Overview

Dataset statistics

Number of variables36
Number of observations53
Missing cells700
Missing cells (%)36.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.9 KiB
Average record size in memory306.5 B

Variable types

Numeric5
Categorical10
DateTime6
Unsupported7
Text8

Dataset

Description23년06월_6270000_대구광역시_09_30_07_P_단독정화조오수처리시설설계시공업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000098783&dataSetDetailId=DDI_0000098805&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
휴업시작일자 has constant value ""Constant
휴업종료일자 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
배출시설연간가동일수 is highly imbalanced (76.8%)Imbalance
방지시설연간가동일수 is highly imbalanced (76.8%)Imbalance
인허가취소일자 has 53 (100.0%) missing valuesMissing
폐업일자 has 6 (11.3%) missing valuesMissing
휴업시작일자 has 52 (98.1%) missing valuesMissing
휴업종료일자 has 52 (98.1%) 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 6 (11.3%) 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 13 (24.5%) missing valuesMissing
좌표정보(Y) has 13 (24.5%) 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
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

Reproduction

Analysis started2023-12-10 20:45:07.166120
Analysis finished2023-12-10 20:45:08.021693
Duration0.86 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 size609.0 B
2023-12-11T05:45:08.159793image/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
2023-12-11T05:45:08.387059image/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 size556.0 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

2023-12-11T05:45:08.588395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:45:08.757947image/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 size556.0 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

2023-12-11T05:45:08.913734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:45:09.049796image/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 size609.0 B
2023-12-11T05:45:09.174607image/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
2023-12-11T05:45:09.359054image/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 size609.0 B
2023-12-11T05:45:09.589139image/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
2023-12-11T05:45:09.816634image/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
Date

Distinct51
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size556.0 B
Minimum1995-04-27 00:00:00
Maximum2014-08-06 00:00:00
2023-12-11T05:45:10.435768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:45:10.693767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing53
Missing (%)100.0%
Memory size609.0 B

영업상태구분코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size556.0 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

2023-12-11T05:45:10.930395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:45:11.077545image/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 size556.0 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

2023-12-11T05:45:11.293175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:45:11.486873image/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 size556.0 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

2023-12-11T05:45:11.678325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:45:11.830776image/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 size556.0 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

2023-12-11T05:45:11.991284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:45:12.165606image/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
Date

MISSING 

Distinct41
Distinct (%)87.2%
Missing6
Missing (%)11.3%
Memory size556.0 B
Minimum2003-07-22 00:00:00
Maximum2019-05-31 00:00:00
2023-12-11T05:45:12.324409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:45:12.537132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)

휴업시작일자
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing52
Missing (%)98.1%
Memory size556.0 B
Minimum2021-01-26 00:00:00
Maximum2021-01-26 00:00:00
2023-12-11T05:45:12.701331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:45:12.859499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

휴업종료일자
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing52
Missing (%)98.1%
Memory size556.0 B
Minimum2022-01-01 00:00:00
Maximum2022-01-01 00:00:00
2023-12-11T05:45:12.982713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:45:13.134589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing53
Missing (%)100.0%
Memory size609.0 B

소재지전화
Text

MISSING 

Distinct27
Distinct (%)96.4%
Missing25
Missing (%)47.2%
Memory size556.0 B
2023-12-11T05:45:13.362870image/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%
2023-12-11T05:45:13.789510image/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 size609.0 B

소재지우편번호
Text

MISSING 

Distinct35
Distinct (%)74.5%
Missing6
Missing (%)11.3%
Memory size556.0 B
2023-12-11T05:45:14.106082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters329
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

Unique26 ?
Unique (%)55.3%

Sample

1st row700-380
2nd row700-380
3rd row701-290
4th row701-011
5th row703-833
ValueCountFrequency (%)
704-340 4
 
8.5%
704-240 3
 
6.4%
700-380 2
 
4.3%
704-170 2
 
4.3%
704-150 2
 
4.3%
704-120 2
 
4.3%
704-220 2
 
4.3%
704-130 2
 
4.3%
706-829 2
 
4.3%
704-190 1
 
2.1%
Other values (25) 25
53.2%
2023-12-11T05:45:14.625689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 88
26.7%
7 53
16.1%
- 47
14.3%
4 32
 
9.7%
1 29
 
8.8%
2 25
 
7.6%
3 20
 
6.1%
8 16
 
4.9%
6 9
 
2.7%
5 5
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 282
85.7%
Dash Punctuation 47
 
14.3%

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%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 329
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 88
26.7%
7 53
16.1%
- 47
14.3%
4 32
 
9.7%
1 29
 
8.8%
2 25
 
7.6%
3 20
 
6.1%
8 16
 
4.9%
6 9
 
2.7%
5 5
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 329
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 88
26.7%
7 53
16.1%
- 47
14.3%
4 32
 
9.7%
1 29
 
8.8%
2 25
 
7.6%
3 20
 
6.1%
8 16
 
4.9%
6 9
 
2.7%
5 5
 
1.5%

소재지전체주소
Text

MISSING 

Distinct43
Distinct (%)82.7%
Missing1
Missing (%)1.9%
Memory size556.0 B
2023-12-11T05:45:15.007773image/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%
2023-12-11T05:45:15.632612image/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 size556.0 B
2023-12-11T05:45:15.954557image/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%
2023-12-11T05:45:16.467577image/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
Text

MISSING 

Distinct7
Distinct (%)100.0%
Missing46
Missing (%)86.8%
Memory size556.0 B
2023-12-11T05:45:16.702020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.4285714
Min length5

Characters and Unicode

Total characters45
Distinct characters9
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

Unique7 ?
Unique (%)100.0%

Sample

1st row701-820
2nd row41419
3rd row706-827
4th row706-829
5th row704-240
ValueCountFrequency (%)
701-820 1
14.3%
41419 1
14.3%
706-827 1
14.3%
706-829 1
14.3%
704-240 1
14.3%
704-816 1
14.3%
42948 1
14.3%
2023-12-11T05:45:17.163004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7
15.6%
4 7
15.6%
7 6
13.3%
- 5
11.1%
8 5
11.1%
2 5
11.1%
1 4
8.9%
9 3
6.7%
6 3
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40
88.9%
Dash Punctuation 5
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7
17.5%
4 7
17.5%
7 6
15.0%
8 5
12.5%
2 5
12.5%
1 4
10.0%
9 3
7.5%
6 3
7.5%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 45
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7
15.6%
4 7
15.6%
7 6
13.3%
- 5
11.1%
8 5
11.1%
2 5
11.1%
1 4
8.9%
9 3
6.7%
6 3
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7
15.6%
4 7
15.6%
7 6
13.3%
- 5
11.1%
8 5
11.1%
2 5
11.1%
1 4
8.9%
9 3
6.7%
6 3
6.7%

사업장명
Text

Distinct44
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Memory size556.0 B
2023-12-11T05:45:17.558445image/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%
2023-12-11T05:45:18.142091image/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
Date

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size556.0 B
Minimum2003-07-22 13:21:21
Maximum2022-11-15 15:59:59
2023-12-11T05:45:18.361241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:45:18.555878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size556.0 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

2023-12-11T05:45:18.774363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:45:19.030008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 46
86.8%
u 7
 
13.2%

데이터갱신일자
Date

Distinct8
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Memory size556.0 B
Minimum2018-08-31 23:59:59
Maximum2022-11-17 02:40:00
2023-12-11T05:45:19.163317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:45:19.404605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)

업태구분명
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing47
Missing (%)88.7%
Memory size556.0 B
2023-12-11T05:45:19.668514image/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%
2023-12-11T05:45:20.156825image/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 

Distinct33
Distinct (%)82.5%
Missing13
Missing (%)24.5%
Infinite0
Infinite (%)0.0%
Mean339847.77
Minimum331206.2
Maximum348355.24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2023-12-11T05:45:20.389685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum331206.2
5-th percentile333256.38
Q1335159.06
median339278.95
Q3344887.66
95-th percentile347273.58
Maximum348355.24
Range17149.037
Interquartile range (IQR)9728.5984

Descriptive statistics

Standard deviation4893.0517
Coefficient of variation (CV)0.014397775
Kurtosis-1.1044023
Mean339847.77
Median Absolute Deviation (MAD)4265.6002
Skewness0.07003873
Sum13593911
Variance23941955
MonotonicityNot monotonic
2023-12-11T05:45:20.582324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
335204.344635042 2
 
3.8%
334132.329267829 2
 
3.8%
339278.945555404 2
 
3.8%
339268.571431824 2
 
3.8%
344912.358902194 2
 
3.8%
335003.494757265 2
 
3.8%
333346.979451825 2
 
3.8%
331206.199479115 1
 
1.9%
336925.111710125 1
 
1.9%
340109.599289952 1
 
1.9%
Other values (23) 23
43.4%
(Missing) 13
24.5%
ValueCountFrequency (%)
331206.199479115 1
1.9%
331535.063936148 1
1.9%
333346.979451825 2
3.8%
334132.329267829 2
3.8%
334847.929146302 1
1.9%
335003.494757265 2
3.8%
335023.196036028 1
1.9%
335204.344635042 2
3.8%
336925.111710125 1
1.9%
337740.137948483 1
1.9%
ValueCountFrequency (%)
348355.236481866 1
1.9%
347476.069562446 1
1.9%
347262.921603298 1
1.9%
347073.127192313 1
1.9%
346621.319604807 1
1.9%
345653.080016443 1
1.9%
345448.163789315 1
1.9%
345374.817551305 1
1.9%
344912.358902194 2
3.8%
344879.421493561 1
1.9%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct33
Distinct (%)82.5%
Missing13
Missing (%)24.5%
Infinite0
Infinite (%)0.0%
Mean261654.17
Minimum243957.69
Maximum272658.57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2023-12-11T05:45:20.769693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum243957.69
5-th percentile256877.65
Q1259870.58
median261067.99
Q3263767.37
95-th percentile268264.98
Maximum272658.57
Range28700.879
Interquartile range (IQR)3896.788

Descriptive statistics

Standard deviation4921.0201
Coefficient of variation (CV)0.018807344
Kurtosis4.1214417
Mean261654.17
Median Absolute Deviation (MAD)2071.9081
Skewness-1.1216823
Sum10466167
Variance24216439
MonotonicityNot monotonic
2023-12-11T05:45:20.962556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
260540.004453834 2
 
3.8%
260892.868330824 2
 
3.8%
260821.061770907 2
 
3.8%
262491.614242377 2
 
3.8%
268253.830252935 2
 
3.8%
257266.281256307 2
 
3.8%
261694.015322099 2
 
3.8%
249493.752629182 1
 
1.9%
260714.533062513 1
 
1.9%
259602.211061994 1
 
1.9%
Other values (23) 23
43.4%
(Missing) 13
24.5%
ValueCountFrequency (%)
243957.688388711 1
1.9%
249493.752629182 1
1.9%
257266.281256307 2
3.8%
257280.684298351 1
1.9%
257791.23342159 1
1.9%
258950.140155541 1
1.9%
259602.211061994 1
1.9%
259623.992930334 1
1.9%
259644.730920875 1
1.9%
259945.860170923 1
1.9%
ValueCountFrequency (%)
272658.567426886 1
1.9%
268476.874902975 1
1.9%
268253.830252935 2
3.8%
266964.397077338 1
1.9%
266643.070989441 1
1.9%
266495.668171522 1
1.9%
265713.85207522 1
1.9%
264809.315220653 1
1.9%
264369.712568155 1
1.9%
263566.583671473 1
1.9%

환경업무구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size556.0 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

2023-12-11T05:45:21.141263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:45:21.279052image/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 size556.0 B
2023-12-11T05:45:21.495588image/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%
2023-12-11T05:45:21.987843image/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 size609.0 B

주생산품명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing53
Missing (%)100.0%
Memory size609.0 B

배출시설조업시간
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing53
Missing (%)100.0%
Memory size609.0 B

배출시설연간가동일수
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size556.0 B
<NA>
51 
0
 
2

Length

Max length4
Median length4
Mean length3.8867925
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 51
96.2%
0 2
 
3.8%

Length

2023-12-11T05:45:22.182518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:45:22.332035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 51
96.2%
0 2
 
3.8%

방지시설조업시간
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing53
Missing (%)100.0%
Memory size609.0 B

방지시설연간가동일수
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size556.0 B
<NA>
51 
0
 
2

Length

Max length4
Median length4
Mean length3.8867925
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 51
96.2%
0 2
 
3.8%

Length

2023-12-11T05:45:22.525129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:45:22.698612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 51
96.2%
0 2
 
3.8%

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명업종구분명종별명주생산품명배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수
01단독정화조/오수처리시설설계시공업09_30_07_P34100003410000540000000032004-07-14<NA>3폐업2폐업2014-01-03<NA><NA><NA><NA><NA>700-380대구광역시 중구 달성동 121-4<NA><NA>주식회사 기술신환경2014-10-14 17:20:36I2018-08-31 23:59:59농업<NA><NA>분뇨등설계시공업관리농업<NA><NA><NA><NA><NA><NA>
12단독정화조/오수처리시설설계시공업09_30_07_P34100003410000542004000042004-07-20<NA>3폐업2폐업2014-01-03<NA><NA><NA><NA><NA>700-380대구광역시 중구 달성동 121-4<NA><NA>(주)기술신환경2014-10-14 17:22:49I2018-08-31 23:59:59<NA><NA><NA>분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA>
23단독정화조/오수처리시설설계시공업09_30_07_P34200003420000542004000031999-04-14<NA>3폐업2폐업2007-11-27<NA><NA><NA><NA><NA>701-290대구광역시 동구 각산동 295-5<NA><NA>한일기공2007-11-27 13:22:36I2018-08-31 23:59:59<NA><NA><NA>분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA>
34단독정화조/오수처리시설설계시공업09_30_07_P34200003420000542006000012006-05-10<NA>3폐업2폐업2018-11-09<NA><NA><NA>952-5570<NA>701-011대구광역시 동구 신암동 722-12대구광역시 동구 평화로 27 (신암동)701-820우경환경건설2018-11-09 16:14:07U2018-11-11 02:38:39<NA><NA><NA>분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA>
45단독정화조/오수처리시설설계시공업09_30_07_P34300003430000542009000012009-01-21<NA>3폐업2폐업2009-04-07<NA><NA><NA>5635123<NA>703-833대구광역시 서구 중리동 1120-10<NA><NA>거성환경(주)2009-06-11 16:53:55I2018-08-31 23:59:59<NA>338877.031094263555.070354분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA>
56단독정화조/오수처리시설설계시공업09_30_07_P34300003430000542004000012004-03-15<NA>3폐업2폐업2006-07-05<NA><NA><NA><NA><NA>703-031대구광역시 서구 원대동1가 79 대원아파트 A동 105호<NA><NA>(주)유일환경건설2007-05-01 17:13:38I2018-08-31 23:59:59<NA>342487.69733265713.852075분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA>
67단독정화조/오수처리시설설계시공업09_30_07_P34300003430000542014000012014-08-06<NA>3폐업2폐업2015-05-18<NA><NA><NA>053-555-6171<NA>703-110대구광역시 서구 이현동 42-292대구광역시 서구 와룡로83길 13 (이현동)<NA>(주)이화환경 지점2015-11-23 11:56:26I2018-08-31 23:59:59<NA>338677.427853264369.712568분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA>
78단독정화조/오수처리시설설계시공업09_30_07_P34500003450000542003000022003-10-22<NA>3폐업2폐업2014-11-18<NA><NA><NA>053 384 3347<NA>702-010대구광역시 북구 산격동 1691<NA><NA>그린엔지니어링(주)2014-11-18 11:54:11I2018-08-31 23:59:59<NA><NA><NA>분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA>
89단독정화조/오수처리시설설계시공업09_30_07_P34500003450000542005000032005-07-05<NA>3폐업2폐업2007-10-22<NA><NA><NA>053 604 3977<NA>702-003대구광역시 북구 산격동 1626 전자도매상가 5동 307호<NA><NA>한솔환경주식회사2007-10-22 15:00:58I2018-08-31 23:59:59<NA>344879.421494268476.874903분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA>
910단독정화조/오수처리시설설계시공업09_30_07_P34500003450000542005000012005-04-15<NA>3폐업2폐업2009-04-28<NA><NA><NA>053607 9000<NA>702-857대구광역시 북구 침산동 416-8<NA><NA>(주)씨앤우방2009-04-28 16:45:43I2018-08-31 23:59:59<NA>342994.81975266495.668172분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명업종구분명종별명주생산품명배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수
4344단독정화조/오수처리시설설계시공업09_30_07_P34700003470000542001001002001-11-02<NA>3폐업2폐업2005-11-14<NA><NA><NA><NA><NA>704-230대구광역시 달서구 호산동 167-3<NA><NA>(주)마니이엔비2003-11-21 13:57:47I2018-08-31 23:59:59<NA><NA><NA>분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA>
4445단독정화조/오수처리시설설계시공업09_30_07_P34700003470000542002001052002-04-22<NA>3폐업2폐업2005-06-01<NA><NA><NA><NA><NA>704-190대구광역시 달서구 장동 116-1대구광역시 달서구 성서동로 184 (장동)<NA>사하라환경건설2009-11-12 15:42:20I2018-08-31 23:59:59<NA>336925.11171260714.533063분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA>
4546단독정화조/오수처리시설설계시공업09_30_07_P34700003470000541999000071999-07-30<NA>3폐업2폐업2015-06-10<NA><NA><NA><NA><NA>704-170대구광역시 달서구 갈산동 358-81대구광역시 달서구 성서공단로25길 6 (갈산동)<NA>(주)로얄정공2015-06-10 11:13:12I2018-08-31 23:59:59<NA>335204.344635260540.004454분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA>
4647단독정화조/오수처리시설설계시공업09_30_07_P34700003470000542004000022004-05-14<NA>3폐업4폐쇄<NA><NA><NA><NA>053 583 8651<NA>704-170대구광역시 달서구 갈산동 358-81대구광역시 달서구 성서공단로25길 6 (갈산동)<NA>(주)로얄정공2009-11-12 17:02:27I2018-08-31 23:59:59<NA>335204.344635260540.004454분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA>
4748단독정화조/오수처리시설설계시공업09_30_07_P34800003480000542002000012002-03-25<NA>3폐업2폐업2009-01-20<NA><NA><NA><NA><NA>711-874대구광역시 달성군 현풍읍 원교리 95-4<NA><NA>달성환경건걸(주)2009-01-20 11:52:42I2018-08-31 23:59:59<NA><NA><NA>분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA>
4849단독정화조/오수처리시설설계시공업09_30_07_P34800003480000541999000011999-02-23<NA>3폐업2폐업2003-11-10<NA><NA><NA><NA><NA>711-852대구광역시 달성군 논공읍 북리 580-34대구광역시 달성군 논공읍 논공로53길 70<NA>(주)대원엔바이로2003-12-18 15:43:14I2018-08-31 23:59:59<NA>331206.199479249493.752629분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA>
4950단독정화조/오수처리시설설계시공업09_30_07_P34800003480000542006000012006-03-03<NA>3폐업2폐업2010-01-11<NA><NA><NA><NA><NA>711-883대구광역시 달성군 유가읍 상리 720대구광역시 달성군 유가면 비슬로96길 97<NA>세하주식회사2010-01-11 17:12:06I2018-08-31 23:59:59<NA>331535.063936243957.688389분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA>
5051단독정화조/오수처리시설설계시공업09_30_07_P34800003480000542008000012008-12-31<NA>1영업/정상11영업<NA><NA><NA><NA>053-643-2323<NA><NA><NA>대구광역시 달성군 화원읍 성천로 12242948(주)금창엔지지어링2022-11-15 15:59:59U2022-11-17 02:40:00<NA>335023.196036257280.684298분뇨등설계시공업관리<NA><NA><NA><NA>0<NA>0
5152단독정화조/오수처리시설설계시공업09_30_07_P34800003480000542004000022004-10-26<NA>3폐업2폐업2007-01-05<NA><NA><NA>053 6163667<NA><NA>대구광역시 달성군 화원읍 천내리 107-1대구광역시 달성군 화원읍 성천로24길 1-5<NA>대한기업(주)2005-08-31 12:15:02I2018-08-31 23:59:59<NA>335003.494757257266.281256분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA>
5253단독정화조/오수처리시설설계시공업09_30_07_P34800003480000542004000032004-12-06<NA>3폐업2폐업2008-03-04<NA><NA><NA>053643 2323<NA><NA>대구광역시 달성군 화원읍 천내리 107-1대구광역시 달성군 화원읍 성천로24길 1-5<NA>(주)금창엔지니어링2008-03-04 17:49:46I2018-08-31 23:59:59<NA>335003.494757257266.281256분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA>