Overview

Dataset statistics

Number of variables33
Number of observations9765
Missing cells92538
Missing cells (%)28.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 MiB
Average record size in memory283.0 B

Variable types

Numeric13
Categorical9
Text6
Unsupported4
DateTime1

Dataset

Description6270000_대구광역시_09_30_13_P_쓰레기종량제봉투판매업_9월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000090915&dataSetDetailId=DDI_0000090978&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스ID has constant value ""Constant
항목값1 has constant value ""Constant
영업상태구분코드 is highly imbalanced (55.0%)Imbalance
영업상태명 is highly imbalanced (55.0%)Imbalance
상세영업상태명 is highly imbalanced (64.7%)Imbalance
휴업종료일자 is highly imbalanced (99.8%)Imbalance
데이터갱신구분 is highly imbalanced (66.1%)Imbalance
인허가일자 has 2722 (27.9%) missing valuesMissing
인허가취소일자 has 9765 (100.0%) missing valuesMissing
폐업일자 has 6856 (70.2%) missing valuesMissing
휴업시작일자 has 7348 (75.2%) missing valuesMissing
재개업일자 has 9765 (100.0%) missing valuesMissing
소재지전화 has 3812 (39.0%) missing valuesMissing
소재지면적 has 9765 (100.0%) missing valuesMissing
소재지우편번호 has 1289 (13.2%) missing valuesMissing
소재지전체주소 has 334 (3.4%) missing valuesMissing
도로명전체주소 has 4639 (47.5%) missing valuesMissing
도로명우편번호 has 6009 (61.5%) missing valuesMissing
업태구분명 has 9765 (100.0%) missing valuesMissing
좌표정보(X) has 3856 (39.5%) missing valuesMissing
좌표정보(Y) has 3856 (39.5%) missing valuesMissing
소재지 has 2843 (29.1%) missing valuesMissing
지정일자 has 6085 (62.3%) missing valuesMissing
신청일자 has 3829 (39.2%) missing valuesMissing
소재지우편번호 is highly skewed (γ1 = -60.72246755)Skewed
신청일자 is highly skewed (γ1 = -42.97493484)Skewed
번호 has unique valuesUnique
관리번호 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
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-20 18:23:35.414186
Analysis finished2024-04-20 18:23:38.192919
Duration2.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct9765
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4883
Minimum1
Maximum9765
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size86.0 KiB
2024-04-21T03:23:38.393738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile489.2
Q12442
median4883
Q37324
95-th percentile9276.8
Maximum9765
Range9764
Interquartile range (IQR)4882

Descriptive statistics

Standard deviation2819.057
Coefficient of variation (CV)0.57732071
Kurtosis-1.2
Mean4883
Median Absolute Deviation (MAD)2441
Skewness0
Sum47682495
Variance7947082.5
MonotonicityStrictly increasing
2024-04-21T03:23:38.826546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
6514 1
 
< 0.1%
6507 1
 
< 0.1%
6508 1
 
< 0.1%
6509 1
 
< 0.1%
6510 1
 
< 0.1%
6511 1
 
< 0.1%
6512 1
 
< 0.1%
6513 1
 
< 0.1%
6515 1
 
< 0.1%
Other values (9755) 9755
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
9765 1
< 0.1%
9764 1
< 0.1%
9763 1
< 0.1%
9762 1
< 0.1%
9761 1
< 0.1%
9760 1
< 0.1%
9759 1
< 0.1%
9758 1
< 0.1%
9757 1
< 0.1%
9756 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size76.4 KiB
쓰레기종량제봉투판매업
9765 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
쓰레기종량제봉투판매업 9765
100.0%

Length

2024-04-21T03:23:39.115395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:23:39.370934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
쓰레기종량제봉투판매업 9765
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size76.4 KiB
09_30_13_P
9765 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09_30_13_P
2nd row09_30_13_P
3rd row09_30_13_P
4th row09_30_13_P
5th row09_30_13_P

Common Values

ValueCountFrequency (%)
09_30_13_P 9765
100.0%

Length

2024-04-21T03:23:39.675103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:23:39.955790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_30_13_p 9765
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3447959
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size86.0 KiB
2024-04-21T03:23:40.216553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3410000
Q13430000
median3450000
Q33470000
95-th percentile3470000
Maximum3480000
Range70000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation21360.965
Coefficient of variation (CV)0.0061952491
Kurtosis-1.3252417
Mean3447959
Median Absolute Deviation (MAD)20000
Skewness-0.32821521
Sum3.366932 × 1010
Variance4.5629082 × 108
MonotonicityIncreasing
2024-04-21T03:23:40.593759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3470000 2894
29.6%
3420000 1618
16.6%
3450000 1437
14.7%
3460000 1272
13.0%
3430000 1143
 
11.7%
3410000 600
 
6.1%
3440000 479
 
4.9%
3480000 322
 
3.3%
ValueCountFrequency (%)
3410000 600
 
6.1%
3420000 1618
16.6%
3430000 1143
 
11.7%
3440000 479
 
4.9%
3450000 1437
14.7%
3460000 1272
13.0%
3470000 2894
29.6%
3480000 322
 
3.3%
ValueCountFrequency (%)
3480000 322
 
3.3%
3470000 2894
29.6%
3460000 1272
13.0%
3450000 1437
14.7%
3440000 479
 
4.9%
3430000 1143
 
11.7%
3420000 1618
16.6%
3410000 600
 
6.1%

관리번호
Text

UNIQUE 

Distinct9765
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size76.4 KiB
2024-04-21T03:23:41.321164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters175770
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

Unique9765 ?
Unique (%)100.0%

Sample

1st row341000014200001113
2nd row341000014200001114
3rd row341000014200001106
4th row341000014200001105
5th row341000014200001207
ValueCountFrequency (%)
341000014200001113 1
 
< 0.1%
346000014200200041 1
 
< 0.1%
346000014200120342 1
 
< 0.1%
346000014200120341 1
 
< 0.1%
346000014200120360 1
 
< 0.1%
346000014200120361 1
 
< 0.1%
346000014200120363 1
 
< 0.1%
346000014200120365 1
 
< 0.1%
346000014200120366 1
 
< 0.1%
346000014200200042 1
 
< 0.1%
Other values (9755) 9755
99.9%
2024-04-21T03:23:42.408347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 81216
46.2%
4 23979
 
13.6%
1 19786
 
11.3%
2 16832
 
9.6%
3 14600
 
8.3%
7 5392
 
3.1%
5 4681
 
2.7%
6 4096
 
2.3%
9 2640
 
1.5%
8 2546
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 175768
> 99.9%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 81216
46.2%
4 23979
 
13.6%
1 19786
 
11.3%
2 16832
 
9.6%
3 14600
 
8.3%
7 5392
 
3.1%
5 4681
 
2.7%
6 4096
 
2.3%
9 2640
 
1.5%
8 2546
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 175770
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 81216
46.2%
4 23979
 
13.6%
1 19786
 
11.3%
2 16832
 
9.6%
3 14600
 
8.3%
7 5392
 
3.1%
5 4681
 
2.7%
6 4096
 
2.3%
9 2640
 
1.5%
8 2546
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 175770
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 81216
46.2%
4 23979
 
13.6%
1 19786
 
11.3%
2 16832
 
9.6%
3 14600
 
8.3%
7 5392
 
3.1%
5 4681
 
2.7%
6 4096
 
2.3%
9 2640
 
1.5%
8 2546
 
1.4%

인허가일자
Real number (ℝ)

MISSING 

Distinct3040
Distinct (%)43.2%
Missing2722
Missing (%)27.9%
Infinite0
Infinite (%)0.0%
Mean20017330
Minimum96
Maximum20210830
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size86.0 KiB
2024-04-21T03:23:42.699584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum96
5-th percentile19950104
Q120021206
median20070704
Q320120214
95-th percentile20180629
Maximum20210830
Range20210734
Interquartile range (IQR)99008

Descriptive statistics

Standard deviation1060836.8
Coefficient of variation (CV)0.052995919
Kurtosis344.60531
Mean20017330
Median Absolute Deviation (MAD)49510
Skewness-18.576833
Sum1.4098206 × 1011
Variance1.1253747 × 1012
MonotonicityNot monotonic
2024-04-21T03:23:43.079616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20120105 176
 
1.8%
19950104 129
 
1.3%
20120106 122
 
1.2%
19950103 121
 
1.2%
20120102 118
 
1.2%
20120214 97
 
1.0%
20120108 93
 
1.0%
19950105 73
 
0.7%
20081231 70
 
0.7%
19941226 38
 
0.4%
Other values (3030) 6006
61.5%
(Missing) 2722
27.9%
ValueCountFrequency (%)
96 1
 
< 0.1%
2014 1
 
< 0.1%
199411 8
0.1%
199501 2
 
< 0.1%
199508 1
 
< 0.1%
199707 1
 
< 0.1%
199804 1
 
< 0.1%
199807 1
 
< 0.1%
199903 1
 
< 0.1%
199912 1
 
< 0.1%
ValueCountFrequency (%)
20210830 1
< 0.1%
20210826 1
< 0.1%
20210825 1
< 0.1%
20210818 1
< 0.1%
20210812 1
< 0.1%
20210730 1
< 0.1%
20210727 1
< 0.1%
20210715 1
< 0.1%
20210708 1
< 0.1%
20210701 1
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9765
Missing (%)100.0%
Memory size86.0 KiB

영업상태구분코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size76.4 KiB
1
6854 
3
2889 
4
 
20
2
 
2

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 6854
70.2%
3 2889
29.6%
4 20
 
0.2%
2 2
 
< 0.1%

Length

2024-04-21T03:23:43.389222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:23:43.585773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 6854
70.2%
3 2889
29.6%
4 20
 
0.2%
2 2
 
< 0.1%

영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size76.4 KiB
영업/정상
6854 
폐업
2889 
취소/말소/만료/정지/중지
 
20
휴업
 
2

Length

Max length14
Median length5
Mean length4.1302611
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 6854
70.2%
폐업 2889
29.6%
취소/말소/만료/정지/중지 20
 
0.2%
휴업 2
 
< 0.1%

Length

2024-04-21T03:23:43.774450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:23:43.952221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 6854
70.2%
폐업 2889
29.6%
취소/말소/만료/정지/중지 20
 
0.2%
휴업 2
 
< 0.1%

상세영업상태코드
Real number (ℝ)

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.3094726
Minimum0
Maximum11
Zeros8
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size86.0 KiB
2024-04-21T03:23:44.111997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q12
median11
Q311
95-th percentile11
Maximum11
Range11
Interquartile range (IQR)9

Descriptive statistics

Standard deviation4.1190395
Coefficient of variation (CV)0.49570408
Kurtosis-1.224395
Mean8.3094726
Median Absolute Deviation (MAD)0
Skewness-0.87917204
Sum81142
Variance16.966486
MonotonicityNot monotonic
2024-04-21T03:23:44.295481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
11 6843
70.1%
2 2889
29.6%
4 20
 
0.2%
0 8
 
0.1%
3 3
 
< 0.1%
1 2
 
< 0.1%
ValueCountFrequency (%)
0 8
 
0.1%
1 2
 
< 0.1%
2 2889
29.6%
3 3
 
< 0.1%
4 20
 
0.2%
11 6843
70.1%
ValueCountFrequency (%)
11 6843
70.1%
4 20
 
0.2%
3 3
 
< 0.1%
2 2889
29.6%
1 2
 
< 0.1%
0 8
 
0.1%

상세영업상태명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size76.4 KiB
영업
6843 
폐업
2889 
폐쇄
 
20
<NA>
 
8
재개업
 
3

Length

Max length4
Median length2
Mean length2.0019457
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 6843
70.1%
폐업 2889
29.6%
폐쇄 20
 
0.2%
<NA> 8
 
0.1%
재개업 3
 
< 0.1%
휴업 2
 
< 0.1%

Length

2024-04-21T03:23:44.522426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:23:44.722453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 6843
70.1%
폐업 2889
29.6%
폐쇄 20
 
0.2%
na 8
 
0.1%
재개업 3
 
< 0.1%
휴업 2
 
< 0.1%

폐업일자
Real number (ℝ)

MISSING 

Distinct1140
Distinct (%)39.2%
Missing6856
Missing (%)70.2%
Infinite0
Infinite (%)0.0%
Mean20123603
Minimum20000805
Maximum20210830
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size86.0 KiB
2024-04-21T03:23:44.944616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000805
5-th percentile20020409
Q120100513
median20131202
Q320151229
95-th percentile20190603
Maximum20210830
Range210025
Interquartile range (IQR)50716

Descriptive statistics

Standard deviation49156.915
Coefficient of variation (CV)0.0024427492
Kurtosis0.15209679
Mean20123603
Median Absolute Deviation (MAD)21076
Skewness-0.69572593
Sum5.8539561 × 1010
Variance2.4164023 × 109
MonotonicityNot monotonic
2024-04-21T03:23:45.191613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20131202 386
 
4.0%
20121231 137
 
1.4%
20090828 98
 
1.0%
20020409 97
 
1.0%
20190326 86
 
0.9%
20151231 67
 
0.7%
20131231 50
 
0.5%
20020321 29
 
0.3%
20210625 25
 
0.3%
20081231 24
 
0.2%
Other values (1130) 1910
 
19.6%
(Missing) 6856
70.2%
ValueCountFrequency (%)
20000805 1
< 0.1%
20000928 1
< 0.1%
20001104 1
< 0.1%
20001130 1
< 0.1%
20001220 1
< 0.1%
20001224 1
< 0.1%
20001231 1
< 0.1%
20010220 1
< 0.1%
20010418 2
< 0.1%
20010427 1
< 0.1%
ValueCountFrequency (%)
20210830 1
 
< 0.1%
20210820 1
 
< 0.1%
20210817 1
 
< 0.1%
20210803 1
 
< 0.1%
20210722 1
 
< 0.1%
20210716 6
0.1%
20210713 1
 
< 0.1%
20210708 1
 
< 0.1%
20210707 9
0.1%
20210701 1
 
< 0.1%

휴업시작일자
Real number (ℝ)

MISSING 

Distinct960
Distinct (%)39.7%
Missing7348
Missing (%)75.2%
Infinite0
Infinite (%)0.0%
Mean20134068
Minimum20001231
Maximum20200310
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size86.0 KiB
2024-04-21T03:23:45.474916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20001231
5-th percentile20081225
Q120120605
median20131202
Q320151229
95-th percentile20190326
Maximum20200310
Range199079
Interquartile range (IQR)30624

Descriptive statistics

Standard deviation29633.949
Coefficient of variation (CV)0.0014718312
Kurtosis-0.19732973
Mean20134068
Median Absolute Deviation (MAD)19424
Skewness-0.093974671
Sum4.8664042 × 1010
Variance8.7817094 × 108
MonotonicityNot monotonic
2024-04-21T03:23:45.944089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20131202 386
 
4.0%
20121231 136
 
1.4%
20090828 99
 
1.0%
20190326 86
 
0.9%
20151231 67
 
0.7%
20131231 50
 
0.5%
20081231 24
 
0.2%
20130102 23
 
0.2%
20140512 22
 
0.2%
20140527 22
 
0.2%
Other values (950) 1502
 
15.4%
(Missing) 7348
75.2%
ValueCountFrequency (%)
20001231 1
< 0.1%
20050628 1
< 0.1%
20060823 1
< 0.1%
20061002 1
< 0.1%
20061013 2
< 0.1%
20061031 1
< 0.1%
20061102 1
< 0.1%
20061109 1
< 0.1%
20061113 1
< 0.1%
20061128 1
< 0.1%
ValueCountFrequency (%)
20200310 1
< 0.1%
20191218 1
< 0.1%
20191118 1
< 0.1%
20191028 1
< 0.1%
20191024 1
< 0.1%
20191021 2
< 0.1%
20190905 1
< 0.1%
20190730 1
< 0.1%
20190626 1
< 0.1%
20190625 2
< 0.1%

휴업종료일자
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size76.4 KiB
<NA>
9762 
20160701
 
1
20170101
 
1
20210412
 
1

Length

Max length8
Median length4
Mean length4.0012289
Min length4

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9762
> 99.9%
20160701 1
 
< 0.1%
20170101 1
 
< 0.1%
20210412 1
 
< 0.1%

Length

2024-04-21T03:23:46.407441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:23:46.742376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9762
> 99.9%
20160701 1
 
< 0.1%
20170101 1
 
< 0.1%
20210412 1
 
< 0.1%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9765
Missing (%)100.0%
Memory size86.0 KiB

소재지전화
Text

MISSING 

Distinct5577
Distinct (%)93.7%
Missing3812
Missing (%)39.0%
Memory size76.4 KiB
2024-04-21T03:23:47.703475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length9.8565429
Min length3

Characters and Unicode

Total characters58676
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5251 ?
Unique (%)88.2%

Sample

1st row053 256 7567
2nd row053 422 1252
3rd row053 254 9879
4th row053 254 9039
5th row053 2562969
ValueCountFrequency (%)
053 1850
 
20.9%
472 38
 
0.4%
471 35
 
0.4%
473 33
 
0.4%
624 32
 
0.4%
627 28
 
0.3%
622 27
 
0.3%
621 24
 
0.3%
628 23
 
0.3%
652 23
 
0.3%
Other values (5675) 6719
76.1%
2024-04-21T03:23:48.818987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 10793
18.4%
3 9030
15.4%
0 7457
12.7%
6 5236
8.9%
2 4722
8.0%
9 3731
 
6.4%
1 3635
 
6.2%
8 3524
 
6.0%
4 3520
 
6.0%
7 3334
 
5.7%
Other values (4) 3694
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 54982
93.7%
Space Separator 2967
 
5.1%
Dash Punctuation 724
 
1.2%
Other Punctuation 2
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 10793
19.6%
3 9030
16.4%
0 7457
13.6%
6 5236
9.5%
2 4722
8.6%
9 3731
 
6.8%
1 3635
 
6.6%
8 3524
 
6.4%
4 3520
 
6.4%
7 3334
 
6.1%
Space Separator
ValueCountFrequency (%)
2967
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 724
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 58676
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 10793
18.4%
3 9030
15.4%
0 7457
12.7%
6 5236
8.9%
2 4722
8.0%
9 3731
 
6.4%
1 3635
 
6.2%
8 3524
 
6.0%
4 3520
 
6.0%
7 3334
 
5.7%
Other values (4) 3694
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58676
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 10793
18.4%
3 9030
15.4%
0 7457
12.7%
6 5236
8.9%
2 4722
8.0%
9 3731
 
6.4%
1 3635
 
6.2%
8 3524
 
6.0%
4 3520
 
6.0%
7 3334
 
5.7%
Other values (4) 3694
 
6.3%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9765
Missing (%)100.0%
Memory size86.0 KiB

소재지우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct799
Distinct (%)9.4%
Missing1289
Missing (%)13.2%
Infinite0
Infinite (%)0.0%
Mean703757.91
Minimum3
Maximum711873
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size86.0 KiB
2024-04-21T03:23:49.063203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile700815
Q1702297.5
median704120
Q3704953
95-th percentile706836
Maximum711873
Range711870
Interquartile range (IQR)2655.5

Descriptive statistics

Standard deviation10023.387
Coefficient of variation (CV)0.014242663
Kurtosis3965.6848
Mean703757.91
Median Absolute Deviation (MAD)1272
Skewness-60.722468
Sum5.965052 × 109
Variance1.0046828 × 108
MonotonicityNot monotonic
2024-04-21T03:23:49.550054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
706010 193
 
2.0%
706020 129
 
1.3%
706090 102
 
1.0%
701120 92
 
0.9%
703014 84
 
0.9%
701011 76
 
0.8%
701031 74
 
0.8%
706040 74
 
0.8%
703042 73
 
0.7%
701020 69
 
0.7%
Other values (789) 7510
76.9%
(Missing) 1289
 
13.2%
ValueCountFrequency (%)
3 1
 
< 0.1%
150095 1
 
< 0.1%
700010 8
 
0.1%
700020 3
 
< 0.1%
700030 2
 
< 0.1%
700050 3
 
< 0.1%
700060 4
 
< 0.1%
700070 6
 
0.1%
700081 61
0.6%
700082 1
 
< 0.1%
ValueCountFrequency (%)
711873 1
 
< 0.1%
711870 44
0.5%
711863 1
 
< 0.1%
711860 16
 
0.2%
711855 53
0.5%
711854 2
 
< 0.1%
711852 1
 
< 0.1%
711850 14
 
0.1%
711845 2
 
< 0.1%
711840 52
0.5%

소재지전체주소
Text

MISSING 

Distinct7686
Distinct (%)81.5%
Missing334
Missing (%)3.4%
Memory size76.4 KiB
2024-04-21T03:23:51.136981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length46
Mean length23.486163
Min length13

Characters and Unicode

Total characters221498
Distinct characters375
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6475 ?
Unique (%)68.7%

Sample

1st row대구광역시 중구 대봉동 186-1번지
2nd row대구광역시 중구 대봉동 18-4번지
3rd row대구광역시 중구 대봉동 55-95번지
4th row대구광역시 중구 대봉동 111-1번지
5th row대구광역시 중구 대봉동 590-281번지
ValueCountFrequency (%)
대구광역시 9427
22.4%
달서구 2753
 
6.5%
번지 1925
 
4.6%
동구 1531
 
3.6%
북구 1306
 
3.1%
수성구 1273
 
3.0%
서구 1148
 
2.7%
중구 600
 
1.4%
남구 484
 
1.2%
평리동 385
 
0.9%
Other values (7774) 21212
50.5%
2024-04-21T03:23:53.133121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44440
20.1%
18666
 
8.4%
11216
 
5.1%
1 10565
 
4.8%
10171
 
4.6%
9520
 
4.3%
9517
 
4.3%
9448
 
4.3%
9443
 
4.3%
9071
 
4.1%
Other values (365) 79441
35.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 124961
56.4%
Space Separator 44440
 
20.1%
Decimal Number 44340
 
20.0%
Dash Punctuation 7605
 
3.4%
Other Punctuation 71
 
< 0.1%
Uppercase Letter 56
 
< 0.1%
Math Symbol 8
 
< 0.1%
Lowercase Letter 8
 
< 0.1%
Close Punctuation 4
 
< 0.1%
Open Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
18666
14.9%
11216
 
9.0%
10171
 
8.1%
9520
 
7.6%
9517
 
7.6%
9448
 
7.6%
9443
 
7.6%
9071
 
7.3%
4153
 
3.3%
3116
 
2.5%
Other values (328) 30640
24.5%
Uppercase Letter
ValueCountFrequency (%)
B 17
30.4%
A 6
 
10.7%
S 6
 
10.7%
L 6
 
10.7%
C 4
 
7.1%
I 4
 
7.1%
H 4
 
7.1%
W 3
 
5.4%
E 2
 
3.6%
K 1
 
1.8%
Other values (3) 3
 
5.4%
Decimal Number
ValueCountFrequency (%)
1 10565
23.8%
2 5442
12.3%
3 4452
10.0%
0 3989
 
9.0%
4 3989
 
9.0%
5 3549
 
8.0%
6 3241
 
7.3%
7 3192
 
7.2%
9 2969
 
6.7%
8 2952
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 39
54.9%
/ 18
25.4%
@ 7
 
9.9%
. 7
 
9.9%
Lowercase Letter
ValueCountFrequency (%)
e 5
62.5%
b 1
 
12.5%
h 1
 
12.5%
c 1
 
12.5%
Space Separator
ValueCountFrequency (%)
44440
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7605
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 124961
56.4%
Common 96473
43.6%
Latin 64
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
18666
14.9%
11216
 
9.0%
10171
 
8.1%
9520
 
7.6%
9517
 
7.6%
9448
 
7.6%
9443
 
7.6%
9071
 
7.3%
4153
 
3.3%
3116
 
2.5%
Other values (328) 30640
24.5%
Common
ValueCountFrequency (%)
44440
46.1%
1 10565
 
11.0%
- 7605
 
7.9%
2 5442
 
5.6%
3 4452
 
4.6%
0 3989
 
4.1%
4 3989
 
4.1%
5 3549
 
3.7%
6 3241
 
3.4%
7 3192
 
3.3%
Other values (10) 6009
 
6.2%
Latin
ValueCountFrequency (%)
B 17
26.6%
A 6
 
9.4%
S 6
 
9.4%
L 6
 
9.4%
e 5
 
7.8%
C 4
 
6.2%
I 4
 
6.2%
H 4
 
6.2%
W 3
 
4.7%
E 2
 
3.1%
Other values (7) 7
10.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 124961
56.4%
ASCII 96537
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44440
46.0%
1 10565
 
10.9%
- 7605
 
7.9%
2 5442
 
5.6%
3 4452
 
4.6%
0 3989
 
4.1%
4 3989
 
4.1%
5 3549
 
3.7%
6 3241
 
3.4%
7 3192
 
3.3%
Other values (27) 6073
 
6.3%
Hangul
ValueCountFrequency (%)
18666
14.9%
11216
 
9.0%
10171
 
8.1%
9520
 
7.6%
9517
 
7.6%
9448
 
7.6%
9443
 
7.6%
9071
 
7.3%
4153
 
3.3%
3116
 
2.5%
Other values (328) 30640
24.5%

도로명전체주소
Text

MISSING 

Distinct4175
Distinct (%)81.4%
Missing4639
Missing (%)47.5%
Memory size76.4 KiB
2024-04-21T03:23:54.693683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length56
Mean length26.880609
Min length16

Characters and Unicode

Total characters137790
Distinct characters405
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3472 ?
Unique (%)67.7%

Sample

1st row대구광역시 중구 동덕로 6 (대봉동)
2nd row대구광역시 중구 동덕로14길 29 (대봉동)
3rd row대구광역시 중구 대봉로 236 (대봉동)
4th row대구광역시 중구 동덕로 33 (대봉동)
5th row대구광역시 중구 명륜로22안길 28 (대봉동)
ValueCountFrequency (%)
대구광역시 5122
 
18.5%
달서구 1909
 
6.9%
북구 1390
 
5.0%
동구 586
 
2.1%
서구 382
 
1.4%
중구 370
 
1.3%
1층 274
 
1.0%
수성구 269
 
1.0%
송현동 199
 
0.7%
상인동 191
 
0.7%
Other values (3358) 17027
61.4%
2024-04-21T03:23:56.584687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23739
 
17.2%
10731
 
7.8%
6875
 
5.0%
6289
 
4.6%
5202
 
3.8%
5147
 
3.7%
5136
 
3.7%
1 5118
 
3.7%
) 5030
 
3.7%
( 5029
 
3.6%
Other values (395) 59494
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 81180
58.9%
Space Separator 23739
 
17.2%
Decimal Number 20486
 
14.9%
Close Punctuation 5030
 
3.7%
Open Punctuation 5029
 
3.6%
Other Punctuation 1570
 
1.1%
Dash Punctuation 659
 
0.5%
Uppercase Letter 60
 
< 0.1%
Math Symbol 23
 
< 0.1%
Lowercase Letter 14
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10731
 
13.2%
6875
 
8.5%
6289
 
7.7%
5202
 
6.4%
5147
 
6.3%
5136
 
6.3%
4982
 
6.1%
2932
 
3.6%
2640
 
3.3%
2424
 
3.0%
Other values (351) 28822
35.5%
Uppercase Letter
ValueCountFrequency (%)
B 19
31.7%
A 9
15.0%
S 5
 
8.3%
I 4
 
6.7%
H 4
 
6.7%
C 4
 
6.7%
M 2
 
3.3%
D 2
 
3.3%
K 2
 
3.3%
L 2
 
3.3%
Other values (6) 7
 
11.7%
Decimal Number
ValueCountFrequency (%)
1 5118
25.0%
2 2908
14.2%
3 2320
11.3%
0 1974
 
9.6%
4 1699
 
8.3%
5 1639
 
8.0%
6 1373
 
6.7%
7 1335
 
6.5%
9 1075
 
5.2%
8 1045
 
5.1%
Lowercase Letter
ValueCountFrequency (%)
e 7
50.0%
m 1
 
7.1%
o 1
 
7.1%
p 1
 
7.1%
l 1
 
7.1%
u 1
 
7.1%
s 1
 
7.1%
h 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 1558
99.2%
/ 5
 
0.3%
. 3
 
0.2%
@ 2
 
0.1%
· 2
 
0.1%
Space Separator
ValueCountFrequency (%)
23739
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5030
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5029
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 659
100.0%
Math Symbol
ValueCountFrequency (%)
~ 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 81180
58.9%
Common 56536
41.0%
Latin 74
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10731
 
13.2%
6875
 
8.5%
6289
 
7.7%
5202
 
6.4%
5147
 
6.3%
5136
 
6.3%
4982
 
6.1%
2932
 
3.6%
2640
 
3.3%
2424
 
3.0%
Other values (351) 28822
35.5%
Latin
ValueCountFrequency (%)
B 19
25.7%
A 9
12.2%
e 7
 
9.5%
S 5
 
6.8%
I 4
 
5.4%
H 4
 
5.4%
C 4
 
5.4%
M 2
 
2.7%
D 2
 
2.7%
K 2
 
2.7%
Other values (14) 16
21.6%
Common
ValueCountFrequency (%)
23739
42.0%
1 5118
 
9.1%
) 5030
 
8.9%
( 5029
 
8.9%
2 2908
 
5.1%
3 2320
 
4.1%
0 1974
 
3.5%
4 1699
 
3.0%
5 1639
 
2.9%
, 1558
 
2.8%
Other values (10) 5522
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 81180
58.9%
ASCII 56608
41.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23739
41.9%
1 5118
 
9.0%
) 5030
 
8.9%
( 5029
 
8.9%
2 2908
 
5.1%
3 2320
 
4.1%
0 1974
 
3.5%
4 1699
 
3.0%
5 1639
 
2.9%
, 1558
 
2.8%
Other values (33) 5594
 
9.9%
Hangul
ValueCountFrequency (%)
10731
 
13.2%
6875
 
8.5%
6289
 
7.7%
5202
 
6.4%
5147
 
6.3%
5136
 
6.3%
4982
 
6.1%
2932
 
3.6%
2640
 
3.3%
2424
 
3.0%
Other values (351) 28822
35.5%
None
ValueCountFrequency (%)
· 2
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct900
Distinct (%)24.0%
Missing6009
Missing (%)61.5%
Infinite0
Infinite (%)0.0%
Mean527442.59
Minimum39037
Maximum711833
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size86.0 KiB
2024-04-21T03:23:56.979426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum39037
5-th percentile41487.75
Q142808.75
median702831
Q3704820
95-th percentile704936
Maximum711833
Range672796
Interquartile range (IQR)662011.25

Descriptive statistics

Standard deviation292341.52
Coefficient of variation (CV)0.55426225
Kurtosis-0.88075765
Mean527442.59
Median Absolute Deviation (MAD)2007
Skewness-1.0581122
Sum1.9810744 × 109
Variance8.5463562 × 1010
MonotonicityNot monotonic
2024-04-21T03:23:57.403557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
702886 41
 
0.4%
704914 30
 
0.3%
704915 30
 
0.3%
704834 29
 
0.3%
704910 29
 
0.3%
704827 29
 
0.3%
702894 25
 
0.3%
704837 25
 
0.3%
702863 24
 
0.2%
704817 24
 
0.2%
Other values (890) 3470
35.5%
(Missing) 6009
61.5%
ValueCountFrequency (%)
39037 1
 
< 0.1%
39852 1
 
< 0.1%
39855 1
 
< 0.1%
41156 2
< 0.1%
41192 1
 
< 0.1%
41400 2
< 0.1%
41401 3
< 0.1%
41402 3
< 0.1%
41403 1
 
< 0.1%
41405 2
< 0.1%
ValueCountFrequency (%)
711833 3
< 0.1%
711831 5
0.1%
705837 1
 
< 0.1%
705834 1
 
< 0.1%
705824 1
 
< 0.1%
705812 1
 
< 0.1%
705810 1
 
< 0.1%
705803 2
 
< 0.1%
705782 1
 
< 0.1%
705764 1
 
< 0.1%
Distinct6451
Distinct (%)66.1%
Missing0
Missing (%)0.0%
Memory size76.4 KiB
2024-04-21T03:23:58.412673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length6.1761393
Min length2

Characters and Unicode

Total characters60310
Distinct characters631
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5341 ?
Unique (%)54.7%

Sample

1st row유성주유소
2nd row은진슈퍼
3rd row대구코아
4th row청운슈퍼
5th row또와
ValueCountFrequency (%)
신우유통 226
 
2.0%
gs25 171
 
1.5%
씨유 155
 
1.4%
세븐일레븐 150
 
1.3%
홈마트 129
 
1.1%
훼미리마트 73
 
0.6%
대백마트 69
 
0.6%
코사마트 65
 
0.6%
원마트 60
 
0.5%
이마트24 60
 
0.5%
Other values (6281) 10269
89.9%
2024-04-21T03:23:59.654223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3367
 
5.6%
3347
 
5.5%
2639
 
4.4%
2388
 
4.0%
1813
 
3.0%
1793
 
3.0%
1670
 
2.8%
1337
 
2.2%
1152
 
1.9%
1013
 
1.7%
Other values (621) 39791
66.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 53474
88.7%
Decimal Number 1877
 
3.1%
Space Separator 1670
 
2.8%
Uppercase Letter 1536
 
2.5%
Close Punctuation 662
 
1.1%
Open Punctuation 662
 
1.1%
Lowercase Letter 206
 
0.3%
Other Punctuation 164
 
0.3%
Dash Punctuation 36
 
0.1%
Other Symbol 21
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3367
 
6.3%
3347
 
6.3%
2639
 
4.9%
2388
 
4.5%
1813
 
3.4%
1793
 
3.4%
1337
 
2.5%
1152
 
2.2%
1013
 
1.9%
903
 
1.7%
Other values (552) 33722
63.1%
Uppercase Letter
ValueCountFrequency (%)
G 459
29.9%
S 442
28.8%
C 118
 
7.7%
K 104
 
6.8%
L 93
 
6.1%
O 56
 
3.6%
U 43
 
2.8%
A 42
 
2.7%
M 28
 
1.8%
D 25
 
1.6%
Other values (15) 126
 
8.2%
Lowercase Letter
ValueCountFrequency (%)
a 26
12.6%
e 23
11.2%
y 19
 
9.2%
r 16
 
7.8%
m 14
 
6.8%
t 14
 
6.8%
i 12
 
5.8%
s 12
 
5.8%
o 11
 
5.3%
u 10
 
4.9%
Other values (9) 49
23.8%
Decimal Number
ValueCountFrequency (%)
2 833
44.4%
5 517
27.5%
4 237
 
12.6%
1 105
 
5.6%
0 65
 
3.5%
3 64
 
3.4%
7 26
 
1.4%
6 21
 
1.1%
9 5
 
0.3%
8 4
 
0.2%
Other Punctuation
ValueCountFrequency (%)
* 113
68.9%
& 28
 
17.1%
. 16
 
9.8%
@ 3
 
1.8%
1
 
0.6%
! 1
 
0.6%
/ 1
 
0.6%
, 1
 
0.6%
Math Symbol
ValueCountFrequency (%)
+ 1
50.0%
~ 1
50.0%
Space Separator
ValueCountFrequency (%)
1670
100.0%
Close Punctuation
ValueCountFrequency (%)
) 662
100.0%
Open Punctuation
ValueCountFrequency (%)
( 662
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Other Symbol
ValueCountFrequency (%)
21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 53495
88.7%
Common 5073
 
8.4%
Latin 1742
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3367
 
6.3%
3347
 
6.3%
2639
 
4.9%
2388
 
4.5%
1813
 
3.4%
1793
 
3.4%
1337
 
2.5%
1152
 
2.2%
1013
 
1.9%
903
 
1.7%
Other values (553) 33743
63.1%
Latin
ValueCountFrequency (%)
G 459
26.3%
S 442
25.4%
C 118
 
6.8%
K 104
 
6.0%
L 93
 
5.3%
O 56
 
3.2%
U 43
 
2.5%
A 42
 
2.4%
M 28
 
1.6%
a 26
 
1.5%
Other values (34) 331
19.0%
Common
ValueCountFrequency (%)
1670
32.9%
2 833
16.4%
) 662
 
13.0%
( 662
 
13.0%
5 517
 
10.2%
4 237
 
4.7%
* 113
 
2.2%
1 105
 
2.1%
0 65
 
1.3%
3 64
 
1.3%
Other values (14) 145
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 53474
88.7%
ASCII 6814
 
11.3%
None 22
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3367
 
6.3%
3347
 
6.3%
2639
 
4.9%
2388
 
4.5%
1813
 
3.4%
1793
 
3.4%
1337
 
2.5%
1152
 
2.2%
1013
 
1.9%
903
 
1.7%
Other values (552) 33722
63.1%
ASCII
ValueCountFrequency (%)
1670
24.5%
2 833
12.2%
) 662
 
9.7%
( 662
 
9.7%
5 517
 
7.6%
G 459
 
6.7%
S 442
 
6.5%
4 237
 
3.5%
C 118
 
1.7%
* 113
 
1.7%
Other values (57) 1101
16.2%
None
ValueCountFrequency (%)
21
95.5%
1
 
4.5%

최종수정시점
Real number (ℝ)

Distinct5799
Distinct (%)59.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0111906 × 1013
Minimum2.007063 × 1013
Maximum2.021083 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size86.0 KiB
2024-04-21T03:24:00.051454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.007063 × 1013
5-th percentile2.007063 × 1013
Q12.0070714 × 1013
median2.0110927 × 1013
Q32.0140623 × 1013
95-th percentile2.0190514 × 1013
Maximum2.021083 × 1013
Range1.4020007 × 1011
Interquartile range (IQR)6.9909059 × 1010

Descriptive statistics

Standard deviation4.3234682 × 1010
Coefficient of variation (CV)0.0021497059
Kurtosis-0.84793766
Mean2.0111906 × 1013
Median Absolute Deviation (MAD)4.021307 × 1010
Skewness0.60930759
Sum1.9639276 × 1017
Variance1.8692377 × 1021
MonotonicityNot monotonic
2024-04-21T03:24:00.349771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20070714112355 1271
 
13.0%
20070630104619 1011
 
10.4%
20070714113128 943
 
9.7%
20070714114235 321
 
3.3%
20070714133604 298
 
3.1%
20070714122950 116
 
1.2%
20071106162732 4
 
< 0.1%
20070630104938 3
 
< 0.1%
20140109100838 3
 
< 0.1%
20140113134752 2
 
< 0.1%
Other values (5789) 5793
59.3%
ValueCountFrequency (%)
20070630104619 1011
10.4%
20070630104938 3
 
< 0.1%
20070714112355 1271
13.0%
20070714113128 943
9.7%
20070714114235 321
 
3.3%
20070714122950 116
 
1.2%
20070714133604 298
 
3.1%
20070719101032 1
 
< 0.1%
20070719151425 1
 
< 0.1%
20070725133429 1
 
< 0.1%
ValueCountFrequency (%)
20210830174825 1
< 0.1%
20210830133733 1
< 0.1%
20210826155102 1
< 0.1%
20210825180013 1
< 0.1%
20210825171820 1
< 0.1%
20210820113432 1
< 0.1%
20210818121007 1
< 0.1%
20210817150743 1
< 0.1%
20210813151201 1
< 0.1%
20210812153650 1
< 0.1%

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size76.4 KiB
I
9151 
U
 
614

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 9151
93.7%
U 614
 
6.3%

Length

2024-04-21T03:24:00.583004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:24:00.737753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 9151
93.7%
u 614
 
6.3%
Distinct370
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size76.4 KiB
Minimum2018-08-31 23:59:59
Maximum2021-09-01 02:40:00
2024-04-21T03:24:00.920491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:24:01.255337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9765
Missing (%)100.0%
Memory size86.0 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct3963
Distinct (%)67.1%
Missing3856
Missing (%)39.5%
Infinite0
Infinite (%)0.0%
Mean341614.54
Minimum189859.07
Maximum358671.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size86.0 KiB
2024-04-21T03:24:01.650530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189859.07
5-th percentile335037.06
Q1338611.19
median340447.42
Q3344585.81
95-th percentile350277.52
Maximum358671.3
Range168812.23
Interquartile range (IQR)5974.6202

Descriptive statistics

Standard deviation5094.2067
Coefficient of variation (CV)0.014912148
Kurtosis133.12467
Mean341614.54
Median Absolute Deviation (MAD)2709.8273
Skewness-3.913481
Sum2.0186003 × 109
Variance25950942
MonotonicityNot monotonic
2024-04-21T03:24:02.084600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
336954.220302 13
 
0.1%
347950.194975 11
 
0.1%
338088.198632 9
 
0.1%
337950.916001 9
 
0.1%
338980.965932 9
 
0.1%
343538.563051 8
 
0.1%
339324.389142 8
 
0.1%
337885.924275 7
 
0.1%
340132.34497 7
 
0.1%
338969.480757 7
 
0.1%
Other values (3953) 5821
59.6%
(Missing) 3856
39.5%
ValueCountFrequency (%)
189859.071768836 1
 
< 0.1%
326605.700797 1
 
< 0.1%
328357.519907 1
 
< 0.1%
328379.70652 1
 
< 0.1%
328432.256141 3
< 0.1%
328544.626117 1
 
< 0.1%
329190.796671 1
 
< 0.1%
329266.125021 1
 
< 0.1%
329266.353804 1
 
< 0.1%
329276.638953 1
 
< 0.1%
ValueCountFrequency (%)
358671.296812 2
< 0.1%
356589.560791 1
< 0.1%
356563.89782 1
< 0.1%
356486.864993 2
< 0.1%
356461.2317 1
< 0.1%
356410.892344 1
< 0.1%
356408.030327 1
< 0.1%
356393.204312 1
< 0.1%
356378.752341 1
< 0.1%
356336.944398 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct3960
Distinct (%)67.0%
Missing3856
Missing (%)39.5%
Infinite0
Infinite (%)0.0%
Mean263656.18
Minimum241477.48
Maximum445875.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size86.0 KiB
2024-04-21T03:24:02.506367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum241477.48
5-th percentile257772.99
Q1260859.26
median263111.08
Q3266132.39
95-th percentile271702.03
Maximum445875.9
Range204398.42
Interquartile range (IQR)5273.1277

Descriptive statistics

Standard deviation4865.7578
Coefficient of variation (CV)0.018454936
Kurtosis332.99561
Mean263656.18
Median Absolute Deviation (MAD)2640.9176
Skewness8.9366345
Sum1.5579443 × 109
Variance23675599
MonotonicityNot monotonic
2024-04-21T03:24:02.973823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
262321.195205 13
 
0.1%
265687.62574 11
 
0.1%
263378.345914 10
 
0.1%
261689.070956 9
 
0.1%
258268.984702 9
 
0.1%
266594.606539 8
 
0.1%
259405.796434 8
 
0.1%
257685.990487 7
 
0.1%
259679.933297 7
 
0.1%
260039.727157 7
 
0.1%
Other values (3950) 5820
59.6%
(Missing) 3856
39.5%
ValueCountFrequency (%)
241477.476504 1
< 0.1%
241924.122554 1
< 0.1%
244299.117529 1
< 0.1%
244584.666286 2
< 0.1%
244707.665942 1
< 0.1%
244716.032592 1
< 0.1%
244719.026226 1
< 0.1%
244838.382091 1
< 0.1%
244883.054949 1
< 0.1%
244896.579004 1
< 0.1%
ValueCountFrequency (%)
445875.89672273 1
< 0.1%
292024.590733752 1
< 0.1%
286377.763753217 1
< 0.1%
278354.822081 1
< 0.1%
278226.867388 1
< 0.1%
278048.41446 1
< 0.1%
277985.228016 1
< 0.1%
277895.651799 1
< 0.1%
277798.822544 1
< 0.1%
277784.134758 1
< 0.1%

업소구분명
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size76.4 KiB
지정
6480 
종료
2182 
<NA>
1103 

Length

Max length4
Median length2
Mean length2.2259089
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지정 6480
66.4%
종료 2182
 
22.3%
<NA> 1103
 
11.3%

Length

2024-04-21T03:24:03.347422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:24:03.570567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지정 6480
66.4%
종료 2182
 
22.3%
na 1103
 
11.3%

소재지
Text

MISSING 

Distinct6114
Distinct (%)88.3%
Missing2843
Missing (%)29.1%
Memory size76.4 KiB
2024-04-21T03:24:04.905047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length48
Mean length20.509535
Min length2

Characters and Unicode

Total characters141967
Distinct characters423
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5500 ?
Unique (%)79.5%

Sample

1st row대구광역시 중구 대봉동 186-1번지
2nd row대구광역시 중구 대봉동 18번지 4호
3rd row대구광역시 중구 대봉동 55번지 95호
4th row대구광역시 중구 대봉동 111번지 1호
5th row대구광역시 중구 대봉동 590번지 281호
ValueCountFrequency (%)
대구광역시 5516
 
18.4%
달서구 2007
 
6.7%
북구 1254
 
4.2%
수성구 1024
 
3.4%
1호 520
 
1.7%
남구 474
 
1.6%
415
 
1.4%
대명동 327
 
1.1%
2호 289
 
1.0%
동구 284
 
0.9%
Other values (5335) 17864
59.6%
2024-04-21T03:24:06.464190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24340
17.1%
11291
 
8.0%
1 7938
 
5.6%
6772
 
4.8%
6165
 
4.3%
5611
 
4.0%
5551
 
3.9%
5549
 
3.9%
5528
 
3.9%
5185
 
3.7%
Other values (413) 58037
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 82554
58.2%
Decimal Number 32608
 
23.0%
Space Separator 24340
 
17.1%
Dash Punctuation 2141
 
1.5%
Uppercase Letter 97
 
0.1%
Other Punctuation 93
 
0.1%
Close Punctuation 56
 
< 0.1%
Open Punctuation 54
 
< 0.1%
Math Symbol 13
 
< 0.1%
Lowercase Letter 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11291
13.7%
6772
 
8.2%
6165
 
7.5%
5611
 
6.8%
5551
 
6.7%
5549
 
6.7%
5528
 
6.7%
5185
 
6.3%
3866
 
4.7%
2486
 
3.0%
Other values (370) 24550
29.7%
Uppercase Letter
ValueCountFrequency (%)
B 21
21.6%
A 21
21.6%
S 14
14.4%
L 7
 
7.2%
I 5
 
5.2%
K 5
 
5.2%
C 4
 
4.1%
G 4
 
4.1%
W 3
 
3.1%
H 3
 
3.1%
Other values (6) 10
10.3%
Decimal Number
ValueCountFrequency (%)
1 7938
24.3%
2 4258
13.1%
3 3324
10.2%
4 2946
 
9.0%
0 2840
 
8.7%
5 2532
 
7.8%
7 2280
 
7.0%
6 2271
 
7.0%
9 2146
 
6.6%
8 2073
 
6.4%
Lowercase Letter
ValueCountFrequency (%)
e 5
50.0%
c 2
 
20.0%
h 1
 
10.0%
t 1
 
10.0%
s 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 42
45.2%
/ 28
30.1%
. 15
 
16.1%
@ 8
 
8.6%
Close Punctuation
ValueCountFrequency (%)
) 55
98.2%
] 1
 
1.8%
Math Symbol
ValueCountFrequency (%)
~ 12
92.3%
= 1
 
7.7%
Space Separator
ValueCountFrequency (%)
24340
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2141
100.0%
Open Punctuation
ValueCountFrequency (%)
( 54
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 82554
58.2%
Common 59306
41.8%
Latin 107
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11291
13.7%
6772
 
8.2%
6165
 
7.5%
5611
 
6.8%
5551
 
6.7%
5549
 
6.7%
5528
 
6.7%
5185
 
6.3%
3866
 
4.7%
2486
 
3.0%
Other values (370) 24550
29.7%
Common
ValueCountFrequency (%)
24340
41.0%
1 7938
 
13.4%
2 4258
 
7.2%
3 3324
 
5.6%
4 2946
 
5.0%
0 2840
 
4.8%
5 2532
 
4.3%
7 2280
 
3.8%
6 2271
 
3.8%
9 2146
 
3.6%
Other values (12) 4431
 
7.5%
Latin
ValueCountFrequency (%)
B 21
19.6%
A 21
19.6%
S 14
13.1%
L 7
 
6.5%
e 5
 
4.7%
I 5
 
4.7%
K 5
 
4.7%
C 4
 
3.7%
G 4
 
3.7%
W 3
 
2.8%
Other values (11) 18
16.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 82553
58.1%
ASCII 59413
41.8%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24340
41.0%
1 7938
 
13.4%
2 4258
 
7.2%
3 3324
 
5.6%
4 2946
 
5.0%
0 2840
 
4.8%
5 2532
 
4.3%
7 2280
 
3.8%
6 2271
 
3.8%
9 2146
 
3.6%
Other values (33) 4538
 
7.6%
Hangul
ValueCountFrequency (%)
11291
13.7%
6772
 
8.2%
6165
 
7.5%
5611
 
6.8%
5551
 
6.7%
5549
 
6.7%
5528
 
6.7%
5185
 
6.3%
3866
 
4.7%
2486
 
3.0%
Other values (369) 24549
29.7%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

지정일자
Real number (ℝ)

MISSING 

Distinct1903
Distinct (%)51.7%
Missing6085
Missing (%)62.3%
Infinite0
Infinite (%)0.0%
Mean20124016
Minimum19940104
Maximum20210830
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size86.0 KiB
2024-04-21T03:24:06.718993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19940104
5-th percentile20060310
Q120091013
median20120226
Q320160315
95-th percentile20190604
Maximum20210830
Range270726
Interquartile range (IQR)69302.5

Descriptive statistics

Standard deviation43431.701
Coefficient of variation (CV)0.0021582025
Kurtosis0.6690788
Mean20124016
Median Absolute Deviation (MAD)30242.5
Skewness-0.41807787
Sum7.4056378 × 1010
Variance1.8863127 × 109
MonotonicityNot monotonic
2024-04-21T03:24:07.209160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20081231 128
 
1.3%
20120214 95
 
1.0%
20120106 77
 
0.8%
20120102 65
 
0.7%
20120215 35
 
0.4%
20111230 35
 
0.4%
20111229 23
 
0.2%
20120105 22
 
0.2%
20081230 22
 
0.2%
20111226 20
 
0.2%
Other values (1893) 3158
32.3%
(Missing) 6085
62.3%
ValueCountFrequency (%)
19940104 3
< 0.1%
19941215 1
 
< 0.1%
19941228 4
< 0.1%
19950105 1
 
< 0.1%
19950109 2
< 0.1%
19950119 1
 
< 0.1%
19950406 1
 
< 0.1%
19950705 1
 
< 0.1%
19950904 1
 
< 0.1%
19951220 1
 
< 0.1%
ValueCountFrequency (%)
20210830 1
< 0.1%
20210826 1
< 0.1%
20210825 1
< 0.1%
20210818 1
< 0.1%
20210812 1
< 0.1%
20210811 1
< 0.1%
20210730 1
< 0.1%
20210727 1
< 0.1%
20210723 1
< 0.1%
20210715 1
< 0.1%

신청일자
Real number (ℝ)

MISSING  SKEWED 

Distinct2903
Distinct (%)48.9%
Missing3829
Missing (%)39.2%
Infinite0
Infinite (%)0.0%
Mean20074749
Minimum199505
Maximum20210825
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size86.0 KiB
2024-04-21T03:24:07.466859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum199505
5-th percentile19950104
Q120031125
median20090320
Q320130946
95-th percentile20181203
Maximum20210825
Range20011320
Interquartile range (IQR)99820.5

Descriptive statistics

Standard deviation425492.32
Coefficient of variation (CV)0.021195399
Kurtosis1895.9423
Mean20074749
Median Absolute Deviation (MAD)50098
Skewness-42.974935
Sum1.1916371 × 1011
Variance1.8104371 × 1011
MonotonicityNot monotonic
2024-04-21T03:24:07.738439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20120106 137
 
1.4%
19950104 128
 
1.3%
20120214 91
 
0.9%
19950105 75
 
0.8%
20120105 72
 
0.7%
20120102 71
 
0.7%
20081231 66
 
0.7%
19950103 62
 
0.6%
20120215 35
 
0.4%
20111230 32
 
0.3%
Other values (2893) 5167
52.9%
(Missing) 3829
39.2%
ValueCountFrequency (%)
199505 1
 
< 0.1%
2010115 2
 
< 0.1%
19940104 3
 
< 0.1%
19940801 7
0.1%
19941001 2
 
< 0.1%
19941031 12
0.1%
19941101 17
0.2%
19941201 8
0.1%
19941205 1
 
< 0.1%
19941206 4
 
< 0.1%
ValueCountFrequency (%)
20210825 1
< 0.1%
20210824 2
< 0.1%
20210812 1
< 0.1%
20210811 1
< 0.1%
20210809 1
< 0.1%
20210726 2
< 0.1%
20210723 1
< 0.1%
20210712 1
< 0.1%
20210707 1
< 0.1%
20210701 1
< 0.1%

항목값1
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size76.4 KiB
관급봉투
9765 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관급봉투 9765
100.0%

Length

2024-04-21T03:24:07.982251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:24:08.135117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관급봉투 9765
100.0%

Sample

번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)업소구분명소재지지정일자신청일자항목값1
01쓰레기종량제봉투판매업09_30_13_P341000034100001420000111319970519<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>700811대구광역시 중구 대봉동 186-1번지대구광역시 중구 동덕로 6 (대봉동)700811유성주유소20140110114512I2018-08-31 23:59:59.0<NA>344831.97444262899.677082지정대구광역시 중구 대봉동 186-1번지<NA><NA>관급봉투
12쓰레기종량제봉투판매업09_30_13_P341000034100001420000111419980209<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>700809대구광역시 중구 대봉동 18-4번지대구광역시 중구 동덕로14길 29 (대봉동)700809은진슈퍼20140110114610I2018-08-31 23:59:59.0<NA>344944.628049263499.508848지정대구광역시 중구 대봉동 18번지 4호<NA><NA>관급봉투
23쓰레기종량제봉투판매업09_30_13_P341000034100001420000110619941230<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>700810대구광역시 중구 대봉동 55-95번지대구광역시 중구 대봉로 236 (대봉동)700810대구코아20140110115715I2018-08-31 23:59:59.0<NA>344563.366332263345.037673지정대구광역시 중구 대봉동 55번지 95호<NA><NA>관급봉투
34쓰레기종량제봉투판매업09_30_13_P341000034100001420000110519941215<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>700761대구광역시 중구 대봉동 111-1번지대구광역시 중구 동덕로 33 (대봉동)700761청운슈퍼20140110115814I2018-08-31 23:59:59.0<NA>344781.041867263166.287036지정대구광역시 중구 대봉동 111번지 1호<NA><NA>관급봉투
45쓰레기종량제봉투판매업09_30_13_P3410000341000014200001207199903<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>700813대구광역시 중구 대봉동 590-281번지대구광역시 중구 명륜로22안길 28 (대봉동)700813또와20140110140010I2018-08-31 23:59:59.0<NA>344062.360257263119.505521지정대구광역시 중구 대봉동 590번지 281호<NA><NA>관급봉투
56쓰레기종량제봉투판매업09_30_13_P341000034100001420030002620030724<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>700421대구광역시 중구 동인동1가 96-1번지대구광역시 중구 국채보상로131길 69 (동인동1가)700421삼진마트20140113111004I2018-08-31 23:59:59.0<NA>344649.83603264821.089303지정대구광역시 중구 동인동1가 96번지 1호<NA>20030724관급봉투
67쓰레기종량제봉투판매업09_30_13_P341000034100001420030004320031030<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>700845대구광역시 중구 동인동3가 271-142번지대구광역시 중구 태평로 266 (동인동3가)700845LA24시편의점20140113134500I2018-08-31 23:59:59.0<NA>345001.809874264769.663002지정대구광역시 중구 동인동3가 271-142번지<NA>20031030관급봉투
78쓰레기종량제봉투판매업09_30_13_P341000034100001420030004420031101<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>700804대구광역시 중구 남산동 2117-7번지대구광역시 중구 남산로6길 81 (남산동)700804신우유통 남산1호점20140113134614I2018-08-31 23:59:59.0<NA>343271.906983263040.314154지정대구광역시 중구 남산동 2117번지 7호<NA>20031101관급봉투
89쓰레기종량제봉투판매업09_30_13_P341000034100001420030005220031129<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>700112대구광역시 중구 태평로2가 1-50번지대구광역시 중구 태평로 135 (태평로2가)700112OK 2120140113152357I2018-08-31 23:59:59.0<NA>343742.132997265123.15101지정대구광역시 중구 태평로2가 1번지 50호<NA>20031129관급봉투
910쓰레기종량제봉투판매업09_30_13_P341000034100001420030005320031129<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>700823대구광역시 중구 봉산동 230-74번지대구광역시 중구 명륜로23길 36 (봉산동)700823제일수퍼20140114090016I2018-08-31 23:59:59.0<NA>344068.262076263557.856723지정대구광역시 중구 봉산동 230-74번지<NA>20031129관급봉투
번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)업소구분명소재지지정일자신청일자항목값1
97559756쓰레기종량제봉투판매업09_30_13_P348000034800001419953000219950105<NA>1영업/정상11영업<NA><NA><NA><NA>053585 0839<NA>711810대구광역시 달성군 다사읍 서재리 121-3번지<NA><NA>알뜰슈퍼20070714114235I2018-08-31 23:59:59.0<NA><NA><NA>지정서재리 121-3번지<NA>19950105관급봉투
97569757쓰레기종량제봉투판매업09_30_13_P348000034800001419954000219950101<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>711860대구광역시 달성군 가창면 용계리 50-1번지대구광역시 달성군 가창면 가창로 1106-2<NA>가창슈퍼20070714114235I2018-08-31 23:59:59.0<NA>346576.115256257031.853316지정용계리 50번지 1호<NA>20010713관급봉투
97579758쓰레기종량제봉투판매업09_30_13_P348000034800001419954000320000101<NA>1영업/정상11영업<NA><NA><NA><NA>053 768 6500<NA>711860대구광역시 달성군 가창면 용계리 30-7번지<NA><NA>가창단위조합20070714114235I2018-08-31 23:59:59.0<NA><NA><NA>지정용계리 30-7번지<NA>20010713관급봉투
97589759쓰레기종량제봉투판매업09_30_13_P348000034800001419954000419950101<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>711860대구광역시 달성군 가창면 용계리 217-5번지<NA><NA>선산수퍼20070714114235I2018-08-31 23:59:59.0<NA><NA><NA>지정용계리 217-5<NA>20010713관급봉투
97599760쓰레기종량제봉투판매업09_30_13_P348000034800001419954000519950101<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>711860대구광역시 달성군 가창면 용계리 465번지<NA><NA>중석할인마트20070714114235I2018-08-31 23:59:59.0<NA>347065.258082256293.424664지정용계리 465번지<NA>20010713관급봉투
97609761쓰레기종량제봉투판매업09_30_13_P348000034800001419952002319950103<NA>1영업/정상11영업<NA><NA><NA><NA>053 6112305<NA>711850대구광역시 달성군 논공읍 금포리 1238번지대구광역시 달성군 논공읍 강림1길 48<NA>금포3리구판장20070714114235I2018-08-31 23:59:59.0<NA>329704.402658253739.398549지정논공읍 금포리 1238<NA>19950103관급봉투
97619762쓰레기종량제봉투판매업09_30_13_P348000034800001419952002419950103<NA>1영업/정상11영업<NA><NA><NA><NA>053 6112508<NA>711850대구광역시 달성군 논공읍 금포리 932번지<NA><NA>공단식품수퍼20070714114235I2018-08-31 23:59:59.0<NA><NA><NA>지정논공읍 금포리 932<NA>19950103관급봉투
97629763쓰레기종량제봉투판매업09_30_13_P348000034800001419952002519950103<NA>1영업/정상11영업<NA><NA><NA><NA>053 6141212<NA>711850대구광역시 달성군 논공읍 금포리 2002번지대구광역시 달성군 논공읍 비슬로 1778<NA>농협연쇄점20070714114235I2018-08-31 23:59:59.0<NA>328357.519907253581.545752지정논공읍 금포리 2002<NA>19950103관급봉투
97639764쓰레기종량제봉투판매업09_30_13_P348000034800001419952002619950103<NA>1영업/정상11영업<NA><NA><NA><NA>053 6112814<NA>711850대구광역시 달성군 논공읍 금포리 1805번지<NA><NA>금포수퍼20070714114235I2018-08-31 23:59:59.0<NA>328432.256141253658.370816지정논공읍 금포리 1805<NA>19950103관급봉투
97649765쓰레기종량제봉투판매업09_30_13_P348000034800001419952002919950103<NA>1영업/정상11영업<NA><NA><NA><NA>053 6162887<NA>711850대구광역시 달성군 논공읍 삼리리 824-122번지<NA><NA>삼리3리구판장20070714114235I2018-08-31 23:59:59.0<NA><NA><NA>지정논공읍 삼리리 824-122<NA>19950103관급봉투