Overview

Dataset statistics

Number of variables37
Number of observations53
Missing cells644
Missing cells (%)32.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.6 KiB
Average record size in memory321.4 B

Variable types

Numeric9
Categorical13
Unsupported8
Text7

Dataset

Description22년06월_6270000_대구광역시_09_30_07_P_단독정화조오수처리시설설계시공업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000093755&dataSetDetailId=DDI_0000093815&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
환경업무구분명 has constant value ""Constant
영업상태구분코드 is highly imbalanced (67.3%)Imbalance
영업상태명 is highly imbalanced (67.3%)Imbalance
상세영업상태코드 is highly imbalanced (67.4%)Imbalance
상세영업상태명 is highly imbalanced (67.4%)Imbalance
휴업시작일자 is highly imbalanced (86.5%)Imbalance
휴업종료일자 is highly imbalanced (86.5%)Imbalance
데이터갱신일자 is highly imbalanced (68.9%)Imbalance
배출시설연간가동일수 is highly imbalanced (86.5%)Imbalance
방지시설연간가동일수 is highly imbalanced (86.5%)Imbalance
인허가취소일자 has 53 (100.0%) missing valuesMissing
폐업일자 has 6 (11.3%) missing valuesMissing
재개업일자 has 53 (100.0%) missing valuesMissing
소재지전화 has 25 (47.2%) missing valuesMissing
소재지면적 has 53 (100.0%) missing valuesMissing
소재지우편번호 has 5 (9.4%) missing valuesMissing
소재지전체주소 has 1 (1.9%) missing valuesMissing
도로명전체주소 has 21 (39.6%) missing valuesMissing
도로명우편번호 has 46 (86.8%) missing valuesMissing
업태구분명 has 47 (88.7%) missing valuesMissing
좌표정보(X) has 11 (20.8%) missing valuesMissing
좌표정보(Y) has 11 (20.8%) missing valuesMissing
업종구분명 has 47 (88.7%) missing valuesMissing
종별명 has 53 (100.0%) missing valuesMissing
주생산품명 has 53 (100.0%) missing valuesMissing
배출시설조업시간 has 53 (100.0%) missing valuesMissing
방지시설조업시간 has 53 (100.0%) missing valuesMissing
사업자등록번호 has 53 (100.0%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
최종수정시점 has unique valuesUnique
인허가취소일자 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
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
종별명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
주생산품명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
배출시설조업시간 is an unsupported type, check if it needs cleaning or further analysisUnsupported
방지시설조업시간 is an unsupported type, check if it needs cleaning or further analysisUnsupported
사업자등록번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-20 18:20:40.839708
Analysis finished2024-04-20 18:20:41.547161
Duration0.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27
Minimum1
Maximum53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size605.0 B
2024-04-21T03:20:41.680236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.6
Q114
median27
Q340
95-th percentile50.4
Maximum53
Range52
Interquartile range (IQR)26

Descriptive statistics

Standard deviation15.443445
Coefficient of variation (CV)0.57197945
Kurtosis-1.2
Mean27
Median Absolute Deviation (MAD)13
Skewness0
Sum1431
Variance238.5
MonotonicityStrictly increasing
2024-04-21T03:20:41.932864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.9%
41 1
 
1.9%
30 1
 
1.9%
31 1
 
1.9%
32 1
 
1.9%
33 1
 
1.9%
34 1
 
1.9%
35 1
 
1.9%
36 1
 
1.9%
37 1
 
1.9%
Other values (43) 43
81.1%
ValueCountFrequency (%)
1 1
1.9%
2 1
1.9%
3 1
1.9%
4 1
1.9%
5 1
1.9%
6 1
1.9%
7 1
1.9%
8 1
1.9%
9 1
1.9%
10 1
1.9%
ValueCountFrequency (%)
53 1
1.9%
52 1
1.9%
51 1
1.9%
50 1
1.9%
49 1
1.9%
48 1
1.9%
47 1
1.9%
46 1
1.9%
45 1
1.9%
44 1
1.9%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size552.0 B
단독정화조/오수처리시설설계시공업
53 

Length

Max length17
Median length17
Mean length17
Min length17

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row단독정화조/오수처리시설설계시공업
2nd row단독정화조/오수처리시설설계시공업
3rd row단독정화조/오수처리시설설계시공업
4th row단독정화조/오수처리시설설계시공업
5th row단독정화조/오수처리시설설계시공업

Common Values

ValueCountFrequency (%)
단독정화조/오수처리시설설계시공업 53
100.0%

Length

2024-04-21T03:20:42.155052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:20:42.311379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단독정화조/오수처리시설설계시공업 53
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size552.0 B
09_30_07_P
53 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09_30_07_P
2nd row09_30_07_P
3rd row09_30_07_P
4th row09_30_07_P
5th row09_30_07_P

Common Values

ValueCountFrequency (%)
09_30_07_P 53
100.0%

Length

2024-04-21T03:20:42.476422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:20:42.732511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_30_07_p 53
100.0%

개방자치단체코드
Real number (ℝ)

Distinct7
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3459811.3
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size605.0 B
2024-04-21T03:20:42.996984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3420000
Q13450000
median3470000
Q33470000
95-th percentile3480000
Maximum3480000
Range70000
Interquartile range (IQR)20000

Descriptive statistics

Standard deviation17703.82
Coefficient of variation (CV)0.0051169901
Kurtosis1.4358668
Mean3459811.3
Median Absolute Deviation (MAD)10000
Skewness-1.3966269
Sum1.8337 × 108
Variance3.1342525 × 108
MonotonicityIncreasing
2024-04-21T03:20:43.355454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
3470000 22
41.5%
3460000 10
18.9%
3450000 8
 
15.1%
3480000 6
 
11.3%
3430000 3
 
5.7%
3410000 2
 
3.8%
3420000 2
 
3.8%
ValueCountFrequency (%)
3410000 2
 
3.8%
3420000 2
 
3.8%
3430000 3
 
5.7%
3450000 8
 
15.1%
3460000 10
18.9%
3470000 22
41.5%
3480000 6
 
11.3%
ValueCountFrequency (%)
3480000 6
 
11.3%
3470000 22
41.5%
3460000 10
18.9%
3450000 8
 
15.1%
3430000 3
 
5.7%
3420000 2
 
3.8%
3410000 2
 
3.8%

관리번호
Real number (ℝ)

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4598119 × 1017
Minimum3.4100005 × 1017
Maximum3.4800005 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size605.0 B
2024-04-21T03:20:43.949687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.4100005 × 1017
5-th percentile3.4200005 × 1017
Q13.4500005 × 1017
median3.4700005 × 1017
Q33.4700005 × 1017
95-th percentile3.4800005 × 1017
Maximum3.4800005 × 1017
Range7.0000002 × 1015
Interquartile range (IQR)2 × 1015

Descriptive statistics

Standard deviation1.770382 × 1015
Coefficient of variation (CV)0.0051169893
Kurtosis1.4358669
Mean3.4598119 × 1017
Median Absolute Deviation (MAD)1 × 1015
Skewness-1.3966269
Sum-1.097412 × 1017
Variance3.1342526 × 1030
MonotonicityNot monotonic
2024-04-21T03:20:44.398245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
341000054000000003 1
 
1.9%
347000054200400003 1
 
1.9%
347000054200300012 1
 
1.9%
347000054200200108 1
 
1.9%
347000054200400008 1
 
1.9%
347000054200400005 1
 
1.9%
347000054200600001 1
 
1.9%
347000054200500003 1
 
1.9%
347000054200500002 1
 
1.9%
347000054200500001 1
 
1.9%
Other values (43) 43
81.1%
ValueCountFrequency (%)
341000054000000003 1
1.9%
341000054200400004 1
1.9%
342000054200400003 1
1.9%
342000054200600001 1
1.9%
343000054200400001 1
1.9%
343000054200900001 1
1.9%
343000054201400001 1
1.9%
345000054200300001 1
1.9%
345000054200300002 1
1.9%
345000054200300003 1
1.9%
ValueCountFrequency (%)
348000054200800001 1
1.9%
348000054200600001 1
1.9%
348000054200400003 1
1.9%
348000054200400002 1
1.9%
348000054200200001 1
1.9%
348000054199900001 1
1.9%
347000054200600001 1
1.9%
347000054200500003 1
1.9%
347000054200500002 1
1.9%
347000054200500001 1
1.9%

인허가일자
Real number (ℝ)

Distinct51
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20035428
Minimum19950427
Maximum20140806
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size605.0 B
2024-04-21T03:20:44.833504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19950427
5-th percentile19976955
Q120021220
median20040624
Q320050624
95-th percentile20090362
Maximum20140806
Range190379
Interquartile range (IQR)29404

Descriptive statistics

Standard deviation36107.383
Coefficient of variation (CV)0.0018021767
Kurtosis1.833166
Mean20035428
Median Absolute Deviation (MAD)10081
Skewness0.3794533
Sum1.0618777 × 109
Variance1.3037431 × 109
MonotonicityNot monotonic
2024-04-21T03:20:45.307105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20040624 2
 
3.8%
20050701 2
 
3.8%
20040720 1
 
1.9%
20030422 1
 
1.9%
20030805 1
 
1.9%
20021220 1
 
1.9%
20040719 1
 
1.9%
20040625 1
 
1.9%
20060714 1
 
1.9%
20050801 1
 
1.9%
Other values (41) 41
77.4%
ValueCountFrequency (%)
19950427 1
1.9%
19970304 1
1.9%
19971002 1
1.9%
19980923 1
1.9%
19981202 1
1.9%
19990223 1
1.9%
19990414 1
1.9%
19990730 1
1.9%
19990913 1
1.9%
19991101 1
1.9%
ValueCountFrequency (%)
20140806 1
1.9%
20140407 1
1.9%
20090724 1
1.9%
20090121 1
1.9%
20081231 1
1.9%
20060714 1
1.9%
20060602 1
1.9%
20060510 1
1.9%
20060303 1
1.9%
20050801 1
1.9%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing53
Missing (%)100.0%
Memory size605.0 B

영업상태구분코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size552.0 B
3
48 
1
 
4
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
3 48
90.6%
1 4
 
7.5%
2 1
 
1.9%

Length

2024-04-21T03:20:45.730050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:20:46.034460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 48
90.6%
1 4
 
7.5%
2 1
 
1.9%

영업상태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size552.0 B
폐업
48 
영업/정상
 
4
휴업
 
1

Length

Max length5
Median length2
Mean length2.2264151
Min length2

Unique

Unique1 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 48
90.6%
영업/정상 4
 
7.5%
휴업 1
 
1.9%

Length

2024-04-21T03:20:46.376824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:20:46.696782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 48
90.6%
영업/정상 4
 
7.5%
휴업 1
 
1.9%

상세영업상태코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size552.0 B
2
47 
11
 
4
1
 
1
4
 
1

Length

Max length2
Median length1
Mean length1.0754717
Min length1

Unique

Unique2 ?
Unique (%)3.8%

Sample

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

Common Values

ValueCountFrequency (%)
2 47
88.7%
11 4
 
7.5%
1 1
 
1.9%
4 1
 
1.9%

Length

2024-04-21T03:20:47.033664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:20:47.351756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 47
88.7%
11 4
 
7.5%
1 1
 
1.9%
4 1
 
1.9%

상세영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size552.0 B
폐업
47 
영업
 
4
휴업
 
1
폐쇄
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique2 ?
Unique (%)3.8%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 47
88.7%
영업 4
 
7.5%
휴업 1
 
1.9%
폐쇄 1
 
1.9%

Length

2024-04-21T03:20:47.682681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:20:47.989476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 47
88.7%
영업 4
 
7.5%
휴업 1
 
1.9%
폐쇄 1
 
1.9%

폐업일자
Real number (ℝ)

MISSING 

Distinct41
Distinct (%)87.2%
Missing6
Missing (%)11.3%
Infinite0
Infinite (%)0.0%
Mean20086450
Minimum20030722
Maximum20190531
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size605.0 B
2024-04-21T03:20:48.319688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030722
5-th percentile20037012
Q120055710
median20071127
Q320091162
95-th percentile20174898
Maximum20190531
Range159809
Interquartile range (IQR)35451.5

Descriptive statistics

Standard deviation42021.574
Coefficient of variation (CV)0.0020920358
Kurtosis0.15001704
Mean20086450
Median Absolute Deviation (MAD)20013
Skewness1.0201148
Sum9.4406317 × 108
Variance1.7658127 × 109
MonotonicityNot monotonic
2024-04-21T03:20:48.743814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
20090909 4
 
7.5%
20050504 2
 
3.8%
20050601 2
 
3.8%
20140103 2
 
3.8%
20150518 1
 
1.9%
20090407 1
 
1.9%
20080703 1
 
1.9%
20061105 1
 
1.9%
20051019 1
 
1.9%
20070709 1
 
1.9%
Other values (31) 31
58.5%
(Missing) 6
 
11.3%
ValueCountFrequency (%)
20030722 1
1.9%
20031110 1
1.9%
20031230 1
1.9%
20050504 2
3.8%
20050601 2
3.8%
20050623 1
1.9%
20050907 1
1.9%
20050914 1
1.9%
20051019 1
1.9%
20051114 1
1.9%
ValueCountFrequency (%)
20190531 1
1.9%
20181120 1
1.9%
20181109 1
1.9%
20160407 1
1.9%
20150610 1
1.9%
20150518 1
1.9%
20141118 1
1.9%
20141104 1
1.9%
20140103 2
3.8%
20100111 1
1.9%

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size552.0 B
<NA>
52 
20210126
 
1

Length

Max length8
Median length4
Mean length4.0754717
Min length4

Unique

Unique1 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 52
98.1%
20210126 1
 
1.9%

Length

2024-04-21T03:20:49.149052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:20:49.330583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 52
98.1%
20210126 1
 
1.9%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size552.0 B
<NA>
52 
20220101
 
1

Length

Max length8
Median length4
Mean length4.0754717
Min length4

Unique

Unique1 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 52
98.1%
20220101 1
 
1.9%

Length

2024-04-21T03:20:49.521438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:20:49.710134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 52
98.1%
20220101 1
 
1.9%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing53
Missing (%)100.0%
Memory size605.0 B

소재지전화
Text

MISSING 

Distinct27
Distinct (%)96.4%
Missing25
Missing (%)47.2%
Memory size552.0 B
2024-04-21T03:20:50.172704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.892857
Min length7

Characters and Unicode

Total characters305
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

Unique26 ?
Unique (%)92.9%

Sample

1st row952-5570
2nd row5635123
3rd row053-555-6171
4th row053 384 3347
5th row053 604 3977
ValueCountFrequency (%)
053 12
25.0%
6218282 2
 
4.2%
0535922301 1
 
2.1%
5624400 1
 
2.1%
525 1
 
2.1%
9492 1
 
2.1%
5922309 1
 
2.1%
587 1
 
2.1%
0436 1
 
2.1%
5238481 1
 
2.1%
Other values (26) 26
54.2%
2024-04-21T03:20:50.896738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 55
18.0%
5 53
17.4%
0 39
12.8%
2 29
9.5%
6 26
8.5%
20
 
6.6%
- 17
 
5.6%
8 16
 
5.2%
7 15
 
4.9%
1 13
 
4.3%
Other values (2) 22
 
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 268
87.9%
Space Separator 20
 
6.6%
Dash Punctuation 17
 
5.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 55
20.5%
5 53
19.8%
0 39
14.6%
2 29
10.8%
6 26
9.7%
8 16
 
6.0%
7 15
 
5.6%
1 13
 
4.9%
4 13
 
4.9%
9 9
 
3.4%
Space Separator
ValueCountFrequency (%)
20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 305
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 55
18.0%
5 53
17.4%
0 39
12.8%
2 29
9.5%
6 26
8.5%
20
 
6.6%
- 17
 
5.6%
8 16
 
5.2%
7 15
 
4.9%
1 13
 
4.3%
Other values (2) 22
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 305
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 55
18.0%
5 53
17.4%
0 39
12.8%
2 29
9.5%
6 26
8.5%
20
 
6.6%
- 17
 
5.6%
8 16
 
5.2%
7 15
 
4.9%
1 13
 
4.3%
Other values (2) 22
 
7.2%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing53
Missing (%)100.0%
Memory size605.0 B

소재지우편번호
Text

MISSING 

Distinct36
Distinct (%)75.0%
Missing5
Missing (%)9.4%
Memory size552.0 B
2024-04-21T03:20:51.514543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters288
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)56.2%

Sample

1st row700380
2nd row700380
3rd row701290
4th row701011
5th row703833
ValueCountFrequency (%)
704340 4
 
8.3%
704240 3
 
6.2%
700380 2
 
4.2%
704170 2
 
4.2%
704150 2
 
4.2%
704120 2
 
4.2%
704220 2
 
4.2%
704130 2
 
4.2%
706829 2
 
4.2%
704190 1
 
2.1%
Other values (26) 26
54.2%
2024-04-21T03:20:52.332380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 88
30.6%
7 53
18.4%
4 32
 
11.1%
1 29
 
10.1%
2 25
 
8.7%
3 20
 
6.9%
8 16
 
5.6%
6 9
 
3.1%
5 5
 
1.7%
9 5
 
1.7%
Other values (4) 6
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 282
97.9%
Lowercase Letter 4
 
1.4%
Space Separator 2
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 88
31.2%
7 53
18.8%
4 32
 
11.3%
1 29
 
10.3%
2 25
 
8.9%
3 20
 
7.1%
8 16
 
5.7%
6 9
 
3.2%
5 5
 
1.8%
9 5
 
1.8%
Lowercase Letter
ValueCountFrequency (%)
l 2
50.0%
n 1
25.0%
u 1
25.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 284
98.6%
Latin 4
 
1.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 88
31.0%
7 53
18.7%
4 32
 
11.3%
1 29
 
10.2%
2 25
 
8.8%
3 20
 
7.0%
8 16
 
5.6%
6 9
 
3.2%
5 5
 
1.8%
9 5
 
1.8%
Latin
ValueCountFrequency (%)
l 2
50.0%
n 1
25.0%
u 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 288
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 88
30.6%
7 53
18.4%
4 32
 
11.1%
1 29
 
10.1%
2 25
 
8.7%
3 20
 
6.9%
8 16
 
5.6%
6 9
 
3.1%
5 5
 
1.7%
9 5
 
1.7%
Other values (4) 6
 
2.1%

소재지전체주소
Text

MISSING 

Distinct43
Distinct (%)82.7%
Missing1
Missing (%)1.9%
Memory size552.0 B
2024-04-21T03:20:53.282210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length29
Mean length21.365385
Min length18

Characters and Unicode

Total characters1111
Distinct characters82
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)67.3%

Sample

1st row대구광역시 중구 달성동 121-4
2nd row대구광역시 중구 달성동 121-4
3rd row대구광역시 동구 각산동 295-5
4th row대구광역시 동구 신암동 722-12
5th row대구광역시 서구 중리동 1120-10
ValueCountFrequency (%)
대구광역시 52
23.5%
달서구 22
 
10.0%
수성구 10
 
4.5%
북구 8
 
3.6%
달성군 5
 
2.3%
송현동 4
 
1.8%
산격동 4
 
1.8%
1941-8 3
 
1.4%
서구 3
 
1.4%
상동 3
 
1.4%
Other values (85) 107
48.4%
2024-04-21T03:20:54.675001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
241
21.7%
구 99
 
8.9%
대 54
 
4.9%
1 54
 
4.9%
광 52
 
4.7%
역 52
 
4.7%
시 52
 
4.7%
동 52
 
4.7%
- 44
 
4.0%
2 31
 
2.8%
Other values (72) 380
34.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 593
53.4%
Space Separator 241
21.7%
Decimal Number 230
 
20.7%
Dash Punctuation 44
 
4.0%
Uppercase Letter 1
 
0.1%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 99
16.7%
대 54
 
9.1%
광 52
 
8.8%
역 52
 
8.8%
시 52
 
8.8%
동 52
 
8.8%
달 29
 
4.9%
서 25
 
4.2%
성 18
 
3.0%
산 14
 
2.4%
Other values (57) 146
24.6%
Decimal Number
ValueCountFrequency (%)
1 54
23.5%
2 31
13.5%
6 25
10.9%
4 23
10.0%
9 17
 
7.4%
5 17
 
7.4%
7 17
 
7.4%
3 16
 
7.0%
0 16
 
7.0%
8 14
 
6.1%
Space Separator
ValueCountFrequency (%)
241
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 593
53.4%
Common 517
46.5%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 99
16.7%
대 54
 
9.1%
광 52
 
8.8%
역 52
 
8.8%
시 52
 
8.8%
동 52
 
8.8%
달 29
 
4.9%
서 25
 
4.2%
성 18
 
3.0%
산 14
 
2.4%
Other values (57) 146
24.6%
Common
ValueCountFrequency (%)
241
46.6%
1 54
 
10.4%
- 44
 
8.5%
2 31
 
6.0%
6 25
 
4.8%
4 23
 
4.4%
9 17
 
3.3%
5 17
 
3.3%
7 17
 
3.3%
3 16
 
3.1%
Other values (4) 32
 
6.2%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 593
53.4%
ASCII 518
46.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
241
46.5%
1 54
 
10.4%
- 44
 
8.5%
2 31
 
6.0%
6 25
 
4.8%
4 23
 
4.4%
9 17
 
3.3%
5 17
 
3.3%
7 17
 
3.3%
3 16
 
3.1%
Other values (5) 33
 
6.4%
Hangul
ValueCountFrequency (%)
구 99
16.7%
대 54
 
9.1%
광 52
 
8.8%
역 52
 
8.8%
시 52
 
8.8%
동 52
 
8.8%
달 29
 
4.9%
서 25
 
4.2%
성 18
 
3.0%
산 14
 
2.4%
Other values (57) 146
24.6%

도로명전체주소
Text

MISSING 

Distinct27
Distinct (%)84.4%
Missing21
Missing (%)39.6%
Memory size552.0 B
2024-04-21T03:20:55.537349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length30
Mean length25.21875
Min length21

Characters and Unicode

Total characters807
Distinct characters86
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)68.8%

Sample

1st row대구광역시 동구 평화로 27 (신암동)
2nd row대구광역시 서구 와룡로83길 13 (이현동)
3rd row대구광역시 북구 학남로17길 20-39 (국우동)
4th row대구광역시 수성구 수성로24길 16 (상동)
5th row대구광역시 수성구 동대구로 111 (황금동)
ValueCountFrequency (%)
대구광역시 32
 
20.0%
달서구 16
 
10.0%
수성구 8
 
5.0%
달성군 5
 
3.1%
45 3
 
1.9%
24 3
 
1.9%
화원읍 3
 
1.9%
상동 3
 
1.9%
6 2
 
1.2%
본리동 2
 
1.2%
Other values (66) 83
51.9%
2024-04-21T03:20:56.520621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
147
18.2%
구 65
 
8.1%
대 37
 
4.6%
동 34
 
4.2%
광 32
 
4.0%
역 32
 
4.0%
시 32
 
4.0%
로 31
 
3.8%
( 28
 
3.5%
) 28
 
3.5%
Other values (76) 341
42.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 486
60.2%
Space Separator 147
 
18.2%
Decimal Number 112
 
13.9%
Open Punctuation 28
 
3.5%
Close Punctuation 28
 
3.5%
Dash Punctuation 5
 
0.6%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 65
13.4%
대 37
 
7.6%
동 34
 
7.0%
광 32
 
6.6%
역 32
 
6.6%
시 32
 
6.6%
로 31
 
6.4%
달 24
 
4.9%
성 22
 
4.5%
서 22
 
4.5%
Other values (61) 155
31.9%
Decimal Number
ValueCountFrequency (%)
1 24
21.4%
2 17
15.2%
4 15
13.4%
3 11
9.8%
5 10
8.9%
7 9
 
8.0%
6 8
 
7.1%
0 7
 
6.2%
9 6
 
5.4%
8 5
 
4.5%
Space Separator
ValueCountFrequency (%)
147
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 486
60.2%
Common 321
39.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 65
13.4%
대 37
 
7.6%
동 34
 
7.0%
광 32
 
6.6%
역 32
 
6.6%
시 32
 
6.6%
로 31
 
6.4%
달 24
 
4.9%
성 22
 
4.5%
서 22
 
4.5%
Other values (61) 155
31.9%
Common
ValueCountFrequency (%)
147
45.8%
( 28
 
8.7%
) 28
 
8.7%
1 24
 
7.5%
2 17
 
5.3%
4 15
 
4.7%
3 11
 
3.4%
5 10
 
3.1%
7 9
 
2.8%
6 8
 
2.5%
Other values (5) 24
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 486
60.2%
ASCII 321
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
147
45.8%
( 28
 
8.7%
) 28
 
8.7%
1 24
 
7.5%
2 17
 
5.3%
4 15
 
4.7%
3 11
 
3.4%
5 10
 
3.1%
7 9
 
2.8%
6 8
 
2.5%
Other values (5) 24
 
7.5%
Hangul
ValueCountFrequency (%)
구 65
13.4%
대 37
 
7.6%
동 34
 
7.0%
광 32
 
6.6%
역 32
 
6.6%
시 32
 
6.6%
로 31
 
6.4%
달 24
 
4.9%
성 22
 
4.5%
서 22
 
4.5%
Other values (61) 155
31.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)100.0%
Missing46
Missing (%)86.8%
Infinite0
Infinite (%)0.0%
Mean515557
Minimum41419
Maximum706829
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size605.0 B
2024-04-21T03:20:56.704957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41419
5-th percentile41877.7
Q1372384
median704240
Q3705821.5
95-th percentile706828.4
Maximum706829
Range665410
Interquartile range (IQR)333437.5

Descriptive statistics

Standard deviation323380.44
Coefficient of variation (CV)0.62724478
Kurtosis-0.8400434
Mean515557
Median Absolute Deviation (MAD)2587
Skewness-1.2295231
Sum3608899
Variance1.0457491 × 1011
MonotonicityNot monotonic
2024-04-21T03:20:56.878765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
701820 1
 
1.9%
41419 1
 
1.9%
706827 1
 
1.9%
706829 1
 
1.9%
704240 1
 
1.9%
704816 1
 
1.9%
42948 1
 
1.9%
(Missing) 46
86.8%
ValueCountFrequency (%)
41419 1
1.9%
42948 1
1.9%
701820 1
1.9%
704240 1
1.9%
704816 1
1.9%
706827 1
1.9%
706829 1
1.9%
ValueCountFrequency (%)
706829 1
1.9%
706827 1
1.9%
704816 1
1.9%
704240 1
1.9%
701820 1
1.9%
42948 1
1.9%
41419 1
1.9%

사업장명
Text

Distinct44
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Memory size552.0 B
2024-04-21T03:20:57.604107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length7.5471698
Min length4

Characters and Unicode

Total characters400
Distinct characters82
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)67.9%

Sample

1st row주식회사 기술신환경
2nd row(주)기술신환경
3rd row한일기공
4th row우경환경건설
5th row거성환경(주)
ValueCountFrequency (%)
사하라환경건설 3
 
5.5%
주)선일인바텍 2
 
3.6%
대일엔지니어링(주 2
 
3.6%
주)이코우 2
 
3.6%
주)유일환경건설 2
 
3.6%
우경환경건설 2
 
3.6%
주)로얄정공 2
 
3.6%
주)기술신환경 2
 
3.6%
주)한도엔지니어링 1
 
1.8%
세하주식회사 1
 
1.8%
Other values (36) 36
65.5%
2024-04-21T03:20:58.569571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 42
 
10.5%
( 39
 
9.8%
) 39
 
9.8%
경 22
 
5.5%
환 20
 
5.0%
엔 12
 
3.0%
건 12
 
3.0%
설 11
 
2.8%
지 10
 
2.5%
일 10
 
2.5%
Other values (72) 183
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 320
80.0%
Open Punctuation 39
 
9.8%
Close Punctuation 39
 
9.8%
Space Separator 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 42
 
13.1%
경 22
 
6.9%
환 20
 
6.2%
엔 12
 
3.8%
건 12
 
3.8%
설 11
 
3.4%
지 10
 
3.1%
일 10
 
3.1%
기 9
 
2.8%
이 8
 
2.5%
Other values (69) 164
51.2%
Open Punctuation
ValueCountFrequency (%)
( 39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 320
80.0%
Common 80
 
20.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 42
 
13.1%
경 22
 
6.9%
환 20
 
6.2%
엔 12
 
3.8%
건 12
 
3.8%
설 11
 
3.4%
지 10
 
3.1%
일 10
 
3.1%
기 9
 
2.8%
이 8
 
2.5%
Other values (69) 164
51.2%
Common
ValueCountFrequency (%)
( 39
48.8%
) 39
48.8%
2
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 320
80.0%
ASCII 80
 
20.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 42
 
13.1%
경 22
 
6.9%
환 20
 
6.2%
엔 12
 
3.8%
건 12
 
3.8%
설 11
 
3.4%
지 10
 
3.1%
일 10
 
3.1%
기 9
 
2.8%
이 8
 
2.5%
Other values (69) 164
51.2%
ASCII
ValueCountFrequency (%)
( 39
48.8%
) 39
48.8%
2
 
2.5%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.009974 × 1013
Minimum2.0030722 × 1013
Maximum2.0220328 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size605.0 B
2024-04-21T03:20:58.819346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0030722 × 1013
5-th percentile2.0036799 × 1013
Q12.0071127 × 1013
median2.0090428 × 1013
Q32.0141014 × 1013
95-th percentile2.0194768 × 1013
Maximum2.0220328 × 1013
Range1.8960604 × 1011
Interquartile range (IQR)6.988704 × 1010

Descriptive statistics

Standard deviation4.8781705 × 1010
Coefficient of variation (CV)0.0024269818
Kurtosis0.063760557
Mean2.009974 × 1013
Median Absolute Deviation (MAD)1.9405071 × 1010
Skewness0.91792127
Sum1.0652862 × 1015
Variance2.3796547 × 1021
MonotonicityNot monotonic
2024-04-21T03:20:59.282964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20141014172036 1
 
1.9%
20040519174029 1
 
1.9%
20081201132752 1
 
1.9%
20081201133036 1
 
1.9%
20091112154349 1
 
1.9%
20081201133738 1
 
1.9%
20080704084202 1
 
1.9%
20081201131258 1
 
1.9%
20050701124542 1
 
1.9%
20081201133605 1
 
1.9%
Other values (43) 43
81.1%
ValueCountFrequency (%)
20030722132121 1
1.9%
20031121135747 1
1.9%
20031218154314 1
1.9%
20040519174029 1
1.9%
20040702165658 1
1.9%
20050701124542 1
1.9%
20050729175842 1
1.9%
20050831121502 1
1.9%
20050926172208 1
1.9%
20050926172402 1
1.9%
ValueCountFrequency (%)
20220328171016 1
1.9%
20210128165633 1
1.9%
20201015134002 1
1.9%
20190603111903 1
1.9%
20190315164908 1
1.9%
20181120164931 1
1.9%
20181109161407 1
1.9%
20160407140851 1
1.9%
20151123115626 1
1.9%
20150610111312 1
1.9%

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size552.0 B
I
46 
U
7 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 46
86.8%
U 7
 
13.2%

Length

2024-04-21T03:20:59.703859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:21:00.004698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 46
86.8%
u 7
 
13.2%

데이터갱신일자
Categorical

IMBALANCE 

Distinct8
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Memory size552.0 B
2018-08-31 23:59:59.0
46 
2018-11-11 02:38:39.0
 
1
2020-10-17 02:40:00.0
 
1
2019-03-17 02:40:00.0
 
1
2019-06-05 02:40:00.0
 
1
Other values (3)
 
3

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique7 ?
Unique (%)13.2%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2018-11-11 02:38:39.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 46
86.8%
2018-11-11 02:38:39.0 1
 
1.9%
2020-10-17 02:40:00.0 1
 
1.9%
2019-03-17 02:40:00.0 1
 
1.9%
2019-06-05 02:40:00.0 1
 
1.9%
2018-11-22 02:37:48.0 1
 
1.9%
2021-01-30 02:40:00.0 1
 
1.9%
2022-03-30 02:40:00.0 1
 
1.9%

Length

2024-04-21T03:21:00.322360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:21:00.653464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-08-31 46
43.4%
23:59:59.0 46
43.4%
02:40:00.0 5
 
4.7%
2018-11-11 1
 
0.9%
02:38:39.0 1
 
0.9%
2020-10-17 1
 
0.9%
2019-03-17 1
 
0.9%
2019-06-05 1
 
0.9%
2018-11-22 1
 
0.9%
02:37:48.0 1
 
0.9%
Other values (2) 2
 
1.9%

업태구분명
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing47
Missing (%)88.7%
Memory size552.0 B
2024-04-21T03:21:01.291233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length12.5
Mean length11.333333
Min length2

Characters and Unicode

Total characters68
Distinct characters31
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st row농업
2nd row건축기술 및 엔지니어링 서비스업
3rd row하수, 분뇨 및 축산폐기물 처리업
4th row하수, 폐수 및 분뇨 처리업
5th row분뇨 처리업
ValueCountFrequency (%)
및 3
15.0%
분뇨 3
15.0%
처리업 3
15.0%
하수 2
10.0%
농업 1
 
5.0%
건축기술 1
 
5.0%
엔지니어링 1
 
5.0%
서비스업 1
 
5.0%
축산폐기물 1
 
5.0%
폐수 1
 
5.0%
Other values (3) 3
15.0%
2024-04-21T03:21:02.554029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14
20.6%
업 6
 
8.8%
뇨 3
 
4.4%
분 3
 
4.4%
및 3
 
4.4%
수 3
 
4.4%
리 3
 
4.4%
처 3
 
4.4%
건 2
 
2.9%
축 2
 
2.9%
Other values (21) 26
38.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 52
76.5%
Space Separator 14
 
20.6%
Other Punctuation 2
 
2.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 6
 
11.5%
뇨 3
 
5.8%
분 3
 
5.8%
및 3
 
5.8%
수 3
 
5.8%
리 3
 
5.8%
처 3
 
5.8%
건 2
 
3.8%
축 2
 
3.8%
기 2
 
3.8%
Other values (19) 22
42.3%
Space Separator
ValueCountFrequency (%)
14
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 52
76.5%
Common 16
 
23.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 6
 
11.5%
뇨 3
 
5.8%
분 3
 
5.8%
및 3
 
5.8%
수 3
 
5.8%
리 3
 
5.8%
처 3
 
5.8%
건 2
 
3.8%
축 2
 
3.8%
기 2
 
3.8%
Other values (19) 22
42.3%
Common
ValueCountFrequency (%)
14
87.5%
, 2
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 52
76.5%
ASCII 16
 
23.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14
87.5%
, 2
 
12.5%
Hangul
ValueCountFrequency (%)
업 6
 
11.5%
뇨 3
 
5.8%
분 3
 
5.8%
및 3
 
5.8%
수 3
 
5.8%
리 3
 
5.8%
처 3
 
5.8%
건 2
 
3.8%
축 2
 
3.8%
기 2
 
3.8%
Other values (19) 22
42.3%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct35
Distinct (%)83.3%
Missing11
Missing (%)20.8%
Infinite0
Infinite (%)0.0%
Mean340138.36
Minimum331388.54
Maximum348355.24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size605.0 B
2024-04-21T03:21:02.916600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum331388.54
5-th percentile333346.98
Q1335204.34
median339553.66
Q3344912.36
95-th percentile347253.43
Maximum348355.24
Range16966.694
Interquartile range (IQR)9708.0143

Descriptive statistics

Standard deviation4937.0465
Coefficient of variation (CV)0.014514818
Kurtosis-1.1988679
Mean340138.36
Median Absolute Deviation (MAD)4550.1684
Skewness-0.019931705
Sum14285811
Variance24374428
MonotonicityNot monotonic
2024-04-21T03:21:03.312991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
344912.358902 2
 
3.8%
335003.494757 2
 
3.8%
333346.979452 2
 
3.8%
334132.329268 2
 
3.8%
339278.945555 2
 
3.8%
335204.344635 2
 
3.8%
339268.571432 2
 
3.8%
334847.929146 1
 
1.9%
338341.26088 1
 
1.9%
340079.030508 1
 
1.9%
Other values (25) 25
47.2%
(Missing) 11
20.8%
ValueCountFrequency (%)
331388.54225 1
1.9%
331535.063936 1
1.9%
333346.979452 2
3.8%
334132.329268 2
3.8%
334847.929146 1
1.9%
335003.494757 2
3.8%
335023.196036 1
1.9%
335204.344635 2
3.8%
336925.11171 1
1.9%
337740.137948 1
1.9%
ValueCountFrequency (%)
348355.236482 1
1.9%
347476.069562 1
1.9%
347262.921603 1
1.9%
347073.127192 1
1.9%
346621.319605 1
1.9%
345924.740679 1
1.9%
345793.409039 1
1.9%
345653.080016 1
1.9%
345448.163789 1
1.9%
345374.817551 1
1.9%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct35
Distinct (%)83.3%
Missing11
Missing (%)20.8%
Infinite0
Infinite (%)0.0%
Mean262105.71
Minimum249892.59
Maximum272658.57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size605.0 B
2024-04-21T03:21:03.697405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum249892.59
5-th percentile257266.28
Q1260094.4
median261468.57
Q3264699.41
95-th percentile268465.72
Maximum272658.57
Range22765.975
Interquartile range (IQR)4605.0183

Descriptive statistics

Standard deviation4409.8944
Coefficient of variation (CV)0.01682487
Kurtosis1.2894349
Mean262105.71
Median Absolute Deviation (MAD)1975.222
Skewness-0.32779306
Sum11008440
Variance19447169
MonotonicityNot monotonic
2024-04-21T03:21:04.080727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
268253.830253 2
 
3.8%
257266.281256 2
 
3.8%
261694.015322 2
 
3.8%
260892.868331 2
 
3.8%
260821.061771 2
 
3.8%
260540.004454 2
 
3.8%
262491.614242 2
 
3.8%
263094.255549 1
 
1.9%
263119.916898 1
 
1.9%
259623.99293 1
 
1.9%
Other values (25) 25
47.2%
(Missing) 11
20.8%
ValueCountFrequency (%)
249892.592076 1
1.9%
250973.809314 1
1.9%
257266.281256 2
3.8%
257280.684298 1
1.9%
257791.233422 1
1.9%
258950.140156 1
1.9%
259602.211062 1
1.9%
259623.99293 1
1.9%
259644.730921 1
1.9%
259945.860171 1
1.9%
ValueCountFrequency (%)
272658.567427 1
1.9%
268730.019954 1
1.9%
268476.874903 1
1.9%
268253.830253 2
3.8%
266964.397077 1
1.9%
266643.070989 1
1.9%
266495.668172 1
1.9%
266130.093353 1
1.9%
265713.852075 1
1.9%
264809.315221 1
1.9%

환경업무구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size552.0 B
분뇨등설계시공업관리
53 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
분뇨등설계시공업관리 53
100.0%

Length

2024-04-21T03:21:04.399286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:21:04.553525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분뇨등설계시공업관리 53
100.0%

업종구분명
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing47
Missing (%)88.7%
Memory size552.0 B
2024-04-21T03:21:05.082285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length12.5
Mean length11.333333
Min length2

Characters and Unicode

Total characters68
Distinct characters31
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st row농업
2nd row건축기술 및 엔지니어링 서비스업
3rd row하수, 분뇨 및 축산폐기물 처리업
4th row하수, 폐수 및 분뇨 처리업
5th row분뇨 처리업
ValueCountFrequency (%)
및 3
15.0%
분뇨 3
15.0%
처리업 3
15.0%
하수 2
10.0%
농업 1
 
5.0%
건축기술 1
 
5.0%
엔지니어링 1
 
5.0%
서비스업 1
 
5.0%
축산폐기물 1
 
5.0%
폐수 1
 
5.0%
Other values (3) 3
15.0%
2024-04-21T03:21:06.128911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14
20.6%
업 6
 
8.8%
뇨 3
 
4.4%
분 3
 
4.4%
및 3
 
4.4%
수 3
 
4.4%
리 3
 
4.4%
처 3
 
4.4%
건 2
 
2.9%
축 2
 
2.9%
Other values (21) 26
38.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 52
76.5%
Space Separator 14
 
20.6%
Other Punctuation 2
 
2.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 6
 
11.5%
뇨 3
 
5.8%
분 3
 
5.8%
및 3
 
5.8%
수 3
 
5.8%
리 3
 
5.8%
처 3
 
5.8%
건 2
 
3.8%
축 2
 
3.8%
기 2
 
3.8%
Other values (19) 22
42.3%
Space Separator
ValueCountFrequency (%)
14
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 52
76.5%
Common 16
 
23.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 6
 
11.5%
뇨 3
 
5.8%
분 3
 
5.8%
및 3
 
5.8%
수 3
 
5.8%
리 3
 
5.8%
처 3
 
5.8%
건 2
 
3.8%
축 2
 
3.8%
기 2
 
3.8%
Other values (19) 22
42.3%
Common
ValueCountFrequency (%)
14
87.5%
, 2
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 52
76.5%
ASCII 16
 
23.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14
87.5%
, 2
 
12.5%
Hangul
ValueCountFrequency (%)
업 6
 
11.5%
뇨 3
 
5.8%
분 3
 
5.8%
및 3
 
5.8%
수 3
 
5.8%
리 3
 
5.8%
처 3
 
5.8%
건 2
 
3.8%
축 2
 
3.8%
기 2
 
3.8%
Other values (19) 22
42.3%

종별명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing53
Missing (%)100.0%
Memory size605.0 B

주생산품명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing53
Missing (%)100.0%
Memory size605.0 B

배출시설조업시간
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing53
Missing (%)100.0%
Memory size605.0 B

배출시설연간가동일수
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size552.0 B
<NA>
52 
0
 
1

Length

Max length4
Median length4
Mean length3.9433962
Min length1

Unique

Unique1 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 52
98.1%
0 1
 
1.9%

Length

2024-04-21T03:21:06.541412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:21:06.854043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 52
98.1%
0 1
 
1.9%

방지시설조업시간
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing53
Missing (%)100.0%
Memory size605.0 B

방지시설연간가동일수
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size552.0 B
<NA>
52 
0
 
1

Length

Max length4
Median length4
Mean length3.9433962
Min length1

Unique

Unique1 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 52
98.1%
0 1
 
1.9%

Length

2024-04-21T03:21:07.193781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:21:07.521924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 52
98.1%
0 1
 
1.9%

사업자등록번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing53
Missing (%)100.0%
Memory size605.0 B

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명업종구분명종별명주생산품명배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수사업자등록번호
01단독정화조/오수처리시설설계시공업09_30_07_P341000034100005400000000320040714<NA>3폐업2폐업20140103<NA><NA><NA><NA><NA>700380대구광역시 중구 달성동 121-4<NA><NA>주식회사 기술신환경20141014172036I2018-08-31 23:59:59.0농업<NA><NA>분뇨등설계시공업관리농업<NA><NA><NA><NA><NA><NA><NA>
12단독정화조/오수처리시설설계시공업09_30_07_P341000034100005420040000420040720<NA>3폐업2폐업20140103<NA><NA><NA><NA><NA>700380대구광역시 중구 달성동 121-4<NA><NA>(주)기술신환경20141014172249I2018-08-31 23:59:59.0<NA><NA><NA>분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
23단독정화조/오수처리시설설계시공업09_30_07_P342000034200005420040000319990414<NA>3폐업2폐업20071127<NA><NA><NA><NA><NA>701290대구광역시 동구 각산동 295-5<NA><NA>한일기공20071127132236I2018-08-31 23:59:59.0<NA><NA><NA>분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
34단독정화조/오수처리시설설계시공업09_30_07_P342000034200005420060000120060510<NA>3폐업2폐업20181109<NA><NA><NA>952-5570<NA>701011대구광역시 동구 신암동 722-12대구광역시 동구 평화로 27 (신암동)701820우경환경건설20181109161407U2018-11-11 02:38:39.0<NA>345924.740679266130.093353분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
45단독정화조/오수처리시설설계시공업09_30_07_P343000034300005420090000120090121<NA>3폐업2폐업20090407<NA><NA><NA>5635123<NA>703833대구광역시 서구 중리동 1120-10<NA><NA>거성환경(주)20090611165355I2018-08-31 23:59:59.0<NA>338877.038343263552.654996분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
56단독정화조/오수처리시설설계시공업09_30_07_P343000034300005420040000120040315<NA>3폐업2폐업20060705<NA><NA><NA><NA><NA>703031대구광역시 서구 원대동1가 79 대원아파트 A동 105호<NA><NA>(주)유일환경건설20070501171338I2018-08-31 23:59:59.0<NA>342487.69733265713.852075분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
67단독정화조/오수처리시설설계시공업09_30_07_P343000034300005420140000120140806<NA>3폐업2폐업20150518<NA><NA><NA>053-555-6171<NA>703110대구광역시 서구 이현동 42-292대구광역시 서구 와룡로83길 13 (이현동)<NA>(주)이화환경 지점20151123115626I2018-08-31 23:59:59.0<NA>338677.427853264369.712568분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
78단독정화조/오수처리시설설계시공업09_30_07_P345000034500005420030000220031022<NA>3폐업2폐업20141118<NA><NA><NA>053 384 3347<NA>702010대구광역시 북구 산격동 1691<NA><NA>그린엔지니어링(주)20141118115411I2018-08-31 23:59:59.0<NA>345793.409039268730.019954분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
89단독정화조/오수처리시설설계시공업09_30_07_P345000034500005420050000320050705<NA>3폐업2폐업20071022<NA><NA><NA>053 604 3977<NA>702003대구광역시 북구 산격동 1626 전자도매상가 5동 307호<NA><NA>한솔환경주식회사20071022150058I2018-08-31 23:59:59.0<NA>344879.421494268476.874903분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
910단독정화조/오수처리시설설계시공업09_30_07_P345000034500005420050000120050415<NA>3폐업2폐업20090428<NA><NA><NA>053607 9000<NA>702857대구광역시 북구 침산동 416-8<NA><NA>(주)씨앤우방20090428164543I2018-08-31 23:59:59.0<NA>342994.81975266495.668172분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명업종구분명종별명주생산품명배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수사업자등록번호
4344단독정화조/오수처리시설설계시공업09_30_07_P347000034700005420010010020011102<NA>3폐업2폐업20051114<NA><NA><NA><NA><NA>704230대구광역시 달서구 호산동 167-3<NA><NA>(주)마니이엔비20031121135747I2018-08-31 23:59:59.0<NA><NA><NA>분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
4445단독정화조/오수처리시설설계시공업09_30_07_P347000034700005420020010520020422<NA>3폐업2폐업20050601<NA><NA><NA><NA><NA>704190대구광역시 달서구 장동 116-1대구광역시 달서구 성서동로 184 (장동)<NA>사하라환경건설20091112154220I2018-08-31 23:59:59.0<NA>336925.11171260714.533063분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
4546단독정화조/오수처리시설설계시공업09_30_07_P347000034700005419990000719990730<NA>3폐업2폐업20150610<NA><NA><NA><NA><NA>704170대구광역시 달서구 갈산동 358-81대구광역시 달서구 성서공단로25길 6 (갈산동)<NA>(주)로얄정공20150610111312I2018-08-31 23:59:59.0<NA>335204.344635260540.004454분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
4647단독정화조/오수처리시설설계시공업09_30_07_P347000034700005420040000220040514<NA>3폐업4폐쇄<NA><NA><NA><NA>053 583 8651<NA>704170대구광역시 달서구 갈산동 358-81대구광역시 달서구 성서공단로25길 6 (갈산동)<NA>(주)로얄정공20091112170227I2018-08-31 23:59:59.0<NA>335204.344635260540.004454분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
4748단독정화조/오수처리시설설계시공업09_30_07_P348000034800005420020000120020325<NA>3폐업2폐업20090120<NA><NA><NA><NA><NA>711874대구광역시 달성군 현풍읍 원교리 95-4<NA><NA>달성환경건걸(주)20090120115242I2018-08-31 23:59:59.0<NA><NA><NA>분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
4849단독정화조/오수처리시설설계시공업09_30_07_P348000034800005419990000119990223<NA>3폐업2폐업20031110<NA><NA><NA><NA><NA>711852대구광역시 달성군 논공읍 북리 580-34대구광역시 달성군 논공읍 논공로53길 70<NA>(주)대원엔바이로20031218154314I2018-08-31 23:59:59.0<NA>331388.54225249892.592076분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
4950단독정화조/오수처리시설설계시공업09_30_07_P348000034800005420060000120060303<NA>3폐업2폐업20100111<NA><NA><NA><NA><NA>711883대구광역시 달성군 유가읍 상리 720대구광역시 달성군 유가면 비슬로96길 97<NA>세하주식회사20100111171206I2018-08-31 23:59:59.0<NA>331535.063936250973.809314분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
5051단독정화조/오수처리시설설계시공업09_30_07_P348000034800005420080000120081231<NA>1영업/정상11영업<NA><NA><NA><NA>053-643-2323<NA><NA><NA>대구광역시 달성군 화원읍 성천로 12242948(주)금창엔지지어링20220328171016U2022-03-30 02:40:00.0<NA>335023.196036257280.684298분뇨등설계시공업관리<NA><NA><NA><NA>0<NA>0<NA>
5152단독정화조/오수처리시설설계시공업09_30_07_P348000034800005420040000220041026<NA>3폐업2폐업20070105<NA><NA><NA>053 6163667<NA><NA>대구광역시 달성군 화원읍 천내리 107-1대구광역시 달성군 화원읍 성천로24길 1-5<NA>대한기업(주)20050831121502I2018-08-31 23:59:59.0<NA>335003.494757257266.281256분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
5253단독정화조/오수처리시설설계시공업09_30_07_P348000034800005420040000320041206<NA>3폐업2폐업20080304<NA><NA><NA>053643 2323<NA>null대구광역시 달성군 화원읍 천내리 107-1대구광역시 달성군 화원읍 성천로24길 1-5<NA>(주)금창엔지니어링20080304174946I2018-08-31 23:59:59.0<NA>335003.494757257266.281256분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>