Overview

Dataset statistics

Number of variables32
Number of observations522
Missing cells4523
Missing cells (%)27.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory141.3 KiB
Average record size in memory277.3 B

Variable types

Numeric14
Categorical9
Unsupported4
Text4
DateTime1

Dataset

Description6270000_대구광역시_11_50_03_P_행정사업_2월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000084278&dataSetDetailId=DDI_0000084304&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스ID has constant value ""Constant
데이터갱신구분 is highly imbalanced (53.8%)Imbalance
인허가취소일자 has 522 (100.0%) missing valuesMissing
폐업일자 has 376 (72.0%) missing valuesMissing
휴업시작일자 has 506 (96.9%) missing valuesMissing
휴업종료일자 has 506 (96.9%) missing valuesMissing
재개업일자 has 496 (95.0%) missing valuesMissing
소재지전화 has 134 (25.7%) missing valuesMissing
소재지면적 has 522 (100.0%) missing valuesMissing
소재지우편번호 has 522 (100.0%) missing valuesMissing
소재지전체주소 has 80 (15.3%) missing valuesMissing
도로명전체주소 has 17 (3.3%) missing valuesMissing
도로명우편번호 has 17 (3.3%) missing valuesMissing
업태구분명 has 522 (100.0%) missing valuesMissing
좌표정보(X) has 20 (3.8%) missing valuesMissing
좌표정보(Y) has 20 (3.8%) missing valuesMissing
변경처리일 has 263 (50.4%) 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 19:11:58.145198
Analysis finished2023-12-10 19:11:59.423718
Duration1.28 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct522
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean261.5
Minimum1
Maximum522
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-11T04:11:59.552426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile27.05
Q1131.25
median261.5
Q3391.75
95-th percentile495.95
Maximum522
Range521
Interquartile range (IQR)260.5

Descriptive statistics

Standard deviation150.83269
Coefficient of variation (CV)0.57679804
Kurtosis-1.2
Mean261.5
Median Absolute Deviation (MAD)130.5
Skewness0
Sum136503
Variance22750.5
MonotonicityStrictly increasing
2023-12-11T04:11:59.862438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
360 1
 
0.2%
358 1
 
0.2%
357 1
 
0.2%
356 1
 
0.2%
355 1
 
0.2%
354 1
 
0.2%
353 1
 
0.2%
352 1
 
0.2%
351 1
 
0.2%
Other values (512) 512
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 (%)
522 1
0.2%
521 1
0.2%
520 1
0.2%
519 1
0.2%
518 1
0.2%
517 1
0.2%
516 1
0.2%
515 1
0.2%
514 1
0.2%
513 1
0.2%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
행정사업
522 

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 522
100.0%

Length

2023-12-11T04:12:00.122766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:12:00.331186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
행정사업 522
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
11_50_03_P
522 

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 522
100.0%

Length

2023-12-11T04:12:00.576679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:12:00.804328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11_50_03_p 522
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3450402.3
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-11T04:12:01.015215image/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 deviation20362.149
Coefficient of variation (CV)0.005901384
Kurtosis-0.76911376
Mean3450402.3
Median Absolute Deviation (MAD)10000
Skewness-0.65448354
Sum1.80111 × 109
Variance4.1461712 × 108
MonotonicityIncreasing
2023-12-11T04:12:01.269799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3460000 194
37.2%
3470000 77
 
14.8%
3420000 65
 
12.5%
3450000 57
 
10.9%
3430000 39
 
7.5%
3410000 36
 
6.9%
3480000 36
 
6.9%
3440000 18
 
3.4%
ValueCountFrequency (%)
3410000 36
 
6.9%
3420000 65
 
12.5%
3430000 39
 
7.5%
3440000 18
 
3.4%
3450000 57
 
10.9%
3460000 194
37.2%
3470000 77
 
14.8%
3480000 36
 
6.9%
ValueCountFrequency (%)
3480000 36
 
6.9%
3470000 77
 
14.8%
3460000 194
37.2%
3450000 57
 
10.9%
3440000 18
 
3.4%
3430000 39
 
7.5%
3420000 65
 
12.5%
3410000 36
 
6.9%

관리번호
Real number (ℝ)

UNIQUE 

Distinct522
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.4235753 × 1012
Minimum3.4100002 × 1011
Maximum3.4600002 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-11T04:12:01.514555image/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 deviation1.275764 × 1013
Coefficient of variation (CV)1.3538004
Kurtosis0.16689271
Mean9.4235753 × 1012
Median Absolute Deviation (MAD)3 × 1010
Skewness1.4580262
Sum4.9191063 × 1015
Variance1.6275738 × 1026
MonotonicityNot monotonic
2023-12-11T04:12:01.779686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3410000201219 1
 
0.2%
346000020123 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%
3460000201230 1
 
0.2%
3460000201231 1
 
0.2%
Other values (512) 512
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 (%)
34600002020210 1
0.2%
34600002020209 1
0.2%
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%

인허가일자
Real number (ℝ)

Distinct418
Distinct (%)80.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20088443
Minimum19820330
Maximum20200220
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-11T04:12:02.121724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19820330
5-th percentile19960216
Q120040349
median20101116
Q320147940
95-th percentile20181128
Maximum20200220
Range379890
Interquartile range (IQR)107590.75

Descriptive statistics

Standard deviation72824.601
Coefficient of variation (CV)0.0036251988
Kurtosis0.060092251
Mean20088443
Median Absolute Deviation (MAD)50861.5
Skewness-0.67876125
Sum1.0486167 × 1010
Variance5.3034225 × 109
MonotonicityNot monotonic
2023-12-11T04:12:02.359173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19960216 19
 
3.6%
20121227 9
 
1.7%
20121220 7
 
1.3%
20121228 5
 
1.0%
20180420 5
 
1.0%
20121207 5
 
1.0%
20121217 4
 
0.8%
20170314 3
 
0.6%
19960129 3
 
0.6%
20121205 3
 
0.6%
Other values (408) 459
87.9%
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 (%)
20200220 1
0.2%
20200217 1
0.2%
20200102 1
0.2%
20191220 1
0.2%
20191023 1
0.2%
20191014 2
0.4%
20190917 1
0.2%
20190809 1
0.2%
20190702 1
0.2%
20190605 1
0.2%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing522
Missing (%)100.0%
Memory size4.7 KiB

영업상태구분코드
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
1
359 
3
147 
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 (%)
1 359
68.8%
3 147
28.2%
2 16
 
3.1%

Length

2023-12-11T04:12:02.599947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:12:03.111125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 359
68.8%
3 147
28.2%
2 16
 
3.1%

영업상태명
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
영업/정상
359 
폐업
147 
휴업
 
16

Length

Max length5
Median length5
Mean length4.0632184
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 359
68.8%
폐업 147
28.2%
휴업 16
 
3.1%

Length

2023-12-11T04:12:03.268843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:12:03.434213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 359
68.8%
폐업 147
28.2%
휴업 16
 
3.1%

상세영업상태코드
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
1
359 
3
147 
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 (%)
1 359
68.8%
3 147
28.2%
2 16
 
3.1%

Length

2023-12-11T04:12:03.581061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:12:03.734129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 359
68.8%
3 147
28.2%
2 16
 
3.1%

상세영업상태명
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
영업중
359 
폐업
147 
휴업
 
16

Length

Max length3
Median length3
Mean length2.6877395
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 359
68.8%
폐업 147
28.2%
휴업 16
 
3.1%

Length

2023-12-11T04:12:03.920790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:12:04.084744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 359
68.8%
폐업 147
28.2%
휴업 16
 
3.1%

폐업일자
Real number (ℝ)

MISSING 

Distinct131
Distinct (%)89.7%
Missing376
Missing (%)72.0%
Infinite0
Infinite (%)0.0%
Mean20158834
Minimum20120227
Maximum20200220
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-11T04:12:04.281544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20120227
5-th percentile20130418
Q120140721
median20155716
Q320180324
95-th percentile20191127
Maximum20200220
Range79993
Interquartile range (IQR)39603

Descriptive statistics

Standard deviation21316.991
Coefficient of variation (CV)0.0010574516
Kurtosis-1.0768422
Mean20158834
Median Absolute Deviation (MAD)15398
Skewness0.31727738
Sum2.9431897 × 109
Variance4.5441408 × 108
MonotonicityNot monotonic
2023-12-11T04:12:04.528188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20171229 4
 
0.8%
20131227 3
 
0.6%
20140328 2
 
0.4%
20150130 2
 
0.4%
20160731 2
 
0.4%
20131219 2
 
0.4%
20180504 2
 
0.4%
20200131 2
 
0.4%
20131230 2
 
0.4%
20140721 2
 
0.4%
Other values (121) 123
 
23.6%
(Missing) 376
72.0%
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 (%)
20200220 1
0.2%
20200131 2
0.4%
20200128 1
0.2%
20200122 1
0.2%
20191231 1
0.2%
20191213 1
0.2%
20191127 1
0.2%
20191126 1
0.2%
20191111 1
0.2%
20191025 1
0.2%

휴업시작일자
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)50.0%
Missing506
Missing (%)96.9%
Infinite0
Infinite (%)0.0%
Mean20136514
Minimum20090123
Maximum20190924
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-11T04:12:04.712504image/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
2023-12-11T04:12:04.829966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
20121231 8
 
1.5%
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) 506
96.9%
ValueCountFrequency (%)
20090123 2
 
0.4%
20121231 8
1.5%
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
1.5%
20090123 2
 
0.4%

휴업종료일자
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)43.8%
Missing506
Missing (%)96.9%
Infinite0
Infinite (%)0.0%
Mean20164790
Minimum20141231
Maximum20220923
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-11T04:12:04.969635image/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
2023-12-11T04:12:05.162512image/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) 506
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 

Distinct25
Distinct (%)96.2%
Missing496
Missing (%)95.0%
Infinite0
Infinite (%)0.0%
Mean20172946
Minimum20140128
Maximum20200110
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-11T04:12:05.375807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20140128
5-th percentile20142762
Q120160541
median20180360
Q320190330
95-th percentile20197856
Maximum20200110
Range59982
Interquartile range (IQR)29788.75

Descriptive statistics

Standard deviation18336.92
Coefficient of variation (CV)0.0009089857
Kurtosis-1.1329634
Mean20172946
Median Absolute Deviation (MAD)10596
Skewness-0.31675689
Sum5.244966 × 108
Variance3.3624263 × 108
MonotonicityNot monotonic
2023-12-11T04:12:05.562413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
20151021 2
 
0.4%
20180302 1
 
0.2%
20191108 1
 
0.2%
20200106 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%
Other values (15) 15
 
2.9%
(Missing) 496
95.0%
ValueCountFrequency (%)
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%
20170717 1
0.2%
ValueCountFrequency (%)
20200110 1
0.2%
20200106 1
0.2%
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%

소재지전화
Text

MISSING 

Distinct374
Distinct (%)96.4%
Missing134
Missing (%)25.7%
Memory size4.2 KiB
2023-12-11T04:12:05.964935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.412371
Min length1

Characters and Unicode

Total characters4428
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

Unique361 ?
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%
053-321-4902 2
 
0.5%
053 2
 
0.5%
053-753-3300 2
 
0.5%
053-355-5546 2
 
0.5%
070-4085-9997 2
 
0.5%
053-627-7576 2
 
0.5%
053-791-8484 2
 
0.5%
0537412941 2
 
0.5%
Other values (365) 369
94.6%
2023-12-11T04:12:06.518549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 711
16.1%
0 623
14.1%
3 612
13.8%
- 569
12.9%
7 328
7.4%
2 294
6.6%
6 286
6.5%
4 275
 
6.2%
1 265
 
6.0%
8 241
 
5.4%
Other values (3) 224
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3856
87.1%
Dash Punctuation 569
 
12.9%
Space Separator 2
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 711
18.4%
0 623
16.2%
3 612
15.9%
7 328
8.5%
2 294
7.6%
6 286
7.4%
4 275
 
7.1%
1 265
 
6.9%
8 241
 
6.2%
9 221
 
5.7%
Dash Punctuation
ValueCountFrequency (%)
- 569
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4428
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 711
16.1%
0 623
14.1%
3 612
13.8%
- 569
12.9%
7 328
7.4%
2 294
6.6%
6 286
6.5%
4 275
 
6.2%
1 265
 
6.0%
8 241
 
5.4%
Other values (3) 224
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4428
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 711
16.1%
0 623
14.1%
3 612
13.8%
- 569
12.9%
7 328
7.4%
2 294
6.6%
6 286
6.5%
4 275
 
6.2%
1 265
 
6.0%
8 241
 
5.4%
Other values (3) 224
 
5.1%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing522
Missing (%)100.0%
Memory size4.7 KiB

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing522
Missing (%)100.0%
Memory size4.7 KiB

소재지전체주소
Text

MISSING 

Distinct410
Distinct (%)92.8%
Missing80
Missing (%)15.3%
Memory size4.2 KiB
2023-12-11T04:12:07.064157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length42
Mean length26.047511
Min length12

Characters and Unicode

Total characters11513
Distinct characters236
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

Unique386 ?
Unique (%)87.3%

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 442
 
17.7%
수성구 190
 
7.6%
범어동 102
 
4.1%
동구 61
 
2.4%
1호 57
 
2.3%
북구 52
 
2.1%
달서구 38
 
1.5%
서구 37
 
1.5%
2호 32
 
1.3%
3호 31
 
1.2%
Other values (693) 1453
58.2%
2023-12-11T04:12:07.817501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2058
17.9%
구 869
 
7.5%
1 586
 
5.1%
동 558
 
4.8%
지 473
 
4.1%
대 471
 
4.1%
호 465
 
4.0%
시 456
 
4.0%
광 445
 
3.9%
역 444
 
3.9%
Other values (226) 4688
40.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7044
61.2%
Decimal Number 2393
 
20.8%
Space Separator 2058
 
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 869
12.3%
동 558
 
7.9%
지 473
 
6.7%
대 471
 
6.7%
호 465
 
6.6%
시 456
 
6.5%
광 445
 
6.3%
역 444
 
6.3%
번 436
 
6.2%
성 284
 
4.0%
Other values (209) 2143
30.4%
Decimal Number
ValueCountFrequency (%)
1 586
24.5%
2 296
12.4%
0 293
12.2%
3 258
10.8%
4 192
 
8.0%
5 183
 
7.6%
7 164
 
6.9%
9 144
 
6.0%
6 139
 
5.8%
8 138
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
A 7
50.0%
S 4
28.6%
C 2
 
14.3%
B 1
 
7.1%
Space Separator
ValueCountFrequency (%)
2058
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7044
61.2%
Common 4454
38.7%
Latin 15
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 869
12.3%
동 558
 
7.9%
지 473
 
6.7%
대 471
 
6.7%
호 465
 
6.6%
시 456
 
6.5%
광 445
 
6.3%
역 444
 
6.3%
번 436
 
6.2%
성 284
 
4.0%
Other values (209) 2143
30.4%
Common
ValueCountFrequency (%)
2058
46.2%
1 586
 
13.2%
2 296
 
6.6%
0 293
 
6.6%
3 258
 
5.8%
4 192
 
4.3%
5 183
 
4.1%
7 164
 
3.7%
9 144
 
3.2%
6 139
 
3.1%
Other values (2) 141
 
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 7044
61.2%
ASCII 4469
38.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2058
46.1%
1 586
 
13.1%
2 296
 
6.6%
0 293
 
6.6%
3 258
 
5.8%
4 192
 
4.3%
5 183
 
4.1%
7 164
 
3.7%
9 144
 
3.2%
6 139
 
3.1%
Other values (7) 156
 
3.5%
Hangul
ValueCountFrequency (%)
구 869
12.3%
동 558
 
7.9%
지 473
 
6.7%
대 471
 
6.7%
호 465
 
6.6%
시 456
 
6.5%
광 445
 
6.3%
역 444
 
6.3%
번 436
 
6.2%
성 284
 
4.0%
Other values (209) 2143
30.4%

도로명전체주소
Text

MISSING 

Distinct452
Distinct (%)89.5%
Missing17
Missing (%)3.3%
Memory size4.2 KiB
2023-12-11T04:12:08.367018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length50
Mean length29.10099
Min length19

Characters and Unicode

Total characters14696
Distinct characters282
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

Unique418 ?
Unique (%)82.8%

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 505
 
17.1%
수성구 184
 
6.2%
범어동 100
 
3.4%
달서구 75
 
2.5%
동구 65
 
2.2%
동대구로 64
 
2.2%
북구 58
 
2.0%
서구 38
 
1.3%
중구 36
 
1.2%
달성군 31
 
1.1%
Other values (877) 1794
60.8%
2023-12-11T04:12:09.186845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2445
 
16.6%
구 1104
 
7.5%
동 755
 
5.1%
대 680
 
4.6%
시 531
 
3.6%
1 514
 
3.5%
역 508
 
3.5%
광 508
 
3.5%
로 500
 
3.4%
( 477
 
3.2%
Other values (272) 6674
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8487
57.8%
Space Separator 2445
 
16.6%
Decimal Number 2416
 
16.4%
Open Punctuation 477
 
3.2%
Close Punctuation 477
 
3.2%
Other Punctuation 290
 
2.0%
Dash Punctuation 89
 
0.6%
Uppercase Letter 15
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1104
 
13.0%
동 755
 
8.9%
대 680
 
8.0%
시 531
 
6.3%
역 508
 
6.0%
광 508
 
6.0%
로 500
 
5.9%
성 310
 
3.7%
수 217
 
2.6%
길 193
 
2.3%
Other values (250) 3181
37.5%
Decimal Number
ValueCountFrequency (%)
1 514
21.3%
3 334
13.8%
2 313
13.0%
0 262
10.8%
6 202
 
8.4%
5 197
 
8.2%
7 185
 
7.7%
4 180
 
7.5%
8 119
 
4.9%
9 110
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
A 5
33.3%
S 4
26.7%
C 2
 
13.3%
L 2
 
13.3%
M 1
 
6.7%
B 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 289
99.7%
. 1
 
0.3%
Space Separator
ValueCountFrequency (%)
2445
100.0%
Open Punctuation
ValueCountFrequency (%)
( 477
100.0%
Close Punctuation
ValueCountFrequency (%)
) 477
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 89
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8487
57.8%
Common 6194
42.1%
Latin 15
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1104
 
13.0%
동 755
 
8.9%
대 680
 
8.0%
시 531
 
6.3%
역 508
 
6.0%
광 508
 
6.0%
로 500
 
5.9%
성 310
 
3.7%
수 217
 
2.6%
길 193
 
2.3%
Other values (250) 3181
37.5%
Common
ValueCountFrequency (%)
2445
39.5%
1 514
 
8.3%
( 477
 
7.7%
) 477
 
7.7%
3 334
 
5.4%
2 313
 
5.1%
, 289
 
4.7%
0 262
 
4.2%
6 202
 
3.3%
5 197
 
3.2%
Other values (6) 684
 
11.0%
Latin
ValueCountFrequency (%)
A 5
33.3%
S 4
26.7%
C 2
 
13.3%
L 2
 
13.3%
M 1
 
6.7%
B 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8487
57.8%
ASCII 6209
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2445
39.4%
1 514
 
8.3%
( 477
 
7.7%
) 477
 
7.7%
3 334
 
5.4%
2 313
 
5.0%
, 289
 
4.7%
0 262
 
4.2%
6 202
 
3.3%
5 197
 
3.2%
Other values (12) 699
 
11.3%
Hangul
ValueCountFrequency (%)
구 1104
 
13.0%
동 755
 
8.9%
대 680
 
8.0%
시 531
 
6.3%
역 508
 
6.0%
광 508
 
6.0%
로 500
 
5.9%
성 310
 
3.7%
수 217
 
2.6%
길 193
 
2.3%
Other values (250) 3181
37.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct310
Distinct (%)61.4%
Missing17
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean51211.814
Minimum41005
Maximum711893
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-11T04:12:09.387981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41005
5-th percentile41146
Q141716
median42020
Q342420
95-th percentile42962.6
Maximum711893
Range670888
Interquartile range (IQR)704

Descriptive statistics

Standard deviation77560.357
Coefficient of variation (CV)1.5145013
Kurtosis67.849272
Mean51211.814
Median Absolute Deviation (MAD)309
Skewness8.3410483
Sum25861966
Variance6.015609 × 109
MonotonicityNot monotonic
2023-12-11T04:12:09.568803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42013 40
 
7.7%
42020 21
 
4.0%
42027 11
 
2.1%
41589 10
 
1.9%
41777 6
 
1.1%
42125 5
 
1.0%
42699 5
 
1.0%
41946 5
 
1.0%
42253 5
 
1.0%
41155 4
 
0.8%
Other values (300) 393
75.3%
(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 3
0.6%
43009 2
0.4%
43008 1
 
0.2%
43005 1
 
0.2%

사업장명
Text

Distinct500
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
2023-12-11T04:12:09.824574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length9.2969349
Min length1

Characters and Unicode

Total characters4853
Distinct characters284
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

Unique479 ?
Unique (%)91.8%

Sample

1st row유니온행정사사무소
2nd row행정사이상무사무소
3rd row대구행정사사무소
4th row동서행정사사무소
5th row천년문화재행정사사무소
ValueCountFrequency (%)
행정사 126
 
14.8%
사무소 100
 
11.7%
행정사사무소 44
 
5.2%
행정사무소 15
 
1.8%
일반행정사 11
 
1.3%
대경 3
 
0.4%
세무회계 3
 
0.4%
토탈행정사사무소 3
 
0.4%
공인대구번역행정사 2
 
0.2%
국제행정사무소 2
 
0.2%
Other values (521) 544
63.8%
2023-12-11T04:12:10.271342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 887
18.3%
정 536
 
11.0%
행 492
 
10.1%
무 441
 
9.1%
소 431
 
8.9%
333
 
6.9%
일 81
 
1.7%
반 67
 
1.4%
김 66
 
1.4%
이 64
 
1.3%
Other values (274) 1455
30.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4481
92.3%
Space Separator 333
 
6.9%
Uppercase Letter 24
 
0.5%
Lowercase Letter 5
 
0.1%
Other Punctuation 3
 
0.1%
Decimal Number 3
 
0.1%
Dash Punctuation 1
 
< 0.1%
Math Symbol 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 887
19.8%
정 536
 
12.0%
행 492
 
11.0%
무 441
 
9.8%
소 431
 
9.6%
일 81
 
1.8%
반 67
 
1.5%
김 66
 
1.5%
이 64
 
1.4%
서 46
 
1.0%
Other values (246) 1370
30.6%
Uppercase Letter
ValueCountFrequency (%)
E 4
16.7%
K 4
16.7%
J 2
 
8.3%
M 2
 
8.3%
B 2
 
8.3%
G 1
 
4.2%
V 1
 
4.2%
I 1
 
4.2%
P 1
 
4.2%
S 1
 
4.2%
Other values (5) 5
20.8%
Lowercase Letter
ValueCountFrequency (%)
l 2
40.0%
a 1
20.0%
z 1
20.0%
i 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 (%)
333
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Math Symbol
ValueCountFrequency (%)
∼ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4481
92.3%
Common 343
 
7.1%
Latin 29
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 887
19.8%
정 536
 
12.0%
행 492
 
11.0%
무 441
 
9.8%
소 431
 
9.6%
일 81
 
1.8%
반 67
 
1.5%
김 66
 
1.5%
이 64
 
1.4%
서 46
 
1.0%
Other values (246) 1370
30.6%
Latin
ValueCountFrequency (%)
E 4
13.8%
K 4
13.8%
J 2
 
6.9%
M 2
 
6.9%
B 2
 
6.9%
l 2
 
6.9%
G 1
 
3.4%
V 1
 
3.4%
I 1
 
3.4%
P 1
 
3.4%
Other values (9) 9
31.0%
Common
ValueCountFrequency (%)
333
97.1%
& 2
 
0.6%
1 2
 
0.6%
- 1
 
0.3%
∼ 1
 
0.3%
4 1
 
0.3%
· 1
 
0.3%
) 1
 
0.3%
( 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4481
92.3%
ASCII 370
 
7.6%
Math Operators 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 887
19.8%
정 536
 
12.0%
행 492
 
11.0%
무 441
 
9.8%
소 431
 
9.6%
일 81
 
1.8%
반 67
 
1.5%
김 66
 
1.5%
이 64
 
1.4%
서 46
 
1.0%
Other values (246) 1370
30.6%
ASCII
ValueCountFrequency (%)
333
90.0%
E 4
 
1.1%
K 4
 
1.1%
J 2
 
0.5%
M 2
 
0.5%
& 2
 
0.5%
B 2
 
0.5%
1 2
 
0.5%
l 2
 
0.5%
- 1
 
0.3%
Other values (16) 16
 
4.3%
Math Operators
ValueCountFrequency (%)
∼ 1
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct522
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0151776 × 1013
Minimum2.012121 × 1013
Maximum2.0200225 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-11T04:12:10.470989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.012121 × 1013
5-th percentile2.0121212 × 1013
Q12.0130128 × 1013
median2.0150203 × 1013
Q32.0171115 × 1013
95-th percentile2.0190923 × 1013
Maximum2.0200225 × 1013
Range7.9015037 × 1010
Interquartile range (IQR)4.0987203 × 1010

Descriptive statistics

Standard deviation2.4884556 × 1010
Coefficient of variation (CV)0.0012348567
Kurtosis-1.2770222
Mean2.0151776 × 1013
Median Absolute Deviation (MAD)2.0075933 × 1010
Skewness0.35796832
Sum1.0519227 × 1016
Variance6.1924112 × 1020
MonotonicityNot monotonic
2023-12-11T04:12:10.679993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20151211084922 1
 
0.2%
20131101161458 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%
20121231165241 1
 
0.2%
20121231165815 1
 
0.2%
Other values (512) 512
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 (%)
20200225180255 1
0.2%
20200225114133 1
0.2%
20200220143333 1
0.2%
20200220135315 1
0.2%
20200218180136 1
0.2%
20200217162332 1
0.2%
20200211174008 1
0.2%
20200131150103 1
0.2%
20200128152448 1
0.2%
20200122155640 1
0.2%

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
I
471 
U
51 

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 471
90.2%
U 51
 
9.8%

Length

2023-12-11T04:12:10.863844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:12:11.004512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 471
90.2%
u 51
 
9.8%

데이터갱신일자
Date

Distinct72
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
Minimum2018-11-26 13:44:42
Maximum2020-02-27 02:40:00
2023-12-11T04:12:11.132383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:12:11.306404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing522
Missing (%)100.0%
Memory size4.7 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct410
Distinct (%)81.7%
Missing20
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean344188.68
Minimum326871
Maximum358200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-11T04:12:11.467606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum326871
5-th percentile334884.33
Q1340761.52
median345494.51
Q3346990.25
95-th percentile353177.7
Maximum358200
Range31329
Interquartile range (IQR)6228.7315

Descriptive statistics

Standard deviation5379.7282
Coefficient of variation (CV)0.015630172
Kurtosis0.93393892
Mean344188.68
Median Absolute Deviation (MAD)2683.0569
Skewness-0.57579593
Sum1.7278272 × 108
Variance28941476
MonotonicityNot monotonic
2023-12-11T04:12:11.649626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
346942.691097 13
 
2.5%
346785.888453 6
 
1.1%
352958.852171 5
 
1.0%
342841.529621 5
 
1.0%
346824.368994 5
 
1.0%
345771.939379 5
 
1.0%
344204.522469 4
 
0.8%
346968.034691 4
 
0.8%
347047.853931 4
 
0.8%
338338.227438 3
 
0.6%
Other values (400) 448
85.8%
(Missing) 20
 
3.8%
ValueCountFrequency (%)
326871.0 1
0.2%
327511.362892 1
0.2%
327683.163129 1
0.2%
327723.104095 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%
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 

Distinct410
Distinct (%)81.7%
Missing20
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean262947.79
Minimum240358.72
Maximum274171.71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-11T04:12:11.848437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum240358.72
5-th percentile257159.1
Q1261709.84
median263768.21
Q3264956.46
95-th percentile267638.08
Maximum274171.71
Range33812.987
Interquartile range (IQR)3246.6188

Descriptive statistics

Standard deviation4729.6729
Coefficient of variation (CV)0.017987118
Kurtosis9.5485304
Mean262947.79
Median Absolute Deviation (MAD)1431.903
Skewness-2.4655664
Sum1.3199979 × 108
Variance22369805
MonotonicityNot monotonic
2023-12-11T04:12:12.044957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
263989.847737 13
 
2.5%
263768.205044 6
 
1.1%
261363.555778 5
 
1.0%
266514.126424 5
 
1.0%
263750.37553 5
 
1.0%
263103.285777 5
 
1.0%
265028.313376 4
 
0.8%
263912.825583 4
 
0.8%
263623.058732 4
 
0.8%
259813.308952 3
 
0.6%
Other values (400) 448
85.8%
(Missing) 20
 
3.8%
ValueCountFrequency (%)
240358.722944 2
0.4%
240602.0 1
0.2%
240717.492649 1
0.2%
240775.599214 1
0.2%
240811.478411 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%
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)

Distinct418
Distinct (%)80.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20088443
Minimum19820330
Maximum20200220
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-11T04:12:12.235421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19820330
5-th percentile19960216
Q120040349
median20101116
Q320147940
95-th percentile20181128
Maximum20200220
Range379890
Interquartile range (IQR)107590.75

Descriptive statistics

Standard deviation72824.601
Coefficient of variation (CV)0.0036251988
Kurtosis0.060092251
Mean20088443
Median Absolute Deviation (MAD)50861.5
Skewness-0.67876125
Sum1.0486167 × 1010
Variance5.3034225 × 109
MonotonicityNot monotonic
2023-12-11T04:12:12.453278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19960216 19
 
3.6%
20121227 9
 
1.7%
20121220 7
 
1.3%
20121228 5
 
1.0%
20180420 5
 
1.0%
20121207 5
 
1.0%
20121217 4
 
0.8%
20170314 3
 
0.6%
19960129 3
 
0.6%
20121205 3
 
0.6%
Other values (408) 459
87.9%
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 (%)
20200220 1
0.2%
20200217 1
0.2%
20200102 1
0.2%
20191220 1
0.2%
20191023 1
0.2%
20191014 2
0.4%
20190917 1
0.2%
20190809 1
0.2%
20190702 1
0.2%
20190605 1
0.2%

변경순번
Categorical

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
263 
1
241 
2
 
15
3
 
3

Length

Max length4
Median length4
Mean length2.5114943
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 263
50.4%
1 241
46.2%
2 15
 
2.9%
3 3
 
0.6%

Length

2023-12-11T04:12:12.652034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:12:13.152565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 263
50.4%
1 241
46.2%
2 15
 
2.9%
3 3
 
0.6%

변경처리일
Real number (ℝ)

MISSING 

Distinct213
Distinct (%)82.2%
Missing263
Missing (%)50.4%
Infinite0
Infinite (%)0.0%
Mean20160084
Minimum20121230
Maximum20200225
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-11T04:12:13.319028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20121230
5-th percentile20130101
Q120140414
median20160513
Q320180512
95-th percentile20191126
Maximum20200225
Range78995
Interquartile range (IQR)40097.5

Descriptive statistics

Standard deviation22904.165
Coefficient of variation (CV)0.0011361146
Kurtosis-1.1901332
Mean20160084
Median Absolute Deviation (MAD)20012
Skewness0.066577358
Sum5.2214617 × 109
Variance5.2460077 × 108
MonotonicityNot monotonic
2023-12-11T04:12:13.578685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20130127 7
 
1.3%
20130101 6
 
1.1%
20121231 6
 
1.1%
20121230 5
 
1.0%
20171229 4
 
0.8%
20190118 3
 
0.6%
20131227 3
 
0.6%
20161230 3
 
0.6%
20160803 2
 
0.4%
20151116 2
 
0.4%
Other values (203) 218
41.8%
(Missing) 263
50.4%
ValueCountFrequency (%)
20121230 5
1.0%
20121231 6
1.1%
20130101 6
1.1%
20130127 7
1.3%
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 (%)
20200225 1
0.2%
20200220 1
0.2%
20200218 1
0.2%
20200211 1
0.2%
20200131 1
0.2%
20200128 1
0.2%
20200122 1
0.2%
20200117 1
0.2%
20200110 1
0.2%
20200106 2
0.4%

민원종류명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
일반행정사
267 
외국어번역행정사
255 

Length

Max length8
Median length5
Mean length6.4655172
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반행정사 267
51.1%
외국어번역행정사 255
48.9%

Length

2023-12-11T04:12:13.840083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:12:14.012147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반행정사 267
51.1%
외국어번역행정사 255
48.9%

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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