Overview

Dataset statistics

Number of variables29
Number of observations1105
Missing cells13195
Missing cells (%)41.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory266.7 KiB
Average record size in memory247.1 B

Variable types

Categorical6
Numeric9
Text8
DateTime3
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
Author강동구
URLhttps://data.seoul.go.kr/dataList/OA-18776/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (82.8%)Imbalance
폐업일자 has 625 (56.6%) missing valuesMissing
휴업시작일자 has 1098 (99.4%) missing valuesMissing
휴업종료일자 has 1098 (99.4%) missing valuesMissing
재개업일자 has 865 (78.3%) missing valuesMissing
전화번호 has 514 (46.5%) missing valuesMissing
소재지면적 has 1105 (100.0%) missing valuesMissing
소재지우편번호 has 731 (66.2%) missing valuesMissing
지번주소 has 231 (20.9%) missing valuesMissing
도로명주소 has 664 (60.1%) missing valuesMissing
도로명우편번호 has 664 (60.1%) missing valuesMissing
업태구분명 has 1105 (100.0%) missing valuesMissing
좌표정보(X) has 328 (29.7%) missing valuesMissing
좌표정보(Y) has 328 (29.7%) missing valuesMissing
자산규모 has 911 (82.4%) missing valuesMissing
부채총액 has 912 (82.5%) missing valuesMissing
자본금 has 911 (82.4%) missing valuesMissing
판매방식명 has 1105 (100.0%) missing valuesMissing
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 47 (4.3%) zerosZeros
부채총액 has 110 (10.0%) zerosZeros
자본금 has 40 (3.6%) zerosZeros

Reproduction

Analysis started2024-05-11 06:06:34.126639
Analysis finished2024-05-11 06:06:35.640404
Duration1.51 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
3240000
1105 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3240000
2nd row3240000
3rd row3240000
4th row3240000
5th row3240000

Common Values

ValueCountFrequency (%)
3240000 1105
100.0%

Length

2024-05-11T15:06:35.749969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:35.950318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3240000 1105
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct1105
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0108199 × 1018
Minimum1.996324 × 1018
Maximum2.024324 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.8 KiB
2024-05-11T15:06:36.279803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.996324 × 1018
5-th percentile2.002324 × 1018
Q12.006324 × 1018
median2.010324 × 1018
Q32.015324 × 1018
95-th percentile2.021324 × 1018
Maximum2.024324 × 1018
Range2.8000015 × 1016
Interquartile range (IQR)9.000005 × 1015

Descriptive statistics

Standard deviation5.881859 × 1015
Coefficient of variation (CV)0.0029251047
Kurtosis-0.65787163
Mean2.0108199 × 1018
Median Absolute Deviation (MAD)4.000005 × 1015
Skewness0.2514052
Sum8.3467496 × 1018
Variance3.4596265 × 1031
MonotonicityStrictly increasing
2024-05-11T15:06:36.631410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1996324013923200003 1
 
0.1%
2013324018923200025 1
 
0.1%
2013324018923200032 1
 
0.1%
2013324018923200030 1
 
0.1%
2013324018923200029 1
 
0.1%
2013324018923200028 1
 
0.1%
2013324018923200027 1
 
0.1%
2013324018923200026 1
 
0.1%
2013324018923200024 1
 
0.1%
2013324018923200014 1
 
0.1%
Other values (1095) 1095
99.1%
ValueCountFrequency (%)
1996324013923200003 1
0.1%
1996324013923200004 1
0.1%
1996324013923200005 1
0.1%
1996324013923200012 1
0.1%
1996324013923200019 1
0.1%
1996324013923200033 1
0.1%
1997324013923200050 1
0.1%
1997324013923200062 1
0.1%
1998324013923200067 1
0.1%
1998324013923200075 1
0.1%
ValueCountFrequency (%)
2024324028923200006 1
0.1%
2024324028923200005 1
0.1%
2024324028923200004 1
0.1%
2024324028923200003 1
0.1%
2024324028923200002 1
0.1%
2024324028923200001 1
0.1%
2023324028923200013 1
0.1%
2023324028923200012 1
0.1%
2023324028923200011 1
0.1%
2023324028923200010 1
0.1%
Distinct959
Distinct (%)86.8%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
2024-05-11T15:06:37.222241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.1122172
Min length8

Characters and Unicode

Total characters8964
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique838 ?
Unique (%)75.8%

Sample

1st row19961004
2nd row19961011
3rd row19961011
4th row19961111
5th row19961122
ValueCountFrequency (%)
20080808 5
 
0.5%
20070821 4
 
0.4%
20080612 4
 
0.4%
20050912 4
 
0.4%
20050622 3
 
0.3%
20030908 3
 
0.3%
20170906 3
 
0.3%
20110316 3
 
0.3%
20020312 3
 
0.3%
20100426 3
 
0.3%
Other values (949) 1070
96.8%
2024-05-11T15:06:38.075542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3103
34.6%
2 1947
21.7%
1 1514
16.9%
3 387
 
4.3%
6 352
 
3.9%
9 337
 
3.8%
7 330
 
3.7%
8 294
 
3.3%
5 294
 
3.3%
4 281
 
3.1%
Other values (2) 125
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8839
98.6%
Dash Punctuation 124
 
1.4%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3103
35.1%
2 1947
22.0%
1 1514
17.1%
3 387
 
4.4%
6 352
 
4.0%
9 337
 
3.8%
7 330
 
3.7%
8 294
 
3.3%
5 294
 
3.3%
4 281
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 124
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8964
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3103
34.6%
2 1947
21.7%
1 1514
16.9%
3 387
 
4.3%
6 352
 
3.9%
9 337
 
3.8%
7 330
 
3.7%
8 294
 
3.3%
5 294
 
3.3%
4 281
 
3.1%
Other values (2) 125
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8964
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3103
34.6%
2 1947
21.7%
1 1514
16.9%
3 387
 
4.3%
6 352
 
3.9%
9 337
 
3.8%
7 330
 
3.7%
8 294
 
3.3%
5 294
 
3.3%
4 281
 
3.1%
Other values (2) 125
 
1.4%

인허가취소일자
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
<NA>
1030 
20190418
 
67
20210916
 
6
20081204
 
1
20190419
 
1

Length

Max length8
Median length4
Mean length4.2714932
Min length4

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row<NA>
2nd row<NA>
3rd row20190418
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1030
93.2%
20190418 67
 
6.1%
20210916 6
 
0.5%
20081204 1
 
0.1%
20190419 1
 
0.1%

Length

2024-05-11T15:06:38.374151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:38.683577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1030
93.2%
20190418 67
 
6.1%
20210916 6
 
0.5%
20081204 1
 
0.1%
20190419 1
 
0.1%
Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
3
472 
4
448 
1
170 
5
 
8
2
 
7

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row4
3rd row4
4th row4
5th row1

Common Values

ValueCountFrequency (%)
3 472
42.7%
4 448
40.5%
1 170
 
15.4%
5 8
 
0.7%
2 7
 
0.6%

Length

2024-05-11T15:06:39.005143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:39.217892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 472
42.7%
4 448
40.5%
1 170
 
15.4%
5 8
 
0.7%
2 7
 
0.6%

영업상태명
Categorical

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
폐업
472 
취소/말소/만료/정지/중지
448 
영업/정상
170 
제외/삭제/전출
 
8
휴업
 
7

Length

Max length14
Median length8
Mean length7.3701357
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 row영업/정상

Common Values

ValueCountFrequency (%)
폐업 472
42.7%
취소/말소/만료/정지/중지 448
40.5%
영업/정상 170
 
15.4%
제외/삭제/전출 8
 
0.7%
휴업 7
 
0.6%

Length

2024-05-11T15:06:39.476716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:39.676558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 472
42.7%
취소/말소/만료/정지/중지 448
40.5%
영업/정상 170
 
15.4%
제외/삭제/전출 8
 
0.7%
휴업 7
 
0.6%

상세영업상태코드
Real number (ℝ)

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0995475
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.8 KiB
2024-05-11T15:06:39.828839image/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 deviation2.1954023
Coefficient of variation (CV)0.53552309
Kurtosis-1.344941
Mean4.0995475
Median Absolute Deviation (MAD)1
Skewness0.27286679
Sum4530
Variance4.8197915
MonotonicityNot monotonic
2024-05-11T15:06:40.001324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 472
42.7%
7 366
33.1%
1 170
 
15.4%
4 82
 
7.4%
5 8
 
0.7%
2 7
 
0.6%
ValueCountFrequency (%)
1 170
 
15.4%
2 7
 
0.6%
3 472
42.7%
4 82
 
7.4%
5 8
 
0.7%
7 366
33.1%
ValueCountFrequency (%)
7 366
33.1%
5 8
 
0.7%
4 82
 
7.4%
3 472
42.7%
2 7
 
0.6%
1 170
 
15.4%
Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
폐업처리
472 
직권말소
366 
정상영업
170 
직권취소
82 
타시군구이관
 
8

Length

Max length6
Median length4
Mean length4.0144796
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업처리 472
42.7%
직권말소 366
33.1%
정상영업 170
 
15.4%
직권취소 82
 
7.4%
타시군구이관 8
 
0.7%
휴업처리 7
 
0.6%

Length

2024-05-11T15:06:40.251758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:40.472182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업처리 472
42.7%
직권말소 366
33.1%
정상영업 170
 
15.4%
직권취소 82
 
7.4%
타시군구이관 8
 
0.7%
휴업처리 7
 
0.6%

폐업일자
Date

MISSING 

Distinct399
Distinct (%)83.1%
Missing625
Missing (%)56.6%
Memory size8.8 KiB
Minimum2007-05-23 00:00:00
Maximum2024-02-14 00:00:00
2024-05-11T15:06:40.742619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:06:41.484743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)85.7%
Missing1098
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean20160937
Minimum20070316
Maximum20201208
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.8 KiB
2024-05-11T15:06:41.713389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20070316
5-th percentile20076582
Q120126201
median20200713
Q320200961
95-th percentile20201208
Maximum20201208
Range130892
Interquartile range (IQR)74760

Descriptive statistics

Standard deviation56984.196
Coefficient of variation (CV)0.0028264656
Kurtosis-0.91416386
Mean20160937
Median Absolute Deviation (MAD)495
Skewness-1.0426661
Sum1.4112656 × 108
Variance3.2471986 × 109
MonotonicityNot monotonic
2024-05-11T15:06:41.917864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
20201208 2
 
0.2%
20070316 1
 
0.1%
20091201 1
 
0.1%
20200714 1
 
0.1%
20161201 1
 
0.1%
20200713 1
 
0.1%
(Missing) 1098
99.4%
ValueCountFrequency (%)
20070316 1
0.1%
20091201 1
0.1%
20161201 1
0.1%
20200713 1
0.1%
20200714 1
0.1%
20201208 2
0.2%
ValueCountFrequency (%)
20201208 2
0.2%
20200714 1
0.1%
20200713 1
0.1%
20161201 1
0.1%
20091201 1
0.1%
20070316 1
0.1%

휴업종료일자
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)100.0%
Missing1098
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean20179579
Minimum20080315
Maximum20231231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.8 KiB
2024-05-11T15:06:42.203622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20080315
5-th percentile20095410
Q120150930
median20201231
Q320221208
95-th percentile20231224
Maximum20231231
Range150916
Interquartile range (IQR)70278

Descriptive statistics

Standard deviation56453.133
Coefficient of variation (CV)0.0027975377
Kurtosis0.034469937
Mean20179579
Median Absolute Deviation (MAD)30000
Skewness-1.0099496
Sum1.4125705 × 108
Variance3.1869563 × 109
MonotonicityNot monotonic
2024-05-11T15:06:42.367245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
20080315 1
 
0.1%
20130630 1
 
0.1%
20201231 1
 
0.1%
20171230 1
 
0.1%
20211208 1
 
0.1%
20231208 1
 
0.1%
20231231 1
 
0.1%
(Missing) 1098
99.4%
ValueCountFrequency (%)
20080315 1
0.1%
20130630 1
0.1%
20171230 1
0.1%
20201231 1
0.1%
20211208 1
0.1%
20231208 1
0.1%
20231231 1
0.1%
ValueCountFrequency (%)
20231231 1
0.1%
20231208 1
0.1%
20211208 1
0.1%
20201231 1
0.1%
20171230 1
0.1%
20130630 1
0.1%
20080315 1
0.1%

재개업일자
Text

MISSING 

Distinct219
Distinct (%)91.2%
Missing865
Missing (%)78.3%
Memory size8.8 KiB
2024-05-11T15:06:42.887099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.0666667
Min length8

Characters and Unicode

Total characters1936
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique200 ?
Unique (%)83.3%

Sample

1st row19961011
2nd row19961011
3rd row19961111
4th row19961122
5th row19971107
ValueCountFrequency (%)
20030908 3
 
1.2%
20020312 3
 
1.2%
20060314 2
 
0.8%
20040302 2
 
0.8%
20030224 2
 
0.8%
20061107 2
 
0.8%
20021231 2
 
0.8%
20060516 2
 
0.8%
20050912 2
 
0.8%
20051123 2
 
0.8%
Other values (209) 218
90.8%
2024-05-11T15:06:43.759492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 755
39.0%
2 411
21.2%
1 234
 
12.1%
3 104
 
5.4%
6 95
 
4.9%
5 80
 
4.1%
4 79
 
4.1%
7 67
 
3.5%
8 49
 
2.5%
9 45
 
2.3%
Other values (2) 17
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1919
99.1%
Dash Punctuation 16
 
0.8%
Space Separator 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 755
39.3%
2 411
21.4%
1 234
 
12.2%
3 104
 
5.4%
6 95
 
5.0%
5 80
 
4.2%
4 79
 
4.1%
7 67
 
3.5%
8 49
 
2.6%
9 45
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1936
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 755
39.0%
2 411
21.2%
1 234
 
12.1%
3 104
 
5.4%
6 95
 
4.9%
5 80
 
4.1%
4 79
 
4.1%
7 67
 
3.5%
8 49
 
2.5%
9 45
 
2.3%
Other values (2) 17
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1936
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 755
39.0%
2 411
21.2%
1 234
 
12.1%
3 104
 
5.4%
6 95
 
4.9%
5 80
 
4.1%
4 79
 
4.1%
7 67
 
3.5%
8 49
 
2.5%
9 45
 
2.3%
Other values (2) 17
 
0.9%

전화번호
Text

MISSING 

Distinct557
Distinct (%)94.2%
Missing514
Missing (%)46.5%
Memory size8.8 KiB
2024-05-11T15:06:44.229221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length9.9813875
Min length1

Characters and Unicode

Total characters5899
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique528 ?
Unique (%)89.3%

Sample

1st row02 472 4792
2nd row02 472 9341
3rd row02 472 1586
4th row02 477 1158
5th row02 478 4080
ValueCountFrequency (%)
02 73
 
9.9%
487 7
 
0.9%
478 7
 
0.9%
473-7083 4
 
0.5%
486 4
 
0.5%
481 4
 
0.5%
471 4
 
0.5%
02-487-3388 3
 
0.4%
485 3
 
0.4%
483 3
 
0.4%
Other values (583) 626
84.8%
2024-05-11T15:06:44.990995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 791
13.4%
- 751
12.7%
4 745
12.6%
2 701
11.9%
8 533
9.0%
7 514
8.7%
1 383
6.5%
3 359
6.1%
5 341
5.8%
6 340
5.8%
Other values (4) 441
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4933
83.6%
Dash Punctuation 751
 
12.7%
Space Separator 212
 
3.6%
Other Punctuation 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 791
16.0%
4 745
15.1%
2 701
14.2%
8 533
10.8%
7 514
10.4%
1 383
7.8%
3 359
7.3%
5 341
6.9%
6 340
6.9%
9 226
 
4.6%
Dash Punctuation
ValueCountFrequency (%)
- 751
100.0%
Space Separator
ValueCountFrequency (%)
212
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5899
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 791
13.4%
- 751
12.7%
4 745
12.6%
2 701
11.9%
8 533
9.0%
7 514
8.7%
1 383
6.5%
3 359
6.1%
5 341
5.8%
6 340
5.8%
Other values (4) 441
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5899
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 791
13.4%
- 751
12.7%
4 745
12.6%
2 701
11.9%
8 533
9.0%
7 514
8.7%
1 383
6.5%
3 359
6.1%
5 341
5.8%
6 340
5.8%
Other values (4) 441
7.5%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1105
Missing (%)100.0%
Memory size9.8 KiB

소재지우편번호
Text

MISSING 

Distinct77
Distinct (%)20.6%
Missing731
Missing (%)66.2%
Memory size8.8 KiB
2024-05-11T15:06:45.435741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0053476
Min length6

Characters and Unicode

Total characters2246
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

Unique30 ?
Unique (%)8.0%

Sample

1st row134874
2nd row134033
3rd row134033
4th row134838
5th row134030
ValueCountFrequency (%)
134030 48
 
12.8%
134010 44
 
11.8%
134020 38
 
10.2%
134070 20
 
5.3%
134033 12
 
3.2%
134830 11
 
2.9%
134864 9
 
2.4%
134861 9
 
2.4%
134050 9
 
2.4%
134840 8
 
2.1%
Other values (67) 166
44.4%
2024-05-11T15:06:46.183771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 490
21.8%
3 485
21.6%
0 443
19.7%
4 430
19.1%
8 164
 
7.3%
2 76
 
3.4%
7 60
 
2.7%
6 49
 
2.2%
5 35
 
1.6%
9 12
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2244
99.9%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 490
21.8%
3 485
21.6%
0 443
19.7%
4 430
19.2%
8 164
 
7.3%
2 76
 
3.4%
7 60
 
2.7%
6 49
 
2.2%
5 35
 
1.6%
9 12
 
0.5%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2246
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 490
21.8%
3 485
21.6%
0 443
19.7%
4 430
19.1%
8 164
 
7.3%
2 76
 
3.4%
7 60
 
2.7%
6 49
 
2.2%
5 35
 
1.6%
9 12
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2246
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 490
21.8%
3 485
21.6%
0 443
19.7%
4 430
19.1%
8 164
 
7.3%
2 76
 
3.4%
7 60
 
2.7%
6 49
 
2.2%
5 35
 
1.6%
9 12
 
0.5%

지번주소
Text

MISSING 

Distinct651
Distinct (%)74.5%
Missing231
Missing (%)20.9%
Memory size8.8 KiB
2024-05-11T15:06:46.477947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length41
Mean length25.447368
Min length11

Characters and Unicode

Total characters22241
Distinct characters271
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

Unique558 ?
Unique (%)63.8%

Sample

1st row강동구 천호동 ***-** 삼오빌딩 ***호
2nd row강동구 천호동 ***-* 상일신관 ***호
3rd row강동구 성내동 ***-* 금익B/D *층
4th row강동구 천호동 *** 호산B/D 가-***호
5th row강동구 성내동 ***-** 우용상가 ***호
ValueCountFrequency (%)
강동구 867
18.5%
660
14.1%
서울특별시 564
12.1%
번지 469
10.0%
393
8.4%
성내동 225
 
4.8%
199
 
4.3%
길동 168
 
3.6%
천호동 155
 
3.3%
명일동 71
 
1.5%
Other values (428) 903
19.3%
2024-05-11T15:06:47.126249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 5202
23.4%
4197
18.9%
1799
 
8.1%
916
 
4.1%
906
 
4.1%
877
 
3.9%
584
 
2.6%
569
 
2.6%
565
 
2.5%
564
 
2.5%
Other values (261) 6062
27.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12074
54.3%
Other Punctuation 5312
23.9%
Space Separator 4197
 
18.9%
Dash Punctuation 379
 
1.7%
Uppercase Letter 133
 
0.6%
Open Punctuation 63
 
0.3%
Close Punctuation 62
 
0.3%
Decimal Number 11
 
< 0.1%
Lowercase Letter 6
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1799
14.9%
916
 
7.6%
906
 
7.5%
877
 
7.3%
584
 
4.8%
569
 
4.7%
565
 
4.7%
564
 
4.7%
564
 
4.7%
530
 
4.4%
Other values (228) 4200
34.8%
Uppercase Letter
ValueCountFrequency (%)
B 60
45.1%
D 52
39.1%
K 5
 
3.8%
S 3
 
2.3%
T 3
 
2.3%
F 2
 
1.5%
A 2
 
1.5%
C 1
 
0.8%
I 1
 
0.8%
L 1
 
0.8%
Other values (3) 3
 
2.3%
Decimal Number
ValueCountFrequency (%)
4 4
36.4%
1 3
27.3%
9 1
 
9.1%
0 1
 
9.1%
3 1
 
9.1%
6 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
* 5202
97.9%
/ 50
 
0.9%
. 41
 
0.8%
, 12
 
0.2%
@ 7
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
k 3
50.0%
b 1
 
16.7%
s 1
 
16.7%
t 1
 
16.7%
Space Separator
ValueCountFrequency (%)
4197
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 379
100.0%
Open Punctuation
ValueCountFrequency (%)
( 63
100.0%
Close Punctuation
ValueCountFrequency (%)
) 62
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12074
54.3%
Common 10028
45.1%
Latin 139
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1799
14.9%
916
 
7.6%
906
 
7.5%
877
 
7.3%
584
 
4.8%
569
 
4.7%
565
 
4.7%
564
 
4.7%
564
 
4.7%
530
 
4.4%
Other values (228) 4200
34.8%
Latin
ValueCountFrequency (%)
B 60
43.2%
D 52
37.4%
K 5
 
3.6%
S 3
 
2.2%
T 3
 
2.2%
k 3
 
2.2%
F 2
 
1.4%
A 2
 
1.4%
C 1
 
0.7%
I 1
 
0.7%
Other values (7) 7
 
5.0%
Common
ValueCountFrequency (%)
* 5202
51.9%
4197
41.9%
- 379
 
3.8%
( 63
 
0.6%
) 62
 
0.6%
/ 50
 
0.5%
. 41
 
0.4%
, 12
 
0.1%
@ 7
 
0.1%
4 4
 
< 0.1%
Other values (6) 11
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12074
54.3%
ASCII 10167
45.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 5202
51.2%
4197
41.3%
- 379
 
3.7%
( 63
 
0.6%
) 62
 
0.6%
B 60
 
0.6%
D 52
 
0.5%
/ 50
 
0.5%
. 41
 
0.4%
, 12
 
0.1%
Other values (23) 49
 
0.5%
Hangul
ValueCountFrequency (%)
1799
14.9%
916
 
7.6%
906
 
7.5%
877
 
7.3%
584
 
4.8%
569
 
4.7%
565
 
4.7%
564
 
4.7%
564
 
4.7%
530
 
4.4%
Other values (228) 4200
34.8%

도로명주소
Text

MISSING 

Distinct366
Distinct (%)83.0%
Missing664
Missing (%)60.1%
Memory size8.8 KiB
2024-05-11T15:06:47.482702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length44
Mean length32.643991
Min length17

Characters and Unicode

Total characters14396
Distinct characters225
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

Unique313 ?
Unique (%)71.0%

Sample

1st row서울특별시 강동구 고덕로 *** (암사동)
2nd row서울특별시 강동구 양재대로 ****, 성환빌딩 (길동)
3rd row서울특별시 강동구 구천면로 *** (상일동)
4th row서울특별시 강동구 올림픽로 *** (천호동)
5th row서울특별시 강동구 양재대로***길 **, *층 (명일동)
ValueCountFrequency (%)
서울특별시 441
15.6%
440
15.6%
강동구 438
15.5%
183
 
6.5%
178
 
6.3%
성내동 119
 
4.2%
천호동 95
 
3.4%
길동 80
 
2.8%
양재대로 52
 
1.8%
명일동 46
 
1.6%
Other values (239) 757
26.8%
2024-05-11T15:06:48.201687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 2522
17.5%
2389
16.6%
943
 
6.6%
470
 
3.3%
465
 
3.2%
447
 
3.1%
445
 
3.1%
) 444
 
3.1%
( 444
 
3.1%
443
 
3.1%
Other values (215) 5384
37.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8038
55.8%
Other Punctuation 2968
 
20.6%
Space Separator 2389
 
16.6%
Close Punctuation 444
 
3.1%
Open Punctuation 444
 
3.1%
Dash Punctuation 54
 
0.4%
Uppercase Letter 35
 
0.2%
Decimal Number 21
 
0.1%
Math Symbol 2
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
943
 
11.7%
470
 
5.8%
465
 
5.8%
447
 
5.6%
445
 
5.5%
443
 
5.5%
441
 
5.5%
441
 
5.5%
433
 
5.4%
368
 
4.6%
Other values (180) 3142
39.1%
Uppercase Letter
ValueCountFrequency (%)
B 9
25.7%
S 4
11.4%
T 3
 
8.6%
K 3
 
8.6%
F 3
 
8.6%
H 2
 
5.7%
E 2
 
5.7%
D 2
 
5.7%
I 2
 
5.7%
C 1
 
2.9%
Other values (4) 4
11.4%
Decimal Number
ValueCountFrequency (%)
1 6
28.6%
2 4
19.0%
5 2
 
9.5%
0 2
 
9.5%
6 2
 
9.5%
3 2
 
9.5%
7 1
 
4.8%
4 1
 
4.8%
8 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
* 2522
85.0%
, 441
 
14.9%
/ 2
 
0.1%
. 1
 
< 0.1%
& 1
 
< 0.1%
@ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
2389
100.0%
Close Punctuation
ValueCountFrequency (%)
) 444
100.0%
Open Punctuation
ValueCountFrequency (%)
( 444
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
n 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8038
55.8%
Common 6322
43.9%
Latin 36
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
943
 
11.7%
470
 
5.8%
465
 
5.8%
447
 
5.6%
445
 
5.5%
443
 
5.5%
441
 
5.5%
441
 
5.5%
433
 
5.4%
368
 
4.6%
Other values (180) 3142
39.1%
Common
ValueCountFrequency (%)
* 2522
39.9%
2389
37.8%
) 444
 
7.0%
( 444
 
7.0%
, 441
 
7.0%
- 54
 
0.9%
1 6
 
0.1%
2 4
 
0.1%
5 2
 
< 0.1%
0 2
 
< 0.1%
Other values (10) 14
 
0.2%
Latin
ValueCountFrequency (%)
B 9
25.0%
S 4
11.1%
T 3
 
8.3%
K 3
 
8.3%
F 3
 
8.3%
H 2
 
5.6%
E 2
 
5.6%
D 2
 
5.6%
I 2
 
5.6%
C 1
 
2.8%
Other values (5) 5
13.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8038
55.8%
ASCII 6358
44.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 2522
39.7%
2389
37.6%
) 444
 
7.0%
( 444
 
7.0%
, 441
 
6.9%
- 54
 
0.8%
B 9
 
0.1%
1 6
 
0.1%
2 4
 
0.1%
S 4
 
0.1%
Other values (25) 41
 
0.6%
Hangul
ValueCountFrequency (%)
943
 
11.7%
470
 
5.8%
465
 
5.8%
447
 
5.6%
445
 
5.5%
443
 
5.5%
441
 
5.5%
441
 
5.5%
433
 
5.4%
368
 
4.6%
Other values (180) 3142
39.1%

도로명우편번호
Text

MISSING 

Distinct181
Distinct (%)41.0%
Missing664
Missing (%)60.1%
Memory size8.8 KiB
2024-05-11T15:06:48.874844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.3741497
Min length5

Characters and Unicode

Total characters2370
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

Unique74 ?
Unique (%)16.8%

Sample

1st row05255
2nd row05342
3rd row134834
4th row134-867
5th row134830
ValueCountFrequency (%)
05376 10
 
2.3%
134868 9
 
2.0%
134830 9
 
2.0%
134851 8
 
1.8%
05302 8
 
1.8%
05303 8
 
1.8%
05354 8
 
1.8%
05246 7
 
1.6%
134814 6
 
1.4%
05352 6
 
1.4%
Other values (171) 362
82.1%
2024-05-11T15:06:49.916816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 405
17.1%
3 402
17.0%
5 379
16.0%
4 280
11.8%
1 251
10.6%
8 209
8.8%
2 183
7.7%
7 108
 
4.6%
6 90
 
3.8%
9 58
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2365
99.8%
Dash Punctuation 5
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 405
17.1%
3 402
17.0%
5 379
16.0%
4 280
11.8%
1 251
10.6%
8 209
8.8%
2 183
7.7%
7 108
 
4.6%
6 90
 
3.8%
9 58
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2370
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 405
17.1%
3 402
17.0%
5 379
16.0%
4 280
11.8%
1 251
10.6%
8 209
8.8%
2 183
7.7%
7 108
 
4.6%
6 90
 
3.8%
9 58
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2370
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 405
17.1%
3 402
17.0%
5 379
16.0%
4 280
11.8%
1 251
10.6%
8 209
8.8%
2 183
7.7%
7 108
 
4.6%
6 90
 
3.8%
9 58
 
2.4%
Distinct1055
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
2024-05-11T15:06:50.372497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length22
Mean length7.0208145
Min length2

Characters and Unicode

Total characters7758
Distinct characters535
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1012 ?
Unique (%)91.6%

Sample

1st row유니베라 광나루대리점
2nd row경향기획
3rd row한국삐아제교육연구원
4th row생그린화장품
5th row기아자동차둔촌대리점
ValueCountFrequency (%)
주식회사 46
 
3.4%
마임 11
 
0.8%
11
 
0.8%
인셀덤 10
 
0.7%
강동지사 7
 
0.5%
강동점 6
 
0.4%
강동대리점 6
 
0.4%
에치와이 6
 
0.4%
윤선생 4
 
0.3%
코리아 4
 
0.3%
Other values (1160) 1257
91.9%
2024-05-11T15:06:51.126248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
270
 
3.5%
263
 
3.4%
192
 
2.5%
179
 
2.3%
( 176
 
2.3%
) 176
 
2.3%
173
 
2.2%
156
 
2.0%
132
 
1.7%
119
 
1.5%
Other values (525) 5922
76.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6584
84.9%
Uppercase Letter 271
 
3.5%
Space Separator 263
 
3.4%
Open Punctuation 176
 
2.3%
Close Punctuation 176
 
2.3%
Lowercase Letter 83
 
1.1%
Decimal Number 73
 
0.9%
Other Symbol 72
 
0.9%
Other Punctuation 49
 
0.6%
Dash Punctuation 10
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
270
 
4.1%
192
 
2.9%
179
 
2.7%
173
 
2.6%
156
 
2.4%
132
 
2.0%
119
 
1.8%
114
 
1.7%
103
 
1.6%
102
 
1.5%
Other values (463) 5044
76.6%
Uppercase Letter
ValueCountFrequency (%)
S 30
 
11.1%
E 27
 
10.0%
T 22
 
8.1%
A 20
 
7.4%
K 19
 
7.0%
N 17
 
6.3%
R 16
 
5.9%
D 16
 
5.9%
M 15
 
5.5%
H 12
 
4.4%
Other values (12) 77
28.4%
Lowercase Letter
ValueCountFrequency (%)
e 14
16.9%
o 9
10.8%
i 7
 
8.4%
r 6
 
7.2%
l 6
 
7.2%
s 5
 
6.0%
d 4
 
4.8%
t 4
 
4.8%
m 4
 
4.8%
a 4
 
4.8%
Other values (11) 20
24.1%
Decimal Number
ValueCountFrequency (%)
0 17
23.3%
3 12
16.4%
2 12
16.4%
1 11
15.1%
7 6
 
8.2%
5 5
 
6.8%
6 5
 
6.8%
9 3
 
4.1%
8 1
 
1.4%
4 1
 
1.4%
Other Punctuation
ValueCountFrequency (%)
. 34
69.4%
& 12
 
24.5%
/ 3
 
6.1%
Space Separator
ValueCountFrequency (%)
263
100.0%
Open Punctuation
ValueCountFrequency (%)
( 176
100.0%
Close Punctuation
ValueCountFrequency (%)
) 176
100.0%
Other Symbol
ValueCountFrequency (%)
72
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6654
85.8%
Common 748
 
9.6%
Latin 354
 
4.6%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
270
 
4.1%
192
 
2.9%
179
 
2.7%
173
 
2.6%
156
 
2.3%
132
 
2.0%
119
 
1.8%
114
 
1.7%
103
 
1.5%
102
 
1.5%
Other values (463) 5114
76.9%
Latin
ValueCountFrequency (%)
S 30
 
8.5%
E 27
 
7.6%
T 22
 
6.2%
A 20
 
5.6%
K 19
 
5.4%
N 17
 
4.8%
R 16
 
4.5%
D 16
 
4.5%
M 15
 
4.2%
e 14
 
4.0%
Other values (33) 158
44.6%
Common
ValueCountFrequency (%)
263
35.2%
( 176
23.5%
) 176
23.5%
. 34
 
4.5%
0 17
 
2.3%
& 12
 
1.6%
3 12
 
1.6%
2 12
 
1.6%
1 11
 
1.5%
- 10
 
1.3%
Other values (8) 25
 
3.3%
Han
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6582
84.8%
ASCII 1102
 
14.2%
None 72
 
0.9%
CJK 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
270
 
4.1%
192
 
2.9%
179
 
2.7%
173
 
2.6%
156
 
2.4%
132
 
2.0%
119
 
1.8%
114
 
1.7%
103
 
1.6%
102
 
1.5%
Other values (462) 5042
76.6%
ASCII
ValueCountFrequency (%)
263
23.9%
( 176
16.0%
) 176
16.0%
. 34
 
3.1%
S 30
 
2.7%
E 27
 
2.5%
T 22
 
2.0%
A 20
 
1.8%
K 19
 
1.7%
0 17
 
1.5%
Other values (51) 318
28.9%
None
ValueCountFrequency (%)
72
100.0%
CJK
ValueCountFrequency (%)
2
100.0%
Distinct1084
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
Minimum2007-06-30 22:18:49
Maximum2024-05-09 13:25:34
2024-05-11T15:06:51.496529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:06:51.782455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
I
849 
U
256 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 849
76.8%
U 256
 
23.2%

Length

2024-05-11T15:06:52.020704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:52.168715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 849
76.8%
u 256
 
23.2%
Distinct177
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T15:06:52.347229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:06:52.585083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1105
Missing (%)100.0%
Memory size9.8 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct515
Distinct (%)66.3%
Missing328
Missing (%)29.7%
Infinite0
Infinite (%)0.0%
Mean211870.66
Minimum167789.6
Maximum226417.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.8 KiB
2024-05-11T15:06:52.826210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum167789.6
5-th percentile210731.34
Q1211308.17
median211898.93
Q3212540.99
95-th percentile213637.6
Maximum226417.65
Range58628.045
Interquartile range (IQR)1232.8225

Descriptive statistics

Standard deviation2331.098
Coefficient of variation (CV)0.011002458
Kurtosis190.75005
Mean211870.66
Median Absolute Deviation (MAD)631.18006
Skewness-11.167916
Sum1.646235 × 108
Variance5434017.9
MonotonicityNot monotonic
2024-05-11T15:06:53.116667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
211336.172451748 13
 
1.2%
212588.317959994 12
 
1.1%
211364.05352846 12
 
1.1%
211542.314116941 9
 
0.8%
211997.374303563 9
 
0.8%
212453.914837248 9
 
0.8%
211980.248325806 8
 
0.7%
211865.631863483 8
 
0.7%
211976.269176583 7
 
0.6%
210648.995783052 7
 
0.6%
Other values (505) 683
61.8%
(Missing) 328
29.7%
ValueCountFrequency (%)
167789.600877091 1
 
0.1%
190461.790473157 2
 
0.2%
191917.450107657 1
 
0.1%
204588.218577866 1
 
0.1%
210553.290352325 2
 
0.2%
210575.541535172 1
 
0.1%
210634.358221322 4
0.4%
210648.995783052 7
0.6%
210649.789630326 1
 
0.1%
210651.061261548 1
 
0.1%
ValueCountFrequency (%)
226417.645595042 1
0.1%
215875.024969 1
0.1%
215784.2264 1
0.1%
215659.154061 1
0.1%
215422.746119624 2
0.2%
215384.844269 1
0.1%
215331.019 1
0.1%
215235.910911 1
0.1%
215212.94326834 1
0.1%
215195.884311721 1
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct515
Distinct (%)66.3%
Missing328
Missing (%)29.7%
Infinite0
Infinite (%)0.0%
Mean448629.24
Minimum420821.92
Maximum460419.89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.8 KiB
2024-05-11T15:06:53.331244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum420821.92
5-th percentile447161.87
Q1447973.17
median448613.06
Q3449479.72
95-th percentile450276.85
Maximum460419.89
Range39597.97
Interquartile range (IQR)1506.5548

Descriptive statistics

Standard deviation1591.7745
Coefficient of variation (CV)0.0035480845
Kurtosis125.79627
Mean448629.24
Median Absolute Deviation (MAD)757.7086
Skewness-6.8813763
Sum3.4858492 × 108
Variance2533745.9
MonotonicityNot monotonic
2024-05-11T15:06:53.572876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
448556.794492412 13
 
1.2%
449831.02984364 12
 
1.1%
448994.865229729 12
 
1.1%
448811.888382662 9
 
0.8%
448273.114107211 9
 
0.8%
447998.814231451 9
 
0.8%
448134.343948346 8
 
0.7%
448111.060277943 8
 
0.7%
447462.077236492 7
 
0.6%
449091.167481686 7
 
0.6%
Other values (505) 683
61.8%
(Missing) 328
29.7%
ValueCountFrequency (%)
420821.921380891 1
0.1%
438699.77460936 1
0.1%
440631.957492255 1
0.1%
442368.090413171 2
0.2%
444353.979805195 1
0.1%
446699.196101461 2
0.2%
446732.640167362 1
0.1%
446830.533862009 1
0.1%
446840.380598728 1
0.1%
446862.234226426 1
0.1%
ValueCountFrequency (%)
460419.891464186 1
0.1%
452309.711718 1
0.1%
452130.329696 1
0.1%
452042.723062516 1
0.1%
451495.534517004 1
0.1%
451415.098861 1
0.1%
451370.39819 1
0.1%
451286.427527 1
0.1%
451133.508498096 1
0.1%
451069.15221101 1
0.1%

자산규모
Real number (ℝ)

MISSING  ZEROS 

Distinct84
Distinct (%)43.3%
Missing911
Missing (%)82.4%
Infinite0
Infinite (%)0.0%
Mean7.9822913 × 109
Minimum0
Maximum1.3308842 × 1012
Zeros47
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size9.8 KiB
2024-05-11T15:06:53.786308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15437500
median50000000
Q32 × 108
95-th percentile3.1513891 × 109
Maximum1.3308842 × 1012
Range1.3308842 × 1012
Interquartile range (IQR)1.945625 × 108

Descriptive statistics

Standard deviation9.5902127 × 1010
Coefficient of variation (CV)12.014361
Kurtosis190.49178
Mean7.9822913 × 109
Median Absolute Deviation (MAD)50000000
Skewness13.750633
Sum1.5485645 × 1012
Variance9.1972179 × 1021
MonotonicityNot monotonic
2024-05-11T15:06:53.969418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 47
 
4.3%
50000000 26
 
2.4%
10000000 17
 
1.5%
100000000 9
 
0.8%
20000000 5
 
0.5%
200000000 5
 
0.5%
300000000 3
 
0.3%
30000000 2
 
0.2%
1188723680 2
 
0.2%
35000000 2
 
0.2%
Other values (74) 76
 
6.9%
(Missing) 911
82.4%
ValueCountFrequency (%)
0 47
4.3%
4370000 1
 
0.1%
5000000 1
 
0.1%
6750000 1
 
0.1%
10000000 17
 
1.5%
11000000 1
 
0.1%
15000000 1
 
0.1%
15356150 1
 
0.1%
15550000 1
 
0.1%
20000000 5
 
0.5%
ValueCountFrequency (%)
1330884250000 1
0.1%
124595187788 1
0.1%
20000000000 1
0.1%
8372605043 1
0.1%
5774587503 1
0.1%
5505422645 1
0.1%
5088628700 1
0.1%
4387527239 1
0.1%
3945368956 1
0.1%
3527156606 1
0.1%

부채총액
Real number (ℝ)

MISSING  ZEROS 

Distinct73
Distinct (%)37.8%
Missing912
Missing (%)82.5%
Infinite0
Infinite (%)0.0%
Mean6.9919105 × 109
Minimum-40000000
Maximum1.2606033 × 1012
Zeros110
Zeros (%)10.0%
Negative1
Negative (%)0.1%
Memory size9.8 KiB
2024-05-11T15:06:54.191458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-40000000
5-th percentile0
Q10
median0
Q378398027
95-th percentile1.448305 × 109
Maximum1.2606033 × 1012
Range1.2606433 × 1012
Interquartile range (IQR)78398027

Descriptive statistics

Standard deviation9.0736133 × 1010
Coefficient of variation (CV)12.977302
Kurtosis192.74755
Mean6.9919105 × 109
Median Absolute Deviation (MAD)0
Skewness13.879022
Sum1.3494387 × 1012
Variance8.2330458 × 1021
MonotonicityNot monotonic
2024-05-11T15:06:54.393569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 110
 
10.0%
20000000 4
 
0.4%
150000000 3
 
0.3%
50000000 3
 
0.3%
10000000 2
 
0.2%
80000000 2
 
0.2%
636375077 2
 
0.2%
5000000 2
 
0.2%
335662734 1
 
0.1%
68587652 1
 
0.1%
Other values (63) 63
 
5.7%
(Missing) 912
82.5%
ValueCountFrequency (%)
-40000000 1
 
0.1%
0 110
10.0%
10 1
 
0.1%
164251 1
 
0.1%
2000000 1
 
0.1%
2244000 1
 
0.1%
3011144 1
 
0.1%
3364160 1
 
0.1%
4079999 1
 
0.1%
5000000 2
 
0.2%
ValueCountFrequency (%)
1260603310000 1
0.1%
25227547240 1
0.1%
15657192839 1
0.1%
9187510080 1
0.1%
6680290482 1
0.1%
4310030216 1
0.1%
2128112653 1
0.1%
2064488972 1
0.1%
1723185280 1
0.1%
1681969985 1
0.1%

자본금
Real number (ℝ)

MISSING  ZEROS 

Distinct49
Distinct (%)25.3%
Missing911
Missing (%)82.4%
Infinite0
Infinite (%)0.0%
Mean9.9931396 × 108
Minimum-9.0570298 × 108
Maximum9.9367641 × 1010
Zeros40
Zeros (%)3.6%
Negative4
Negative (%)0.4%
Memory size9.8 KiB
2024-05-11T15:06:54.545317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-9.0570298 × 108
5-th percentile0
Q16760000
median50000000
Q31 × 108
95-th percentile5.0933797 × 108
Maximum9.9367641 × 1010
Range1.0027334 × 1011
Interquartile range (IQR)93240000

Descriptive statistics

Standard deviation8.718802 × 109
Coefficient of variation (CV)8.7247875
Kurtosis104.86773
Mean9.9931396 × 108
Median Absolute Deviation (MAD)47570969
Skewness10.145041
Sum1.9386691 × 1011
Variance7.6017508 × 1019
MonotonicityNot monotonic
2024-05-11T15:06:54.711794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
50000000 47
 
4.3%
0 40
 
3.6%
10000000 28
 
2.5%
100000000 11
 
1.0%
200000000 7
 
0.6%
300000000 6
 
0.5%
150000000 4
 
0.4%
20000000 4
 
0.4%
30000000 3
 
0.3%
250000000 3
 
0.3%
Other values (39) 41
 
3.7%
(Missing) 911
82.4%
ValueCountFrequency (%)
-905702979 1
 
0.1%
-364661260 1
 
0.1%
-70782448 1
 
0.1%
-37271901 1
 
0.1%
0 40
3.6%
1 1
 
0.1%
1000000 1
 
0.1%
1858062 1
 
0.1%
3000000 1
 
0.1%
6750000 1
 
0.1%
ValueCountFrequency (%)
99367640548 1
0.1%
70280897000 1
0.1%
5660353474 1
0.1%
3365443330 1
0.1%
1739390840 1
0.1%
728643460 1
0.1%
665000000 1
0.1%
623422220 1
0.1%
531156712 1
0.1%
526679921 1
0.1%

판매방식명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1105
Missing (%)100.0%
Memory size9.8 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
03240000199632401392320000319961004<NA>3폐업3폐업처리20110916<NA><NA><NA>02 472 4792<NA><NA>강동구 천호동 ***-** 삼오빌딩 ***호<NA><NA>유니베라 광나루대리점2011-09-16 13:57:38I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
13240000199632401392320000419961011<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA>1996101102 472 9341<NA><NA>강동구 천호동 ***-* 상일신관 ***호<NA><NA>경향기획2010-10-06 10:47:23I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
23240000199632401392320000519961011201904184취소/말소/만료/정지/중지4직권취소<NA><NA><NA>1996101102 472 1586<NA><NA>강동구 성내동 ***-* 금익B/D *층<NA><NA>한국삐아제교육연구원2019-04-19 18:14:23U2019-04-21 02:40:00.0<NA><NA><NA><NA><NA><NA><NA>
33240000199632401392320001219961111<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA>1996111102 477 1158<NA><NA>강동구 천호동 *** 호산B/D 가-***호<NA><NA>생그린화장품2018-01-25 08:56:45I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
43240000199632401392320001919961122<NA>1영업/정상1정상영업<NA><NA><NA>1996112202 478 4080<NA><NA>강동구 성내동 ***-** 우용상가 ***호<NA><NA>기아자동차둔촌대리점2012-08-22 22:38:29I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
53240000199632401392320003319961227<NA>3폐업3폐업처리20200707<NA><NA><NA>02 478 3344<NA><NA>강동구 성내동 ***<NA><NA>예은화장품㈜2020-07-07 19:39:54U2020-07-09 02:40:00.0<NA><NA><NA>3000000000300000000<NA>
63240000199732401392320005019970704<NA>3폐업3폐업처리20170314<NA><NA><NA>02 478 6288<NA><NA>강동구 길동 **-**<NA><NA>금성서적2017-03-14 13:24:07I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
73240000199732401392320006219971107<NA>1영업/정상1정상영업<NA><NA><NA>1997110702 488 6688<NA><NA>서울특별시 강동구 암사동 ***-*서울특별시 강동구 고덕로 *** (암사동)05255기아 고덕대리점2021-06-11 14:46:16U2021-06-13 02:40:00.0<NA>211972.531931450259.890084<NA><NA><NA><NA>
83240000199832401392320006719980119<NA>3폐업3폐업처리20131007<NA><NA><NA>476-0896,484-0897<NA>134874서울특별시 강동구 천호*동 ***번지 *호 우장빌딩 *층<NA><NA>태평양동서울특약점2013-10-07 15:38:42I2018-08-31 23:59:59.0<NA>210841.05373448640.7102941555000087600006790000<NA>
93240000199832401392320007519980324<NA>3폐업3폐업처리20080331<NA><NA><NA>02 477 5222<NA><NA>강동구 성내동 ***-* (*층)<NA><NA>아이템플강동지사2008-03-31 11:49:22I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
1095324000020233240289232000102023-06-30<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 강동구 길동 ***-**서울특별시 강동구 양재대로***길 **-*, ***호 (길동)05352나유타 코리아 글로벌2023-06-30 11:31:59I2022-12-07 00:02:00.0<NA>212459.740997448126.808794<NA><NA><NA><NA>
1096324000020233240289232000112023-08-17<NA>1영업/정상1정상영업<NA><NA><NA><NA>1522-1577<NA><NA>서울특별시 강동구 천호동 ***-* 대우 한강 베네시티서울특별시 강동구 올림픽로 ***, *층 ***호 (천호동, 대우 한강 베네시티)05328포크앤솔루션 주식회사2023-08-17 10:29:09I2022-12-07 23:09:00.0<NA>210970.757073448713.316697<NA><NA><NA><NA>
1097324000020233240289232000122023-10-10<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 강동구 길동 ***-* 보성빌딩서울특별시 강동구 양재대로***길 **, 보성빌딩 *층 ***호 (길동)05302(G&H)레저2023-10-10 13:59:24I2022-10-30 23:02:00.0<NA>212588.31796448994.86523<NA><NA><NA><NA>
1098324000020233240289232000132023-12-12<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 강동구 성내동 ***-** 건창빌딩서울특별시 강동구 올림픽로**길 **, 건창빌딩 *층 ***호 (성내동)05398(주)닥터팜헬스케어2024-04-03 10:52:34U2023-12-04 00:05:00.0<NA>210671.486636447412.187372<NA><NA><NA><NA>
1099324000020243240289232000012024-01-15<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-6380-8302<NA><NA>서울특별시 강동구 암사동 ***-** 정산아파트 상가서울특별시 강동구 고덕로 **, 상가 *층 ***-**호 (암사동, 정산아파트)05238올리버스 주식회사2024-01-15 15:37:47I2023-11-30 23:07:00.0<NA>211458.648093450316.255473<NA><NA><NA><NA>
1100324000020243240289232000022023-09-22<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 강동구 암사동 ***-** LS지산빌딩서울특별시 강동구 올림픽로**길 **, LS지산빌딩 제지*층 제비***호 (암사동)05263조타(JOTA)홈엔온 쇼핑2024-01-16 10:53:16I2023-11-30 23:08:00.0<NA>211327.90591449907.519477<NA><NA><NA><NA>
1101324000020243240289232000032024-03-25<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-461-7588<NA><NA>서울특별시 강동구 성내동 ***-**서울특별시 강동구 양재대로**길 **, *층 (성내동)05404웰니스생활 둔촌점2024-05-09 13:25:34U2023-12-04 23:01:00.0<NA>211804.185343447344.070468<NA><NA><NA><NA>
1102324000020243240289232000042022-06-24<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-487-7223<NA><NA>서울특별시 강동구 둔촌동 ** 원경빌딩서울특별시 강동구 천호대로 ****, 원경빌딩 *층 (둔촌동)05361노블레스2024-03-26 10:55:00I2023-12-02 22:08:00.0<NA>212589.743487447977.592821<NA><NA><NA><NA>
1103324000020243240289232000052022-05-18<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 강동구 천호동 ***-** 광진타워빌딩서울특별시 강동구 구천면로 ***, 광진타워빌딩 지하*층 (천호동)05246한솔라이프2024-04-04 13:39:41I2023-12-04 00:06:00.0<NA>210832.9891448855.154872<NA><NA><NA><NA>
1104324000020243240289232000062024-05-07<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 강동구 천호동 ***-* 우성그린빌라서울특별시 강동구 구천면로 ***-**, 비동 *층 ***호 (천호동, 우성그린빌라)05330일동2024-05-07 10:13:06I2023-12-05 00:09:00.0<NA>211663.378935448999.028388<NA><NA><NA><NA>