Overview

Dataset statistics

Number of variables29
Number of observations93
Missing cells859
Missing cells (%)31.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.7 KiB
Average record size in memory249.4 B

Variable types

Categorical7
Numeric8
DateTime4
Unsupported4
Text6

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
Author서대문구
URLhttps://data.seoul.go.kr/dataList/OA-18789/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
휴업시작일자 is highly imbalanced (91.4%)Imbalance
휴업종료일자 is highly imbalanced (91.4%)Imbalance
인허가취소일자 has 93 (100.0%) missing valuesMissing
폐업일자 has 27 (29.0%) missing valuesMissing
재개업일자 has 63 (67.7%) missing valuesMissing
전화번호 has 16 (17.2%) missing valuesMissing
소재지면적 has 93 (100.0%) missing valuesMissing
소재지우편번호 has 57 (61.3%) missing valuesMissing
지번주소 has 1 (1.1%) missing valuesMissing
도로명주소 has 31 (33.3%) missing valuesMissing
도로명우편번호 has 41 (44.1%) missing valuesMissing
업태구분명 has 93 (100.0%) missing valuesMissing
좌표정보(X) has 28 (30.1%) missing valuesMissing
좌표정보(Y) has 28 (30.1%) missing valuesMissing
자산규모 has 65 (69.9%) missing valuesMissing
부채총액 has 65 (69.9%) missing valuesMissing
자본금 has 65 (69.9%) missing valuesMissing
판매방식명 has 93 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
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 6 (6.5%) zerosZeros
부채총액 has 9 (9.7%) zerosZeros
자본금 has 5 (5.4%) zerosZeros

Reproduction

Analysis started2024-05-11 08:46:45.577365
Analysis finished2024-05-11 08:46:46.934599
Duration1.36 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size876.0 B
3120000
93 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3120000
2nd row3120000
3rd row3120000
4th row3120000
5th row3120000

Common Values

ValueCountFrequency (%)
3120000 93
100.0%

Length

2024-05-11T08:46:47.122888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:46:47.389709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3120000 93
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct93
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0115916 × 1018
Minimum2.002312 × 1018
Maximum2.024312 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2024-05-11T08:46:47.789969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.002312 × 1018
5-th percentile2.002912 × 1018
Q12.006312 × 1018
median2.012312 × 1018
Q32.015312 × 1018
95-th percentile2.020712 × 1018
Maximum2.024312 × 1018
Range2.2000011 × 1016
Interquartile range (IQR)9.0000076 × 1015

Descriptive statistics

Standard deviation6.0976966 × 1015
Coefficient of variation (CV)0.0030312796
Kurtosis-1.0902014
Mean2.0115916 × 1018
Median Absolute Deviation (MAD)5.0000038 × 1015
Skewness0.1536977
Sum2.6105766 × 1018
Variance3.7181904 × 1031
MonotonicityStrictly increasing
2024-05-11T08:46:48.366380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2002312010724200001 1
 
1.1%
2014312018324200005 1
 
1.1%
2015312018324200010 1
 
1.1%
2015312018324200008 1
 
1.1%
2015312018324200007 1
 
1.1%
2015312018324200006 1
 
1.1%
2015312018324200005 1
 
1.1%
2015312018324200004 1
 
1.1%
2015312018324200003 1
 
1.1%
2015312018324200002 1
 
1.1%
Other values (83) 83
89.2%
ValueCountFrequency (%)
2002312010724200001 1
1.1%
2002312010724200002 1
1.1%
2002312010724200003 1
1.1%
2002312010724200004 1
1.1%
2002312010724200005 1
1.1%
2003312010724200007 1
1.1%
2003312010724200008 1
1.1%
2003312010724200009 1
1.1%
2003312010724200010 1
1.1%
2003312010724200011 1
1.1%
ValueCountFrequency (%)
2024312021924200002 1
1.1%
2024312021924200001 1
1.1%
2023312021924200001 1
1.1%
2022312019224200001 1
1.1%
2021312019224200001 1
1.1%
2020312019224200003 1
1.1%
2020312019224200002 1
1.1%
2020312019224200001 1
1.1%
2019312019224200007 1
1.1%
2019312019224200006 1
1.1%

인허가일자
Date

Distinct84
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Memory size876.0 B
Minimum2002-06-05 00:00:00
Maximum2024-04-22 00:00:00
2024-05-11T08:46:48.873208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:46:49.415692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing93
Missing (%)100.0%
Memory size969.0 B

영업상태코드
Categorical

Distinct5
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size876.0 B
3
59 
4
21 
1
10 
5
 
2
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
3 59
63.4%
4 21
 
22.6%
1 10
 
10.8%
5 2
 
2.2%
2 1
 
1.1%

Length

2024-05-11T08:46:50.040622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:46:50.530339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 59
63.4%
4 21
 
22.6%
1 10
 
10.8%
5 2
 
2.2%
2 1
 
1.1%

영업상태명
Categorical

Distinct5
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size876.0 B
폐업
59 
취소/말소/만료/정지/중지
21 
영업/정상
10 
제외/삭제/전출
 
2
휴업
 
1

Length

Max length14
Median length2
Mean length5.1612903
Min length2

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 59
63.4%
취소/말소/만료/정지/중지 21
 
22.6%
영업/정상 10
 
10.8%
제외/삭제/전출 2
 
2.2%
휴업 1
 
1.1%

Length

2024-05-11T08:46:51.076545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:46:51.606786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 59
63.4%
취소/말소/만료/정지/중지 21
 
22.6%
영업/정상 10
 
10.8%
제외/삭제/전출 2
 
2.2%
휴업 1
 
1.1%

상세영업상태코드
Real number (ℝ)

Distinct6
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.688172
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2024-05-11T08:46:52.024914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q33
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.8822887
Coefficient of variation (CV)0.51035816
Kurtosis-0.36870984
Mean3.688172
Median Absolute Deviation (MAD)0
Skewness0.85407983
Sum343
Variance3.5430108
MonotonicityNot monotonic
2024-05-11T08:46:52.465500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 59
63.4%
7 20
 
21.5%
1 10
 
10.8%
5 2
 
2.2%
4 1
 
1.1%
2 1
 
1.1%
ValueCountFrequency (%)
1 10
 
10.8%
2 1
 
1.1%
3 59
63.4%
4 1
 
1.1%
5 2
 
2.2%
7 20
 
21.5%
ValueCountFrequency (%)
7 20
 
21.5%
5 2
 
2.2%
4 1
 
1.1%
3 59
63.4%
2 1
 
1.1%
1 10
 
10.8%

상세영업상태명
Categorical

Distinct6
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size876.0 B
폐업처리
59 
직권말소
20 
정상영업
10 
타시군구이관
 
2
직권취소
 
1

Length

Max length6
Median length4
Mean length4.0430108
Min length4

Unique

Unique2 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
폐업처리 59
63.4%
직권말소 20
 
21.5%
정상영업 10
 
10.8%
타시군구이관 2
 
2.2%
직권취소 1
 
1.1%
휴업처리 1
 
1.1%

Length

2024-05-11T08:46:52.867295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:46:53.515490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업처리 59
63.4%
직권말소 20
 
21.5%
정상영업 10
 
10.8%
타시군구이관 2
 
2.2%
직권취소 1
 
1.1%
휴업처리 1
 
1.1%

폐업일자
Date

MISSING 

Distinct62
Distinct (%)93.9%
Missing27
Missing (%)29.0%
Memory size876.0 B
Minimum2002-11-22 00:00:00
Maximum2023-09-06 00:00:00
2024-05-11T08:46:53.810130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:46:54.135979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
<NA>
92 
20210811
 
1

Length

Max length8
Median length4
Mean length4.0430108
Min length4

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 92
98.9%
20210811 1
 
1.1%

Length

2024-05-11T08:46:54.562809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:46:54.882547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 92
98.9%
20210811 1
 
1.1%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
<NA>
92 
20220810
 
1

Length

Max length8
Median length4
Mean length4.0430108
Min length4

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 92
98.9%
20220810 1
 
1.1%

Length

2024-05-11T08:46:55.242480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:46:55.558985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 92
98.9%
20220810 1
 
1.1%

재개업일자
Real number (ℝ)

MISSING 

Distinct26
Distinct (%)86.7%
Missing63
Missing (%)67.7%
Infinite0
Infinite (%)0.0%
Mean20043824
Minimum20020927
Maximum20070529
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2024-05-11T08:46:55.875327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20020927
5-th percentile20020966
Q120030970
median20041070
Q320058292
95-th percentile20066177
Maximum20070529
Range49602
Interquartile range (IQR)27321.5

Descriptive statistics

Standard deviation15512.725
Coefficient of variation (CV)0.00077394038
Kurtosis-1.1191766
Mean20043824
Median Absolute Deviation (MAD)10460
Skewness-0.0098737498
Sum6.0131473 × 108
Variance2.4064464 × 108
MonotonicityNot monotonic
2024-05-11T08:46:56.315700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
20061226 2
 
2.2%
20060714 2
 
2.2%
20051026 2
 
2.2%
20040501 2
 
2.2%
20041227 1
 
1.1%
20070529 1
 
1.1%
20070228 1
 
1.1%
20061121 1
 
1.1%
20060804 1
 
1.1%
20050812 1
 
1.1%
Other values (16) 16
 
17.2%
(Missing) 63
67.7%
ValueCountFrequency (%)
20020927 1
1.1%
20020930 1
1.1%
20021010 1
1.1%
20021111 1
1.1%
20021122 1
1.1%
20030121 1
1.1%
20030303 1
1.1%
20030918 1
1.1%
20031128 1
1.1%
20031205 1
1.1%
ValueCountFrequency (%)
20070529 1
1.1%
20070228 1
1.1%
20061226 2
2.2%
20061121 1
1.1%
20060804 1
1.1%
20060714 2
2.2%
20051026 2
2.2%
20050812 1
1.1%
20050713 1
1.1%
20050624 1
1.1%

전화번호
Text

MISSING 

Distinct68
Distinct (%)88.3%
Missing16
Missing (%)17.2%
Memory size876.0 B
2024-05-11T08:46:57.108424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length10.896104
Min length8

Characters and Unicode

Total characters839
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

Unique59 ?
Unique (%)76.6%

Sample

1st row02-362-2410
2nd row02-1588-2131
3rd row02-3147-0815
4th row02-722-9722
5th row02-302-8087
ValueCountFrequency (%)
02-303-3696 2
 
2.6%
02-336-2545 2
 
2.6%
02-1588-1074 2
 
2.6%
02-372-1952 2
 
2.6%
02-395-8888 2
 
2.6%
02-2274-3119 2
 
2.6%
1877-5537 2
 
2.6%
02-392-1473 2
 
2.6%
02-395-5740 2
 
2.6%
02-364-5200 1
 
1.3%
Other values (58) 58
75.3%
2024-05-11T08:46:58.185398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 142
16.9%
0 137
16.3%
2 118
14.1%
3 100
11.9%
1 68
8.1%
7 53
 
6.3%
5 48
 
5.7%
6 46
 
5.5%
8 44
 
5.2%
9 42
 
5.0%
Other values (2) 41
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 696
83.0%
Dash Punctuation 142
 
16.9%
Math Symbol 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 137
19.7%
2 118
17.0%
3 100
14.4%
1 68
9.8%
7 53
 
7.6%
5 48
 
6.9%
6 46
 
6.6%
8 44
 
6.3%
9 42
 
6.0%
4 40
 
5.7%
Dash Punctuation
ValueCountFrequency (%)
- 142
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 839
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 142
16.9%
0 137
16.3%
2 118
14.1%
3 100
11.9%
1 68
8.1%
7 53
 
6.3%
5 48
 
5.7%
6 46
 
5.5%
8 44
 
5.2%
9 42
 
5.0%
Other values (2) 41
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 839
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 142
16.9%
0 137
16.3%
2 118
14.1%
3 100
11.9%
1 68
8.1%
7 53
 
6.3%
5 48
 
5.7%
6 46
 
5.5%
8 44
 
5.2%
9 42
 
5.0%
Other values (2) 41
 
4.9%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing93
Missing (%)100.0%
Memory size969.0 B

소재지우편번호
Text

MISSING 

Distinct23
Distinct (%)63.9%
Missing57
Missing (%)61.3%
Memory size876.0 B
2024-05-11T08:46:58.687023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0277778
Min length6

Characters and Unicode

Total characters217
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

Unique16 ?
Unique (%)44.4%

Sample

1st row120110
2nd row120103
3rd row120834
4th row120812
5th row120180
ValueCountFrequency (%)
120110 4
 
11.1%
120012 4
 
11.1%
120030 3
 
8.3%
120180 3
 
8.3%
120866 2
 
5.6%
120101 2
 
5.6%
120130 2
 
5.6%
120707 1
 
2.8%
120120 1
 
2.8%
120-012 1
 
2.8%
Other values (13) 13
36.1%
2024-05-11T08:46:59.635121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 70
32.3%
1 65
30.0%
2 44
20.3%
8 10
 
4.6%
3 9
 
4.1%
6 5
 
2.3%
7 5
 
2.3%
4 4
 
1.8%
9 3
 
1.4%
5 1
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 216
99.5%
Dash Punctuation 1
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 70
32.4%
1 65
30.1%
2 44
20.4%
8 10
 
4.6%
3 9
 
4.2%
6 5
 
2.3%
7 5
 
2.3%
4 4
 
1.9%
9 3
 
1.4%
5 1
 
0.5%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 217
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 70
32.3%
1 65
30.0%
2 44
20.3%
8 10
 
4.6%
3 9
 
4.1%
6 5
 
2.3%
7 5
 
2.3%
4 4
 
1.8%
9 3
 
1.4%
5 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 217
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 70
32.3%
1 65
30.0%
2 44
20.3%
8 10
 
4.6%
3 9
 
4.1%
6 5
 
2.3%
7 5
 
2.3%
4 4
 
1.8%
9 3
 
1.4%
5 1
 
0.5%

지번주소
Text

MISSING 

Distinct79
Distinct (%)85.9%
Missing1
Missing (%)1.1%
Memory size876.0 B
2024-05-11T08:47:00.259910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length37
Mean length29.880435
Min length19

Characters and Unicode

Total characters2749
Distinct characters121
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique69 ?
Unique (%)75.0%

Sample

1st row서울특별시 서대문구 북아현동 일반 ***-** 무림빌딩 *층
2nd row서울특별시 서대문구 충정로*가 일반번지 **-* 동신 B/D *F
3rd row서울특별시 서대문구 신촌동 일반번지 ***-* 연세공학원 ***
4th row서울특별시 서대문구 홍제동 일반 ***-* 도시하우스 ***호
5th row서울특별시 서대문구 북가좌동 일반 ***-** 월드컵빌딩 *층
ValueCountFrequency (%)
서울특별시 92
16.8%
서대문구 92
16.8%
호 60
11.0%
번지 54
9.9%
47
8.6%
층 24
 
4.4%
충정로*가 17
 
3.1%
북가좌동 17
 
3.1%
일반번지 16
 
2.9%
일반 14
 
2.6%
Other values (63) 114
20.8%
2024-05-11T08:47:01.674838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 522
19.0%
505
18.4%
서 186
 
6.8%
대 96
 
3.5%
문 94
 
3.4%
시 94
 
3.4%
구 93
 
3.4%
울 92
 
3.3%
별 92
 
3.3%
특 92
 
3.3%
Other values (111) 883
32.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1674
60.9%
Other Punctuation 526
 
19.1%
Space Separator 505
 
18.4%
Dash Punctuation 39
 
1.4%
Uppercase Letter 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 186
 
11.1%
대 96
 
5.7%
문 94
 
5.6%
시 94
 
5.6%
구 93
 
5.6%
울 92
 
5.5%
별 92
 
5.5%
특 92
 
5.5%
동 80
 
4.8%
지 71
 
4.2%
Other values (102) 684
40.9%
Uppercase Letter
ValueCountFrequency (%)
B 2
40.0%
D 1
20.0%
F 1
20.0%
A 1
20.0%
Other Punctuation
ValueCountFrequency (%)
* 522
99.2%
, 3
 
0.6%
/ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
505
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1674
60.9%
Common 1070
38.9%
Latin 5
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 186
 
11.1%
대 96
 
5.7%
문 94
 
5.6%
시 94
 
5.6%
구 93
 
5.6%
울 92
 
5.5%
별 92
 
5.5%
특 92
 
5.5%
동 80
 
4.8%
지 71
 
4.2%
Other values (102) 684
40.9%
Common
ValueCountFrequency (%)
* 522
48.8%
505
47.2%
- 39
 
3.6%
, 3
 
0.3%
/ 1
 
0.1%
Latin
ValueCountFrequency (%)
B 2
40.0%
D 1
20.0%
F 1
20.0%
A 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1674
60.9%
ASCII 1075
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 522
48.6%
505
47.0%
- 39
 
3.6%
, 3
 
0.3%
B 2
 
0.2%
/ 1
 
0.1%
D 1
 
0.1%
F 1
 
0.1%
A 1
 
0.1%
Hangul
ValueCountFrequency (%)
서 186
 
11.1%
대 96
 
5.7%
문 94
 
5.6%
시 94
 
5.6%
구 93
 
5.6%
울 92
 
5.5%
별 92
 
5.5%
특 92
 
5.5%
동 80
 
4.8%
지 71
 
4.2%
Other values (102) 684
40.9%

도로명주소
Text

MISSING 

Distinct58
Distinct (%)93.5%
Missing31
Missing (%)33.3%
Memory size876.0 B
2024-05-11T08:47:02.484729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length42
Mean length34.080645
Min length24

Characters and Unicode

Total characters2113
Distinct characters125
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)87.1%

Sample

1st row서울특별시 서대문구 성산로 *** (연희동,부광빌딩 *층)
2nd row서울특별시 서대문구 통일로**길 **, ***호 (홍제동)
3rd row서울특별시 서대문구 명지대길 ** (홍은동)
4th row서울특별시 서대문구 응암로 *** (북가좌동)
5th row서울특별시 서대문구 연희로*길 **-* (창천동,*층)
ValueCountFrequency (%)
64
16.2%
서울특별시 61
15.5%
서대문구 61
15.5%
호 28
 
7.1%
층 23
 
5.8%
북가좌동 13
 
3.3%
충정로*가 9
 
2.3%
서소문로 7
 
1.8%
합동 6
 
1.5%
통일로 5
 
1.3%
Other values (79) 117
29.7%
2024-05-11T08:47:03.894069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
333
 
15.8%
* 331
 
15.7%
서 131
 
6.2%
문 73
 
3.5%
로 71
 
3.4%
, 70
 
3.3%
대 66
 
3.1%
구 63
 
3.0%
시 63
 
3.0%
( 62
 
2.9%
Other values (115) 850
40.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1237
58.5%
Other Punctuation 401
 
19.0%
Space Separator 333
 
15.8%
Open Punctuation 62
 
2.9%
Close Punctuation 62
 
2.9%
Dash Punctuation 17
 
0.8%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 131
 
10.6%
문 73
 
5.9%
로 71
 
5.7%
대 66
 
5.3%
구 63
 
5.1%
시 63
 
5.1%
울 61
 
4.9%
특 61
 
4.9%
별 61
 
4.9%
동 56
 
4.5%
Other values (108) 531
42.9%
Other Punctuation
ValueCountFrequency (%)
* 331
82.5%
, 70
 
17.5%
Space Separator
ValueCountFrequency (%)
333
100.0%
Open Punctuation
ValueCountFrequency (%)
( 62
100.0%
Close Punctuation
ValueCountFrequency (%)
) 62
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1237
58.5%
Common 875
41.4%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 131
 
10.6%
문 73
 
5.9%
로 71
 
5.7%
대 66
 
5.3%
구 63
 
5.1%
시 63
 
5.1%
울 61
 
4.9%
특 61
 
4.9%
별 61
 
4.9%
동 56
 
4.5%
Other values (108) 531
42.9%
Common
ValueCountFrequency (%)
333
38.1%
* 331
37.8%
, 70
 
8.0%
( 62
 
7.1%
) 62
 
7.1%
- 17
 
1.9%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1237
58.5%
ASCII 876
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
333
38.0%
* 331
37.8%
, 70
 
8.0%
( 62
 
7.1%
) 62
 
7.1%
- 17
 
1.9%
A 1
 
0.1%
Hangul
ValueCountFrequency (%)
서 131
 
10.6%
문 73
 
5.9%
로 71
 
5.7%
대 66
 
5.3%
구 63
 
5.1%
시 63
 
5.1%
울 61
 
4.9%
특 61
 
4.9%
별 61
 
4.9%
동 56
 
4.5%
Other values (108) 531
42.9%

도로명우편번호
Text

MISSING 

Distinct42
Distinct (%)80.8%
Missing41
Missing (%)44.1%
Memory size876.0 B
2024-05-11T08:47:04.464726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.5
Min length5

Characters and Unicode

Total characters286
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

Unique34 ?
Unique (%)65.4%

Sample

1st row03634
2nd row120812
3rd row120826
4th row120861
5th row120013
ValueCountFrequency (%)
120030 3
 
5.8%
03737 3
 
5.8%
120707 2
 
3.8%
03667 2
 
3.8%
120866 2
 
3.8%
120807 2
 
3.8%
120101 2
 
3.8%
03681 2
 
3.8%
03665 1
 
1.9%
03786 1
 
1.9%
Other values (32) 32
61.5%
2024-05-11T08:47:05.628245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 73
25.5%
1 48
16.8%
3 37
12.9%
2 33
11.5%
7 33
11.5%
6 29
 
10.1%
8 18
 
6.3%
4 6
 
2.1%
9 4
 
1.4%
5 4
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 285
99.7%
Dash Punctuation 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 73
25.6%
1 48
16.8%
3 37
13.0%
2 33
11.6%
7 33
11.6%
6 29
 
10.2%
8 18
 
6.3%
4 6
 
2.1%
9 4
 
1.4%
5 4
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 286
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 73
25.5%
1 48
16.8%
3 37
12.9%
2 33
11.5%
7 33
11.5%
6 29
 
10.1%
8 18
 
6.3%
4 6
 
2.1%
9 4
 
1.4%
5 4
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 286
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 73
25.5%
1 48
16.8%
3 37
12.9%
2 33
11.5%
7 33
11.5%
6 29
 
10.1%
8 18
 
6.3%
4 6
 
2.1%
9 4
 
1.4%
5 4
 
1.4%

사업장명
Text

Distinct87
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size876.0 B
2024-05-11T08:47:06.444229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length8.172043
Min length2

Characters and Unicode

Total characters760
Distinct characters222
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique82 ?
Unique (%)88.2%

Sample

1st row원호통상
2nd row금산GNB
3rd row코리아티브이네트워크(주)
4th row명성
5th row(주)캐릭세상
ValueCountFrequency (%)
주식회사 14
 
11.7%
씨재이엠시스템 3
 
2.5%
주 3
 
2.5%
주)씨이피스트 2
 
1.7%
js솔루션 2
 
1.7%
미래통신 2
 
1.7%
소방안전신문사업국 2
 
1.7%
주)한국경제비즈니스 1
 
0.8%
아모레카운셀러 1
 
0.8%
자연올 1
 
0.8%
Other values (89) 89
74.2%
2024-05-11T08:47:07.865048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 42
 
5.5%
) 30
 
3.9%
( 30
 
3.9%
27
 
3.6%
사 22
 
2.9%
이 21
 
2.8%
스 19
 
2.5%
회 17
 
2.2%
신 17
 
2.2%
식 15
 
2.0%
Other values (212) 520
68.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 629
82.8%
Close Punctuation 30
 
3.9%
Open Punctuation 30
 
3.9%
Space Separator 27
 
3.6%
Uppercase Letter 20
 
2.6%
Lowercase Letter 11
 
1.4%
Decimal Number 7
 
0.9%
Other Punctuation 5
 
0.7%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 42
 
6.7%
사 22
 
3.5%
이 21
 
3.3%
스 19
 
3.0%
회 17
 
2.7%
신 17
 
2.7%
식 15
 
2.4%
통 11
 
1.7%
아 11
 
1.7%
리 11
 
1.7%
Other values (178) 443
70.4%
Uppercase Letter
ValueCountFrequency (%)
S 3
15.0%
G 2
 
10.0%
J 2
 
10.0%
H 1
 
5.0%
R 1
 
5.0%
K 1
 
5.0%
E 1
 
5.0%
P 1
 
5.0%
C 1
 
5.0%
D 1
 
5.0%
Other values (6) 6
30.0%
Lowercase Letter
ValueCountFrequency (%)
m 2
18.2%
o 2
18.2%
s 1
9.1%
r 1
9.1%
c 1
9.1%
p 1
9.1%
a 1
9.1%
n 1
9.1%
y 1
9.1%
Other Punctuation
ValueCountFrequency (%)
. 3
60.0%
? 1
 
20.0%
& 1
 
20.0%
Decimal Number
ValueCountFrequency (%)
1 5
71.4%
9 2
 
28.6%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Space Separator
ValueCountFrequency (%)
27
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 629
82.8%
Common 99
 
13.0%
Latin 31
 
4.1%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 42
 
6.7%
사 22
 
3.5%
이 21
 
3.3%
스 19
 
3.0%
회 17
 
2.7%
신 17
 
2.7%
식 15
 
2.4%
통 11
 
1.7%
아 11
 
1.7%
리 11
 
1.7%
Other values (178) 443
70.4%
Latin
ValueCountFrequency (%)
S 3
 
9.7%
m 2
 
6.5%
G 2
 
6.5%
J 2
 
6.5%
o 2
 
6.5%
H 1
 
3.2%
R 1
 
3.2%
s 1
 
3.2%
K 1
 
3.2%
E 1
 
3.2%
Other values (15) 15
48.4%
Common
ValueCountFrequency (%)
) 30
30.3%
( 30
30.3%
27
27.3%
1 5
 
5.1%
. 3
 
3.0%
9 2
 
2.0%
? 1
 
1.0%
& 1
 
1.0%
Han
ValueCountFrequency (%)
花 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 628
82.6%
ASCII 130
 
17.1%
CJK 1
 
0.1%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 42
 
6.7%
사 22
 
3.5%
이 21
 
3.3%
스 19
 
3.0%
회 17
 
2.7%
신 17
 
2.7%
식 15
 
2.4%
통 11
 
1.8%
아 11
 
1.8%
리 11
 
1.8%
Other values (177) 442
70.4%
ASCII
ValueCountFrequency (%)
) 30
23.1%
( 30
23.1%
27
20.8%
1 5
 
3.8%
S 3
 
2.3%
. 3
 
2.3%
m 2
 
1.5%
G 2
 
1.5%
J 2
 
1.5%
9 2
 
1.5%
Other values (23) 24
18.5%
CJK
ValueCountFrequency (%)
花 1
100.0%
None
ValueCountFrequency (%)
㈜ 1
100.0%

최종수정일자
Date

Distinct81
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Memory size876.0 B
Minimum2007-10-10 17:06:00
Maximum2024-04-22 15:08:02
2024-05-11T08:47:08.512120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:47:09.023637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
I
72 
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 72
77.4%
U 21
 
22.6%

Length

2024-05-11T08:47:09.418007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:47:09.715079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 72
77.4%
u 21
 
22.6%

데이터갱신일자
Date

Distinct24
Distinct (%)25.8%
Missing0
Missing (%)0.0%
Memory size876.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:01:00
2024-05-11T08:47:10.111938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:47:10.654320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing93
Missing (%)100.0%
Memory size969.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct54
Distinct (%)83.1%
Missing28
Missing (%)30.1%
Infinite0
Infinite (%)0.0%
Mean194167.67
Minimum174012.01
Maximum197028.13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2024-05-11T08:47:11.548742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174012.01
5-th percentile191622.54
Q1193042.67
median194157.72
Q3196545.64
95-th percentile196892.09
Maximum197028.13
Range23016.126
Interquartile range (IQR)3502.9716

Descriptive statistics

Standard deviation3124.7164
Coefficient of variation (CV)0.016092877
Kurtosis26.794344
Mean194167.67
Median Absolute Deviation (MAD)1839.0938
Skewness-4.2161333
Sum12620899
Variance9763852.3
MonotonicityNot monotonic
2024-05-11T08:47:12.006360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
196892.09236853 5
 
5.4%
196884.166631688 2
 
2.2%
191971.959380003 2
 
2.2%
192430.725694996 2
 
2.2%
195609.653653663 2
 
2.2%
194157.720432032 2
 
2.2%
196934.602353655 2
 
2.2%
193998.104669318 2
 
2.2%
196545.638545744 1
 
1.1%
194929.118373323 1
 
1.1%
Other values (44) 44
47.3%
(Missing) 28
30.1%
ValueCountFrequency (%)
174012.006343785 1
1.1%
191526.125663524 1
1.1%
191543.28 1
1.1%
191599.991681053 1
1.1%
191712.752734779 1
1.1%
191971.959380003 2
2.2%
192000.945942229 1
1.1%
192079.366557621 1
1.1%
192138.952818859 1
1.1%
192293.790106355 1
1.1%
ValueCountFrequency (%)
197028.132153511 1
 
1.1%
196934.602353655 2
 
2.2%
196892.09236853 5
5.4%
196884.166631688 2
 
2.2%
196824.072701729 1
 
1.1%
196801.661639204 1
 
1.1%
196746.77643876 1
 
1.1%
196654.148266378 1
 
1.1%
196626.844541919 1
 
1.1%
196595.551427249 1
 
1.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct54
Distinct (%)83.1%
Missing28
Missing (%)30.1%
Infinite0
Infinite (%)0.0%
Mean451944.31
Minimum440999.63
Maximum454793.32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2024-05-11T08:47:12.450971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum440999.63
5-th percentile450603.37
Q1450948.92
median451768.3
Q3453150.85
95-th percentile453725.59
Maximum454793.32
Range13793.686
Interquartile range (IQR)2201.9386

Descriptive statistics

Standard deviation1803.2386
Coefficient of variation (CV)0.0039899575
Kurtosis20.52726
Mean451944.31
Median Absolute Deviation (MAD)1000.0338
Skewness-3.4062397
Sum29376380
Variance3251669.4
MonotonicityNot monotonic
2024-05-11T08:47:12.890027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450948.915518467 5
 
5.4%
451568.612782385 2
 
2.2%
452913.889257902 2
 
2.2%
453502.779170904 2
 
2.2%
451009.97474614 2
 
2.2%
453303.726825303 2
 
2.2%
451330.791514213 2
 
2.2%
453150.85412164 2
 
2.2%
451796.010085486 1
 
1.1%
454154.612346047 1
 
1.1%
Other values (44) 44
47.3%
(Missing) 28
30.1%
ValueCountFrequency (%)
440999.634757388 1
1.1%
450525.834024158 1
1.1%
450545.586789985 1
1.1%
450594.958070864 1
1.1%
450637.010875398 1
1.1%
450674.235866897 1
1.1%
450725.101344006 1
1.1%
450768.268233425 1
1.1%
450797.549782031 1
1.1%
450804.598854289 1
1.1%
ValueCountFrequency (%)
454793.320707152 1
1.1%
454202.157007871 1
1.1%
454154.612346047 1
1.1%
453728.173624151 1
1.1%
453715.25791697 1
1.1%
453591.299331803 1
1.1%
453502.779170904 2
2.2%
453486.385286129 1
1.1%
453483.787496388 1
1.1%
453474.882927471 1
1.1%

자산규모
Real number (ℝ)

MISSING  ZEROS 

Distinct22
Distinct (%)78.6%
Missing65
Missing (%)69.9%
Infinite0
Infinite (%)0.0%
Mean4.1039799 × 109
Minimum0
Maximum7.4945756 × 1010
Zeros6
Zeros (%)6.5%
Negative0
Negative (%)0.0%
Memory size969.0 B
2024-05-11T08:47:13.402007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12809521.2
median1.9288074 × 108
Q38.3793135 × 108
95-th percentile1.6701513 × 1010
Maximum7.4945756 × 1010
Range7.4945756 × 1010
Interquartile range (IQR)8.3512183 × 108

Descriptive statistics

Standard deviation1.4506031 × 1010
Coefficient of variation (CV)3.5346254
Kurtosis23.051708
Mean4.1039799 × 109
Median Absolute Deviation (MAD)1.9288074 × 108
Skewness4.6962334
Sum1.1491144 × 1011
Variance2.1042495 × 1020
MonotonicityNot monotonic
2024-05-11T08:47:13.859228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 6
 
6.5%
3000000 2
 
2.2%
425043647 1
 
1.1%
428573000 1
 
1.1%
2238085 1
 
1.1%
2100000000 1
 
1.1%
107893232 1
 
1.1%
193000000 1
 
1.1%
216952186 1
 
1.1%
21386884750 1
 
1.1%
Other values (12) 12
 
12.9%
(Missing) 65
69.9%
ValueCountFrequency (%)
0 6
6.5%
2238085 1
 
1.1%
3000000 2
 
2.2%
100000000 1
 
1.1%
106918213 1
 
1.1%
107893232 1
 
1.1%
134606399 1
 
1.1%
192761477 1
 
1.1%
193000000 1
 
1.1%
216952186 1
 
1.1%
ValueCountFrequency (%)
74945755704 1
1.1%
21386884750 1
1.1%
8000109155 1
1.1%
2417876627 1
1.1%
2100000000 1
1.1%
1235227217 1
1.1%
1191133572 1
1.1%
720197277 1
1.1%
648858986 1
1.1%
428573000 1
1.1%

부채총액
Real number (ℝ)

MISSING  ZEROS 

Distinct20
Distinct (%)71.4%
Missing65
Missing (%)69.9%
Infinite0
Infinite (%)0.0%
Mean1.2028948 × 109
Minimum0
Maximum1.3675789 × 1010
Zeros9
Zeros (%)9.7%
Negative0
Negative (%)0.0%
Memory size969.0 B
2024-05-11T08:47:14.297111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.6981115 × 108
Q35.1086006 × 108
95-th percentile7.8867734 × 109
Maximum1.3675789 × 1010
Range1.3675789 × 1010
Interquartile range (IQR)5.1086006 × 108

Descriptive statistics

Standard deviation3.2140588 × 109
Coefficient of variation (CV)2.6719368
Kurtosis11.238628
Mean1.2028948 × 109
Median Absolute Deviation (MAD)1.6981115 × 108
Skewness3.448511
Sum3.3681053 × 1010
Variance1.0330174 × 1019
MonotonicityNot monotonic
2024-05-11T08:47:14.643039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 9
 
9.7%
173934321 1
 
1.1%
18647000 1
 
1.1%
16805398 1
 
1.1%
1400000000 1
 
1.1%
497652709 1
 
1.1%
175900000 1
 
1.1%
58271198 1
 
1.1%
13675789458 1
 
1.1%
1283033420 1
 
1.1%
Other values (10) 10
 
10.8%
(Missing) 65
69.9%
ValueCountFrequency (%)
0 9
9.7%
16805398 1
 
1.1%
18647000 1
 
1.1%
43162975 1
 
1.1%
58271198 1
 
1.1%
165687978 1
 
1.1%
173934321 1
 
1.1%
175900000 1
 
1.1%
257272200 1
 
1.1%
290407469 1
 
1.1%
ValueCountFrequency (%)
13675789458 1
1.1%
11061258816 1
1.1%
1991300369 1
1.1%
1400000000 1
1.1%
1283033420 1
1.1%
1136293713 1
1.1%
550482126 1
1.1%
497652709 1
1.1%
461026311 1
1.1%
424127990 1
1.1%

자본금
Real number (ℝ)

MISSING  ZEROS 

Distinct21
Distinct (%)75.0%
Missing65
Missing (%)69.9%
Infinite0
Infinite (%)0.0%
Mean9.1179656 × 108
Minimum-1.226658 × 108
Maximum1.149082 × 1010
Zeros5
Zeros (%)5.4%
Negative1
Negative (%)1.1%
Memory size969.0 B
2024-05-11T08:47:15.045818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.226658 × 108
5-th percentile0
Q13000000
median1.0394662 × 108
Q35.25 × 108
95-th percentile5.460766 × 109
Maximum1.149082 × 1010
Range1.1613486 × 1010
Interquartile range (IQR)5.22 × 108

Descriptive statistics

Standard deviation2.5293233 × 109
Coefficient of variation (CV)2.7739996
Kurtosis13.222851
Mean9.1179656 × 108
Median Absolute Deviation (MAD)1.0394662 × 108
Skewness3.663201
Sum2.5530304 × 1010
Variance6.3974761 × 1018
MonotonicityNot monotonic
2024-05-11T08:47:15.410393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 5
 
5.4%
300000000 2
 
2.2%
100000000 2
 
2.2%
3000000 2
 
2.2%
500000000 1
 
1.1%
107893232 1
 
1.1%
225000000 1
 
1.1%
150000000 1
 
1.1%
7711095292 1
 
1.1%
50000000 1
 
1.1%
Other values (11) 11
 
11.8%
(Missing) 65
69.9%
ValueCountFrequency (%)
-122665801 1
 
1.1%
0 5
5.4%
3000000 2
 
2.2%
25000000 1
 
1.1%
50000000 1
 
1.1%
58769765 1
 
1.1%
60999927 1
 
1.1%
100000000 2
 
2.2%
107893232 1
 
1.1%
150000000 1
 
1.1%
ValueCountFrequency (%)
11490820000 1
1.1%
7711095292 1
1.1%
1281582914 1
1.1%
946225000 1
1.1%
730107261 1
1.1%
684745091 1
1.1%
600000000 1
1.1%
500000000 1
1.1%
300000000 2
2.2%
225000000 1
1.1%

판매방식명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing93
Missing (%)100.0%
Memory size969.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
03120000200231201072420000120020927<NA>3폐업3폐업처리20051116<NA><NA>2002092702-362-2410<NA><NA>서울특별시 서대문구 북아현동 일반 ***-** 무림빌딩 *층<NA><NA>원호통상2008-02-01 21:56:46I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
13120000200231201072420000220020930<NA>3폐업3폐업처리20021122<NA><NA>2002093002-1588-2131<NA><NA>서울특별시 서대문구 충정로*가 일반번지 **-* 동신 B/D *F<NA><NA>금산GNB2008-02-01 21:56:46I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
23120000200231201072420000320021010<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA>2002101002-3147-0815<NA><NA>서울특별시 서대문구 신촌동 일반번지 ***-* 연세공학원 ***<NA><NA>코리아티브이네트워크(주)2010-04-06 10:42:37I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
33120000200231201072420000420021111<NA>3폐업3폐업처리20030904<NA><NA>2002111102-722-9722<NA><NA>서울특별시 서대문구 홍제동 일반 ***-* 도시하우스 ***호<NA><NA>명성2008-02-01 21:56:46I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
43120000200231201072420000520020605<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA>2002112202-302-8087<NA><NA>서울특별시 서대문구 북가좌동 일반 ***-** 월드컵빌딩 *층<NA><NA>(주)캐릭세상2014-02-06 17:51:25I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
53120000200331201072420000720030121<NA>3폐업3폐업처리20070622<NA><NA>2003012102-393-3322<NA><NA>서울특별시 서대문구 신촌동 일반번지 ***-* 연세공학원 *** A호<NA><NA>한국통신돔닷컴(주)2008-02-01 21:56:46I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
63120000200331201072420000820030303<NA>3폐업3폐업처리20041122<NA><NA>2003030302-302-1249<NA><NA>서울특별시 서대문구 북가좌동 일반번지 ***-* 삼호상가 ***호<NA><NA>전주유과2008-02-01 21:56:46I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
73120000200331201072420000920030407<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA>2003112802-363-3291<NA><NA>서울특별시 서대문구 충정로*가 일반번지 ***-*<NA><NA>(주)라트2010-04-06 10:42:06I2018-08-31 23:59:59.0<NA><NA><NA>000<NA>
83120000200331201072420001020030918<NA>3폐업3폐업처리20040413<NA><NA>2003091802-305-8868<NA><NA>서울특별시 서대문구 남가좌동 일반번지 ***-**<NA><NA>피어나2008-02-01 21:56:46I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
93120000200331201072420001120031205<NA>3폐업3폐업처리20071211<NA><NA>2003120502-305-3468<NA><NA>서울특별시 서대문구 북가좌동 일반번지 ***-** 명덕빌라 B-***<NA><NA>태양2007-12-11 11:26:45I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
833120000201931201922420000620191204<NA>3폐업3폐업처리20200326<NA><NA><NA><NA><NA><NA>서울특별시 서대문구 북가좌동 ***번지 *호 기룡하이츠서울특별시 서대문구 증가로**길 **, A동 *층 *호 (북가좌동, 기룡하이츠)03676씨디컴퍼니(CDcompany)2020-03-26 15:17:24U2020-03-28 02:40:00.0<NA>192318.626628453591.299332<NA><NA><NA><NA>
84312000020193120192242000072019-12-23<NA>3폐업3폐업처리2023-08-23<NA><NA><NA><NA><NA><NA>서울특별시 서대문구 북가좌동 ***번지 *호서울특별시 서대문구 응암로 ***, *층 (북가좌동)03677(주)아이티리더스2023-08-23 15:27:46U2022-12-07 22:05:00.0<NA>192293.790106453486.385286<NA><NA><NA><NA>
853120000202031201922420000120190419<NA>2휴업2휴업처리<NA>2021081120220810<NA>02-564-1114<NA><NA>서울특별시 서대문구 창천동 ***번지 **호서울특별시 서대문구 신촌로 **, ***호 (창천동)03786주식회사 퍼플큐브2021-08-12 13:26:54U2021-08-14 02:40:00.0<NA>193946.39522450525.834024223808516805398100000000<NA>
863120000202031201922420000220200423<NA>5제외/삭제/전출5타시군구이관20230110<NA><NA><NA><NA><NA><NA>서울특별시 서대문구 북가좌동 ***번지 *호 선정오피스텔서울특별시 서대문구 증가로 ***, ***호 (북가좌동, 선정오피스텔)03678케이이컴퍼니 (KE 컴퍼니)2023-01-10 13:16:17U2022-11-30 23:02:00.0<NA>192079.366558453483.787496<NA><NA><NA><NA>
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