Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells19113
Missing cells (%)12.7%
Duplicate rows3
Duplicate rows (%)< 0.1%
Total size in memory1.3 MiB
Average record size in memory133.0 B

Variable types

Categorical4
Text6
Numeric5

Dataset

Description등록신청사업,영업구분,등록증번호,상호,법인여부,사업장 전화번호,소재지,소재지(도로명),우편번호,등록일자,유효기간만료일자,폐쇄일자,지점설립일자,본점여부,최근수정일자
Author강동구
URLhttps://data.seoul.go.kr/dataList/OA-10712/S/1/datasetView.do

Alerts

Dataset has 3 (< 0.1%) duplicate rowsDuplicates
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 (94.4%)Imbalance
등록증번호 has 179 (1.8%) missing valuesMissing
사업장 전화번호 has 3404 (34.0%) missing valuesMissing
소재지 has 295 (2.9%) missing valuesMissing
소재지(도로명) has 4759 (47.6%) missing valuesMissing
우편번호 has 5615 (56.1%) missing valuesMissing
유효기간만료일자 has 2034 (20.3%) missing valuesMissing
폐쇄일자 has 1573 (15.7%) missing valuesMissing
지점설립일자 has 1254 (12.5%) missing valuesMissing

Reproduction

Analysis started2024-05-18 00:22:24.363791
Analysis finished2024-05-18 00:22:39.256605
Duration14.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
대부업
6199 
대부중개업
3410 
<NA>
 
391

Length

Max length5
Median length3
Mean length3.7211
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대부업 6199
62.0%
대부중개업 3410
34.1%
<NA> 391
 
3.9%

Length

2024-05-18T09:22:39.400745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:22:39.631953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대부업 6199
62.0%
대부중개업 3410
34.1%
na 391
 
3.9%

영업구분
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
3700 
<NA>
2873 
타시군구이관
1185 
유효기간만료
851 
영업중
828 
Other values (2)
563 

Length

Max length6
Median length4
Mean length3.5844
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3700
37.0%
<NA> 2873
28.7%
타시군구이관 1185
 
11.8%
유효기간만료 851
 
8.5%
영업중 828
 
8.3%
직권취소 562
 
5.6%
영업정지 1
 
< 0.1%

Length

2024-05-18T09:22:39.871156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:22:40.122373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3700
37.0%
na 2873
28.7%
타시군구이관 1185
 
11.8%
유효기간만료 851
 
8.5%
영업중 828
 
8.3%
직권취소 562
 
5.6%
영업정지 1
 
< 0.1%

등록증번호
Text

MISSING 

Distinct9767
Distinct (%)99.5%
Missing179
Missing (%)1.8%
Memory size156.2 KiB
2024-05-18T09:22:40.557318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length27
Mean length19.538642
Min length10

Characters and Unicode

Total characters191889
Distinct characters78
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

Unique9717 ?
Unique (%)98.9%

Sample

1st row2008-서울특별시-03663(대부업)
2nd row2013-서울중구-0117(대부업)
3rd row2015-서울강남-0023(대부중개업)
4th row2012-서울영등포-0334(대부업)
5th row2017-서울강동-00044
ValueCountFrequency (%)
2011-서울특별시 20
 
0.2%
2013-서울특별시 17
 
0.2%
2010-서울 17
 
0.2%
2016-서울특별시 13
 
0.1%
2015-서울특별시 12
 
0.1%
2012-서울특별시 12
 
0.1%
대부업 10
 
0.1%
2014-서울특별시 8
 
0.1%
대부중개업 7
 
0.1%
2020-서울 6
 
0.1%
Other values (9738) 9857
98.8%
2024-05-18T09:22:41.256273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 33939
17.7%
- 19626
 
10.2%
2 15786
 
8.2%
1 11858
 
6.2%
10873
 
5.7%
9797
 
5.1%
8528
 
4.4%
( 8236
 
4.3%
8195
 
4.3%
) 8185
 
4.3%
Other values (68) 56866
29.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82608
43.0%
Other Letter 73076
38.1%
Dash Punctuation 19626
 
10.2%
Open Punctuation 8236
 
4.3%
Close Punctuation 8185
 
4.3%
Space Separator 158
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10873
14.9%
9797
13.4%
8528
11.7%
8195
11.2%
7951
10.9%
3536
 
4.8%
2913
 
4.0%
2504
 
3.4%
2498
 
3.4%
2498
 
3.4%
Other values (54) 13783
18.9%
Decimal Number
ValueCountFrequency (%)
0 33939
41.1%
2 15786
19.1%
1 11858
 
14.4%
3 3772
 
4.6%
8 3116
 
3.8%
4 3046
 
3.7%
9 2869
 
3.5%
6 2762
 
3.3%
5 2736
 
3.3%
7 2724
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 19626
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8236
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8185
100.0%
Space Separator
ValueCountFrequency (%)
158
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 118813
61.9%
Hangul 73076
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10873
14.9%
9797
13.4%
8528
11.7%
8195
11.2%
7951
10.9%
3536
 
4.8%
2913
 
4.0%
2504
 
3.4%
2498
 
3.4%
2498
 
3.4%
Other values (54) 13783
18.9%
Common
ValueCountFrequency (%)
0 33939
28.6%
- 19626
16.5%
2 15786
13.3%
1 11858
 
10.0%
( 8236
 
6.9%
) 8185
 
6.9%
3 3772
 
3.2%
8 3116
 
2.6%
4 3046
 
2.6%
9 2869
 
2.4%
Other values (4) 8380
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 118813
61.9%
Hangul 73076
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 33939
28.6%
- 19626
16.5%
2 15786
13.3%
1 11858
 
10.0%
( 8236
 
6.9%
) 8185
 
6.9%
3 3772
 
3.2%
8 3116
 
2.6%
4 3046
 
2.6%
9 2869
 
2.4%
Other values (4) 8380
 
7.1%
Hangul
ValueCountFrequency (%)
10873
14.9%
9797
13.4%
8528
11.7%
8195
11.2%
7951
10.9%
3536
 
4.8%
2913
 
4.0%
2504
 
3.4%
2498
 
3.4%
2498
 
3.4%
Other values (54) 13783
18.9%

상호
Text

Distinct8661
Distinct (%)86.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T09:22:41.717453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length26
Mean length7.7246
Min length1

Characters and Unicode

Total characters77246
Distinct characters774
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7601 ?
Unique (%)76.0%

Sample

1st row대신
2nd row영풍상사대부
3rd row주식회사 에이디자산운용대부
4th row(주)코리아인포메이션서비스자산관리대부
5th row스마일재무 대부중개
ValueCountFrequency (%)
주식회사 800
 
6.7%
대부중개 328
 
2.8%
대부 287
 
2.4%
유한회사 51
 
0.4%
대부업 23
 
0.2%
캐피탈 21
 
0.2%
12
 
0.1%
미래 12
 
0.1%
전당포대부 10
 
0.1%
the 10
 
0.1%
Other values (8672) 10363
87.0%
2024-05-18T09:22:42.679260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8575
 
11.1%
8188
 
10.6%
2662
 
3.4%
2256
 
2.9%
2160
 
2.8%
2152
 
2.8%
1923
 
2.5%
) 1871
 
2.4%
1870
 
2.4%
( 1865
 
2.4%
Other values (764) 43724
56.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67701
87.6%
Uppercase Letter 2295
 
3.0%
Space Separator 1923
 
2.5%
Close Punctuation 1871
 
2.4%
Open Punctuation 1865
 
2.4%
Lowercase Letter 1046
 
1.4%
Decimal Number 253
 
0.3%
Other Punctuation 248
 
0.3%
Dash Punctuation 29
 
< 0.1%
Other Symbol 12
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8575
 
12.7%
8188
 
12.1%
2662
 
3.9%
2256
 
3.3%
2160
 
3.2%
2152
 
3.2%
1870
 
2.8%
1325
 
2.0%
1149
 
1.7%
1041
 
1.5%
Other values (690) 36323
53.7%
Uppercase Letter
ValueCountFrequency (%)
S 327
14.2%
K 193
 
8.4%
C 180
 
7.8%
J 180
 
7.8%
M 164
 
7.1%
H 131
 
5.7%
B 110
 
4.8%
G 95
 
4.1%
A 90
 
3.9%
O 90
 
3.9%
Other values (15) 735
32.0%
Lowercase Letter
ValueCountFrequency (%)
e 142
13.6%
o 117
11.2%
n 109
10.4%
a 91
 
8.7%
i 67
 
6.4%
l 61
 
5.8%
t 57
 
5.4%
c 56
 
5.4%
s 54
 
5.2%
d 44
 
4.2%
Other values (15) 248
23.7%
Decimal Number
ValueCountFrequency (%)
1 71
28.1%
2 44
17.4%
4 33
13.0%
5 24
 
9.5%
3 24
 
9.5%
9 20
 
7.9%
6 15
 
5.9%
0 10
 
4.0%
7 7
 
2.8%
8 5
 
2.0%
Other Punctuation
ValueCountFrequency (%)
. 134
54.0%
& 105
42.3%
, 4
 
1.6%
? 2
 
0.8%
1
 
0.4%
* 1
 
0.4%
' 1
 
0.4%
Space Separator
ValueCountFrequency (%)
1923
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1871
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1865
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Other Symbol
ValueCountFrequency (%)
12
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67702
87.6%
Common 6192
 
8.0%
Latin 3341
 
4.3%
Han 11
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8575
 
12.7%
8188
 
12.1%
2662
 
3.9%
2256
 
3.3%
2160
 
3.2%
2152
 
3.2%
1870
 
2.8%
1325
 
2.0%
1149
 
1.7%
1041
 
1.5%
Other values (681) 36324
53.7%
Latin
ValueCountFrequency (%)
S 327
 
9.8%
K 193
 
5.8%
C 180
 
5.4%
J 180
 
5.4%
M 164
 
4.9%
e 142
 
4.3%
H 131
 
3.9%
o 117
 
3.5%
B 110
 
3.3%
n 109
 
3.3%
Other values (40) 1688
50.5%
Common
ValueCountFrequency (%)
1923
31.1%
) 1871
30.2%
( 1865
30.1%
. 134
 
2.2%
& 105
 
1.7%
1 71
 
1.1%
2 44
 
0.7%
4 33
 
0.5%
- 29
 
0.5%
5 24
 
0.4%
Other values (13) 93
 
1.5%
Han
ValueCountFrequency (%)
2
18.2%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67690
87.6%
ASCII 9532
 
12.3%
None 13
 
< 0.1%
CJK 11
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
8575
 
12.7%
8188
 
12.1%
2662
 
3.9%
2256
 
3.3%
2160
 
3.2%
2152
 
3.2%
1870
 
2.8%
1325
 
2.0%
1149
 
1.7%
1041
 
1.5%
Other values (680) 36312
53.6%
ASCII
ValueCountFrequency (%)
1923
20.2%
) 1871
19.6%
( 1865
19.6%
S 327
 
3.4%
K 193
 
2.0%
C 180
 
1.9%
J 180
 
1.9%
M 164
 
1.7%
e 142
 
1.5%
. 134
 
1.4%
Other values (62) 2553
26.8%
None
ValueCountFrequency (%)
12
92.3%
1
 
7.7%
CJK
ValueCountFrequency (%)
2
18.2%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%

법인여부
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
개인
7242 
법인
2758 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 7242
72.4%
법인 2758
 
27.6%

Length

2024-05-18T09:22:43.079739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:22:43.416891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 7242
72.4%
법인 2758
 
27.6%
Distinct5808
Distinct (%)88.1%
Missing3404
Missing (%)34.0%
Memory size156.2 KiB
2024-05-18T09:22:43.827631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length41
Mean length10.601122
Min length1

Characters and Unicode

Total characters69925
Distinct characters37
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

Unique5162 ?
Unique (%)78.3%

Sample

1st row025886110
2nd row02-318-5584
3rd row02-889-1765
4th row0237865825
5th row02-475-1019
ValueCountFrequency (%)
02 298
 
4.0%
57
 
0.8%
070 34
 
0.5%
010 10
 
0.1%
1566 9
 
0.1%
703 6
 
0.1%
02-734-6901 5
 
0.1%
1599 5
 
0.1%
1661-1547 5
 
0.1%
02-6272-1300 4
 
0.1%
Other values (6106) 6974
94.2%
2024-05-18T09:22:44.634161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11314
16.2%
2 10282
14.7%
- 7108
10.2%
5 5895
8.4%
7 5429
7.8%
6 5185
7.4%
1 5026
7.2%
3 4919
7.0%
4 4857
6.9%
8 4708
6.7%
Other values (27) 5202
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61627
88.1%
Dash Punctuation 7108
 
10.2%
Space Separator 908
 
1.3%
Other Punctuation 153
 
0.2%
Close Punctuation 65
 
0.1%
Math Symbol 22
 
< 0.1%
Other Letter 20
 
< 0.1%
Open Punctuation 15
 
< 0.1%
Uppercase Letter 6
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
 
10.0%
2
 
10.0%
2
 
10.0%
2
 
10.0%
2
 
10.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
Other values (5) 5
25.0%
Decimal Number
ValueCountFrequency (%)
0 11314
18.4%
2 10282
16.7%
5 5895
9.6%
7 5429
8.8%
6 5185
8.4%
1 5026
8.2%
3 4919
8.0%
4 4857
7.9%
8 4708
7.6%
9 4012
 
6.5%
Other Punctuation
ValueCountFrequency (%)
* 93
60.8%
/ 39
25.5%
. 21
 
13.7%
Math Symbol
ValueCountFrequency (%)
~ 21
95.5%
× 1
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
K 3
50.0%
T 3
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 7108
100.0%
Space Separator
ValueCountFrequency (%)
908
100.0%
Close Punctuation
ValueCountFrequency (%)
) 65
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69899
> 99.9%
Hangul 20
 
< 0.1%
Latin 6
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11314
16.2%
2 10282
14.7%
- 7108
10.2%
5 5895
8.4%
7 5429
7.8%
6 5185
7.4%
1 5026
7.2%
3 4919
7.0%
4 4857
6.9%
8 4708
6.7%
Other values (10) 5176
7.4%
Hangul
ValueCountFrequency (%)
2
 
10.0%
2
 
10.0%
2
 
10.0%
2
 
10.0%
2
 
10.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
Other values (5) 5
25.0%
Latin
ValueCountFrequency (%)
K 3
50.0%
T 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69904
> 99.9%
Hangul 20
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11314
16.2%
2 10282
14.7%
- 7108
10.2%
5 5895
8.4%
7 5429
7.8%
6 5185
7.4%
1 5026
7.2%
3 4919
7.0%
4 4857
6.9%
8 4708
6.7%
Other values (11) 5181
7.4%
Hangul
ValueCountFrequency (%)
2
 
10.0%
2
 
10.0%
2
 
10.0%
2
 
10.0%
2
 
10.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
Other values (5) 5
25.0%
None
ValueCountFrequency (%)
× 1
100.0%

소재지
Text

MISSING 

Distinct8615
Distinct (%)88.8%
Missing295
Missing (%)2.9%
Memory size156.2 KiB
2024-05-18T09:22:46.045842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length51
Mean length31.514992
Min length15

Characters and Unicode

Total characters305853
Distinct characters612
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

Unique7845 ?
Unique (%)80.8%

Sample

1st row서울특별시 서초구 서초동 1319번지 13호 현대타워 907호
2nd row서울특별시 중구 을지로2가 195번지 3호 한양빌딩
3rd row서울특별시 강남구 역삼동 706번지 15호 성보빌딩Ⅱ
4th row서울특별시 영등포구 여의도동 13번지 13호 크레딧플라자 10층
5th row서울특별시 강동구 성내동 533번지 1호 -202
ValueCountFrequency (%)
서울특별시 9702
 
17.0%
강남구 1565
 
2.7%
서초구 936
 
1.6%
1호 759
 
1.3%
역삼동 656
 
1.1%
송파구 618
 
1.1%
서초동 569
 
1.0%
중구 555
 
1.0%
영등포구 465
 
0.8%
2호 447
 
0.8%
Other values (9396) 40966
71.6%
2024-05-18T09:22:47.172359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
67782
22.2%
1 13449
 
4.4%
12064
 
3.9%
11144
 
3.6%
10499
 
3.4%
9944
 
3.3%
9752
 
3.2%
9710
 
3.2%
9703
 
3.2%
2 8747
 
2.9%
Other values (602) 143059
46.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 167422
54.7%
Space Separator 67782
22.2%
Decimal Number 63490
 
20.8%
Dash Punctuation 5460
 
1.8%
Uppercase Letter 1097
 
0.4%
Other Punctuation 258
 
0.1%
Lowercase Letter 124
 
< 0.1%
Close Punctuation 97
 
< 0.1%
Open Punctuation 92
 
< 0.1%
Letter Number 26
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12064
 
7.2%
11144
 
6.7%
10499
 
6.3%
9944
 
5.9%
9752
 
5.8%
9710
 
5.8%
9703
 
5.8%
8622
 
5.1%
8482
 
5.1%
7976
 
4.8%
Other values (529) 69526
41.5%
Uppercase Letter
ValueCountFrequency (%)
B 272
24.8%
A 199
18.1%
D 78
 
7.1%
S 70
 
6.4%
K 52
 
4.7%
T 47
 
4.3%
I 41
 
3.7%
E 38
 
3.5%
C 38
 
3.5%
L 37
 
3.4%
Other values (16) 225
20.5%
Lowercase Letter
ValueCountFrequency (%)
e 24
19.4%
r 12
 
9.7%
n 11
 
8.9%
i 9
 
7.3%
c 7
 
5.6%
t 7
 
5.6%
o 7
 
5.6%
w 6
 
4.8%
l 6
 
4.8%
k 5
 
4.0%
Other values (13) 30
24.2%
Decimal Number
ValueCountFrequency (%)
1 13449
21.2%
2 8747
13.8%
0 8139
12.8%
3 6827
10.8%
4 5823
9.2%
5 5013
 
7.9%
6 4565
 
7.2%
7 4037
 
6.4%
9 3476
 
5.5%
8 3414
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 97
37.6%
/ 95
36.8%
. 63
24.4%
; 1
 
0.4%
& 1
 
0.4%
* 1
 
0.4%
Letter Number
ValueCountFrequency (%)
22
84.6%
2
 
7.7%
2
 
7.7%
Space Separator
ValueCountFrequency (%)
67782
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5460
100.0%
Close Punctuation
ValueCountFrequency (%)
) 97
100.0%
Open Punctuation
ValueCountFrequency (%)
( 92
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 167419
54.7%
Common 137184
44.9%
Latin 1247
 
0.4%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12064
 
7.2%
11144
 
6.7%
10499
 
6.3%
9944
 
5.9%
9752
 
5.8%
9710
 
5.8%
9703
 
5.8%
8622
 
5.1%
8482
 
5.1%
7976
 
4.8%
Other values (526) 69523
41.5%
Latin
ValueCountFrequency (%)
B 272
21.8%
A 199
16.0%
D 78
 
6.3%
S 70
 
5.6%
K 52
 
4.2%
T 47
 
3.8%
I 41
 
3.3%
E 38
 
3.0%
C 38
 
3.0%
L 37
 
3.0%
Other values (42) 375
30.1%
Common
ValueCountFrequency (%)
67782
49.4%
1 13449
 
9.8%
2 8747
 
6.4%
0 8139
 
5.9%
3 6827
 
5.0%
4 5823
 
4.2%
- 5460
 
4.0%
5 5013
 
3.7%
6 4565
 
3.3%
7 4037
 
2.9%
Other values (11) 7342
 
5.4%
Han
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 167419
54.7%
ASCII 138405
45.3%
Number Forms 26
 
< 0.1%
CJK 2
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
67782
49.0%
1 13449
 
9.7%
2 8747
 
6.3%
0 8139
 
5.9%
3 6827
 
4.9%
4 5823
 
4.2%
- 5460
 
3.9%
5 5013
 
3.6%
6 4565
 
3.3%
7 4037
 
2.9%
Other values (60) 8563
 
6.2%
Hangul
ValueCountFrequency (%)
12064
 
7.2%
11144
 
6.7%
10499
 
6.3%
9944
 
5.9%
9752
 
5.8%
9710
 
5.8%
9703
 
5.8%
8622
 
5.1%
8482
 
5.1%
7976
 
4.8%
Other values (526) 69523
41.5%
Number Forms
ValueCountFrequency (%)
22
84.6%
2
 
7.7%
2
 
7.7%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

소재지(도로명)
Text

MISSING 

Distinct4784
Distinct (%)91.3%
Missing4759
Missing (%)47.6%
Memory size156.2 KiB
2024-05-18T09:22:47.884553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length56
Mean length37.239458
Min length19

Characters and Unicode

Total characters195172
Distinct characters600
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4375 ?
Unique (%)83.5%

Sample

1st row서울특별시 중구 명동9길 23, 한양빌딩 6층 712호 (을지로2가)
2nd row서울특별시 강남구 언주로 432-6, 성보빌딩Ⅱ 4층 019호 (역삼동)
3rd row서울특별시 강동구 성내로3가길 49, 202호 (성내동, 호성빌딩)
4th row서울특별시 강서구 양천로 470, 그레이스힐 지하1층 115호-(4)호 (등촌동)
5th row서울특별시 송파구 가락로 102, 석촌꽃마을빌딩 212호 (석촌동)
ValueCountFrequency (%)
서울특별시 5239
 
14.1%
강남구 887
 
2.4%
서초구 574
 
1.5%
2층 447
 
1.2%
서초동 379
 
1.0%
역삼동 375
 
1.0%
3층 375
 
1.0%
송파구 336
 
0.9%
영등포구 332
 
0.9%
4층 308
 
0.8%
Other values (6608) 27898
75.1%
2024-05-18T09:22:49.058906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31935
 
16.4%
1 7454
 
3.8%
, 7229
 
3.7%
6916
 
3.5%
6892
 
3.5%
5764
 
3.0%
5761
 
3.0%
5441
 
2.8%
2 5409
 
2.8%
5283
 
2.7%
Other values (590) 107088
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 108511
55.6%
Decimal Number 34878
 
17.9%
Space Separator 31935
 
16.4%
Other Punctuation 7248
 
3.7%
Open Punctuation 5277
 
2.7%
Close Punctuation 5277
 
2.7%
Dash Punctuation 1056
 
0.5%
Uppercase Letter 844
 
0.4%
Lowercase Letter 115
 
0.1%
Letter Number 24
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6916
 
6.4%
6892
 
6.4%
5764
 
5.3%
5761
 
5.3%
5441
 
5.0%
5283
 
4.9%
5247
 
4.8%
5240
 
4.8%
4306
 
4.0%
2750
 
2.5%
Other values (520) 54911
50.6%
Uppercase Letter
ValueCountFrequency (%)
B 172
20.4%
A 112
13.3%
S 74
 
8.8%
T 46
 
5.5%
E 45
 
5.3%
C 44
 
5.2%
I 40
 
4.7%
K 37
 
4.4%
G 34
 
4.0%
L 34
 
4.0%
Other values (16) 206
24.4%
Lowercase Letter
ValueCountFrequency (%)
e 17
14.8%
r 14
12.2%
n 11
9.6%
o 11
9.6%
w 9
 
7.8%
c 8
 
7.0%
t 7
 
6.1%
i 5
 
4.3%
u 5
 
4.3%
s 5
 
4.3%
Other values (9) 23
20.0%
Decimal Number
ValueCountFrequency (%)
1 7454
21.4%
2 5409
15.5%
0 4551
13.0%
3 4213
12.1%
4 2955
 
8.5%
5 2764
 
7.9%
6 2231
 
6.4%
7 1882
 
5.4%
8 1816
 
5.2%
9 1603
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 7229
99.7%
. 10
 
0.1%
/ 3
 
< 0.1%
? 2
 
< 0.1%
@ 2
 
< 0.1%
& 1
 
< 0.1%
# 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
19
79.2%
3
 
12.5%
2
 
8.3%
Space Separator
ValueCountFrequency (%)
31935
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5277
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5277
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1056
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 108511
55.6%
Common 85678
43.9%
Latin 983
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6916
 
6.4%
6892
 
6.4%
5764
 
5.3%
5761
 
5.3%
5441
 
5.0%
5283
 
4.9%
5247
 
4.8%
5240
 
4.8%
4306
 
4.0%
2750
 
2.5%
Other values (520) 54911
50.6%
Latin
ValueCountFrequency (%)
B 172
17.5%
A 112
 
11.4%
S 74
 
7.5%
T 46
 
4.7%
E 45
 
4.6%
C 44
 
4.5%
I 40
 
4.1%
K 37
 
3.8%
G 34
 
3.5%
L 34
 
3.5%
Other values (38) 345
35.1%
Common
ValueCountFrequency (%)
31935
37.3%
1 7454
 
8.7%
, 7229
 
8.4%
2 5409
 
6.3%
( 5277
 
6.2%
) 5277
 
6.2%
0 4551
 
5.3%
3 4213
 
4.9%
4 2955
 
3.4%
5 2764
 
3.2%
Other values (12) 8614
 
10.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 108511
55.6%
ASCII 86637
44.4%
Number Forms 24
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31935
36.9%
1 7454
 
8.6%
, 7229
 
8.3%
2 5409
 
6.2%
( 5277
 
6.1%
) 5277
 
6.1%
0 4551
 
5.3%
3 4213
 
4.9%
4 2955
 
3.4%
5 2764
 
3.2%
Other values (57) 9573
 
11.0%
Hangul
ValueCountFrequency (%)
6916
 
6.4%
6892
 
6.4%
5764
 
5.3%
5761
 
5.3%
5441
 
5.0%
5283
 
4.9%
5247
 
4.8%
5240
 
4.8%
4306
 
4.0%
2750
 
2.5%
Other values (520) 54911
50.6%
Number Forms
ValueCountFrequency (%)
19
79.2%
3
 
12.5%
2
 
8.3%

우편번호
Real number (ℝ)

MISSING 

Distinct1347
Distinct (%)30.7%
Missing5615
Missing (%)56.1%
Infinite0
Infinite (%)0.0%
Mean136228.86
Minimum3182
Maximum429842
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T09:22:49.378825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3182
5-th percentile100859
Q1132010
median136130
Q3143190
95-th percentile157030
Maximum429842
Range426660
Interquartile range (IQR)11180

Descriptive statistics

Standard deviation15503.488
Coefficient of variation (CV)0.11380473
Kurtosis53.684111
Mean136228.86
Median Absolute Deviation (MAD)5286
Skewness1.6464038
Sum5.9736355 × 108
Variance2.4035814 × 108
MonotonicityNot monotonic
2024-05-18T09:22:49.632167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
135080 153
 
1.5%
137070 136
 
1.4%
135010 69
 
0.7%
157010 57
 
0.6%
151015 50
 
0.5%
151050 44
 
0.4%
139200 44
 
0.4%
158070 44
 
0.4%
152050 42
 
0.4%
142100 40
 
0.4%
Other values (1337) 3706
37.1%
(Missing) 5615
56.1%
ValueCountFrequency (%)
3182 1
 
< 0.1%
4526 1
 
< 0.1%
4534 1
 
< 0.1%
7326 1
 
< 0.1%
100011 9
 
0.1%
100012 3
 
< 0.1%
100013 1
 
< 0.1%
100014 1
 
< 0.1%
100015 4
 
< 0.1%
100021 27
0.3%
ValueCountFrequency (%)
429842 1
 
< 0.1%
403866 1
 
< 0.1%
158881 1
 
< 0.1%
158877 1
 
< 0.1%
158871 1
 
< 0.1%
158865 1
 
< 0.1%
158864 2
 
< 0.1%
158860 6
0.1%
158859 1
 
< 0.1%
158856 1
 
< 0.1%

등록일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3535
Distinct (%)35.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20136864
Minimum20060306
Maximum20240516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T09:22:49.917145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060306
5-th percentile20070928
Q120091126
median20130228
Q320170727
95-th percentile20230217
Maximum20240516
Range180210
Interquartile range (IQR)79601

Descriptive statistics

Standard deviation48847.892
Coefficient of variation (CV)0.0024257944
Kurtosis-0.90786437
Mean20136864
Median Absolute Deviation (MAD)39509.5
Skewness0.46721128
Sum2.0136864 × 1011
Variance2.3861166 × 109
MonotonicityNot monotonic
2024-05-18T09:22:50.192829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20080731 25
 
0.2%
20080814 23
 
0.2%
20080818 22
 
0.2%
20080926 20
 
0.2%
20090611 17
 
0.2%
20081017 16
 
0.2%
20090514 16
 
0.2%
20080822 14
 
0.1%
20080806 14
 
0.1%
20081222 14
 
0.1%
Other values (3525) 9819
98.2%
ValueCountFrequency (%)
20060306 2
< 0.1%
20060320 2
< 0.1%
20060324 1
 
< 0.1%
20060329 1
 
< 0.1%
20060331 2
< 0.1%
20060405 2
< 0.1%
20060407 4
< 0.1%
20060410 1
 
< 0.1%
20060418 2
< 0.1%
20060501 3
< 0.1%
ValueCountFrequency (%)
20240516 3
< 0.1%
20240514 2
 
< 0.1%
20240507 3
< 0.1%
20240503 1
 
< 0.1%
20240502 1
 
< 0.1%
20240430 1
 
< 0.1%
20240429 2
 
< 0.1%
20240425 2
 
< 0.1%
20240424 2
 
< 0.1%
20240422 6
0.1%

유효기간만료일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3314
Distinct (%)41.6%
Missing2034
Missing (%)20.3%
Infinite0
Infinite (%)0.0%
Mean20181185
Minimum20091116
Maximum20270516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T09:22:50.465497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20091116
5-th percentile20120213
Q120141007
median20171223
Q320220109
95-th percentile20260508
Maximum20270516
Range179400
Interquartile range (IQR)79102

Descriptive statistics

Standard deviation44766.522
Coefficient of variation (CV)0.0022182306
Kurtosis-0.98887376
Mean20181185
Median Absolute Deviation (MAD)30693
Skewness0.31899759
Sum1.6076332 × 1011
Variance2.0040415 × 109
MonotonicityNot monotonic
2024-05-18T09:22:50.929756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110831 18
 
0.2%
20190718 13
 
0.1%
20150531 12
 
0.1%
20140711 11
 
0.1%
20141108 11
 
0.1%
20110731 11
 
0.1%
20140622 11
 
0.1%
20140223 10
 
0.1%
20170306 10
 
0.1%
20170421 10
 
0.1%
Other values (3304) 7849
78.5%
(Missing) 2034
 
20.3%
ValueCountFrequency (%)
20091116 2
< 0.1%
20100323 1
< 0.1%
20100410 1
< 0.1%
20100418 1
< 0.1%
20100419 1
< 0.1%
20100514 1
< 0.1%
20100515 1
< 0.1%
20100521 1
< 0.1%
20100522 1
< 0.1%
20100627 2
< 0.1%
ValueCountFrequency (%)
20270516 3
< 0.1%
20270514 2
< 0.1%
20270507 2
< 0.1%
20270506 1
 
< 0.1%
20270503 1
 
< 0.1%
20270501 1
 
< 0.1%
20270430 1
 
< 0.1%
20270429 2
< 0.1%
20270425 2
< 0.1%
20270424 2
< 0.1%

폐쇄일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3141
Distinct (%)37.3%
Missing1573
Missing (%)15.7%
Infinite0
Infinite (%)0.0%
Mean20142431
Minimum20071115
Maximum20240516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T09:22:51.345258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20071115
5-th percentile20091014
Q120110412
median20130725
Q320170514
95-th percentile20221124
Maximum20240516
Range169401
Interquartile range (IQR)60101

Descriptive statistics

Standard deviation41014.36
Coefficient of variation (CV)0.002036217
Kurtosis-0.56826738
Mean20142431
Median Absolute Deviation (MAD)29798
Skewness0.6902426
Sum1.6974026 × 1011
Variance1.6821777 × 109
MonotonicityNot monotonic
2024-05-18T09:22:51.781371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091116 190
 
1.9%
20100927 86
 
0.9%
20160725 25
 
0.2%
20101213 23
 
0.2%
20110914 21
 
0.2%
20170124 21
 
0.2%
20110420 17
 
0.2%
20110901 16
 
0.2%
20110425 16
 
0.2%
20110823 15
 
0.1%
Other values (3131) 7997
80.0%
(Missing) 1573
 
15.7%
ValueCountFrequency (%)
20071115 1
 
< 0.1%
20080730 1
 
< 0.1%
20090306 1
 
< 0.1%
20090307 2
< 0.1%
20090309 1
 
< 0.1%
20090311 1
 
< 0.1%
20090312 3
< 0.1%
20090313 4
< 0.1%
20090316 1
 
< 0.1%
20090317 2
< 0.1%
ValueCountFrequency (%)
20240516 1
 
< 0.1%
20240514 1
 
< 0.1%
20240513 2
 
< 0.1%
20240508 1
 
< 0.1%
20240507 3
< 0.1%
20240503 2
 
< 0.1%
20240502 1
 
< 0.1%
20240501 3
< 0.1%
20240430 5
0.1%
20240426 1
 
< 0.1%

지점설립일자
Text

MISSING 

Distinct3578
Distinct (%)40.9%
Missing1254
Missing (%)12.5%
Memory size156.2 KiB
2024-05-18T09:22:52.533835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters69968
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1374 ?
Unique (%)15.7%

Sample

1st row20080718
2nd row20131028
3rd row20150120
4th row20090701
5th row20171016
ValueCountFrequency (%)
20090820 19
 
0.2%
20090611 18
 
0.2%
20090514 18
 
0.2%
20090528 16
 
0.2%
20090511 16
 
0.2%
20090821 16
 
0.2%
20090605 14
 
0.2%
20090520 14
 
0.2%
20090507 13
 
0.1%
20090722 13
 
0.1%
Other values (3568) 8589
98.2%
2024-05-18T09:22:53.702855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22662
32.4%
2 15941
22.8%
1 14127
20.2%
3 2808
 
4.0%
9 2683
 
3.8%
7 2560
 
3.7%
6 2405
 
3.4%
5 2319
 
3.3%
8 2266
 
3.2%
4 2191
 
3.1%
Other values (4) 6
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69962
> 99.9%
Space Separator 3
 
< 0.1%
Lowercase Letter 2
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 22662
32.4%
2 15941
22.8%
1 14127
20.2%
3 2808
 
4.0%
9 2683
 
3.8%
7 2560
 
3.7%
6 2405
 
3.4%
5 2319
 
3.3%
8 2266
 
3.2%
4 2191
 
3.1%
Lowercase Letter
ValueCountFrequency (%)
a 1
50.0%
y 1
50.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Uppercase Letter
ValueCountFrequency (%)
M 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69965
> 99.9%
Latin 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 22662
32.4%
2 15941
22.8%
1 14127
20.2%
3 2808
 
4.0%
9 2683
 
3.8%
7 2560
 
3.7%
6 2405
 
3.4%
5 2319
 
3.3%
8 2266
 
3.2%
4 2191
 
3.1%
Latin
ValueCountFrequency (%)
M 1
33.3%
a 1
33.3%
y 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 22662
32.4%
2 15941
22.8%
1 14127
20.2%
3 2808
 
4.0%
9 2683
 
3.8%
7 2560
 
3.7%
6 2405
 
3.4%
5 2319
 
3.3%
8 2266
 
3.2%
4 2191
 
3.1%
Other values (4) 6
 
< 0.1%

본점여부
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
본점
9936 
지점
 
64

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 9936
99.4%
지점 64
 
0.6%

Length

2024-05-18T09:22:54.134164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:22:54.443592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
본점 9936
99.4%
지점 64
 
0.6%

최근수정일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3195
Distinct (%)31.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20153169
Minimum20090518
Maximum20240517
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T09:22:54.834250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090518
5-th percentile20091118
Q120111012
median20140928
Q320190423
95-th percentile20231026
Maximum20240517
Range149999
Interquartile range (IQR)79411

Descriptive statistics

Standard deviation45984.989
Coefficient of variation (CV)0.0022817746
Kurtosis-1.0641055
Mean20153169
Median Absolute Deviation (MAD)30603.5
Skewness0.45040845
Sum2.0153169 × 1011
Variance2.1146192 × 109
MonotonicityNot monotonic
2024-05-18T09:22:55.291358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091117 74
 
0.7%
20100927 57
 
0.6%
20091118 48
 
0.5%
20090609 48
 
0.5%
20160812 37
 
0.4%
20091116 35
 
0.4%
20100330 35
 
0.4%
20090622 32
 
0.3%
20100517 32
 
0.3%
20130621 32
 
0.3%
Other values (3185) 9570
95.7%
ValueCountFrequency (%)
20090518 2
 
< 0.1%
20090519 1
 
< 0.1%
20090521 6
 
0.1%
20090601 3
 
< 0.1%
20090602 1
 
< 0.1%
20090603 6
 
0.1%
20090604 16
 
0.2%
20090605 3
 
< 0.1%
20090608 2
 
< 0.1%
20090609 48
0.5%
ValueCountFrequency (%)
20240517 2
 
< 0.1%
20240516 5
0.1%
20240514 5
0.1%
20240513 2
 
< 0.1%
20240510 3
 
< 0.1%
20240508 5
0.1%
20240507 6
0.1%
20240503 10
0.1%
20240502 8
0.1%
20240501 6
0.1%

Interactions

2024-05-18T09:22:36.368195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:22:30.861090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:22:31.943819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:22:33.355635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:22:34.890062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:22:36.617032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:22:31.017697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:22:32.206129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:22:33.657342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:22:35.166651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:22:36.909927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:22:31.193478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:22:32.481705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:22:33.978931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:22:35.454523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:22:37.251273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:22:31.380104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:22:32.775883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:22:34.274235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:22:35.758698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:22:37.524989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:22:31.666645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:22:33.064527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:22:34.594335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:22:36.069714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T09:22:55.597599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록신청사업영업구분법인여부우편번호등록일자유효기간만료일자폐쇄일자본점여부최근수정일자
등록신청사업1.0000.1020.0000.0390.2230.1580.1620.0000.177
영업구분0.1021.0000.2870.0920.6190.6280.2250.0390.541
법인여부0.0000.2871.0000.0760.3470.2920.2560.1740.344
우편번호0.0390.0920.0761.0000.1700.2090.0810.0000.138
등록일자0.2230.6190.3470.1701.0001.0000.9350.1020.937
유효기간만료일자0.1580.6280.2920.2091.0001.0000.8460.0850.924
폐쇄일자0.1620.2250.2560.0810.9350.8461.0000.0650.985
본점여부0.0000.0390.1740.0000.1020.0850.0651.0000.112
최근수정일자0.1770.5410.3440.1380.9370.9240.9850.1121.000
2024-05-18T09:22:55.917294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
본점여부법인여부등록신청사업영업구분
본점여부1.0000.1110.0000.028
법인여부0.1111.0000.0000.207
등록신청사업0.0000.0001.0000.073
영업구분0.0280.2070.0731.000
2024-05-18T09:22:56.177776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호등록일자유효기간만료일자폐쇄일자최근수정일자등록신청사업영업구분법인여부본점여부
우편번호1.0000.0330.0280.0530.0440.0280.0750.0540.000
등록일자0.0331.0000.9960.9600.9640.1710.3850.2660.078
유효기간만료일자0.0280.9961.0000.9640.9660.1210.3940.2240.065
폐쇄일자0.0530.9600.9641.0000.9910.1620.1320.1960.050
최근수정일자0.0440.9640.9660.9911.0000.1350.3040.2640.086
등록신청사업0.0280.1710.1210.1620.1351.0000.0730.0000.000
영업구분0.0750.3850.3940.1320.3040.0731.0000.2070.028
법인여부0.0540.2660.2240.1960.2640.0000.2071.0000.111
본점여부0.0000.0780.0650.0500.0860.0000.0280.1111.000

Missing values

2024-05-18T09:22:37.807632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T09:22:38.497294image/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.
2024-05-18T09:22:39.026306image/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
29199대부업<NA>2008-서울특별시-03663(대부업)대신개인025886110서울특별시 서초구 서초동 1319번지 13호 현대타워 907호<NA><NA>20080718<NA>2010011820080718본점20100118
4111대부업유효기간만료2013-서울중구-0117(대부업)영풍상사대부개인02-318-5584서울특별시 중구 을지로2가 195번지 3호 한양빌딩서울특별시 중구 명동9길 23, 한양빌딩 6층 712호 (을지로2가)<NA>2019071220220712<NA>20131028본점20220726
345대부중개업영업중2015-서울강남-0023(대부중개업)주식회사 에이디자산운용대부법인02-889-1765서울특별시 강남구 역삼동 706번지 15호 성보빌딩Ⅱ서울특별시 강남구 언주로 432-6, 성보빌딩Ⅱ 4층 019호 (역삼동)<NA>2023091520260915<NA>20150120본점20240411
16816대부업폐업2012-서울영등포-0334(대부업)(주)코리아인포메이션서비스자산관리대부법인0237865825서울특별시 영등포구 여의도동 13번지 13호 크레딧플라자 10층<NA>15001020120522201505222014012920090701본점20140129
8555대부중개업폐업2017-서울강동-00044스마일재무 대부중개개인02-475-1019서울특별시 강동구 성내동 533번지 1호 -202서울특별시 강동구 성내로3가길 49, 202호 (성내동, 호성빌딩)<NA>20171016202010162018090420171016본점20180904
20461대부업유효기간만료2009-서울특별시-02452(대부업)G.P대부개인<NA>서울특별시 광진구 자양동 809번지 강변아이파크 101-405호<NA><NA>2009102320121023<NA>20091023본점20121109
1080대부업폐업2021-서울강서-0046(대부업)(주)홍티경매유튜브대부11호법인.서울특별시 강서구 등촌동 717번지 그레이스힐서울특별시 강서구 양천로 470, 그레이스힐 지하1층 115호-(4)호 (등촌동)<NA>20211119202411192024011020211119본점20240110
1631대부업영업중2023-서울송파-0070(대부업)주식회사 이에스엔젤네트웍스대부법인<NA>서울특별시 송파구 석촌동 276번지 2호 석촌꽃마을빌딩서울특별시 송파구 가락로 102, 석촌꽃마을빌딩 212호 (석촌동)<NA>2023101120261010<NA>20231011본점20231013
14045대부업유효기간만료2012-서울노원-00069한양대부개인02-6081-3722서울특별시 노원구 공릉동 513번지 48호 주인맨션 가동 B01호서울특별시 노원구 동일로184길 35 (공릉동,주인맨션 가동 B01호)13924120120822201508222015082320120822본점20150824
23277대부업<NA>2011-서울금천-0036우리오토대부개인02-862-3132서울특별시 금천구 가산동 371번지 37호 에스티엑스브이타워-507<NA>15302320090623201206232011110220090623본점20111102
등록신청사업영업구분등록증번호상호법인여부사업장 전화번호소재지소재지(도로명)우편번호등록일자유효기간만료일자폐쇄일자지점설립일자본점여부최근수정일자
26549대부업<NA>2007-서울특별시-01324(대부업)대성개인024155377서울특별시 송파구 송파동 180번지 301호<NA>13817020071022<NA>2010102320071016본점20101025
25840대부업<NA>2009-서울특별시-01806(대부업)배태헌대부개인<NA>서울특별시 송파구 송파동 151번지 한양아파트 21-805<NA><NA>20090731<NA>2011012020090731본점20110121
15507대부중개업타시군구이관2012-서울구로-020(대부중개업)아원아이엔디대부중개개인02-2069-1878서울특별시 구로구 신도림동 416번지 26호 3층서울특별시 구로구 신도림로11길 2, 3층 (신도림동)15288720120217201502172014101720120217본점20141017
3506대부업영업중2017-서울종로-00001(대부업)주식회사 우정파이낸스대부법인<NA>서울특별시 종로구 종로1가 24번지 르메이에르종로타운-1016서울특별시 종로구 종로 19, 르메이에르종로타운 1016호 (종로1가)<NA>2022121620251216<NA>20110406본점20221216
8337대부업폐업2012-서울강북-0012(대부업)가나에프엔씨대부개인02-981-5644서울특별시 강북구 수유동 188번지 6호 현광빌딩서울특별시 강북구 한천로 1077, 3층 22호 (수유동, 오피스프렌즈)<NA>20171204202012042018112320120313본점20181126
6331대부업폐업2014-서울서초-0174(대부업)이지자산대부개인02-3486-4329서울특별시 서초구 방배동 451번지 7호 삼원빌딩-405서울특별시 서초구 방배천로4안길 6, 405호 (방배동, 삼원빌딩)<NA>20171024202010242020092120141219본점20200921
5752대부중개업폐업2020-서울금천-0002세움자산관리대부중개개인<NA>서울특별시 금천구 독산동 900번지 8호 서원빌딩서울특별시 금천구 남부순환로 1414, 서원빌딩 305호 (독산동)<NA>20200130202301302021042820200130본점20210428
7022대부중개업폐업2016-서울은평-0031(대부중개업)아이앤유캐피탈대부중개개인02-6406-5986서울특별시 은평구 응암동 97번지 35호 1층서울특별시 은평구 은평로12길 11, 1층 (응암동)<NA>20191002202210022020011420161021본점20200115
4785대부중개업폐업2020-서울중랑-0039(대부중개업)드림파이낸스 대부중개개인<NA>서울특별시 중랑구 묵동 246번지 38호 3층서울특별시 중랑구 중랑역로 149, 3층 (묵동)<NA>20200227202302272022012820200227본점20220128
16842대부업직권취소2008-서울특별시-02057(대부업)우인기획개인028389728서울특별시 관악구 신림동 1479-14<NA><NA>200807292011072920100913<NA>본점20140127

Duplicate rows

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등록신청사업영업구분등록증번호상호법인여부사업장 전화번호소재지소재지(도로명)우편번호등록일자유효기간만료일자폐쇄일자지점설립일자본점여부최근수정일자# duplicates
0대부업<NA>2009-서울특별시-02231(대부업)한빛투자금융대부개인025638488서울특별시 은평구 구산동 177번지 2호 명성골든빌 A-502호<NA><NA>20090918<NA>2010021120090918본점201006043
1대부중개업타시군구이관2013-서울광진-0050(대부중개)ONE PLUS대부중개개인02-2201-8863서울특별시 광진구 자양동 769번지 10호 Y타워-917<NA>14385320130828201608282014032420130828본점201403242
2대부중개업<NA>2009-서울특별시-02581(대부중개업)브이지에프대부중개개인<NA>서울특별시 마포구 도화동 250번지 4호 근신빌딩 본관 5층 505호<NA>12170220091111<NA>2010040520091111본점201007012