Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells19295
Missing cells (%)12.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 MiB
Average record size in memory133.0 B

Variable types

Categorical4
Text5
Numeric6

Dataset

Description등록신청사업,영업구분,등록증번호,상호,법인여부,사업장 전화번호,소재지,소재지(도로명),우편번호,등록일자,유효기간만료일자,폐쇄일자,지점설립일자,본점여부,최근수정일자
Author금천구
URLhttps://data.seoul.go.kr/dataList/OA-10173/S/1/datasetView.do

Alerts

등록일자 is highly overall correlated with 유효기간만료일자 and 3 other fieldsHigh correlation
유효기간만료일자 is highly overall correlated with 등록일자 and 3 other fieldsHigh correlation
폐쇄일자 is highly overall correlated with 등록일자 and 3 other fieldsHigh correlation
지점설립일자 is highly overall correlated with 등록일자 and 3 other fieldsHigh correlation
최근수정일자 is highly overall correlated with 등록일자 and 3 other fieldsHigh correlation
본점여부 is highly imbalanced (94.2%)Imbalance
등록증번호 has 208 (2.1%) missing valuesMissing
사업장 전화번호 has 3380 (33.8%) missing valuesMissing
소재지 has 318 (3.2%) missing valuesMissing
소재지(도로명) has 4801 (48.0%) missing valuesMissing
우편번호 has 5647 (56.5%) missing valuesMissing
유효기간만료일자 has 2111 (21.1%) missing valuesMissing
폐쇄일자 has 1579 (15.8%) missing valuesMissing
지점설립일자 has 1251 (12.5%) missing valuesMissing

Reproduction

Analysis started2024-05-04 03:52:33.660166
Analysis finished2024-05-04 03:54:20.419791
Duration1 minute and 46.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
대부업
6237 
대부중개업
3334 
<NA>
 
429

Length

Max length5
Median length3
Mean length3.7097
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대부중개업
2nd row대부중개업
3rd row대부업
4th row대부중개업
5th row대부업

Common Values

ValueCountFrequency (%)
대부업 6237
62.4%
대부중개업 3334
33.3%
<NA> 429
 
4.3%

Length

2024-05-04T03:54:20.662385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T03:54:21.046872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대부업 6237
62.4%
대부중개업 3334
33.3%
na 429
 
4.3%

영업구분
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
3710 
<NA>
2932 
타시군구이관
1173 
영업중
831 
유효기간만료
799 
Other values (3)
555 

Length

Max length6
Median length4
Mean length3.5697
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3710
37.1%
<NA> 2932
29.3%
타시군구이관 1173
 
11.7%
영업중 831
 
8.3%
유효기간만료 799
 
8.0%
직권취소 551
 
5.5%
갱신등록불가 3
 
< 0.1%
휴업 1
 
< 0.1%

Length

2024-05-04T03:54:21.422567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T03:54:21.791665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3710
37.1%
na 2932
29.3%
타시군구이관 1173
 
11.7%
영업중 831
 
8.3%
유효기간만료 799
 
8.0%
직권취소 551
 
5.5%
갱신등록불가 3
 
< 0.1%
휴업 1
 
< 0.1%

등록증번호
Text

MISSING 

Distinct9740
Distinct (%)99.5%
Missing208
Missing (%)2.1%
Memory size156.2 KiB
2024-05-04T03:54:22.257122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length19.513787
Min length1

Characters and Unicode

Total characters191079
Distinct characters68
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

Unique9690 ?
Unique (%)99.0%

Sample

1st row2014-서울서대문-00007(대부중개업)
2nd row2016-서울송파-0010(대부중개업)
3rd row2007-서울특별시-01551(대부업)
4th row2024-서울서초-0035(대부중개업)
5th row2015-서울서대문-00002(대부업)
ValueCountFrequency (%)
2012-서울특별시 19
 
0.2%
2011-서울특별시 18
 
0.2%
2010-서울 15
 
0.2%
2013-서울특별시 14
 
0.1%
2015-서울특별시 11
 
0.1%
2016-서울특별시 11
 
0.1%
2014-서울특별시 9
 
0.1%
대부업 7
 
0.1%
성북구-00008 6
 
0.1%
성북구-00005 6
 
0.1%
Other values (9698) 9839
98.8%
2024-05-04T03:54:23.021947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 33813
17.7%
- 19569
 
10.2%
2 15640
 
8.2%
1 11802
 
6.2%
10856
 
5.7%
9763
 
5.1%
8452
 
4.4%
( 8166
 
4.3%
8128
 
4.3%
) 8116
 
4.2%
Other values (58) 56774
29.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82409
43.1%
Other Letter 72655
38.0%
Dash Punctuation 19569
 
10.2%
Open Punctuation 8166
 
4.3%
Close Punctuation 8116
 
4.2%
Space Separator 164
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10856
14.9%
9763
13.4%
8452
11.6%
8128
11.2%
7900
10.9%
3453
 
4.8%
2844
 
3.9%
2548
 
3.5%
2538
 
3.5%
2537
 
3.5%
Other values (44) 13636
18.8%
Decimal Number
ValueCountFrequency (%)
0 33813
41.0%
2 15640
19.0%
1 11802
 
14.3%
3 3658
 
4.4%
8 3145
 
3.8%
4 3066
 
3.7%
9 2892
 
3.5%
7 2866
 
3.5%
6 2767
 
3.4%
5 2760
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 19569
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8166
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8116
100.0%
Space Separator
ValueCountFrequency (%)
164
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 118424
62.0%
Hangul 72655
38.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10856
14.9%
9763
13.4%
8452
11.6%
8128
11.2%
7900
10.9%
3453
 
4.8%
2844
 
3.9%
2548
 
3.5%
2538
 
3.5%
2537
 
3.5%
Other values (44) 13636
18.8%
Common
ValueCountFrequency (%)
0 33813
28.6%
- 19569
16.5%
2 15640
13.2%
1 11802
 
10.0%
( 8166
 
6.9%
) 8116
 
6.9%
3 3658
 
3.1%
8 3145
 
2.7%
4 3066
 
2.6%
9 2892
 
2.4%
Other values (4) 8557
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 118424
62.0%
Hangul 72655
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 33813
28.6%
- 19569
16.5%
2 15640
13.2%
1 11802
 
10.0%
( 8166
 
6.9%
) 8116
 
6.9%
3 3658
 
3.1%
8 3145
 
2.7%
4 3066
 
2.6%
9 2892
 
2.4%
Other values (4) 8557
 
7.2%
Hangul
ValueCountFrequency (%)
10856
14.9%
9763
13.4%
8452
11.6%
8128
11.2%
7900
10.9%
3453
 
4.8%
2844
 
3.9%
2548
 
3.5%
2538
 
3.5%
2537
 
3.5%
Other values (44) 13636
18.8%

상호
Text

Distinct8696
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T03:54:23.502210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length22
Mean length7.6973
Min length1

Characters and Unicode

Total characters76973
Distinct characters780
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

Unique7634 ?
Unique (%)76.3%

Sample

1st row이루 대부 중개
2nd rowOK더드림대부
3rd row진솔함
4th row주식회사 어니스티자산관리대부
5th row홍은사 전당포대부
ValueCountFrequency (%)
주식회사 813
 
6.8%
대부중개 324
 
2.7%
대부 297
 
2.5%
유한회사 55
 
0.5%
캐피탈 23
 
0.2%
대부업 17
 
0.1%
money 16
 
0.1%
loan 12
 
0.1%
the 12
 
0.1%
capital 11
 
0.1%
Other values (8729) 10367
86.8%
2024-05-04T03:54:24.267083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8439
 
11.0%
8075
 
10.5%
2640
 
3.4%
2210
 
2.9%
2113
 
2.7%
2091
 
2.7%
1951
 
2.5%
1892
 
2.5%
) 1837
 
2.4%
( 1827
 
2.4%
Other values (770) 43898
57.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67131
87.2%
Uppercase Letter 2406
 
3.1%
Space Separator 1951
 
2.5%
Close Punctuation 1837
 
2.4%
Open Punctuation 1827
 
2.4%
Lowercase Letter 1261
 
1.6%
Decimal Number 261
 
0.3%
Other Punctuation 253
 
0.3%
Dash Punctuation 31
 
< 0.1%
Other Symbol 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8439
 
12.6%
8075
 
12.0%
2640
 
3.9%
2210
 
3.3%
2113
 
3.1%
2091
 
3.1%
1892
 
2.8%
1320
 
2.0%
1105
 
1.6%
1016
 
1.5%
Other values (695) 36230
54.0%
Uppercase Letter
ValueCountFrequency (%)
S 300
 
12.5%
K 219
 
9.1%
M 192
 
8.0%
J 183
 
7.6%
C 181
 
7.5%
H 138
 
5.7%
B 105
 
4.4%
G 100
 
4.2%
T 98
 
4.1%
O 95
 
3.9%
Other values (16) 795
33.0%
Lowercase Letter
ValueCountFrequency (%)
e 160
12.7%
n 134
10.6%
o 124
 
9.8%
a 114
 
9.0%
s 86
 
6.8%
i 76
 
6.0%
t 74
 
5.9%
l 62
 
4.9%
c 60
 
4.8%
r 56
 
4.4%
Other values (15) 315
25.0%
Decimal Number
ValueCountFrequency (%)
1 84
32.2%
2 44
16.9%
4 34
13.0%
3 23
 
8.8%
9 21
 
8.0%
5 21
 
8.0%
6 14
 
5.4%
0 10
 
3.8%
7 5
 
1.9%
8 5
 
1.9%
Other Punctuation
ValueCountFrequency (%)
. 127
50.2%
& 112
44.3%
? 8
 
3.2%
, 2
 
0.8%
1
 
0.4%
/ 1
 
0.4%
@ 1
 
0.4%
* 1
 
0.4%
Space Separator
ValueCountFrequency (%)
1951
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1837
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1827
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Other Symbol
ValueCountFrequency (%)
13
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67130
87.2%
Common 6162
 
8.0%
Latin 3667
 
4.8%
Han 14
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8439
 
12.6%
8075
 
12.0%
2640
 
3.9%
2210
 
3.3%
2113
 
3.1%
2091
 
3.1%
1892
 
2.8%
1320
 
2.0%
1105
 
1.6%
1016
 
1.5%
Other values (682) 36229
54.0%
Latin
ValueCountFrequency (%)
S 300
 
8.2%
K 219
 
6.0%
M 192
 
5.2%
J 183
 
5.0%
C 181
 
4.9%
e 160
 
4.4%
H 138
 
3.8%
n 134
 
3.7%
o 124
 
3.4%
a 114
 
3.1%
Other values (41) 1922
52.4%
Common
ValueCountFrequency (%)
1951
31.7%
) 1837
29.8%
( 1827
29.6%
. 127
 
2.1%
& 112
 
1.8%
1 84
 
1.4%
2 44
 
0.7%
4 34
 
0.6%
- 31
 
0.5%
3 23
 
0.4%
Other values (13) 92
 
1.5%
Han
ValueCountFrequency (%)
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
Other values (4) 4
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67116
87.2%
ASCII 9828
 
12.8%
None 14
 
< 0.1%
CJK 14
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
8439
 
12.6%
8075
 
12.0%
2640
 
3.9%
2210
 
3.3%
2113
 
3.1%
2091
 
3.1%
1892
 
2.8%
1320
 
2.0%
1105
 
1.6%
1016
 
1.5%
Other values (680) 36215
54.0%
ASCII
ValueCountFrequency (%)
1951
19.9%
) 1837
18.7%
( 1827
18.6%
S 300
 
3.1%
K 219
 
2.2%
M 192
 
2.0%
J 183
 
1.9%
C 181
 
1.8%
e 160
 
1.6%
H 138
 
1.4%
Other values (63) 2840
28.9%
None
ValueCountFrequency (%)
13
92.9%
1
 
7.1%
CJK
ValueCountFrequency (%)
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
Other values (4) 4
28.6%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

법인여부
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
개인
7263 
법인
2737 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 7263
72.6%
법인 2737
 
27.4%

Length

2024-05-04T03:54:24.993521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T03:54:25.279819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 7263
72.6%
법인 2737
 
27.4%
Distinct5864
Distinct (%)88.6%
Missing3380
Missing (%)33.8%
Memory size156.2 KiB
2024-05-04T03:54:25.728515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length39
Mean length10.58852
Min length1

Characters and Unicode

Total characters70096
Distinct characters26
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5260 ?
Unique (%)79.5%

Sample

1st row02-722-5379
2nd row02)555-8891
3rd row070-7537-0420
4th row02-3216-6870
5th row025551177
ValueCountFrequency (%)
02 305
 
4.1%
54
 
0.7%
070 39
 
0.5%
010 9
 
0.1%
1688 6
 
0.1%
02-563-1486 5
 
0.1%
2209 5
 
0.1%
495 5
 
0.1%
455 5
 
0.1%
1644 5
 
0.1%
Other values (6183) 7036
94.1%
2024-05-04T03:54:26.565740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11383
16.2%
2 10303
14.7%
- 7118
10.2%
5 5842
8.3%
7 5435
7.8%
6 5189
7.4%
1 5163
7.4%
3 4868
6.9%
8 4841
6.9%
4 4636
6.6%
Other values (16) 5318
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61747
88.1%
Dash Punctuation 7118
 
10.2%
Space Separator 964
 
1.4%
Other Punctuation 132
 
0.2%
Close Punctuation 68
 
0.1%
Open Punctuation 31
 
< 0.1%
Math Symbol 19
 
< 0.1%
Other Letter 14
 
< 0.1%
Uppercase Letter 2
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11383
18.4%
2 10303
16.7%
5 5842
9.5%
7 5435
8.8%
6 5189
8.4%
1 5163
8.4%
3 4868
7.9%
8 4841
7.8%
4 4636
7.5%
9 4087
 
6.6%
Other Letter
ValueCountFrequency (%)
4
28.6%
4
28.6%
4
28.6%
1
 
7.1%
1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
* 67
50.8%
/ 45
34.1%
. 20
 
15.2%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 7118
100.0%
Space Separator
ValueCountFrequency (%)
964
100.0%
Close Punctuation
ValueCountFrequency (%)
) 68
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Math Symbol
ValueCountFrequency (%)
~ 19
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70080
> 99.9%
Hangul 14
 
< 0.1%
Latin 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11383
16.2%
2 10303
14.7%
- 7118
10.2%
5 5842
8.3%
7 5435
7.8%
6 5189
7.4%
1 5163
7.4%
3 4868
6.9%
8 4841
6.9%
4 4636
6.6%
Other values (9) 5302
7.6%
Hangul
ValueCountFrequency (%)
4
28.6%
4
28.6%
4
28.6%
1
 
7.1%
1
 
7.1%
Latin
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70082
> 99.9%
Hangul 14
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11383
16.2%
2 10303
14.7%
- 7118
10.2%
5 5842
8.3%
7 5435
7.8%
6 5189
7.4%
1 5163
7.4%
3 4868
6.9%
8 4841
6.9%
4 4636
6.6%
Other values (11) 5304
7.6%
Hangul
ValueCountFrequency (%)
4
28.6%
4
28.6%
4
28.6%
1
 
7.1%
1
 
7.1%

소재지
Text

MISSING 

Distinct8659
Distinct (%)89.4%
Missing318
Missing (%)3.2%
Memory size156.2 KiB
2024-05-04T03:54:27.232149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length51
Mean length31.513737
Min length15

Characters and Unicode

Total characters305116
Distinct characters616
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

Unique7918 ?
Unique (%)81.8%

Sample

1st row서울특별시 서대문구 홍은동 8번지 31호
2nd row서울특별시 송파구 가락동 99번지 3호 제일오피스텔-1705
3rd row서울특별시 서초구 반포동 728-26 302호
4th row서울특별시 서초구 서초동 1338번지 20호 현대렉시온
5th row서울특별시 서대문구 홍은동 48번지 213호
ValueCountFrequency (%)
서울특별시 9678
 
17.0%
강남구 1549
 
2.7%
서초구 949
 
1.7%
1호 705
 
1.2%
역삼동 702
 
1.2%
송파구 614
 
1.1%
서초동 579
 
1.0%
중구 517
 
0.9%
영등포구 465
 
0.8%
2호 455
 
0.8%
Other values (9487) 40869
71.6%
2024-05-04T03:54:28.129427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
67635
22.2%
1 13603
 
4.5%
12046
 
3.9%
11105
 
3.6%
10485
 
3.4%
9922
 
3.3%
9722
 
3.2%
9685
 
3.2%
9679
 
3.2%
2 8931
 
2.9%
Other values (606) 142303
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 166782
54.7%
Space Separator 67635
22.2%
Decimal Number 63566
 
20.8%
Dash Punctuation 5503
 
1.8%
Uppercase Letter 1076
 
0.4%
Other Punctuation 238
 
0.1%
Lowercase Letter 96
 
< 0.1%
Close Punctuation 95
 
< 0.1%
Open Punctuation 91
 
< 0.1%
Letter Number 27
 
< 0.1%
Other values (2) 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12046
 
7.2%
11105
 
6.7%
10485
 
6.3%
9922
 
5.9%
9722
 
5.8%
9685
 
5.8%
9679
 
5.8%
8599
 
5.2%
8413
 
5.0%
7895
 
4.7%
Other values (534) 69231
41.5%
Uppercase Letter
ValueCountFrequency (%)
B 229
21.3%
A 206
19.1%
S 77
 
7.2%
D 76
 
7.1%
T 51
 
4.7%
C 50
 
4.6%
K 44
 
4.1%
I 42
 
3.9%
L 41
 
3.8%
E 33
 
3.1%
Other values (16) 227
21.1%
Lowercase Letter
ValueCountFrequency (%)
e 19
19.8%
n 13
13.5%
i 11
11.5%
a 8
8.3%
r 7
 
7.3%
c 5
 
5.2%
s 4
 
4.2%
u 4
 
4.2%
l 4
 
4.2%
t 4
 
4.2%
Other values (10) 17
17.7%
Decimal Number
ValueCountFrequency (%)
1 13603
21.4%
2 8931
14.0%
0 8015
12.6%
3 6913
10.9%
4 5793
9.1%
5 4982
 
7.8%
6 4584
 
7.2%
7 4055
 
6.4%
9 3393
 
5.3%
8 3297
 
5.2%
Other Punctuation
ValueCountFrequency (%)
/ 83
34.9%
, 81
34.0%
. 66
27.7%
4
 
1.7%
@ 2
 
0.8%
* 1
 
0.4%
; 1
 
0.4%
Letter Number
ValueCountFrequency (%)
17
63.0%
7
25.9%
3
 
11.1%
Space Separator
ValueCountFrequency (%)
67635
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5503
100.0%
Close Punctuation
ValueCountFrequency (%)
) 95
100.0%
Open Punctuation
ValueCountFrequency (%)
( 91
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%
Other Number
ValueCountFrequency (%)
½ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 166780
54.7%
Common 137135
44.9%
Latin 1199
 
0.4%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12046
 
7.2%
11105
 
6.7%
10485
 
6.3%
9922
 
5.9%
9722
 
5.8%
9685
 
5.8%
9679
 
5.8%
8599
 
5.2%
8413
 
5.0%
7895
 
4.7%
Other values (532) 69229
41.5%
Latin
ValueCountFrequency (%)
B 229
19.1%
A 206
17.2%
S 77
 
6.4%
D 76
 
6.3%
T 51
 
4.3%
C 50
 
4.2%
K 44
 
3.7%
I 42
 
3.5%
L 41
 
3.4%
E 33
 
2.8%
Other values (39) 350
29.2%
Common
ValueCountFrequency (%)
67635
49.3%
1 13603
 
9.9%
2 8931
 
6.5%
0 8015
 
5.8%
3 6913
 
5.0%
4 5793
 
4.2%
- 5503
 
4.0%
5 4982
 
3.6%
6 4584
 
3.3%
7 4055
 
3.0%
Other values (13) 7121
 
5.2%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 166780
54.7%
ASCII 138302
45.3%
Number Forms 27
 
< 0.1%
None 5
 
< 0.1%
CJK 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
67635
48.9%
1 13603
 
9.8%
2 8931
 
6.5%
0 8015
 
5.8%
3 6913
 
5.0%
4 5793
 
4.2%
- 5503
 
4.0%
5 4982
 
3.6%
6 4584
 
3.3%
7 4055
 
2.9%
Other values (57) 8288
 
6.0%
Hangul
ValueCountFrequency (%)
12046
 
7.2%
11105
 
6.7%
10485
 
6.3%
9922
 
5.9%
9722
 
5.8%
9685
 
5.8%
9679
 
5.8%
8599
 
5.2%
8413
 
5.0%
7895
 
4.7%
Other values (532) 69229
41.5%
Number Forms
ValueCountFrequency (%)
17
63.0%
7
25.9%
3
 
11.1%
None
ValueCountFrequency (%)
4
80.0%
½ 1
 
20.0%
CJK
ValueCountFrequency (%)
1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%

소재지(도로명)
Text

MISSING 

Distinct4762
Distinct (%)91.6%
Missing4801
Missing (%)48.0%
Memory size156.2 KiB
2024-05-04T03:54:28.735096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length54
Mean length37.227159
Min length22

Characters and Unicode

Total characters193544
Distinct characters599
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4378 ?
Unique (%)84.2%

Sample

1st row서울특별시 서대문구 홍은중앙로 155, 101호 (홍은동, 이루하이빌)
2nd row서울특별시 송파구 송파대로 260, 1705호 (가락동, 제일오피스텔)
3rd row서울특별시 서초구 강남대로 305, 현대렉시온 11층 1118호 (서초동)
4th row서울특별시 서대문구 세검정로 15 (홍은동)
5th row서울특별시 중구 마장로 3, 맥스타일오피스텔 16층 4호 (신당동)
ValueCountFrequency (%)
서울특별시 5199
 
14.1%
강남구 928
 
2.5%
서초구 575
 
1.6%
2층 481
 
1.3%
역삼동 406
 
1.1%
서초동 381
 
1.0%
3층 373
 
1.0%
영등포구 339
 
0.9%
송파구 324
 
0.9%
4층 312
 
0.8%
Other values (6583) 27474
74.7%
2024-05-04T03:54:29.655496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31618
 
16.3%
1 7476
 
3.9%
, 7128
 
3.7%
6919
 
3.6%
6862
 
3.5%
5740
 
3.0%
5738
 
3.0%
5369
 
2.8%
2 5336
 
2.8%
5241
 
2.7%
Other values (589) 106117
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 107758
55.7%
Decimal Number 34559
 
17.9%
Space Separator 31618
 
16.3%
Other Punctuation 7145
 
3.7%
Close Punctuation 5239
 
2.7%
Open Punctuation 5237
 
2.7%
Dash Punctuation 1052
 
0.5%
Uppercase Letter 800
 
0.4%
Lowercase Letter 98
 
0.1%
Letter Number 28
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6919
 
6.4%
6862
 
6.4%
5740
 
5.3%
5738
 
5.3%
5369
 
5.0%
5241
 
4.9%
5206
 
4.8%
5200
 
4.8%
4270
 
4.0%
2730
 
2.5%
Other values (521) 54483
50.6%
Uppercase Letter
ValueCountFrequency (%)
B 178
22.2%
A 115
14.4%
S 77
9.6%
C 47
 
5.9%
T 44
 
5.5%
E 36
 
4.5%
K 34
 
4.2%
L 33
 
4.1%
I 31
 
3.9%
G 23
 
2.9%
Other values (16) 182
22.8%
Lowercase Letter
ValueCountFrequency (%)
e 19
19.4%
n 13
13.3%
r 10
10.2%
i 9
9.2%
c 7
 
7.1%
w 6
 
6.1%
t 5
 
5.1%
b 4
 
4.1%
o 4
 
4.1%
s 4
 
4.1%
Other values (9) 17
17.3%
Decimal Number
ValueCountFrequency (%)
1 7476
21.6%
2 5336
15.4%
0 4446
12.9%
3 4122
11.9%
4 2894
 
8.4%
5 2727
 
7.9%
6 2238
 
6.5%
7 1977
 
5.7%
8 1841
 
5.3%
9 1502
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 7128
99.8%
. 10
 
0.1%
@ 3
 
< 0.1%
2
 
< 0.1%
? 2
 
< 0.1%
Letter Number
ValueCountFrequency (%)
17
60.7%
8
28.6%
3
 
10.7%
Space Separator
ValueCountFrequency (%)
31618
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5239
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5237
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1052
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 107755
55.7%
Common 84860
43.8%
Latin 926
 
0.5%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6919
 
6.4%
6862
 
6.4%
5740
 
5.3%
5738
 
5.3%
5369
 
5.0%
5241
 
4.9%
5206
 
4.8%
5200
 
4.8%
4270
 
4.0%
2730
 
2.5%
Other values (518) 54480
50.6%
Latin
ValueCountFrequency (%)
B 178
19.2%
A 115
 
12.4%
S 77
 
8.3%
C 47
 
5.1%
T 44
 
4.8%
E 36
 
3.9%
K 34
 
3.7%
L 33
 
3.6%
I 31
 
3.3%
G 23
 
2.5%
Other values (38) 308
33.3%
Common
ValueCountFrequency (%)
31618
37.3%
1 7476
 
8.8%
, 7128
 
8.4%
2 5336
 
6.3%
) 5239
 
6.2%
( 5237
 
6.2%
0 4446
 
5.2%
3 4122
 
4.9%
4 2894
 
3.4%
5 2727
 
3.2%
Other values (10) 8637
 
10.2%
Han
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 107755
55.7%
ASCII 85756
44.3%
Number Forms 28
 
< 0.1%
None 2
 
< 0.1%
CJK 2
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31618
36.9%
1 7476
 
8.7%
, 7128
 
8.3%
2 5336
 
6.2%
) 5239
 
6.1%
( 5237
 
6.1%
0 4446
 
5.2%
3 4122
 
4.8%
4 2894
 
3.4%
5 2727
 
3.2%
Other values (54) 9533
 
11.1%
Hangul
ValueCountFrequency (%)
6919
 
6.4%
6862
 
6.4%
5740
 
5.3%
5738
 
5.3%
5369
 
5.0%
5241
 
4.9%
5206
 
4.8%
5200
 
4.8%
4270
 
4.0%
2730
 
2.5%
Other values (518) 54480
50.6%
Number Forms
ValueCountFrequency (%)
17
60.7%
8
28.6%
3
 
10.7%
None
ValueCountFrequency (%)
2
100.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%

우편번호
Real number (ℝ)

MISSING 

Distinct1382
Distinct (%)31.7%
Missing5647
Missing (%)56.5%
Infinite0
Infinite (%)0.0%
Mean136659.36
Minimum4538
Maximum410762
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T03:54:30.069889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4538
5-th percentile110050.4
Q1132040
median136150
Q3143220
95-th percentile157200
Maximum410762
Range406224
Interquartile range (IQR)11180

Descriptive statistics

Standard deviation15236.549
Coefficient of variation (CV)0.1114929
Kurtosis50.269311
Mean136659.36
Median Absolute Deviation (MAD)5310
Skewness1.4837796
Sum5.948782 × 108
Variance2.3215242 × 108
MonotonicityNot monotonic
2024-05-04T03:54:30.515031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
135080 160
 
1.6%
137070 144
 
1.4%
157010 64
 
0.6%
151015 52
 
0.5%
152050 51
 
0.5%
158070 51
 
0.5%
135010 46
 
0.5%
158050 46
 
0.5%
151050 43
 
0.4%
142100 40
 
0.4%
Other values (1372) 3656
36.6%
(Missing) 5647
56.5%
ValueCountFrequency (%)
4538 2
 
< 0.1%
5510 1
 
< 0.1%
7327 1
 
< 0.1%
100011 3
 
< 0.1%
100012 1
 
< 0.1%
100013 1
 
< 0.1%
100014 2
 
< 0.1%
100015 3
 
< 0.1%
100021 27
0.3%
100022 6
 
0.1%
ValueCountFrequency (%)
410762 1
 
< 0.1%
403866 1
 
< 0.1%
158877 2
< 0.1%
158871 2
< 0.1%
158864 1
 
< 0.1%
158863 1
 
< 0.1%
158860 4
< 0.1%
158859 1
 
< 0.1%
158845 1
 
< 0.1%
158842 1
 
< 0.1%

등록일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3562
Distinct (%)35.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20136373
Minimum20060124
Maximum20240502
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T03:54:30.934234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060124
5-th percentile20070807
Q120091110
median20130307
Q320170706
95-th percentile20230134
Maximum20240502
Range180378
Interquartile range (IQR)79596

Descriptive statistics

Standard deviation48810.517
Coefficient of variation (CV)0.0024239974
Kurtosis-0.90869702
Mean20136373
Median Absolute Deviation (MAD)39605
Skewness0.45669181
Sum2.0136373 × 1011
Variance2.3824666 × 109
MonotonicityNot monotonic
2024-05-04T03:54:31.408236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20080814 31
 
0.3%
20090611 21
 
0.2%
20080818 19
 
0.2%
20081222 19
 
0.2%
20080822 18
 
0.2%
20080926 16
 
0.2%
20090507 16
 
0.2%
20080731 16
 
0.2%
20080806 16
 
0.2%
20080728 14
 
0.1%
Other values (3552) 9814
98.1%
ValueCountFrequency (%)
20060124 1
 
< 0.1%
20060308 1
 
< 0.1%
20060320 2
< 0.1%
20060323 3
< 0.1%
20060324 4
< 0.1%
20060329 1
 
< 0.1%
20060407 1
 
< 0.1%
20060410 2
< 0.1%
20060411 1
 
< 0.1%
20060412 1
 
< 0.1%
ValueCountFrequency (%)
20240502 1
 
< 0.1%
20240429 2
< 0.1%
20240425 2
< 0.1%
20240424 4
< 0.1%
20240423 2
< 0.1%
20240422 3
< 0.1%
20240419 2
< 0.1%
20240417 1
 
< 0.1%
20240415 1
 
< 0.1%
20240411 4
< 0.1%

유효기간만료일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3313
Distinct (%)42.0%
Missing2111
Missing (%)21.1%
Infinite0
Infinite (%)0.0%
Mean20181609
Minimum20100122
Maximum22180428
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T03:54:31.843203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100122
5-th percentile20120304
Q120141028
median20180122
Q320220109
95-th percentile20260425
Maximum22180428
Range2080306
Interquartile range (IQR)79081

Descriptive statistics

Standard deviation49649.51
Coefficient of variation (CV)0.0024601364
Kurtosis331.54687
Mean20181609
Median Absolute Deviation (MAD)39097
Skewness8.4833228
Sum1.5921271 × 1011
Variance2.4650738 × 109
MonotonicityNot monotonic
2024-05-04T03:54:32.264659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110831 14
 
0.1%
20150531 13
 
0.1%
20150508 13
 
0.1%
20140711 12
 
0.1%
20140831 12
 
0.1%
20190216 12
 
0.1%
20140816 11
 
0.1%
20190720 11
 
0.1%
20130329 11
 
0.1%
20140608 11
 
0.1%
Other values (3303) 7769
77.7%
(Missing) 2111
 
21.1%
ValueCountFrequency (%)
20100122 1
< 0.1%
20100125 1
< 0.1%
20100216 1
< 0.1%
20100308 1
< 0.1%
20100326 1
< 0.1%
20100405 1
< 0.1%
20100418 2
< 0.1%
20100427 1
< 0.1%
20100514 1
< 0.1%
20100515 1
< 0.1%
ValueCountFrequency (%)
22180428 1
 
< 0.1%
20270501 1
 
< 0.1%
20270429 2
< 0.1%
20270425 2
< 0.1%
20270424 4
< 0.1%
20270423 2
< 0.1%
20270421 3
< 0.1%
20270419 2
< 0.1%
20270417 1
 
< 0.1%
20270415 1
 
< 0.1%

폐쇄일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3127
Distinct (%)37.1%
Missing1579
Missing (%)15.8%
Infinite0
Infinite (%)0.0%
Mean20141639
Minimum20081023
Maximum20240503
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T03:54:32.666623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20081023
5-th percentile20090924
Q120110323
median20130725
Q320170403
95-th percentile20220809
Maximum20240503
Range159480
Interquartile range (IQR)60080

Descriptive statistics

Standard deviation40500.387
Coefficient of variation (CV)0.0020107791
Kurtosis-0.56188217
Mean20141639
Median Absolute Deviation (MAD)29798
Skewness0.67962943
Sum1.6961274 × 1011
Variance1.6402814 × 109
MonotonicityNot monotonic
2024-05-04T03:54:33.115606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091116 223
 
2.2%
20100927 69
 
0.7%
20101213 23
 
0.2%
20170124 21
 
0.2%
20111108 20
 
0.2%
20110420 19
 
0.2%
20110125 19
 
0.2%
20130529 18
 
0.2%
20170125 18
 
0.2%
20110425 18
 
0.2%
Other values (3117) 7973
79.7%
(Missing) 1579
 
15.8%
ValueCountFrequency (%)
20081023 1
 
< 0.1%
20090125 1
 
< 0.1%
20090211 1
 
< 0.1%
20090309 2
 
< 0.1%
20090311 2
 
< 0.1%
20090312 5
0.1%
20090313 3
< 0.1%
20090316 2
 
< 0.1%
20090317 1
 
< 0.1%
20090318 2
 
< 0.1%
ValueCountFrequency (%)
20240503 3
< 0.1%
20240502 2
< 0.1%
20240501 1
 
< 0.1%
20240430 3
< 0.1%
20240429 1
 
< 0.1%
20240426 1
 
< 0.1%
20240423 2
< 0.1%
20240422 3
< 0.1%
20240419 2
< 0.1%
20240418 1
 
< 0.1%

지점설립일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3567
Distinct (%)40.8%
Missing1251
Missing (%)12.5%
Infinite0
Infinite (%)0.0%
Mean20135166
Minimum19670425
Maximum20240429
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T03:54:33.535669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19670425
5-th percentile20070107
Q120100407
median20130429
Q320170428
95-th percentile20220426
Maximum20240429
Range570004
Interquartile range (IQR)70021

Descriptive statistics

Standard deviation47575.943
Coefficient of variation (CV)0.0023628284
Kurtosis0.84591889
Mean20135166
Median Absolute Deviation (MAD)30680
Skewness0.065197888
Sum1.7616257 × 1011
Variance2.2634703 × 109
MonotonicityNot monotonic
2024-05-04T03:54:33.956474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20090611 24
 
0.2%
20090820 24
 
0.2%
20090507 21
 
0.2%
20090528 18
 
0.2%
20090512 16
 
0.2%
20090514 14
 
0.1%
20090511 14
 
0.1%
20090821 14
 
0.1%
20101102 12
 
0.1%
20130214 12
 
0.1%
Other values (3557) 8580
85.8%
(Missing) 1251
 
12.5%
ValueCountFrequency (%)
19670425 1
< 0.1%
19770919 1
< 0.1%
19880302 1
< 0.1%
19940223 1
< 0.1%
19940418 1
< 0.1%
19950501 1
< 0.1%
19960327 1
< 0.1%
19960712 1
< 0.1%
19961231 1
< 0.1%
19970302 1
< 0.1%
ValueCountFrequency (%)
20240429 2
< 0.1%
20240425 2
< 0.1%
20240423 2
< 0.1%
20240422 1
 
< 0.1%
20240419 3
< 0.1%
20240417 1
 
< 0.1%
20240415 1
 
< 0.1%
20240411 2
< 0.1%
20240408 1
 
< 0.1%
20240404 1
 
< 0.1%

본점여부
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
본점
9933 
지점
 
67

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 9933
99.3%
지점 67
 
0.7%

Length

2024-05-04T03:54:34.376562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T03:54:34.705935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
본점 9933
99.3%
지점 67
 
0.7%

최근수정일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3194
Distinct (%)31.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20152606
Minimum20090518
Maximum20240503
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T03:54:34.912049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090518
5-th percentile20091118
Q120110923
median20140822
Q320190313
95-th percentile20231004
Maximum20240503
Range149985
Interquartile range (IQR)79390.25

Descriptive statistics

Standard deviation45766.925
Coefficient of variation (CV)0.0022710177
Kurtosis-1.0574454
Mean20152606
Median Absolute Deviation (MAD)30513.5
Skewness0.44682299
Sum2.0152606 × 1011
Variance2.0946114 × 109
MonotonicityNot monotonic
2024-05-04T03:54:35.221720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091117 89
 
0.9%
20090609 48
 
0.5%
20100330 46
 
0.5%
20091118 45
 
0.4%
20091116 41
 
0.4%
20091119 38
 
0.4%
20100927 38
 
0.4%
20110425 35
 
0.4%
20090622 35
 
0.4%
20160812 34
 
0.3%
Other values (3184) 9551
95.5%
ValueCountFrequency (%)
20090518 1
 
< 0.1%
20090521 2
 
< 0.1%
20090601 3
 
< 0.1%
20090602 4
 
< 0.1%
20090603 7
 
0.1%
20090604 19
 
0.2%
20090605 3
 
< 0.1%
20090608 3
 
< 0.1%
20090609 48
0.5%
20090610 18
 
0.2%
ValueCountFrequency (%)
20240503 10
0.1%
20240502 8
0.1%
20240501 2
 
< 0.1%
20240430 4
 
< 0.1%
20240429 6
0.1%
20240426 2
 
< 0.1%
20240425 3
 
< 0.1%
20240424 7
0.1%
20240423 7
0.1%
20240422 10
0.1%

Interactions

2024-05-04T03:54:09.458301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:52:40.872211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:52:46.489809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:52:55.967600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:53:04.298314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:53:14.876101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:54:09.902813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:52:41.164913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:52:46.797606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:52:56.175255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:53:04.598454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:53:17.525074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:54:10.198463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:52:41.467845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:52:47.082518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:52:56.372115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:53:04.919647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:53:26.779597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:54:10.515974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:52:41.770301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:52:47.350723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:52:56.539553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:53:05.233310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:53:34.629956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:54:10.869915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:52:42.072324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:52:47.671074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:52:56.788754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:53:05.559587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:53:42.828387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:54:18.553372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:52:46.196556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:52:55.761022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:53:04.009935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:53:14.566646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:54:01.764136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T03:54:35.512891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록신청사업영업구분법인여부우편번호등록일자유효기간만료일자폐쇄일자지점설립일자본점여부최근수정일자
등록신청사업1.0000.0810.0090.0000.2290.0000.2180.1860.0000.167
영업구분0.0811.0000.1720.0220.5950.0000.2890.5010.0470.486
법인여부0.0090.1721.0000.0520.3460.0000.2710.2730.1930.354
우편번호0.0000.0220.0521.0000.120NaN0.0000.0660.0000.125
등록일자0.2290.5950.3460.1201.0000.0000.9380.7300.0810.939
유효기간만료일자0.0000.0000.000NaN0.0001.0000.0000.0000.0000.000
폐쇄일자0.2180.2890.2710.0000.9380.0001.0000.7180.0560.986
지점설립일자0.1860.5010.2730.0660.7300.0000.7181.0000.1710.700
본점여부0.0000.0470.1930.0000.0810.0000.0560.1711.0000.093
최근수정일자0.1670.4860.3540.1250.9390.0000.9860.7000.0931.000
2024-05-04T03:54:35.826797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법인여부등록신청사업영업구분본점여부
법인여부1.0000.0060.1840.124
등록신청사업0.0061.0000.0870.000
영업구분0.1840.0871.0000.050
본점여부0.1240.0000.0501.000
2024-05-04T03:54:36.011585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호등록일자유효기간만료일자폐쇄일자지점설립일자최근수정일자등록신청사업영업구분법인여부본점여부
우편번호1.0000.0170.0170.0380.0680.0230.0000.0000.0530.000
등록일자0.0171.0000.9960.9620.9290.9660.1760.3530.2650.062
유효기간만료일자0.0170.9961.0000.9640.9020.9670.0000.0000.0000.000
폐쇄일자0.0380.9620.9641.0000.9110.9920.1670.1240.2080.043
지점설립일자0.0680.9290.9020.9111.0000.9010.0740.3810.3210.173
최근수정일자0.0230.9660.9670.9920.9011.0000.1280.2820.2710.071
등록신청사업0.0000.1760.0000.1670.0740.1281.0000.0870.0060.000
영업구분0.0000.3530.0000.1240.3810.2820.0871.0000.1840.050
법인여부0.0530.2650.0000.2080.3210.2710.0060.1841.0000.124
본점여부0.0000.0620.0000.0430.1730.0710.0000.0500.1241.000

Missing values

2024-05-04T03:54:18.979696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T03:54:19.608978image/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.
2024-05-04T03:54:20.115206image/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
14229대부중개업폐업2014-서울서대문-00007(대부중개업)이루 대부 중개개인02-722-5379서울특별시 서대문구 홍은동 8번지 31호서울특별시 서대문구 홍은중앙로 155, 101호 (홍은동, 이루하이빌)12010120140808201708072015071620140808본점20150716
10356대부중개업폐업2016-서울송파-0010(대부중개업)OK더드림대부개인02)555-8891서울특별시 송파구 가락동 99번지 3호 제일오피스텔-1705서울특별시 송파구 송파대로 260, 1705호 (가락동, 제일오피스텔)<NA>20150914201809142017072520150914본점20170725
27404대부업<NA>2007-서울특별시-01551(대부업)진솔함개인<NA>서울특별시 서초구 반포동 728-26 302호<NA><NA>20071218<NA>20100803<NA>본점20100803
96대부중개업영업중2024-서울서초-0035(대부중개업)주식회사 어니스티자산관리대부법인070-7537-0420서울특별시 서초구 서초동 1338번지 20호 현대렉시온서울특별시 서초구 강남대로 305, 현대렉시온 11층 1118호 (서초동)<NA>2024042520270425<NA>20240425본점20240425
1477대부업영업중2015-서울서대문-00002(대부업)홍은사 전당포대부개인02-3216-6870서울특별시 서대문구 홍은동 48번지 213호서울특별시 서대문구 세검정로 15 (홍은동)1201012023102520261025<NA>20150210본점20231025
31160대부중개업<NA>2008-서울특별시-02898광야산업개인025551177서울특별시 성동구 성수1가1동 656-410 홍성빌딩 421호<NA>13311120081106<NA>20090422<NA>본점20090609
21020대부업폐업2010-서울강남-0317다빈치캐피탈대부개인0804942222서울특별시 강남구 논현동 227번지 4호 양지상가 3층-326<NA>13501020100929201309292012072720100929본점20120727
4883대부중개업영업중2021-서울중구-0048(대부중개업)유진홀딩스대부개인02-2238-3338서울특별시 중구 신당동 773번지 맥스타일서울특별시 중구 마장로 3, 맥스타일오피스텔 16층 4호 (신당동)<NA>2021122820241228<NA>20211228본점20211228
12190대부업<NA>2013-서울강남-0258조이크레디트대부금융 강남센터법인02-6925-0107서울특별시 강남구 역삼동 707번지 34호 한신인터밸리24 서관6층 601~607호서울특별시 강남구 테헤란로 322, 서관6층 601~607호 (역삼동, 한신인터밸리24빌딩)<NA>2013092720160927<NA>20130927지점20160906
26170대부중개업<NA>2009-서울특별시-00722(대부중개업)독도 대부중개개인07075019950서울특별시 서초구 반포동 715-8번지 206호<NA><NA>20090514<NA>2010121320090514본점20101213
등록신청사업영업구분등록증번호상호법인여부사업장 전화번호소재지소재지(도로명)우편번호등록일자유효기간만료일자폐쇄일자지점설립일자본점여부최근수정일자
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