 28
 
1.1%
619953 26
 
1.0%
614844 26
 
1.0%
601838 25
 
1.0%
614865 23
 
0.9%
607804 21
 
0.8%
Other values (595) 2273
86.8%
(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
 
0.6%
619904 5
 
0.2%
Distinct2416
Distinct (%)92.8%
Missing14
Missing (%)0.5%
Memory size20.6 KiB
2024-04-21T00:29:45.209507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length45
Mean length25.412442
Min length2

Characters and Unicode

Total characters66174
Distinct characters405
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2257 ?
Unique (%)86.7%

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 2602
 
20.8%
부산진구 348
 
2.8%
동래구 296
 
2.4%
동구 237
 
1.9%
기장군 226
 
1.8%
해운대구 208
 
1.7%
연제구 200
 
1.6%
초량동 161
 
1.3%
남구 161
 
1.3%
금정구 151
 
1.2%
Other values (3152) 7931
63.3%
2024-04-21T00:29:46.510551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9920
 
15.0%
3214
 
4.9%
3212
 
4.9%
1 3200
 
4.8%
3167
 
4.8%
2702
 
4.1%
2630
 
4.0%
2610
 
3.9%
2488
 
3.8%
2464
 
3.7%
Other values (395) 30567
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39288
59.4%
Decimal Number 13976
 
21.1%
Space Separator 9920
 
15.0%
Dash Punctuation 2375
 
3.6%
Uppercase Letter 247
 
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 (%)
3214
 
8.2%
3212
 
8.2%
3167
 
8.1%
2702
 
6.9%
2630
 
6.7%
2610
 
6.6%
2488
 
6.3%
2464
 
6.3%
2366
 
6.0%
530
 
1.3%
Other values (348) 13905
35.4%
Uppercase Letter
ValueCountFrequency (%)
B 98
39.7%
T 76
30.8%
O 14
 
5.7%
D 9
 
3.6%
A 9
 
3.6%
S 9
 
3.6%
I 6
 
2.4%
K 6
 
2.4%
C 5
 
2.0%
P 4
 
1.6%
Other values (8) 11
 
4.5%
Decimal Number
ValueCountFrequency (%)
1 3200
22.9%
2 1928
13.8%
3 1590
11.4%
4 1318
9.4%
0 1244
 
8.9%
5 1177
 
8.4%
6 1005
 
7.2%
7 949
 
6.8%
8 862
 
6.2%
9 703
 
5.0%
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 (%)
9920
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2375
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 39288
59.4%
Common 26626
40.2%
Latin 260
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3214
 
8.2%
3212
 
8.2%
3167
 
8.1%
2702
 
6.9%
2630
 
6.7%
2610
 
6.6%
2488
 
6.3%
2464
 
6.3%
2366
 
6.0%
530
 
1.3%
Other values (348) 13905
35.4%
Latin
ValueCountFrequency (%)
B 98
37.7%
T 76
29.2%
O 14
 
5.4%
D 9
 
3.5%
A 9
 
3.5%
S 9
 
3.5%
I 6
 
2.3%
K 6
 
2.3%
C 5
 
1.9%
P 4
 
1.5%
Other values (18) 24
 
9.2%
Common
ValueCountFrequency (%)
9920
37.3%
1 3200
 
12.0%
- 2375
 
8.9%
2 1928
 
7.2%
3 1590
 
6.0%
4 1318
 
5.0%
0 1244
 
4.7%
5 1177
 
4.4%
6 1005
 
3.8%
7 949
 
3.6%
Other values (9) 1920
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39288
59.4%
ASCII 26886
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9920
36.9%
1 3200
 
11.9%
- 2375
 
8.8%
2 1928
 
7.2%
3 1590
 
5.9%
4 1318
 
4.9%
0 1244
 
4.6%
5 1177
 
4.4%
6 1005
 
3.7%
7 949
 
3.5%
Other values (37) 2180
 
8.1%
Hangul
ValueCountFrequency (%)
3214
 
8.2%
3212
 
8.2%
3167
 
8.1%
2702
 
6.9%
2630
 
6.7%
2610
 
6.6%
2488
 
6.3%
2464
 
6.3%
2366
 
6.0%
530
 
1.3%
Other values (348) 13905
35.4%

도로명전체주소
Text

MISSING 

Distinct1758
Distinct (%)95.8%
Missing783
Missing (%)29.9%
Memory size20.6 KiB
2024-04-21T00:29:47.733891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length49
Mean length31.716621
Min length20

Characters and Unicode

Total characters58200
Distinct characters422
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

Unique1691 ?
Unique (%)92.2%

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 1834
 
16.3%
부산진구 247
 
2.2%
2층 229
 
2.0%
1층 228
 
2.0%
동래구 205
 
1.8%
기장군 194
 
1.7%
해운대구 162
 
1.4%
연제구 146
 
1.3%
3층 130
 
1.2%
동구 130
 
1.2%
Other values (2431) 7777
68.9%
2024-04-21T00:29:49.396672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9449
 
16.2%
2375
 
4.1%
2305
 
4.0%
2287
 
3.9%
1 2232
 
3.8%
1939
 
3.3%
1919
 
3.3%
1841
 
3.2%
1738
 
3.0%
1727
 
3.0%
Other values (412) 30388
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33653
57.8%
Decimal Number 9605
 
16.5%
Space Separator 9449
 
16.2%
Open Punctuation 1717
 
3.0%
Close Punctuation 1717
 
3.0%
Other Punctuation 1620
 
2.8%
Dash Punctuation 310
 
0.5%
Uppercase Letter 115
 
0.2%
Lowercase Letter 11
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2375
 
7.1%
2305
 
6.8%
2287
 
6.8%
1939
 
5.8%
1919
 
5.7%
1841
 
5.5%
1738
 
5.2%
1727
 
5.1%
961
 
2.9%
919
 
2.7%
Other values (369) 15642
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 2232
23.2%
2 1609
16.8%
3 1159
12.1%
0 881
 
9.2%
4 808
 
8.4%
5 711
 
7.4%
6 606
 
6.3%
7 562
 
5.9%
8 539
 
5.6%
9 498
 
5.2%
Lowercase Letter
ValueCountFrequency (%)
e 2
18.2%
s 2
18.2%
k 2
18.2%
d 1
9.1%
h 1
9.1%
u 1
9.1%
b 1
9.1%
y 1
9.1%
Other Punctuation
ValueCountFrequency (%)
, 1610
99.4%
/ 6
 
0.4%
@ 2
 
0.1%
. 2
 
0.1%
Space Separator
ValueCountFrequency (%)
9449
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1717
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1717
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 310
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33653
57.8%
Common 24421
42.0%
Latin 126
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2375
 
7.1%
2305
 
6.8%
2287
 
6.8%
1939
 
5.8%
1919
 
5.7%
1841
 
5.5%
1738
 
5.2%
1727
 
5.1%
961
 
2.9%
919
 
2.7%
Other values (369) 15642
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 (%)
9449
38.7%
1 2232
 
9.1%
( 1717
 
7.0%
) 1717
 
7.0%
, 1610
 
6.6%
2 1609
 
6.6%
3 1159
 
4.7%
0 881
 
3.6%
4 808
 
3.3%
5 711
 
2.9%
Other values (9) 2528
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33653
57.8%
ASCII 24547
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9449
38.5%
1 2232
 
9.1%
( 1717
 
7.0%
) 1717
 
7.0%
, 1610
 
6.6%
2 1609
 
6.6%
3 1159
 
4.7%
0 881
 
3.6%
4 808
 
3.3%
5 711
 
2.9%
Other values (33) 2654
 
10.8%
Hangul
ValueCountFrequency (%)
2375
 
7.1%
2305
 
6.8%
2287
 
6.8%
1939
 
5.8%
1919
 
5.7%
1841
 
5.5%
1738
 
5.2%
1727
 
5.1%
961
 
2.9%
919
 
2.7%
Other values (369) 15642
46.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct858
Distinct (%)47.9%
Missing827
Missing (%)31.6%
Infinite0
Infinite (%)0.0%
Mean47613.926
Minimum22385
Maximum49524
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2024-04-21T00:29:49.646273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22385
5-th percentile46037
Q146960.5
median47709
Q348315
95-th percentile49260.5
Maximum49524
Range27139
Interquartile range (IQR)1354.5

Descriptive statistics

Standard deviation1141.2626
Coefficient of variation (CV)0.023969093
Kurtosis131.9562
Mean47613.926
Median Absolute Deviation (MAD)722
Skewness-6.0327758
Sum85276541
Variance1302480.4
MonotonicityNot monotonic
2024-04-21T00:29:49.901082image/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 11
 
0.4%
47246 11
 
0.4%
Other values (848) 1623
62.0%
(Missing) 827
31.6%
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%
Distinct2228
Distinct (%)85.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
2024-04-21T00:29:50.618539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length22
Mean length7.1925134
Min length2

Characters and Unicode

Total characters18830
Distinct characters540
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1922 ?
Unique (%)73.4%

Sample

1st row고클린
2nd row(주)성수인력
3rd row(주)남영산업
4th row청소협동조합 청소하는사람들 부산경남본점
5th row(주)천우이엔지
ValueCountFrequency (%)
주식회사 168
 
5.5%
16
 
0.5%
주)만비종합관리 7
 
0.2%
주)만송 7
 
0.2%
시스템 7
 
0.2%
주)금강종합개발 6
 
0.2%
청소나라 6
 
0.2%
유한회사 6
 
0.2%
그린산업 6
 
0.2%
클린 5
 
0.2%
Other values (2341) 2794
92.3%
2024-04-21T00:29:51.618214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1477
 
7.8%
) 1309
 
7.0%
( 1273
 
6.8%
559
 
3.0%
453
 
2.4%
413
 
2.2%
376
 
2.0%
330
 
1.8%
329
 
1.7%
319
 
1.7%
Other values (530) 11992
63.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15446
82.0%
Close Punctuation 1309
 
7.0%
Open Punctuation 1273
 
6.8%
Space Separator 413
 
2.2%
Uppercase Letter 241
 
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 (%)
1477
 
9.6%
559
 
3.6%
453
 
2.9%
376
 
2.4%
330
 
2.1%
329
 
2.1%
319
 
2.1%
303
 
2.0%
294
 
1.9%
245
 
1.6%
Other values (476) 10761
69.7%
Uppercase Letter
ValueCountFrequency (%)
C 41
17.0%
S 23
9.5%
E 22
9.1%
B 18
 
7.5%
G 17
 
7.1%
M 16
 
6.6%
H 16
 
6.6%
N 15
 
6.2%
T 13
 
5.4%
J 8
 
3.3%
Other values (10) 52
21.6%
Lowercase Letter
ValueCountFrequency (%)
e 13
24.1%
o 6
11.1%
a 5
 
9.3%
s 5
 
9.3%
l 4
 
7.4%
n 4
 
7.4%
r 4
 
7.4%
c 3
 
5.6%
t 3
 
5.6%
i 3
 
5.6%
Other values (4) 4
 
7.4%
Decimal Number
ValueCountFrequency (%)
1 16
41.0%
2 8
20.5%
4 3
 
7.7%
0 3
 
7.7%
9 3
 
7.7%
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 (%)
) 1309
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1273
100.0%
Space Separator
ValueCountFrequency (%)
413
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15461
82.1%
Common 3074
 
16.3%
Latin 295
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1477
 
9.6%
559
 
3.6%
453
 
2.9%
376
 
2.4%
330
 
2.1%
329
 
2.1%
319
 
2.1%
303
 
2.0%
294
 
1.9%
245
 
1.6%
Other values (478) 10776
69.7%
Latin
ValueCountFrequency (%)
C 41
13.9%
S 23
 
7.8%
E 22
 
7.5%
B 18
 
6.1%
G 17
 
5.8%
M 16
 
5.4%
H 16
 
5.4%
N 15
 
5.1%
T 13
 
4.4%
e 13
 
4.4%
Other values (24) 101
34.2%
Common
ValueCountFrequency (%)
) 1309
42.6%
( 1273
41.4%
413
 
13.4%
1 16
 
0.5%
& 16
 
0.5%
. 11
 
0.4%
2 8
 
0.3%
, 5
 
0.2%
· 4
 
0.1%
4 3
 
0.1%
Other values (8) 16
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15446
82.0%
ASCII 3363
 
17.9%
None 21
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1477
 
9.6%
559
 
3.6%
453
 
2.9%
376
 
2.4%
330
 
2.1%
329
 
2.1%
319
 
2.1%
303
 
2.0%
294
 
1.9%
245
 
1.6%
Other values (476) 10761
69.7%
ASCII
ValueCountFrequency (%)
) 1309
38.9%
( 1273
37.9%
413
 
12.3%
C 41
 
1.2%
S 23
 
0.7%
E 22
 
0.7%
B 18
 
0.5%
G 17
 
0.5%
1 16
 
0.5%
M 16
 
0.5%
Other values (40) 215
 
6.4%
None
ValueCountFrequency (%)
14
66.7%
· 4
 
19.0%
2
 
9.5%
1
 
4.8%

최종수정시점
Real number (ℝ)

Distinct2363
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0130759 × 1013
Minimum1.9990201 × 1013
Maximum2.0210227 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2024-04-21T00:29:51.865621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990201 × 1013
5-th percentile2.0030212 × 1013
Q12.0080724 × 1013
median2.014073 × 1013
Q32.0181228 × 1013
95-th percentile2.0201113 × 1013
Maximum2.0210227 × 1013
Range2.2002621 × 1011
Interquartile range (IQR)1.0050346 × 1011

Descriptive statistics

Standard deviation6.1165416 × 1010
Coefficient of variation (CV)0.0030384058
Kurtosis-0.94528725
Mean2.0130759 × 1013
Median Absolute Deviation (MAD)4.9599014 × 1010
Skewness-0.54063091
Sum5.2702328 × 1016
Variance3.7412081 × 1021
MonotonicityNot monotonic
2024-04-21T00:29:52.120190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20060616000000 19
 
0.7%
20020419000000 16
 
0.6%
20050920000000 12
 
0.5%
20030403000000 11
 
0.4%
19990201000000 11
 
0.4%
20051110000000 10
 
0.4%
20030404000000 10
 
0.4%
20021112000000 10
 
0.4%
20030521000000 8
 
0.3%
20020403000000 8
 
0.3%
Other values (2353) 2503
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 (%)
20210227210019 1
< 0.1%
20210226155202 1
< 0.1%
20210226105631 1
< 0.1%
20210225175620 1
< 0.1%
20210225124248 1
< 0.1%
20210225102011 1
< 0.1%
20210224120428 1
< 0.1%
20210223152022 1
< 0.1%
20210223134547 1
< 0.1%
20210223102615 1
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
I
2020 
U
598 

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 2020
77.2%
U 598
 
22.8%

Length

2024-04-21T00:29:52.345535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:29:52.504142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2020
77.2%
u 598
 
22.8%
Distinct467
Distinct (%)17.8%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
Minimum2018-08-31 23:59:59
Maximum2021-03-02 02:40:00
2024-04-21T00:29:52.690431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T00:29:52.941856image/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 size20.6 KiB
건물위생관리업
2589 
건물위생관리업 기타
 
21
<NA>
 
8

Length

Max length10
Median length7
Mean length7.0148969
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 2589
98.9%
건물위생관리업 기타 21
 
0.8%
<NA> 8
 
0.3%

Length

2024-04-21T00:29:53.184532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:29:53.360271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 2610
98.9%
기타 21
 
0.8%
na 8
 
0.3%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct1954
Distinct (%)76.7%
Missing70
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean389114.81
Minimum148671.32
Maximum408081.98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2024-04-21T00:29:53.559007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum148671.32
5-th percentile380054.48
Q1385779.55
median388630.28
Q3391494.32
95-th percentile403663.75
Maximum408081.98
Range259410.66
Interquartile range (IQR)5714.7682

Descriptive statistics

Standard deviation8009.1539
Coefficient of variation (CV)0.02058301
Kurtosis318.54851
Mean389114.81
Median Absolute Deviation (MAD)2860.7095
Skewness-10.248043
Sum9.9146454 × 108
Variance64146547
MonotonicityNot monotonic
2024-04-21T00:29:53.813607image/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%
407871.508884898 8
 
0.3%
387869.134317928 8
 
0.3%
387225.613588405 8
 
0.3%
386351.941329364 8
 
0.3%
Other values (1944) 2458
93.9%
(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 

Distinct1954
Distinct (%)76.7%
Missing70
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean188407.07
Minimum174156.62
Maximum436093.42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2024-04-21T00:29:54.345651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174156.62
5-th percentile179713.85
Q1184002.77
median187548.91
Q3191384.84
95-th percentile203500.98
Maximum436093.42
Range261936.8
Interquartile range (IQR)7382.0693

Descriptive statistics

Standard deviation8080.7005
Coefficient of variation (CV)0.042889582
Kurtosis345.90941
Mean188407.07
Median Absolute Deviation (MAD)3708.2121
Skewness11.721151
Sum4.8006122 × 108
Variance65297721
MonotonicityNot monotonic
2024-04-21T00:29:54.759429image/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%
205389.277197702 8
 
0.3%
186381.28184674 8
 
0.3%
186408.726533861 8
 
0.3%
182468.78681462 8
 
0.3%
Other values (1944) 2458
93.9%
(Missing) 70
 
2.7%
ValueCountFrequency (%)
174156.617297535 1
 
< 0.1%
174213.492106852 3
0.1%
174368.201258807 1
 
< 0.1%
174569.500346208 1
 
< 0.1%
174587.185782495 1
 
< 0.1%
174665.706660618 1
 
< 0.1%
174676.412428464 1
 
< 0.1%
174685.736751117 1
 
< 0.1%
174835.290190736 1
 
< 0.1%
175120.936107909 1
 
< 0.1%
ValueCountFrequency (%)
436093.419886508 1
< 0.1%
211676.684692594 1
< 0.1%
210934.754379078 1
< 0.1%
210528.52313338 1
< 0.1%
210316.862590787 1
< 0.1%
210315.278301031 1
< 0.1%
210312.176730581 1
< 0.1%
207754.636746297 1
< 0.1%
207714.152838506 1
< 0.1%
207360.485553669 1
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
건물위생관리업
2589 
건물위생관리업 기타
 
21
<NA>
 
8

Length

Max length10
Median length7
Mean length7.0148969
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 2589
98.9%
건물위생관리업 기타 21
 
0.8%
<NA> 8
 
0.3%

Length

2024-04-21T00:29:55.172394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:29:55.491683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 2610
98.9%
기타 21
 
0.8%
na 8
 
0.3%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct31
Distinct (%)1.4%
Missing433
Missing (%)16.5%
Infinite0
Infinite (%)0.0%
Mean3.7551487
Minimum0
Maximum51
Zeros626
Zeros (%)23.9%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2024-04-21T00:29:55.813637image/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 deviation4.664377
Coefficient of variation (CV)1.2421284
Kurtosis15.980326
Mean3.7551487
Median Absolute Deviation (MAD)2
Skewness3.0506033
Sum8205
Variance21.756412
MonotonicityNot monotonic
2024-04-21T00:29:56.221782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 626
23.9%
4 350
13.4%
3 250
 
9.5%
5 233
 
8.9%
2 232
 
8.9%
1 111
 
4.2%
6 88
 
3.4%
7 51
 
1.9%
10 40
 
1.5%
8 35
 
1.3%
Other values (21) 169
 
6.5%
(Missing) 433
16.5%
ValueCountFrequency (%)
0 626
23.9%
1 111
 
4.2%
2 232
 
8.9%
3 250
 
9.5%
4 350
13.4%
5 233
 
8.9%
6 88
 
3.4%
7 51
 
1.9%
8 35
 
1.3%
9 24
 
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%
Missing591
Missing (%)22.6%
Infinite0
Infinite (%)0.0%
Mean0.61026147
Minimum0
Maximum8
Zeros1159
Zeros (%)44.3%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2024-04-21T00:29:56.583984image/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 deviation0.96178372
Coefficient of variation (CV)1.5760191
Kurtosis9.5471482
Mean0.61026147
Median Absolute Deviation (MAD)0
Skewness2.6474231
Sum1237
Variance0.92502792
MonotonicityNot monotonic
2024-04-21T00:29:56.948459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 1159
44.3%
1 682
26.1%
2 94
 
3.6%
3 41
 
1.6%
5 22
 
0.8%
4 21
 
0.8%
6 7
 
0.3%
8 1
 
< 0.1%
(Missing) 591
22.6%
ValueCountFrequency (%)
0 1159
44.3%
1 682
26.1%
2 94
 
3.6%
3 41
 
1.6%
4 21
 
0.8%
5 22
 
0.8%
6 7
 
0.3%
8 1
 
< 0.1%
ValueCountFrequency (%)
8 1
 
< 0.1%
6 7
 
0.3%
5 22
 
0.8%
4 21
 
0.8%
3 41
 
1.6%
2 94
 
3.6%
1 682
26.1%
0 1159
44.3%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct26
Distinct (%)1.3%
Missing685
Missing (%)26.2%
Infinite0
Infinite (%)0.0%
Mean2.6632178
Minimum0
Maximum48
Zeros354
Zeros (%)13.5%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2024-04-21T00:29:57.326650image/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 deviation3.315513
Coefficient of variation (CV)1.2449275
Kurtosis28.112915
Mean2.6632178
Median Absolute Deviation (MAD)1
Skewness3.9367019
Sum5148
Variance10.992627
MonotonicityNot monotonic
2024-04-21T00:29:57.709466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
2 458
17.5%
1 424
16.2%
0 354
13.5%
3 281
10.7%
4 148
 
5.7%
5 70
 
2.7%
6 45
 
1.7%
7 35
 
1.3%
9 19
 
0.7%
8 19
 
0.7%
Other values (16) 80
 
3.1%
(Missing) 685
26.2%
ValueCountFrequency (%)
0 354
13.5%
1 424
16.2%
2 458
17.5%
3 281
10.7%
4 148
 
5.7%
5 70
 
2.7%
6 45
 
1.7%
7 35
 
1.3%
8 19
 
0.7%
9 19
 
0.7%
ValueCountFrequency (%)
48 1
 
< 0.1%
26 2
 
0.1%
24 2
 
0.1%
23 2
 
0.1%
22 1
 
< 0.1%
21 1
 
< 0.1%
20 4
0.2%
18 1
 
< 0.1%
17 3
0.1%
16 6
0.2%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct25
Distinct (%)1.5%
Missing947
Missing (%)36.2%
Infinite0
Infinite (%)0.0%
Mean2.5332136
Minimum0
Maximum48
Zeros347
Zeros (%)13.3%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2024-04-21T00:29:58.068825image/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 deviation3.2797607
Coefficient of variation (CV)1.2947036
Kurtosis31.766261
Mean2.5332136
Median Absolute Deviation (MAD)1
Skewness4.163419
Sum4233
Variance10.75683
MonotonicityNot monotonic
2024-04-21T00:29:58.467174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
2 384
14.7%
1 369
 
14.1%
0 347
 
13.3%
3 234
 
8.9%
4 128
 
4.9%
5 49
 
1.9%
6 42
 
1.6%
7 29
 
1.1%
8 12
 
0.5%
9 10
 
0.4%
Other values (15) 67
 
2.6%
(Missing) 947
36.2%
ValueCountFrequency (%)
0 347
13.3%
1 369
14.1%
2 384
14.7%
3 234
8.9%
4 128
 
4.9%
5 49
 
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%
Missing1403
Missing (%)53.6%
Infinite0
Infinite (%)0.0%
Mean0.15555556
Minimum0
Maximum5
Zeros1041
Zeros (%)39.8%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2024-04-21T00:29:58.813753image/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 deviation0.4214199
Coefficient of variation (CV)2.7091279
Kurtosis27.789145
Mean0.15555556
Median Absolute Deviation (MAD)0
Skewness4.0328421
Sum189
Variance0.17759473
MonotonicityNot monotonic
2024-04-21T00:29:59.157448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 1041
39.8%
1 167
 
6.4%
2 3
 
0.1%
4 2
 
0.1%
5 1
 
< 0.1%
3 1
 
< 0.1%
(Missing) 1403
53.6%
ValueCountFrequency (%)
0 1041
39.8%
1 167
 
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%
1 167
 
6.4%
0 1041
39.8%

사용끝지하층
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.7%
Missing1579
Missing (%)60.3%
Infinite0
Infinite (%)0.0%
Mean0.1761309
Minimum0
Maximum10
Zeros881
Zeros (%)33.7%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2024-04-21T00:29:59.490112image/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 deviation0.53289485
Coefficient of variation (CV)3.0255615
Kurtosis121.00104
Mean0.1761309
Median Absolute Deviation (MAD)0
Skewness8.0978813
Sum183
Variance0.28397692
MonotonicityNot monotonic
2024-04-21T00:29:59.834194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 881
33.7%
1 148
 
5.7%
2 5
 
0.2%
3 2
 
0.1%
5 1
 
< 0.1%
4 1
 
< 0.1%
10 1
 
< 0.1%
(Missing) 1579
60.3%
ValueCountFrequency (%)
0 881
33.7%
1 148
 
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%
1 148
 
5.7%
0 881
33.7%

한실수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
0
1735 
<NA>
882 
1
 
1

Length

Max length4
Median length1
Mean length2.0106952
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 1735
66.3%
<NA> 882
33.7%
1 1
 
< 0.1%

Length

2024-04-21T00:30:00.230540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:30:00.558583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1735
66.3%
na 882
33.7%
1 1
 
< 0.1%

양실수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
0
1735 
<NA>
882 
29
 
1

Length

Max length4
Median length1
Mean length2.0110772
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 1735
66.3%
<NA> 882
33.7%
29 1
 
< 0.1%

Length

2024-04-21T00:30:00.922386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:30:01.259805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1735
66.3%
na 882
33.7%
29 1
 
< 0.1%

욕실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
0
1736 
<NA>
882 

Length

Max length4
Median length1
Mean length2.0106952
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 1736
66.3%
<NA> 882
33.7%

Length

2024-04-21T00:30:01.594785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:30:01.806990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1736
66.3%
na 882
33.7%

발한실여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing72
Missing (%)2.8%
Memory size5.2 KiB
False
2545 
True
 
1
(Missing)
 
72
ValueCountFrequency (%)
False 2545
97.2%
True 1
 
< 0.1%
(Missing) 72
 
2.8%
2024-04-21T00:30:01.968924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

의자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
0
1735 
<NA>
880 
9
 
2
1
 
1

Length

Max length4
Median length1
Mean length2.0084034
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 1735
66.3%
<NA> 880
33.6%
9 2
 
0.1%
1 1
 
< 0.1%

Length

2024-04-21T00:30:02.186780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:30:02.410117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1735
66.3%
na 880
33.6%
9 2
 
0.1%
1 1
 
< 0.1%
Distinct5
Distinct (%)83.3%
Missing2612
Missing (%)99.8%
Memory size20.6 KiB
2024-04-21T00:30:02.989386image/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%
2024-04-21T00:30:03.971875image/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 size20.6 KiB
<NA>
2612 
20140301
 
2
20140212
 
1
20060825
 
1
20060106
 
1

Length

Max length8
Median length4
Mean length4.0091673
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> 2612
99.8%
20140301 2
 
0.1%
20140212 1
 
< 0.1%
20060825 1
 
< 0.1%
20060106 1
 
< 0.1%
20100210 1
 
< 0.1%

Length

2024-04-21T00:30:04.407362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:30:04.755958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2612
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%
Missing2611
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean20126313
Minimum20061231
Maximum20200415
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2024-04-21T00:30:05.060453image/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
2024-04-21T00:30:05.411859image/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) 2611
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 size20.6 KiB
<NA>
1739 
임대
837 
자가
 
42

Length

Max length4
Median length4
Mean length3.328495
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> 1739
66.4%
임대 837
32.0%
자가 42
 
1.6%

Length

2024-04-21T00:30:05.854015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:30:06.196041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1739
66.4%
임대 837
32.0%
자가 42
 
1.6%

세탁기수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
0
1560 
<NA>
1058 

Length

Max length4
Median length1
Mean length2.2123759
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 1560
59.6%
<NA> 1058
40.4%

Length

2024-04-21T00:30:06.555137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:30:06.870560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1560
59.6%
na 1058
40.4%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct19
Distinct (%)3.8%
Missing2117
Missing (%)80.9%
Infinite0
Infinite (%)0.0%
Mean2.245509
Minimum0
Maximum340
Zeros439
Zeros (%)16.8%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2024-04-21T00:30:07.159207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation18.147
Coefficient of variation (CV)8.0814639
Kurtosis247.31556
Mean2.245509
Median Absolute Deviation (MAD)0
Skewness14.386186
Sum1125
Variance329.3136
MonotonicityNot monotonic
2024-04-21T00:30:07.530922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 439
 
16.8%
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) 2117
80.9%
ValueCountFrequency (%)
0 439
16.8%
1 22
 
0.8%
2 11
 
0.4%
3 4
 
0.2%
4 1
 
< 0.1%
5 4
 
0.2%
7 1
 
< 0.1%
8 2
 
0.1%
9 2
 
0.1%
10 2
 
0.1%
ValueCountFrequency (%)
340 1
 
< 0.1%
102 1
 
< 0.1%
95 4
0.2%
40 1
 
< 0.1%
30 1
 
< 0.1%
26 1
 
< 0.1%
20 2
0.1%
15 1
 
< 0.1%
11 1
 
< 0.1%
10 2
0.1%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct27
Distinct (%)4.9%
Missing2072
Missing (%)79.1%
Infinite0
Infinite (%)0.0%
Mean4.459707
Minimum0
Maximum560
Zeros370
Zeros (%)14.1%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2024-04-21T00:30:07.885627image/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 deviation29.827381
Coefficient of variation (CV)6.6881931
Kurtosis230.41598
Mean4.459707
Median Absolute Deviation (MAD)0
Skewness13.699667
Sum2435
Variance889.67269
MonotonicityNot monotonic
2024-04-21T00:30:08.246475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 370
 
14.1%
2 44
 
1.7%
1 42
 
1.6%
3 25
 
1.0%
4 17
 
0.6%
5 15
 
0.6%
8 7
 
0.3%
183 4
 
0.2%
30 2
 
0.1%
7 2
 
0.1%
Other values (17) 18
 
0.7%
(Missing) 2072
79.1%
ValueCountFrequency (%)
0 370
14.1%
1 42
 
1.6%
2 44
 
1.7%
3 25
 
1.0%
4 17
 
0.6%
5 15
 
0.6%
6 2
 
0.1%
7 2
 
0.1%
8 7
 
0.3%
9 1
 
< 0.1%
ValueCountFrequency (%)
560 1
 
< 0.1%
183 4
0.2%
101 1
 
< 0.1%
100 1
 
< 0.1%
97 1
 
< 0.1%
76 1
 
< 0.1%
51 1
 
< 0.1%
48 1
 
< 0.1%
36 1
 
< 0.1%
34 1
 
< 0.1%

회수건조수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
0
1420 
<NA>
1198 

Length

Max length4
Median length1
Mean length2.3728037
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 1420
54.2%
<NA> 1198
45.8%

Length

2024-04-21T00:30:08.662121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:30:08.989210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1420
54.2%
na 1198
45.8%

침대수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
0
1359 
<NA>
1259 

Length

Max length4
Median length1
Mean length2.4427044
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 1359
51.9%
<NA> 1259
48.1%

Length

2024-04-21T00:30:09.340751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:30:09.669515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1359
51.9%
na 1259
48.1%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
False
2617 
True
 
1
ValueCountFrequency (%)
False 2617
> 99.9%
True 1
 
< 0.1%
2024-04-21T00:30:09.927857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Unnamed: 50
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2618
Missing (%)100.0%
Memory size23.1 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
26082609건물위생관리업09_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>
26092610건물위생관리업09_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>
26102611건물위생관리업09_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>
26112612건물위생관리업09_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>
26122613건물위생관리업09_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>
26132614건물위생관리업09_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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26152616건물위생관리업09_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>
26162617건물위생관리업09_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>
26172618건물위생관리업09_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>