Overview

Dataset statistics

Number of variables29
Number of observations135
Missing cells1022
Missing cells (%)26.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory33.1 KiB
Average record size in memory251.0 B

Variable types

Categorical10
Numeric9
DateTime3
Text4
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
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-18782/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (93.7%)Imbalance
휴업시작일자 is highly imbalanced (93.7%)Imbalance
휴업종료일자 is highly imbalanced (93.7%)Imbalance
데이터갱신일자 is highly imbalanced (54.2%)Imbalance
폐업일자 has 38 (28.1%) missing valuesMissing
재개업일자 has 126 (93.3%) missing valuesMissing
전화번호 has 39 (28.9%) missing valuesMissing
소재지면적 has 135 (100.0%) missing valuesMissing
소재지우편번호 has 82 (60.7%) missing valuesMissing
지번주소 has 37 (27.4%) missing valuesMissing
도로명우편번호 has 38 (28.1%) missing valuesMissing
업태구분명 has 135 (100.0%) missing valuesMissing
자산규모 has 85 (63.0%) missing valuesMissing
부채총액 has 85 (63.0%) missing valuesMissing
자본금 has 85 (63.0%) missing valuesMissing
판매방식명 has 135 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 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 11 (8.1%) zerosZeros
부채총액 has 26 (19.3%) zerosZeros
자본금 has 6 (4.4%) zerosZeros

Reproduction

Analysis started2024-05-11 09:12:00.716073
Analysis finished2024-05-11 09:12:01.724078
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
3050000
135 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3050000
2nd row3050000
3rd row3050000
4th row3050000
5th row3050000

Common Values

ValueCountFrequency (%)
3050000 135
100.0%

Length

2024-05-11T09:12:01.915008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:12:02.231429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3050000 135
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct135
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0140235 × 1018
Minimum2.005305 × 1018
Maximum2.024305 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T09:12:02.580870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.005305 × 1018
5-th percentile2.007305 × 1018
Q12.010305 × 1018
median2.013305 × 1018
Q32.017305 × 1018
95-th percentile2.022305 × 1018
Maximum2.024305 × 1018
Range1.9000011 × 1016
Interquartile range (IQR)7.000004 × 1015

Descriptive statistics

Standard deviation4.7247412 × 1015
Coefficient of variation (CV)0.0023459215
Kurtosis-0.8117607
Mean2.0140235 × 1018
Median Absolute Deviation (MAD)3.000004 × 1015
Skewness0.3387735
Sum-4.8079844 × 1018
Variance2.2323179 × 1031
MonotonicityStrictly increasing
2024-05-11T09:12:03.239546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2005305010024200051 1
 
0.7%
2016305014024200001 1
 
0.7%
2015305014024200003 1
 
0.7%
2015305014024200004 1
 
0.7%
2015305014024200005 1
 
0.7%
2015305014024200007 1
 
0.7%
2015305014024200008 1
 
0.7%
2015305014024200009 1
 
0.7%
2016305014024200002 1
 
0.7%
2006305010024200072 1
 
0.7%
Other values (125) 125
92.6%
ValueCountFrequency (%)
2005305010024200051 1
0.7%
2006305010024200072 1
0.7%
2006305010024200081 1
0.7%
2006305010024200082 1
0.7%
2006305010024203132 1
0.7%
2007305010024200085 1
0.7%
2007305010024200087 1
0.7%
2007305010024200088 1
0.7%
2007305010024200090 1
0.7%
2007305010024200091 1
0.7%
ValueCountFrequency (%)
2024305021024200001 1
0.7%
2023305021024200003 1
0.7%
2023305021024200002 1
0.7%
2023305021024200001 1
0.7%
2022305014024200005 1
0.7%
2022305014024200004 1
0.7%
2022305014024200003 1
0.7%
2022305014024200002 1
0.7%
2022305014024200001 1
0.7%
2021305014024200008 1
0.7%

인허가일자
Date

Distinct126
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2005-04-08 00:00:00
Maximum2023-11-15 00:00:00
2024-05-11T09:12:03.756298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:12:04.404248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
134 
20210722
 
1

Length

Max length8
Median length4
Mean length4.0296296
Min length4

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 134
99.3%
20210722 1
 
0.7%

Length

2024-05-11T09:12:04.913461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:12:05.321404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 134
99.3%
20210722 1
 
0.7%

영업상태코드
Categorical

Distinct4
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
3
51 
4
50 
1
32 
5
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 51
37.8%
4 50
37.0%
1 32
23.7%
5 2
 
1.5%

Length

2024-05-11T09:12:05.816773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:12:06.154353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 51
37.8%
4 50
37.0%
1 32
23.7%
5 2
 
1.5%

영업상태명
Categorical

Distinct4
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
폐업
51 
취소/말소/만료/정지/중지
50 
영업/정상
32 
제외/삭제/전출
 
2

Length

Max length14
Median length8
Mean length7.2444444
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 51
37.8%
취소/말소/만료/정지/중지 50
37.0%
영업/정상 32
23.7%
제외/삭제/전출 2
 
1.5%

Length

2024-05-11T09:12:06.528567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:12:06.864853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 51
37.8%
취소/말소/만료/정지/중지 50
37.0%
영업/정상 32
23.7%
제외/삭제/전출 2
 
1.5%

상세영업상태코드
Categorical

Distinct5
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
3
51 
7
49 
1
32 
5
 
2
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st row3
2nd row3
3rd row3
4th row7
5th row3

Common Values

ValueCountFrequency (%)
3 51
37.8%
7 49
36.3%
1 32
23.7%
5 2
 
1.5%
4 1
 
0.7%

Length

2024-05-11T09:12:07.345003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:12:08.057013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 51
37.8%
7 49
36.3%
1 32
23.7%
5 2
 
1.5%
4 1
 
0.7%

상세영업상태명
Categorical

Distinct5
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
폐업처리
51 
직권말소
49 
정상영업
32 
타시군구이관
 
2
직권취소
 
1

Length

Max length6
Median length4
Mean length4.0296296
Min length4

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
폐업처리 51
37.8%
직권말소 49
36.3%
정상영업 32
23.7%
타시군구이관 2
 
1.5%
직권취소 1
 
0.7%

Length

2024-05-11T09:12:08.646946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:12:09.052744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업처리 51
37.8%
직권말소 49
36.3%
정상영업 32
23.7%
타시군구이관 2
 
1.5%
직권취소 1
 
0.7%

폐업일자
Date

MISSING 

Distinct60
Distinct (%)61.9%
Missing38
Missing (%)28.1%
Memory size1.2 KiB
Minimum2008-06-19 00:00:00
Maximum2023-10-25 00:00:00
2024-05-11T09:12:09.614419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:12:10.107260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
134 
20080229
 
1

Length

Max length8
Median length4
Mean length4.0296296
Min length4

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 134
99.3%
20080229 1
 
0.7%

Length

2024-05-11T09:12:10.611194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:12:10.996710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 134
99.3%
20080229 1
 
0.7%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
134 
20080930
 
1

Length

Max length8
Median length4
Mean length4.0296296
Min length4

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 134
99.3%
20080930 1
 
0.7%

Length

2024-05-11T09:12:11.611756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:12:12.102468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 134
99.3%
20080930 1
 
0.7%

재개업일자
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)88.9%
Missing126
Missing (%)93.3%
Infinite0
Infinite (%)0.0%
Mean20066362
Minimum20060427
Maximum20070906
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T09:12:12.543621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060427
5-th percentile20060625
Q120060921
median20070702
Q320070726
95-th percentile20070834
Maximum20070906
Range10479
Interquartile range (IQR)9805

Descriptive statistics

Standard deviation5214.5886
Coefficient of variation (CV)0.00025986717
Kurtosis-2.5554359
Mean20066362
Median Absolute Deviation (MAD)204
Skewness-0.27592502
Sum1.8059725 × 108
Variance27191934
MonotonicityNot monotonic
2024-05-11T09:12:12.970465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
20060921 2
 
1.5%
20060427 1
 
0.7%
20061208 1
 
0.7%
20070702 1
 
0.7%
20070726 1
 
0.7%
20070727 1
 
0.7%
20070906 1
 
0.7%
20070716 1
 
0.7%
(Missing) 126
93.3%
ValueCountFrequency (%)
20060427 1
0.7%
20060921 2
1.5%
20061208 1
0.7%
20070702 1
0.7%
20070716 1
0.7%
20070726 1
0.7%
20070727 1
0.7%
20070906 1
0.7%
ValueCountFrequency (%)
20070906 1
0.7%
20070727 1
0.7%
20070726 1
0.7%
20070716 1
0.7%
20070702 1
0.7%
20061208 1
0.7%
20060921 2
1.5%
20060427 1
0.7%

전화번호
Text

MISSING 

Distinct96
Distinct (%)100.0%
Missing39
Missing (%)28.9%
Memory size1.2 KiB
2024-05-11T09:12:13.913562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length9.9166667
Min length2

Characters and Unicode

Total characters952
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

Unique96 ?
Unique (%)100.0%

Sample

1st row6223-8585
2nd row952-1005
3rd row2245-3611
4th row2248-6300
5th row3295-5338
ValueCountFrequency (%)
3394-3831 1
 
1.0%
2245-3611 1
 
1.0%
02-928-4367 1
 
1.0%
02-2217-7770 1
 
1.0%
02-960-4529 1
 
1.0%
02-533-8518 1
 
1.0%
02-2216-1155 1
 
1.0%
070-8627-1988 1
 
1.0%
070-4340-9419 1
 
1.0%
02-2212-2737 1
 
1.0%
Other values (86) 86
89.6%
2024-05-11T09:12:15.412760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 133
14.0%
2 127
13.3%
0 109
11.4%
3 88
9.2%
9 83
8.7%
1 80
8.4%
4 74
7.8%
5 67
7.0%
7 67
7.0%
8 65
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 819
86.0%
Dash Punctuation 133
 
14.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 127
15.5%
0 109
13.3%
3 88
10.7%
9 83
10.1%
1 80
9.8%
4 74
9.0%
5 67
8.2%
7 67
8.2%
8 65
7.9%
6 59
7.2%
Dash Punctuation
ValueCountFrequency (%)
- 133
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 133
14.0%
2 127
13.3%
0 109
11.4%
3 88
9.2%
9 83
8.7%
1 80
8.4%
4 74
7.8%
5 67
7.0%
7 67
7.0%
8 65
6.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 133
14.0%
2 127
13.3%
0 109
11.4%
3 88
9.2%
9 83
8.7%
1 80
8.4%
4 74
7.8%
5 67
7.0%
7 67
7.0%
8 65
6.8%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing135
Missing (%)100.0%
Memory size1.3 KiB

소재지우편번호
Real number (ℝ)

MISSING 

Distinct25
Distinct (%)47.2%
Missing82
Missing (%)60.7%
Infinite0
Infinite (%)0.0%
Mean130548.68
Minimum130010
Maximum130876
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T09:12:15.983871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum130010
5-th percentile130017.6
Q1130101
median130812
Q3130843
95-th percentile130848.4
Maximum130876
Range866
Interquartile range (IQR)742

Descriptive statistics

Standard deviation370.17131
Coefficient of variation (CV)0.0028355041
Kurtosis-1.7659091
Mean130548.68
Median Absolute Deviation (MAD)32
Skewness-0.52781483
Sum6919080
Variance137026.8
MonotonicityNot monotonic
2024-05-11T09:12:16.519499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
130844 8
 
5.9%
130810 5
 
3.7%
130110 4
 
3.0%
130100 4
 
3.0%
130101 3
 
2.2%
130070 3
 
2.2%
130823 3
 
2.2%
130841 3
 
2.2%
130814 2
 
1.5%
130010 2
 
1.5%
Other values (15) 16
 
11.9%
(Missing) 82
60.7%
ValueCountFrequency (%)
130010 2
1.5%
130011 1
 
0.7%
130022 1
 
0.7%
130070 3
2.2%
130080 1
 
0.7%
130091 1
 
0.7%
130100 4
3.0%
130101 3
2.2%
130110 4
3.0%
130804 1
 
0.7%
ValueCountFrequency (%)
130876 1
 
0.7%
130864 1
 
0.7%
130852 1
 
0.7%
130846 1
 
0.7%
130845 1
 
0.7%
130844 8
5.9%
130843 1
 
0.7%
130842 2
 
1.5%
130841 3
 
2.2%
130838 1
 
0.7%

지번주소
Text

MISSING 

Distinct84
Distinct (%)85.7%
Missing37
Missing (%)27.4%
Memory size1.2 KiB
2024-05-11T09:12:17.194918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length34
Mean length28.306122
Min length20

Characters and Unicode

Total characters2774
Distinct characters136
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

Unique73 ?
Unique (%)74.5%

Sample

1st row서울특별시 동대문구 장안*동 ***번지 *호
2nd row서울특별시 동대문구 제기동 ****번지 *호 영진빌딩 *층
3rd row서울특별시 동대문구 휘경동 **번지 *호 *층
4th row서울특별시 동대문구 휘경동 **번지 *호 태림빌딩 *층
5th row서울특별시 동대문구 이문동 ***번지 ***호
ValueCountFrequency (%)
서울특별시 98
17.4%
동대문구 98
17.4%
호 96
17.1%
번지 76
13.5%
장안동 30
 
5.3%
25
 
4.4%
신설동 20
 
3.6%
층 13
 
2.3%
용두동 9
 
1.6%
제기동 8
 
1.4%
Other values (61) 89
15.8%
2024-05-11T09:12:18.659948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 549
19.8%
465
16.8%
동 201
 
7.2%
서 102
 
3.7%
대 101
 
3.6%
문 100
 
3.6%
구 99
 
3.6%
호 99
 
3.6%
시 99
 
3.6%
울 98
 
3.5%
Other values (126) 861
31.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1714
61.8%
Other Punctuation 550
 
19.8%
Space Separator 465
 
16.8%
Dash Punctuation 22
 
0.8%
Lowercase Letter 11
 
0.4%
Decimal Number 5
 
0.2%
Uppercase Letter 4
 
0.1%
Math Symbol 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 201
 
11.7%
서 102
 
6.0%
대 101
 
5.9%
문 100
 
5.8%
구 99
 
5.8%
호 99
 
5.8%
시 99
 
5.8%
울 98
 
5.7%
별 98
 
5.7%
특 98
 
5.7%
Other values (105) 619
36.1%
Lowercase Letter
ValueCountFrequency (%)
e 3
27.3%
t 2
18.2%
s 2
18.2%
l 2
18.2%
a 1
 
9.1%
w 1
 
9.1%
Decimal Number
ValueCountFrequency (%)
6 2
40.0%
4 1
20.0%
7 1
20.0%
5 1
20.0%
Uppercase Letter
ValueCountFrequency (%)
G 1
25.0%
A 1
25.0%
S 1
25.0%
K 1
25.0%
Other Punctuation
ValueCountFrequency (%)
* 549
99.8%
, 1
 
0.2%
Space Separator
ValueCountFrequency (%)
465
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1714
61.8%
Common 1045
37.7%
Latin 15
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 201
 
11.7%
서 102
 
6.0%
대 101
 
5.9%
문 100
 
5.8%
구 99
 
5.8%
호 99
 
5.8%
시 99
 
5.8%
울 98
 
5.7%
별 98
 
5.7%
특 98
 
5.7%
Other values (105) 619
36.1%
Common
ValueCountFrequency (%)
* 549
52.5%
465
44.5%
- 22
 
2.1%
6 2
 
0.2%
~ 1
 
0.1%
4 1
 
0.1%
7 1
 
0.1%
5 1
 
0.1%
, 1
 
0.1%
( 1
 
0.1%
Latin
ValueCountFrequency (%)
e 3
20.0%
t 2
13.3%
s 2
13.3%
l 2
13.3%
a 1
 
6.7%
w 1
 
6.7%
G 1
 
6.7%
A 1
 
6.7%
S 1
 
6.7%
K 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1714
61.8%
ASCII 1060
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 549
51.8%
465
43.9%
- 22
 
2.1%
e 3
 
0.3%
6 2
 
0.2%
t 2
 
0.2%
s 2
 
0.2%
l 2
 
0.2%
a 1
 
0.1%
~ 1
 
0.1%
Other values (11) 11
 
1.0%
Hangul
ValueCountFrequency (%)
동 201
 
11.7%
서 102
 
6.0%
대 101
 
5.9%
문 100
 
5.8%
구 99
 
5.8%
호 99
 
5.8%
시 99
 
5.8%
울 98
 
5.7%
별 98
 
5.7%
특 98
 
5.7%
Other values (105) 619
36.1%

도로명주소
Text

Distinct124
Distinct (%)91.9%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-11T09:12:19.455089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length43
Mean length33.466667
Min length22

Characters and Unicode

Total characters4518
Distinct characters173
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

Unique113 ?
Unique (%)83.7%

Sample

1st row서울특별시 동대문구 천호대로 *** (장안동)
2nd row서울특별시 동대문구 무학로**길 * (제기동,영진빌딩 *층)
3rd row서울특별시 동대문구 망우로 ** (휘경동,*층)
4th row서울특별시 동대문구 망우로 ** (휘경동,태림빌딩 *층)
5th row서울특별시 동대문구 신이문로*길 * (이문동)
ValueCountFrequency (%)
136
16.0%
서울특별시 135
15.9%
동대문구 135
15.9%
호 62
 
7.3%
층 46
 
5.4%
장안동 34
 
4.0%
왕산로 19
 
2.2%
신설동 18
 
2.1%
용두동 16
 
1.9%
장한로 14
 
1.6%
Other values (128) 234
27.6%
2024-05-11T09:12:20.693491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
724
16.0%
* 697
 
15.4%
동 287
 
6.4%
대 164
 
3.6%
, 154
 
3.4%
서 143
 
3.2%
문 142
 
3.1%
시 141
 
3.1%
울 138
 
3.1%
( 136
 
3.0%
Other values (163) 1792
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2622
58.0%
Other Punctuation 852
 
18.9%
Space Separator 724
 
16.0%
Open Punctuation 136
 
3.0%
Close Punctuation 136
 
3.0%
Dash Punctuation 21
 
0.5%
Lowercase Letter 12
 
0.3%
Uppercase Letter 8
 
0.2%
Decimal Number 6
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 287
 
10.9%
대 164
 
6.3%
서 143
 
5.5%
문 142
 
5.4%
시 141
 
5.4%
울 138
 
5.3%
구 136
 
5.2%
별 135
 
5.1%
특 135
 
5.1%
로 134
 
5.1%
Other values (139) 1067
40.7%
Lowercase Letter
ValueCountFrequency (%)
e 3
25.0%
s 2
16.7%
l 2
16.7%
t 2
16.7%
a 1
 
8.3%
w 1
 
8.3%
c 1
 
8.3%
Decimal Number
ValueCountFrequency (%)
2 2
33.3%
3 1
16.7%
4 1
16.7%
0 1
16.7%
1 1
16.7%
Uppercase Letter
ValueCountFrequency (%)
A 3
37.5%
K 2
25.0%
S 2
25.0%
G 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
* 697
81.8%
, 154
 
18.1%
. 1
 
0.1%
Space Separator
ValueCountFrequency (%)
724
100.0%
Open Punctuation
ValueCountFrequency (%)
( 136
100.0%
Close Punctuation
ValueCountFrequency (%)
) 136
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2622
58.0%
Common 1876
41.5%
Latin 20
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 287
 
10.9%
대 164
 
6.3%
서 143
 
5.5%
문 142
 
5.4%
시 141
 
5.4%
울 138
 
5.3%
구 136
 
5.2%
별 135
 
5.1%
특 135
 
5.1%
로 134
 
5.1%
Other values (139) 1067
40.7%
Common
ValueCountFrequency (%)
724
38.6%
* 697
37.2%
, 154
 
8.2%
( 136
 
7.2%
) 136
 
7.2%
- 21
 
1.1%
2 2
 
0.1%
3 1
 
0.1%
4 1
 
0.1%
0 1
 
0.1%
Other values (3) 3
 
0.2%
Latin
ValueCountFrequency (%)
A 3
15.0%
e 3
15.0%
s 2
10.0%
l 2
10.0%
t 2
10.0%
K 2
10.0%
S 2
10.0%
G 1
 
5.0%
a 1
 
5.0%
w 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2622
58.0%
ASCII 1896
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
724
38.2%
* 697
36.8%
, 154
 
8.1%
( 136
 
7.2%
) 136
 
7.2%
- 21
 
1.1%
A 3
 
0.2%
e 3
 
0.2%
2 2
 
0.1%
s 2
 
0.1%
Other values (14) 18
 
0.9%
Hangul
ValueCountFrequency (%)
동 287
 
10.9%
대 164
 
6.3%
서 143
 
5.5%
문 142
 
5.4%
시 141
 
5.4%
울 138
 
5.3%
구 136
 
5.2%
별 135
 
5.1%
특 135
 
5.1%
로 134
 
5.1%
Other values (139) 1067
40.7%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct56
Distinct (%)57.7%
Missing38
Missing (%)28.1%
Infinite0
Infinite (%)0.0%
Mean75253.856
Minimum2452
Maximum130876
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T09:12:21.266959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2452
5-th percentile2492.4
Q12603
median130713
Q3130832
95-th percentile130867
Maximum130876
Range128424
Interquartile range (IQR)128229

Descriptive statistics

Standard deviation63832.866
Coefficient of variation (CV)0.84823383
Kurtosis-1.9654552
Mean75253.856
Median Absolute Deviation (MAD)163
Skewness-0.27472563
Sum7299624
Variance4.0746348 × 109
MonotonicityNot monotonic
2024-05-11T09:12:21.898266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
130844 7
 
5.2%
2644 5
 
3.7%
130810 4
 
3.0%
130070 4
 
3.0%
130823 4
 
3.0%
130805 4
 
3.0%
130811 3
 
2.2%
2586 3
 
2.2%
2580 3
 
2.2%
130867 2
 
1.5%
Other values (46) 58
43.0%
(Missing) 38
28.1%
ValueCountFrequency (%)
2452 1
0.7%
2453 1
0.7%
2468 1
0.7%
2478 2
1.5%
2496 1
0.7%
2522 1
0.7%
2523 1
0.7%
2568 1
0.7%
2572 1
0.7%
2574 1
0.7%
ValueCountFrequency (%)
130876 2
 
1.5%
130873 1
 
0.7%
130872 1
 
0.7%
130867 2
 
1.5%
130864 1
 
0.7%
130854 1
 
0.7%
130852 2
 
1.5%
130850 1
 
0.7%
130846 1
 
0.7%
130844 7
5.2%

사업장명
Text

Distinct132
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-11T09:12:22.737750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length18
Mean length8.2666667
Min length2

Characters and Unicode

Total characters1116
Distinct characters264
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

Unique129 ?
Unique (%)95.6%

Sample

1st row하나로넷(주)
2nd row천호물산
3rd row송악
4th row송악실업
5th row리스원
ValueCountFrequency (%)
주식회사 21
 
10.7%
주 11
 
5.6%
제이퓨쳐 2
 
1.0%
대부중개 2
 
1.0%
inc 2
 
1.0%
정보통신 2
 
1.0%
company 2
 
1.0%
테라네트웍스 2
 
1.0%
복지코리아 2
 
1.0%
은창상사 1
 
0.5%
Other values (150) 150
76.1%
2024-05-11T09:12:24.986853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
62
 
5.6%
주 57
 
5.1%
이 42
 
3.8%
( 41
 
3.7%
) 41
 
3.7%
스 35
 
3.1%
사 28
 
2.5%
회 26
 
2.3%
리 22
 
2.0%
식 21
 
1.9%
Other values (254) 741
66.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 873
78.2%
Space Separator 62
 
5.6%
Lowercase Letter 53
 
4.7%
Open Punctuation 41
 
3.7%
Close Punctuation 41
 
3.7%
Uppercase Letter 33
 
3.0%
Decimal Number 7
 
0.6%
Other Punctuation 5
 
0.4%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 57
 
6.5%
이 42
 
4.8%
스 35
 
4.0%
사 28
 
3.2%
회 26
 
3.0%
리 22
 
2.5%
식 21
 
2.4%
에 19
 
2.2%
아 14
 
1.6%
보 13
 
1.5%
Other values (210) 596
68.3%
Lowercase Letter
ValueCountFrequency (%)
e 8
15.1%
n 6
11.3%
c 5
9.4%
t 4
 
7.5%
a 4
 
7.5%
o 4
 
7.5%
m 3
 
5.7%
s 3
 
5.7%
h 3
 
5.7%
i 2
 
3.8%
Other values (7) 11
20.8%
Uppercase Letter
ValueCountFrequency (%)
M 5
15.2%
S 4
12.1%
I 3
9.1%
B 3
9.1%
H 3
9.1%
C 3
9.1%
K 2
 
6.1%
N 2
 
6.1%
U 1
 
3.0%
F 1
 
3.0%
Other values (6) 6
18.2%
Decimal Number
ValueCountFrequency (%)
0 3
42.9%
1 2
28.6%
9 1
 
14.3%
3 1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
. 3
60.0%
, 1
 
20.0%
& 1
 
20.0%
Space Separator
ValueCountFrequency (%)
62
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 873
78.2%
Common 157
 
14.1%
Latin 86
 
7.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 57
 
6.5%
이 42
 
4.8%
스 35
 
4.0%
사 28
 
3.2%
회 26
 
3.0%
리 22
 
2.5%
식 21
 
2.4%
에 19
 
2.2%
아 14
 
1.6%
보 13
 
1.5%
Other values (210) 596
68.3%
Latin
ValueCountFrequency (%)
e 8
 
9.3%
n 6
 
7.0%
c 5
 
5.8%
M 5
 
5.8%
t 4
 
4.7%
a 4
 
4.7%
o 4
 
4.7%
S 4
 
4.7%
I 3
 
3.5%
m 3
 
3.5%
Other values (23) 40
46.5%
Common
ValueCountFrequency (%)
62
39.5%
( 41
26.1%
) 41
26.1%
0 3
 
1.9%
. 3
 
1.9%
1 2
 
1.3%
, 1
 
0.6%
- 1
 
0.6%
& 1
 
0.6%
9 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 873
78.2%
ASCII 243
 
21.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
62
25.5%
( 41
16.9%
) 41
16.9%
e 8
 
3.3%
n 6
 
2.5%
c 5
 
2.1%
M 5
 
2.1%
t 4
 
1.6%
a 4
 
1.6%
o 4
 
1.6%
Other values (34) 63
25.9%
Hangul
ValueCountFrequency (%)
주 57
 
6.5%
이 42
 
4.8%
스 35
 
4.0%
사 28
 
3.2%
회 26
 
3.0%
리 22
 
2.5%
식 21
 
2.4%
에 19
 
2.2%
아 14
 
1.6%
보 13
 
1.5%
Other values (210) 596
68.3%

최종수정일자
Date

UNIQUE 

Distinct135
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2008-06-19 17:32:34
Maximum2024-02-28 10:17:28
2024-05-11T09:12:25.678566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:12:26.260836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
I
114 
U
21 

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 114
84.4%
U 21
 
15.6%

Length

2024-05-11T09:12:26.807204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:12:27.116416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 114
84.4%
u 21
 
15.6%

데이터갱신일자
Categorical

IMBALANCE 

Distinct40
Distinct (%)29.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2018-08-31 23:59:59.0
95 
2019-08-24 02:40:00.0
 
2
2021-11-02 00:08:00.0
 
1
2019-07-11 02:40:00.0
 
1
2019-04-11 02:40:00.0
 
1
Other values (35)
35 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique38 ?
Unique (%)28.1%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 95
70.4%
2019-08-24 02:40:00.0 2
 
1.5%
2021-11-02 00:08:00.0 1
 
0.7%
2019-07-11 02:40:00.0 1
 
0.7%
2019-04-11 02:40:00.0 1
 
0.7%
2019-01-12 02:40:00.0 1
 
0.7%
2019-12-19 02:40:00.0 1
 
0.7%
2020-12-03 02:40:00.0 1
 
0.7%
2019-01-19 02:40:00.0 1
 
0.7%
2021-04-14 02:40:00.0 1
 
0.7%
Other values (30) 30
 
22.2%

Length

2024-05-11T09:12:27.562034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 95
35.2%
23:59:59.0 95
35.2%
02:40:00.0 15
 
5.6%
00:23:01.0 2
 
0.7%
23:07:00.0 2
 
0.7%
22:09:00.0 2
 
0.7%
2021-12-06 2
 
0.7%
22:03:00.0 2
 
0.7%
2021-10-30 2
 
0.7%
2019-08-24 2
 
0.7%
Other values (51) 51
18.9%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing135
Missing (%)100.0%
Memory size1.3 KiB

좌표정보(X)
Real number (ℝ)

Distinct108
Distinct (%)80.6%
Missing1
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean204276.38
Minimum202023.92
Maximum206385.67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T09:12:28.053225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum202023.92
5-th percentile202071.04
Q1202722.21
median204662.59
Q3205721.39
95-th percentile206161.54
Maximum206385.67
Range4361.7487
Interquartile range (IQR)2999.1832

Descriptive statistics

Standard deviation1492.6344
Coefficient of variation (CV)0.0073069361
Kurtosis-1.5158049
Mean204276.38
Median Absolute Deviation (MAD)1313.5493
Skewness-0.23112933
Sum27373034
Variance2227957.5
MonotonicityNot monotonic
2024-05-11T09:12:28.566750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202207.233857938 3
 
2.2%
204687.977091636 3
 
2.2%
202045.581261433 3
 
2.2%
205117.174747188 2
 
1.5%
206287.477164822 2
 
1.5%
205401.574373249 2
 
1.5%
202474.62650398 2
 
1.5%
206024.581400212 2
 
1.5%
206141.179571336 2
 
1.5%
202582.019563324 2
 
1.5%
Other values (98) 111
82.2%
ValueCountFrequency (%)
202023.921749857 1
 
0.7%
202033.22548938 2
1.5%
202045.581261433 3
2.2%
202056.394367168 1
 
0.7%
202078.922252296 1
 
0.7%
202091.896824059 1
 
0.7%
202093.908184725 1
 
0.7%
202128.460068469 1
 
0.7%
202132.961071614 1
 
0.7%
202142.710943758 1
 
0.7%
ValueCountFrequency (%)
206385.670474902 1
0.7%
206323.706589841 1
0.7%
206312.735517645 1
0.7%
206287.477164822 2
1.5%
206218.682577242 1
0.7%
206199.354351212 1
0.7%
206141.179571336 2
1.5%
206101.9138443 2
1.5%
206040.667208341 1
0.7%
206024.581400212 2
1.5%

좌표정보(Y)
Real number (ℝ)

Distinct108
Distinct (%)80.6%
Missing1
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean452483.16
Minimum450994.91
Maximum455590.11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T09:12:29.116913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum450994.91
5-th percentile451101.71
Q1451582.58
median452586.08
Q3452954.98
95-th percentile454269.59
Maximum455590.11
Range4595.1927
Interquartile range (IQR)1372.4017

Descriptive statistics

Standard deviation971.20666
Coefficient of variation (CV)0.002146393
Kurtosis0.015429064
Mean452483.16
Median Absolute Deviation (MAD)666.70122
Skewness0.48357663
Sum60632743
Variance943242.38
MonotonicityNot monotonic
2024-05-11T09:12:29.545069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
452586.081387626 3
 
2.2%
451578.200073082 3
 
2.2%
452672.881757271 3
 
2.2%
451469.359849259 2
 
1.5%
453248.952213731 2
 
1.5%
451108.047802152 2
 
1.5%
452684.679816566 2
 
1.5%
451697.932743893 2
 
1.5%
451851.162759383 2
 
1.5%
452860.046752763 2
 
1.5%
Other values (98) 111
82.2%
ValueCountFrequency (%)
450994.913744005 1
0.7%
451017.540622804 1
0.7%
451031.672241199 1
0.7%
451059.346901649 1
0.7%
451080.986788942 1
0.7%
451088.609204795 1
0.7%
451089.9361667 1
0.7%
451108.047802152 2
1.5%
451126.481053284 1
0.7%
451164.874072088 1
0.7%
ValueCountFrequency (%)
455590.10646389 1
0.7%
454833.337679973 1
0.7%
454751.864083743 1
0.7%
454525.241253654 1
0.7%
454372.264612659 1
0.7%
454316.398752992 1
0.7%
454269.587501201 2
1.5%
454259.917056147 1
0.7%
454250.566057225 1
0.7%
454182.452784872 1
0.7%

자산규모
Real number (ℝ)

MISSING  ZEROS 

Distinct31
Distinct (%)62.0%
Missing85
Missing (%)63.0%
Infinite0
Infinite (%)0.0%
Mean6.1943478 × 1010
Minimum0
Maximum2.9239155 × 1012
Zeros11
Zeros (%)8.1%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T09:12:29.950557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q110000000
median50114770
Q35.9535301 × 108
95-th percentile1.9602848 × 1010
Maximum2.9239155 × 1012
Range2.9239155 × 1012
Interquartile range (IQR)5.8535301 × 108

Descriptive statistics

Standard deviation4.1333036 × 1011
Coefficient of variation (CV)6.6727018
Kurtosis49.832304
Mean6.1943478 × 1010
Median Absolute Deviation (MAD)50114770
Skewness7.0540414
Sum3.0971739 × 1012
Variance1.7084198 × 1023
MonotonicityNot monotonic
2024-05-11T09:12:30.351860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 11
 
8.1%
50000000 4
 
3.0%
10000000 3
 
2.2%
100000000 3
 
2.2%
30000000 2
 
1.5%
20000000 2
 
1.5%
2923915496587 1
 
0.7%
1042453011 1
 
0.7%
32447307 1
 
0.7%
1364634176 1
 
0.7%
Other values (21) 21
 
15.6%
(Missing) 85
63.0%
ValueCountFrequency (%)
0 11
8.1%
3000000 1
 
0.7%
10000000 3
 
2.2%
20000000 2
 
1.5%
25000000 1
 
0.7%
30000000 2
 
1.5%
32447307 1
 
0.7%
50000000 4
 
3.0%
50229540 1
 
0.7%
60000000 1
 
0.7%
ValueCountFrequency (%)
2923915496587 1
0.7%
113541479196 1
0.7%
27753832640 1
0.7%
9640532751 1
0.7%
5719153118 1
0.7%
4207237259 1
0.7%
2815479973 1
0.7%
2294911608 1
0.7%
1461743556 1
0.7%
1364634176 1
0.7%

부채총액
Real number (ℝ)

MISSING  ZEROS 

Distinct25
Distinct (%)50.0%
Missing85
Missing (%)63.0%
Infinite0
Infinite (%)0.0%
Mean4.4276445 × 1010
Minimum0
Maximum2.1677288 × 1012
Zeros26
Zeros (%)19.3%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T09:12:30.742969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36.4404968 × 108
95-th percentile4.0706013 × 109
Maximum2.1677288 × 1012
Range2.1677288 × 1012
Interquartile range (IQR)6.4404968 × 108

Descriptive statistics

Standard deviation3.0645226 × 1011
Coefficient of variation (CV)6.9213383
Kurtosis49.98464
Mean4.4276445 × 1010
Median Absolute Deviation (MAD)0
Skewness7.0694823
Sum2.2138223 × 1012
Variance9.3912987 × 1022
MonotonicityNot monotonic
2024-05-11T09:12:31.108928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 26
 
19.3%
2167728792420 1
 
0.7%
60000000 1
 
0.7%
107533460 1
 
0.7%
874985009 1
 
0.7%
5184290315 1
 
0.7%
756310097 1
 
0.7%
25636699588 1
 
0.7%
1281979005 1
 
0.7%
58776008 1
 
0.7%
Other values (15) 15
 
11.1%
(Missing) 85
63.0%
ValueCountFrequency (%)
0 26
19.3%
2000000 1
 
0.7%
10000000 1
 
0.7%
15520623 1
 
0.7%
20000000 1
 
0.7%
58776008 1
 
0.7%
60000000 1
 
0.7%
107533460 1
 
0.7%
129563509 1
 
0.7%
160648606 1
 
0.7%
ValueCountFrequency (%)
2167728792420 1
0.7%
25636699588 1
0.7%
5184290315 1
0.7%
2709425849 1
0.7%
2393916259 1
0.7%
1731451631 1
0.7%
1403298561 1
0.7%
1281979005 1
0.7%
1093835503 1
0.7%
1008730588 1
0.7%

자본금
Real number (ℝ)

MISSING  ZEROS 

Distinct23
Distinct (%)46.0%
Missing85
Missing (%)63.0%
Infinite0
Infinite (%)0.0%
Mean1.7548422 × 1010
Minimum0
Maximum7.561867 × 1011
Zeros6
Zeros (%)4.4%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T09:12:31.452110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q110000000
median50000000
Q31 × 108
95-th percentile1.612131 × 1010
Maximum7.561867 × 1011
Range7.561867 × 1011
Interquartile range (IQR)90000000

Descriptive statistics

Standard deviation1.0736575 × 1011
Coefficient of variation (CV)6.1182567
Kurtosis48.485844
Mean1.7548422 × 1010
Median Absolute Deviation (MAD)43500000
Skewness6.923719
Sum8.774211 × 1011
Variance1.1527404 × 1022
MonotonicityNot monotonic
2024-05-11T09:12:31.901427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
50000000 11
 
8.1%
10000000 6
 
4.4%
0 6
 
4.4%
100000000 5
 
3.7%
1000000 2
 
1.5%
20000000 2
 
1.5%
60000000 2
 
1.5%
3000000 1
 
0.7%
25000000 1
 
0.7%
286142914 1
 
0.7%
Other values (13) 13
 
9.6%
(Missing) 85
63.0%
ValueCountFrequency (%)
0 6
4.4%
1000000 2
 
1.5%
2000000 1
 
0.7%
3000000 1
 
0.7%
10000000 6
4.4%
20000000 2
 
1.5%
25000000 1
 
0.7%
30000000 1
 
0.7%
34203925 1
 
0.7%
48229540 1
 
0.7%
ValueCountFrequency (%)
756186704167 1
0.7%
87904779608 1
0.7%
26022381009 1
0.7%
4020000000 1
0.7%
1000000000 1
0.7%
286142914 1
0.7%
200000000 1
0.7%
150000000 1
0.7%
130000000 1
0.7%
106654124 1
0.7%

판매방식명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing135
Missing (%)100.0%
Memory size1.3 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
03050000200530501002420005120050408<NA>3폐업3폐업처리20160222<NA><NA><NA>6223-8585<NA>130844서울특별시 동대문구 장안*동 ***번지 *호서울특별시 동대문구 천호대로 *** (장안동)130844하나로넷(주)2016-02-22 18:02:39I2018-08-31 23:59:59.0<NA>205597.832562451080.986789000<NA>
13050000200630501002420007220060427<NA>3폐업3폐업처리20090615<NA><NA>20060427952-1005<NA><NA>서울특별시 동대문구 제기동 ****번지 *호 영진빌딩 *층서울특별시 동대문구 무학로**길 * (제기동,영진빌딩 *층)<NA>천호물산2009-06-15 15:26:19I2018-08-31 23:59:59.0<NA>202612.185386453233.722488<NA><NA><NA><NA>
23050000200630501002420008120060921<NA>3폐업3폐업처리20090813<NA><NA>200609212245-3611<NA><NA>서울특별시 동대문구 휘경동 **번지 *호 *층서울특별시 동대문구 망우로 ** (휘경동,*층)<NA>송악2009-08-13 13:52:25I2018-08-31 23:59:59.0<NA>205535.496774454269.587501<NA><NA><NA><NA>
33050000200630501002420008220060921<NA>4취소/말소/만료/정지/중지7직권말소20130121<NA><NA>200609212248-6300<NA><NA>서울특별시 동대문구 휘경동 **번지 *호 태림빌딩 *층서울특별시 동대문구 망우로 ** (휘경동,태림빌딩 *층)<NA>송악실업2013-01-22 17:22:03I2018-08-31 23:59:59.0<NA>205535.496774454269.587501<NA><NA><NA><NA>
43050000200630501002420313220061208<NA>3폐업3폐업처리20080715<NA><NA>200612083295-5338<NA><NA>서울특별시 동대문구 이문동 ***번지 ***호서울특별시 동대문구 신이문로*길 * (이문동)<NA>리스원2008-07-15 15:22:22I2018-08-31 23:59:59.0<NA>205445.545575455590.106464<NA><NA><NA><NA>
53050000200730501002420008520070501<NA>3폐업3폐업처리20190730<NA><NA><NA>02-925-2563<NA><NA>서울특별시 동대문구 신설동 **번지 **호 풍한빌딩 ***호서울특별시 동대문구 하정로*길 **, ***호 (신설동, 풍한빌딩)130811(주) 다인에듀2019-07-30 11:25:15U2019-08-01 02:40:00.0<NA>202207.233858452586.0813888777375722678706850000000<NA>
63050000200730501002420008720070702<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA>20070702959-0996<NA><NA>서울특별시 동대문구 청량리동 **번지 **호 *층서울특별시 동대문구 왕산로 ***-* (청량리동,*층)<NA>씨엠2010-04-14 13:48:04I2018-08-31 23:59:59.0<NA>204257.27418453459.013903<NA><NA><NA><NA>
73050000200730501002420008820070705<NA>3폐업3폐업처리20190709<NA><NA><NA>2115-4069<NA><NA>서울특별시 동대문구 신설동 ***번지 **호 한국도자기빌딩*층,*층서울특별시 동대문구 청계천로 ***, *.*층 (신설동, 한국도자기빌딩)130811비씨카드(주)2019-07-09 10:05:48U2019-07-11 02:40:00.0<NA>202318.050602452088.64740929239154965872167728792420756186704167<NA>
83050000200730501002420009020070726<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA>20070726922-8929<NA><NA>서울특별시 동대문구 제기동 ****번지 **호 유니텔 ****호서울특별시 동대문구 왕산로**라길 *, ****호 (제기동,유니텔)<NA>두리정보통신2010-04-14 13:47:25I2018-08-31 23:59:59.0<NA>202929.726171452956.947115<NA><NA><NA><NA>
93050000200730501002420009120070727<NA>3폐업3폐업처리20091123<NA><NA>200707272215-9907<NA><NA>서울특별시 동대문구 전농동 ***번지 *호 ***호서울특별시 동대문구 전농로 ***, ***호 (전농동)<NA>이코노맥2009-11-23 09:29:00I2018-08-31 23:59:59.0<NA>205014.611607452740.70616<NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
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