Overview

Dataset statistics

Number of variables30
Number of observations805
Missing cells7473
Missing cells (%)30.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory199.8 KiB
Average record size in memory254.2 B

Variable types

Categorical7
Numeric7
DateTime4
Unsupported5
Text7

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),업소구분명,소재지,지정일자,신청일자,항목값1
Author마포구
URLhttps://data.seoul.go.kr/dataList/OA-19465/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업상태코드 is highly imbalanced (65.4%)Imbalance
영업상태명 is highly imbalanced (65.4%)Imbalance
상세영업상태명 is highly imbalanced (68.4%)Imbalance
인허가취소일자 has 805 (100.0%) missing valuesMissing
폐업일자 has 634 (78.8%) missing valuesMissing
휴업시작일자 has 766 (95.2%) missing valuesMissing
휴업종료일자 has 805 (100.0%) missing valuesMissing
재개업일자 has 805 (100.0%) missing valuesMissing
전화번호 has 227 (28.2%) missing valuesMissing
소재지면적 has 805 (100.0%) missing valuesMissing
소재지우편번호 has 740 (91.9%) missing valuesMissing
지번주소 has 187 (23.2%) missing valuesMissing
도로명주소 has 11 (1.4%) missing valuesMissing
도로명우편번호 has 11 (1.4%) missing valuesMissing
업태구분명 has 805 (100.0%) missing valuesMissing
좌표정보(X) has 19 (2.4%) missing valuesMissing
좌표정보(Y) has 19 (2.4%) missing valuesMissing
소재지 has 395 (49.1%) missing valuesMissing
지정일자 has 224 (27.8%) missing valuesMissing
신청일자 has 215 (26.7%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
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 started2024-05-11 06:46:01.946912
Analysis finished2024-05-11 06:46:03.337269
Duration1.39 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
3130000
805 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3130000
2nd row3130000
3rd row3130000
4th row3130000
5th row3130000

Common Values

ValueCountFrequency (%)
3130000 805
100.0%

Length

2024-05-11T15:46:03.490322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:46:03.715377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3130000 805
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct805
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1300001 × 1017
Minimum3.1300001 × 1017
Maximum3.1300001 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-05-11T15:46:03.893861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.1300001 × 1017
5-th percentile3.1300001 × 1017
Q13.1300001 × 1017
median3.1300001 × 1017
Q33.1300001 × 1017
95-th percentile3.1300001 × 1017
Maximum3.1300001 × 1017
Range1400018
Interquartile range (IQR)500096

Descriptive statistics

Standard deviation281261.15
Coefficient of variation (CV)8.9859789 × 10-13
Kurtosis-1.0153589
Mean3.1300001 × 1017
Median Absolute Deviation (MAD)200000
Skewness-0.34517512
Sum-6.2894056 × 1018
Variance7.9107835 × 1010
MonotonicityStrictly increasing
2024-05-11T15:46:04.130240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
313000014201000001 1
 
0.1%
313000014202100127 1
 
0.1%
313000014202100117 1
 
0.1%
313000014202100118 1
 
0.1%
313000014202100119 1
 
0.1%
313000014202100120 1
 
0.1%
313000014202100121 1
 
0.1%
313000014202100122 1
 
0.1%
313000014202100123 1
 
0.1%
313000014202100124 1
 
0.1%
Other values (795) 795
98.8%
ValueCountFrequency (%)
313000014201000001 1
0.1%
313000014201000002 1
0.1%
313000014201000003 1
0.1%
313000014201400001 1
0.1%
313000014201400002 1
0.1%
313000014201400003 1
0.1%
313000014201400004 1
0.1%
313000014201400005 1
0.1%
313000014201400006 1
0.1%
313000014201400007 1
0.1%
ValueCountFrequency (%)
313000014202400019 1
0.1%
313000014202400018 1
0.1%
313000014202400017 1
0.1%
313000014202400016 1
0.1%
313000014202400015 1
0.1%
313000014202400014 1
0.1%
313000014202400011 1
0.1%
313000014202400010 1
0.1%
313000014202400009 1
0.1%
313000014202400008 1
0.1%

인허가일자
Date

Distinct242
Distinct (%)30.1%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
Minimum2010-11-16 00:00:00
Maximum2024-04-23 00:00:00
2024-05-11T15:46:04.387324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:04.617353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing805
Missing (%)100.0%
Memory size7.2 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
1
631 
3
169 
4
 
2
5
 
2
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 631
78.4%
3 169
 
21.0%
4 2
 
0.2%
5 2
 
0.2%
2 1
 
0.1%

Length

2024-05-11T15:46:04.784548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:46:04.922531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 631
78.4%
3 169
 
21.0%
4 2
 
0.2%
5 2
 
0.2%
2 1
 
0.1%

영업상태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
영업/정상
631 
폐업
169 
취소/말소/만료/정지/중지
 
2
제외/삭제/전출
 
2
휴업
 
1

Length

Max length14
Median length5
Mean length4.3962733
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 631
78.4%
폐업 169
 
21.0%
취소/말소/만료/정지/중지 2
 
0.2%
제외/삭제/전출 2
 
0.2%
휴업 1
 
0.1%

Length

2024-05-11T15:46:05.082123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:46:05.232208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 631
78.4%
폐업 169
 
21.0%
취소/말소/만료/정지/중지 2
 
0.2%
제외/삭제/전출 2
 
0.2%
휴업 1
 
0.1%

상세영업상태코드
Real number (ℝ)

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.0521739
Minimum0
Maximum11
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-05-11T15:46:05.361626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q111
median11
Q311
95-th percentile11
Maximum11
Range11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.7032003
Coefficient of variation (CV)0.40909513
Kurtosis-0.080585801
Mean9.0521739
Median Absolute Deviation (MAD)0
Skewness-1.381606
Sum7287
Variance13.713692
MonotonicityNot monotonic
2024-05-11T15:46:05.492013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
11 630
78.3%
2 169
 
21.0%
4 2
 
0.2%
5 2
 
0.2%
0 1
 
0.1%
1 1
 
0.1%
ValueCountFrequency (%)
0 1
 
0.1%
1 1
 
0.1%
2 169
 
21.0%
4 2
 
0.2%
5 2
 
0.2%
11 630
78.3%
ValueCountFrequency (%)
11 630
78.3%
5 2
 
0.2%
4 2
 
0.2%
2 169
 
21.0%
1 1
 
0.1%
0 1
 
0.1%

상세영업상태명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
영업
630 
폐업
169 
폐쇄
 
2
제외사항
 
2
<NA>
 
1

Length

Max length4
Median length2
Mean length2.0074534
Min length2

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
영업 630
78.3%
폐업 169
 
21.0%
폐쇄 2
 
0.2%
제외사항 2
 
0.2%
<NA> 1
 
0.1%
휴업 1
 
0.1%

Length

2024-05-11T15:46:05.996564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:46:06.161284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 630
78.3%
폐업 169
 
21.0%
폐쇄 2
 
0.2%
제외사항 2
 
0.2%
na 1
 
0.1%
휴업 1
 
0.1%

폐업일자
Date

MISSING 

Distinct53
Distinct (%)31.0%
Missing634
Missing (%)78.8%
Memory size6.4 KiB
Minimum2014-12-05 00:00:00
Maximum2024-03-22 00:00:00
2024-05-11T15:46:06.332497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:06.500771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Real number (ℝ)

MISSING 

Distinct22
Distinct (%)56.4%
Missing766
Missing (%)95.2%
Infinite0
Infinite (%)0.0%
Mean20181269
Minimum20160928
Maximum20211014
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-05-11T15:46:06.649914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20160928
5-th percentile20161011
Q120171121
median20181023
Q320190408
95-th percentile20191034
Maximum20211014
Range50086
Interquartile range (IQR)19287

Descriptive statistics

Standard deviation10862.224
Coefficient of variation (CV)0.00053823294
Kurtosis0.10586665
Mean20181269
Median Absolute Deviation (MAD)9797
Skewness0.055037214
Sum7.8706949 × 108
Variance1.1798791 × 108
MonotonicityNot monotonic
2024-05-11T15:46:06.815871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
20171121 4
 
0.5%
20181023 4
 
0.5%
20180419 4
 
0.5%
20190822 3
 
0.4%
20191024 2
 
0.2%
20190408 2
 
0.2%
20171226 2
 
0.2%
20190214 2
 
0.2%
20190613 2
 
0.2%
20190111 2
 
0.2%
Other values (12) 12
 
1.5%
(Missing) 766
95.2%
ValueCountFrequency (%)
20160928 1
 
0.1%
20161004 1
 
0.1%
20161012 1
 
0.1%
20170307 1
 
0.1%
20170822 1
 
0.1%
20170825 1
 
0.1%
20171012 1
 
0.1%
20171121 4
0.5%
20171226 2
0.2%
20180418 1
 
0.1%
ValueCountFrequency (%)
20211014 1
 
0.1%
20191119 1
 
0.1%
20191024 2
0.2%
20190822 3
0.4%
20190613 2
0.2%
20190408 2
0.2%
20190403 1
 
0.1%
20190214 2
0.2%
20190111 2
0.2%
20181023 4
0.5%

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing805
Missing (%)100.0%
Memory size7.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing805
Missing (%)100.0%
Memory size7.2 KiB

전화번호
Text

MISSING 

Distinct545
Distinct (%)94.3%
Missing227
Missing (%)28.2%
Memory size6.4 KiB
2024-05-11T15:46:07.138314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length10.738754
Min length7

Characters and Unicode

Total characters6207
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

Unique517 ?
Unique (%)89.4%

Sample

1st row3088295
2nd row3732233
3rd row3023788
4th row02-714-1761
5th row02-3144-4815
ValueCountFrequency (%)
02-313-7689 4
 
0.7%
02-324-8247 3
 
0.5%
1577-9621 3
 
0.5%
02-703-8645 3
 
0.5%
715-2218 2
 
0.3%
02-3143-6980 2
 
0.3%
02-797-5050 2
 
0.3%
02-324-4555 2
 
0.3%
02-365-5901 2
 
0.3%
02-322-8559 2
 
0.3%
Other values (535) 553
95.7%
2024-05-11T15:46:07.673700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1062
17.1%
2 986
15.9%
3 899
14.5%
0 863
13.9%
7 486
7.8%
1 446
7.2%
4 323
 
5.2%
6 308
 
5.0%
5 308
 
5.0%
8 269
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5145
82.9%
Dash Punctuation 1062
 
17.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 986
19.2%
3 899
17.5%
0 863
16.8%
7 486
9.4%
1 446
8.7%
4 323
 
6.3%
6 308
 
6.0%
5 308
 
6.0%
8 269
 
5.2%
9 257
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 1062
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6207
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1062
17.1%
2 986
15.9%
3 899
14.5%
0 863
13.9%
7 486
7.8%
1 446
7.2%
4 323
 
5.2%
6 308
 
5.0%
5 308
 
5.0%
8 269
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6207
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1062
17.1%
2 986
15.9%
3 899
14.5%
0 863
13.9%
7 486
7.8%
1 446
7.2%
4 323
 
5.2%
6 308
 
5.0%
5 308
 
5.0%
8 269
 
4.3%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing805
Missing (%)100.0%
Memory size7.2 KiB

소재지우편번호
Text

MISSING 

Distinct44
Distinct (%)67.7%
Missing740
Missing (%)91.9%
Memory size6.4 KiB
2024-05-11T15:46:07.921204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1076923
Min length6

Characters and Unicode

Total characters397
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

Unique32 ?
Unique (%)49.2%

Sample

1st row121270
2nd row121270
3rd row121270
4th row121876
5th row121843
ValueCountFrequency (%)
121876 4
 
6.2%
121270 4
 
6.2%
121838 4
 
6.2%
121818 3
 
4.6%
121837 3
 
4.6%
121904 3
 
4.6%
121010 2
 
3.1%
121850 2
 
3.1%
121841 2
 
3.1%
121829 2
 
3.1%
Other values (34) 36
55.4%
2024-05-11T15:46:08.439414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 145
36.5%
2 78
19.6%
8 63
15.9%
0 27
 
6.8%
7 17
 
4.3%
3 15
 
3.8%
6 14
 
3.5%
9 11
 
2.8%
4 11
 
2.8%
5 9
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 390
98.2%
Dash Punctuation 7
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 145
37.2%
2 78
20.0%
8 63
16.2%
0 27
 
6.9%
7 17
 
4.4%
3 15
 
3.8%
6 14
 
3.6%
9 11
 
2.8%
4 11
 
2.8%
5 9
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 397
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 145
36.5%
2 78
19.6%
8 63
15.9%
0 27
 
6.8%
7 17
 
4.3%
3 15
 
3.8%
6 14
 
3.5%
9 11
 
2.8%
4 11
 
2.8%
5 9
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 397
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 145
36.5%
2 78
19.6%
8 63
15.9%
0 27
 
6.8%
7 17
 
4.3%
3 15
 
3.8%
6 14
 
3.5%
9 11
 
2.8%
4 11
 
2.8%
5 9
 
2.3%

지번주소
Text

MISSING 

Distinct572
Distinct (%)92.6%
Missing187
Missing (%)23.2%
Memory size6.4 KiB
2024-05-11T15:46:08.758964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length43
Mean length23.804207
Min length14

Characters and Unicode

Total characters14711
Distinct characters283
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

Unique529 ?
Unique (%)85.6%

Sample

1st row서울특별시 마포구 상암동 1689번지 상암월드컵파크6단지상가 105호
2nd row서울특별시 마포구 상암동 31-6번지
3rd row서울특별시 마포구 상암동 상암2택지개발사업지구상가9단지105
4th row서울특별시 마포구 용강동 473-1번지
5th row서울특별시 마포구 성산동 53-2번지
ValueCountFrequency (%)
서울특별시 618
21.5%
마포구 617
21.4%
서교동 114
 
4.0%
성산동 58
 
2.0%
망원동 48
 
1.7%
아현동 45
 
1.6%
상암동 44
 
1.5%
도화동 35
 
1.2%
공덕동 35
 
1.2%
합정동 28
 
1.0%
Other values (832) 1236
42.9%
2024-05-11T15:46:09.227482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2664
18.1%
서 744
 
5.1%
동 670
 
4.6%
마 669
 
4.5%
포 667
 
4.5%
시 639
 
4.3%
구 625
 
4.2%
울 620
 
4.2%
별 618
 
4.2%
특 618
 
4.2%
Other values (273) 6177
42.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8766
59.6%
Decimal Number 2687
 
18.3%
Space Separator 2664
 
18.1%
Dash Punctuation 477
 
3.2%
Uppercase Letter 81
 
0.6%
Lowercase Letter 12
 
0.1%
Other Punctuation 11
 
0.1%
Close Punctuation 5
 
< 0.1%
Open Punctuation 5
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 744
 
8.5%
동 670
 
7.6%
마 669
 
7.6%
포 667
 
7.6%
시 639
 
7.3%
구 625
 
7.1%
울 620
 
7.1%
별 618
 
7.0%
특 618
 
7.0%
지 170
 
1.9%
Other values (227) 2726
31.1%
Uppercase Letter
ValueCountFrequency (%)
D 9
11.1%
M 9
11.1%
C 9
11.1%
T 6
 
7.4%
E 5
 
6.2%
S 5
 
6.2%
K 5
 
6.2%
P 4
 
4.9%
G 4
 
4.9%
R 4
 
4.9%
Other values (10) 21
25.9%
Decimal Number
ValueCountFrequency (%)
1 514
19.1%
3 349
13.0%
4 330
12.3%
2 302
11.2%
5 270
10.0%
7 217
8.1%
6 217
8.1%
0 174
 
6.5%
9 159
 
5.9%
8 155
 
5.8%
Lowercase Letter
ValueCountFrequency (%)
e 2
16.7%
y 2
16.7%
t 2
16.7%
i 2
16.7%
c 1
8.3%
w 1
8.3%
r 1
8.3%
o 1
8.3%
Other Punctuation
ValueCountFrequency (%)
, 10
90.9%
. 1
 
9.1%
Space Separator
ValueCountFrequency (%)
2664
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 477
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8766
59.6%
Common 5851
39.8%
Latin 94
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 744
 
8.5%
동 670
 
7.6%
마 669
 
7.6%
포 667
 
7.6%
시 639
 
7.3%
구 625
 
7.1%
울 620
 
7.1%
별 618
 
7.0%
특 618
 
7.0%
지 170
 
1.9%
Other values (227) 2726
31.1%
Latin
ValueCountFrequency (%)
D 9
 
9.6%
M 9
 
9.6%
C 9
 
9.6%
T 6
 
6.4%
E 5
 
5.3%
S 5
 
5.3%
K 5
 
5.3%
P 4
 
4.3%
G 4
 
4.3%
R 4
 
4.3%
Other values (19) 34
36.2%
Common
ValueCountFrequency (%)
2664
45.5%
1 514
 
8.8%
- 477
 
8.2%
3 349
 
6.0%
4 330
 
5.6%
2 302
 
5.2%
5 270
 
4.6%
7 217
 
3.7%
6 217
 
3.7%
0 174
 
3.0%
Other values (7) 337
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8766
59.6%
ASCII 5944
40.4%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2664
44.8%
1 514
 
8.6%
- 477
 
8.0%
3 349
 
5.9%
4 330
 
5.6%
2 302
 
5.1%
5 270
 
4.5%
7 217
 
3.7%
6 217
 
3.7%
0 174
 
2.9%
Other values (35) 430
 
7.2%
Hangul
ValueCountFrequency (%)
서 744
 
8.5%
동 670
 
7.6%
마 669
 
7.6%
포 667
 
7.6%
시 639
 
7.3%
구 625
 
7.1%
울 620
 
7.1%
별 618
 
7.0%
특 618
 
7.0%
지 170
 
1.9%
Other values (227) 2726
31.1%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

도로명주소
Text

MISSING 

Distinct742
Distinct (%)93.5%
Missing11
Missing (%)1.4%
Memory size6.4 KiB
2024-05-11T15:46:09.570025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length49
Mean length30.993703
Min length21

Characters and Unicode

Total characters24609
Distinct characters316
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

Unique693 ?
Unique (%)87.3%

Sample

1st row서울특별시 마포구 토정로 271, 1층 (용강동, 대현빌딩)
2nd row서울특별시 마포구 월드컵북로 121 (성산동)
3rd row서울특별시 마포구 포은로 27, 1층 (합정동)
4th row서울특별시 마포구 토정로 38, 101호 (합정동, 국토빌)
5th row서울특별시 마포구 구룡길 19, C동 101층 (상암동, 상암한화오벨리스크)
ValueCountFrequency (%)
서울특별시 794
 
16.1%
마포구 793
 
16.1%
1층 275
 
5.6%
서교동 134
 
2.7%
성산동 79
 
1.6%
망원동 72
 
1.5%
상암동 54
 
1.1%
아현동 48
 
1.0%
공덕동 45
 
0.9%
월드컵북로 44
 
0.9%
Other values (906) 2592
52.6%
2024-05-11T15:46:10.116451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4136
 
16.8%
1 1137
 
4.6%
서 957
 
3.9%
동 932
 
3.8%
포 920
 
3.7%
마 919
 
3.7%
시 821
 
3.3%
울 816
 
3.3%
구 803
 
3.3%
) 799
 
3.2%
Other values (306) 12369
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14621
59.4%
Space Separator 4136
 
16.8%
Decimal Number 3362
 
13.7%
Close Punctuation 799
 
3.2%
Open Punctuation 799
 
3.2%
Other Punctuation 697
 
2.8%
Uppercase Letter 106
 
0.4%
Dash Punctuation 66
 
0.3%
Lowercase Letter 18
 
0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 957
 
6.5%
동 932
 
6.4%
포 920
 
6.3%
마 919
 
6.3%
시 821
 
5.6%
울 816
 
5.6%
구 803
 
5.5%
특 794
 
5.4%
별 794
 
5.4%
로 745
 
5.1%
Other values (258) 6120
41.9%
Uppercase Letter
ValueCountFrequency (%)
C 15
14.2%
B 13
12.3%
M 11
10.4%
D 11
10.4%
K 6
 
5.7%
T 6
 
5.7%
S 5
 
4.7%
E 5
 
4.7%
L 4
 
3.8%
N 4
 
3.8%
Other values (10) 26
24.5%
Decimal Number
ValueCountFrequency (%)
1 1137
33.8%
2 452
 
13.4%
0 307
 
9.1%
3 297
 
8.8%
4 251
 
7.5%
5 223
 
6.6%
6 191
 
5.7%
7 174
 
5.2%
9 169
 
5.0%
8 161
 
4.8%
Lowercase Letter
ValueCountFrequency (%)
b 5
27.8%
t 2
 
11.1%
e 2
 
11.1%
y 2
 
11.1%
i 2
 
11.1%
c 1
 
5.6%
a 1
 
5.6%
r 1
 
5.6%
w 1
 
5.6%
o 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 694
99.6%
. 3
 
0.4%
Space Separator
ValueCountFrequency (%)
4136
100.0%
Close Punctuation
ValueCountFrequency (%)
) 799
100.0%
Open Punctuation
ValueCountFrequency (%)
( 799
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 66
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14621
59.4%
Common 9862
40.1%
Latin 126
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 957
 
6.5%
동 932
 
6.4%
포 920
 
6.3%
마 919
 
6.3%
시 821
 
5.6%
울 816
 
5.6%
구 803
 
5.5%
특 794
 
5.4%
별 794
 
5.4%
로 745
 
5.1%
Other values (258) 6120
41.9%
Latin
ValueCountFrequency (%)
C 15
 
11.9%
B 13
 
10.3%
M 11
 
8.7%
D 11
 
8.7%
K 6
 
4.8%
T 6
 
4.8%
b 5
 
4.0%
S 5
 
4.0%
E 5
 
4.0%
L 4
 
3.2%
Other values (21) 45
35.7%
Common
ValueCountFrequency (%)
4136
41.9%
1 1137
 
11.5%
) 799
 
8.1%
( 799
 
8.1%
, 694
 
7.0%
2 452
 
4.6%
0 307
 
3.1%
3 297
 
3.0%
4 251
 
2.5%
5 223
 
2.3%
Other values (7) 767
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14621
59.4%
ASCII 9986
40.6%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4136
41.4%
1 1137
 
11.4%
) 799
 
8.0%
( 799
 
8.0%
, 694
 
6.9%
2 452
 
4.5%
0 307
 
3.1%
3 297
 
3.0%
4 251
 
2.5%
5 223
 
2.2%
Other values (37) 891
 
8.9%
Hangul
ValueCountFrequency (%)
서 957
 
6.5%
동 932
 
6.4%
포 920
 
6.3%
마 919
 
6.3%
시 821
 
5.6%
울 816
 
5.6%
구 803
 
5.5%
특 794
 
5.4%
별 794
 
5.4%
로 745
 
5.1%
Other values (258) 6120
41.9%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%

도로명우편번호
Text

MISSING 

Distinct305
Distinct (%)38.4%
Missing11
Missing (%)1.4%
Memory size6.4 KiB
2024-05-11T15:46:10.620212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.1057935
Min length5

Characters and Unicode

Total characters4054
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

Unique101 ?
Unique (%)12.7%

Sample

1st row121876
2nd row121843
3rd row121886
4th row121883
5th row121270
ValueCountFrequency (%)
03938 11
 
1.4%
04002 10
 
1.3%
04057 9
 
1.1%
03964 9
 
1.1%
03930 8
 
1.0%
04059 8
 
1.0%
04129 7
 
0.9%
04034 7
 
0.9%
03925 6
 
0.8%
04031 6
 
0.8%
Other values (295) 713
89.8%
2024-05-11T15:46:11.209892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1176
29.0%
4 661
16.3%
1 517
12.8%
9 385
 
9.5%
3 378
 
9.3%
2 252
 
6.2%
8 211
 
5.2%
7 165
 
4.1%
5 163
 
4.0%
6 140
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4048
99.9%
Dash Punctuation 6
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1176
29.1%
4 661
16.3%
1 517
12.8%
9 385
 
9.5%
3 378
 
9.3%
2 252
 
6.2%
8 211
 
5.2%
7 165
 
4.1%
5 163
 
4.0%
6 140
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4054
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1176
29.0%
4 661
16.3%
1 517
12.8%
9 385
 
9.5%
3 378
 
9.3%
2 252
 
6.2%
8 211
 
5.2%
7 165
 
4.1%
5 163
 
4.0%
6 140
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4054
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1176
29.0%
4 661
16.3%
1 517
12.8%
9 385
 
9.5%
3 378
 
9.3%
2 252
 
6.2%
8 211
 
5.2%
7 165
 
4.1%
5 163
 
4.0%
6 140
 
3.5%

사업장명
Text

Distinct766
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2024-05-11T15:46:11.513892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length19
Mean length9.3378882
Min length1

Characters and Unicode

Total characters7517
Distinct characters402
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

Unique731 ?
Unique (%)90.8%

Sample

1st row하모니24 상암6단지점
2nd row(주)다은유통
3rd row열린할인마트
4th row드림디포
5th rowGS25 마포성산점
ValueCountFrequency (%)
씨유 110
 
8.5%
세븐일레븐 101
 
7.8%
gs25 68
 
5.3%
지에스25 36
 
2.8%
이마트24 31
 
2.4%
지에스(gs)25 10
 
0.8%
미니스톱 10
 
0.8%
주식회사 10
 
0.8%
cu 9
 
0.7%
주)코리아세븐 8
 
0.6%
Other values (779) 896
69.5%
2024-05-11T15:46:11.997720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 520
 
6.9%
484
 
6.4%
마 310
 
4.1%
븐 261
 
3.5%
2 220
 
2.9%
5 178
 
2.4%
유 173
 
2.3%
씨 167
 
2.2%
포 160
 
2.1%
스 155
 
2.1%
Other values (392) 4889
65.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5984
79.6%
Decimal Number 485
 
6.5%
Space Separator 484
 
6.4%
Uppercase Letter 319
 
4.2%
Close Punctuation 89
 
1.2%
Open Punctuation 88
 
1.2%
Lowercase Letter 54
 
0.7%
Other Symbol 8
 
0.1%
Other Punctuation 4
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 520
 
8.7%
마 310
 
5.2%
븐 261
 
4.4%
유 173
 
2.9%
씨 167
 
2.8%
포 160
 
2.7%
스 155
 
2.6%
일 150
 
2.5%
트 147
 
2.5%
세 146
 
2.4%
Other values (347) 3795
63.4%
Uppercase Letter
ValueCountFrequency (%)
S 118
37.0%
G 117
36.7%
C 24
 
7.5%
U 15
 
4.7%
M 5
 
1.6%
K 5
 
1.6%
L 4
 
1.3%
I 3
 
0.9%
D 3
 
0.9%
Y 3
 
0.9%
Other values (11) 22
 
6.9%
Decimal Number
ValueCountFrequency (%)
2 220
45.4%
5 178
36.7%
4 37
 
7.6%
1 16
 
3.3%
3 14
 
2.9%
6 8
 
1.6%
7 7
 
1.4%
0 2
 
0.4%
8 2
 
0.4%
9 1
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
s 20
37.0%
g 15
27.8%
c 7
 
13.0%
u 6
 
11.1%
k 5
 
9.3%
l 1
 
1.9%
Other Punctuation
ValueCountFrequency (%)
& 2
50.0%
. 1
25.0%
? 1
25.0%
Space Separator
ValueCountFrequency (%)
484
100.0%
Close Punctuation
ValueCountFrequency (%)
) 89
100.0%
Open Punctuation
ValueCountFrequency (%)
( 88
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5992
79.7%
Common 1152
 
15.3%
Latin 373
 
5.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 520
 
8.7%
마 310
 
5.2%
븐 261
 
4.4%
유 173
 
2.9%
씨 167
 
2.8%
포 160
 
2.7%
스 155
 
2.6%
일 150
 
2.5%
트 147
 
2.5%
세 146
 
2.4%
Other values (348) 3803
63.5%
Latin
ValueCountFrequency (%)
S 118
31.6%
G 117
31.4%
C 24
 
6.4%
s 20
 
5.4%
g 15
 
4.0%
U 15
 
4.0%
c 7
 
1.9%
u 6
 
1.6%
k 5
 
1.3%
M 5
 
1.3%
Other values (17) 41
 
11.0%
Common
ValueCountFrequency (%)
484
42.0%
2 220
19.1%
5 178
 
15.5%
) 89
 
7.7%
( 88
 
7.6%
4 37
 
3.2%
1 16
 
1.4%
3 14
 
1.2%
6 8
 
0.7%
7 7
 
0.6%
Other values (7) 11
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5984
79.6%
ASCII 1525
 
20.3%
None 8
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 520
 
8.7%
마 310
 
5.2%
븐 261
 
4.4%
유 173
 
2.9%
씨 167
 
2.8%
포 160
 
2.7%
스 155
 
2.6%
일 150
 
2.5%
트 147
 
2.5%
세 146
 
2.4%
Other values (347) 3795
63.4%
ASCII
ValueCountFrequency (%)
484
31.7%
2 220
14.4%
5 178
 
11.7%
S 118
 
7.7%
G 117
 
7.7%
) 89
 
5.8%
( 88
 
5.8%
4 37
 
2.4%
C 24
 
1.6%
s 20
 
1.3%
Other values (34) 150
 
9.8%
None
ValueCountFrequency (%)
㈜ 8
100.0%

최종수정일자
Date

Distinct804
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
Minimum2010-12-02 16:44:01
Maximum2024-04-23 17:23:23
2024-05-11T15:46:12.170949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:12.331363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
I
462 
U
343 

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 462
57.4%
U 343
42.6%

Length

2024-05-11T15:46:12.490641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:46:12.642993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 462
57.4%
u 343
42.6%

데이터갱신일자
Date

Distinct203
Distinct (%)25.2%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 22:05:00
2024-05-11T15:46:12.843045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:13.051047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing805
Missing (%)100.0%
Memory size7.2 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct666
Distinct (%)84.7%
Missing19
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean193355.85
Minimum189212.74
Maximum196702.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-05-11T15:46:13.234002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189212.74
5-th percentile190527.13
Q1192039.75
median193102.34
Q3194989.33
95-th percentile196159.74
Maximum196702.05
Range7489.3123
Interquartile range (IQR)2949.5764

Descriptive statistics

Standard deviation1773.6372
Coefficient of variation (CV)0.0091729175
Kurtosis-0.88542226
Mean193355.85
Median Absolute Deviation (MAD)1383.756
Skewness0.04465144
Sum1.519777 × 108
Variance3145789.1
MonotonicityNot monotonic
2024-05-11T15:46:13.431080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
192311.642580307 7
 
0.9%
195852.524254164 4
 
0.5%
191263.451931121 4
 
0.5%
195766.588069694 3
 
0.4%
192773.485248028 3
 
0.4%
192639.20704379 3
 
0.4%
192505.813067066 3
 
0.4%
192407.856156312 3
 
0.4%
195835.448021829 3
 
0.4%
195422.34197138 3
 
0.4%
Other values (656) 750
93.2%
(Missing) 19
 
2.4%
ValueCountFrequency (%)
189212.737535822 1
0.1%
189315.310470024 1
0.1%
189337.0 1
0.1%
189378.0 1
0.1%
189392.975995366 1
0.1%
189461.587933606 1
0.1%
189520.410979113 1
0.1%
189520.465145926 1
0.1%
189586.493821292 1
0.1%
189592.30107511 1
0.1%
ValueCountFrequency (%)
196702.04987465 1
0.1%
196699.188309549 1
0.1%
196660.618569254 1
0.1%
196659.241554945 1
0.1%
196616.185721389 1
0.1%
196594.39064686 1
0.1%
196583.868057127 1
0.1%
196576.645261532 1
0.1%
196552.593993299 1
0.1%
196549.907298732 1
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct666
Distinct (%)84.7%
Missing19
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean450296.25
Minimum448229.06
Maximum454136.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-05-11T15:46:13.620789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum448229.06
5-th percentile448787.97
Q1449588.39
median450191.56
Q3450702.43
95-th percentile452750.67
Maximum454136.9
Range5907.8372
Interquartile range (IQR)1114.0382

Descriptive statistics

Standard deviation1091.2633
Coefficient of variation (CV)0.0024234341
Kurtosis1.0197799
Mean450296.25
Median Absolute Deviation (MAD)570.20319
Skewness0.95173213
Sum3.5393285 × 108
Variance1190855.6
MonotonicityNot monotonic
2024-05-11T15:46:13.803690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
449855.643910445 7
 
0.9%
448575.779442887 4
 
0.5%
452207.500653521 4
 
0.5%
449083.306922623 3
 
0.4%
449597.533762388 3
 
0.4%
450191.171275812 3
 
0.4%
449766.110553102 3
 
0.4%
449823.062441616 3
 
0.4%
450370.13541991 3
 
0.4%
448592.809876038 3
 
0.4%
Other values (656) 750
93.2%
(Missing) 19
 
2.4%
ValueCountFrequency (%)
448229.063825491 2
0.2%
448265.495016598 1
0.1%
448274.441478548 1
0.1%
448276.965250949 1
0.1%
448305.518618358 1
0.1%
448336.153416428 1
0.1%
448393.658663222 1
0.1%
448396.633869719 1
0.1%
448452.378072345 1
0.1%
448470.97363262 1
0.1%
ValueCountFrequency (%)
454136.901035 1
0.1%
453872.42578746 1
0.1%
453685.545865753 1
0.1%
453685.460423342 1
0.1%
453647.190988422 1
0.1%
453618.0 1
0.1%
453614.583448105 1
0.1%
453469.0 1
0.1%
453468.379147545 1
0.1%
453367.521771928 1
0.1%

업소구분명
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
지정
575 
<NA>
215 
종료
 
15

Length

Max length4
Median length2
Mean length2.5341615
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지정 575
71.4%
<NA> 215
 
26.7%
종료 15
 
1.9%

Length

2024-05-11T15:46:13.981427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:46:14.128175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지정 575
71.4%
na 215
 
26.7%
종료 15
 
1.9%

소재지
Text

MISSING 

Distinct401
Distinct (%)97.8%
Missing395
Missing (%)49.1%
Memory size6.4 KiB
2024-05-11T15:46:14.469027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length43
Mean length23.746341
Min length16

Characters and Unicode

Total characters9736
Distinct characters248
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique392 ?
Unique (%)95.6%

Sample

1st row서울특별시 마포구 상암동 1689번지 상암월드컵파크6단지상가 105호
2nd row서울특별시 마포구 상암동 31번지 6호
3rd row서울특별시 마포구 상암동 상암2택지개발사업지구상가9단지 105
4th row서울특별시 마포구 용강동 473번지 1호
5th row서울특별시 마포구 성산동 53번지 2호
ValueCountFrequency (%)
서울특별시 410
20.4%
마포구 410
20.4%
서교동 72
 
3.6%
성산동 35
 
1.7%
망원동 32
 
1.6%
상암동 29
 
1.4%
아현동 27
 
1.3%
도화동 24
 
1.2%
동교동 21
 
1.0%
공덕동 20
 
1.0%
Other values (627) 927
46.2%
2024-05-11T15:46:15.145532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1597
 
16.4%
서 490
 
5.0%
동 451
 
4.6%
마 443
 
4.6%
포 442
 
4.5%
시 421
 
4.3%
구 414
 
4.3%
울 410
 
4.2%
별 410
 
4.2%
특 410
 
4.2%
Other values (238) 4248
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6012
61.8%
Decimal Number 1826
 
18.8%
Space Separator 1597
 
16.4%
Dash Punctuation 217
 
2.2%
Uppercase Letter 59
 
0.6%
Lowercase Letter 9
 
0.1%
Other Punctuation 6
 
0.1%
Open Punctuation 4
 
< 0.1%
Close Punctuation 4
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 490
 
8.2%
동 451
 
7.5%
마 443
 
7.4%
포 442
 
7.4%
시 421
 
7.0%
구 414
 
6.9%
울 410
 
6.8%
별 410
 
6.8%
특 410
 
6.8%
지 188
 
3.1%
Other values (193) 1933
32.2%
Uppercase Letter
ValueCountFrequency (%)
M 6
 
10.2%
D 6
 
10.2%
C 5
 
8.5%
T 5
 
8.5%
K 5
 
8.5%
S 4
 
6.8%
B 3
 
5.1%
R 3
 
5.1%
N 3
 
5.1%
A 3
 
5.1%
Other values (10) 16
27.1%
Decimal Number
ValueCountFrequency (%)
1 372
20.4%
3 248
13.6%
4 226
12.4%
2 205
11.2%
5 180
9.9%
7 146
 
8.0%
6 132
 
7.2%
0 115
 
6.3%
9 101
 
5.5%
8 101
 
5.5%
Lowercase Letter
ValueCountFrequency (%)
e 2
22.2%
c 1
11.1%
t 1
11.1%
i 1
11.1%
w 1
11.1%
o 1
11.1%
r 1
11.1%
y 1
11.1%
Other Punctuation
ValueCountFrequency (%)
, 5
83.3%
. 1
 
16.7%
Space Separator
ValueCountFrequency (%)
1597
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 217
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6012
61.8%
Common 3656
37.6%
Latin 68
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 490
 
8.2%
동 451
 
7.5%
마 443
 
7.4%
포 442
 
7.4%
시 421
 
7.0%
구 414
 
6.9%
울 410
 
6.8%
별 410
 
6.8%
특 410
 
6.8%
지 188
 
3.1%
Other values (193) 1933
32.2%
Latin
ValueCountFrequency (%)
M 6
 
8.8%
D 6
 
8.8%
C 5
 
7.4%
T 5
 
7.4%
K 5
 
7.4%
S 4
 
5.9%
B 3
 
4.4%
R 3
 
4.4%
N 3
 
4.4%
A 3
 
4.4%
Other values (18) 25
36.8%
Common
ValueCountFrequency (%)
1597
43.7%
1 372
 
10.2%
3 248
 
6.8%
4 226
 
6.2%
- 217
 
5.9%
2 205
 
5.6%
5 180
 
4.9%
7 146
 
4.0%
6 132
 
3.6%
0 115
 
3.1%
Other values (7) 218
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6012
61.8%
ASCII 3724
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1597
42.9%
1 372
 
10.0%
3 248
 
6.7%
4 226
 
6.1%
- 217
 
5.8%
2 205
 
5.5%
5 180
 
4.8%
7 146
 
3.9%
6 132
 
3.5%
0 115
 
3.1%
Other values (35) 286
 
7.7%
Hangul
ValueCountFrequency (%)
서 490
 
8.2%
동 451
 
7.5%
마 443
 
7.4%
포 442
 
7.4%
시 421
 
7.0%
구 414
 
6.9%
울 410
 
6.8%
별 410
 
6.8%
특 410
 
6.8%
지 188
 
3.1%
Other values (193) 1933
32.2%

지정일자
Real number (ℝ)

MISSING 

Distinct236
Distinct (%)40.6%
Missing224
Missing (%)27.8%
Infinite0
Infinite (%)0.0%
Mean20172247
Minimum20041214
Maximum22070709
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-05-11T15:46:15.361202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20041214
5-th percentile20091110
Q120150507
median20170621
Q320210401
95-th percentile20210801
Maximum22070709
Range2029495
Interquartile range (IQR)59894

Descriptive statistics

Standard deviation87409.693
Coefficient of variation (CV)0.0043331659
Kurtosis384.7528
Mean20172247
Median Absolute Deviation (MAD)29507
Skewness17.640087
Sum1.1720075 × 1010
Variance7.6404544 × 109
MonotonicityNot monotonic
2024-05-11T15:46:15.600717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210801 104
 
12.9%
20150110 12
 
1.5%
20171121 12
 
1.5%
20190408 10
 
1.2%
20151229 9
 
1.1%
20171226 8
 
1.0%
20180419 8
 
1.0%
20181023 8
 
1.0%
20150507 7
 
0.9%
20170529 7
 
0.9%
Other values (226) 396
49.2%
(Missing) 224
27.8%
ValueCountFrequency (%)
20041214 1
0.1%
20060515 2
0.2%
20060619 1
0.1%
20060803 1
0.1%
20061023 1
0.1%
20061031 1
0.1%
20070109 1
0.1%
20070516 1
0.1%
20070709 1
0.1%
20070829 1
0.1%
ValueCountFrequency (%)
22070709 1
0.1%
20220311 1
0.1%
20220307 1
0.1%
20220304 1
0.1%
20220121 1
0.1%
20220111 2
0.2%
20220106 1
0.1%
20211224 1
0.1%
20211130 1
0.1%
20211127 1
0.1%

신청일자
Real number (ℝ)

MISSING 

Distinct304
Distinct (%)51.5%
Missing215
Missing (%)26.7%
Infinite0
Infinite (%)0.0%
Mean20169188
Minimum20041129
Maximum20220311
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-05-11T15:46:15.832022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20041129
5-th percentile20091113
Q120150430
median20170608
Q320210208
95-th percentile20210801
Maximum20220311
Range179182
Interquartile range (IQR)59778

Descriptive statistics

Standard deviation37423.458
Coefficient of variation (CV)0.0018554767
Kurtosis0.2751718
Mean20169188
Median Absolute Deviation (MAD)29496.5
Skewness-0.8078498
Sum1.1899821 × 1010
Variance1.4005152 × 109
MonotonicityNot monotonic
2024-05-11T15:46:16.411466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210801 105
 
13.0%
20150110 12
 
1.5%
20190401 10
 
1.2%
20181001 8
 
1.0%
20180409 8
 
1.0%
20191111 7
 
0.9%
20150430 7
 
0.9%
20180917 7
 
0.9%
20141111 6
 
0.7%
20191018 5
 
0.6%
Other values (294) 415
51.6%
(Missing) 215
26.7%
ValueCountFrequency (%)
20041129 1
0.1%
20060515 2
0.2%
20060619 1
0.1%
20060803 1
0.1%
20061023 1
0.1%
20061031 1
0.1%
20070109 1
0.1%
20070516 1
0.1%
20070709 1
0.1%
20070829 1
0.1%
ValueCountFrequency (%)
20220311 1
0.1%
20220304 2
0.2%
20220121 1
0.1%
20220111 2
0.2%
20220106 1
0.1%
20211224 1
0.1%
20211130 1
0.1%
20211127 1
0.1%
20211126 1
0.1%
20211119 1
0.1%

항목값1
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
관급봉투
590 
<NA>
215 

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 590
73.3%
<NA> 215
 
26.7%

Length

2024-05-11T15:46:16.610758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:46:16.769113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관급봉투 590
73.3%
na 215
 
26.7%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)업소구분명소재지지정일자신청일자항목값1
0313000031300001420100000120101202<NA>1영업/정상11영업<NA><NA><NA><NA>3088295<NA>121270서울특별시 마포구 상암동 1689번지 상암월드컵파크6단지상가 105호<NA><NA>하모니24 상암6단지점2010-12-02 16:45:29I2018-08-31 23:59:59.0<NA>189706.400188453064.248567지정서울특별시 마포구 상암동 1689번지 상암월드컵파크6단지상가 105호2010111620101202관급봉투
1313000031300001420100000220101202<NA>1영업/정상11영업<NA><NA><NA><NA>3732233<NA>121270서울특별시 마포구 상암동 31-6번지<NA><NA>(주)다은유통2016-05-25 13:39:21I2018-08-31 23:59:59.0<NA>190707.026134452612.042328종료서울특별시 마포구 상암동 31번지 6호2010111620101116관급봉투
2313000031300001420100000320101116<NA>1영업/정상11영업<NA><NA><NA><NA>3023788<NA>121270서울특별시 마포구 상암동 상암2택지개발사업지구상가9단지105<NA><NA>열린할인마트2010-12-02 16:44:01I2018-08-31 23:59:59.0<NA><NA><NA>지정서울특별시 마포구 상암동 상암2택지개발사업지구상가9단지 1052010111620101116관급봉투
3313000031300001420140000120140820<NA>1영업/정상11영업<NA><NA><NA><NA>02-714-1761<NA>121876서울특별시 마포구 용강동 473-1번지서울특별시 마포구 토정로 271, 1층 (용강동, 대현빌딩)121876드림디포2014-08-22 17:18:22I2018-08-31 23:59:59.0<NA>194654.585203448914.521961지정서울특별시 마포구 용강동 473번지 1호2014082020140820관급봉투
4313000031300001420140000220140820<NA>1영업/정상11영업<NA><NA><NA><NA>02-3144-4815<NA>121843서울특별시 마포구 성산동 53-2번지서울특별시 마포구 월드컵북로 121 (성산동)121843GS25 마포성산점2014-08-21 03:55:49I2018-08-31 23:59:59.0<NA>192215.720978451280.973202지정서울특별시 마포구 성산동 53번지 2호2014082020140820관급봉투
5313000031300001420140000320140820<NA>3폐업2폐업20220719<NA><NA><NA>02-323-3320<NA>121886서울특별시 마포구 합정동 395-1서울특별시 마포구 포은로 27, 1층 (합정동)121886씨유 신합정공원점2022-07-19 14:17:14U2021-12-06 22:01:00.0<NA>191810.896641449771.725223<NA><NA><NA><NA><NA>
6313000031300001420140000420140820<NA>3폐업2폐업2019082220190822<NA><NA>02-337-7579<NA>121883서울특별시 마포구 합정동 204-3번지서울특별시 마포구 토정로 38, 101호 (합정동, 국토빌)121883GS25 합정토정로점2019-08-22 14:24:24U2019-08-24 02:40:00.0<NA>192427.286251449242.675735지정서울특별시 마포구 합정동 204번지 3호2014082020140820관급봉투
7313000031300001420140000520140820<NA>1영업/정상11영업<NA><NA><NA><NA>02-305-9765<NA>121270서울특별시 마포구 상암동 1734번지서울특별시 마포구 구룡길 19, C동 101층 (상암동, 상암한화오벨리스크)121270씨유 상암오벨리스크2014-08-21 04:47:52I2018-08-31 23:59:59.0<NA>189624.641758453872.425787지정서울특별시 마포구 상암동 1734번지2014040720140820관급봉투
8313000031300001420140000620140723<NA>1영업/정상11영업<NA><NA><NA><NA>02-3143-6777<NA>121818서울특별시 마포구 동교동 174-4번지서울특별시 마포구 신촌로4길 4 (동교동)121818씨유 동교행복2014-08-21 04:56:42I2018-08-31 23:59:59.0<NA>193613.677005450606.988215지정서울특별시 마포구 동교동 174번지 4호2014072320140723관급봉투
9313000031300001420140000720140723<NA>1영업/정상11영업<NA><NA><NA><NA>02-332-6765<NA>121837서울특별시 마포구 서교동 342-3번지서울특별시 마포구 와우산로25길 13, 1층 (서교동)121837GS25 서교사랑2018-10-01 22:38:39U2018-10-03 02:36:42.0<NA>193376.593439450193.415123지정서울특별시 마포구 서교동 342번지 3호2007070920140723관급봉투
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)업소구분명소재지지정일자신청일자항목값1
79531300003130000142024000082024-01-29<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 상수동 402 래미안밤섬리베뉴 1서울특별시 마포구 독막로20나길 22, 1층 104호 (상수동, 래미안밤섬리베뉴 1)04076지에스(GS)25 뉴상수사랑2024-01-29 17:05:37I2023-11-30 21:01:00.0<NA>193345.6351449376.251557<NA><NA><NA><NA><NA>
79631300003130000142024000092024-01-31<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 공덕동 456 한국사회복지회관 르네상스타워서울특별시 마포구 만리재로 14, 한국사회복지회관 르네상스타워 지하1층 9호 (공덕동)04195행복마트2024-01-31 11:18:56I2023-12-02 00:02:00.0<NA>195766.58807449083.306923<NA><NA><NA><NA><NA>
79731300003130000142024000102024-01-31<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 서교동 467-3서울특별시 마포구 잔다리로 89, 1층 (서교동)04003CU마포성제점2024-01-31 11:25:55I2023-12-02 00:02:00.0<NA>192446.902559450319.955832<NA><NA><NA><NA><NA>
79831300003130000142024000112024-01-31<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 서교동 395-91서울특별시 마포구 잔다리로 25, 1층 (서교동)04043㈜비지에프리테일 플래그십홍대점 (CU 홍대상상점)2024-01-31 11:33:04I2023-12-02 00:02:00.0<NA>192866.453646449849.09236<NA><NA><NA><NA><NA>
79931300003130000142024000142024-03-05<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 노고산동 40-1서울특별시 마포구 신촌로 128, 1호 (노고산동)04101씨유 신촌로점2024-03-05 10:48:21I2023-12-03 00:07:00.0<NA>194624.665636450387.14561<NA><NA><NA><NA><NA>
80031300003130000142024000152024-03-15<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 망원동 454-1 참존2차아파트서울특별시 마포구 망원로 16, 101동 101호 (망원동, 참존2차아파트)04006지에스25망원참존점2024-03-15 13:34:06I2023-12-02 23:07:00.0<NA>190998.838892450403.766067<NA><NA><NA><NA><NA>
80131300003130000142024000162024-03-22<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 상암동 1736 상암월드컵파크10단지서울특별시 마포구 월드컵북로 502-36 (상암동, 상암월드컵파크10단지)03918지에스(GS)25 상암10단지점2024-03-22 13:15:09I2023-12-02 22:04:00.0<NA>189520.465146453685.460423<NA><NA><NA><NA><NA>
80231300003130000142024000172024-04-23<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 노고산동 106-52 준빌딩서울특별시 마포구 백범로4길 12, 준빌딩 2층 (노고산동)04109GS25마포신촌점2024-04-23 16:10:27I2023-12-03 22:05:00.0<NA>194313.827747450069.854126<NA><NA><NA><NA><NA>
80331300003130000142024000182024-04-23<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 신수동 88-16서울특별시 마포구 광성로4길 11-10 (신수동)04096GS25마포신수2024-04-23 16:30:55I2023-12-03 22:05:00.0<NA>194446.968198449684.193616<NA><NA><NA><NA><NA>
80431300003130000142024000192024-04-23<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 합정동 362-1서울특별시 마포구 독막로 42, 1층 (합정동)04072지에스(GS)25 합정유니버스점2024-04-23 17:23:23I2023-12-03 22:05:00.0<NA>192665.897224449510.335754<NA><NA><NA><NA><NA>