Overview

Dataset statistics

Number of variables29
Number of observations1542
Missing cells14786
Missing cells (%)33.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory372.1 KiB
Average record size in memory247.1 B

Variable types

Categorical6
Numeric9
DateTime5
Text6
Unsupported3

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),자산규모,부채총액,자본금,판매방식명
Author강남구
URLhttps://data.seoul.go.kr/dataList/OA-18799/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (98.7%)Imbalance
폐업일자 has 302 (19.6%) missing valuesMissing
휴업시작일자 has 1531 (99.3%) missing valuesMissing
휴업종료일자 has 1531 (99.3%) missing valuesMissing
재개업일자 has 862 (55.9%) missing valuesMissing
전화번호 has 116 (7.5%) missing valuesMissing
소재지면적 has 1542 (100.0%) missing valuesMissing
소재지우편번호 has 1172 (76.0%) missing valuesMissing
지번주소 has 113 (7.3%) missing valuesMissing
도로명주소 has 663 (43.0%) missing valuesMissing
도로명우편번호 has 939 (60.9%) missing valuesMissing
업태구분명 has 1542 (100.0%) missing valuesMissing
좌표정보(X) has 663 (43.0%) missing valuesMissing
좌표정보(Y) has 663 (43.0%) missing valuesMissing
자산규모 has 535 (34.7%) missing valuesMissing
부채총액 has 537 (34.8%) missing valuesMissing
자본금 has 533 (34.6%) missing valuesMissing
판매방식명 has 1542 (100.0%) missing valuesMissing
자본금 is highly skewed (γ1 = 24.60425273)Skewed
관리번호 has unique valuesUnique
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
판매방식명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
자산규모 has 495 (32.1%) zerosZeros
부채총액 has 687 (44.6%) zerosZeros
자본금 has 440 (28.5%) zerosZeros

Reproduction

Analysis started2024-05-11 06:02:52.193145
Analysis finished2024-05-11 06:02:53.510073
Duration1.32 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.2 KiB
3220000
1542 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3220000
2nd row3220000
3rd row3220000
4th row3220000
5th row3220000

Common Values

ValueCountFrequency (%)
3220000 1542
100.0%

Length

2024-05-11T15:02:53.594110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:02:53.720269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3220000 1542
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct1542
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0103317 × 1018
Minimum2.000322 × 1018
Maximum2.024322 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.7 KiB
2024-05-11T15:02:53.880753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.000322 × 1018
5-th percentile2.002322 × 1018
Q12.005322 × 1018
median2.008322 × 1018
Q32.015322 × 1018
95-th percentile2.022322 × 1018
Maximum2.024322 × 1018
Range2.4000012 × 1016
Interquartile range (IQR)1.0000003 × 1016

Descriptive statistics

Standard deviation6.1223159 × 1015
Coefficient of variation (CV)0.0030454256
Kurtosis-0.83996894
Mean2.0103317 × 1018
Median Absolute Deviation (MAD)4 × 1015
Skewness0.62912686
Sum8.7854306 × 1017
Variance3.7482751 × 1031
MonotonicityStrictly increasing
2024-05-11T15:02:54.079280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2000322012724200011 1
 
0.1%
2011322016224200030 1
 
0.1%
2013322016224200013 1
 
0.1%
2013322016224200012 1
 
0.1%
2013322016224200011 1
 
0.1%
2013322016224200010 1
 
0.1%
2013322016224200009 1
 
0.1%
2013322016224200008 1
 
0.1%
2013322016224200007 1
 
0.1%
2013322016224200006 1
 
0.1%
Other values (1532) 1532
99.4%
ValueCountFrequency (%)
2000322012724200011 1
0.1%
2000322012724200110 1
0.1%
2002322012724200001 1
0.1%
2002322012724200002 1
0.1%
2002322012724200003 1
0.1%
2002322012724200004 1
0.1%
2002322012724200005 1
0.1%
2002322012724200006 1
0.1%
2002322012724200007 1
0.1%
2002322012724200009 1
0.1%
ValueCountFrequency (%)
2024322024924200011 1
0.1%
2024322024924200010 1
0.1%
2024322024924200009 1
0.1%
2024322024924200008 1
0.1%
2024322024924200007 1
0.1%
2024322024924200006 1
0.1%
2024322024924200005 1
0.1%
2024322024924200004 1
0.1%
2024322024924200003 1
0.1%
2024322024924200002 1
0.1%

인허가일자
Date

Distinct1097
Distinct (%)71.1%
Missing0
Missing (%)0.0%
Memory size12.2 KiB
Minimum2000-08-29 00:00:00
Maximum2024-04-24 00:00:00
2024-05-11T15:02:54.686269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:02:54.942428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size12.2 KiB
<NA>
1538 
20070530
 
1
20080708
 
1
20090921
 
1
20160314
 
1

Length

Max length8
Median length4
Mean length4.0103761
Min length4

Unique

Unique4 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1538
99.7%
20070530 1
 
0.1%
20080708 1
 
0.1%
20090921 1
 
0.1%
20160314 1
 
0.1%

Length

2024-05-11T15:02:55.192906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:02:55.360929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1538
99.7%
20070530 1
 
0.1%
20080708 1
 
0.1%
20090921 1
 
0.1%
20160314 1
 
0.1%

영업상태코드
Categorical

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size12.2 KiB
4
744 
3
512 
1
262 
5
 
20
2
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row4
3rd row4
4th row4
5th row4

Common Values

ValueCountFrequency (%)
4 744
48.2%
3 512
33.2%
1 262
 
17.0%
5 20
 
1.3%
2 4
 
0.3%

Length

2024-05-11T15:02:55.549968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:02:55.705783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 744
48.2%
3 512
33.2%
1 262
 
17.0%
5 20
 
1.3%
2 4
 
0.3%

영업상태명
Categorical

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size12.2 KiB
취소/말소/만료/정지/중지
744 
폐업
512 
영업/정상
262 
제외/삭제/전출
 
20
휴업
 
4

Length

Max length14
Median length8
Mean length8.3774319
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row취소/말소/만료/정지/중지
3rd row취소/말소/만료/정지/중지
4th row취소/말소/만료/정지/중지
5th row취소/말소/만료/정지/중지

Common Values

ValueCountFrequency (%)
취소/말소/만료/정지/중지 744
48.2%
폐업 512
33.2%
영업/정상 262
 
17.0%
제외/삭제/전출 20
 
1.3%
휴업 4
 
0.3%

Length

2024-05-11T15:02:55.880540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:02:56.030393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
취소/말소/만료/정지/중지 744
48.2%
폐업 512
33.2%
영업/정상 262
 
17.0%
제외/삭제/전출 20
 
1.3%
휴업 4
 
0.3%

상세영업상태코드
Real number (ℝ)

Distinct6
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6018158
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.7 KiB
2024-05-11T15:02:56.197188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q37
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.4152762
Coefficient of variation (CV)0.52485287
Kurtosis-1.6263477
Mean4.6018158
Median Absolute Deviation (MAD)2
Skewness-0.19545296
Sum7096
Variance5.8335593
MonotonicityNot monotonic
2024-05-11T15:02:56.432049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
7 738
47.9%
3 512
33.2%
1 262
 
17.0%
5 20
 
1.3%
4 6
 
0.4%
2 4
 
0.3%
ValueCountFrequency (%)
1 262
 
17.0%
2 4
 
0.3%
3 512
33.2%
4 6
 
0.4%
5 20
 
1.3%
7 738
47.9%
ValueCountFrequency (%)
7 738
47.9%
5 20
 
1.3%
4 6
 
0.4%
3 512
33.2%
2 4
 
0.3%
1 262
 
17.0%

상세영업상태명
Categorical

Distinct6
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size12.2 KiB
직권말소
738 
폐업처리
512 
정상영업
262 
타시군구이관
 
20
직권취소
 
6

Length

Max length6
Median length4
Mean length4.0259403
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업처리
2nd row직권말소
3rd row직권말소
4th row직권말소
5th row직권말소

Common Values

ValueCountFrequency (%)
직권말소 738
47.9%
폐업처리 512
33.2%
정상영업 262
 
17.0%
타시군구이관 20
 
1.3%
직권취소 6
 
0.4%
휴업처리 4
 
0.3%

Length

2024-05-11T15:02:56.658422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:02:56.827208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
직권말소 738
47.9%
폐업처리 512
33.2%
정상영업 262
 
17.0%
타시군구이관 20
 
1.3%
직권취소 6
 
0.4%
휴업처리 4
 
0.3%

폐업일자
Date

MISSING 

Distinct482
Distinct (%)38.9%
Missing302
Missing (%)19.6%
Memory size12.2 KiB
Minimum2002-11-11 00:00:00
Maximum2024-04-05 00:00:00
2024-05-11T15:02:57.029727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:02:57.234072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)100.0%
Missing1531
Missing (%)99.3%
Infinite0
Infinite (%)0.0%
Mean20110530
Minimum20040101
Maximum20181218
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.7 KiB
2024-05-11T15:02:57.403350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20040101
5-th percentile20045362
Q120080766
median20090701
Q320155158
95-th percentile20176118
Maximum20181218
Range141117
Interquartile range (IQR)74392.5

Descriptive statistics

Standard deviation49305.894
Coefficient of variation (CV)0.0024517451
Kurtosis-1.3377079
Mean20110530
Median Absolute Deviation (MAD)40078
Skewness0.18419058
Sum2.2121583 × 108
Variance2.4310712 × 109
MonotonicityNot monotonic
2024-05-11T15:02:57.591350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
20040101 1
 
0.1%
20050623 1
 
0.1%
20080728 1
 
0.1%
20090218 1
 
0.1%
20090701 1
 
0.1%
20080804 1
 
0.1%
20120101 1
 
0.1%
20140101 1
 
0.1%
20170216 1
 
0.1%
20171018 1
 
0.1%
(Missing) 1531
99.3%
ValueCountFrequency (%)
20040101 1
0.1%
20050623 1
0.1%
20080728 1
0.1%
20080804 1
0.1%
20090218 1
0.1%
20090701 1
0.1%
20120101 1
0.1%
20140101 1
0.1%
20170216 1
0.1%
20171018 1
0.1%
ValueCountFrequency (%)
20181218 1
0.1%
20171018 1
0.1%
20170216 1
0.1%
20140101 1
0.1%
20120101 1
0.1%
20090701 1
0.1%
20090218 1
0.1%
20080804 1
0.1%
20080728 1
0.1%
20050623 1
0.1%

휴업종료일자
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)100.0%
Missing1531
Missing (%)99.3%
Infinite0
Infinite (%)0.0%
Mean20119072
Minimum20040630
Maximum20191231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.7 KiB
2024-05-11T15:02:57.758265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20040630
5-th percentile20045930
Q120085816
median20100630
Q320175880
95-th percentile20190723
Maximum20191231
Range150601
Interquartile range (IQR)90064.5

Descriptive statistics

Standard deviation55589.128
Coefficient of variation (CV)0.0027630066
Kurtosis-1.5378349
Mean20119072
Median Absolute Deviation (MAD)49399
Skewness0.14850976
Sum2.2130979 × 108
Variance3.0901512 × 109
MonotonicityNot monotonic
2024-05-11T15:02:57.924237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
20040630 1
 
0.1%
20051231 1
 
0.1%
20090728 1
 
0.1%
20091231 1
 
0.1%
20100630 1
 
0.1%
20080904 1
 
0.1%
20121231 1
 
0.1%
20171231 1
 
0.1%
20190215 1
 
0.1%
20180530 1
 
0.1%
(Missing) 1531
99.3%
ValueCountFrequency (%)
20040630 1
0.1%
20051231 1
0.1%
20080904 1
0.1%
20090728 1
0.1%
20091231 1
0.1%
20100630 1
0.1%
20121231 1
0.1%
20171231 1
0.1%
20180530 1
0.1%
20190215 1
0.1%
ValueCountFrequency (%)
20191231 1
0.1%
20190215 1
0.1%
20180530 1
0.1%
20171231 1
0.1%
20121231 1
0.1%
20100630 1
0.1%
20091231 1
0.1%
20090728 1
0.1%
20080904 1
0.1%
20051231 1
0.1%

재개업일자
Date

MISSING 

Distinct392
Distinct (%)57.6%
Missing862
Missing (%)55.9%
Memory size12.2 KiB
Minimum2000-08-29 00:00:00
Maximum2016-06-01 00:00:00
2024-05-11T15:02:58.097181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:02:58.289286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

전화번호
Text

MISSING 

Distinct1313
Distinct (%)92.1%
Missing116
Missing (%)7.5%
Memory size12.2 KiB
2024-05-11T15:02:58.561490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length10.506311
Min length1

Characters and Unicode

Total characters14982
Distinct characters15
Distinct categories6 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1245 ?
Unique (%)87.3%

Sample

1st row02-552-4200
2nd row02-515-4488
3rd row02-555-2359
4th row02-508-3448
5th row02-3452-3423
ValueCountFrequency (%)
02 40
 
2.7%
6
 
0.4%
501-0260 3
 
0.2%
02-563-5070 3
 
0.2%
02-566-1191 3
 
0.2%
070 3
 
0.2%
02-6257-3000 3
 
0.2%
02-549-3921 3
 
0.2%
1588-1555 3
 
0.2%
02-3412-9911 3
 
0.2%
Other values (1330) 1392
95.2%
2024-05-11T15:02:59.100042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2723
18.2%
- 2375
15.9%
2 2011
13.4%
5 1765
11.8%
1 1024
 
6.8%
6 999
 
6.7%
3 911
 
6.1%
8 878
 
5.9%
4 867
 
5.8%
7 790
 
5.3%
Other values (5) 639
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12564
83.9%
Dash Punctuation 2375
 
15.9%
Space Separator 37
 
0.2%
Other Punctuation 4
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2723
21.7%
2 2011
16.0%
5 1765
14.0%
1 1024
 
8.2%
6 999
 
8.0%
3 911
 
7.3%
8 878
 
7.0%
4 867
 
6.9%
7 790
 
6.3%
9 596
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 2375
100.0%
Space Separator
ValueCountFrequency (%)
37
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14982
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2723
18.2%
- 2375
15.9%
2 2011
13.4%
5 1765
11.8%
1 1024
 
6.8%
6 999
 
6.7%
3 911
 
6.1%
8 878
 
5.9%
4 867
 
5.8%
7 790
 
5.3%
Other values (5) 639
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14982
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2723
18.2%
- 2375
15.9%
2 2011
13.4%
5 1765
11.8%
1 1024
 
6.8%
6 999
 
6.7%
3 911
 
6.1%
8 878
 
5.9%
4 867
 
5.8%
7 790
 
5.3%
Other values (5) 639
 
4.3%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1542
Missing (%)100.0%
Memory size13.7 KiB

소재지우편번호
Text

MISSING 

Distinct62
Distinct (%)16.8%
Missing1172
Missing (%)76.0%
Memory size12.2 KiB
2024-05-11T15:02:59.805551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0108108
Min length6

Characters and Unicode

Total characters2224
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

Unique33 ?
Unique (%)8.9%

Sample

1st row135270
2nd row135280
3rd row135190
4th row135280
5th row135-833
ValueCountFrequency (%)
135080 145
39.2%
135280 34
 
9.2%
135090 33
 
8.9%
135010 26
 
7.0%
135270 15
 
4.1%
135120 12
 
3.2%
135100 7
 
1.9%
135240 7
 
1.9%
135910 6
 
1.6%
135839 5
 
1.4%
Other values (52) 80
21.6%
2024-05-11T15:03:01.046285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 517
23.2%
1 451
20.3%
3 392
17.6%
5 390
17.5%
8 231
10.4%
2 95
 
4.3%
9 83
 
3.7%
7 28
 
1.3%
4 23
 
1.0%
6 10
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2220
99.8%
Dash Punctuation 4
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 517
23.3%
1 451
20.3%
3 392
17.7%
5 390
17.6%
8 231
10.4%
2 95
 
4.3%
9 83
 
3.7%
7 28
 
1.3%
4 23
 
1.0%
6 10
 
0.5%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2224
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 517
23.2%
1 451
20.3%
3 392
17.6%
5 390
17.5%
8 231
10.4%
2 95
 
4.3%
9 83
 
3.7%
7 28
 
1.3%
4 23
 
1.0%
6 10
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2224
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 517
23.2%
1 451
20.3%
3 392
17.6%
5 390
17.5%
8 231
10.4%
2 95
 
4.3%
9 83
 
3.7%
7 28
 
1.3%
4 23
 
1.0%
6 10
 
0.4%

지번주소
Text

MISSING 

Distinct545
Distinct (%)38.1%
Missing113
Missing (%)7.3%
Memory size12.2 KiB
2024-05-11T15:03:01.485566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length43
Mean length26.094472
Min length16

Characters and Unicode

Total characters37289
Distinct characters316
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique415 ?
Unique (%)29.0%

Sample

1st row서울특별시 강남구 역삼동 일반번지 ***-*
2nd row서울특별시 강남구 논현동 일반 ***-**
3rd row서울특별시 강남구 역삼동 일반번지 ***-**
4th row서울특별시 강남구 역삼동 일반번지 ***-**
5th row서울특별시 강남구 역삼동 일반번지 ***-**
ValueCountFrequency (%)
서울특별시 1429
18.8%
강남구 1428
18.8%
888
11.7%
역삼동 672
8.8%
번지 611
8.0%
호 605
8.0%
일반번지 430
 
5.7%
일반 232
 
3.1%
대치동 210
 
2.8%
삼성동 188
 
2.5%
Other values (372) 906
11.9%
2024-05-11T15:03:02.029662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7503
20.1%
* 6985
18.7%
서 1454
 
3.9%
남 1443
 
3.9%
동 1439
 
3.9%
강 1435
 
3.8%
시 1433
 
3.8%
구 1432
 
3.8%
울 1430
 
3.8%
특 1429
 
3.8%
Other values (306) 11306
30.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21888
58.7%
Space Separator 7503
 
20.1%
Other Punctuation 7008
 
18.8%
Dash Punctuation 795
 
2.1%
Uppercase Letter 49
 
0.1%
Decimal Number 40
 
0.1%
Lowercase Letter 5
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 1454
 
6.6%
남 1443
 
6.6%
동 1439
 
6.6%
강 1435
 
6.6%
시 1433
 
6.5%
구 1432
 
6.5%
울 1430
 
6.5%
특 1429
 
6.5%
별 1429
 
6.5%
지 1069
 
4.9%
Other values (264) 7895
36.1%
Uppercase Letter
ValueCountFrequency (%)
R 5
10.2%
W 4
 
8.2%
T 4
 
8.2%
B 4
 
8.2%
C 4
 
8.2%
K 4
 
8.2%
A 4
 
8.2%
M 3
 
6.1%
E 3
 
6.1%
O 2
 
4.1%
Other values (10) 12
24.5%
Decimal Number
ValueCountFrequency (%)
2 7
17.5%
7 7
17.5%
3 6
15.0%
5 6
15.0%
1 4
10.0%
9 3
7.5%
4 2
 
5.0%
0 2
 
5.0%
8 2
 
5.0%
6 1
 
2.5%
Lowercase Letter
ValueCountFrequency (%)
c 1
20.0%
e 1
20.0%
o 1
20.0%
r 1
20.0%
k 1
20.0%
Other Punctuation
ValueCountFrequency (%)
* 6985
99.7%
, 20
 
0.3%
& 2
 
< 0.1%
/ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
7503
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 795
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21888
58.7%
Common 15346
41.2%
Latin 55
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 1454
 
6.6%
남 1443
 
6.6%
동 1439
 
6.6%
강 1435
 
6.6%
시 1433
 
6.5%
구 1432
 
6.5%
울 1430
 
6.5%
특 1429
 
6.5%
별 1429
 
6.5%
지 1069
 
4.9%
Other values (264) 7895
36.1%
Latin
ValueCountFrequency (%)
R 5
 
9.1%
W 4
 
7.3%
T 4
 
7.3%
B 4
 
7.3%
C 4
 
7.3%
K 4
 
7.3%
A 4
 
7.3%
M 3
 
5.5%
E 3
 
5.5%
O 2
 
3.6%
Other values (16) 18
32.7%
Common
ValueCountFrequency (%)
7503
48.9%
* 6985
45.5%
- 795
 
5.2%
, 20
 
0.1%
2 7
 
< 0.1%
7 7
 
< 0.1%
3 6
 
< 0.1%
5 6
 
< 0.1%
1 4
 
< 0.1%
9 3
 
< 0.1%
Other values (6) 10
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21888
58.7%
ASCII 15400
41.3%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7503
48.7%
* 6985
45.4%
- 795
 
5.2%
, 20
 
0.1%
2 7
 
< 0.1%
7 7
 
< 0.1%
3 6
 
< 0.1%
5 6
 
< 0.1%
R 5
 
< 0.1%
1 4
 
< 0.1%
Other values (31) 62
 
0.4%
Hangul
ValueCountFrequency (%)
서 1454
 
6.6%
남 1443
 
6.6%
동 1439
 
6.6%
강 1435
 
6.6%
시 1433
 
6.5%
구 1432
 
6.5%
울 1430
 
6.5%
특 1429
 
6.5%
별 1429
 
6.5%
지 1069
 
4.9%
Other values (264) 7895
36.1%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

도로명주소
Text

MISSING 

Distinct789
Distinct (%)89.8%
Missing663
Missing (%)43.0%
Memory size12.2 KiB
2024-05-11T15:03:02.483250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length48
Mean length35.095563
Min length22

Characters and Unicode

Total characters30849
Distinct characters356
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

Unique723 ?
Unique (%)82.3%

Sample

1st row서울특별시 강남구 영동대로 ***, **층 *호 (삼성동, 무역센타)
2nd row서울특별시 강남구 강남대로**길 ** (도곡동)
3rd row서울특별시 강남구 봉은사로**길 **, *층 (역삼동)
4th row서울특별시 강남구 삼성로 *** (삼성동)
5th row서울특별시 강남구 테헤란로**길 **, ***호 (삼성동, 마젤란 ** 아스테리움)
ValueCountFrequency (%)
938
16.4%
서울특별시 879
15.3%
강남구 879
15.3%
층 400
 
7.0%
호 277
 
4.8%
역삼동 273
 
4.8%
테헤란로 132
 
2.3%
테헤란로**길 132
 
2.3%
삼성동 98
 
1.7%
대치동 95
 
1.7%
Other values (702) 1631
28.4%
2024-05-11T15:03:03.098364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 5132
 
16.6%
4855
 
15.7%
, 1115
 
3.6%
동 1015
 
3.3%
남 979
 
3.2%
강 950
 
3.1%
서 907
 
2.9%
로 906
 
2.9%
구 893
 
2.9%
시 883
 
2.9%
Other values (346) 13214
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17729
57.5%
Other Punctuation 6256
 
20.3%
Space Separator 4855
 
15.7%
Close Punctuation 882
 
2.9%
Open Punctuation 882
 
2.9%
Uppercase Letter 104
 
0.3%
Dash Punctuation 85
 
0.3%
Decimal Number 44
 
0.1%
Lowercase Letter 9
 
< 0.1%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1015
 
5.7%
남 979
 
5.5%
강 950
 
5.4%
서 907
 
5.1%
로 906
 
5.1%
구 893
 
5.0%
시 883
 
5.0%
별 881
 
5.0%
울 880
 
5.0%
특 879
 
5.0%
Other values (299) 8556
48.3%
Uppercase Letter
ValueCountFrequency (%)
B 14
13.5%
C 12
11.5%
K 10
 
9.6%
A 8
 
7.7%
T 7
 
6.7%
M 6
 
5.8%
L 6
 
5.8%
R 6
 
5.8%
W 5
 
4.8%
S 5
 
4.8%
Other values (12) 25
24.0%
Decimal Number
ValueCountFrequency (%)
1 8
18.2%
3 7
15.9%
2 5
11.4%
8 5
11.4%
4 5
11.4%
0 4
9.1%
6 4
9.1%
5 4
9.1%
7 2
 
4.5%
Lowercase Letter
ValueCountFrequency (%)
e 3
33.3%
o 2
22.2%
s 1
 
11.1%
t 1
 
11.1%
k 1
 
11.1%
r 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
* 5132
82.0%
, 1115
 
17.8%
. 7
 
0.1%
& 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
4855
100.0%
Close Punctuation
ValueCountFrequency (%)
) 882
100.0%
Open Punctuation
ValueCountFrequency (%)
( 882
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 85
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17729
57.5%
Common 13005
42.2%
Latin 115
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1015
 
5.7%
남 979
 
5.5%
강 950
 
5.4%
서 907
 
5.1%
로 906
 
5.1%
구 893
 
5.0%
시 883
 
5.0%
별 881
 
5.0%
울 880
 
5.0%
특 879
 
5.0%
Other values (299) 8556
48.3%
Latin
ValueCountFrequency (%)
B 14
 
12.2%
C 12
 
10.4%
K 10
 
8.7%
A 8
 
7.0%
T 7
 
6.1%
M 6
 
5.2%
L 6
 
5.2%
R 6
 
5.2%
W 5
 
4.3%
S 5
 
4.3%
Other values (19) 36
31.3%
Common
ValueCountFrequency (%)
* 5132
39.5%
4855
37.3%
, 1115
 
8.6%
) 882
 
6.8%
( 882
 
6.8%
- 85
 
0.7%
1 8
 
0.1%
3 7
 
0.1%
. 7
 
0.1%
2 5
 
< 0.1%
Other values (8) 27
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17729
57.5%
ASCII 13118
42.5%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 5132
39.1%
4855
37.0%
, 1115
 
8.5%
) 882
 
6.7%
( 882
 
6.7%
- 85
 
0.6%
B 14
 
0.1%
C 12
 
0.1%
K 10
 
0.1%
A 8
 
0.1%
Other values (36) 123
 
0.9%
Hangul
ValueCountFrequency (%)
동 1015
 
5.7%
남 979
 
5.5%
강 950
 
5.4%
서 907
 
5.1%
로 906
 
5.1%
구 893
 
5.0%
시 883
 
5.0%
별 881
 
5.0%
울 880
 
5.0%
특 879
 
5.0%
Other values (299) 8556
48.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%

도로명우편번호
Text

MISSING 

Distinct240
Distinct (%)39.8%
Missing939
Missing (%)60.9%
Memory size12.2 KiB
2024-05-11T15:03:03.683986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.331675
Min length5

Characters and Unicode

Total characters3215
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

Unique111 ?
Unique (%)18.4%

Sample

1st row135091
2nd row06129
3rd row135091
4th row06169
5th row135546
ValueCountFrequency (%)
06132 20
 
3.3%
135081 20
 
3.3%
135011 10
 
1.7%
06193 10
 
1.7%
06236 10
 
1.7%
06150 9
 
1.5%
135091 8
 
1.3%
135933 8
 
1.3%
06212 8
 
1.3%
06083 8
 
1.3%
Other values (230) 492
81.6%
2024-05-11T15:03:04.574239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 598
18.6%
0 592
18.4%
6 516
16.0%
3 396
12.3%
5 296
9.2%
2 272
8.5%
9 172
 
5.3%
8 168
 
5.2%
4 109
 
3.4%
7 90
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3209
99.8%
Dash Punctuation 6
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 598
18.6%
0 592
18.4%
6 516
16.1%
3 396
12.3%
5 296
9.2%
2 272
8.5%
9 172
 
5.4%
8 168
 
5.2%
4 109
 
3.4%
7 90
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3215
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 598
18.6%
0 592
18.4%
6 516
16.0%
3 396
12.3%
5 296
9.2%
2 272
8.5%
9 172
 
5.3%
8 168
 
5.2%
4 109
 
3.4%
7 90
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3215
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 598
18.6%
0 592
18.4%
6 516
16.0%
3 396
12.3%
5 296
9.2%
2 272
8.5%
9 172
 
5.3%
8 168
 
5.2%
4 109
 
3.4%
7 90
 
2.8%

사업장명
Text

Distinct1509
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size12.2 KiB
2024-05-11T15:03:05.068604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length39
Mean length9.1789883
Min length2

Characters and Unicode

Total characters14154
Distinct characters558
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1477 ?
Unique (%)95.8%

Sample

1st row(주)엘리온정보기술
2nd row(주)재우지에프
3rd row밸리시스
4th rowI.P club
5th rowBest Life
ValueCountFrequency (%)
주식회사 335
 
15.0%
주 173
 
7.7%
ltd 9
 
0.4%
co 9
 
0.4%
co.,ltd 7
 
0.3%
농업회사법인 6
 
0.3%
5
 
0.2%
유한회사 4
 
0.2%
컨설팅 4
 
0.2%
inc 4
 
0.2%
Other values (1622) 1679
75.1%
2024-05-11T15:03:05.787799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 1260
 
8.9%
) 892
 
6.3%
( 888
 
6.3%
696
 
4.9%
이 505
 
3.6%
스 454
 
3.2%
사 394
 
2.8%
회 383
 
2.7%
식 361
 
2.6%
아 230
 
1.6%
Other values (548) 8091
57.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10972
77.5%
Close Punctuation 892
 
6.3%
Open Punctuation 888
 
6.3%
Space Separator 696
 
4.9%
Lowercase Letter 296
 
2.1%
Uppercase Letter 275
 
1.9%
Other Punctuation 74
 
0.5%
Dash Punctuation 48
 
0.3%
Decimal Number 13
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 1260
 
11.5%
이 505
 
4.6%
스 454
 
4.1%
사 394
 
3.6%
회 383
 
3.5%
식 361
 
3.3%
아 230
 
2.1%
에 229
 
2.1%
디 213
 
1.9%
앤 185
 
1.7%
Other values (489) 6758
61.6%
Uppercase Letter
ValueCountFrequency (%)
C 36
 
13.1%
L 30
 
10.9%
S 16
 
5.8%
M 16
 
5.8%
G 16
 
5.8%
O 16
 
5.8%
E 15
 
5.5%
A 15
 
5.5%
P 12
 
4.4%
T 12
 
4.4%
Other values (15) 91
33.1%
Lowercase Letter
ValueCountFrequency (%)
o 47
15.9%
e 31
10.5%
d 29
9.8%
t 26
8.8%
n 24
8.1%
l 23
 
7.8%
i 20
 
6.8%
c 15
 
5.1%
s 12
 
4.1%
a 11
 
3.7%
Other values (13) 58
19.6%
Other Punctuation
ValueCountFrequency (%)
. 52
70.3%
, 16
 
21.6%
& 5
 
6.8%
/ 1
 
1.4%
Decimal Number
ValueCountFrequency (%)
2 6
46.2%
1 5
38.5%
0 2
 
15.4%
Close Punctuation
ValueCountFrequency (%)
) 892
100.0%
Open Punctuation
ValueCountFrequency (%)
( 888
100.0%
Space Separator
ValueCountFrequency (%)
696
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10972
77.5%
Common 2611
 
18.4%
Latin 571
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 1260
 
11.5%
이 505
 
4.6%
스 454
 
4.1%
사 394
 
3.6%
회 383
 
3.5%
식 361
 
3.3%
아 230
 
2.1%
에 229
 
2.1%
디 213
 
1.9%
앤 185
 
1.7%
Other values (489) 6758
61.6%
Latin
ValueCountFrequency (%)
o 47
 
8.2%
C 36
 
6.3%
e 31
 
5.4%
L 30
 
5.3%
d 29
 
5.1%
t 26
 
4.6%
n 24
 
4.2%
l 23
 
4.0%
i 20
 
3.5%
S 16
 
2.8%
Other values (38) 289
50.6%
Common
ValueCountFrequency (%)
) 892
34.2%
( 888
34.0%
696
26.7%
. 52
 
2.0%
- 48
 
1.8%
, 16
 
0.6%
2 6
 
0.2%
1 5
 
0.2%
& 5
 
0.2%
0 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10972
77.5%
ASCII 3182
 
22.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 1260
 
11.5%
이 505
 
4.6%
스 454
 
4.1%
사 394
 
3.6%
회 383
 
3.5%
식 361
 
3.3%
아 230
 
2.1%
에 229
 
2.1%
디 213
 
1.9%
앤 185
 
1.7%
Other values (489) 6758
61.6%
ASCII
ValueCountFrequency (%)
) 892
28.0%
( 888
27.9%
696
21.9%
. 52
 
1.6%
- 48
 
1.5%
o 47
 
1.5%
C 36
 
1.1%
e 31
 
1.0%
L 30
 
0.9%
d 29
 
0.9%
Other values (49) 433
13.6%

최종수정일자
Date

Distinct1380
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Memory size12.2 KiB
Minimum2007-07-13 18:13:27
Maximum2024-05-08 14:39:21
2024-05-11T15:03:06.062294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:03:06.314723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.2 KiB
I
1162 
U
380 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 1162
75.4%
U 380
 
24.6%

Length

2024-05-11T15:03:06.551314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:03:06.704481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1162
75.4%
u 380
 
24.6%

데이터갱신일자
Date

Distinct269
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size12.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 23:00:00
2024-05-11T15:03:06.880794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:03:07.184020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1542
Missing (%)100.0%
Memory size13.7 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct574
Distinct (%)65.3%
Missing663
Missing (%)43.0%
Infinite0
Infinite (%)0.0%
Mean203800.21
Minimum190612.78
Maximum209205.69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.7 KiB
2024-05-11T15:03:07.485805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum190612.78
5-th percentile202339.85
Q1202951.13
median203595.04
Q3204536.39
95-th percentile205680.59
Maximum209205.69
Range18592.909
Interquartile range (IQR)1585.2535

Descriptive statistics

Standard deviation1312.7317
Coefficient of variation (CV)0.0064412677
Kurtosis14.235526
Mean203800.21
Median Absolute Deviation (MAD)748.11491
Skewness0.10261886
Sum1.7914038 × 108
Variance1723264.5
MonotonicityNot monotonic
2024-05-11T15:03:07.772120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
203120.866692148 21
 
1.4%
204175.169991518 12
 
0.8%
204536.822020513 8
 
0.5%
203081.161708641 8
 
0.5%
202667.551184905 7
 
0.5%
203578.799034139 7
 
0.5%
204181.823243711 7
 
0.5%
204044.789948927 7
 
0.5%
203111.505626639 6
 
0.4%
204197.395 6
 
0.4%
Other values (564) 790
51.2%
(Missing) 663
43.0%
ValueCountFrequency (%)
190612.779366379 1
0.1%
201609.62721933 2
0.1%
201639.245453617 2
0.1%
201650.787158848 2
0.1%
201668.828802609 1
0.1%
201715.095225261 1
0.1%
201757.494098748 1
0.1%
201774.365077827 1
0.1%
201775.499150035 1
0.1%
201846.147108521 1
0.1%
ValueCountFrequency (%)
209205.687910519 1
 
0.1%
209144.783150288 1
 
0.1%
209055.480464368 3
0.2%
209052.072465426 5
0.3%
208951.069799114 1
 
0.1%
208937.760652081 4
0.3%
208547.303164015 1
 
0.1%
208154.566102274 1
 
0.1%
207558.938632664 1
 
0.1%
207418.573590049 1
 
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct574
Distinct (%)65.3%
Missing663
Missing (%)43.0%
Infinite0
Infinite (%)0.0%
Mean444666.47
Minimum439995.65
Maximum447393.51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.7 KiB
2024-05-11T15:03:08.134219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum439995.65
5-th percentile442797.14
Q1444122.84
median444660.78
Q3445141.77
95-th percentile446579.13
Maximum447393.51
Range7397.8603
Interquartile range (IQR)1018.9327

Descriptive statistics

Standard deviation1043.9179
Coefficient of variation (CV)0.0023476424
Kurtosis1.5098622
Mean444666.47
Median Absolute Deviation (MAD)517.28786
Skewness-0.22744779
Sum3.9086182 × 108
Variance1089764.5
MonotonicityNot monotonic
2024-05-11T15:03:08.852281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
444313.008610517 21
 
1.4%
444722.241675859 12
 
0.8%
444660.784269339 8
 
0.5%
444381.101104143 8
 
0.5%
443299.218136257 7
 
0.5%
444715.394917107 7
 
0.5%
444950.728644939 7
 
0.5%
444529.84042741 7
 
0.5%
444387.529455918 6
 
0.4%
444564.045 6
 
0.4%
Other values (564) 790
51.2%
(Missing) 663
43.0%
ValueCountFrequency (%)
439995.651613168 1
0.1%
440515.70109382 1
0.1%
440518.651807226 1
0.1%
441244.529854811 2
0.1%
441387.362646313 1
0.1%
441457.423640678 1
0.1%
441478.676728686 1
0.1%
441578.155263877 1
0.1%
441675.495465839 1
0.1%
441716.969176407 1
0.1%
ValueCountFrequency (%)
447393.51192286 1
 
0.1%
447301.71571803 1
 
0.1%
447300.581590235 1
 
0.1%
447274.492095426 3
0.2%
447237.128145742 1
 
0.1%
447224.219814083 1
 
0.1%
447216.564224994 1
 
0.1%
447193.199632297 1
 
0.1%
447173.476030359 2
0.1%
447170.103028229 1
 
0.1%

자산규모
Real number (ℝ)

MISSING  ZEROS 

Distinct295
Distinct (%)29.3%
Missing535
Missing (%)34.7%
Infinite0
Infinite (%)0.0%
Mean1.2296232 × 1010
Minimum0
Maximum3.4259418 × 1012
Zeros495
Zeros (%)32.1%
Negative0
Negative (%)0.0%
Memory size13.7 KiB
2024-05-11T15:03:09.115641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31.0027099 × 108
95-th percentile5.4341475 × 109
Maximum3.4259418 × 1012
Range3.4259418 × 1012
Interquartile range (IQR)1.0027099 × 108

Descriptive statistics

Standard deviation1.4624504 × 1011
Coefficient of variation (CV)11.893484
Kurtosis351.24687
Mean1.2296232 × 1010
Median Absolute Deviation (MAD)1
Skewness17.476814
Sum1.2382306 × 1013
Variance2.1387613 × 1022
MonotonicityNot monotonic
2024-05-11T15:03:09.414635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 495
32.1%
50000000 59
 
3.8%
1 40
 
2.6%
10000000 33
 
2.1%
100000000 20
 
1.3%
30000000 13
 
0.8%
20000000 9
 
0.6%
5000000 7
 
0.5%
200000000 7
 
0.5%
150000000 6
 
0.4%
Other values (285) 318
20.6%
(Missing) 535
34.7%
ValueCountFrequency (%)
0 495
32.1%
1 40
 
2.6%
1000000 1
 
0.1%
1695600 1
 
0.1%
3000000 1
 
0.1%
5000000 7
 
0.5%
6000000 2
 
0.1%
8930000 1
 
0.1%
10000000 33
 
2.1%
10117067 1
 
0.1%
ValueCountFrequency (%)
3425941807247 1
0.1%
2068129647456 1
0.1%
1581883842265 1
0.1%
1089349620000 1
0.1%
901489402779 1
0.1%
696796605919 1
0.1%
558584915317 1
0.1%
463534307000 1
0.1%
273228751333 1
0.1%
150088804865 1
0.1%

부채총액
Real number (ℝ)

MISSING  ZEROS 

Distinct267
Distinct (%)26.6%
Missing537
Missing (%)34.8%
Infinite0
Infinite (%)0.0%
Mean9.6608236 × 109
Minimum0
Maximum2.6194335 × 1012
Zeros687
Zeros (%)44.6%
Negative0
Negative (%)0.0%
Memory size13.7 KiB
2024-05-11T15:03:09.686888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q313137807
95-th percentile4.3319029 × 109
Maximum2.6194335 × 1012
Range2.6194335 × 1012
Interquartile range (IQR)13137807

Descriptive statistics

Standard deviation1.1855026 × 1011
Coefficient of variation (CV)12.271238
Kurtosis312.6816
Mean9.6608236 × 109
Median Absolute Deviation (MAD)0
Skewness16.787235
Sum9.7091277 × 1012
Variance1.4054164 × 1022
MonotonicityNot monotonic
2024-05-11T15:03:09.954144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 687
44.6%
1 40
 
2.6%
50000000 5
 
0.3%
10000000 3
 
0.2%
3892155 2
 
0.1%
74000000 2
 
0.1%
4331902925 2
 
0.1%
35091335 2
 
0.1%
1416191018 2
 
0.1%
40000000 2
 
0.1%
Other values (257) 258
 
16.7%
(Missing) 537
34.8%
ValueCountFrequency (%)
0 687
44.6%
1 40
 
2.6%
8181 1
 
0.1%
52800 1
 
0.1%
336790 1
 
0.1%
710000 1
 
0.1%
1555800 1
 
0.1%
1815121 1
 
0.1%
1835834 1
 
0.1%
1851000 1
 
0.1%
ValueCountFrequency (%)
2619433458767 1
0.1%
1812055671623 1
0.1%
1380953294924 1
0.1%
1087454170385 1
0.1%
794860980000 1
0.1%
355021085423 1
0.1%
289110858000 1
0.1%
220257176642 1
0.1%
189763635501 1
0.1%
148510483913 1
0.1%

자본금
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct171
Distinct (%)16.9%
Missing533
Missing (%)34.6%
Infinite0
Infinite (%)0.0%
Mean2.0600431 × 109
Minimum-1.8364842 × 1010
Maximum8.0650835 × 1011
Zeros440
Zeros (%)28.5%
Negative9
Negative (%)0.6%
Memory size13.7 KiB
2024-05-11T15:03:10.203520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.8364842 × 1010
5-th percentile0
Q10
median5000000
Q350000000
95-th percentile9.9448046 × 108
Maximum8.0650835 × 1011
Range8.2487319 × 1011
Interquartile range (IQR)50000000

Descriptive statistics

Standard deviation2.8074279 × 1010
Coefficient of variation (CV)13.628005
Kurtosis679.33215
Mean2.0600431 × 109
Median Absolute Deviation (MAD)5000000
Skewness24.604253
Sum2.0785835 × 1012
Variance7.8816516 × 1020
MonotonicityNot monotonic
2024-05-11T15:03:10.433691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 440
28.5%
50000000 136
 
8.8%
10000000 61
 
4.0%
1 41
 
2.7%
100000000 40
 
2.6%
30000000 21
 
1.4%
300000000 20
 
1.3%
20000000 19
 
1.2%
200000000 16
 
1.0%
500000000 11
 
0.7%
Other values (161) 204
 
13.2%
(Missing) 533
34.6%
ValueCountFrequency (%)
-18364841834 1
 
0.1%
-1219916553 1
 
0.1%
-842572442 1
 
0.1%
-690133461 1
 
0.1%
-390986902 1
 
0.1%
-145834523 1
 
0.1%
-45548448 1
 
0.1%
-3484965 1
 
0.1%
-1430640 1
 
0.1%
0 440
28.5%
ValueCountFrequency (%)
806508348480 1
0.1%
256073975833 1
0.1%
200000000000 1
0.1%
100000000000 1
0.1%
84104788000 1
0.1%
83465115832 1
0.1%
77286200000 1
0.1%
72710917898 1
0.1%
44740000000 1
0.1%
34707631011 1
0.1%

판매방식명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1542
Missing (%)100.0%
Memory size13.7 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
03220000200032201272420001120000829<NA>3폐업3폐업처리20060206<NA><NA>2000082902-552-4200<NA><NA>서울특별시 강남구 역삼동 일반번지 ***-*<NA><NA>(주)엘리온정보기술2008-01-31 16:20:47I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
13220000200032201272420011020030331<NA>4취소/말소/만료/정지/중지7직권말소20100406<NA><NA><NA>02-515-4488<NA><NA>서울특별시 강남구 논현동 일반 ***-**<NA><NA>(주)재우지에프2010-04-05 20:56:53I2018-08-31 23:59:59.0<NA><NA><NA>000<NA>
23220000200232201272420000120020801<NA>4취소/말소/만료/정지/중지7직권말소20100406<NA><NA>2002080102-555-2359<NA><NA>서울특별시 강남구 역삼동 일반번지 ***-**<NA><NA>밸리시스2010-04-20 15:27:00I2018-08-31 23:59:59.0<NA><NA><NA>000<NA>
33220000200232201272420000220020816<NA>4취소/말소/만료/정지/중지7직권말소20181203<NA><NA>2002081602-508-3448<NA><NA>서울특별시 강남구 역삼동 일반번지 ***-**<NA><NA>I.P club2018-11-19 18:14:03U2018-11-21 02:37:58.0<NA><NA><NA>000<NA>
43220000200232201272420000320020817<NA>4취소/말소/만료/정지/중지7직권말소20100406<NA><NA>2002081702-3452-3423<NA><NA>서울특별시 강남구 역삼동 일반번지 ***-**<NA><NA>Best Life2010-04-20 15:22:07I2018-08-31 23:59:59.0<NA><NA><NA>000<NA>
53220000200232201272420000420020819<NA>3폐업3폐업처리<NA><NA><NA>2002081902-708-5900<NA><NA>서울특별시 강남구 일반번지 ***-**<NA><NA>신화2008-01-31 16:20:47I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
63220000200232201272420000520020821<NA>4취소/말소/만료/정지/중지7직권말소20181203<NA><NA>2002082102-512-9881<NA><NA>서울특별시 강남구 논현동 일반번지 **-**<NA><NA>(주)아람에스알아이2018-11-05 18:43:25U2018-11-07 02:37:44.0<NA><NA><NA>000<NA>
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개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
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1533322000020243220249242000032024-02-22<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-6959-7017<NA><NA>서울특별시 강남구 대치동 ***-* 익성대치서울특별시 강남구 삼성로 ***, 쥬비스타워 *층 (대치동)06178주식회사 참투자자문2024-02-29 12:09:18U2023-12-03 00:02:00.0<NA>205029.234915444833.232388<NA><NA><NA><NA>
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