Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells19249
Missing cells (%)12.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 MiB
Average record size in memory133.0 B

Variable types

Categorical4
Text5
Numeric5
DateTime1

Dataset

Description등록신청사업,영업구분,등록증번호,상호,법인여부,사업장 전화번호,소재지,소재지(도로명),우편번호,등록일자,유효기간만료일자,폐쇄일자,지점설립일자,본점여부,최근수정일자
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-10404/S/1/datasetView.do

Alerts

등록일자 is highly overall correlated with 유효기간만료일자 and 2 other fieldsHigh correlation
유효기간만료일자 is highly overall correlated with 등록일자 and 2 other fieldsHigh correlation
폐쇄일자 is highly overall correlated with 등록일자 and 2 other fieldsHigh correlation
최근수정일자 is highly overall correlated with 등록일자 and 2 other fieldsHigh correlation
본점여부 is highly imbalanced (93.5%)Imbalance
등록증번호 has 157 (1.6%) missing valuesMissing
사업장 전화번호 has 3499 (35.0%) missing valuesMissing
소재지 has 298 (3.0%) missing valuesMissing
소재지(도로명) has 4778 (47.8%) missing valuesMissing
우편번호 has 5627 (56.3%) missing valuesMissing
유효기간만료일자 has 2040 (20.4%) missing valuesMissing
폐쇄일자 has 1614 (16.1%) missing valuesMissing
지점설립일자 has 1236 (12.4%) missing valuesMissing

Reproduction

Analysis started2024-05-11 06:52:23.325303
Analysis finished2024-05-11 06:52:31.976979
Duration8.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
대부업
6224 
대부중개업
3382 
<NA>
 
394

Length

Max length5
Median length3
Mean length3.7158
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대부업 6224
62.2%
대부중개업 3382
33.8%
<NA> 394
 
3.9%

Length

2024-05-11T15:52:32.096993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:52:32.294149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대부업 6224
62.2%
대부중개업 3382
33.8%
na 394
 
3.9%

영업구분
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
3703 
<NA>
2826 
타시군구이관
1228 
영업중
859 
유효기간만료
811 
Other values (2)
573 

Length

Max length6
Median length4
Mean length3.5815
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3703
37.0%
<NA> 2826
28.3%
타시군구이관 1228
 
12.3%
영업중 859
 
8.6%
유효기간만료 811
 
8.1%
직권취소 572
 
5.7%
갱신등록불가 1
 
< 0.1%

Length

2024-05-11T15:52:32.478623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:52:32.675382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3703
37.0%
na 2826
28.3%
타시군구이관 1228
 
12.3%
영업중 859
 
8.6%
유효기간만료 811
 
8.1%
직권취소 572
 
5.7%
갱신등록불가 1
 
< 0.1%

등록증번호
Text

MISSING 

Distinct9789
Distinct (%)99.5%
Missing157
Missing (%)1.6%
Memory size156.2 KiB
2024-05-11T15:52:32.991759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length27
Mean length19.515188
Min length1

Characters and Unicode

Total characters192088
Distinct characters72
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9737 ?
Unique (%)98.9%

Sample

1st row2011-서울도봉-0022(대부중개업)
2nd row2019-서울강서-0006(대부업)
3rd row2012-서울특별시 성북구-00014
4th row2013-서울강남-0340
5th row2008-서울특별시-01083
ValueCountFrequency (%)
2012-서울특별시 17
 
0.2%
2011-서울특별시 17
 
0.2%
2010-서울 17
 
0.2%
2014-서울특별시 14
 
0.1%
2013-서울특별시 13
 
0.1%
대부업 11
 
0.1%
2015-서울특별시 10
 
0.1%
대부중개업 8
 
0.1%
2016-서울특별시 8
 
0.1%
2018-서울특별시 8
 
0.1%
Other values (9748) 9885
98.8%
2024-05-11T15:52:33.502301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 34021
17.7%
- 19670
 
10.2%
2 15752
 
8.2%
1 11878
 
6.2%
10913
 
5.7%
9808
 
5.1%
8498
 
4.4%
( 8217
 
4.3%
8188
 
4.3%
) 8153
 
4.2%
Other values (62) 56990
29.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82821
43.1%
Other Letter 73062
38.0%
Dash Punctuation 19670
 
10.2%
Open Punctuation 8217
 
4.3%
Close Punctuation 8153
 
4.2%
Space Separator 165
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10913
14.9%
9808
13.4%
8498
11.6%
8188
11.2%
7954
10.9%
3506
 
4.8%
2877
 
3.9%
2524
 
3.5%
2514
 
3.4%
2513
 
3.4%
Other values (48) 13767
18.8%
Decimal Number
ValueCountFrequency (%)
0 34021
41.1%
2 15752
19.0%
1 11878
 
14.3%
3 3797
 
4.6%
8 3085
 
3.7%
4 3048
 
3.7%
9 2836
 
3.4%
6 2819
 
3.4%
5 2798
 
3.4%
7 2787
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 19670
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8217
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8153
100.0%
Space Separator
ValueCountFrequency (%)
165
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 119026
62.0%
Hangul 73062
38.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10913
14.9%
9808
13.4%
8498
11.6%
8188
11.2%
7954
10.9%
3506
 
4.8%
2877
 
3.9%
2524
 
3.5%
2514
 
3.4%
2513
 
3.4%
Other values (48) 13767
18.8%
Common
ValueCountFrequency (%)
0 34021
28.6%
- 19670
16.5%
2 15752
13.2%
1 11878
 
10.0%
( 8217
 
6.9%
) 8153
 
6.8%
3 3797
 
3.2%
8 3085
 
2.6%
4 3048
 
2.6%
9 2836
 
2.4%
Other values (4) 8569
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 119026
62.0%
Hangul 73062
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 34021
28.6%
- 19670
16.5%
2 15752
13.2%
1 11878
 
10.0%
( 8217
 
6.9%
) 8153
 
6.8%
3 3797
 
3.2%
8 3085
 
2.6%
4 3048
 
2.6%
9 2836
 
2.4%
Other values (4) 8569
 
7.2%
Hangul
ValueCountFrequency (%)
10913
14.9%
9808
13.4%
8498
11.6%
8188
11.2%
7954
10.9%
3506
 
4.8%
2877
 
3.9%
2524
 
3.5%
2514
 
3.4%
2513
 
3.4%
Other values (48) 13767
18.8%

상호
Text

Distinct8672
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T15:52:33.977075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length33
Mean length7.7274
Min length2

Characters and Unicode

Total characters77274
Distinct characters773
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7595 ?
Unique (%)75.9%

Sample

1st row하이파이낸스대부중개
2nd row(주)신밧드월드대부
3rd row대부신안금융
4th row핑크 뱅 대부
5th row하나에셋투자금융
ValueCountFrequency (%)
주식회사 825
 
6.9%
대부중개 324
 
2.7%
대부 300
 
2.5%
유한회사 55
 
0.5%
대부업 22
 
0.2%
캐피탈 19
 
0.2%
대부중개업 14
 
0.1%
전당포대부 14
 
0.1%
미래 13
 
0.1%
money 12
 
0.1%
Other values (8720) 10399
86.7%
2024-05-11T15:52:34.789721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8546
 
11.1%
8179
 
10.6%
2645
 
3.4%
2241
 
2.9%
2093
 
2.7%
2077
 
2.7%
2003
 
2.6%
1857
 
2.4%
) 1835
 
2.4%
( 1827
 
2.4%
Other values (763) 43971
56.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67518
87.4%
Uppercase Letter 2323
 
3.0%
Space Separator 2003
 
2.6%
Close Punctuation 1835
 
2.4%
Open Punctuation 1827
 
2.4%
Lowercase Letter 1229
 
1.6%
Other Punctuation 255
 
0.3%
Decimal Number 242
 
0.3%
Dash Punctuation 31
 
< 0.1%
Other Symbol 7
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8546
 
12.7%
8179
 
12.1%
2645
 
3.9%
2241
 
3.3%
2093
 
3.1%
2077
 
3.1%
1857
 
2.8%
1376
 
2.0%
1058
 
1.6%
1026
 
1.5%
Other values (690) 36420
53.9%
Uppercase Letter
ValueCountFrequency (%)
S 308
13.3%
K 223
 
9.6%
C 183
 
7.9%
J 177
 
7.6%
M 170
 
7.3%
H 136
 
5.9%
G 94
 
4.0%
L 94
 
4.0%
B 93
 
4.0%
O 91
 
3.9%
Other values (15) 754
32.5%
Lowercase Letter
ValueCountFrequency (%)
o 143
11.6%
e 143
11.6%
n 123
10.0%
a 103
 
8.4%
i 85
 
6.9%
t 80
 
6.5%
c 67
 
5.5%
l 63
 
5.1%
r 62
 
5.0%
s 60
 
4.9%
Other values (15) 300
24.4%
Decimal Number
ValueCountFrequency (%)
1 80
33.1%
2 38
15.7%
4 33
13.6%
9 21
 
8.7%
3 19
 
7.9%
5 19
 
7.9%
6 11
 
4.5%
7 9
 
3.7%
0 7
 
2.9%
8 5
 
2.1%
Other Punctuation
ValueCountFrequency (%)
. 146
57.3%
& 92
36.1%
, 8
 
3.1%
? 7
 
2.7%
' 1
 
0.4%
/ 1
 
0.4%
Space Separator
ValueCountFrequency (%)
2003
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1835
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1827
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Other Symbol
ValueCountFrequency (%)
7
100.0%
Letter Number
ValueCountFrequency (%)
3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67513
87.4%
Common 6194
 
8.0%
Latin 3555
 
4.6%
Han 12
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8546
 
12.7%
8179
 
12.1%
2645
 
3.9%
2241
 
3.3%
2093
 
3.1%
2077
 
3.1%
1857
 
2.8%
1376
 
2.0%
1058
 
1.6%
1026
 
1.5%
Other values (680) 36415
53.9%
Latin
ValueCountFrequency (%)
S 308
 
8.7%
K 223
 
6.3%
C 183
 
5.1%
J 177
 
5.0%
M 170
 
4.8%
o 143
 
4.0%
e 143
 
4.0%
H 136
 
3.8%
n 123
 
3.5%
a 103
 
2.9%
Other values (41) 1846
51.9%
Common
ValueCountFrequency (%)
2003
32.3%
) 1835
29.6%
( 1827
29.5%
. 146
 
2.4%
& 92
 
1.5%
1 80
 
1.3%
2 38
 
0.6%
4 33
 
0.5%
- 31
 
0.5%
9 21
 
0.3%
Other values (11) 88
 
1.4%
Han
ValueCountFrequency (%)
2
16.7%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67505
87.4%
ASCII 9746
 
12.6%
CJK 12
 
< 0.1%
None 7
 
< 0.1%
Number Forms 3
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
8546
 
12.7%
8179
 
12.1%
2645
 
3.9%
2241
 
3.3%
2093
 
3.1%
2077
 
3.1%
1857
 
2.8%
1376
 
2.0%
1058
 
1.6%
1026
 
1.5%
Other values (678) 36407
53.9%
ASCII
ValueCountFrequency (%)
2003
20.6%
) 1835
18.8%
( 1827
18.7%
S 308
 
3.2%
K 223
 
2.3%
C 183
 
1.9%
J 177
 
1.8%
M 170
 
1.7%
. 146
 
1.5%
o 143
 
1.5%
Other values (61) 2731
28.0%
None
ValueCountFrequency (%)
7
100.0%
Number Forms
ValueCountFrequency (%)
3
100.0%
CJK
ValueCountFrequency (%)
2
16.7%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

법인여부
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
개인
7269 
법인
2731 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row개인
2nd row법인
3rd row개인
4th row개인
5th row개인

Common Values

ValueCountFrequency (%)
개인 7269
72.7%
법인 2731
 
27.3%

Length

2024-05-11T15:52:34.996468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:52:35.120534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 7269
72.7%
법인 2731
 
27.3%
Distinct5748
Distinct (%)88.4%
Missing3499
Missing (%)35.0%
Memory size156.2 KiB
2024-05-11T15:52:35.400488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length37
Mean length10.599754
Min length1

Characters and Unicode

Total characters68909
Distinct characters41
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5133 ?
Unique (%)79.0%

Sample

1st row02-6455-1511
2nd row02-941-0209
3rd row0234861008
4th row02-6091-1007
5th row070-8161-5000
ValueCountFrequency (%)
02 300
 
4.1%
52
 
0.7%
070 41
 
0.6%
010 12
 
0.2%
0 6
 
0.1%
1688 6
 
0.1%
02-563-1486 6
 
0.1%
02-737-2882 5
 
0.1%
02-889-1765 5
 
0.1%
0236745525 5
 
0.1%
Other values (6069) 6907
94.0%
2024-05-11T15:52:35.918448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11291
16.4%
2 10045
14.6%
- 7017
10.2%
5 5754
8.4%
7 5455
7.9%
1 5049
7.3%
6 4898
7.1%
3 4884
7.1%
4 4683
6.8%
8 4652
6.8%
Other values (31) 5181
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60680
88.1%
Dash Punctuation 7017
 
10.2%
Space Separator 935
 
1.4%
Other Punctuation 135
 
0.2%
Close Punctuation 67
 
0.1%
Open Punctuation 25
 
< 0.1%
Math Symbol 25
 
< 0.1%
Other Letter 23
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
 
8.7%
2
 
8.7%
2
 
8.7%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
Other values (10) 10
43.5%
Decimal Number
ValueCountFrequency (%)
0 11291
18.6%
2 10045
16.6%
5 5754
9.5%
7 5455
9.0%
1 5049
8.3%
6 4898
8.1%
3 4884
8.0%
4 4683
7.7%
8 4652
7.7%
9 3969
 
6.5%
Other Punctuation
ValueCountFrequency (%)
* 77
57.0%
/ 38
28.1%
. 20
 
14.8%
Math Symbol
ValueCountFrequency (%)
~ 24
96.0%
× 1
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 7017
100.0%
Space Separator
ValueCountFrequency (%)
935
100.0%
Close Punctuation
ValueCountFrequency (%)
) 67
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 68884
> 99.9%
Hangul 23
 
< 0.1%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2
 
8.7%
2
 
8.7%
2
 
8.7%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
Other values (10) 10
43.5%
Common
ValueCountFrequency (%)
0 11291
16.4%
2 10045
14.6%
- 7017
10.2%
5 5754
8.4%
7 5455
7.9%
1 5049
7.3%
6 4898
7.1%
3 4884
7.1%
4 4683
6.8%
8 4652
6.8%
Other values (9) 5156
7.5%
Latin
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 68885
> 99.9%
Hangul 23
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11291
16.4%
2 10045
14.6%
- 7017
10.2%
5 5754
8.4%
7 5455
7.9%
1 5049
7.3%
6 4898
7.1%
3 4884
7.1%
4 4683
6.8%
8 4652
6.8%
Other values (10) 5157
7.5%
Hangul
ValueCountFrequency (%)
2
 
8.7%
2
 
8.7%
2
 
8.7%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
Other values (10) 10
43.5%
None
ValueCountFrequency (%)
× 1
100.0%

소재지
Text

MISSING 

Distinct8630
Distinct (%)89.0%
Missing298
Missing (%)3.0%
Memory size156.2 KiB
2024-05-11T15:52:36.375145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length50
Mean length31.448773
Min length15

Characters and Unicode

Total characters305116
Distinct characters621
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7871 ?
Unique (%)81.1%

Sample

1st row서울특별시 도봉구 창동 10번지 점보빌딩-508
2nd row서울특별시 강서구 방화동 830번지 2호 하이포트
3rd row서울특별시 성북구 보문동7가 22번지 5호 -511
4th row서울특별시 강남구 논현동 42번지 9호 광림빌딩
5th row서울특별시 서초구 서초동 1588-7 석탑오피스텔 609호
ValueCountFrequency (%)
서울특별시 9698
 
17.0%
강남구 1643
 
2.9%
서초구 954
 
1.7%
1호 744
 
1.3%
역삼동 735
 
1.3%
송파구 596
 
1.0%
서초동 577
 
1.0%
중구 540
 
0.9%
2호 474
 
0.8%
영등포구 462
 
0.8%
Other values (9491) 40756
71.3%
2024-05-11T15:52:36.996676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
67721
22.2%
1 13510
 
4.4%
12065
 
4.0%
11099
 
3.6%
10475
 
3.4%
9960
 
3.3%
9753
 
3.2%
9706
 
3.2%
9699
 
3.2%
2 8825
 
2.9%
Other values (611) 142303
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 166824
54.7%
Space Separator 67721
22.2%
Decimal Number 63343
 
20.8%
Dash Punctuation 5462
 
1.8%
Uppercase Letter 1144
 
0.4%
Other Punctuation 228
 
0.1%
Lowercase Letter 143
 
< 0.1%
Close Punctuation 110
 
< 0.1%
Open Punctuation 106
 
< 0.1%
Letter Number 30
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12065
 
7.2%
11099
 
6.7%
10475
 
6.3%
9960
 
6.0%
9753
 
5.8%
9706
 
5.8%
9699
 
5.8%
8567
 
5.1%
8463
 
5.1%
7942
 
4.8%
Other values (540) 69095
41.4%
Uppercase Letter
ValueCountFrequency (%)
B 242
21.2%
A 218
19.1%
S 75
 
6.6%
D 74
 
6.5%
C 62
 
5.4%
T 58
 
5.1%
K 57
 
5.0%
I 49
 
4.3%
E 36
 
3.1%
L 35
 
3.1%
Other values (16) 238
20.8%
Lowercase Letter
ValueCountFrequency (%)
e 23
16.1%
i 19
13.3%
n 13
9.1%
t 10
 
7.0%
r 10
 
7.0%
l 10
 
7.0%
s 8
 
5.6%
c 6
 
4.2%
a 6
 
4.2%
o 6
 
4.2%
Other values (11) 32
22.4%
Decimal Number
ValueCountFrequency (%)
1 13510
21.3%
2 8825
13.9%
0 8011
12.6%
3 7013
11.1%
4 5744
9.1%
5 4892
 
7.7%
6 4647
 
7.3%
7 4050
 
6.4%
9 3350
 
5.3%
8 3301
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 84
36.8%
/ 79
34.6%
. 61
26.8%
@ 2
 
0.9%
& 1
 
0.4%
1
 
0.4%
Letter Number
ValueCountFrequency (%)
21
70.0%
7
 
23.3%
2
 
6.7%
Space Separator
ValueCountFrequency (%)
67721
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5462
100.0%
Close Punctuation
ValueCountFrequency (%)
) 110
100.0%
Open Punctuation
ValueCountFrequency (%)
( 106
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 166823
54.7%
Common 136975
44.9%
Latin 1317
 
0.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12065
 
7.2%
11099
 
6.7%
10475
 
6.3%
9960
 
6.0%
9753
 
5.8%
9706
 
5.8%
9699
 
5.8%
8567
 
5.1%
8463
 
5.1%
7942
 
4.8%
Other values (539) 69094
41.4%
Latin
ValueCountFrequency (%)
B 242
18.4%
A 218
16.6%
S 75
 
5.7%
D 74
 
5.6%
C 62
 
4.7%
T 58
 
4.4%
K 57
 
4.3%
I 49
 
3.7%
E 36
 
2.7%
L 35
 
2.7%
Other values (40) 411
31.2%
Common
ValueCountFrequency (%)
67721
49.4%
1 13510
 
9.9%
2 8825
 
6.4%
0 8011
 
5.8%
3 7013
 
5.1%
4 5744
 
4.2%
- 5462
 
4.0%
5 4892
 
3.6%
6 4647
 
3.4%
7 4050
 
3.0%
Other values (11) 7100
 
5.2%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 166823
54.7%
ASCII 138261
45.3%
Number Forms 30
 
< 0.1%
CJK 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
67721
49.0%
1 13510
 
9.8%
2 8825
 
6.4%
0 8011
 
5.8%
3 7013
 
5.1%
4 5744
 
4.2%
- 5462
 
4.0%
5 4892
 
3.5%
6 4647
 
3.4%
7 4050
 
2.9%
Other values (57) 8386
 
6.1%
Hangul
ValueCountFrequency (%)
12065
 
7.2%
11099
 
6.7%
10475
 
6.3%
9960
 
6.0%
9753
 
5.8%
9706
 
5.8%
9699
 
5.8%
8567
 
5.1%
8463
 
5.1%
7942
 
4.8%
Other values (539) 69094
41.4%
Number Forms
ValueCountFrequency (%)
21
70.0%
7
 
23.3%
2
 
6.7%
CJK
ValueCountFrequency (%)
1
100.0%
None
ValueCountFrequency (%)
1
100.0%

소재지(도로명)
Text

MISSING 

Distinct4768
Distinct (%)91.3%
Missing4778
Missing (%)47.8%
Memory size156.2 KiB
2024-05-11T15:52:37.375762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length54
Mean length37.171773
Min length22

Characters and Unicode

Total characters194111
Distinct characters616
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4366 ?
Unique (%)83.6%

Sample

1st row서울특별시 강서구 금낭화로 128, 하이포트 601호 (방화동)
2nd row서울특별시 성북구 보문로 58-1, 511호 (보문동7가, 한주빌딩)
3rd row서울특별시 강남구 강남대로132길 55, 5층 (논현동, 광림빌딩)
4th row서울특별시 성동구 용답중앙15길 19-7, 2층 (용답동)
5th row서울특별시 영등포구 당산로41길 11, 당산 SK V1 center E동 1405호-B2호 (당산동4가)
ValueCountFrequency (%)
서울특별시 5220
 
14.1%
강남구 973
 
2.6%
서초구 596
 
1.6%
2층 475
 
1.3%
역삼동 425
 
1.1%
서초동 385
 
1.0%
3층 371
 
1.0%
영등포구 322
 
0.9%
4층 321
 
0.9%
송파구 309
 
0.8%
Other values (6604) 27592
74.6%
2024-05-11T15:52:37.922160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31781
 
16.4%
1 7483
 
3.9%
, 7127
 
3.7%
6935
 
3.6%
6729
 
3.5%
5812
 
3.0%
5715
 
2.9%
5413
 
2.8%
2 5328
 
2.7%
) 5268
 
2.7%
Other values (606) 106520
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 108016
55.6%
Decimal Number 34509
 
17.8%
Space Separator 31781
 
16.4%
Other Punctuation 7142
 
3.7%
Close Punctuation 5268
 
2.7%
Open Punctuation 5267
 
2.7%
Dash Punctuation 1060
 
0.5%
Uppercase Letter 876
 
0.5%
Lowercase Letter 147
 
0.1%
Letter Number 36
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6935
 
6.4%
6729
 
6.2%
5812
 
5.4%
5715
 
5.3%
5413
 
5.0%
5265
 
4.9%
5231
 
4.8%
5221
 
4.8%
4244
 
3.9%
2738
 
2.5%
Other values (533) 54713
50.7%
Uppercase Letter
ValueCountFrequency (%)
B 151
17.2%
A 112
12.8%
S 73
 
8.3%
C 63
 
7.2%
T 55
 
6.3%
K 44
 
5.0%
E 40
 
4.6%
I 38
 
4.3%
L 35
 
4.0%
D 32
 
3.7%
Other values (16) 233
26.6%
Lowercase Letter
ValueCountFrequency (%)
e 22
15.0%
i 16
10.9%
n 15
10.2%
r 13
8.8%
t 12
8.2%
c 9
 
6.1%
o 9
 
6.1%
l 8
 
5.4%
w 8
 
5.4%
a 6
 
4.1%
Other values (11) 29
19.7%
Decimal Number
ValueCountFrequency (%)
1 7483
21.7%
2 5328
15.4%
0 4459
12.9%
3 4032
11.7%
4 2905
 
8.4%
5 2768
 
8.0%
6 2258
 
6.5%
7 1925
 
5.6%
8 1768
 
5.1%
9 1583
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 7127
99.8%
. 8
 
0.1%
/ 3
 
< 0.1%
@ 2
 
< 0.1%
& 1
 
< 0.1%
1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
23
63.9%
9
 
25.0%
4
 
11.1%
Math Symbol
ValueCountFrequency (%)
~ 7
77.8%
< 1
 
11.1%
> 1
 
11.1%
Space Separator
ValueCountFrequency (%)
31781
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5268
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5267
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1060
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 108016
55.6%
Common 85036
43.8%
Latin 1059
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6935
 
6.4%
6729
 
6.2%
5812
 
5.4%
5715
 
5.3%
5413
 
5.0%
5265
 
4.9%
5231
 
4.8%
5221
 
4.8%
4244
 
3.9%
2738
 
2.5%
Other values (533) 54713
50.7%
Latin
ValueCountFrequency (%)
B 151
 
14.3%
A 112
 
10.6%
S 73
 
6.9%
C 63
 
5.9%
T 55
 
5.2%
K 44
 
4.2%
E 40
 
3.8%
I 38
 
3.6%
L 35
 
3.3%
D 32
 
3.0%
Other values (40) 416
39.3%
Common
ValueCountFrequency (%)
31781
37.4%
1 7483
 
8.8%
, 7127
 
8.4%
2 5328
 
6.3%
) 5268
 
6.2%
( 5267
 
6.2%
0 4459
 
5.2%
3 4032
 
4.7%
4 2905
 
3.4%
5 2768
 
3.3%
Other values (13) 8618
 
10.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 108016
55.6%
ASCII 86058
44.3%
Number Forms 36
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31781
36.9%
1 7483
 
8.7%
, 7127
 
8.3%
2 5328
 
6.2%
) 5268
 
6.1%
( 5267
 
6.1%
0 4459
 
5.2%
3 4032
 
4.7%
4 2905
 
3.4%
5 2768
 
3.2%
Other values (59) 9640
 
11.2%
Hangul
ValueCountFrequency (%)
6935
 
6.4%
6729
 
6.2%
5812
 
5.4%
5715
 
5.3%
5413
 
5.0%
5265
 
4.9%
5231
 
4.8%
5221
 
4.8%
4244
 
3.9%
2738
 
2.5%
Other values (533) 54713
50.7%
Number Forms
ValueCountFrequency (%)
23
63.9%
9
 
25.0%
4
 
11.1%
None
ValueCountFrequency (%)
1
100.0%

우편번호
Real number (ℝ)

MISSING 

Distinct1367
Distinct (%)31.3%
Missing5627
Missing (%)56.3%
Infinite0
Infinite (%)0.0%
Mean136440.18
Minimum4526
Maximum410380
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:52:38.112739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4526
5-th percentile100876
Q1132040
median136721
Q3143190
95-th percentile157031
Maximum410380
Range405854
Interquartile range (IQR)11150

Descriptive statistics

Standard deviation15361.568
Coefficient of variation (CV)0.1125883
Kurtosis49.28929
Mean136440.18
Median Absolute Deviation (MAD)5379
Skewness1.3032659
Sum5.9665292 × 108
Variance2.3597778 × 108
MonotonicityNot monotonic
2024-05-11T15:52:38.259043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
135080 163
 
1.6%
137070 140
 
1.4%
135010 68
 
0.7%
157010 55
 
0.5%
151015 51
 
0.5%
142070 50
 
0.5%
152050 49
 
0.5%
151050 48
 
0.5%
139200 45
 
0.4%
158070 43
 
0.4%
Other values (1357) 3661
36.6%
(Missing) 5627
56.3%
ValueCountFrequency (%)
4526 1
 
< 0.1%
4534 1
 
< 0.1%
4554 1
 
< 0.1%
7238 1
 
< 0.1%
14538 1
 
< 0.1%
100011 8
0.1%
100012 2
 
< 0.1%
100013 3
 
< 0.1%
100014 1
 
< 0.1%
100015 2
 
< 0.1%
ValueCountFrequency (%)
410380 1
 
< 0.1%
403866 1
 
< 0.1%
158864 3
< 0.1%
158863 1
 
< 0.1%
158860 4
< 0.1%
158859 3
< 0.1%
158858 1
 
< 0.1%
158856 1
 
< 0.1%
158845 1
 
< 0.1%
158838 2
< 0.1%

등록일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3532
Distinct (%)35.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20137138
Minimum20030519
Maximum20240510
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:52:38.420468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030519
5-th percentile20070827
Q120091207
median20130319
Q320170825
95-th percentile20230220
Maximum20240510
Range209991
Interquartile range (IQR)79618

Descriptive statistics

Standard deviation49093.951
Coefficient of variation (CV)0.0024379806
Kurtosis-0.92728655
Mean20137138
Median Absolute Deviation (MAD)39600.5
Skewness0.45436599
Sum2.0137138 × 1011
Variance2.4102161 × 109
MonotonicityNot monotonic
2024-05-11T15:52:38.612793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20080814 30
 
0.3%
20080731 23
 
0.2%
20080818 21
 
0.2%
20080926 20
 
0.2%
20090520 18
 
0.2%
20090213 16
 
0.2%
20081222 16
 
0.2%
20080806 15
 
0.1%
20090611 15
 
0.1%
20090514 15
 
0.1%
Other values (3522) 9811
98.1%
ValueCountFrequency (%)
20030519 1
< 0.1%
20060127 1
< 0.1%
20060306 1
< 0.1%
20060308 1
< 0.1%
20060310 1
< 0.1%
20060320 2
< 0.1%
20060321 1
< 0.1%
20060323 2
< 0.1%
20060324 1
< 0.1%
20060331 1
< 0.1%
ValueCountFrequency (%)
20240510 1
 
< 0.1%
20240507 1
 
< 0.1%
20240503 4
< 0.1%
20240430 3
< 0.1%
20240429 2
 
< 0.1%
20240425 5
0.1%
20240424 1
 
< 0.1%
20240423 1
 
< 0.1%
20240422 3
< 0.1%
20240419 1
 
< 0.1%

유효기간만료일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3269
Distinct (%)41.1%
Missing2040
Missing (%)20.4%
Infinite0
Infinite (%)0.0%
Mean20181675
Minimum20100117
Maximum20270510
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:52:39.131820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100117
5-th percentile20120402
Q120141014
median20180112
Q320220321
95-th percentile20260508
Maximum20270510
Range170393
Interquartile range (IQR)79306.75

Descriptive statistics

Standard deviation44719.61
Coefficient of variation (CV)0.0022158523
Kurtosis-1.0148782
Mean20181675
Median Absolute Deviation (MAD)39203
Skewness0.31917742
Sum1.6064613 × 1011
Variance1.9998435 × 109
MonotonicityNot monotonic
2024-05-11T15:52:39.301754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110831 20
 
0.2%
20230707 14
 
0.1%
20140711 13
 
0.1%
20140808 11
 
0.1%
20150531 11
 
0.1%
20190718 11
 
0.1%
20120520 11
 
0.1%
20140831 11
 
0.1%
20131102 10
 
0.1%
20140905 10
 
0.1%
Other values (3259) 7838
78.4%
(Missing) 2040
 
20.4%
ValueCountFrequency (%)
20100117 1
 
< 0.1%
20100418 2
< 0.1%
20100419 1
 
< 0.1%
20100426 1
 
< 0.1%
20100613 1
 
< 0.1%
20100627 2
< 0.1%
20100711 1
 
< 0.1%
20100827 3
< 0.1%
20100830 2
< 0.1%
20100905 1
 
< 0.1%
ValueCountFrequency (%)
20270510 1
 
< 0.1%
20270507 1
 
< 0.1%
20270503 4
< 0.1%
20270430 3
< 0.1%
20270429 2
 
< 0.1%
20270425 5
0.1%
20270424 1
 
< 0.1%
20270423 1
 
< 0.1%
20270422 3
< 0.1%
20270419 1
 
< 0.1%

폐쇄일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3117
Distinct (%)37.2%
Missing1614
Missing (%)16.1%
Infinite0
Infinite (%)0.0%
Mean20142164
Minimum20050517
Maximum20240510
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:52:39.464213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20050517
5-th percentile20090910
Q120110408
median20130724
Q320170419
95-th percentile20221012
Maximum20240510
Range189993
Interquartile range (IQR)60011

Descriptive statistics

Standard deviation41029.868
Coefficient of variation (CV)0.0020370139
Kurtosis-0.55994369
Mean20142164
Median Absolute Deviation (MAD)29796.5
Skewness0.69004423
Sum1.6891219 × 1011
Variance1.6834501 × 109
MonotonicityNot monotonic
2024-05-11T15:52:39.695210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091116 188
 
1.9%
20100927 83
 
0.8%
20101213 23
 
0.2%
20160725 21
 
0.2%
20170124 20
 
0.2%
20110420 17
 
0.2%
20110425 17
 
0.2%
20170126 17
 
0.2%
20170125 15
 
0.1%
20100726 14
 
0.1%
Other values (3107) 7971
79.7%
(Missing) 1614
 
16.1%
ValueCountFrequency (%)
20050517 1
< 0.1%
20060920 1
< 0.1%
20071115 1
< 0.1%
20080730 1
< 0.1%
20081212 1
< 0.1%
20090128 1
< 0.1%
20090211 1
< 0.1%
20090219 1
< 0.1%
20090306 1
< 0.1%
20090307 1
< 0.1%
ValueCountFrequency (%)
20240510 2
< 0.1%
20240509 1
 
< 0.1%
20240508 1
 
< 0.1%
20240507 2
< 0.1%
20240503 3
< 0.1%
20240502 1
 
< 0.1%
20240501 4
< 0.1%
20240430 2
< 0.1%
20240426 1
 
< 0.1%
20240425 1
 
< 0.1%

지점설립일자
Date

MISSING 

Distinct3562
Distinct (%)40.6%
Missing1236
Missing (%)12.4%
Memory size156.2 KiB
Minimum1905-06-27 00:00:00
Maximum2024-05-02 00:00:00
2024-05-11T15:52:39.898617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:52:40.110528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

본점여부
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
본점
9923 
지점
 
77

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
본점 9923
99.2%
지점 77
 
0.8%

Length

2024-05-11T15:52:40.284176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:52:40.405499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
본점 9923
99.2%
지점 77
 
0.8%

최근수정일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3161
Distinct (%)31.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20153329
Minimum20090518
Maximum20240510
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:52:40.590059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090518
5-th percentile20091118
Q120111017
median20140818
Q320190508
95-th percentile20231024
Maximum20240510
Range149992
Interquartile range (IQR)79491.5

Descriptive statistics

Standard deviation46135.731
Coefficient of variation (CV)0.0022892362
Kurtosis-1.0786522
Mean20153329
Median Absolute Deviation (MAD)30505.5
Skewness0.44124383
Sum2.0153329 × 1011
Variance2.1285057 × 109
MonotonicityNot monotonic
2024-05-11T15:52:40.790970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091117 77
 
0.8%
20100927 54
 
0.5%
20090609 44
 
0.4%
20091118 43
 
0.4%
20110425 39
 
0.4%
20091116 36
 
0.4%
20130621 36
 
0.4%
20090622 34
 
0.3%
20091119 33
 
0.3%
20100330 33
 
0.3%
Other values (3151) 9571
95.7%
ValueCountFrequency (%)
20090518 2
 
< 0.1%
20090519 2
 
< 0.1%
20090521 4
 
< 0.1%
20090601 2
 
< 0.1%
20090603 3
 
< 0.1%
20090604 19
0.2%
20090605 3
 
< 0.1%
20090608 7
 
0.1%
20090609 44
0.4%
20090610 23
0.2%
ValueCountFrequency (%)
20240510 3
 
< 0.1%
20240509 6
0.1%
20240508 6
0.1%
20240507 4
 
< 0.1%
20240503 14
0.1%
20240502 6
0.1%
20240501 5
 
0.1%
20240430 6
0.1%
20240429 4
 
< 0.1%
20240426 1
 
< 0.1%

Interactions

2024-05-11T15:52:30.322474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:52:26.877936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:52:27.767992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:52:28.465374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:52:29.476552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:52:30.470350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:52:27.045284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:52:27.920479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:52:28.626611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:52:29.673290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:52:30.605015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:52:27.201034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:52:28.034068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:52:28.952001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:52:29.836176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:52:30.745112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:52:27.393612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:52:28.174487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:52:29.123825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:52:30.016177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:52:30.912784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:52:27.578288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:52:28.332667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:52:29.291517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:52:30.165229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T15:52:40.969832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록신청사업영업구분법인여부우편번호등록일자유효기간만료일자폐쇄일자본점여부최근수정일자
등록신청사업1.0000.0890.0190.0000.1600.1350.1810.0000.148
영업구분0.0891.0000.2860.0340.6300.6120.1990.0710.540
법인여부0.0190.2861.0000.0000.2650.2850.2580.2020.348
우편번호0.0000.0340.0001.0000.2350.2350.1870.0000.235
등록일자0.1600.6300.2650.2351.0000.9350.8630.0760.855
유효기간만료일자0.1350.6120.2850.2350.9351.0000.8360.1000.928
폐쇄일자0.1810.1990.2580.1870.8630.8361.0000.0490.984
본점여부0.0000.0710.2020.0000.0760.1000.0491.0000.125
최근수정일자0.1480.5400.3480.2350.8550.9280.9840.1251.000
2024-05-11T15:52:41.140176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
본점여부등록신청사업법인여부영업구분
본점여부1.0000.0000.1290.051
등록신청사업0.0001.0000.0120.064
법인여부0.1290.0121.0000.206
영업구분0.0510.0640.2061.000
2024-05-11T15:52:41.300688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호등록일자유효기간만료일자폐쇄일자최근수정일자등록신청사업영업구분법인여부본점여부
우편번호1.000-0.005-0.0050.002-0.0100.0000.0560.0000.000
등록일자-0.0051.0000.9970.9620.9660.1600.3740.2640.075
유효기간만료일자-0.0050.9971.0000.9640.9660.1030.3790.2190.077
폐쇄일자0.0020.9620.9641.0000.9920.1390.1160.1970.037
최근수정일자-0.0100.9660.9660.9921.0000.1130.3030.2670.095
등록신청사업0.0000.1600.1030.1390.1131.0000.0640.0120.000
영업구분0.0560.3740.3790.1160.3030.0641.0000.2060.051
법인여부0.0000.2640.2190.1970.2670.0120.2061.0000.129
본점여부0.0000.0750.0770.0370.0950.0000.0510.1291.000

Missing values

2024-05-11T15:52:31.150996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T15:52:31.504432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-05-11T15:52:31.750149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

등록신청사업영업구분등록증번호상호법인여부사업장 전화번호소재지소재지(도로명)우편번호등록일자유효기간만료일자폐쇄일자지점설립일자본점여부최근수정일자
21103대부중개업폐업2011-서울도봉-0022(대부중개업)하이파이낸스대부중개개인<NA>서울특별시 도봉구 창동 10번지 점보빌딩-508<NA>13204020110316201403162012072320110316본점20120723
6771대부업유효기간만료2019-서울강서-0006(대부업)(주)신밧드월드대부법인02-6455-1511서울특별시 강서구 방화동 830번지 2호 하이포트서울특별시 강서구 금낭화로 128, 하이포트 601호 (방화동)<NA>2017033020200330<NA>20170330본점20200408
9462대부업유효기간만료2012-서울특별시 성북구-00014대부신안금융개인02-941-0209서울특별시 성북구 보문동7가 22번지 5호 -511서울특별시 성북구 보문로 58-1, 511호 (보문동7가, 한주빌딩)<NA>2015013020180130<NA><NA>본점20180131
13048대부업폐업2013-서울강남-0340핑크 뱅 대부개인<NA>서울특별시 강남구 논현동 42번지 9호 광림빌딩서울특별시 강남구 강남대로132길 55, 5층 (논현동, 광림빌딩)13581520131202201612022016042620131202본점20160426
30832<NA><NA>2008-서울특별시-01083하나에셋투자금융개인0234861008서울특별시 서초구 서초동 1588-7 석탑오피스텔 609호<NA>13707020080117<NA>2009052820080110본점20090622
16775대부중개업폐업2011-서울영등포-0269(대부중개업)주식회사 채권추심전문 엘씨대부법인02-6091-1007서울특별시 영등포구 여의도동 14번지 14호 용산빌딩 12층<NA>15087120111122201411222014020420111122본점20140204
27959대부업<NA>2009-서울특별시-00824(대부업)주식회사 타우자산법인<NA>서울특별시 강남구 논현동 116-5번지 7층<NA><NA>20090520<NA>2010052720090520본점20100528
13062대부중개업타시군구이관2013-서울성동-0014(주)마이퍼스트대부중개법인070-8161-5000서울특별시 성동구 용답동 61번지 1호 2층서울특별시 성동구 용답중앙15길 19-7, 2층 (용답동)13384820160313201903202016042220130313본점20160422
18716대부중개업직권취소2011-서울영등포-0179(대부중개업)주식회사 다산플러스대부중개법인02-3439-0121서울특별시 영등포구 문래동3가 55번지 20호 1 에이스하이테크시티-207<NA>15097220110530201405302013052920110530본점20130529
2898대부업폐업2021-서울영등포-2152(대부업)토탈금융대부개인<NA>서울특별시 영등포구 당산동4가 80번지 당산 SK V1 center서울특별시 영등포구 당산로41길 11, 당산 SK V1 center E동 1405호-B2호 (당산동4가)<NA>20211025202410252023040320211025본점20230403
등록신청사업영업구분등록증번호상호법인여부사업장 전화번호소재지소재지(도로명)우편번호등록일자유효기간만료일자폐쇄일자지점설립일자본점여부최근수정일자
27652대부업<NA>2009-서울특별시-01103(대부업)한진캐피탈개인0226051993서울특별시 양천구 목동 805번지 17호 201호<NA>15805020090416<NA>2010071220090416본점20100712
9947대부업폐업2016-서울광진-0013(대부업)좋은이웃대부개인02-467-4200서울특별시 광진구 중곡동 193번지 35호서울특별시 광진구 긴고랑로9길 43, 4층 (중곡동)<NA>20160225201902252017110820160225본점20171108
26481대부중개업<NA>2008-서울특별시-02485(대부중개업)S.H투자금융대부개인0222748888서울특별시 강남구 논현동 18번지 3호 영창빌딩801호<NA>13501020080922<NA>20101026<NA>본점20101104
27794대부중개업<NA>2009-서울특별시-01229(대부중개업)부흥투자개인<NA>서울특별시 강남구 대치동 633 청실아파트 9동 206호<NA><NA>20090128<NA>20100622<NA>본점20100622
8378대부업타시군구이관2018-서울강남-0119(대부업)부동산담보대출대부개인02-542-1118서울특별시 강남구 대치동 890번지 54호 선릉역 풍림아이원레몬-1011a서울특별시 강남구 테헤란로64길 13, 10층 1011a호 (대치동, 선릉역 풍림아이원레몬)<NA>20180726202107262018111420180726본점20181114
14859대부업폐업2013-서울강서-00033(대부업)대부서진기획개인02 2665 1113서울특별시 강서구 화곡동 1111번지 3호 경동엠파이어스테이트-1209서울특별시 강서구 화곡로 344, 1209호 (화곡동, 경동엠파이어스테이트)15701620130617201606172015022520130617본점20150225
25860대부중개업<NA>2009-서울특별시-02326(대부중개업)L&A대부중개개인027777654서울특별시 서대문구 홍은동 455번지 벽산아파트 107-702호<NA><NA>20090929<NA>2011011820090929본점20110119
2700대부업폐업2022-서울노원-0004(대부업)에이이대부개인02-930-7854서울특별시 노원구 상계동 387번지 64호 창현빌딩서울특별시 노원구 상계로 140, 창현빌딩 401호 (상계동)<NA>20220411202504112023050820220411본점20230508
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