Overview

Dataset statistics

Number of variables32
Number of observations514
Missing cells4465
Missing cells (%)27.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory139.2 KiB
Average record size in memory277.3 B

Variable types

Numeric14
Categorical9
Unsupported4
Text4
DateTime1

Dataset

Description6270000_대구광역시_11_50_03_P_행정사업_12월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000083478&dataSetDetailId=DDI_0000083504&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스ID has constant value ""Constant
데이터갱신구분 is highly imbalanced (59.2%)Imbalance
인허가취소일자 has 514 (100.0%) missing valuesMissing
폐업일자 has 375 (73.0%) missing valuesMissing
휴업시작일자 has 498 (96.9%) missing valuesMissing
휴업종료일자 has 498 (96.9%) missing valuesMissing
재개업일자 has 489 (95.1%) missing valuesMissing
소재지전화 has 130 (25.3%) missing valuesMissing
소재지면적 has 514 (100.0%) missing valuesMissing
소재지우편번호 has 514 (100.0%) missing valuesMissing
소재지전체주소 has 80 (15.6%) missing valuesMissing
도로명전체주소 has 17 (3.3%) missing valuesMissing
도로명우편번호 has 17 (3.3%) missing valuesMissing
업태구분명 has 514 (100.0%) missing valuesMissing
좌표정보(X) has 20 (3.9%) missing valuesMissing
좌표정보(Y) has 20 (3.9%) missing valuesMissing
변경처리일 has 265 (51.6%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
최종수정시점 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지우편번호 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 started2023-12-10 20:09:30.455874
Analysis finished2023-12-10 20:09:31.191220
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct514
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean257.5
Minimum1
Maximum514
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-11T05:09:31.258524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile26.65
Q1129.25
median257.5
Q3385.75
95-th percentile488.35
Maximum514
Range513
Interquartile range (IQR)256.5

Descriptive statistics

Standard deviation148.52329
Coefficient of variation (CV)0.57678946
Kurtosis-1.2
Mean257.5
Median Absolute Deviation (MAD)128.5
Skewness0
Sum132355
Variance22059.167
MonotonicityStrictly increasing
2023-12-11T05:09:31.413380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
387 1
 
0.2%
353 1
 
0.2%
352 1
 
0.2%
351 1
 
0.2%
350 1
 
0.2%
349 1
 
0.2%
348 1
 
0.2%
347 1
 
0.2%
346 1
 
0.2%
Other values (504) 504
98.1%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
514 1
0.2%
513 1
0.2%
512 1
0.2%
511 1
0.2%
510 1
0.2%
509 1
0.2%
508 1
0.2%
507 1
0.2%
506 1
0.2%
505 1
0.2%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
행정사업
514 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
행정사업 514
100.0%

Length

2023-12-11T05:09:31.546153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:09:31.647728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
행정사업 514
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
11_50_03_P
514 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11_50_03_P
2nd row11_50_03_P
3rd row11_50_03_P
4th row11_50_03_P
5th row11_50_03_P

Common Values

ValueCountFrequency (%)
11_50_03_P 514
100.0%

Length

2023-12-11T05:09:31.737829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:09:31.823140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11_50_03_p 514
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3450505.8
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-11T05:09:31.897787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3410000
Q13430000
median3460000
Q33460000
95-th percentile3480000
Maximum3480000
Range70000
Interquartile range (IQR)30000

Descriptive statistics

Standard deviation20216.59
Coefficient of variation (CV)0.005859022
Kurtosis-0.7337634
Mean3450505.8
Median Absolute Deviation (MAD)10000
Skewness-0.67173065
Sum1.77356 × 109
Variance4.0871049 × 108
MonotonicityIncreasing
2023-12-11T05:09:31.993842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3460000 192
37.4%
3470000 77
15.0%
3420000 62
 
12.1%
3450000 57
 
11.1%
3430000 39
 
7.6%
3410000 35
 
6.8%
3480000 34
 
6.6%
3440000 18
 
3.5%
ValueCountFrequency (%)
3410000 35
 
6.8%
3420000 62
 
12.1%
3430000 39
 
7.6%
3440000 18
 
3.5%
3450000 57
 
11.1%
3460000 192
37.4%
3470000 77
15.0%
3480000 34
 
6.6%
ValueCountFrequency (%)
3480000 34
 
6.6%
3470000 77
15.0%
3460000 192
37.4%
3450000 57
 
11.1%
3440000 18
 
3.5%
3430000 39
 
7.6%
3420000 62
 
12.1%
3410000 35
 
6.8%

관리번호
Real number (ℝ)

UNIQUE 

Distinct514
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.3954791 × 1012
Minimum3.4100002 × 1011
Maximum3.4600002 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-11T05:09:32.112222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.4100002 × 1011
5-th percentile3.4400002 × 1011
Q13.4200002 × 1012
median3.4600002 × 1012
Q33.4800002 × 1012
95-th percentile3.4600002 × 1013
Maximum3.4600002 × 1013
Range3.4259002 × 1013
Interquartile range (IQR)5.9999999 × 1010

Descriptive statistics

Standard deviation1.2743805 × 1013
Coefficient of variation (CV)1.3563762
Kurtosis0.18324225
Mean9.3954791 × 1012
Median Absolute Deviation (MAD)3 × 1010
Skewness1.4633587
Sum4.8292763 × 1015
Variance1.6240456 × 1026
MonotonicityNot monotonic
2023-12-11T05:09:32.236876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3410000201219 1
 
0.2%
3460000201369 1
 
0.2%
346000020123 1
 
0.2%
34600002018194 1
 
0.2%
34600002014171 1
 
0.2%
34600002015173 1
 
0.2%
34600002015174 1
 
0.2%
34600002015175 1
 
0.2%
34600002015177 1
 
0.2%
34600002016178 1
 
0.2%
Other values (504) 504
98.1%
ValueCountFrequency (%)
341000020121 1
0.2%
341000020123 1
0.2%
341000020124 1
0.2%
341000020125 1
0.2%
341000020126 1
0.2%
341000020127 1
0.2%
341000020128 1
0.2%
341000020129 1
0.2%
342000020121 1
0.2%
342000020122 1
0.2%
ValueCountFrequency (%)
34600002019208 1
0.2%
34600002019207 1
0.2%
34600002019206 1
0.2%
34600002019205 1
0.2%
34600002018204 1
0.2%
34600002018203 1
0.2%
34600002018202 1
0.2%
34600002018201 1
0.2%
34600002018200 1
0.2%
34600002018199 1
0.2%

인허가일자
Real number (ℝ)

Distinct413
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20087341
Minimum19820330
Maximum20191023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-11T05:09:32.356529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19820330
5-th percentile19960216
Q120040236
median20101068
Q320140328
95-th percentile20181112
Maximum20191023
Range370693
Interquartile range (IQR)100092.25

Descriptive statistics

Standard deviation72466.822
Coefficient of variation (CV)0.0036075866
Kurtosis0.078158763
Mean20087341
Median Absolute Deviation (MAD)50637
Skewness-0.68359256
Sum1.0324893 × 1010
Variance5.2514403 × 109
MonotonicityNot monotonic
2023-12-11T05:09:32.682898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19960216 19
 
3.7%
20121227 9
 
1.8%
20121220 7
 
1.4%
20121207 5
 
1.0%
20121228 5
 
1.0%
20180420 5
 
1.0%
20121217 4
 
0.8%
20170314 3
 
0.6%
20121204 3
 
0.6%
20180601 3
 
0.6%
Other values (403) 451
87.7%
ValueCountFrequency (%)
19820330 1
0.2%
19830109 1
0.2%
19840620 1
0.2%
19860311 1
0.2%
19871024 1
0.2%
19890526 1
0.2%
19911025 1
0.2%
19930430 1
0.2%
19940902 1
0.2%
19951106 1
0.2%
ValueCountFrequency (%)
20191023 1
0.2%
20191014 2
0.4%
20190917 1
0.2%
20190809 1
0.2%
20190702 1
0.2%
20190605 1
0.2%
20190530 1
0.2%
20190523 1
0.2%
20190521 1
0.2%
20190516 1
0.2%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing514
Missing (%)100.0%
Memory size4.6 KiB

영업상태구분코드
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
1
358 
3
140 
2
 
16

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row1
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
1 358
69.6%
3 140
 
27.2%
2 16
 
3.1%

Length

2023-12-11T05:09:32.797976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:09:32.888501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 358
69.6%
3 140
 
27.2%
2 16
 
3.1%

영업상태명
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
영업/정상
358 
폐업
140 
휴업
 
16

Length

Max length5
Median length5
Mean length4.0894942
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 358
69.6%
폐업 140
 
27.2%
휴업 16
 
3.1%

Length

2023-12-11T05:09:32.980995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:09:33.070308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 358
69.6%
폐업 140
 
27.2%
휴업 16
 
3.1%

상세영업상태코드
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
1
358 
3
140 
2
 
16

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row1
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
1 358
69.6%
3 140
 
27.2%
2 16
 
3.1%

Length

2023-12-11T05:09:33.154515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:09:33.231152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 358
69.6%
3 140
 
27.2%
2 16
 
3.1%

상세영업상태명
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
영업중
358 
폐업
140 
휴업
 
16

Length

Max length3
Median length3
Mean length2.6964981
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 358
69.6%
폐업 140
 
27.2%
휴업 16
 
3.1%

Length

2023-12-11T05:09:33.324366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:09:33.416054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 358
69.6%
폐업 140
 
27.2%
휴업 16
 
3.1%

폐업일자
Real number (ℝ)

MISSING 

Distinct125
Distinct (%)89.9%
Missing375
Missing (%)73.0%
Infinite0
Infinite (%)0.0%
Mean20156881
Minimum20120227
Maximum20191127
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-11T05:09:33.513424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20120227
5-th percentile20130415
Q120140657
median20151113
Q320171172
95-th percentile20190539
Maximum20191127
Range70900
Interquartile range (IQR)30515.5

Descriptive statistics

Standard deviation19914.413
Coefficient of variation (CV)0.00098797096
Kurtosis-1.0596919
Mean20156881
Median Absolute Deviation (MAD)10908
Skewness0.31704331
Sum2.8018065 × 109
Variance3.9658386 × 108
MonotonicityNot monotonic
2023-12-11T05:09:33.637167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20171229 4
 
0.8%
20131227 3
 
0.6%
20161229 2
 
0.4%
20140721 2
 
0.4%
20140328 2
 
0.4%
20131219 2
 
0.4%
20160731 2
 
0.4%
20150130 2
 
0.4%
20160811 2
 
0.4%
20180504 2
 
0.4%
Other values (115) 116
 
22.6%
(Missing) 375
73.0%
ValueCountFrequency (%)
20120227 1
0.2%
20130103 1
0.2%
20130121 1
0.2%
20130206 1
0.2%
20130320 1
0.2%
20130402 1
0.2%
20130403 1
0.2%
20130416 1
0.2%
20130426 1
0.2%
20130601 1
0.2%
ValueCountFrequency (%)
20191127 1
0.2%
20191126 1
0.2%
20191111 1
0.2%
20191025 1
0.2%
20190903 1
0.2%
20190705 1
0.2%
20190626 1
0.2%
20190529 1
0.2%
20190430 1
0.2%
20190419 1
0.2%

휴업시작일자
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)50.0%
Missing498
Missing (%)96.9%
Infinite0
Infinite (%)0.0%
Mean20136514
Minimum20090123
Maximum20190924
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-11T05:09:33.734962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090123
5-th percentile20090123
Q120121231
median20121231
Q320156002
95-th percentile20190317
Maximum20190924
Range100801
Interquartile range (IQR)34770.75

Descriptive statistics

Standard deviation32158.526
Coefficient of variation (CV)0.0015970255
Kurtosis-0.74033283
Mean20136514
Median Absolute Deviation (MAD)14897.5
Skewness0.49693903
Sum3.2218422 × 108
Variance1.0341708 × 109
MonotonicityNot monotonic
2023-12-11T05:09:33.817700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
20121231 8
 
1.6%
20090123 2
 
0.4%
20190924 1
 
0.2%
20180515 1
 
0.2%
20190115 1
 
0.2%
20151228 1
 
0.2%
20151026 1
 
0.2%
20170323 1
 
0.2%
(Missing) 498
96.9%
ValueCountFrequency (%)
20090123 2
 
0.4%
20121231 8
1.6%
20151026 1
 
0.2%
20151228 1
 
0.2%
20170323 1
 
0.2%
20180515 1
 
0.2%
20190115 1
 
0.2%
20190924 1
 
0.2%
ValueCountFrequency (%)
20190924 1
 
0.2%
20190115 1
 
0.2%
20180515 1
 
0.2%
20170323 1
 
0.2%
20151228 1
 
0.2%
20151026 1
 
0.2%
20121231 8
1.6%
20090123 2
 
0.4%

휴업종료일자
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)43.8%
Missing498
Missing (%)96.9%
Infinite0
Infinite (%)0.0%
Mean20164790
Minimum20141231
Maximum20220923
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-11T05:09:33.899041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20141231
5-th percentile20141231
Q120141231
median20141231
Q320200692
95-th percentile20212816
Maximum20220923
Range79692
Interquartile range (IQR)59460.75

Descriptive statistics

Standard deviation31977.875
Coefficient of variation (CV)0.0015858274
Kurtosis-1.5356246
Mean20164790
Median Absolute Deviation (MAD)0
Skewness0.69483004
Sum3.2263664 × 108
Variance1.0225845 × 109
MonotonicityNot monotonic
2023-12-11T05:09:33.996299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
20141231 10
 
1.9%
20220923 1
 
0.2%
20200514 1
 
0.2%
20210114 1
 
0.2%
20201228 1
 
0.2%
20201225 1
 
0.2%
20190322 1
 
0.2%
(Missing) 498
96.9%
ValueCountFrequency (%)
20141231 10
1.9%
20190322 1
 
0.2%
20200514 1
 
0.2%
20201225 1
 
0.2%
20201228 1
 
0.2%
20210114 1
 
0.2%
20220923 1
 
0.2%
ValueCountFrequency (%)
20220923 1
 
0.2%
20210114 1
 
0.2%
20201228 1
 
0.2%
20201225 1
 
0.2%
20200514 1
 
0.2%
20190322 1
 
0.2%
20141231 10
1.9%

재개업일자
Real number (ℝ)

MISSING 

Distinct24
Distinct (%)96.0%
Missing489
Missing (%)95.1%
Infinite0
Infinite (%)0.0%
Mean20169104
Minimum20131218
Maximum20191108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-11T05:09:34.105626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20131218
5-th percentile20140164
Q120151130
median20171128
Q320181210
95-th percentile20190728
Maximum20191108
Range59890
Interquartile range (IQR)30080

Descriptive statistics

Standard deviation18599.701
Coefficient of variation (CV)0.00092218774
Kurtosis-1.0441781
Mean20169104
Median Absolute Deviation (MAD)18988
Skewness-0.42716433
Sum5.0422761 × 108
Variance3.4594887 × 108
MonotonicityNot monotonic
2023-12-11T05:09:34.210254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
20151021 2
 
0.4%
20140310 1
 
0.2%
20191108 1
 
0.2%
20180919 1
 
0.2%
20161005 1
 
0.2%
20181102 1
 
0.2%
20180627 1
 
0.2%
20151130 1
 
0.2%
20180419 1
 
0.2%
20171128 1
 
0.2%
Other values (14) 14
 
2.7%
(Missing) 489
95.1%
ValueCountFrequency (%)
20131218 1
0.2%
20140128 1
0.2%
20140310 1
0.2%
20150120 1
0.2%
20151021 2
0.4%
20151130 1
0.2%
20160512 1
0.2%
20160628 1
0.2%
20160829 1
0.2%
20161005 1
0.2%
ValueCountFrequency (%)
20191108 1
0.2%
20190805 1
0.2%
20190422 1
0.2%
20190409 1
0.2%
20190401 1
0.2%
20190116 1
0.2%
20181210 1
0.2%
20181102 1
0.2%
20180919 1
0.2%
20180627 1
0.2%

소재지전화
Text

MISSING 

Distinct370
Distinct (%)96.4%
Missing130
Missing (%)25.3%
Memory size4.1 KiB
2023-12-11T05:09:34.447566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.416667
Min length1

Characters and Unicode

Total characters4384
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique357 ?
Unique (%)93.0%

Sample

1st row053-425-5615
2nd row053-252-0402
3rd row053-425-3412
4th row053-424-9111
5th row053-252-0747
ValueCountFrequency (%)
0537918484 3
 
0.8%
053-584-9315 2
 
0.5%
053-627-7576 2
 
0.5%
053 2
 
0.5%
053-963-0379 2
 
0.5%
053-355-5546 2
 
0.5%
070-4085-9997 2
 
0.5%
053-745-3577 2
 
0.5%
053-321-4902 2
 
0.5%
0537412941 2
 
0.5%
Other values (361) 365
94.6%
2023-12-11T05:09:34.865277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 705
16.1%
0 616
14.1%
3 606
13.8%
- 565
12.9%
7 324
7.4%
2 290
6.6%
6 282
 
6.4%
4 273
 
6.2%
1 262
 
6.0%
8 239
 
5.5%
Other values (3) 222
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3816
87.0%
Dash Punctuation 565
 
12.9%
Space Separator 2
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 705
18.5%
0 616
16.1%
3 606
15.9%
7 324
8.5%
2 290
7.6%
6 282
 
7.4%
4 273
 
7.2%
1 262
 
6.9%
8 239
 
6.3%
9 219
 
5.7%
Dash Punctuation
ValueCountFrequency (%)
- 565
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4384
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 705
16.1%
0 616
14.1%
3 606
13.8%
- 565
12.9%
7 324
7.4%
2 290
6.6%
6 282
 
6.4%
4 273
 
6.2%
1 262
 
6.0%
8 239
 
5.5%
Other values (3) 222
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4384
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 705
16.1%
0 616
14.1%
3 606
13.8%
- 565
12.9%
7 324
7.4%
2 290
6.6%
6 282
 
6.4%
4 273
 
6.2%
1 262
 
6.0%
8 239
 
5.5%
Other values (3) 222
 
5.1%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing514
Missing (%)100.0%
Memory size4.6 KiB

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing514
Missing (%)100.0%
Memory size4.6 KiB

소재지전체주소
Text

MISSING 

Distinct402
Distinct (%)92.6%
Missing80
Missing (%)15.6%
Memory size4.1 KiB
2023-12-11T05:09:35.374308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length42
Mean length26.036866
Min length12

Characters and Unicode

Total characters11300
Distinct characters234
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique378 ?
Unique (%)87.1%

Sample

1st row대구광역시 중구 대봉동 47번지 21호
2nd row대구광역시 중구 삼덕동1가 8번지 13호
3rd row대구광역시 중구 동인동4가 390번지 1호 은송빌딩
4th row대구광역시 중구 동인동4가 390번지 1호 은송빌딩
5th row대구광역시 중구 대봉동 741번지 10호
ValueCountFrequency (%)
대구광역시 434
 
17.7%
수성구 188
 
7.7%
범어동 101
 
4.1%
동구 58
 
2.4%
1호 57
 
2.3%
북구 52
 
2.1%
달서구 38
 
1.6%
서구 37
 
1.5%
2호 31
 
1.3%
3호 30
 
1.2%
Other values (683) 1423
58.1%
2023-12-11T05:09:36.138435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2020
17.9%
구 854
 
7.6%
1 578
 
5.1%
동 547
 
4.8%
지 464
 
4.1%
대 462
 
4.1%
호 457
 
4.0%
시 448
 
4.0%
광 437
 
3.9%
역 436
 
3.9%
Other values (224) 4597
40.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6909
61.1%
Decimal Number 2353
 
20.8%
Space Separator 2020
 
17.9%
Uppercase Letter 14
 
0.1%
Dash Punctuation 3
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 854
12.4%
동 547
 
7.9%
지 464
 
6.7%
대 462
 
6.7%
호 457
 
6.6%
시 448
 
6.5%
광 437
 
6.3%
역 436
 
6.3%
번 428
 
6.2%
성 280
 
4.1%
Other values (207) 2096
30.3%
Decimal Number
ValueCountFrequency (%)
1 578
24.6%
0 290
12.3%
2 288
12.2%
3 255
10.8%
4 185
 
7.9%
5 180
 
7.6%
7 163
 
6.9%
9 140
 
5.9%
6 139
 
5.9%
8 135
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
A 7
50.0%
S 4
28.6%
C 2
 
14.3%
B 1
 
7.1%
Space Separator
ValueCountFrequency (%)
2020
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6909
61.1%
Common 4376
38.7%
Latin 15
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 854
12.4%
동 547
 
7.9%
지 464
 
6.7%
대 462
 
6.7%
호 457
 
6.6%
시 448
 
6.5%
광 437
 
6.3%
역 436
 
6.3%
번 428
 
6.2%
성 280
 
4.1%
Other values (207) 2096
30.3%
Common
ValueCountFrequency (%)
2020
46.2%
1 578
 
13.2%
0 290
 
6.6%
2 288
 
6.6%
3 255
 
5.8%
4 185
 
4.2%
5 180
 
4.1%
7 163
 
3.7%
9 140
 
3.2%
6 139
 
3.2%
Other values (2) 138
 
3.2%
Latin
ValueCountFrequency (%)
A 7
46.7%
S 4
26.7%
C 2
 
13.3%
B 1
 
6.7%
b 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6909
61.1%
ASCII 4391
38.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2020
46.0%
1 578
 
13.2%
0 290
 
6.6%
2 288
 
6.6%
3 255
 
5.8%
4 185
 
4.2%
5 180
 
4.1%
7 163
 
3.7%
9 140
 
3.2%
6 139
 
3.2%
Other values (7) 153
 
3.5%
Hangul
ValueCountFrequency (%)
구 854
12.4%
동 547
 
7.9%
지 464
 
6.7%
대 462
 
6.7%
호 457
 
6.6%
시 448
 
6.5%
광 437
 
6.3%
역 436
 
6.3%
번 428
 
6.2%
성 280
 
4.1%
Other values (207) 2096
30.3%

도로명전체주소
Text

MISSING 

Distinct444
Distinct (%)89.3%
Missing17
Missing (%)3.3%
Memory size4.1 KiB
2023-12-11T05:09:36.710815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length50
Mean length29.078471
Min length19

Characters and Unicode

Total characters14452
Distinct characters281
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique410 ?
Unique (%)82.5%

Sample

1st row대구광역시 중구 국채보상로 572, 403호 (전동)
2nd row대구광역시 중구 동덕로 54, 304호 (대봉동)
3rd row대구광역시 중구 경상감영길 62 (서성로1가)
4th row대구광역시 중구 동성로5길 20 (삼덕동1가)
5th row대구광역시 중구 국채보상로142길 33-26 (동인동4가)
ValueCountFrequency (%)
대구광역시 497
 
17.1%
수성구 182
 
6.3%
범어동 99
 
3.4%
달서구 75
 
2.6%
동대구로 64
 
2.2%
동구 62
 
2.1%
북구 58
 
2.0%
서구 38
 
1.3%
중구 35
 
1.2%
달성군 29
 
1.0%
Other values (867) 1762
60.7%
2023-12-11T05:09:37.580545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2404
 
16.6%
구 1089
 
7.5%
동 742
 
5.1%
대 672
 
4.6%
시 523
 
3.6%
1 508
 
3.5%
광 500
 
3.5%
역 500
 
3.5%
로 492
 
3.4%
( 471
 
3.3%
Other values (271) 6551
45.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8351
57.8%
Space Separator 2404
 
16.6%
Decimal Number 2370
 
16.4%
Open Punctuation 471
 
3.3%
Close Punctuation 471
 
3.3%
Other Punctuation 283
 
2.0%
Dash Punctuation 87
 
0.6%
Uppercase Letter 15
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1089
 
13.0%
동 742
 
8.9%
대 672
 
8.0%
시 523
 
6.3%
광 500
 
6.0%
역 500
 
6.0%
로 492
 
5.9%
성 306
 
3.7%
수 215
 
2.6%
길 188
 
2.3%
Other values (249) 3124
37.4%
Decimal Number
ValueCountFrequency (%)
1 508
21.4%
3 325
13.7%
2 305
12.9%
0 258
10.9%
6 196
 
8.3%
5 190
 
8.0%
7 184
 
7.8%
4 175
 
7.4%
8 119
 
5.0%
9 110
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
A 5
33.3%
S 4
26.7%
L 2
 
13.3%
C 2
 
13.3%
M 1
 
6.7%
B 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 282
99.6%
. 1
 
0.4%
Space Separator
ValueCountFrequency (%)
2404
100.0%
Open Punctuation
ValueCountFrequency (%)
( 471
100.0%
Close Punctuation
ValueCountFrequency (%)
) 471
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 87
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8351
57.8%
Common 6086
42.1%
Latin 15
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1089
 
13.0%
동 742
 
8.9%
대 672
 
8.0%
시 523
 
6.3%
광 500
 
6.0%
역 500
 
6.0%
로 492
 
5.9%
성 306
 
3.7%
수 215
 
2.6%
길 188
 
2.3%
Other values (249) 3124
37.4%
Common
ValueCountFrequency (%)
2404
39.5%
1 508
 
8.3%
( 471
 
7.7%
) 471
 
7.7%
3 325
 
5.3%
2 305
 
5.0%
, 282
 
4.6%
0 258
 
4.2%
6 196
 
3.2%
5 190
 
3.1%
Other values (6) 676
 
11.1%
Latin
ValueCountFrequency (%)
A 5
33.3%
S 4
26.7%
L 2
 
13.3%
C 2
 
13.3%
M 1
 
6.7%
B 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8351
57.8%
ASCII 6101
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2404
39.4%
1 508
 
8.3%
( 471
 
7.7%
) 471
 
7.7%
3 325
 
5.3%
2 305
 
5.0%
, 282
 
4.6%
0 258
 
4.2%
6 196
 
3.2%
5 190
 
3.1%
Other values (12) 691
 
11.3%
Hangul
ValueCountFrequency (%)
구 1089
 
13.0%
동 742
 
8.9%
대 672
 
8.0%
시 523
 
6.3%
광 500
 
6.0%
역 500
 
6.0%
로 492
 
5.9%
성 306
 
3.7%
수 215
 
2.6%
길 188
 
2.3%
Other values (249) 3124
37.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct308
Distinct (%)62.0%
Missing17
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean51360.785
Minimum41005
Maximum711893
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-11T05:09:37.806358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41005
5-th percentile41143
Q141752
median42020
Q342420
95-th percentile42955.4
Maximum711893
Range670888
Interquartile range (IQR)668

Descriptive statistics

Standard deviation78174.315
Coefficient of variation (CV)1.5220623
Kurtosis66.706132
Mean51360.785
Median Absolute Deviation (MAD)307
Skewness8.2722686
Sum25526310
Variance6.1112235 × 109
MonotonicityNot monotonic
2023-12-11T05:09:38.031957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42013 40
 
7.8%
42020 21
 
4.1%
42027 11
 
2.1%
41589 10
 
1.9%
41777 6
 
1.2%
41946 5
 
1.0%
42699 5
 
1.0%
42253 5
 
1.0%
42125 5
 
1.0%
41155 4
 
0.8%
Other values (298) 385
74.9%
(Missing) 17
 
3.3%
ValueCountFrequency (%)
41005 2
0.4%
41009 1
0.2%
41018 1
0.2%
41034 1
0.2%
41046 1
0.2%
41047 1
0.2%
41049 1
0.2%
41070 1
0.2%
41075 1
0.2%
41076 2
0.4%
ValueCountFrequency (%)
711893 1
0.2%
711851 1
0.2%
706817 1
0.2%
701828 1
0.2%
700261 2
0.4%
700150 1
0.2%
43010 2
0.4%
43009 2
0.4%
43008 1
0.2%
43005 1
0.2%

사업장명
Text

Distinct493
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2023-12-11T05:09:38.389018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length9.3035019
Min length1

Characters and Unicode

Total characters4782
Distinct characters281
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique473 ?
Unique (%)92.0%

Sample

1st row유니온행정사사무소
2nd row행정사이상무사무소
3rd row대구행정사사무소
4th row동서행정사사무소
5th row천년문화재행정사사무소
ValueCountFrequency (%)
행정사 125
 
14.8%
사무소 99
 
11.8%
행정사사무소 43
 
5.1%
행정사무소 15
 
1.8%
일반행정사 11
 
1.3%
세무회계 3
 
0.4%
대경 3
 
0.4%
토탈행정사사무소 3
 
0.4%
정의 2
 
0.2%
전갑삼일반행정서사 2
 
0.2%
Other values (514) 536
63.7%
2023-12-11T05:09:38.998042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 872
18.2%
정 527
 
11.0%
행 484
 
10.1%
무 434
 
9.1%
소 424
 
8.9%
330
 
6.9%
일 81
 
1.7%
반 67
 
1.4%
김 66
 
1.4%
이 63
 
1.3%
Other values (271) 1434
30.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4416
92.3%
Space Separator 330
 
6.9%
Uppercase Letter 21
 
0.4%
Lowercase Letter 5
 
0.1%
Other Punctuation 3
 
0.1%
Decimal Number 3
 
0.1%
Math Symbol 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 872
19.7%
정 527
 
11.9%
행 484
 
11.0%
무 434
 
9.8%
소 424
 
9.6%
일 81
 
1.8%
반 67
 
1.5%
김 66
 
1.5%
이 63
 
1.4%
서 46
 
1.0%
Other values (244) 1352
30.6%
Uppercase Letter
ValueCountFrequency (%)
E 4
19.0%
K 3
14.3%
M 2
9.5%
J 2
9.5%
I 1
 
4.8%
P 1
 
4.8%
V 1
 
4.8%
S 1
 
4.8%
R 1
 
4.8%
O 1
 
4.8%
Other values (4) 4
19.0%
Lowercase Letter
ValueCountFrequency (%)
l 2
40.0%
a 1
20.0%
i 1
20.0%
z 1
20.0%
Other Punctuation
ValueCountFrequency (%)
& 2
66.7%
· 1
33.3%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
4 1
33.3%
Space Separator
ValueCountFrequency (%)
330
100.0%
Math Symbol
ValueCountFrequency (%)
∼ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4416
92.3%
Common 340
 
7.1%
Latin 26
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 872
19.7%
정 527
 
11.9%
행 484
 
11.0%
무 434
 
9.8%
소 424
 
9.6%
일 81
 
1.8%
반 67
 
1.5%
김 66
 
1.5%
이 63
 
1.4%
서 46
 
1.0%
Other values (244) 1352
30.6%
Latin
ValueCountFrequency (%)
E 4
15.4%
K 3
 
11.5%
M 2
 
7.7%
l 2
 
7.7%
J 2
 
7.7%
I 1
 
3.8%
P 1
 
3.8%
V 1
 
3.8%
S 1
 
3.8%
R 1
 
3.8%
Other values (8) 8
30.8%
Common
ValueCountFrequency (%)
330
97.1%
& 2
 
0.6%
1 2
 
0.6%
∼ 1
 
0.3%
- 1
 
0.3%
( 1
 
0.3%
4 1
 
0.3%
) 1
 
0.3%
· 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4416
92.3%
ASCII 364
 
7.6%
Math Operators 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 872
19.7%
정 527
 
11.9%
행 484
 
11.0%
무 434
 
9.8%
소 424
 
9.6%
일 81
 
1.8%
반 67
 
1.5%
김 66
 
1.5%
이 63
 
1.4%
서 46
 
1.0%
Other values (244) 1352
30.6%
ASCII
ValueCountFrequency (%)
330
90.7%
E 4
 
1.1%
K 3
 
0.8%
M 2
 
0.5%
& 2
 
0.5%
l 2
 
0.5%
J 2
 
0.5%
1 2
 
0.5%
I 1
 
0.3%
- 1
 
0.3%
Other values (15) 15
 
4.1%
Math Operators
ValueCountFrequency (%)
∼ 1
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct514
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0150282 × 1013
Minimum2.012121 × 1013
Maximum2.0191128 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-11T05:09:39.245757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.012121 × 1013
5-th percentile2.0121212 × 1013
Q12.0130128 × 1013
median2.0150113 × 1013
Q32.0170816 × 1013
95-th percentile2.0190525 × 1013
Maximum2.0191128 × 1013
Range6.9917942 × 1010
Interquartile range (IQR)4.0688262 × 1010

Descriptive statistics

Standard deviation2.3832032 × 1010
Coefficient of variation (CV)0.0011827146
Kurtosis-1.3019263
Mean2.0150282 × 1013
Median Absolute Deviation (MAD)1.9985959 × 1010
Skewness0.36904197
Sum1.0357245 × 1016
Variance5.6796577 × 1020
MonotonicityNot monotonic
2023-12-11T05:09:39.512595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20151211084922 1
 
0.2%
20130127180300 1
 
0.2%
20131101161458 1
 
0.2%
20180509142413 1
 
0.2%
20140310144207 1
 
0.2%
20150112104729 1
 
0.2%
20160829115116 1
 
0.2%
20150409114110 1
 
0.2%
20151123141208 1
 
0.2%
20160408135443 1
 
0.2%
Other values (504) 504
98.1%
ValueCountFrequency (%)
20121210143614 1
0.2%
20121210143849 1
0.2%
20121210152205 1
0.2%
20121210224048 1
0.2%
20121210224843 1
0.2%
20121210225559 1
0.2%
20121211152119 1
0.2%
20121211154312 1
0.2%
20121211155351 1
0.2%
20121211164124 1
0.2%
ValueCountFrequency (%)
20191128085303 1
0.2%
20191126165937 1
0.2%
20191117143034 1
0.2%
20191108180429 1
0.2%
20191108093108 1
0.2%
20191025165049 1
0.2%
20191023170549 1
0.2%
20191014180502 1
0.2%
20191014170946 1
0.2%
20191014102439 1
0.2%

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
I
472 
U
 
42

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 472
91.8%
U 42
 
8.2%

Length

2023-12-11T05:09:39.752414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:09:39.909962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 472
91.8%
u 42
 
8.2%

데이터갱신일자
Date

Distinct57
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
Minimum2018-11-26 13:44:42
Maximum2019-11-30 02:40:00
2023-12-11T05:09:40.072521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:09:40.308268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing514
Missing (%)100.0%
Memory size4.6 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct402
Distinct (%)81.4%
Missing20
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean344173.63
Minimum326871
Maximum358200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-11T05:09:40.591166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum326871
5-th percentile334888.26
Q1340758.57
median345466.71
Q3346978.17
95-th percentile353261.93
Maximum358200
Range31329
Interquartile range (IQR)6219.5983

Descriptive statistics

Standard deviation5353.5273
Coefficient of variation (CV)0.015554728
Kurtosis0.88232157
Mean344173.63
Median Absolute Deviation (MAD)2686.7425
Skewness-0.53214081
Sum1.7002177 × 108
Variance28660255
MonotonicityNot monotonic
2023-12-11T05:09:40.855184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
346942.691097 13
 
2.5%
346785.888453 6
 
1.2%
346824.368994 5
 
1.0%
345771.939379 5
 
1.0%
352958.852171 5
 
1.0%
342841.529621 5
 
1.0%
344204.522469 4
 
0.8%
347047.853931 4
 
0.8%
346968.034691 4
 
0.8%
338734.539877 3
 
0.6%
Other values (392) 440
85.6%
(Missing) 20
 
3.9%
ValueCountFrequency (%)
326871.0 1
0.2%
327511.362892 1
0.2%
327683.163129 1
0.2%
327853.173809 2
0.4%
328385.759632 1
0.2%
328437.0 1
0.2%
328454.835468 1
0.2%
330039.817716 1
0.2%
330407.953238 1
0.2%
330484.91238 1
0.2%
ValueCountFrequency (%)
358200.0 1
0.2%
356430.936586 1
0.2%
356310.917659 1
0.2%
356294.40891 1
0.2%
356287.192197 1
0.2%
356046.170437 1
0.2%
355943.824177 1
0.2%
355730.852718 1
0.2%
355685.598935 1
0.2%
355252.890804 1
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct402
Distinct (%)81.4%
Missing20
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean262992.22
Minimum240358.72
Maximum274171.71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-11T05:09:41.061954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum240358.72
5-th percentile257200.06
Q1261709.84
median263768.21
Q3264926.08
95-th percentile267723.49
Maximum274171.71
Range33812.987
Interquartile range (IQR)3216.2413

Descriptive statistics

Standard deviation4635.1382
Coefficient of variation (CV)0.017624621
Kurtosis9.8141596
Mean262992.22
Median Absolute Deviation (MAD)1417.7648
Skewness-2.4519948
Sum1.2991815 × 108
Variance21484507
MonotonicityNot monotonic
2023-12-11T05:09:41.269507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
263989.847737 13
 
2.5%
263768.205044 6
 
1.2%
263750.37553 5
 
1.0%
263103.285777 5
 
1.0%
261363.555778 5
 
1.0%
266514.126424 5
 
1.0%
265028.313376 4
 
0.8%
263623.058732 4
 
0.8%
263912.825583 4
 
0.8%
264959.713105 3
 
0.6%
Other values (392) 440
85.6%
(Missing) 20
 
3.9%
ValueCountFrequency (%)
240358.722944 2
0.4%
240602.0 1
0.2%
240717.492649 1
0.2%
240775.599214 1
0.2%
242011.0 1
0.2%
242062.498804 1
0.2%
242138.448546 1
0.2%
242394.720331 1
0.2%
244543.0 1
0.2%
244674.919516 1
0.2%
ValueCountFrequency (%)
274171.709713 1
0.2%
273712.082489 1
0.2%
273233.71206 1
0.2%
272799.665005 1
0.2%
272417.0 1
0.2%
272394.002904 1
0.2%
272309.461236 1
0.2%
272271.250409 1
0.2%
272229.951945 1
0.2%
271876.675858 1
0.2%

지정일자
Real number (ℝ)

Distinct413
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20087341
Minimum19820330
Maximum20191023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-11T05:09:41.947737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19820330
5-th percentile19960216
Q120040236
median20101068
Q320140328
95-th percentile20181112
Maximum20191023
Range370693
Interquartile range (IQR)100092.25

Descriptive statistics

Standard deviation72466.822
Coefficient of variation (CV)0.0036075866
Kurtosis0.078158763
Mean20087341
Median Absolute Deviation (MAD)50637
Skewness-0.68359256
Sum1.0324893 × 1010
Variance5.2514403 × 109
MonotonicityNot monotonic
2023-12-11T05:09:42.192963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19960216 19
 
3.7%
20121227 9
 
1.8%
20121220 7
 
1.4%
20121207 5
 
1.0%
20121228 5
 
1.0%
20180420 5
 
1.0%
20121217 4
 
0.8%
20170314 3
 
0.6%
20121204 3
 
0.6%
20180601 3
 
0.6%
Other values (403) 451
87.7%
ValueCountFrequency (%)
19820330 1
0.2%
19830109 1
0.2%
19840620 1
0.2%
19860311 1
0.2%
19871024 1
0.2%
19890526 1
0.2%
19911025 1
0.2%
19930430 1
0.2%
19940902 1
0.2%
19951106 1
0.2%
ValueCountFrequency (%)
20191023 1
0.2%
20191014 2
0.4%
20190917 1
0.2%
20190809 1
0.2%
20190702 1
0.2%
20190605 1
0.2%
20190530 1
0.2%
20190523 1
0.2%
20190521 1
0.2%
20190516 1
0.2%

변경순번
Categorical

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
<NA>
265 
1
231 
2
 
15
3
 
3

Length

Max length4
Median length4
Mean length2.5466926
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 265
51.6%
1 231
44.9%
2 15
 
2.9%
3 3
 
0.6%

Length

2023-12-11T05:09:42.423253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:09:42.601606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 265
51.6%
1 231
44.9%
2 15
 
2.9%
3 3
 
0.6%

변경처리일
Real number (ℝ)

MISSING 

Distinct204
Distinct (%)81.9%
Missing265
Missing (%)51.6%
Infinite0
Infinite (%)0.0%
Mean20158195
Minimum20121230
Maximum20191128
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-11T05:09:42.798530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20121230
5-th percentile20130101
Q120140320
median20160316
Q320180302
95-th percentile20190673
Maximum20191128
Range69898
Interquartile range (IQR)39982

Descriptive statistics

Standard deviation21775.424
Coefficient of variation (CV)0.0010802269
Kurtosis-1.2214767
Mean20158195
Median Absolute Deviation (MAD)19996
Skewness0.054815063
Sum5.0193906 × 109
Variance4.741691 × 108
MonotonicityNot monotonic
2023-12-11T05:09:43.047624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20130127 7
 
1.4%
20121231 6
 
1.2%
20130101 6
 
1.2%
20121230 5
 
1.0%
20171229 4
 
0.8%
20190118 3
 
0.6%
20131227 3
 
0.6%
20161230 3
 
0.6%
20191108 2
 
0.4%
20160803 2
 
0.4%
Other values (194) 208
40.5%
(Missing) 265
51.6%
ValueCountFrequency (%)
20121230 5
1.0%
20121231 6
1.2%
20130101 6
1.2%
20130127 7
1.4%
20130128 2
 
0.4%
20130206 1
 
0.2%
20130325 1
 
0.2%
20130328 1
 
0.2%
20130402 1
 
0.2%
20130404 1
 
0.2%
ValueCountFrequency (%)
20191128 1
0.2%
20191126 1
0.2%
20191114 1
0.2%
20191108 2
0.4%
20191025 1
0.2%
20191014 1
0.2%
20190924 1
0.2%
20190904 1
0.2%
20190903 1
0.2%
20190829 1
0.2%

민원종류명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
외국어번역행정사
258 
일반행정사
256 

Length

Max length8
Median length8
Mean length6.5058366
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
외국어번역행정사 258
50.2%
일반행정사 256
49.8%

Length

2023-12-11T05:09:43.307821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:09:43.523167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
외국어번역행정사 258
50.2%
일반행정사 256
49.8%

Sample

번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)지정일자변경순번변경처리일민원종류명
01행정사업11_50_03_P3410000341000020121920121227<NA>3폐업3폐업20151210<NA><NA><NA>053-425-5615<NA><NA><NA>대구광역시 중구 국채보상로 572, 403호 (전동)41935유니온행정사사무소20151211084922I2018-11-26 13:44:42.0<NA>343816.020297264554.62315120121227120151210일반행정사
12행정사업11_50_03_P3410000341000020193920190917<NA>1영업/정상1영업중<NA><NA><NA><NA><NA><NA><NA>대구광역시 중구 대봉동 47번지 21호대구광역시 중구 동덕로 54, 304호 (대봉동)41952행정사이상무사무소20191014180502I2019-10-16 00:22:51.0<NA>344880.319985263361.15230620190917120191014일반행정사
23행정사업11_50_03_P3410000341000020121720111031<NA>3폐업3폐업20190529<NA><NA><NA>053-252-0402<NA><NA><NA>대구광역시 중구 경상감영길 62 (서성로1가)700261대구행정사사무소20190529170053U2019-05-31 02:40:00.0<NA>343597.874905264638.58135720111031120190529일반행정사
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