Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells19163
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
Author금천구
URLhttps://data.seoul.go.kr/dataList/OA-10173/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 168 (1.7%) missing valuesMissing
사업장 전화번호 has 3356 (33.6%) missing valuesMissing
소재지 has 299 (3.0%) missing valuesMissing
소재지(도로명) has 4786 (47.9%) missing valuesMissing
우편번호 has 5646 (56.5%) missing valuesMissing
유효기간만료일자 has 2050 (20.5%) missing valuesMissing
폐쇄일자 has 1560 (15.6%) missing valuesMissing
지점설립일자 has 1298 (13.0%) missing valuesMissing

Reproduction

Analysis started2024-05-18 05:40:21.490371
Analysis finished2024-05-18 05:40:39.998869
Duration18.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
대부업
6231 
대부중개업
3331 
<NA>
 
438

Length

Max length5
Median length3
Mean length3.71
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대부업 6231
62.3%
대부중개업 3331
33.3%
<NA> 438
 
4.4%

Length

2024-05-18T14:40:40.346405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:40:40.828325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대부업 6231
62.3%
대부중개업 3331
33.3%
na 438
 
4.4%

영업구분
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
3767 
<NA>
2856 
타시군구이관
1172 
유효기간만료
841 
영업중
813 
Other values (3)
551 

Length

Max length6
Median length4
Mean length3.5683
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3767
37.7%
<NA> 2856
28.6%
타시군구이관 1172
 
11.7%
유효기간만료 841
 
8.4%
영업중 813
 
8.1%
직권취소 548
 
5.5%
갱신등록불가 2
 
< 0.1%
영업정지 1
 
< 0.1%

Length

2024-05-18T14:40:41.397468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:40:41.773793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3767
37.7%
na 2856
28.6%
타시군구이관 1172
 
11.7%
유효기간만료 841
 
8.4%
영업중 813
 
8.1%
직권취소 548
 
5.5%
갱신등록불가 2
 
< 0.1%
영업정지 1
 
< 0.1%

등록증번호
Text

MISSING 

Distinct9784
Distinct (%)99.5%
Missing168
Missing (%)1.7%
Memory size156.2 KiB
2024-05-18T14:40:42.483194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length27
Mean length19.518206
Min length7

Characters and Unicode

Total characters191903
Distinct characters86
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

Unique9739 ?
Unique (%)99.1%

Sample

1st row2016-서울중랑-0018(대부중개업)
2nd row2016-서울영등포-0803(대부업)
3rd row2010-서울서초-0047(대부업)
4th row2012-서울강남-0035
5th row2011-서울강북-0043
ValueCountFrequency (%)
2010-서울 22
 
0.2%
2011-서울특별시 17
 
0.2%
2012-서울특별시 15
 
0.2%
2015-서울특별시 10
 
0.1%
2013-서울특별시 9
 
0.1%
2016-서울특별시 7
 
0.1%
대부업 7
 
0.1%
2014-서울특별시 7
 
0.1%
2020-서울특별시 5
 
0.1%
2017-서울특별시 5
 
0.1%
Other values (9761) 9865
99.0%
2024-05-18T14:40:43.600297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 33891
17.7%
- 19655
 
10.2%
2 15807
 
8.2%
1 11878
 
6.2%
10880
 
5.7%
9809
 
5.1%
8503
 
4.4%
( 8235
 
4.3%
8197
 
4.3%
) 8185
 
4.3%
Other values (76) 56863
29.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82684
43.1%
Other Letter 73006
38.0%
Dash Punctuation 19655
 
10.2%
Open Punctuation 8235
 
4.3%
Close Punctuation 8185
 
4.3%
Space Separator 138
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10880
14.9%
9809
13.4%
8503
11.6%
8197
11.2%
7975
10.9%
3484
 
4.8%
2866
 
3.9%
2537
 
3.5%
2527
 
3.5%
2527
 
3.5%
Other values (62) 13701
18.8%
Decimal Number
ValueCountFrequency (%)
0 33891
41.0%
2 15807
19.1%
1 11878
 
14.4%
3 3699
 
4.5%
8 3127
 
3.8%
4 3058
 
3.7%
9 2880
 
3.5%
6 2792
 
3.4%
7 2788
 
3.4%
5 2764
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 19655
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8235
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8185
100.0%
Space Separator
ValueCountFrequency (%)
138
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 118897
62.0%
Hangul 73006
38.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10880
14.9%
9809
13.4%
8503
11.6%
8197
11.2%
7975
10.9%
3484
 
4.8%
2866
 
3.9%
2537
 
3.5%
2527
 
3.5%
2527
 
3.5%
Other values (62) 13701
18.8%
Common
ValueCountFrequency (%)
0 33891
28.5%
- 19655
16.5%
2 15807
13.3%
1 11878
 
10.0%
( 8235
 
6.9%
) 8185
 
6.9%
3 3699
 
3.1%
8 3127
 
2.6%
4 3058
 
2.6%
9 2880
 
2.4%
Other values (4) 8482
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 118897
62.0%
Hangul 73006
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 33891
28.5%
- 19655
16.5%
2 15807
13.3%
1 11878
 
10.0%
( 8235
 
6.9%
) 8185
 
6.9%
3 3699
 
3.1%
8 3127
 
2.6%
4 3058
 
2.6%
9 2880
 
2.4%
Other values (4) 8482
 
7.1%
Hangul
ValueCountFrequency (%)
10880
14.9%
9809
13.4%
8503
11.6%
8197
11.2%
7975
10.9%
3484
 
4.8%
2866
 
3.9%
2537
 
3.5%
2527
 
3.5%
2527
 
3.5%
Other values (62) 13701
18.8%

상호
Text

Distinct8679
Distinct (%)86.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T14:40:44.112054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length30
Mean length7.7233
Min length1

Characters and Unicode

Total characters77233
Distinct characters759
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7618 ?
Unique (%)76.2%

Sample

1st row한국이지컨설팅 대부중개
2nd row소망대부
3rd row제이에스캐피탈대부
4th row동원대부
5th row위드피플대부중개
ValueCountFrequency (%)
주식회사 794
 
6.7%
대부중개 298
 
2.5%
대부 272
 
2.3%
유한회사 58
 
0.5%
캐피탈 21
 
0.2%
대부업 20
 
0.2%
미래 14
 
0.1%
13
 
0.1%
대부중개업 11
 
0.1%
loan 11
 
0.1%
Other values (8679) 10329
87.2%
2024-05-18T14:40:45.052434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8469
 
11.0%
8110
 
10.5%
2708
 
3.5%
2306
 
3.0%
2061
 
2.7%
2047
 
2.7%
) 1934
 
2.5%
1932
 
2.5%
( 1924
 
2.5%
1847
 
2.4%
Other values (749) 43895
56.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67711
87.7%
Uppercase Letter 2267
 
2.9%
Close Punctuation 1934
 
2.5%
Open Punctuation 1924
 
2.5%
Space Separator 1847
 
2.4%
Lowercase Letter 1041
 
1.3%
Other Punctuation 238
 
0.3%
Decimal Number 233
 
0.3%
Dash Punctuation 28
 
< 0.1%
Other Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8469
 
12.5%
8110
 
12.0%
2708
 
4.0%
2306
 
3.4%
2061
 
3.0%
2047
 
3.0%
1932
 
2.9%
1345
 
2.0%
1159
 
1.7%
1033
 
1.5%
Other values (678) 36541
54.0%
Uppercase Letter
ValueCountFrequency (%)
S 293
 
12.9%
K 198
 
8.7%
C 169
 
7.5%
M 160
 
7.1%
J 152
 
6.7%
H 141
 
6.2%
L 108
 
4.8%
B 97
 
4.3%
N 97
 
4.3%
G 94
 
4.1%
Other values (14) 758
33.4%
Lowercase Letter
ValueCountFrequency (%)
e 127
12.2%
n 123
11.8%
o 117
11.2%
a 99
 
9.5%
i 73
 
7.0%
t 57
 
5.5%
l 53
 
5.1%
c 48
 
4.6%
s 47
 
4.5%
r 38
 
3.7%
Other values (14) 259
24.9%
Decimal Number
ValueCountFrequency (%)
1 87
37.3%
2 37
15.9%
4 29
 
12.4%
9 25
 
10.7%
5 15
 
6.4%
3 12
 
5.2%
0 10
 
4.3%
7 9
 
3.9%
6 6
 
2.6%
8 3
 
1.3%
Other Punctuation
ValueCountFrequency (%)
. 128
53.8%
& 89
37.4%
, 8
 
3.4%
? 7
 
2.9%
* 4
 
1.7%
' 1
 
0.4%
@ 1
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 1934
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1924
100.0%
Space Separator
ValueCountFrequency (%)
1847
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Other Symbol
ValueCountFrequency (%)
7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67700
87.7%
Common 6207
 
8.0%
Latin 3308
 
4.3%
Han 18
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8469
 
12.5%
8110
 
12.0%
2708
 
4.0%
2306
 
3.4%
2061
 
3.0%
2047
 
3.0%
1932
 
2.9%
1345
 
2.0%
1159
 
1.7%
1033
 
1.5%
Other values (661) 36530
54.0%
Latin
ValueCountFrequency (%)
S 293
 
8.9%
K 198
 
6.0%
C 169
 
5.1%
M 160
 
4.8%
J 152
 
4.6%
H 141
 
4.3%
e 127
 
3.8%
n 123
 
3.7%
o 117
 
3.5%
L 108
 
3.3%
Other values (38) 1720
52.0%
Common
ValueCountFrequency (%)
) 1934
31.2%
( 1924
31.0%
1847
29.8%
. 128
 
2.1%
& 89
 
1.4%
1 87
 
1.4%
2 37
 
0.6%
4 29
 
0.5%
- 28
 
0.5%
9 25
 
0.4%
Other values (12) 79
 
1.3%
Han
ValueCountFrequency (%)
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
Other values (8) 8
44.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67693
87.6%
ASCII 9515
 
12.3%
CJK 18
 
< 0.1%
None 7
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
8469
 
12.5%
8110
 
12.0%
2708
 
4.0%
2306
 
3.4%
2061
 
3.0%
2047
 
3.0%
1932
 
2.9%
1345
 
2.0%
1159
 
1.7%
1033
 
1.5%
Other values (660) 36523
54.0%
ASCII
ValueCountFrequency (%)
) 1934
20.3%
( 1924
20.2%
1847
19.4%
S 293
 
3.1%
K 198
 
2.1%
C 169
 
1.8%
M 160
 
1.7%
J 152
 
1.6%
H 141
 
1.5%
. 128
 
1.3%
Other values (60) 2569
27.0%
None
ValueCountFrequency (%)
7
100.0%
CJK
ValueCountFrequency (%)
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
Other values (8) 8
44.4%

법인여부
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
개인
7178 
법인
2822 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 7178
71.8%
법인 2822
 
28.2%

Length

2024-05-18T14:40:45.505781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:40:45.809511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 7178
71.8%
법인 2822
 
28.2%
Distinct5872
Distinct (%)88.4%
Missing3356
Missing (%)33.6%
Memory size156.2 KiB
2024-05-18T14:40:46.266746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length41
Mean length10.559452
Min length1

Characters and Unicode

Total characters70157
Distinct characters34
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5247 ?
Unique (%)79.0%

Sample

1st row070-8743-5130
2nd row02445-1300
3rd row027322567
4th row0232850147
5th row070-4055-9009
ValueCountFrequency (%)
02 306
 
4.1%
62
 
0.8%
070 45
 
0.6%
010 9
 
0.1%
1688 8
 
0.1%
2212 6
 
0.1%
2209 6
 
0.1%
0 6
 
0.1%
432 6
 
0.1%
070-4814-3914 5
 
0.1%
Other values (6180) 7026
93.9%
2024-05-18T14:40:47.327987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11432
16.3%
2 10301
14.7%
- 7060
10.1%
5 5840
8.3%
7 5467
7.8%
1 5099
7.3%
6 5070
7.2%
3 5010
7.1%
8 4830
6.9%
4 4790
6.8%
Other values (24) 5258
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61891
88.2%
Dash Punctuation 7060
 
10.1%
Space Separator 944
 
1.3%
Other Punctuation 126
 
0.2%
Close Punctuation 65
 
0.1%
Math Symbol 28
 
< 0.1%
Open Punctuation 23
 
< 0.1%
Other Letter 16
 
< 0.1%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
12.5%
2
12.5%
2
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (3) 3
18.8%
Decimal Number
ValueCountFrequency (%)
0 11432
18.5%
2 10301
16.6%
5 5840
9.4%
7 5467
8.8%
1 5099
8.2%
6 5070
8.2%
3 5010
8.1%
8 4830
7.8%
4 4790
7.7%
9 4052
 
6.5%
Other Punctuation
ValueCountFrequency (%)
* 56
44.4%
/ 45
35.7%
. 25
19.8%
Uppercase Letter
ValueCountFrequency (%)
K 2
50.0%
S 1
25.0%
T 1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 7060
100.0%
Space Separator
ValueCountFrequency (%)
944
100.0%
Close Punctuation
ValueCountFrequency (%)
) 65
100.0%
Math Symbol
ValueCountFrequency (%)
~ 28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70137
> 99.9%
Hangul 16
 
< 0.1%
Latin 4
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11432
16.3%
2 10301
14.7%
- 7060
10.1%
5 5840
8.3%
7 5467
7.8%
1 5099
7.3%
6 5070
7.2%
3 5010
7.1%
8 4830
6.9%
4 4790
6.8%
Other values (8) 5238
7.5%
Hangul
ValueCountFrequency (%)
2
12.5%
2
12.5%
2
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (3) 3
18.8%
Latin
ValueCountFrequency (%)
K 2
50.0%
S 1
25.0%
T 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70141
> 99.9%
Hangul 16
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11432
16.3%
2 10301
14.7%
- 7060
10.1%
5 5840
8.3%
7 5467
7.8%
1 5099
7.3%
6 5070
7.2%
3 5010
7.1%
8 4830
6.9%
4 4790
6.8%
Other values (11) 5242
7.5%
Hangul
ValueCountFrequency (%)
2
12.5%
2
12.5%
2
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (3) 3
18.8%

소재지
Text

MISSING 

Distinct8637
Distinct (%)89.0%
Missing299
Missing (%)3.0%
Memory size156.2 KiB
2024-05-18T14:40:48.039819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length49
Mean length31.453252
Min length15

Characters and Unicode

Total characters305128
Distinct characters630
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

Unique7880 ?
Unique (%)81.2%

Sample

1st row서울특별시 중랑구 신내동 539번지 9호
2nd row서울특별시 서초구 양재동 8번지 56호 서진빌라 지층 102호
3rd row서울특별시 강남구 일원동 734번지 105 상록수아파트-103
4th row서울특별시 강북구 수유동 48번지 23호 규봉빌딩 9층
5th row서울특별시 종로구 종로1가 24번지 르메이에르빌딩 410-1호
ValueCountFrequency (%)
서울특별시 9698
 
17.0%
강남구 1640
 
2.9%
서초구 947
 
1.7%
1호 747
 
1.3%
역삼동 720
 
1.3%
송파구 650
 
1.1%
서초동 575
 
1.0%
중구 556
 
1.0%
영등포구 467
 
0.8%
2호 461
 
0.8%
Other values (9474) 40725
71.2%
2024-05-18T14:40:49.210444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
67734
22.2%
1 13493
 
4.4%
12051
 
3.9%
11076
 
3.6%
10493
 
3.4%
9950
 
3.3%
9742
 
3.2%
9709
 
3.2%
9699
 
3.2%
2 8923
 
2.9%
Other values (620) 142258
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 166845
54.7%
Space Separator 67734
22.2%
Decimal Number 63348
 
20.8%
Dash Punctuation 5461
 
1.8%
Uppercase Letter 1152
 
0.4%
Other Punctuation 241
 
0.1%
Lowercase Letter 118
 
< 0.1%
Close Punctuation 98
 
< 0.1%
Open Punctuation 93
 
< 0.1%
Letter Number 30
 
< 0.1%
Other values (2) 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12051
 
7.2%
11076
 
6.6%
10493
 
6.3%
9950
 
6.0%
9742
 
5.8%
9709
 
5.8%
9699
 
5.8%
8592
 
5.1%
8388
 
5.0%
7884
 
4.7%
Other values (542) 69261
41.5%
Uppercase Letter
ValueCountFrequency (%)
B 252
21.9%
A 224
19.4%
D 80
 
6.9%
S 78
 
6.8%
C 54
 
4.7%
I 50
 
4.3%
T 49
 
4.3%
K 47
 
4.1%
L 38
 
3.3%
G 35
 
3.0%
Other values (16) 245
21.3%
Lowercase Letter
ValueCountFrequency (%)
e 21
17.8%
i 14
11.9%
n 9
 
7.6%
t 9
 
7.6%
r 8
 
6.8%
l 8
 
6.8%
s 7
 
5.9%
k 7
 
5.9%
c 5
 
4.2%
a 5
 
4.2%
Other values (12) 25
21.2%
Decimal Number
ValueCountFrequency (%)
1 13493
21.3%
2 8923
14.1%
0 8030
12.7%
3 6917
10.9%
4 5782
9.1%
5 4949
 
7.8%
6 4506
 
7.1%
7 4080
 
6.4%
8 3374
 
5.3%
9 3294
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 87
36.1%
/ 83
34.4%
. 66
27.4%
& 2
 
0.8%
* 1
 
0.4%
# 1
 
0.4%
1
 
0.4%
Letter Number
ValueCountFrequency (%)
24
80.0%
3
 
10.0%
3
 
10.0%
Math Symbol
ValueCountFrequency (%)
~ 3
42.9%
> 2
28.6%
< 2
28.6%
Close Punctuation
ValueCountFrequency (%)
) 97
99.0%
] 1
 
1.0%
Open Punctuation
ValueCountFrequency (%)
( 92
98.9%
[ 1
 
1.1%
Space Separator
ValueCountFrequency (%)
67734
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5461
100.0%
Other Number
ValueCountFrequency (%)
½ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 166843
54.7%
Common 136983
44.9%
Latin 1300
 
0.4%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12051
 
7.2%
11076
 
6.6%
10493
 
6.3%
9950
 
6.0%
9742
 
5.8%
9709
 
5.8%
9699
 
5.8%
8592
 
5.1%
8388
 
5.0%
7884
 
4.7%
Other values (540) 69259
41.5%
Latin
ValueCountFrequency (%)
B 252
19.4%
A 224
17.2%
D 80
 
6.2%
S 78
 
6.0%
C 54
 
4.2%
I 50
 
3.8%
T 49
 
3.8%
K 47
 
3.6%
L 38
 
2.9%
G 35
 
2.7%
Other values (41) 393
30.2%
Common
ValueCountFrequency (%)
67734
49.4%
1 13493
 
9.9%
2 8923
 
6.5%
0 8030
 
5.9%
3 6917
 
5.0%
4 5782
 
4.2%
- 5461
 
4.0%
5 4949
 
3.6%
6 4506
 
3.3%
7 4080
 
3.0%
Other values (17) 7108
 
5.2%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 166843
54.7%
ASCII 138251
45.3%
Number Forms 30
 
< 0.1%
None 2
 
< 0.1%
CJK 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
67734
49.0%
1 13493
 
9.8%
2 8923
 
6.5%
0 8030
 
5.8%
3 6917
 
5.0%
4 5782
 
4.2%
- 5461
 
4.0%
5 4949
 
3.6%
6 4506
 
3.3%
7 4080
 
3.0%
Other values (63) 8376
 
6.1%
Hangul
ValueCountFrequency (%)
12051
 
7.2%
11076
 
6.6%
10493
 
6.3%
9950
 
6.0%
9742
 
5.8%
9709
 
5.8%
9699
 
5.8%
8592
 
5.1%
8388
 
5.0%
7884
 
4.7%
Other values (540) 69259
41.5%
Number Forms
ValueCountFrequency (%)
24
80.0%
3
 
10.0%
3
 
10.0%
None
ValueCountFrequency (%)
½ 1
50.0%
1
50.0%
CJK
ValueCountFrequency (%)
1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%

소재지(도로명)
Text

MISSING 

Distinct4741
Distinct (%)90.9%
Missing4786
Missing (%)47.9%
Memory size156.2 KiB
2024-05-18T14:40:49.971936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length54
Mean length37.209628
Min length20

Characters and Unicode

Total characters194011
Distinct characters613
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

Unique4318 ?
Unique (%)82.8%

Sample

1st row서울특별시 중랑구 신내로8길 5-6, C동 B101호 (신내동)
2nd row서울특별시 영등포구 대림로31가길 7, 1층 (대림동)
3rd row서울특별시 강남구 광평로10길 15, 105동 103호 (일원동, 상록수아파트)
4th row서울특별시 강북구 덕릉로24길 6 (수유동,규봉빌딩 9층)
5th row서울특별시 송파구 위례성대로2길 8, 새천년잠실헤리츠오피스텔 1동 1120호 (방이동)
ValueCountFrequency (%)
서울특별시 5213
 
14.1%
강남구 962
 
2.6%
서초구 568
 
1.5%
2층 450
 
1.2%
역삼동 406
 
1.1%
서초동 372
 
1.0%
3층 363
 
1.0%
송파구 346
 
0.9%
영등포구 327
 
0.9%
4층 303
 
0.8%
Other values (6646) 27591
74.8%
2024-05-18T14:40:51.158259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31705
 
16.3%
1 7400
 
3.8%
, 7163
 
3.7%
6857
 
3.5%
6818
 
3.5%
5785
 
3.0%
5725
 
3.0%
2 5454
 
2.8%
5408
 
2.8%
5267
 
2.7%
Other values (603) 106429
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 107984
55.7%
Decimal Number 34611
 
17.8%
Space Separator 31705
 
16.3%
Other Punctuation 7180
 
3.7%
Close Punctuation 5254
 
2.7%
Open Punctuation 5253
 
2.7%
Dash Punctuation 1044
 
0.5%
Uppercase Letter 845
 
0.4%
Lowercase Letter 98
 
0.1%
Letter Number 27
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6857
 
6.4%
6818
 
6.3%
5785
 
5.4%
5725
 
5.3%
5408
 
5.0%
5267
 
4.9%
5225
 
4.8%
5213
 
4.8%
4232
 
3.9%
2734
 
2.5%
Other values (529) 54720
50.7%
Uppercase Letter
ValueCountFrequency (%)
B 176
20.8%
A 120
14.2%
S 74
 
8.8%
T 47
 
5.6%
C 44
 
5.2%
E 42
 
5.0%
I 40
 
4.7%
K 39
 
4.6%
L 36
 
4.3%
G 33
 
3.9%
Other values (15) 194
23.0%
Lowercase Letter
ValueCountFrequency (%)
e 15
15.3%
r 9
 
9.2%
i 9
 
9.2%
n 8
 
8.2%
t 8
 
8.2%
c 6
 
6.1%
l 5
 
5.1%
w 5
 
5.1%
b 5
 
5.1%
s 4
 
4.1%
Other values (11) 24
24.5%
Decimal Number
ValueCountFrequency (%)
1 7400
21.4%
2 5454
15.8%
0 4516
13.0%
3 4149
12.0%
4 2947
 
8.5%
5 2676
 
7.7%
6 2221
 
6.4%
7 1909
 
5.5%
8 1745
 
5.0%
9 1594
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 7163
99.8%
. 11
 
0.2%
& 2
 
< 0.1%
@ 2
 
< 0.1%
# 1
 
< 0.1%
/ 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
18
66.7%
5
 
18.5%
4
 
14.8%
Math Symbol
ValueCountFrequency (%)
~ 4
40.0%
< 3
30.0%
> 3
30.0%
Close Punctuation
ValueCountFrequency (%)
) 5253
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 5252
> 99.9%
[ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
31705
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1044
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 107984
55.7%
Common 85057
43.8%
Latin 970
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6857
 
6.4%
6818
 
6.3%
5785
 
5.4%
5725
 
5.3%
5408
 
5.0%
5267
 
4.9%
5225
 
4.8%
5213
 
4.8%
4232
 
3.9%
2734
 
2.5%
Other values (529) 54720
50.7%
Latin
ValueCountFrequency (%)
B 176
18.1%
A 120
 
12.4%
S 74
 
7.6%
T 47
 
4.8%
C 44
 
4.5%
E 42
 
4.3%
I 40
 
4.1%
K 39
 
4.0%
L 36
 
3.7%
G 33
 
3.4%
Other values (39) 319
32.9%
Common
ValueCountFrequency (%)
31705
37.3%
1 7400
 
8.7%
, 7163
 
8.4%
2 5454
 
6.4%
) 5253
 
6.2%
( 5252
 
6.2%
0 4516
 
5.3%
3 4149
 
4.9%
4 2947
 
3.5%
5 2676
 
3.1%
Other values (15) 8542
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 107984
55.7%
ASCII 86000
44.3%
Number Forms 27
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31705
36.9%
1 7400
 
8.6%
, 7163
 
8.3%
2 5454
 
6.3%
) 5253
 
6.1%
( 5252
 
6.1%
0 4516
 
5.3%
3 4149
 
4.8%
4 2947
 
3.4%
5 2676
 
3.1%
Other values (61) 9485
 
11.0%
Hangul
ValueCountFrequency (%)
6857
 
6.4%
6818
 
6.3%
5785
 
5.4%
5725
 
5.3%
5408
 
5.0%
5267
 
4.9%
5225
 
4.8%
5213
 
4.8%
4232
 
3.9%
2734
 
2.5%
Other values (529) 54720
50.7%
Number Forms
ValueCountFrequency (%)
18
66.7%
5
 
18.5%
4
 
14.8%

우편번호
Real number (ℝ)

MISSING 

Distinct1356
Distinct (%)31.1%
Missing5646
Missing (%)56.5%
Infinite0
Infinite (%)0.0%
Mean136490.93
Minimum3163
Maximum423060
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T14:40:51.865281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3163
5-th percentile110121
Q1132030
median136095
Q3143190
95-th percentile157031
Maximum423060
Range419897
Interquartile range (IQR)11160

Descriptive statistics

Standard deviation15368.411
Coefficient of variation (CV)0.11259657
Kurtosis55.568626
Mean136490.93
Median Absolute Deviation (MAD)5219
Skewness1.3738269
Sum5.9428153 × 108
Variance2.3618806 × 108
MonotonicityNot monotonic
2024-05-18T14:40:52.278946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
135080 179
 
1.8%
137070 135
 
1.4%
157010 58
 
0.6%
135010 55
 
0.5%
152050 54
 
0.5%
151050 52
 
0.5%
151015 51
 
0.5%
139200 41
 
0.4%
158070 41
 
0.4%
142100 41
 
0.4%
Other values (1346) 3647
36.5%
(Missing) 5646
56.5%
ValueCountFrequency (%)
3163 1
< 0.1%
4534 1
< 0.1%
4537 1
< 0.1%
4538 1
< 0.1%
4554 1
< 0.1%
4801 1
< 0.1%
100011 2
< 0.1%
100012 1
< 0.1%
100013 2
< 0.1%
100014 2
< 0.1%
ValueCountFrequency (%)
423060 1
 
< 0.1%
403866 1
 
< 0.1%
158871 2
 
< 0.1%
158864 5
0.1%
158860 6
0.1%
158859 1
 
< 0.1%
158857 1
 
< 0.1%
158849 1
 
< 0.1%
158845 1
 
< 0.1%
158838 1
 
< 0.1%

등록일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3554
Distinct (%)35.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20136854
Minimum20060306
Maximum20240516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T14:40:52.653186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060306
5-th percentile20070828
Q120091126
median20130228
Q320170828
95-th percentile20230217
Maximum20240516
Range180210
Interquartile range (IQR)79702

Descriptive statistics

Standard deviation49033.344
Coefficient of variation (CV)0.0024350052
Kurtosis-0.925045
Mean20136854
Median Absolute Deviation (MAD)39563
Skewness0.45190261
Sum2.0136854 × 1011
Variance2.4042688 × 109
MonotonicityNot monotonic
2024-05-18T14:40:53.066996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20080814 30
 
0.3%
20080818 25
 
0.2%
20080926 19
 
0.2%
20080731 18
 
0.2%
20081229 16
 
0.2%
20110808 15
 
0.1%
20080806 14
 
0.1%
20081222 14
 
0.1%
20080805 14
 
0.1%
20110711 13
 
0.1%
Other values (3544) 9822
98.2%
ValueCountFrequency (%)
20060306 2
< 0.1%
20060308 1
 
< 0.1%
20060310 1
 
< 0.1%
20060320 4
< 0.1%
20060323 3
< 0.1%
20060324 2
< 0.1%
20060329 1
 
< 0.1%
20060331 1
 
< 0.1%
20060405 2
< 0.1%
20060407 4
< 0.1%
ValueCountFrequency (%)
20240516 4
< 0.1%
20240514 1
 
< 0.1%
20240507 3
< 0.1%
20240503 1
 
< 0.1%
20240502 1
 
< 0.1%
20240430 1
 
< 0.1%
20240425 1
 
< 0.1%
20240424 4
< 0.1%
20240422 5
0.1%
20240418 2
 
< 0.1%

유효기간만료일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3321
Distinct (%)41.8%
Missing2050
Missing (%)20.5%
Infinite0
Infinite (%)0.0%
Mean20181560
Minimum20100112
Maximum20270516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T14:40:53.554936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100112
5-th percentile20120323
Q120141019
median20180103
Q320220225
95-th percentile20260509
Maximum20270516
Range170404
Interquartile range (IQR)79206

Descriptive statistics

Standard deviation44616.073
Coefficient of variation (CV)0.0022107346
Kurtosis-1.0030199
Mean20181560
Median Absolute Deviation (MAD)39183
Skewness0.31739155
Sum1.604434 × 1011
Variance1.990594 × 109
MonotonicityNot monotonic
2024-05-18T14:40:54.096376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20140831 18
 
0.2%
20140711 13
 
0.1%
20140808 13
 
0.1%
20190718 12
 
0.1%
20150109 12
 
0.1%
20140816 12
 
0.1%
20150112 11
 
0.1%
20140131 11
 
0.1%
20170602 11
 
0.1%
20150531 10
 
0.1%
Other values (3311) 7827
78.3%
(Missing) 2050
 
20.5%
ValueCountFrequency (%)
20100112 1
< 0.1%
20100405 1
< 0.1%
20100411 1
< 0.1%
20100418 1
< 0.1%
20100419 1
< 0.1%
20100501 1
< 0.1%
20100515 1
< 0.1%
20100528 2
< 0.1%
20100608 1
< 0.1%
20100615 1
< 0.1%
ValueCountFrequency (%)
20270516 4
< 0.1%
20270514 1
 
< 0.1%
20270507 2
< 0.1%
20270506 1
 
< 0.1%
20270503 1
 
< 0.1%
20270501 1
 
< 0.1%
20270430 1
 
< 0.1%
20270425 1
 
< 0.1%
20270424 4
< 0.1%
20270422 1
 
< 0.1%

폐쇄일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3124
Distinct (%)37.0%
Missing1560
Missing (%)15.6%
Infinite0
Infinite (%)0.0%
Mean20142474
Minimum20060920
Maximum20240514
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T14:40:54.694910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060920
5-th percentile20090901
Q120110411
median20130722
Q320170549
95-th percentile20221205
Maximum20240514
Range179594
Interquartile range (IQR)60137.75

Descriptive statistics

Standard deviation41462.113
Coefficient of variation (CV)0.0020584419
Kurtosis-0.59544851
Mean20142474
Median Absolute Deviation (MAD)29805.5
Skewness0.68101258
Sum1.7000248 × 1011
Variance1.7191068 × 109
MonotonicityNot monotonic
2024-05-18T14:40:55.133311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091116 222
 
2.2%
20100927 80
 
0.8%
20160725 21
 
0.2%
20101213 17
 
0.2%
20110420 16
 
0.2%
20110425 16
 
0.2%
20110914 16
 
0.2%
20111007 13
 
0.1%
20101126 13
 
0.1%
20131210 13
 
0.1%
Other values (3114) 8013
80.1%
(Missing) 1560
 
15.6%
ValueCountFrequency (%)
20060920 1
 
< 0.1%
20071030 1
 
< 0.1%
20071115 1
 
< 0.1%
20090219 1
 
< 0.1%
20090220 1
 
< 0.1%
20090305 2
< 0.1%
20090306 2
< 0.1%
20090307 2
< 0.1%
20090309 2
< 0.1%
20090311 3
< 0.1%
ValueCountFrequency (%)
20240514 1
 
< 0.1%
20240513 4
< 0.1%
20240510 3
< 0.1%
20240509 3
< 0.1%
20240507 1
 
< 0.1%
20240503 1
 
< 0.1%
20240501 3
< 0.1%
20240430 3
< 0.1%
20240429 2
< 0.1%
20240426 1
 
< 0.1%

지점설립일자
Date

MISSING 

Distinct3571
Distinct (%)41.0%
Missing1298
Missing (%)13.0%
Memory size156.2 KiB
Minimum1905-06-28 00:00:00
Maximum2024-05-16 00:00:00
2024-05-18T14:40:55.703056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:40:56.189641image/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

2024-05-18T14:40:56.864461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:40:57.356416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
본점 9923
99.2%
지점 77
 
0.8%

최근수정일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3174
Distinct (%)31.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20153149
Minimum20090518
Maximum20240517
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T14:40:58.155568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090518
5-th percentile20091117
Q120111013
median20140911
Q320190511
95-th percentile20231030
Maximum20240517
Range149999
Interquartile range (IQR)79497.75

Descriptive statistics

Standard deviation46199.281
Coefficient of variation (CV)0.0022924101
Kurtosis-1.0817331
Mean20153149
Median Absolute Deviation (MAD)30683
Skewness0.43901731
Sum2.0153149 × 1011
Variance2.1343736 × 109
MonotonicityNot monotonic
2024-05-18T14:40:59.135407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091117 80
 
0.8%
20091118 59
 
0.6%
20090609 56
 
0.6%
20100927 54
 
0.5%
20100330 52
 
0.5%
20091116 42
 
0.4%
20091119 34
 
0.3%
20090622 34
 
0.3%
20090611 32
 
0.3%
20100517 32
 
0.3%
Other values (3164) 9525
95.2%
ValueCountFrequency (%)
20090518 1
 
< 0.1%
20090519 1
 
< 0.1%
20090521 2
 
< 0.1%
20090601 3
 
< 0.1%
20090602 4
 
< 0.1%
20090603 14
 
0.1%
20090604 19
 
0.2%
20090605 4
 
< 0.1%
20090608 3
 
< 0.1%
20090609 56
0.6%
ValueCountFrequency (%)
20240517 2
 
< 0.1%
20240516 6
0.1%
20240514 3
 
< 0.1%
20240513 6
0.1%
20240510 3
 
< 0.1%
20240509 8
0.1%
20240508 4
< 0.1%
20240507 5
0.1%
20240503 6
0.1%
20240502 3
 
< 0.1%

Interactions

2024-05-18T14:40:35.601522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:40:29.465525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:40:31.273443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:40:32.708026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:40:34.259224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:40:35.959110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:40:29.802876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:40:31.556501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:40:33.191540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:40:34.520258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:40:36.269212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:40:30.168732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:40:31.855355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:40:33.484123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:40:34.812411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:40:36.674873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:40:30.575328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:40:32.141221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:40:33.781769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:40:35.032378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:40:37.056301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:40:30.925457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:40:32.420267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:40:34.007421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:40:35.258222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T14:40:59.717570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록신청사업영업구분법인여부우편번호등록일자유효기간만료일자폐쇄일자본점여부최근수정일자
등록신청사업1.0000.0620.0440.0000.2610.1780.2600.0150.208
영업구분0.0621.0000.1870.0590.5810.5850.1740.0400.479
법인여부0.0440.1871.0000.0280.3380.2640.2600.2010.343
우편번호0.0000.0590.0281.0000.2240.2210.1660.0000.214
등록일자0.2610.5810.3380.2241.0000.9860.9350.1010.938
유효기간만료일자0.1780.5850.2640.2210.9861.0000.8480.0930.845
폐쇄일자0.2600.1740.2600.1660.9350.8481.0000.0750.988
본점여부0.0150.0400.2010.0000.1010.0930.0751.0000.119
최근수정일자0.2080.4790.3430.2140.9380.8450.9880.1191.000
2024-05-18T14:41:00.405431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법인여부본점여부등록신청사업영업구분
법인여부1.0000.1290.0280.200
본점여부0.1291.0000.0090.042
등록신청사업0.0280.0091.0000.066
영업구분0.2000.0420.0661.000
2024-05-18T14:41:00.866238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호등록일자유효기간만료일자폐쇄일자최근수정일자등록신청사업영업구분법인여부본점여부
우편번호1.0000.0200.0450.0350.0240.0000.0430.0060.000
등록일자0.0201.0000.9960.9620.9660.2000.3420.2590.077
유효기간만료일자0.0450.9961.0000.9640.9660.1370.3460.2020.071
폐쇄일자0.0350.9620.9641.0000.9920.1990.1070.1990.058
최근수정일자0.0240.9660.9660.9921.0000.1590.2770.2630.091
등록신청사업0.0000.2000.1370.1990.1591.0000.0660.0280.009
영업구분0.0430.3420.3460.1070.2770.0661.0000.2000.042
법인여부0.0060.2590.2020.1990.2630.0280.2001.0000.129
본점여부0.0000.0770.0710.0580.0910.0090.0420.1291.000

Missing values

2024-05-18T14:40:37.626760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T14:40:38.553005image/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.
2024-05-18T14:40:39.474481image/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
12599대부중개업폐업2016-서울중랑-0018(대부중개업)한국이지컨설팅 대부중개개인<NA>서울특별시 중랑구 신내동 539번지 9호서울특별시 중랑구 신내로8길 5-6, C동 B101호 (신내동)<NA>20160422201904222016080420160422본점20160804
11006대부업폐업2016-서울영등포-0803(대부업)소망대부개인<NA><NA>서울특별시 영등포구 대림로31가길 7, 1층 (대림동)<NA>20160324201903242017022120160324본점20170222
20163대부업폐업2010-서울서초-0047(대부업)제이에스캐피탈대부개인070-8743-5130서울특별시 서초구 양재동 8번지 56호 서진빌라 지층 102호<NA>13713020100329201303292012121320100329본점20121213
16077대부업폐업2012-서울강남-0035동원대부개인02445-1300서울특별시 강남구 일원동 734번지 105 상록수아파트-103서울특별시 강남구 광평로10길 15, 105동 103호 (일원동, 상록수아파트)13594720120209201502092014061820120209본점20140618
15344대부중개업유효기간만료2011-서울강북-0043위드피플대부중개개인<NA>서울특별시 강북구 수유동 48번지 23호 규봉빌딩 9층서울특별시 강북구 덕릉로24길 6 (수유동,규봉빌딩 9층)1420702011100620141006<NA>20111006본점20141119
23626대부업<NA>2010-서울종로-00064(대부업)동광캐피탈대부개인027322567서울특별시 종로구 종로1가 24번지 르메이에르빌딩 410-1호<NA>11088820101110201311102011092720101110본점20110927
17248대부중개업폐업2010-서울관악-00088(대부중개업)삼정대부중개개인0232850147서울특별시 관악구 신림동 1424번지 28호 태영아파트-2306<NA>1510152010110920131109<NA>20101109본점20131121
18541대부업타시군구이관2013-서울마포-0014(대부업)SK대부개인070-4055-9009서울특별시 마포구 성산동 597번지 동성아파트-1508<NA>12185020130204201602042013061920130204본점20130619
24242대부업<NA>2010-서울구로-00004(대부업)플러스원캐싱개인070-7582-0885서울특별시 구로구 구로동 1130번지 21호 세종오피스텔-411<NA>15205020080716201107162011071720080716본점20110719
31300<NA><NA>2008-서울특별시-00727자립회개인26774904서울특별시 영등포구 양평동4가 249-2<NA>15010420080814<NA>2009060520050529본점20090605
등록신청사업영업구분등록증번호상호법인여부사업장 전화번호소재지소재지(도로명)우편번호등록일자유효기간만료일자폐쇄일자지점설립일자본점여부최근수정일자
20864대부중개업타시군구이관2012-서울강북-0018하나오토론 대부중개개인1544-5983서울특별시 강북구 미아동 126번지 46호 한일빌딩-405<NA>14210020120410201504102012082020120410본점20120820
11586대부업폐업2016-서울구로-042(대부업)성화플러스대부개인<NA>서울특별시 구로구 고척동 334번지 208 -801서울특별시 구로구 경인로 390, 208동 801호 (고척동, 벽산블루밍아파트)<NA>20160623201906232016122320160622본점20161223
28470대부중개업<NA>2010-서울강남-0087진흥개인027730653서울특별시 강남구 역삼동 824번지 25호 대우디오빌플러스-429호<NA>13508020070806<NA>2010041320070806본점20100413
9817대부중개업유효기간만료2014-서울송파-0073(대부중개업)황금 대부중개업개인<NA>서울특별시 송파구 문정동 79번지 9호 황금빌라-402서울특별시 송파구 새말로6길 24-8, 402호 (문정동, 황금빌라)<NA>20140917201709172017091720140918본점20171128
20125대부업폐업2011-서울영등포-0262(대부업)제노솔루션 주식회사법인02-554-5677서울특별시 영등포구 여의도동 35번지 4호 한국화재보험협회빌딩 13층<NA>15088520111115201411152012121720111115본점20121217
28718<NA><NA>2008-서울특별시-00522(주)원엔디법인7555873서울특별시 중구 을지로2가 195-8 영생일호빌딩 1101호<NA>10084520080630<NA>20091116<NA>본점20100329
31061<NA><NA>2008-서울특별시-02930장흥개인0222310460서울특별시 종로구 숭인동 201-14 경일빌딩 202호<NA>11055020080110<NA>20090331<NA>본점20090610
271대부중개업폐업2023-서울송파-0061(대부중개업)은하수대부중개개인<NA>서울특별시 송파구 송파동 95번지 55호 장원빌딩서울특별시 송파구 가락로 139-1, 장원빌딩 202-1호 (송파동)<NA>20230912202609112024041920230912본점20240419
21242대부업폐업2010-서울종로-00073(대부업)프린시펄어드바이저파트너스대부 유한회사법인02-734-6901서울특별시 종로구 인사동 (4/) 하나로빌딩 5층 514<NA>11079420101210201312102012071220101210본점20120712
30669<NA><NA>2006-서울특별시-00397송석봉개인<NA>서울특별시 중구 남창동 169-2 삼선빌딩 15층<NA>10080620060920<NA>2009070220060908본점20090706