Overview

Dataset statistics

Number of variables37
Number of observations113
Missing cells1344
Missing cells (%)32.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory35.4 KiB
Average record size in memory321.2 B

Variable types

Numeric11
Categorical15
Unsupported9
Text2

Dataset

Description22년08월_6270000_대구광역시_09_30_10_P_분뇨수집운반업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000094295&dataSetDetailId=DDI_0000094350&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
환경업무구분명 has constant value ""Constant
업태구분명 is highly imbalanced (60.8%)Imbalance
업종구분명 is highly imbalanced (60.8%)Imbalance
인허가취소일자 has 113 (100.0%) missing valuesMissing
폐업일자 has 84 (74.3%) missing valuesMissing
휴업시작일자 has 113 (100.0%) missing valuesMissing
휴업종료일자 has 113 (100.0%) missing valuesMissing
재개업일자 has 102 (90.3%) missing valuesMissing
소재지전화 has 11 (9.7%) missing valuesMissing
소재지면적 has 113 (100.0%) missing valuesMissing
소재지우편번호 has 47 (41.6%) missing valuesMissing
도로명우편번호 has 57 (50.4%) missing valuesMissing
좌표정보(X) has 13 (11.5%) missing valuesMissing
좌표정보(Y) has 13 (11.5%) missing valuesMissing
종별명 has 113 (100.0%) missing valuesMissing
주생산품명 has 113 (100.0%) missing valuesMissing
배출시설조업시간 has 113 (100.0%) missing valuesMissing
방지시설조업시간 has 113 (100.0%) missing valuesMissing
사업자등록번호 has 113 (100.0%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
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 started2024-04-17 17:50:53.812612
Analysis finished2024-04-17 17:50:54.187043
Duration0.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct113
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57
Minimum1
Maximum113
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-18T02:50:54.262492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.6
Q129
median57
Q385
95-th percentile107.4
Maximum113
Range112
Interquartile range (IQR)56

Descriptive statistics

Standard deviation32.76431
Coefficient of variation (CV)0.57481245
Kurtosis-1.2
Mean57
Median Absolute Deviation (MAD)28
Skewness0
Sum6441
Variance1073.5
MonotonicityStrictly increasing
2024-04-18T02:50:54.407580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
86 1
 
0.9%
84 1
 
0.9%
83 1
 
0.9%
82 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
Other values (103) 103
91.2%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
113 1
0.9%
112 1
0.9%
111 1
0.9%
110 1
0.9%
109 1
0.9%
108 1
0.9%
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
분뇨수집운반업
113 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
분뇨수집운반업 113
100.0%

Length

2024-04-18T02:50:54.518849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:50:54.586498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분뇨수집운반업 113
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
09_30_10_P
113 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09_30_10_P
2nd row09_30_10_P
3rd row09_30_10_P
4th row09_30_10_P
5th row09_30_10_P

Common Values

ValueCountFrequency (%)
09_30_10_P 113
100.0%

Length

2024-04-18T02:50:54.654712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:50:54.719690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_30_10_p 113
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3444247.8
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-18T02:50:54.780549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3420000
Q13430000
median3440000
Q33460000
95-th percentile3480000
Maximum3480000
Range70000
Interquartile range (IQR)30000

Descriptive statistics

Standard deviation19946.594
Coefficient of variation (CV)0.0057912774
Kurtosis-1.0221874
Mean3444247.8
Median Absolute Deviation (MAD)10000
Skewness0.18494954
Sum3.892 × 108
Variance3.9786662 × 108
MonotonicityIncreasing
2024-04-18T02:50:54.875495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3450000 21
18.6%
3430000 20
17.7%
3420000 18
15.9%
3440000 16
14.2%
3470000 16
14.2%
3460000 9
8.0%
3480000 8
 
7.1%
3410000 5
 
4.4%
ValueCountFrequency (%)
3410000 5
 
4.4%
3420000 18
15.9%
3430000 20
17.7%
3440000 16
14.2%
3450000 21
18.6%
3460000 9
8.0%
3470000 16
14.2%
3480000 8
 
7.1%
ValueCountFrequency (%)
3480000 8
 
7.1%
3470000 16
14.2%
3460000 9
8.0%
3450000 21
18.6%
3440000 16
14.2%
3430000 20
17.7%
3420000 18
15.9%
3410000 5
 
4.4%

관리번호
Real number (ℝ)

UNIQUE 

Distinct113
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4442483 × 1017
Minimum3.4100005 × 1017
Maximum3.4800005 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-18T02:50:55.007327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.4100005 × 1017
5-th percentile3.4200005 × 1017
Q13.4300005 × 1017
median3.4400005 × 1017
Q33.4600005 × 1017
95-th percentile3.4800005 × 1017
Maximum3.4800005 × 1017
Range7 × 1015
Interquartile range (IQR)3 × 1015

Descriptive statistics

Standard deviation1.9946595 × 1015
Coefficient of variation (CV)0.0057912766
Kurtosis-1.0221874
Mean3.4442483 × 1017
Median Absolute Deviation (MAD)1 × 1015
Skewness0.18494952
Sum2.0265179 × 1018
Variance3.9786664 × 1030
MonotonicityNot monotonic
2024-04-18T02:50:55.149438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
341000053199500001 1
 
0.9%
346000053200800002 1
 
0.9%
346000053200200003 1
 
0.9%
346000053200100002 1
 
0.9%
346000053200000007 1
 
0.9%
346000053200000005 1
 
0.9%
345000053200100004 1
 
0.9%
345000053199900005 1
 
0.9%
345000053199900015 1
 
0.9%
345000053199900013 1
 
0.9%
Other values (103) 103
91.2%
ValueCountFrequency (%)
341000053199500001 1
0.9%
341000053199500002 1
0.9%
341000053199500003 1
0.9%
341000053199500004 1
0.9%
341000053199900005 1
0.9%
342000053000000001 1
0.9%
342000053000000002 1
0.9%
342000053000000003 1
0.9%
342000053000000004 1
0.9%
342000053000000005 1
0.9%
ValueCountFrequency (%)
348000053199910006 1
0.9%
348000053199910005 1
0.9%
348000053199910004 1
0.9%
348000053199910003 1
0.9%
348000053199910002 1
0.9%
348000053199900006 1
0.9%
348000053199410001 1
0.9%
348000053199400001 1
0.9%
347000053201200001 1
0.9%
347000053200900001 1
0.9%

인허가일자
Real number (ℝ)

Distinct83
Distinct (%)73.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20007723
Minimum19900119
Maximum20201204
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-18T02:50:55.294900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19900119
5-th percentile19930119
Q119990507
median20000308
Q320030510
95-th percentile20102816
Maximum20201204
Range301085
Interquartile range (IQR)40003

Descriptive statistics

Standard deviation59356.283
Coefficient of variation (CV)0.0029666685
Kurtosis2.6305634
Mean20007723
Median Absolute Deviation (MAD)10902
Skewness1.2075669
Sum2.2608727 × 109
Variance3.5231683 × 109
MonotonicityNot monotonic
2024-04-18T02:50:55.421594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000818 8
 
7.1%
19950222 4
 
3.5%
19930119 4
 
3.5%
19990519 3
 
2.7%
19990517 3
 
2.7%
19990520 3
 
2.7%
19930120 3
 
2.7%
19990727 2
 
1.8%
19940517 2
 
1.8%
20200414 2
 
1.8%
Other values (73) 79
69.9%
ValueCountFrequency (%)
19900119 1
 
0.9%
19900120 1
 
0.9%
19911015 1
 
0.9%
19911228 1
 
0.9%
19920227 1
 
0.9%
19930119 4
3.5%
19930120 3
2.7%
19940113 1
 
0.9%
19940517 2
1.8%
19941012 1
 
0.9%
ValueCountFrequency (%)
20201204 1
0.9%
20200414 2
1.8%
20190807 1
0.9%
20180710 1
0.9%
20120208 1
0.9%
20091222 1
0.9%
20080805 1
0.9%
20080603 1
0.9%
20080507 2
1.8%
20080404 2
1.8%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing113
Missing (%)100.0%
Memory size1.1 KiB
Distinct3
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
1
69 
3
29 
4
15 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 69
61.1%
3 29
25.7%
4 15
 
13.3%

Length

2024-04-18T02:50:55.529394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:50:55.612423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 69
61.1%
3 29
25.7%
4 15
 
13.3%

영업상태명
Categorical

Distinct3
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
영업/정상
69 
폐업
29 
취소/말소/만료/정지/중지
15 

Length

Max length14
Median length5
Mean length5.4247788
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 69
61.1%
폐업 29
25.7%
취소/말소/만료/정지/중지 15
 
13.3%

Length

2024-04-18T02:50:55.690696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:50:55.765069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 69
61.1%
폐업 29
25.7%
취소/말소/만료/정지/중지 15
 
13.3%
Distinct4
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
11
58 
2
29 
4
15 
3
11 

Length

Max length2
Median length2
Mean length1.5132743
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11
2nd row11
3rd row11
4th row11
5th row11

Common Values

ValueCountFrequency (%)
11 58
51.3%
2 29
25.7%
4 15
 
13.3%
3 11
 
9.7%

Length

2024-04-18T02:50:55.845106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:50:55.933670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11 58
51.3%
2 29
25.7%
4 15
 
13.3%
3 11
 
9.7%
Distinct4
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
영업
58 
폐업
29 
폐쇄
15 
재개업
11 

Length

Max length3
Median length2
Mean length2.0973451
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 58
51.3%
폐업 29
25.7%
폐쇄 15
 
13.3%
재개업 11
 
9.7%

Length

2024-04-18T02:50:56.039073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:50:56.113648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 58
51.3%
폐업 29
25.7%
폐쇄 15
 
13.3%
재개업 11
 
9.7%

폐업일자
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)69.0%
Missing84
Missing (%)74.3%
Infinite0
Infinite (%)0.0%
Mean20071418
Minimum20001123
Maximum20190807
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-18T02:50:56.198049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20001123
5-th percentile20001124
Q120020712
median20070928
Q320090914
95-th percentile20169183
Maximum20190807
Range189684
Interquartile range (IQR)70202

Descriptive statistics

Standard deviation49872.184
Coefficient of variation (CV)0.0024847364
Kurtosis0.37784525
Mean20071418
Median Absolute Deviation (MAD)29275
Skewness0.68644923
Sum5.8207113 × 108
Variance2.4872347 × 109
MonotonicityNot monotonic
2024-04-18T02:50:56.290113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
20070928 5
 
4.4%
20020712 2
 
1.8%
20080616 2
 
1.8%
20090914 2
 
1.8%
20001124 2
 
1.8%
20020101 2
 
1.8%
20050525 1
 
0.9%
20050527 1
 
0.9%
20140116 1
 
0.9%
20100427 1
 
0.9%
Other values (10) 10
 
8.8%
(Missing) 84
74.3%
ValueCountFrequency (%)
20001123 1
 
0.9%
20001124 2
 
1.8%
20020101 2
 
1.8%
20020403 1
 
0.9%
20020712 2
 
1.8%
20050525 1
 
0.9%
20050527 1
 
0.9%
20060724 1
 
0.9%
20070820 1
 
0.9%
20070928 5
4.4%
ValueCountFrequency (%)
20190807 1
0.9%
20181231 1
0.9%
20151111 1
0.9%
20140116 1
0.9%
20100427 1
0.9%
20100326 1
0.9%
20100203 1
0.9%
20090914 2
1.8%
20080616 2
1.8%
20071212 1
0.9%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing113
Missing (%)100.0%
Memory size1.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing113
Missing (%)100.0%
Memory size1.1 KiB

재개업일자
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)72.7%
Missing102
Missing (%)90.3%
Infinite0
Infinite (%)0.0%
Mean20100816
Minimum20020501
Maximum20131201
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-18T02:50:56.379511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20020501
5-th percentile20025560
Q120095822
median20120101
Q320121206
95-th percentile20131201
Maximum20131201
Range110700
Interquartile range (IQR)25384

Descriptive statistics

Standard deviation39673.566
Coefficient of variation (CV)0.0019737291
Kurtosis0.9079272
Mean20100816
Median Absolute Deviation (MAD)8873
Skewness-1.5177812
Sum2.2110898 × 108
Variance1.5739919 × 109
MonotonicityNot monotonic
2024-04-18T02:50:56.461200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
20131201 2
 
1.8%
20121201 2
 
1.8%
20120101 2
 
1.8%
20121210 1
 
0.9%
20111228 1
 
0.9%
20030620 1
 
0.9%
20020501 1
 
0.9%
20080415 1
 
0.9%
(Missing) 102
90.3%
ValueCountFrequency (%)
20020501 1
0.9%
20030620 1
0.9%
20080415 1
0.9%
20111228 1
0.9%
20120101 2
1.8%
20121201 2
1.8%
20121210 1
0.9%
20131201 2
1.8%
ValueCountFrequency (%)
20131201 2
1.8%
20121210 1
0.9%
20121201 2
1.8%
20120101 2
1.8%
20111228 1
0.9%
20080415 1
0.9%
20030620 1
0.9%
20020501 1
0.9%

소재지전화
Text

MISSING 

Distinct87
Distinct (%)85.3%
Missing11
Missing (%)9.7%
Memory size1.0 KiB
2024-04-18T02:50:56.625556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.892157
Min length7

Characters and Unicode

Total characters1111
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

Unique72 ?
Unique (%)70.6%

Sample

1st row053-287-3000
2nd row053-565-0780
3rd row053-565-3637
4th row053-565-0115
5th row053-565-0116
ValueCountFrequency (%)
053 44
27.3%
6386868 2
 
1.2%
6347800 2
 
1.2%
355 2
 
1.2%
0535625160 2
 
1.2%
053-765-1515 2
 
1.2%
5001 2
 
1.2%
959 2
 
1.2%
6237447 2
 
1.2%
6536086 2
 
1.2%
Other values (88) 99
61.5%
2024-04-18T02:50:56.919510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 207
18.6%
5 207
18.6%
3 176
15.8%
6 87
7.8%
1 69
 
6.2%
59
 
5.3%
8 59
 
5.3%
- 59
 
5.3%
4 58
 
5.2%
2 47
 
4.2%
Other values (2) 83
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 993
89.4%
Space Separator 59
 
5.3%
Dash Punctuation 59
 
5.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 207
20.8%
5 207
20.8%
3 176
17.7%
6 87
8.8%
1 69
 
6.9%
8 59
 
5.9%
4 58
 
5.8%
2 47
 
4.7%
7 43
 
4.3%
9 40
 
4.0%
Space Separator
ValueCountFrequency (%)
59
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 59
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1111
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 207
18.6%
5 207
18.6%
3 176
15.8%
6 87
7.8%
1 69
 
6.2%
59
 
5.3%
8 59
 
5.3%
- 59
 
5.3%
4 58
 
5.2%
2 47
 
4.2%
Other values (2) 83
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1111
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 207
18.6%
5 207
18.6%
3 176
15.8%
6 87
7.8%
1 69
 
6.2%
59
 
5.3%
8 59
 
5.3%
- 59
 
5.3%
4 58
 
5.2%
2 47
 
4.2%
Other values (2) 83
7.5%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing113
Missing (%)100.0%
Memory size1.1 KiB

소재지우편번호
Real number (ℝ)

MISSING 

Distinct25
Distinct (%)37.9%
Missing47
Missing (%)41.6%
Infinite0
Infinite (%)0.0%
Mean704776.12
Minimum701013
Maximum711837
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-18T02:50:57.274384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum701013
5-th percentile701815
Q1703016
median704080
Q3705041
95-th percentile711834
Maximum711837
Range10824
Interquartile range (IQR)2025

Descriptive statistics

Standard deviation2636.2517
Coefficient of variation (CV)0.0037405519
Kurtosis2.3941532
Mean704776.12
Median Absolute Deviation (MAD)1064
Skewness1.6142286
Sum46515224
Variance6949822.8
MonotonicityNot monotonic
2024-04-18T02:50:57.411221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
704080 10
 
8.8%
703016 9
 
8.0%
703836 7
 
6.2%
701815 5
 
4.4%
706852 5
 
4.4%
705041 4
 
3.5%
711837 3
 
2.7%
703010 3
 
2.7%
705040 2
 
1.8%
711834 2
 
1.8%
Other values (15) 16
 
14.2%
(Missing) 47
41.6%
ValueCountFrequency (%)
701013 1
 
0.9%
701801 1
 
0.9%
701815 5
4.4%
702072 1
 
0.9%
703010 3
 
2.7%
703016 9
8.0%
703836 7
6.2%
704080 10
8.8%
704360 1
 
0.9%
704390 2
 
1.8%
ValueCountFrequency (%)
711837 3
2.7%
711834 2
 
1.8%
711830 1
 
0.9%
706852 5
4.4%
706841 1
 
0.9%
706091 1
 
0.9%
706060 1
 
0.9%
705041 4
3.5%
705040 2
 
1.8%
705035 1
 
0.9%
Distinct33
Distinct (%)29.2%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
대구광역시 서구 평리동 617-18
17 
대구광역시 동구 신암동 804-5 3층
11 
대구광역시 북구 고성동2가 113-2
11 
대구광역시 달서구 성당동 670-25
11 
대구광역시 남구 대명동 1889-14
Other values (28)
57 

Length

Max length25
Median length24
Mean length20.79646
Min length17

Unique

Unique13 ?
Unique (%)11.5%

Sample

1st row대구광역시 중구 태평로3가 190-6
2nd row대구광역시 중구 태평로3가 190-6
3rd row대구광역시 중구 태평로3가 190-6
4th row대구광역시 중구 태평로3가 190-6
5th row대구광역시 중구 태평로3가 190-6

Common Values

ValueCountFrequency (%)
대구광역시 서구 평리동 617-18 17
15.0%
대구광역시 동구 신암동 804-5 3층 11
 
9.7%
대구광역시 북구 고성동2가 113-2 11
 
9.7%
대구광역시 달서구 성당동 670-25 11
 
9.7%
대구광역시 남구 대명동 1889-14 6
 
5.3%
대구광역시 동구 신암동 211 6
 
5.3%
대구광역시 중구 태평로3가 190-6 5
 
4.4%
대구광역시 달성군 화원읍 천내리 27-3 5
 
4.4%
대구광역시 남구 대명동 1122-2 3
 
2.7%
대구광역시 서구 평리동 618-19 3
 
2.7%
Other values (23) 35
31.0%

Length

2024-04-18T02:50:57.516400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대구광역시 113
23.9%
북구 21
 
4.4%
평리동 20
 
4.2%
서구 20
 
4.2%
동구 18
 
3.8%
617-18 17
 
3.6%
신암동 17
 
3.6%
남구 16
 
3.4%
달서구 16
 
3.4%
대명동 16
 
3.4%
Other values (55) 198
41.9%
Distinct30
Distinct (%)26.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
<NA>
13 
대구광역시 동구 대현로 137, 3층 (신암동)
11 
대구광역시 서구 서대구로 201 (평리동)
10 
대구광역시 북구 고성로 142 (고성동2가)
대구광역시 달서구 야외음악당로 103 (성당동)
Other values (25)
62 

Length

Max length33
Median length28
Mean length22.584071
Min length4

Unique

Unique11 ?
Unique (%)9.7%

Sample

1st row대구광역시 중구 태평로 65-10, 3층 (태평로3가)
2nd row대구광역시 중구 태평로 65-10, 3층 (태평로3가)
3rd row대구광역시 중구 태평로 65-10, 3층 (태평로3가)
4th row대구광역시 중구 태평로 65-10, 3층 (태평로3가)
5th row대구광역시 중구 태평로 65-10, 3층 (태평로3가)

Common Values

ValueCountFrequency (%)
<NA> 13
 
11.5%
대구광역시 동구 대현로 137, 3층 (신암동) 11
 
9.7%
대구광역시 서구 서대구로 201 (평리동) 10
 
8.8%
대구광역시 북구 고성로 142 (고성동2가) 9
 
8.0%
대구광역시 달서구 야외음악당로 103 (성당동) 8
 
7.1%
대구광역시 서구 서대구로 201 (평리동) 7
 
6.2%
대구광역시 남구 명덕로 134-1 (대명동) 6
 
5.3%
대구광역시 중구 태평로 65-10, 3층 (태평로3가) 5
 
4.4%
대구광역시 달성군 화원읍 화원로1길 36-4 5
 
4.4%
대구광역시 수성구 희망로 189 (황금동) 5
 
4.4%
Other values (20) 34
30.1%

Length

2024-04-18T02:50:57.610522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대구광역시 100
 
18.7%
서구 20
 
3.7%
평리동 20
 
3.7%
3층 19
 
3.6%
동구 18
 
3.4%
신암동 17
 
3.2%
서대구로 17
 
3.2%
201 17
 
3.2%
북구 17
 
3.2%
달서구 16
 
3.0%
Other values (64) 273
51.1%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct16
Distinct (%)28.6%
Missing57
Missing (%)50.4%
Infinite0
Infinite (%)0.0%
Mean196207.93
Minimum41196
Maximum711837
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-18T02:50:57.689436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41196
5-th percentile41196
Q141461.75
median41831.5
Q342923.5
95-th percentile711837
Maximum711837
Range670641
Interquartile range (IQR)1461.75

Descriptive statistics

Standard deviation283493.4
Coefficient of variation (CV)1.4448621
Kurtosis-0.31122447
Mean196207.93
Median Absolute Deviation (MAD)577.5
Skewness1.3042001
Sum10987644
Variance8.0368509 × 1010
MonotonicityNot monotonic
2024-04-18T02:50:57.766117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
41596 12
 
10.6%
41196 11
 
9.7%
703836 6
 
5.3%
42409 6
 
5.3%
711837 5
 
4.4%
41901 5
 
4.4%
41434 2
 
1.8%
41469 1
 
0.9%
41440 1
 
0.9%
706091 1
 
0.9%
Other values (6) 6
 
5.3%
(Missing) 57
50.4%
ValueCountFrequency (%)
41196 11
9.7%
41434 2
 
1.8%
41440 1
 
0.9%
41469 1
 
0.9%
41596 12
10.6%
41762 1
 
0.9%
41901 5
4.4%
42176 1
 
0.9%
42409 6
5.3%
42655 1
 
0.9%
ValueCountFrequency (%)
711837 5
4.4%
706091 1
 
0.9%
704837 1
 
0.9%
703836 6
5.3%
42970 1
 
0.9%
42908 1
 
0.9%
42655 1
 
0.9%
42409 6
5.3%
42176 1
 
0.9%
41901 5
4.4%
Distinct85
Distinct (%)75.2%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-04-18T02:50:57.985039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length6.7610619
Min length4

Characters and Unicode

Total characters764
Distinct characters76
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

Unique61 ?
Unique (%)54.0%

Sample

1st row(주)중성
2nd row대우위생(주)
3rd row중구정화(주)
4th row원진위생(주)
5th row한일청화(주)
ValueCountFrequency (%)
주)달서정화조 3
 
2.7%
서부정화조(유 3
 
2.7%
남도위생(주 3
 
2.7%
주)강변정화위생 3
 
2.7%
주)서구정화 2
 
1.8%
주)신세계위생 2
 
1.8%
남구위생사 2
 
1.8%
남부써비스 2
 
1.8%
주)경진기업 2
 
1.8%
주)강번정화위생 2
 
1.8%
Other values (75) 89
78.8%
2024-04-18T02:50:58.313206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 84
 
11.0%
) 84
 
11.0%
80
 
10.5%
57
 
7.5%
57
 
7.5%
46
 
6.0%
43
 
5.6%
25
 
3.3%
25
 
3.3%
24
 
3.1%
Other values (66) 239
31.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 596
78.0%
Open Punctuation 84
 
11.0%
Close Punctuation 84
 
11.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
80
 
13.4%
57
 
9.6%
57
 
9.6%
46
 
7.7%
43
 
7.2%
25
 
4.2%
25
 
4.2%
24
 
4.0%
16
 
2.7%
16
 
2.7%
Other values (64) 207
34.7%
Open Punctuation
ValueCountFrequency (%)
( 84
100.0%
Close Punctuation
ValueCountFrequency (%)
) 84
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 596
78.0%
Common 168
 
22.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
80
 
13.4%
57
 
9.6%
57
 
9.6%
46
 
7.7%
43
 
7.2%
25
 
4.2%
25
 
4.2%
24
 
4.0%
16
 
2.7%
16
 
2.7%
Other values (64) 207
34.7%
Common
ValueCountFrequency (%)
( 84
50.0%
) 84
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 596
78.0%
ASCII 168
 
22.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 84
50.0%
) 84
50.0%
Hangul
ValueCountFrequency (%)
80
 
13.4%
57
 
9.6%
57
 
9.6%
46
 
7.7%
43
 
7.2%
25
 
4.2%
25
 
4.2%
24
 
4.0%
16
 
2.7%
16
 
2.7%
Other values (64) 207
34.7%

최종수정시점
Real number (ℝ)

Distinct112
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.016707 × 1013
Minimum2.0020406 × 1013
Maximum2.0220824 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-18T02:50:58.427083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0020406 × 1013
5-th percentile2.0056647 × 1013
Q12.0130704 × 1013
median2.020021 × 1013
Q32.0210804 × 1013
95-th percentile2.0220624 × 1013
Maximum2.0220824 × 1013
Range2.00418 × 1011
Interquartile range (IQR)8.009998 × 1010

Descriptive statistics

Standard deviation6.0635463 × 1010
Coefficient of variation (CV)0.003006657
Kurtosis-0.39353743
Mean2.016707 × 1013
Median Absolute Deviation (MAD)2.029599 × 1010
Skewness-1.0080625
Sum2.2788789 × 1015
Variance3.6766594 × 1021
MonotonicityNot monotonic
2024-04-18T02:50:58.540880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210630164141 2
 
1.8%
20220620115347 1
 
0.9%
20210804132700 1
 
0.9%
20130704152241 1
 
0.9%
20211215195846 1
 
0.9%
20210310143619 1
 
0.9%
20200831092337 1
 
0.9%
20200826163805 1
 
0.9%
20200210102155 1
 
0.9%
20201015105531 1
 
0.9%
Other values (102) 102
90.3%
ValueCountFrequency (%)
20020406094947 1
0.9%
20020520131540 1
0.9%
20020712100956 1
0.9%
20020712101202 1
0.9%
20040514164400 1
0.9%
20050530102047 1
0.9%
20060724141503 1
0.9%
20061228155639 1
0.9%
20061228155805 1
0.9%
20061228161650 1
0.9%
ValueCountFrequency (%)
20220824091156 1
0.9%
20220808141928 1
0.9%
20220729093656 1
0.9%
20220729093527 1
0.9%
20220712163059 1
0.9%
20220630174547 1
0.9%
20220620115534 1
0.9%
20220620115347 1
0.9%
20220613155829 1
0.9%
20220613130215 1
0.9%
Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
U
70 
I
43 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 70
61.9%
I 43
38.1%

Length

2024-04-18T02:50:58.639615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:50:58.707690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 70
61.9%
i 43
38.1%
Distinct45
Distinct (%)39.8%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2018-08-31 23:59:59.0
42 
2021-07-02 02:40:00.0
2020-02-12 02:40:00.0
2020-02-05 02:40:00.0
 
4
2021-08-20 02:40:00.0
 
3
Other values (40)
52 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique29 ?
Unique (%)25.7%

Sample

1st row2022-06-22 02:40:00.0
2nd row2022-07-31 02:40:00.0
3rd row2022-07-31 02:40:00.0
4th row2021-10-31 02:40:00.0
5th row2022-06-22 02:40:00.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 42
37.2%
2021-07-02 02:40:00.0 6
 
5.3%
2020-02-12 02:40:00.0 6
 
5.3%
2020-02-05 02:40:00.0 4
 
3.5%
2021-08-20 02:40:00.0 3
 
2.7%
2021-08-06 02:40:00.0 3
 
2.7%
2020-10-17 02:40:00.0 2
 
1.8%
2021-12-17 02:40:00.0 2
 
1.8%
2022-05-27 02:40:00.0 2
 
1.8%
2022-07-31 02:40:00.0 2
 
1.8%
Other values (35) 41
36.3%

Length

2024-04-18T02:50:58.779126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
02:40:00.0 70
31.0%
2018-08-31 42
18.6%
23:59:59.0 42
18.6%
2021-07-02 6
 
2.7%
2020-02-12 6
 
2.7%
2020-02-05 4
 
1.8%
2021-08-20 3
 
1.3%
2021-08-06 3
 
1.3%
2022-06-16 2
 
0.9%
2021-01-01 2
 
0.9%
Other values (38) 46
20.4%

업태구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
<NA>
94 
분뇨 처리업
16 
하수처리, 폐기물처리 및 청소관련 서비스업
 
2
하수, 폐수 및 분뇨 처리업
 
1

Length

Max length23
Median length4
Mean length4.7168142
Min length4

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 94
83.2%
분뇨 처리업 16
 
14.2%
하수처리, 폐기물처리 및 청소관련 서비스업 2
 
1.8%
하수, 폐수 및 분뇨 처리업 1
 
0.9%

Length

2024-04-18T02:50:58.869644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:50:58.948638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 94
66.7%
분뇨 17
 
12.1%
처리업 17
 
12.1%
3
 
2.1%
하수처리 2
 
1.4%
폐기물처리 2
 
1.4%
청소관련 2
 
1.4%
서비스업 2
 
1.4%
하수 1
 
0.7%
폐수 1
 
0.7%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)23.0%
Missing13
Missing (%)11.5%
Infinite0
Infinite (%)0.0%
Mean341913.33
Minimum331454.6
Maximum350029.79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-18T02:50:59.027667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum331454.6
5-th percentile335412.29
Q1340089.81
median342734.97
Q3345657.45
95-th percentile346245.59
Maximum350029.79
Range18575.186
Interquartile range (IQR)5567.6384

Descriptive statistics

Standard deviation3388.6792
Coefficient of variation (CV)0.0099109304
Kurtosis0.59791857
Mean341913.33
Median Absolute Deviation (MAD)2645.1605
Skewness-0.46949965
Sum34191333
Variance11483147
MonotonicityNot monotonic
2024-04-18T02:50:59.117452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
340307.732389 17
15.0%
342739.079007 12
10.6%
340089.810411 11
9.7%
345657.448776 11
9.7%
346167.636957 6
 
5.3%
343080.677255 6
 
5.3%
335412.290298 5
 
4.4%
346245.585557 5
 
4.4%
343098.263297 5
 
4.4%
346750.246549 3
 
2.7%
Other values (13) 19
16.8%
(Missing) 13
11.5%
ValueCountFrequency (%)
331454.600278 1
 
0.9%
331770.735791 1
 
0.9%
335412.290298 5
4.4%
337160.204416 2
 
1.8%
337827.110178 2
 
1.8%
339184.114832 1
 
0.9%
339813.06123 1
 
0.9%
339814.124909 2
 
1.8%
339862.5926 1
 
0.9%
340089.810411 11
9.7%
ValueCountFrequency (%)
350029.786653 1
 
0.9%
346750.246549 3
 
2.7%
346245.585557 5
4.4%
346167.636957 6
5.3%
345657.448776 11
9.7%
343476.576909 1
 
0.9%
343098.263297 5
4.4%
343080.677255 6
5.3%
342739.079007 12
10.6%
342730.862748 1
 
0.9%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)23.0%
Missing13
Missing (%)11.5%
Infinite0
Infinite (%)0.0%
Mean263813.53
Minimum255218.28
Maximum272453.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-18T02:50:59.207137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum255218.28
5-th percentile257110.44
Q1261793.62
median265104.44
Q3265678.94
95-th percentile265798.93
Maximum272453.41
Range17235.137
Interquartile range (IQR)3885.3235

Descriptive statistics

Standard deviation3147.3248
Coefficient of variation (CV)0.011930111
Kurtosis1.117897
Mean263813.53
Median Absolute Deviation (MAD)681.22511
Skewness-0.3347576
Sum26381353
Variance9905653.1
MonotonicityNot monotonic
2024-04-18T02:50:59.295230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
265104.435004 17
15.0%
265678.944992 12
10.6%
261793.621496 11
9.7%
265785.660112 11
9.7%
265739.32165 6
 
5.3%
262945.79611 6
 
5.3%
257110.442035 5
 
4.4%
261953.805328 5
 
4.4%
265308.377976 5
 
4.4%
260720.749614 3
 
2.7%
Other values (13) 19
16.8%
(Missing) 13
11.5%
ValueCountFrequency (%)
255218.275233 1
 
0.9%
257110.442035 5
4.4%
257769.378672 2
 
1.8%
258012.944248 2
 
1.8%
259818.860026 1
 
0.9%
260720.749614 3
 
2.7%
260861.595372 2
 
1.8%
261690.581987 1
 
0.9%
261793.621496 11
9.7%
261953.805328 5
4.4%
ValueCountFrequency (%)
272453.412525 1
 
0.9%
272173.966766 2
 
1.8%
269717.035024 1
 
0.9%
266051.129335 1
 
0.9%
265785.660112 11
9.7%
265739.32165 6
 
5.3%
265678.944992 12
10.6%
265613.947043 1
 
0.9%
265308.377976 5
 
4.4%
265104.435004 17
15.0%

환경업무구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
분뇨등관련영업관리
113 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
분뇨등관련영업관리 113
100.0%

Length

2024-04-18T02:50:59.389257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:50:59.455460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분뇨등관련영업관리 113
100.0%

업종구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
<NA>
94 
분뇨 처리업
16 
하수처리, 폐기물처리 및 청소관련 서비스업
 
2
하수, 폐수 및 분뇨 처리업
 
1

Length

Max length23
Median length4
Mean length4.7168142
Min length4

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 94
83.2%
분뇨 처리업 16
 
14.2%
하수처리, 폐기물처리 및 청소관련 서비스업 2
 
1.8%
하수, 폐수 및 분뇨 처리업 1
 
0.9%

Length

2024-04-18T02:50:59.534907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:50:59.615588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 94
66.7%
분뇨 17
 
12.1%
처리업 17
 
12.1%
3
 
2.1%
하수처리 2
 
1.4%
폐기물처리 2
 
1.4%
청소관련 2
 
1.4%
서비스업 2
 
1.4%
하수 1
 
0.7%
폐수 1
 
0.7%

종별명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing113
Missing (%)100.0%
Memory size1.1 KiB

주생산품명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing113
Missing (%)100.0%
Memory size1.1 KiB

배출시설조업시간
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing113
Missing (%)100.0%
Memory size1.1 KiB
Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
<NA>
82 
0
31 

Length

Max length4
Median length4
Mean length3.1769912
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 82
72.6%
0 31
 
27.4%

Length

2024-04-18T02:50:59.711353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:50:59.784816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 82
72.6%
0 31
 
27.4%

방지시설조업시간
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing113
Missing (%)100.0%
Memory size1.1 KiB
Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
<NA>
82 
0
31 

Length

Max length4
Median length4
Mean length3.1769912
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 82
72.6%
0 31
 
27.4%

Length

2024-04-18T02:50:59.859547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:50:59.937734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 82
72.6%
0 31
 
27.4%

사업자등록번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing113
Missing (%)100.0%
Memory size1.1 KiB

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명업종구분명종별명주생산품명배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수사업자등록번호
01분뇨수집운반업09_30_10_P341000034100005319950000119950222<NA>1영업/정상11영업<NA><NA><NA><NA>053-287-3000<NA><NA>대구광역시 중구 태평로3가 190-6대구광역시 중구 태평로 65-10, 3층 (태평로3가)41901(주)중성20220620115347U2022-06-22 02:40:00.0<NA>343098.263297265308.377976분뇨등관련영업관리<NA><NA><NA><NA>0<NA>0<NA>
12분뇨수집운반업09_30_10_P341000034100005319950000219950222<NA>1영업/정상11영업<NA><NA><NA><NA>053-565-0780<NA><NA>대구광역시 중구 태평로3가 190-6대구광역시 중구 태평로 65-10, 3층 (태평로3가)41901대우위생(주)20220729093527U2022-07-31 02:40:00.0<NA>343098.263297265308.377976분뇨등관련영업관리<NA><NA><NA><NA>0<NA>0<NA>
23분뇨수집운반업09_30_10_P341000034100005319990000519990423<NA>1영업/정상11영업<NA><NA><NA><NA>053-565-3637<NA><NA>대구광역시 중구 태평로3가 190-6대구광역시 중구 태평로 65-10, 3층 (태평로3가)41901중구정화(주)20220729093656U2022-07-31 02:40:00.0<NA>343098.263297265308.377976분뇨등관련영업관리<NA><NA><NA><NA>0<NA>0<NA>
34분뇨수집운반업09_30_10_P341000034100005319950000419950222<NA>1영업/정상11영업<NA><NA><NA><NA>053-565-0115<NA><NA>대구광역시 중구 태평로3가 190-6대구광역시 중구 태평로 65-10, 3층 (태평로3가)41901원진위생(주)20211029101523U2021-10-31 02:40:00.0<NA>343098.263297265308.377976분뇨등관련영업관리<NA><NA><NA><NA>0<NA>0<NA>
45분뇨수집운반업09_30_10_P341000034100005319950000319950222<NA>1영업/정상11영업<NA><NA><NA><NA>053-565-0116<NA><NA>대구광역시 중구 태평로3가 190-6대구광역시 중구 태평로 65-10, 3층 (태평로3가)41901한일청화(주)20220620115534U2022-06-22 02:40:00.0<NA>343098.263297265308.377976분뇨등관련영업관리<NA><NA><NA><NA>0<NA>0<NA>
56분뇨수집운반업09_30_10_P342000034200005300000000219930119<NA>1영업/정상11영업<NA><NA><NA><NA>05309513400<NA><NA>대구광역시 동구 신암동 804-5 3층대구광역시 동구 대현로 137, 3층 (신암동)41196현대위생(주)20210630164141U2021-07-02 02:40:00.0분뇨 처리업345657.448776265785.660112분뇨등관련영업관리분뇨 처리업<NA><NA><NA><NA><NA><NA><NA>
67분뇨수집운반업09_30_10_P342000034200005300000000519981114<NA>1영업/정상11영업<NA><NA><NA><NA>053 9410333<NA><NA>대구광역시 동구 신암동 804-5 3층대구광역시 동구 대현로 137, 3층 (신암동)41196동구정화조(주)20210818164201U2021-08-20 02:40:00.0<NA>345657.448776265785.660112분뇨등관련영업관리<NA><NA><NA><NA>0<NA>0<NA>
78분뇨수집운반업09_30_10_P342000034200005300000001720000308<NA>1영업/정상11영업<NA><NA><NA><NA>053 9419296<NA><NA>대구광역시 동구 신암동 804-5 3층대구광역시 동구 대현로 137, 3층 (신암동)41196우방환경20210907164321U2021-09-09 02:40:00.0<NA>345657.448776265785.660112분뇨등관련영업관리<NA><NA><NA><NA>0<NA>0<NA>
89분뇨수집운반업09_30_10_P342000034200005320190000120190807<NA>3폐업2폐업20190807<NA><NA><NA>053 9441874<NA>701815대구광역시 동구 신암동 211대구광역시 동구 아양로8길 11 (신암동)<NA>(주)안심위생크리닉20191113151527U2019-11-15 02:40:00.0<NA>346167.636957265739.32165분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA><NA>
910분뇨수집운반업09_30_10_P342000034200005300000000419941012<NA>3폐업2폐업20100203<NA><NA><NA>053 7410010<NA>701815대구광역시 동구 신암동 211대구광역시 동구 아양로8길 11 (신암동)<NA>동구위생사20100322115234I2018-08-31 23:59:59.0<NA>346167.636957265739.32165분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA><NA>
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