Overview

Dataset statistics

Number of variables29
Number of observations628
Missing cells4755
Missing cells (%)26.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory151.6 KiB
Average record size in memory247.2 B

Variable types

Categorical9
Numeric7
DateTime5
Text5
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
Author서초구
URLhttps://data.seoul.go.kr/dataList/OA-18798/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (78.5%)Imbalance
휴업시작일자 is highly imbalanced (97.8%)Imbalance
휴업종료일자 is highly imbalanced (97.8%)Imbalance
소재지우편번호 is highly imbalanced (64.4%)Imbalance
폐업일자 has 157 (25.0%) missing valuesMissing
재개업일자 has 563 (89.6%) missing valuesMissing
전화번호 has 46 (7.3%) missing valuesMissing
소재지면적 has 628 (100.0%) missing valuesMissing
지번주소 has 110 (17.5%) missing valuesMissing
도로명주소 has 237 (37.7%) missing valuesMissing
도로명우편번호 has 348 (55.4%) missing valuesMissing
업태구분명 has 628 (100.0%) missing valuesMissing
좌표정보(X) has 234 (37.3%) missing valuesMissing
좌표정보(Y) has 234 (37.3%) missing valuesMissing
자산규모 has 314 (50.0%) missing valuesMissing
부채총액 has 314 (50.0%) missing valuesMissing
자본금 has 314 (50.0%) missing valuesMissing
판매방식명 has 628 (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 145 (23.1%) zerosZeros
부채총액 has 200 (31.8%) zerosZeros
자본금 has 89 (14.2%) zerosZeros

Reproduction

Analysis started2024-04-29 19:48:39.126448
Analysis finished2024-04-29 19:48:40.058480
Duration0.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
3210000
628 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3210000
2nd row3210000
3rd row3210000
4th row3210000
5th row3210000

Common Values

ValueCountFrequency (%)
3210000 628
100.0%

Length

2024-04-30T04:48:40.119301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:48:40.198196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3210000 628
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct628
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0116857 × 1018
Minimum2.002321 × 1018
Maximum2.024321 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-04-30T04:48:40.294812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.002321 × 1018
5-th percentile2.003321 × 1018
Q12.007321 × 1018
median2.009321 × 1018
Q32.016321 × 1018
95-th percentile2.022321 × 1018
Maximum2.024321 × 1018
Range2.2000003 × 1016
Interquartile range (IQR)9.0000032 × 1015

Descriptive statistics

Standard deviation5.8961649 × 1015
Coefficient of variation (CV)0.0029309574
Kurtosis-0.94143914
Mean2.0116857 × 1018
Median Absolute Deviation (MAD)3 × 1015
Skewness0.54223691
Sum8.9599992 × 1018
Variance3.4764761 × 1031
MonotonicityStrictly increasing
2024-04-30T04:48:40.406035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2002321012124200001 1
 
0.2%
2014321012124200010 1
 
0.2%
2014321012124200003 1
 
0.2%
2014321012124200004 1
 
0.2%
2014321012124200005 1
 
0.2%
2014321012124200006 1
 
0.2%
2014321012124200007 1
 
0.2%
2014321012124200008 1
 
0.2%
2014321012124200009 1
 
0.2%
2014321012124200011 1
 
0.2%
Other values (618) 618
98.4%
ValueCountFrequency (%)
2002321012124200001 1
0.2%
2002321012124200002 1
0.2%
2002321012124200003 1
0.2%
2002321012124200004 1
0.2%
2002321012124200008 1
0.2%
2002321012124200009 1
0.2%
2002321012124200010 1
0.2%
2002321012124200013 1
0.2%
2002321012124200014 1
0.2%
2002321012124200015 1
0.2%
ValueCountFrequency (%)
2024321015324200003 1
0.2%
2024321015324200002 1
0.2%
2024321015324200001 1
0.2%
2023321015324200013 1
0.2%
2023321015324200012 1
0.2%
2023321015324200011 1
0.2%
2023321015324200010 1
0.2%
2023321015324200009 1
0.2%
2023321015324200008 1
0.2%
2023321015324200007 1
0.2%

인허가일자
Date

Distinct543
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
Minimum2002-08-07 00:00:00
Maximum2024-04-08 00:00:00
2024-04-30T04:48:40.512174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:48:40.635529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
<NA>
590 
20080827
 
37
20160201
 
1

Length

Max length8
Median length4
Mean length4.2420382
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 590
93.9%
20080827 37
 
5.9%
20160201 1
 
0.2%

Length

2024-04-30T04:48:40.768045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:48:40.862626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 590
93.9%
20080827 37
 
5.9%
20160201 1
 
0.2%

영업상태코드
Categorical

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
3
321 
4
159 
1
138 
5
 
8
2
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 321
51.1%
4 159
25.3%
1 138
22.0%
5 8
 
1.3%
2 2
 
0.3%

Length

2024-04-30T04:48:40.951200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:48:41.048150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 321
51.1%
4 159
25.3%
1 138
22.0%
5 8
 
1.3%
2 2
 
0.3%

영업상태명
Categorical

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
폐업
321 
취소/말소/만료/정지/중지
159 
영업/정상
138 
제외/삭제/전출
 
8
휴업
 
2

Length

Max length14
Median length2
Mean length5.7738854
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 321
51.1%
취소/말소/만료/정지/중지 159
25.3%
영업/정상 138
22.0%
제외/삭제/전출 8
 
1.3%
휴업 2
 
0.3%

Length

2024-04-30T04:48:41.168717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:48:41.273424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 321
51.1%
취소/말소/만료/정지/중지 159
25.3%
영업/정상 138
22.0%
제외/삭제/전출 8
 
1.3%
휴업 2
 
0.3%

상세영업상태코드
Real number (ℝ)

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4156051
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-04-30T04:48:41.362011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q34
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.9761444
Coefficient of variation (CV)0.5785635
Kurtosis-0.40486611
Mean3.4156051
Median Absolute Deviation (MAD)0
Skewness0.75655826
Sum2145
Variance3.9051468
MonotonicityNot monotonic
2024-04-30T04:48:41.445679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 321
51.1%
1 137
21.8%
7 121
 
19.3%
4 38
 
6.1%
5 8
 
1.3%
2 3
 
0.5%
ValueCountFrequency (%)
1 137
21.8%
2 3
 
0.5%
3 321
51.1%
4 38
 
6.1%
5 8
 
1.3%
7 121
 
19.3%
ValueCountFrequency (%)
7 121
 
19.3%
5 8
 
1.3%
4 38
 
6.1%
3 321
51.1%
2 3
 
0.5%
1 137
21.8%

상세영업상태명
Categorical

Distinct7
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
폐업처리
321 
정상영업
137 
직권말소
121 
직권취소
38 
타시군구이관
 
8
Other values (2)
 
3

Length

Max length6
Median length4
Mean length4.0254777
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
폐업처리 321
51.1%
정상영업 137
21.8%
직권말소 121
 
19.3%
직권취소 38
 
6.1%
타시군구이관 8
 
1.3%
휴업처리 2
 
0.3%
<NA> 1
 
0.2%

Length

2024-04-30T04:48:41.555983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:48:41.659845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업처리 321
51.1%
정상영업 137
21.8%
직권말소 121
 
19.3%
직권취소 38
 
6.1%
타시군구이관 8
 
1.3%
휴업처리 2
 
0.3%
na 1
 
0.2%

폐업일자
Date

MISSING 

Distinct258
Distinct (%)54.8%
Missing157
Missing (%)25.0%
Memory size5.0 KiB
Minimum2003-08-08 00:00:00
Maximum2024-04-23 00:00:00
2024-04-30T04:48:41.784173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:48:41.897334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
<NA>
626 
20140430
 
1
20191031
 
1

Length

Max length8
Median length4
Mean length4.0127389
Min length4

Unique

Unique2 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 626
99.7%
20140430 1
 
0.2%
20191031 1
 
0.2%

Length

2024-04-30T04:48:42.012596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:48:42.125683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 626
99.7%
20140430 1
 
0.2%
20191031 1
 
0.2%

휴업종료일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
<NA>
626 
20190430
 
1
20211231
 
1

Length

Max length8
Median length4
Mean length4.0127389
Min length4

Unique

Unique2 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 626
99.7%
20190430 1
 
0.2%
20211231 1
 
0.2%

Length

2024-04-30T04:48:42.220553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:48:42.326443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 626
99.7%
20190430 1
 
0.2%
20211231 1
 
0.2%

재개업일자
Date

MISSING 

Distinct53
Distinct (%)81.5%
Missing563
Missing (%)89.6%
Memory size5.0 KiB
Minimum2002-08-07 00:00:00
Maximum2019-08-02 00:00:00
2024-04-30T04:48:42.422434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:48:42.548979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

전화번호
Text

MISSING 

Distinct539
Distinct (%)92.6%
Missing46
Missing (%)7.3%
Memory size5.0 KiB
2024-04-30T04:48:42.755757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length10.95189
Min length2

Characters and Unicode

Total characters6374
Distinct characters14
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique510 ?
Unique (%)87.6%

Sample

1st row02-6444-1114
2nd row02-6444-1234
3rd row02-535-7878
4th row02-521-1651
5th row02-2057-2741
ValueCountFrequency (%)
02 11
 
1.9%
070-7709-5490 4
 
0.7%
070-8109-1177 4
 
0.7%
070-5099-7992 4
 
0.7%
02-6969-3939 3
 
0.5%
02-3019-5041 3
 
0.5%
02-521-0300 2
 
0.3%
02-571-8170 2
 
0.3%
02-556-0081 2
 
0.3%
025881291 2
 
0.3%
Other values (531) 551
93.7%
2024-04-30T04:48:43.096837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1120
17.6%
- 928
14.6%
2 894
14.0%
5 643
10.1%
1 428
 
6.7%
7 423
 
6.6%
8 402
 
6.3%
3 401
 
6.3%
4 386
 
6.1%
6 354
 
5.6%
Other values (4) 395
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5378
84.4%
Dash Punctuation 928
 
14.6%
Other Punctuation 62
 
1.0%
Space Separator 6
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1120
20.8%
2 894
16.6%
5 643
12.0%
1 428
 
8.0%
7 423
 
7.9%
8 402
 
7.5%
3 401
 
7.5%
4 386
 
7.2%
6 354
 
6.6%
9 327
 
6.1%
Other Punctuation
ValueCountFrequency (%)
. 61
98.4%
/ 1
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 928
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6374
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1120
17.6%
- 928
14.6%
2 894
14.0%
5 643
10.1%
1 428
 
6.7%
7 423
 
6.6%
8 402
 
6.3%
3 401
 
6.3%
4 386
 
6.1%
6 354
 
5.6%
Other values (4) 395
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6374
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1120
17.6%
- 928
14.6%
2 894
14.0%
5 643
10.1%
1 428
 
6.7%
7 423
 
6.6%
8 402
 
6.3%
3 401
 
6.3%
4 386
 
6.1%
6 354
 
5.6%
Other values (4) 395
 
6.2%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing628
Missing (%)100.0%
Memory size5.6 KiB

소재지우편번호
Categorical

IMBALANCE 

Distinct10
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
<NA>
494 
137070
74 
137060
 
23
137130
 
13
137040
 
11
Other values (5)
 
13

Length

Max length7
Median length4
Mean length4.4283439
Min length4

Unique

Unique3 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 494
78.7%
137070 74
 
11.8%
137060 23
 
3.7%
137130 13
 
2.1%
137040 11
 
1.8%
137030 7
 
1.1%
137071 3
 
0.5%
137131 1
 
0.2%
137-060 1
 
0.2%
137140 1
 
0.2%

Length

2024-04-30T04:48:43.216761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:48:43.324293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 494
78.7%
137070 74
 
11.8%
137060 23
 
3.7%
137130 13
 
2.1%
137040 11
 
1.8%
137030 7
 
1.1%
137071 3
 
0.5%
137131 1
 
0.2%
137-060 1
 
0.2%
137140 1
 
0.2%

지번주소
Text

MISSING 

Distinct251
Distinct (%)48.5%
Missing110
Missing (%)17.5%
Memory size5.0 KiB
2024-04-30T04:48:43.611923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length37
Mean length27.698842
Min length17

Characters and Unicode

Total characters14348
Distinct characters235
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

Unique196 ?
Unique (%)37.8%

Sample

1st row서울특별시 서초구 서초동 일반번지 ****-*
2nd row서울특별시 서초구 서초동 일반번지 ****-*
3rd row서울특별시 서초구 서초동 일반번지 ****-*
4th row서울특별시 서초구 서초동 일반번지 ****-*
5th row서울특별시 서초구 양재동 일반번지 ***-*
ValueCountFrequency (%)
서울특별시 518
18.3%
서초구 518
18.3%
339
12.0%
서초동 286
10.1%
일반번지 234
8.3%
호 226
8.0%
번지 182
 
6.4%
방배동 90
 
3.2%
양재동 57
 
2.0%
층 51
 
1.8%
Other values (184) 323
11.4%
2024-04-30T04:48:44.013590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2852
19.9%
* 2753
19.2%
서 1340
 
9.3%
초 817
 
5.7%
동 522
 
3.6%
시 521
 
3.6%
울 520
 
3.6%
특 518
 
3.6%
별 518
 
3.6%
구 518
 
3.6%
Other values (225) 3469
24.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8348
58.2%
Space Separator 2852
 
19.9%
Other Punctuation 2762
 
19.3%
Dash Punctuation 325
 
2.3%
Uppercase Letter 49
 
0.3%
Decimal Number 9
 
0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 1340
16.1%
초 817
 
9.8%
동 522
 
6.3%
시 521
 
6.2%
울 520
 
6.2%
특 518
 
6.2%
별 518
 
6.2%
구 518
 
6.2%
지 428
 
5.1%
번 417
 
5.0%
Other values (200) 2229
26.7%
Uppercase Letter
ValueCountFrequency (%)
T 7
14.3%
R 6
12.2%
E 5
10.2%
W 5
10.2%
O 5
10.2%
I 5
10.2%
A 5
10.2%
N 4
8.2%
M 4
8.2%
V 1
 
2.0%
Other values (2) 2
 
4.1%
Decimal Number
ValueCountFrequency (%)
1 2
22.2%
7 2
22.2%
0 2
22.2%
8 1
11.1%
9 1
11.1%
3 1
11.1%
Other Punctuation
ValueCountFrequency (%)
* 2753
99.7%
, 9
 
0.3%
Space Separator
ValueCountFrequency (%)
2852
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 325
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8348
58.2%
Common 5951
41.5%
Latin 49
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 1340
16.1%
초 817
 
9.8%
동 522
 
6.3%
시 521
 
6.2%
울 520
 
6.2%
특 518
 
6.2%
별 518
 
6.2%
구 518
 
6.2%
지 428
 
5.1%
번 417
 
5.0%
Other values (200) 2229
26.7%
Common
ValueCountFrequency (%)
2852
47.9%
* 2753
46.3%
- 325
 
5.5%
, 9
 
0.2%
1 2
 
< 0.1%
7 2
 
< 0.1%
0 2
 
< 0.1%
8 1
 
< 0.1%
) 1
 
< 0.1%
( 1
 
< 0.1%
Other values (3) 3
 
0.1%
Latin
ValueCountFrequency (%)
T 7
14.3%
R 6
12.2%
E 5
10.2%
W 5
10.2%
O 5
10.2%
I 5
10.2%
A 5
10.2%
N 4
8.2%
M 4
8.2%
V 1
 
2.0%
Other values (2) 2
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8348
58.2%
ASCII 6000
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2852
47.5%
* 2753
45.9%
- 325
 
5.4%
, 9
 
0.1%
T 7
 
0.1%
R 6
 
0.1%
E 5
 
0.1%
W 5
 
0.1%
O 5
 
0.1%
I 5
 
0.1%
Other values (15) 28
 
0.5%
Hangul
ValueCountFrequency (%)
서 1340
16.1%
초 817
 
9.8%
동 522
 
6.3%
시 521
 
6.2%
울 520
 
6.2%
특 518
 
6.2%
별 518
 
6.2%
구 518
 
6.2%
지 428
 
5.1%
번 417
 
5.0%
Other values (200) 2229
26.7%

도로명주소
Text

MISSING 

Distinct342
Distinct (%)87.5%
Missing237
Missing (%)37.7%
Memory size5.0 KiB
2024-04-30T04:48:44.395404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length45
Mean length35.053708
Min length22

Characters and Unicode

Total characters13706
Distinct characters270
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

Unique307 ?
Unique (%)78.5%

Sample

1st row서울특별시 서초구 효령로 *** (서초동)
2nd row서울특별시 서초구 헌릉로 ** (양재동)
3rd row서울특별시 서초구 사임당로 ** (서초동)
4th row서울특별시 서초구 양재천로 **, *층 (양재동, 정원빌딩)
5th row서울특별시 서초구 반포대로 **, ***호 (서초동,명정빌딩)
ValueCountFrequency (%)
405
15.7%
서울특별시 391
15.1%
서초구 390
15.1%
층 170
 
6.6%
호 166
 
6.4%
서초동 155
 
6.0%
방배동 54
 
2.1%
강남대로 44
 
1.7%
양재동 44
 
1.7%
서초대로**길 35
 
1.4%
Other values (353) 730
28.3%
2024-04-30T04:48:44.720573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2194
16.0%
* 2151
15.7%
서 1102
 
8.0%
초 696
 
5.1%
, 534
 
3.9%
동 425
 
3.1%
시 395
 
2.9%
울 394
 
2.9%
) 392
 
2.9%
( 392
 
2.9%
Other values (260) 5031
36.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7886
57.5%
Other Punctuation 2686
 
19.6%
Space Separator 2194
 
16.0%
Close Punctuation 392
 
2.9%
Open Punctuation 392
 
2.9%
Uppercase Letter 87
 
0.6%
Dash Punctuation 51
 
0.4%
Decimal Number 16
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 1102
 
14.0%
초 696
 
8.8%
동 425
 
5.4%
시 395
 
5.0%
울 394
 
5.0%
특 391
 
5.0%
별 391
 
5.0%
구 390
 
4.9%
로 389
 
4.9%
층 234
 
3.0%
Other values (232) 3079
39.0%
Uppercase Letter
ValueCountFrequency (%)
E 12
13.8%
A 11
12.6%
R 10
11.5%
T 9
10.3%
O 9
10.3%
B 7
8.0%
W 7
8.0%
N 6
6.9%
I 5
5.7%
M 4
 
4.6%
Other values (3) 7
8.0%
Decimal Number
ValueCountFrequency (%)
5 6
37.5%
2 4
25.0%
1 2
 
12.5%
0 1
 
6.2%
4 1
 
6.2%
9 1
 
6.2%
3 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
* 2151
80.1%
, 534
 
19.9%
/ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
2194
100.0%
Close Punctuation
ValueCountFrequency (%)
) 392
100.0%
Open Punctuation
ValueCountFrequency (%)
( 392
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 51
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7886
57.5%
Common 5733
41.8%
Latin 87
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 1102
 
14.0%
초 696
 
8.8%
동 425
 
5.4%
시 395
 
5.0%
울 394
 
5.0%
특 391
 
5.0%
별 391
 
5.0%
구 390
 
4.9%
로 389
 
4.9%
층 234
 
3.0%
Other values (232) 3079
39.0%
Common
ValueCountFrequency (%)
2194
38.3%
* 2151
37.5%
, 534
 
9.3%
) 392
 
6.8%
( 392
 
6.8%
- 51
 
0.9%
5 6
 
0.1%
2 4
 
0.1%
~ 2
 
< 0.1%
1 2
 
< 0.1%
Other values (5) 5
 
0.1%
Latin
ValueCountFrequency (%)
E 12
13.8%
A 11
12.6%
R 10
11.5%
T 9
10.3%
O 9
10.3%
B 7
8.0%
W 7
8.0%
N 6
6.9%
I 5
5.7%
M 4
 
4.6%
Other values (3) 7
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7886
57.5%
ASCII 5820
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2194
37.7%
* 2151
37.0%
, 534
 
9.2%
) 392
 
6.7%
( 392
 
6.7%
- 51
 
0.9%
E 12
 
0.2%
A 11
 
0.2%
R 10
 
0.2%
T 9
 
0.2%
Other values (18) 64
 
1.1%
Hangul
ValueCountFrequency (%)
서 1102
 
14.0%
초 696
 
8.8%
동 425
 
5.4%
시 395
 
5.0%
울 394
 
5.0%
특 391
 
5.0%
별 391
 
5.0%
구 390
 
4.9%
로 389
 
4.9%
층 234
 
3.0%
Other values (232) 3079
39.0%

도로명우편번호
Text

MISSING 

Distinct135
Distinct (%)48.2%
Missing348
Missing (%)55.4%
Memory size5.0 KiB
2024-04-30T04:48:44.998670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.2785714
Min length5

Characters and Unicode

Total characters1478
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

Unique72 ?
Unique (%)25.7%

Sample

1st row137891
2nd row137891
3rd row06730
4th row06707
5th row137131
ValueCountFrequency (%)
137071 13
 
4.6%
06621 8
 
2.9%
137061 7
 
2.5%
06649 6
 
2.1%
06754 6
 
2.1%
06627 6
 
2.1%
06710 6
 
2.1%
137131 6
 
2.1%
137030 5
 
1.8%
06721 5
 
1.8%
Other values (125) 212
75.7%
2024-04-30T04:48:45.388662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 333
22.5%
0 283
19.1%
7 211
14.3%
1 161
10.9%
3 150
10.1%
5 89
 
6.0%
2 77
 
5.2%
8 71
 
4.8%
4 60
 
4.1%
9 42
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1477
99.9%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 333
22.5%
0 283
19.2%
7 211
14.3%
1 161
10.9%
3 150
10.2%
5 89
 
6.0%
2 77
 
5.2%
8 71
 
4.8%
4 60
 
4.1%
9 42
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1478
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 333
22.5%
0 283
19.1%
7 211
14.3%
1 161
10.9%
3 150
10.1%
5 89
 
6.0%
2 77
 
5.2%
8 71
 
4.8%
4 60
 
4.1%
9 42
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1478
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 333
22.5%
0 283
19.1%
7 211
14.3%
1 161
10.9%
3 150
10.1%
5 89
 
6.0%
2 77
 
5.2%
8 71
 
4.8%
4 60
 
4.1%
9 42
 
2.8%

사업장명
Text

Distinct614
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2024-04-30T04:48:45.638470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length25
Mean length8.6783439
Min length2

Characters and Unicode

Total characters5450
Distinct characters450
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique600 ?
Unique (%)95.5%

Sample

1st row(주)데이타링크
2nd row주식회사비즈아이링크
3rd row삼호투자정보(주)
4th row화이트뷰티 주식회사
5th row(주)미래로홈쇼핑
ValueCountFrequency (%)
주식회사 98
 
12.2%
주 18
 
2.2%
서초지점 4
 
0.5%
컴퍼니 3
 
0.4%
에이치씨엔 3
 
0.4%
닥스클럽(주 2
 
0.2%
co.,ltd 2
 
0.2%
농업회사법인 2
 
0.2%
태영 2
 
0.2%
동작방송 2
 
0.2%
Other values (650) 665
83.0%
2024-04-30T04:48:45.998233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 463
 
8.5%
( 377
 
6.9%
) 377
 
6.9%
이 251
 
4.6%
173
 
3.2%
스 161
 
3.0%
사 125
 
2.3%
회 111
 
2.0%
식 105
 
1.9%
에 97
 
1.8%
Other values (440) 3210
58.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4317
79.2%
Open Punctuation 377
 
6.9%
Close Punctuation 377
 
6.9%
Space Separator 173
 
3.2%
Uppercase Letter 114
 
2.1%
Lowercase Letter 54
 
1.0%
Other Punctuation 23
 
0.4%
Decimal Number 9
 
0.2%
Other Symbol 5
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 463
 
10.7%
이 251
 
5.8%
스 161
 
3.7%
사 125
 
2.9%
회 111
 
2.6%
식 105
 
2.4%
에 97
 
2.2%
아 87
 
2.0%
리 61
 
1.4%
씨 58
 
1.3%
Other values (390) 2798
64.8%
Uppercase Letter
ValueCountFrequency (%)
T 18
15.8%
S 11
9.6%
L 10
 
8.8%
C 10
 
8.8%
K 10
 
8.8%
M 6
 
5.3%
N 6
 
5.3%
E 6
 
5.3%
G 5
 
4.4%
O 5
 
4.4%
Other values (11) 27
23.7%
Lowercase Letter
ValueCountFrequency (%)
o 11
20.4%
n 7
13.0%
t 6
11.1%
i 5
9.3%
e 5
9.3%
d 3
 
5.6%
r 3
 
5.6%
m 3
 
5.6%
c 2
 
3.7%
u 2
 
3.7%
Other values (5) 7
13.0%
Decimal Number
ValueCountFrequency (%)
2 3
33.3%
1 3
33.3%
5 1
 
11.1%
6 1
 
11.1%
3 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
. 17
73.9%
& 3
 
13.0%
, 2
 
8.7%
' 1
 
4.3%
Open Punctuation
ValueCountFrequency (%)
( 377
100.0%
Close Punctuation
ValueCountFrequency (%)
) 377
100.0%
Space Separator
ValueCountFrequency (%)
173
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4322
79.3%
Common 960
 
17.6%
Latin 168
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 463
 
10.7%
이 251
 
5.8%
스 161
 
3.7%
사 125
 
2.9%
회 111
 
2.6%
식 105
 
2.4%
에 97
 
2.2%
아 87
 
2.0%
리 61
 
1.4%
씨 58
 
1.3%
Other values (391) 2803
64.9%
Latin
ValueCountFrequency (%)
T 18
 
10.7%
o 11
 
6.5%
S 11
 
6.5%
L 10
 
6.0%
C 10
 
6.0%
K 10
 
6.0%
n 7
 
4.2%
t 6
 
3.6%
M 6
 
3.6%
N 6
 
3.6%
Other values (26) 73
43.5%
Common
ValueCountFrequency (%)
( 377
39.3%
) 377
39.3%
173
18.0%
. 17
 
1.8%
& 3
 
0.3%
2 3
 
0.3%
1 3
 
0.3%
, 2
 
0.2%
5 1
 
0.1%
6 1
 
0.1%
Other values (3) 3
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4317
79.2%
ASCII 1128
 
20.7%
None 5
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 463
 
10.7%
이 251
 
5.8%
스 161
 
3.7%
사 125
 
2.9%
회 111
 
2.6%
식 105
 
2.4%
에 97
 
2.2%
아 87
 
2.0%
리 61
 
1.4%
씨 58
 
1.3%
Other values (390) 2798
64.8%
ASCII
ValueCountFrequency (%)
( 377
33.4%
) 377
33.4%
173
15.3%
T 18
 
1.6%
. 17
 
1.5%
o 11
 
1.0%
S 11
 
1.0%
L 10
 
0.9%
C 10
 
0.9%
K 10
 
0.9%
Other values (39) 114
 
10.1%
None
ValueCountFrequency (%)
㈜ 5
100.0%

최종수정일자
Date

Distinct496
Distinct (%)79.0%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
Minimum2007-08-21 16:28:00
Maximum2024-04-23 17:19:58
2024-04-30T04:48:46.122375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:48:46.240605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
I
487 
U
141 

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 487
77.5%
U 141
 
22.5%

Length

2024-04-30T04:48:46.349518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:48:46.440625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 487
77.5%
u 141
 
22.5%

데이터갱신일자
Date

Distinct135
Distinct (%)21.5%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:04:00
2024-04-30T04:48:46.534053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:48:46.640831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing628
Missing (%)100.0%
Memory size5.6 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct279
Distinct (%)70.8%
Missing234
Missing (%)37.3%
Infinite0
Infinite (%)0.0%
Mean201460.78
Minimum198349.16
Maximum206161.93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-04-30T04:48:46.762647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum198349.16
5-th percentile198541.92
Q1200886.03
median201569.7
Q3202469.95
95-th percentile203686.27
Maximum206161.93
Range7812.7697
Interquartile range (IQR)1583.9218

Descriptive statistics

Standard deviation1460.7392
Coefficient of variation (CV)0.0072507373
Kurtosis-0.089661822
Mean201460.78
Median Absolute Deviation (MAD)857.14602
Skewness-0.3379116
Sum79375547
Variance2133759
MonotonicityNot monotonic
2024-04-30T04:48:46.886075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200886.032544788 11
 
1.8%
200976.965811773 9
 
1.4%
200214.828933969 7
 
1.1%
202501.602561199 6
 
1.0%
198358.536839066 5
 
0.8%
202374.665 4
 
0.6%
202459.257859185 4
 
0.6%
203091.887944423 4
 
0.6%
202503.485056887 4
 
0.6%
201788.911303223 4
 
0.6%
Other values (269) 336
53.5%
(Missing) 234
37.3%
ValueCountFrequency (%)
198349.158592224 1
 
0.2%
198358.536839066 5
0.8%
198359.105676344 1
 
0.2%
198380.114292953 1
 
0.2%
198391.007333333 1
 
0.2%
198409.59135773 1
 
0.2%
198443.274372584 1
 
0.2%
198444.667531433 1
 
0.2%
198464.569551277 2
 
0.3%
198469.85580049 1
 
0.2%
ValueCountFrequency (%)
206161.92827043 1
0.2%
204911.736143026 1
0.2%
204848.795091048 1
0.2%
204180.485422373 1
0.2%
204145.273488218 1
0.2%
204116.577978744 1
0.2%
204106.051432322 1
0.2%
204045.305024541 2
0.3%
203997.623430765 1
0.2%
203976.509189755 1
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct279
Distinct (%)70.8%
Missing234
Missing (%)37.3%
Infinite0
Infinite (%)0.0%
Mean442932.88
Minimum438355.07
Maximum446135.83
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-04-30T04:48:47.006476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum438355.07
5-th percentile440857.54
Q1442235.09
median442840.13
Q3443591.95
95-th percentile445269.16
Maximum446135.83
Range7780.7624
Interquartile range (IQR)1356.8575

Descriptive statistics

Standard deviation1253.2604
Coefficient of variation (CV)0.002829459
Kurtosis0.7668473
Mean442932.88
Median Absolute Deviation (MAD)634.00829
Skewness0.016739672
Sum1.7451556 × 108
Variance1570661.7
MonotonicityNot monotonic
2024-04-30T04:48:47.138978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
442481.68257248 11
 
1.8%
442218.566296199 9
 
1.4%
442206.118999192 7
 
1.1%
443226.434038556 6
 
1.0%
441651.560578965 5
 
0.8%
443842.38 4
 
0.6%
443620.263219246 4
 
0.6%
441525.467888004 4
 
0.6%
442457.349985651 4
 
0.6%
442649.482582399 4
 
0.6%
Other values (269) 336
53.5%
(Missing) 234
37.3%
ValueCountFrequency (%)
438355.065946358 1
0.2%
438983.342243657 1
0.2%
439287.784364838 1
0.2%
439715.760765925 1
0.2%
439960.533113874 2
0.3%
440053.553486368 1
0.2%
440136.781183797 1
0.2%
440215.751657504 1
0.2%
440222.152896766 2
0.3%
440281.405998565 1
0.2%
ValueCountFrequency (%)
446135.828367442 1
0.2%
446094.650854533 2
0.3%
445960.835289042 1
0.2%
445889.401388054 2
0.3%
445824.056378303 1
0.2%
445818.335734799 2
0.3%
445802.100265801 1
0.2%
445715.447249109 1
0.2%
445666.908243581 1
0.2%
445533.225557562 1
0.2%

자산규모
Real number (ℝ)

MISSING  ZEROS 

Distinct128
Distinct (%)40.8%
Missing314
Missing (%)50.0%
Infinite0
Infinite (%)0.0%
Mean3.956256 × 1011
Minimum0
Maximum8.50712 × 1013
Zeros145
Zeros (%)23.1%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-04-30T04:48:47.269021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median11616530
Q32.5863781 × 108
95-th percentile4.3431487 × 1010
Maximum8.50712 × 1013
Range8.50712 × 1013
Interquartile range (IQR)2.5863781 × 108

Descriptive statistics

Standard deviation5.1249767 × 1012
Coefficient of variation (CV)12.954108
Kurtosis244.36756
Mean3.956256 × 1011
Median Absolute Deviation (MAD)11616530
Skewness15.255811
Sum1.2422644 × 1014
Variance2.6265387 × 1025
MonotonicityNot monotonic
2024-04-30T04:48:47.386531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 145
23.1%
100000000 13
 
2.1%
50000000 12
 
1.9%
300000000 6
 
1.0%
20000000 4
 
0.6%
5000000 4
 
0.6%
30000000 4
 
0.6%
10000000 3
 
0.5%
150000000 2
 
0.3%
400000000 2
 
0.3%
Other values (118) 119
 
18.9%
(Missing) 314
50.0%
ValueCountFrequency (%)
0 145
23.1%
690180 1
 
0.2%
1000000 1
 
0.2%
3000000 1
 
0.2%
5000000 4
 
0.6%
10000000 3
 
0.5%
11068745 1
 
0.2%
11070000 1
 
0.2%
12163059 1
 
0.2%
12592991 1
 
0.2%
ValueCountFrequency (%)
85071200000000 1
0.2%
32000000000000 1
0.2%
1842120532000 1
0.2%
1682500000000 1
0.2%
1536806287145 1
0.2%
441200000000 1
0.2%
409955676717 1
0.2%
272886000000 1
0.2%
176974654946 1
0.2%
123912107529 1
0.2%

부채총액
Real number (ℝ)

MISSING  ZEROS 

Distinct113
Distinct (%)36.0%
Missing314
Missing (%)50.0%
Infinite0
Infinite (%)0.0%
Mean2.3059935 × 1011
Minimum0
Maximum5.626344 × 1013
Zeros200
Zeros (%)31.8%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-04-30T04:48:47.498598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31.2762014 × 108
95-th percentile9.2887939 × 109
Maximum5.626344 × 1013
Range5.626344 × 1013
Interquartile range (IQR)1.2762014 × 108

Descriptive statistics

Standard deviation3.2456924 × 1012
Coefficient of variation (CV)14.075029
Kurtosis286.81662
Mean2.3059935 × 1011
Median Absolute Deviation (MAD)0
Skewness16.69711
Sum7.2408195 × 1013
Variance1.0534519 × 1025
MonotonicityNot monotonic
2024-04-30T04:48:47.618418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 200
31.8%
200000000 2
 
0.3%
30000000 2
 
0.3%
8877413400 1
 
0.2%
769370940 1
 
0.2%
341104614 1
 
0.2%
52185385424 1
 
0.2%
6282209412 1
 
0.2%
111446657971 1
 
0.2%
305802435 1
 
0.2%
Other values (103) 103
 
16.4%
(Missing) 314
50.0%
ValueCountFrequency (%)
0 200
31.8%
1070000 1
 
0.2%
1102005 1
 
0.2%
1340444 1
 
0.2%
1805000 1
 
0.2%
3951240 1
 
0.2%
5000000 1
 
0.2%
7791000 1
 
0.2%
10000000 1
 
0.2%
10315810 1
 
0.2%
ValueCountFrequency (%)
56263440000000 1
0.2%
12000000000000 1
0.2%
1439867328844 1
0.2%
1315314712289 1
0.2%
762300000000 1
0.2%
140992665219 1
0.2%
111446657971 1
0.2%
57200000000 1
0.2%
52185385424 1
0.2%
42161000000 1
0.2%

자본금
Real number (ℝ)

MISSING  ZEROS 

Distinct78
Distinct (%)24.8%
Missing314
Missing (%)50.0%
Infinite0
Infinite (%)0.0%
Mean7.5042077 × 1010
Minimum-1.624882 × 108
Maximum1.9 × 1013
Zeros89
Zeros (%)14.2%
Negative4
Negative (%)0.6%
Memory size5.6 KiB
2024-04-30T04:48:47.734393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.624882 × 108
5-th percentile0
Q10
median50000000
Q32 × 108
95-th percentile1.0042607 × 1010
Maximum1.9 × 1013
Range1.9000162 × 1013
Interquartile range (IQR)2 × 108

Descriptive statistics

Standard deviation1.0812195 × 1012
Coefficient of variation (CV)14.408177
Kurtosis302.69226
Mean7.5042077 × 1010
Median Absolute Deviation (MAD)50000000
Skewness17.268273
Sum2.3563212 × 1013
Variance1.1690357 × 1024
MonotonicityNot monotonic
2024-04-30T04:48:47.884758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 89
 
14.2%
50000000 50
 
8.0%
100000000 31
 
4.9%
10000000 17
 
2.7%
300000000 14
 
2.2%
200000000 9
 
1.4%
150000000 8
 
1.3%
20000000 7
 
1.1%
400000000 6
 
1.0%
5000000 5
 
0.8%
Other values (68) 78
 
12.4%
(Missing) 314
50.0%
ValueCountFrequency (%)
-162488201 1
 
0.2%
-120872837 1
 
0.2%
-33665284 1
 
0.2%
-2031071 1
 
0.2%
0 89
14.2%
1000000 5
 
0.8%
1813923 1
 
0.2%
3000000 1
 
0.2%
4000000 1
 
0.2%
5000000 5
 
0.8%
ValueCountFrequency (%)
19000000000000 1
0.2%
1848652275000 1
0.2%
1755870000000 1
0.2%
384000000000 1
0.2%
96938958301 1
0.2%
71726722105 1
0.2%
65527996975 1
0.2%
53946380000 1
0.2%
50279847179 1
0.2%
44000000000 1
0.2%

판매방식명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing628
Missing (%)100.0%
Memory size5.6 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
03210000200232101212420000120020807<NA>3폐업3폐업처리20060627<NA><NA>2002080702-6444-1114<NA><NA>서울특별시 서초구 서초동 일반번지 ****-*<NA><NA>(주)데이타링크2008-02-01 21:21:33I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
13210000200232101212420000220020807<NA>3폐업3폐업처리20060627<NA><NA>2002080702-6444-1234<NA><NA>서울특별시 서초구 서초동 일반번지 ****-*<NA><NA>주식회사비즈아이링크2008-02-01 21:21:33I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
23210000200232101212420000320020813<NA>3폐업3폐업처리20050328<NA><NA>2002081302-535-7878<NA><NA>서울특별시 서초구 서초동 일반번지 ****-*<NA><NA>삼호투자정보(주)2008-02-01 21:21:33I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
33210000200232101212420000420020813<NA>3폐업3폐업처리20050328<NA><NA>2002090402-521-1651<NA><NA>서울특별시 서초구 서초동 일반번지 ****-*<NA><NA>화이트뷰티 주식회사2008-02-01 21:21:33I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
43210000200232101212420000820020817<NA>3폐업3폐업처리20050328<NA><NA>2002081702-2057-2741<NA><NA>서울특별시 서초구 양재동 일반번지 ***-*<NA><NA>(주)미래로홈쇼핑2008-02-01 21:21:33I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
53210000200232101212420000920020819<NA>3폐업3폐업처리20031007<NA><NA>2002081902-597-5577<NA><NA>서울특별시 서초구 방배동 일반번지 ***-*<NA><NA>(주)대동씨앤디2008-02-01 21:21:33I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
63210000200232101212420001020020819<NA>3폐업3폐업처리20030808<NA><NA>2002081902-592-5991<NA><NA>서울특별시 서초구 방배동 일반번지 ***-**<NA><NA>문헌가훈2008-02-01 21:21:33I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
73210000200232101212420001320020821<NA>3폐업3폐업처리20160830<NA><NA><NA>1588.4000<NA><NA>서울특별시 서초구 서초동 ****번지서울특별시 서초구 효령로 *** (서초동)<NA>비씨카드(주)2016-08-30 16:06:31I2018-08-31 23:59:59.0<NA>201186.096157442533.1572381842120532000131531471228944000000000<NA>
83210000200232101212420001420020821<NA>3폐업3폐업처리20031001<NA><NA>2002082102-3477-0615<NA><NA>서울특별시 서초구 서초동 일반번지 ****-**<NA><NA>E.J.C미디어2008-02-01 21:21:33I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
93210000200232101212420001520020829<NA>3폐업3폐업처리20050328<NA><NA>2002082902-534-1001<NA><NA>서울특별시 서초구 서초동 일반번지 ****-*<NA><NA>제일사2008-02-01 21:21:33I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
618321000020233210153242000072023-03-10<NA>5제외/삭제/전출5타시군구이관2024-03-28<NA><NA><NA>1588-1555<NA><NA>서울특별시 서초구 서초동 ****-* 남서울빌딩서울특별시 서초구 강남대로 ***, 남서울빌딩 (서초동)06611(주)인터파크커머스2024-03-28 15:15:11U2023-12-02 21:00:00.0<NA>202137.581932444438.154651<NA><NA><NA><NA>
619321000020233210153242000082023-05-18<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 서초구 서초동 ****-* 현빌딩서울특별시 서초구 서초대로**길 **, 현빌딩 *층 ****호 (서초동)06650세강정보통신2023-05-18 10:25:07I2022-12-04 22:00:00.0<NA>201122.363486443111.971546<NA><NA><NA><NA>
620321000020233210153242000092023-05-22<NA>1영업/정상1정상영업<NA><NA><NA><NA>1899-9796<NA><NA>서울특별시 서초구 방배동 ***-*서울특별시 서초구 효령로*길 *, 비***호 (방배동)06699주식회사 해피나우2023-05-22 14:26:09I2022-12-04 22:04:00.0<NA>198740.157883441570.644239<NA><NA><NA><NA>
621321000020233210153242000102023-07-14<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-1533-2870<NA><NA>서울특별시 서초구 양재동 ***-*서울특별시 서초구 동산로*길 **, *층 (양재동)06787클럽그라운드㈜2023-07-19 11:54:07U2022-12-06 22:01:00.0<NA>203666.725440726.19<NA><NA><NA><NA>
622321000020233210153242000112020-04-06<NA>1영업/정상1정상영업<NA><NA><NA><NA>070-7938-3232<NA><NA>서울특별시 서초구 방배동 ***-* 유중문화재단서울특별시 서초구 방배로 ***, 유중문화재단 *층 ***호 (방배동)06586주식회사 글로벌212023-11-23 15:09:36U2022-10-31 22:05:00.0<NA>199285.043158443069.163643<NA><NA><NA><NA>
623321000020233210153242000122023-11-16<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 서초구 양재동 ***-* 신영빌딩서울특별시 서초구 마방로*길 **, 신영빌딩 *층 (양재동)06777쑨랩주식회사2024-03-21 09:48:50U2023-12-02 22:03:00.0<NA>203679.997001441382.148319<NA><NA><NA><NA>
624321000020233210153242000132019-11-21<NA>1영업/정상1정상영업<NA><NA><NA><NA>070-7709-5490<NA><NA>서울특별시 서초구 서초동 ****-** 강남 MAIN TOWER서울특별시 서초구 강남대로 ***, 강남 MAIN TOWER *층 ***호 (서초동)06729주식회사 에프에스씨(FSC)2024-01-15 15:02:17U2023-11-30 23:07:00.0<NA>202760.817265442855.50352<NA><NA><NA><NA>
625321000020243210153242000012024-02-02<NA>1영업/정상1정상영업<NA><NA><NA><NA>0264882695<NA><NA>서울특별시 서초구 방배동 ***-** 디엠타워 *관서울특별시 서초구 방배로 ***, 디엠타워 *관 (방배동)06683프롭티어 주식회사(proptier Co.,Ltd.)2024-02-02 11:01:30I2023-12-02 00:04:00.0<NA>199563.715755442383.113143<NA><NA><NA><NA>
626321000020243210153242000022016-05-30<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-795-2300<NA><NA>서울특별시 서초구 서초동 ****-* 프랜드호텔서울특별시 서초구 효령로 ***, *,*층 (서초동)06643(주) 파라텍2024-04-08 09:29:50U2023-12-03 23:00:00.0<NA>201846.586838442752.888685<NA><NA><NA><NA>
627321000020243210153242000032024-04-08<NA>1영업/정상1정상영업<NA><NA><NA><NA>025218220<NA><NA>서울특별시 서초구 방배동 ****-*서울특별시 서초구 효령로 ***, 신관 지하*층 (방배동)06707주식회사 케이티엔에스티2024-04-08 11:06:45I2023-12-03 23:00:00.0<NA>200214.828934442206.118999<NA><NA><NA><NA>