Overview

Dataset statistics

Number of variables36
Number of observations63
Missing cells841
Missing cells (%)37.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.3 KiB
Average record size in memory313.1 B

Variable types

Numeric10
Categorical11
Unsupported9
Text6

Dataset

Description6270000_대구광역시_09_30_07_P_단독정화조오수처리시설설계시공업_8월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000085943&dataSetDetailId=DDI_0000085965&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스ID has constant value ""Constant
환경업무구분명 has constant value ""Constant
상세영업상태코드 is highly imbalanced (57.1%)Imbalance
상세영업상태명 is highly imbalanced (57.1%)Imbalance
휴업종료일자 is highly imbalanced (88.2%)Imbalance
재개업일자 is highly imbalanced (88.2%)Imbalance
데이터갱신구분 is highly imbalanced (54.6%)Imbalance
데이터갱신일자 is highly imbalanced (72.8%)Imbalance
인허가일자 has 6 (9.5%) missing valuesMissing
인허가취소일자 has 63 (100.0%) missing valuesMissing
폐업일자 has 7 (11.1%) missing valuesMissing
휴업시작일자 has 63 (100.0%) missing valuesMissing
소재지전화 has 30 (47.6%) missing valuesMissing
소재지면적 has 63 (100.0%) missing valuesMissing
소재지우편번호 has 9 (14.3%) missing valuesMissing
소재지전체주소 has 1 (1.6%) missing valuesMissing
도로명전체주소 has 26 (41.3%) missing valuesMissing
도로명우편번호 has 55 (87.3%) missing valuesMissing
업태구분명 has 55 (87.3%) missing valuesMissing
좌표정보(X) has 15 (23.8%) missing valuesMissing
좌표정보(Y) has 15 (23.8%) missing valuesMissing
업종구분명 has 55 (87.3%) missing valuesMissing
종별명 has 63 (100.0%) missing valuesMissing
주생산품명 has 63 (100.0%) missing valuesMissing
배출시설조업시간 has 63 (100.0%) missing valuesMissing
배출시설연간가동일수 has 63 (100.0%) missing valuesMissing
방지시설조업시간 has 63 (100.0%) missing valuesMissing
방지시설연간가동일수 has 63 (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
휴업시작일자 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
배출시설연간가동일수 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
방지시설연간가동일수 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 19:21:02.999404
Analysis finished2023-12-10 19:21:03.666334
Duration0.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32
Minimum1
Maximum63
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T04:21:03.808584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.1
Q116.5
median32
Q347.5
95-th percentile59.9
Maximum63
Range62
Interquartile range (IQR)31

Descriptive statistics

Standard deviation18.330303
Coefficient of variation (CV)0.57282196
Kurtosis-1.2
Mean32
Median Absolute Deviation (MAD)16
Skewness0
Sum2016
Variance336
MonotonicityStrictly increasing
2023-12-11T04:21:04.052095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.6%
2 1
 
1.6%
35 1
 
1.6%
36 1
 
1.6%
37 1
 
1.6%
38 1
 
1.6%
39 1
 
1.6%
40 1
 
1.6%
41 1
 
1.6%
42 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
1 1
1.6%
2 1
1.6%
3 1
1.6%
4 1
1.6%
5 1
1.6%
6 1
1.6%
7 1
1.6%
8 1
1.6%
9 1
1.6%
10 1
1.6%
ValueCountFrequency (%)
63 1
1.6%
62 1
1.6%
61 1
1.6%
60 1
1.6%
59 1
1.6%
58 1
1.6%
57 1
1.6%
56 1
1.6%
55 1
1.6%
54 1
1.6%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
단독정화조/오수처리시설설계시공업
63 

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 63
100.0%

Length

2023-12-11T04:21:04.259003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:21:04.415861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단독정화조/오수처리시설설계시공업 63
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
09_30_07_P
63 

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 63
100.0%

Length

2023-12-11T04:21:04.592250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:21:04.746706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_30_07_p 63
100.0%

개방자치단체코드
Real number (ℝ)

Distinct7
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3456825.4
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T04:21:04.881671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3410000
Q13450000
median3460000
Q33470000
95-th percentile3480000
Maximum3480000
Range70000
Interquartile range (IQR)20000

Descriptive statistics

Standard deviation20066.454
Coefficient of variation (CV)0.0058048792
Kurtosis0.52619739
Mean3456825.4
Median Absolute Deviation (MAD)10000
Skewness-1.2291784
Sum2.1778 × 108
Variance4.0266257 × 108
MonotonicityIncreasing
2023-12-11T04:21:05.060309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
3470000 23
36.5%
3460000 14
22.2%
3450000 9
 
14.3%
3480000 6
 
9.5%
3410000 5
 
7.9%
3420000 3
 
4.8%
3430000 3
 
4.8%
ValueCountFrequency (%)
3410000 5
 
7.9%
3420000 3
 
4.8%
3430000 3
 
4.8%
3450000 9
 
14.3%
3460000 14
22.2%
3470000 23
36.5%
3480000 6
 
9.5%
ValueCountFrequency (%)
3480000 6
 
9.5%
3470000 23
36.5%
3460000 14
22.2%
3450000 9
 
14.3%
3430000 3
 
4.8%
3420000 3
 
4.8%
3410000 5
 
7.9%

관리번호
Real number (ℝ)

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4568259 × 1017
Minimum3.4100005 × 1017
Maximum3.4800005 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T04:21:05.290206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.4100005 × 1017
5-th percentile3.4100005 × 1017
Q13.4500005 × 1017
median3.4600005 × 1017
Q33.4700005 × 1017
95-th percentile3.4800005 × 1017
Maximum3.4800005 × 1017
Range7.0000002 × 1015
Interquartile range (IQR)2 × 1015

Descriptive statistics

Standard deviation2.0066454 × 1015
Coefficient of variation (CV)0.0058048784
Kurtosis0.52619746
Mean3.4568259 × 1017
Median Absolute Deviation (MAD)1 × 1015
Skewness-1.2291784
Sum3.3312593 × 1018
Variance4.0266258 × 1030
MonotonicityNot monotonic
2023-12-11T04:21:05.502894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
341000054000000001 1
 
1.6%
341000054000000002 1
 
1.6%
347000054200700001 1
 
1.6%
347000054200300111 1
 
1.6%
347000054200300012 1
 
1.6%
347000054200100100 1
 
1.6%
347000054200400003 1
 
1.6%
347000054200400006 1
 
1.6%
347000054200500002 1
 
1.6%
347000054199200016 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
341000054000000001 1
1.6%
341000054000000002 1
1.6%
341000054000000003 1
1.6%
341000054200400004 1
1.6%
341000054200400006 1
1.6%
342000054200400003 1
1.6%
342000054200600001 1
1.6%
342000054200700001 1
1.6%
343000054200400001 1
1.6%
343000054200900001 1
1.6%
ValueCountFrequency (%)
348000054200800001 1
1.6%
348000054200600001 1
1.6%
348000054200400003 1
1.6%
348000054200400002 1
1.6%
348000054200200001 1
1.6%
348000054199900001 1
1.6%
347000054200700001 1
1.6%
347000054200600001 1
1.6%
347000054200500003 1
1.6%
347000054200500002 1
1.6%

인허가일자
Real number (ℝ)

MISSING 

Distinct54
Distinct (%)94.7%
Missing6
Missing (%)9.5%
Infinite0
Infinite (%)0.0%
Mean20036335
Minimum19950427
Maximum20140806
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T04:21:05.788728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19950427
5-th percentile19978939
Q120030422
median20040624
Q320050624
95-th percentile20090242
Maximum20140806
Range190379
Interquartile range (IQR)20202

Descriptive statistics

Standard deviation35324.213
Coefficient of variation (CV)0.0017630077
Kurtosis1.8860302
Mean20036335
Median Absolute Deviation (MAD)10077
Skewness0.33455268
Sum1.1420711 × 109
Variance1.2478 × 109
MonotonicityNot monotonic
2023-12-11T04:21:06.029679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20041230 2
 
3.2%
20050701 2
 
3.2%
20040624 2
 
3.2%
20030625 1
 
1.6%
20011102 1
 
1.6%
20031208 1
 
1.6%
20040702 1
 
1.6%
19950427 1
 
1.6%
20040719 1
 
1.6%
20030422 1
 
1.6%
Other values (44) 44
69.8%
(Missing) 6
 
9.5%
ValueCountFrequency (%)
19950427 1
1.6%
19970304 1
1.6%
19971002 1
1.6%
19980923 1
1.6%
19981202 1
1.6%
19990223 1
1.6%
19990414 1
1.6%
19990730 1
1.6%
19990913 1
1.6%
19991101 1
1.6%
ValueCountFrequency (%)
20140806 1
1.6%
20140407 1
1.6%
20090724 1
1.6%
20090121 1
1.6%
20081231 1
1.6%
20080715 1
1.6%
20060714 1
1.6%
20060602 1
1.6%
20060510 1
1.6%
20060303 1
1.6%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing63
Missing (%)100.0%
Memory size699.0 B

영업상태구분코드
Categorical

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size636.0 B
3
52 
1
11 

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 52
82.5%
1 11
 
17.5%

Length

2023-12-11T04:21:06.267678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:21:06.440039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 52
82.5%
1 11
 
17.5%

영업상태명
Categorical

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size636.0 B
폐업
52 
영업/정상
11 

Length

Max length5
Median length2
Mean length2.5238095
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 52
82.5%
영업/정상 11
 
17.5%

Length

2023-12-11T04:21:06.642951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:21:06.808714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 52
82.5%
영업/정상 11
 
17.5%

상세영업상태코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Memory size636.0 B
2
51 
11
10 
4
 
1
3
 
1

Length

Max length2
Median length1
Mean length1.1587302
Min length1

Unique

Unique2 ?
Unique (%)3.2%

Sample

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

Common Values

ValueCountFrequency (%)
2 51
81.0%
11 10
 
15.9%
4 1
 
1.6%
3 1
 
1.6%

Length

2023-12-11T04:21:06.981564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:21:07.161544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 51
81.0%
11 10
 
15.9%
4 1
 
1.6%
3 1
 
1.6%

상세영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Memory size636.0 B
폐업
51 
영업
10 
폐쇄
 
1
재개업
 
1

Length

Max length3
Median length2
Mean length2.015873
Min length2

Unique

Unique2 ?
Unique (%)3.2%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 51
81.0%
영업 10
 
15.9%
폐쇄 1
 
1.6%
재개업 1
 
1.6%

Length

2023-12-11T04:21:07.372314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:21:07.546100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 51
81.0%
영업 10
 
15.9%
폐쇄 1
 
1.6%
재개업 1
 
1.6%

폐업일자
Real number (ℝ)

MISSING 

Distinct47
Distinct (%)83.9%
Missing7
Missing (%)11.1%
Infinite0
Infinite (%)0.0%
Mean20080297
Minimum19000101
Maximum21000101
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T04:21:07.745330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19000101
5-th percentile20031013
Q120051090
median20080458
Q320093437
95-th percentile20183473
Maximum21000101
Range2000000
Interquartile range (IQR)42346.5

Descriptive statistics

Standard deviation273495.48
Coefficient of variation (CV)0.013620091
Kurtosis11.888523
Mean20080297
Median Absolute Deviation (MAD)24747.5
Skewness-0.88428364
Sum1.1244967 × 109
Variance7.4799777 × 1010
MonotonicityNot monotonic
2023-12-11T04:21:07.982074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
20090909 4
 
6.3%
20140103 3
 
4.8%
20050504 2
 
3.2%
20050601 2
 
3.2%
21000101 2
 
3.2%
19000101 2
 
3.2%
20090407 1
 
1.6%
20060411 1
 
1.6%
20060623 1
 
1.6%
20061207 1
 
1.6%
Other values (37) 37
58.7%
(Missing) 7
 
11.1%
ValueCountFrequency (%)
19000101 2
3.2%
20030722 1
1.6%
20031110 1
1.6%
20031230 1
1.6%
20040630 1
1.6%
20050504 2
3.2%
20050601 2
3.2%
20050729 1
1.6%
20050907 1
1.6%
20050914 1
1.6%
ValueCountFrequency (%)
21000101 2
3.2%
20190531 1
 
1.6%
20181120 1
 
1.6%
20181109 1
 
1.6%
20160407 1
 
1.6%
20150610 1
 
1.6%
20150518 1
 
1.6%
20141118 1
 
1.6%
20141104 1
 
1.6%
20140103 3
4.8%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing63
Missing (%)100.0%
Memory size699.0 B

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
62 
20150309
 
1

Length

Max length8
Median length4
Mean length4.0634921
Min length4

Unique

Unique1 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 62
98.4%
20150309 1
 
1.6%

Length

2023-12-11T04:21:08.204157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:21:08.339773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 62
98.4%
20150309 1
 
1.6%

재개업일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
62 
20150309
 
1

Length

Max length8
Median length4
Mean length4.0634921
Min length4

Unique

Unique1 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 62
98.4%
20150309 1
 
1.6%

Length

2023-12-11T04:21:08.498010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:21:08.648295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 62
98.4%
20150309 1
 
1.6%

소재지전화
Text

MISSING 

Distinct32
Distinct (%)97.0%
Missing30
Missing (%)47.6%
Memory size636.0 B
2023-12-11T04:21:08.874342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.636364
Min length7

Characters and Unicode

Total characters351
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

Unique31 ?
Unique (%)93.9%

Sample

1st row522-5755
2nd row952-5570
3rd row9525570
4th row053-555-6171
5th row5635123
ValueCountFrequency (%)
053 12
 
22.6%
6218282 2
 
3.8%
053643 1
 
1.9%
5624400 1
 
1.9%
053-760-3842 1
 
1.9%
7603815 1
 
1.9%
5238481 1
 
1.9%
587 1
 
1.9%
0436 1
 
1.9%
5656292 1
 
1.9%
Other values (31) 31
58.5%
2023-12-11T04:21:09.333812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 66
18.8%
3 58
16.5%
0 44
12.5%
2 33
9.4%
6 28
8.0%
- 22
 
6.3%
7 21
 
6.0%
20
 
5.7%
8 19
 
5.4%
1 14
 
4.0%
Other values (2) 26
 
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 309
88.0%
Dash Punctuation 22
 
6.3%
Space Separator 20
 
5.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 66
21.4%
3 58
18.8%
0 44
14.2%
2 33
10.7%
6 28
9.1%
7 21
 
6.8%
8 19
 
6.1%
1 14
 
4.5%
4 14
 
4.5%
9 12
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Space Separator
ValueCountFrequency (%)
20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 351
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 66
18.8%
3 58
16.5%
0 44
12.5%
2 33
9.4%
6 28
8.0%
- 22
 
6.3%
7 21
 
6.0%
20
 
5.7%
8 19
 
5.4%
1 14
 
4.0%
Other values (2) 26
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 351
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 66
18.8%
3 58
16.5%
0 44
12.5%
2 33
9.4%
6 28
8.0%
- 22
 
6.3%
7 21
 
6.0%
20
 
5.7%
8 19
 
5.4%
1 14
 
4.0%
Other values (2) 26
 
7.4%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing63
Missing (%)100.0%
Memory size699.0 B

소재지우편번호
Real number (ℝ)

MISSING 

Distinct39
Distinct (%)72.2%
Missing9
Missing (%)14.3%
Infinite0
Infinite (%)0.0%
Mean704359.5
Minimum700280
Maximum711883
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T04:21:09.555989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700280
5-th percentile700380
Q1702900.5
median704195
Q3706010
95-th percentile708596.8
Maximum711883
Range11603
Interquartile range (IQR)3109.5

Descriptive statistics

Standard deviation2576.6452
Coefficient of variation (CV)0.0036581393
Kurtosis2.2555283
Mean704359.5
Median Absolute Deviation (MAD)1587.5
Skewness1.0786619
Sum38035413
Variance6639100.3
MonotonicityNot monotonic
2023-12-11T04:21:09.746511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
704340 4
 
6.3%
706010 3
 
4.8%
704120 3
 
4.8%
704240 3
 
4.8%
704170 2
 
3.2%
704150 2
 
3.2%
704130 2
 
3.2%
704220 2
 
3.2%
700380 2
 
3.2%
706829 2
 
3.2%
Other values (29) 29
46.0%
(Missing) 9
 
14.3%
ValueCountFrequency (%)
700280 1
1.6%
700320 1
1.6%
700380 2
3.2%
701010 1
1.6%
701011 1
1.6%
701290 1
1.6%
702003 1
1.6%
702010 1
1.6%
702011 1
1.6%
702082 1
1.6%
ValueCountFrequency (%)
711883 1
1.6%
711874 1
1.6%
711852 1
1.6%
706844 1
1.6%
706829 2
3.2%
706827 1
1.6%
706803 1
1.6%
706170 1
1.6%
706091 1
1.6%
706034 1
1.6%

소재지전체주소
Text

MISSING 

Distinct52
Distinct (%)83.9%
Missing1
Missing (%)1.6%
Memory size636.0 B
2023-12-11T04:21:10.177338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length31
Mean length23
Min length18

Characters and Unicode

Total characters1426
Distinct characters84
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

Unique42 ?
Unique (%)67.7%

Sample

1st row대구광역시 중구 대신동 1450-1
2nd row대구광역시 중구 대안동 65-7번지
3rd row대구광역시 중구 달성동 121-4 번지
4th row대구광역시 중구 달성동 121-4 번지
5th row대구광역시 중구 달성동 121-4번지
ValueCountFrequency (%)
대구광역시 62
23.0%
달서구 23
 
8.5%
수성구 14
 
5.2%
번지 9
 
3.3%
북구 9
 
3.3%
달성군 5
 
1.9%
중구 5
 
1.9%
송현동 4
 
1.5%
산격동 4
 
1.5%
서구 3
 
1.1%
Other values (99) 132
48.9%
2023-12-11T04:21:10.768460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
283
19.8%
구 119
 
8.3%
대 67
 
4.7%
1 66
 
4.6%
동 63
 
4.4%
광 62
 
4.3%
역 62
 
4.3%
시 62
 
4.3%
지 59
 
4.1%
번 57
 
4.0%
Other values (74) 526
36.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 811
56.9%
Space Separator 283
 
19.8%
Decimal Number 275
 
19.3%
Dash Punctuation 54
 
3.8%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 119
14.7%
대 67
 
8.3%
동 63
 
7.8%
광 62
 
7.6%
역 62
 
7.6%
시 62
 
7.6%
지 59
 
7.3%
번 57
 
7.0%
달 31
 
3.8%
서 26
 
3.2%
Other values (59) 203
25.0%
Decimal Number
ValueCountFrequency (%)
1 66
24.0%
2 41
14.9%
4 29
10.5%
6 28
10.2%
7 22
 
8.0%
5 19
 
6.9%
0 19
 
6.9%
3 18
 
6.5%
9 17
 
6.2%
8 16
 
5.8%
Space Separator
ValueCountFrequency (%)
283
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 811
56.9%
Common 614
43.1%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 119
14.7%
대 67
 
8.3%
동 63
 
7.8%
광 62
 
7.6%
역 62
 
7.6%
시 62
 
7.6%
지 59
 
7.3%
번 57
 
7.0%
달 31
 
3.8%
서 26
 
3.2%
Other values (59) 203
25.0%
Common
ValueCountFrequency (%)
283
46.1%
1 66
 
10.7%
- 54
 
8.8%
2 41
 
6.7%
4 29
 
4.7%
6 28
 
4.6%
7 22
 
3.6%
5 19
 
3.1%
0 19
 
3.1%
3 18
 
2.9%
Other values (4) 35
 
5.7%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 811
56.9%
ASCII 615
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
283
46.0%
1 66
 
10.7%
- 54
 
8.8%
2 41
 
6.7%
4 29
 
4.7%
6 28
 
4.6%
7 22
 
3.6%
5 19
 
3.1%
0 19
 
3.1%
3 18
 
2.9%
Other values (5) 36
 
5.9%
Hangul
ValueCountFrequency (%)
구 119
14.7%
대 67
 
8.3%
동 63
 
7.8%
광 62
 
7.6%
역 62
 
7.6%
시 62
 
7.6%
지 59
 
7.3%
번 57
 
7.0%
달 31
 
3.8%
서 26
 
3.2%
Other values (59) 203
25.0%

도로명전체주소
Text

MISSING 

Distinct31
Distinct (%)83.8%
Missing26
Missing (%)41.3%
Memory size636.0 B
2023-12-11T04:21:11.104413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length30
Mean length25.108108
Min length21

Characters and Unicode

Total characters929
Distinct characters90
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

Unique25 ?
Unique (%)67.6%

Sample

1st row대구광역시 중구 태평로 17 (달성동)
2nd row대구광역시 동구 평화로 27 (신암동)
3rd row대구광역시 서구 와룡로83길 13 (이현동)
4th row대구광역시 북구 학남로17길 20-39 (국우동)
5th row대구광역시 북구 대현로13길 5 (대현동)
ValueCountFrequency (%)
대구광역시 37
 
20.0%
달서구 16
 
8.6%
수성구 11
 
5.9%
달성군 5
 
2.7%
화원읍 3
 
1.6%
상동 3
 
1.6%
24 3
 
1.6%
45 3
 
1.6%
범어동 2
 
1.1%
111 2
 
1.1%
Other values (78) 100
54.1%
2023-12-11T04:21:11.623802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
170
18.3%
구 76
 
8.2%
대 45
 
4.8%
동 40
 
4.3%
광 37
 
4.0%
역 37
 
4.0%
시 37
 
4.0%
로 36
 
3.9%
) 33
 
3.6%
( 33
 
3.6%
Other values (80) 385
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 558
60.1%
Space Separator 170
 
18.3%
Decimal Number 128
 
13.8%
Close Punctuation 33
 
3.6%
Open Punctuation 33
 
3.6%
Dash Punctuation 6
 
0.6%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 76
13.6%
대 45
 
8.1%
동 40
 
7.2%
광 37
 
6.6%
역 37
 
6.6%
시 37
 
6.6%
로 36
 
6.5%
성 27
 
4.8%
달 25
 
4.5%
서 22
 
3.9%
Other values (65) 176
31.5%
Decimal Number
ValueCountFrequency (%)
1 29
22.7%
2 17
13.3%
4 16
12.5%
3 13
10.2%
5 13
10.2%
7 11
 
8.6%
6 9
 
7.0%
9 7
 
5.5%
0 7
 
5.5%
8 6
 
4.7%
Space Separator
ValueCountFrequency (%)
170
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 558
60.1%
Common 371
39.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 76
13.6%
대 45
 
8.1%
동 40
 
7.2%
광 37
 
6.6%
역 37
 
6.6%
시 37
 
6.6%
로 36
 
6.5%
성 27
 
4.8%
달 25
 
4.5%
서 22
 
3.9%
Other values (65) 176
31.5%
Common
ValueCountFrequency (%)
170
45.8%
) 33
 
8.9%
( 33
 
8.9%
1 29
 
7.8%
2 17
 
4.6%
4 16
 
4.3%
3 13
 
3.5%
5 13
 
3.5%
7 11
 
3.0%
6 9
 
2.4%
Other values (5) 27
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 558
60.1%
ASCII 371
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
170
45.8%
) 33
 
8.9%
( 33
 
8.9%
1 29
 
7.8%
2 17
 
4.6%
4 16
 
4.3%
3 13
 
3.5%
5 13
 
3.5%
7 11
 
3.0%
6 9
 
2.4%
Other values (5) 27
 
7.3%
Hangul
ValueCountFrequency (%)
구 76
13.6%
대 45
 
8.1%
동 40
 
7.2%
광 37
 
6.6%
역 37
 
6.6%
시 37
 
6.6%
로 36
 
6.5%
성 27
 
4.8%
달 25
 
4.5%
서 22
 
3.9%
Other values (65) 176
31.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)100.0%
Missing55
Missing (%)87.3%
Infinite0
Infinite (%)0.0%
Mean456308.38
Minimum41419
Maximum706829
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T04:21:11.803367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41419
5-th percentile41471.15
Q142603
median703030
Q3705318.75
95-th percentile706828.3
Maximum706829
Range665410
Interquartile range (IQR)662715.75

Descriptive statistics

Standard deviation343101.78
Coefficient of variation (CV)0.7519077
Kurtosis-2.2399262
Mean456308.38
Median Absolute Deviation (MAD)3798
Skewness-0.6439865
Sum3650467
Variance1.1771883 × 1011
MonotonicityNot monotonic
2023-12-11T04:21:11.941302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
701820 1
 
1.6%
41419 1
 
1.6%
41568 1
 
1.6%
706827 1
 
1.6%
706829 1
 
1.6%
704240 1
 
1.6%
704816 1
 
1.6%
42948 1
 
1.6%
(Missing) 55
87.3%
ValueCountFrequency (%)
41419 1
1.6%
41568 1
1.6%
42948 1
1.6%
701820 1
1.6%
704240 1
1.6%
704816 1
1.6%
706827 1
1.6%
706829 1
1.6%
ValueCountFrequency (%)
706829 1
1.6%
706827 1
1.6%
704816 1
1.6%
704240 1
1.6%
701820 1
1.6%
42948 1
1.6%
41568 1
1.6%
41419 1
1.6%

사업장명
Text

Distinct49
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-12-11T04:21:12.555329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length7.4126984
Min length4

Characters and Unicode

Total characters467
Distinct characters85
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

Unique39 ?
Unique (%)61.9%

Sample

1st row(주)동서개발
2nd row(주)태경엔지니어링
3rd row주식회사 기술신환경
4th row(주)기술신환경
5th row(주)기술신환경
ValueCountFrequency (%)
우경환경건설 4
 
6.2%
사하라환경건설 3
 
4.6%
주)기술신환경 3
 
4.6%
주)유일환경건설 2
 
3.1%
주)선일인바텍 2
 
3.1%
대일환경기술 2
 
3.1%
주)로얄정공 2
 
3.1%
주)이코우 2
 
3.1%
화성산업(주 2
 
3.1%
대일엔지니어링(주 2
 
3.1%
Other values (41) 41
63.1%
2023-12-11T04:21:13.131402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 47
 
10.1%
( 44
 
9.4%
) 44
 
9.4%
경 31
 
6.6%
환 26
 
5.6%
건 17
 
3.6%
설 14
 
3.0%
엔 13
 
2.8%
지 11
 
2.4%
기 11
 
2.4%
Other values (75) 209
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 377
80.7%
Open Punctuation 44
 
9.4%
Close Punctuation 44
 
9.4%
Space Separator 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 47
 
12.5%
경 31
 
8.2%
환 26
 
6.9%
건 17
 
4.5%
설 14
 
3.7%
엔 13
 
3.4%
지 11
 
2.9%
기 11
 
2.9%
일 11
 
2.9%
한 9
 
2.4%
Other values (72) 187
49.6%
Open Punctuation
ValueCountFrequency (%)
( 44
100.0%
Close Punctuation
ValueCountFrequency (%)
) 44
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 377
80.7%
Common 90
 
19.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 47
 
12.5%
경 31
 
8.2%
환 26
 
6.9%
건 17
 
4.5%
설 14
 
3.7%
엔 13
 
3.4%
지 11
 
2.9%
기 11
 
2.9%
일 11
 
2.9%
한 9
 
2.4%
Other values (72) 187
49.6%
Common
ValueCountFrequency (%)
( 44
48.9%
) 44
48.9%
2
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 377
80.7%
ASCII 90
 
19.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 47
 
12.5%
경 31
 
8.2%
환 26
 
6.9%
건 17
 
4.5%
설 14
 
3.7%
엔 13
 
3.4%
지 11
 
2.9%
기 11
 
2.9%
일 11
 
2.9%
한 9
 
2.4%
Other values (72) 187
49.6%
ASCII
ValueCountFrequency (%)
( 44
48.9%
) 44
48.9%
2
 
2.2%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0102447 × 1013
Minimum2.0030722 × 1013
Maximum2.0200601 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T04:21:13.351218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0030722 × 1013
5-th percentile2.0040537 × 1013
Q12.0080658 × 1013
median2.0091001 × 1013
Q32.0141059 × 1013
95-th percentile2.0189396 × 1013
Maximum2.0200601 × 1013
Range1.6987898 × 1011
Interquartile range (IQR)6.0401579 × 1010

Descriptive statistics

Standard deviation4.5201811 × 1010
Coefficient of variation (CV)0.0022485726
Kurtosis-0.56190904
Mean2.0102447 × 1013
Median Absolute Deviation (MAD)1.997806 × 1010
Skewness0.59156037
Sum1.2664542 × 1015
Variance2.0432037 × 1021
MonotonicityNot monotonic
2023-12-11T04:21:13.575831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20151231092532 1
 
1.6%
20151231092554 1
 
1.6%
20081205173400 1
 
1.6%
20081201132309 1
 
1.6%
20081201132752 1
 
1.6%
20031121135747 1
 
1.6%
20040519174029 1
 
1.6%
20040702165658 1
 
1.6%
20050701124542 1
 
1.6%
20081201132907 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
20030722132121 1
1.6%
20031121135747 1
1.6%
20031218154314 1
1.6%
20040519174029 1
1.6%
20040702165658 1
1.6%
20050701124542 1
1.6%
20050729175842 1
1.6%
20050831121502 1
1.6%
20050926172208 1
1.6%
20050926172402 1
1.6%
ValueCountFrequency (%)
20200601112311 1
1.6%
20190603111903 1
1.6%
20190523172812 1
1.6%
20190315164908 1
1.6%
20181120164931 1
1.6%
20181109161407 1
1.6%
20181025174758 1
1.6%
20170126113423 1
1.6%
20160407140851 1
1.6%
20151231092554 1
1.6%

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size636.0 B
I
57 
U
6 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 57
90.5%
U 6
 
9.5%

Length

2023-12-11T04:21:13.798274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:21:13.973981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 57
90.5%
u 6
 
9.5%

데이터갱신일자
Categorical

IMBALANCE 

Distinct8
Distinct (%)12.7%
Missing0
Missing (%)0.0%
Memory size636.0 B
2018-08-31 23:59:59.0
56 
2018-11-11 02:38:39.0
 
1
2018-10-27 02:37:54.0
 
1
2020-06-04 02:40:00.0
 
1
2018-11-22 02:37:48.0
 
1
Other values (3)
 
3

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique7 ?
Unique (%)11.1%

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 row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 56
88.9%
2018-11-11 02:38:39.0 1
 
1.6%
2018-10-27 02:37:54.0 1
 
1.6%
2020-06-04 02:40:00.0 1
 
1.6%
2018-11-22 02:37:48.0 1
 
1.6%
2019-06-05 02:40:00.0 1
 
1.6%
2019-03-17 02:40:00.0 1
 
1.6%
2019-05-25 02:20:54.0 1
 
1.6%

Length

2023-12-11T04:21:14.135460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:21:14.314305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-08-31 56
44.4%
23:59:59.0 56
44.4%
02:40:00.0 3
 
2.4%
2018-11-11 1
 
0.8%
02:38:39.0 1
 
0.8%
2018-10-27 1
 
0.8%
02:37:54.0 1
 
0.8%
2020-06-04 1
 
0.8%
2018-11-22 1
 
0.8%
02:37:48.0 1
 
0.8%
Other values (4) 4
 
3.2%

업태구분명
Text

MISSING 

Distinct8
Distinct (%)100.0%
Missing55
Missing (%)87.3%
Memory size636.0 B
2023-12-11T04:21:14.590149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length11.75
Min length2

Characters and Unicode

Total characters94
Distinct characters39
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

Unique8 ?
Unique (%)100.0%

Sample

1st row기타 토목시설물 건설업
2nd row농업
3rd row건축설계 및 관련 서비스업
4th row건축기술 및 엔지니어링 서비스업
5th row하수, 폐수 및 분뇨 처리업
ValueCountFrequency (%)
및 4
14.8%
처리업 3
 
11.1%
분뇨 3
 
11.1%
하수 2
 
7.4%
서비스업 2
 
7.4%
기타 1
 
3.7%
건물 1
 
3.7%
주거용 1
 
3.7%
축산폐기물 1
 
3.7%
폐수 1
 
3.7%
Other values (8) 8
29.6%
2023-12-11T04:21:15.154891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19
20.2%
업 8
 
8.5%
및 4
 
4.3%
건 4
 
4.3%
기 3
 
3.2%
축 3
 
3.2%
분 3
 
3.2%
뇨 3
 
3.2%
처 3
 
3.2%
리 3
 
3.2%
Other values (29) 41
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 73
77.7%
Space Separator 19
 
20.2%
Other Punctuation 2
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 8
 
11.0%
및 4
 
5.5%
건 4
 
5.5%
기 3
 
4.1%
축 3
 
4.1%
분 3
 
4.1%
뇨 3
 
4.1%
처 3
 
4.1%
리 3
 
4.1%
수 3
 
4.1%
Other values (27) 36
49.3%
Space Separator
ValueCountFrequency (%)
19
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 73
77.7%
Common 21
 
22.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 8
 
11.0%
및 4
 
5.5%
건 4
 
5.5%
기 3
 
4.1%
축 3
 
4.1%
분 3
 
4.1%
뇨 3
 
4.1%
처 3
 
4.1%
리 3
 
4.1%
수 3
 
4.1%
Other values (27) 36
49.3%
Common
ValueCountFrequency (%)
19
90.5%
, 2
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 73
77.7%
ASCII 21
 
22.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19
90.5%
, 2
 
9.5%
Hangul
ValueCountFrequency (%)
업 8
 
11.0%
및 4
 
5.5%
건 4
 
5.5%
기 3
 
4.1%
축 3
 
4.1%
분 3
 
4.1%
뇨 3
 
4.1%
처 3
 
4.1%
리 3
 
4.1%
수 3
 
4.1%
Other values (27) 36
49.3%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct39
Distinct (%)81.2%
Missing15
Missing (%)23.8%
Infinite0
Infinite (%)0.0%
Mean340835.82
Minimum331388.54
Maximum348355.24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T04:21:15.387466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum331388.54
5-th percentile333346.98
Q1336494.92
median340499.95
Q3345499.39
95-th percentile347401.47
Maximum348355.24
Range16966.694
Interquartile range (IQR)9004.4729

Descriptive statistics

Standard deviation5008.6835
Coefficient of variation (CV)0.014695297
Kurtosis-1.2233035
Mean340835.82
Median Absolute Deviation (MAD)5050.6701
Skewness-0.22610768
Sum16360120
Variance25086911
MonotonicityNot monotonic
2023-12-11T04:21:15.609510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
335204.344635 2
 
3.2%
346621.319605 2
 
3.2%
333346.979452 2
 
3.2%
339278.945555 2
 
3.2%
334132.329268 2
 
3.2%
339268.571432 2
 
3.2%
345924.740679 2
 
3.2%
344912.358902 2
 
3.2%
335003.494757 2
 
3.2%
339828.380823 1
 
1.6%
Other values (29) 29
46.0%
(Missing) 15
23.8%
ValueCountFrequency (%)
331388.54225 1
1.6%
331535.063936 1
1.6%
333346.979452 2
3.2%
334132.329268 2
3.2%
334847.929146 1
1.6%
335003.494757 2
3.2%
335023.196036 1
1.6%
335204.344635 2
3.2%
336925.11171 1
1.6%
337740.137948 1
1.6%
ValueCountFrequency (%)
348355.236482 1
1.6%
347993.559844 1
1.6%
347476.069562 1
1.6%
347262.921603 1
1.6%
347073.127192 1
1.6%
346621.319605 2
3.2%
346123.39795 1
1.6%
345924.740679 2
3.2%
345793.409039 1
1.6%
345653.080016 1
1.6%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct39
Distinct (%)81.2%
Missing15
Missing (%)23.8%
Infinite0
Infinite (%)0.0%
Mean262375
Minimum249892.59
Maximum272658.57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T04:21:15.834442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum249892.59
5-th percentile257266.28
Q1260540
median262092.81
Q3265453.3
95-th percentile268398.81
Maximum272658.57
Range22765.975
Interquartile range (IQR)4913.2946

Descriptive statistics

Standard deviation4229.4883
Coefficient of variation (CV)0.016120013
Kurtosis1.5254746
Mean262375
Median Absolute Deviation (MAD)2362.4908
Skewness-0.4726642
Sum12594000
Variance17888571
MonotonicityNot monotonic
2023-12-11T04:21:16.051384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
260540.004454 2
 
3.2%
261243.121518 2
 
3.2%
261694.015322 2
 
3.2%
260821.061771 2
 
3.2%
260892.868331 2
 
3.2%
262491.614242 2
 
3.2%
266130.093353 2
 
3.2%
268253.830253 2
 
3.2%
257266.281256 2
 
3.2%
257791.233422 1
 
1.6%
Other values (29) 29
46.0%
(Missing) 15
23.8%
ValueCountFrequency (%)
249892.592076 1
1.6%
250973.809314 1
1.6%
257266.281256 2
3.2%
257280.684298 1
1.6%
257791.233422 1
1.6%
258950.140156 1
1.6%
259602.211062 1
1.6%
259623.99293 1
1.6%
259644.730921 1
1.6%
259945.860171 1
1.6%
ValueCountFrequency (%)
272658.567427 1
1.6%
268730.019954 1
1.6%
268476.874903 1
1.6%
268253.830253 2
3.2%
266964.397077 1
1.6%
266643.070989 1
1.6%
266495.668172 1
1.6%
266130.093353 2
3.2%
266068.997796 1
1.6%
265713.852075 1
1.6%

환경업무구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
분뇨등설계시공업관리
63 

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 63
100.0%

Length

2023-12-11T04:21:16.258693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:21:16.424731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분뇨등설계시공업관리 63
100.0%

업종구분명
Text

MISSING 

Distinct8
Distinct (%)100.0%
Missing55
Missing (%)87.3%
Memory size636.0 B
2023-12-11T04:21:16.636348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length11.75
Min length2

Characters and Unicode

Total characters94
Distinct characters39
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

Unique8 ?
Unique (%)100.0%

Sample

1st row기타 토목시설물 건설업
2nd row농업
3rd row건축설계 및 관련 서비스업
4th row건축기술 및 엔지니어링 서비스업
5th row하수, 폐수 및 분뇨 처리업
ValueCountFrequency (%)
및 4
14.8%
처리업 3
 
11.1%
분뇨 3
 
11.1%
하수 2
 
7.4%
서비스업 2
 
7.4%
기타 1
 
3.7%
건물 1
 
3.7%
주거용 1
 
3.7%
축산폐기물 1
 
3.7%
폐수 1
 
3.7%
Other values (8) 8
29.6%
2023-12-11T04:21:17.217647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19
20.2%
업 8
 
8.5%
및 4
 
4.3%
건 4
 
4.3%
기 3
 
3.2%
축 3
 
3.2%
분 3
 
3.2%
뇨 3
 
3.2%
처 3
 
3.2%
리 3
 
3.2%
Other values (29) 41
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 73
77.7%
Space Separator 19
 
20.2%
Other Punctuation 2
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 8
 
11.0%
및 4
 
5.5%
건 4
 
5.5%
기 3
 
4.1%
축 3
 
4.1%
분 3
 
4.1%
뇨 3
 
4.1%
처 3
 
4.1%
리 3
 
4.1%
수 3
 
4.1%
Other values (27) 36
49.3%
Space Separator
ValueCountFrequency (%)
19
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 73
77.7%
Common 21
 
22.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 8
 
11.0%
및 4
 
5.5%
건 4
 
5.5%
기 3
 
4.1%
축 3
 
4.1%
분 3
 
4.1%
뇨 3
 
4.1%
처 3
 
4.1%
리 3
 
4.1%
수 3
 
4.1%
Other values (27) 36
49.3%
Common
ValueCountFrequency (%)
19
90.5%
, 2
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 73
77.7%
ASCII 21
 
22.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19
90.5%
, 2
 
9.5%
Hangul
ValueCountFrequency (%)
업 8
 
11.0%
및 4
 
5.5%
건 4
 
5.5%
기 3
 
4.1%
축 3
 
4.1%
분 3
 
4.1%
뇨 3
 
4.1%
처 3
 
4.1%
리 3
 
4.1%
수 3
 
4.1%
Other values (27) 36
49.3%

종별명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing63
Missing (%)100.0%
Memory size699.0 B

주생산품명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing63
Missing (%)100.0%
Memory size699.0 B

배출시설조업시간
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing63
Missing (%)100.0%
Memory size699.0 B

배출시설연간가동일수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing63
Missing (%)100.0%
Memory size699.0 B

방지시설조업시간
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing63
Missing (%)100.0%
Memory size699.0 B

방지시설연간가동일수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing63
Missing (%)100.0%
Memory size699.0 B

Sample

번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명업종구분명종별명주생산품명배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수
01단독정화조/오수처리시설설계시공업09_30_07_P341000034100005400000000120031018<NA>3폐업2폐업19000101<NA><NA><NA><NA><NA>700320대구광역시 중구 대신동 1450-1<NA><NA>(주)동서개발20151231092532I2018-08-31 23:59:59.0<NA><NA><NA>분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA>
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