Overview

Dataset statistics

Number of variables11
Number of observations21
Missing cells13
Missing cells (%)5.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory94.3 B

Variable types

Categorical4
Text5
DateTime2

Dataset

Description경상남도 거제시 대부업현황(시군구명, 등록신청사업, 영업구분, 등록증번호, 상호, 사업자구분, 전화번호, 소재지, 등록일자, 기준일자)등에 대한 정보를 제공합니다.
Author경상남도 거제시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3079269

Alerts

시군구명 has constant value ""Constant
영업구분 has constant value ""Constant
기준일자 has constant value ""Constant
전화번호 has 13 (61.9%) missing valuesMissing
등록증번호 has unique valuesUnique

Reproduction

Analysis started2024-04-16 18:43:26.131739
Analysis finished2024-04-16 18:43:29.190724
Duration3.06 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
경상남도 거제시
21 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경상남도 거제시
2nd row경상남도 거제시
3rd row경상남도 거제시
4th row경상남도 거제시
5th row경상남도 거제시

Common Values

ValueCountFrequency (%)
경상남도 거제시 21
100.0%

Length

2024-04-17T03:43:29.258410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T03:43:29.351894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 21
50.0%
거제시 21
50.0%

등록신청사업
Categorical

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
대부업
16 
대부중개업
5 

Length

Max length5
Median length3
Mean length3.4761905
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대부업 16
76.2%
대부중개업 5
 
23.8%

Length

2024-04-17T03:43:29.460743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T03:43:29.585008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대부업 16
76.2%
대부중개업 5
 
23.8%

영업구분
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
영업중
21 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 21
100.0%

Length

2024-04-17T03:43:29.683045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T03:43:29.777896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 21
100.0%

등록증번호
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-04-17T03:43:29.951303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length13.428571
Min length5

Characters and Unicode

Total characters282
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row2022-경남거제-0009
2nd row2022-경남거제-0008
3rd row2022-경남거제-0007
4th row2022-경남거제-0006
5th row2022-경남거제-0005
ValueCountFrequency (%)
2022-경남거제-0009 1
 
3.8%
2022-경남거제-0008 1
 
3.8%
거제-106 1
 
3.8%
거제-0201 1
 
3.8%
2017-경남 1
 
3.8%
거제-0003 1
 
3.8%
2018-경남 1
 
3.8%
거제-0005 1
 
3.8%
2019-경남 1
 
3.8%
거제-0004 1
 
3.8%
Other values (16) 16
61.5%
2024-04-17T03:43:30.262489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 78
27.7%
2 46
16.3%
- 40
14.2%
거 21
 
7.4%
제 21
 
7.4%
경 19
 
6.7%
남 19
 
6.7%
1 12
 
4.3%
5
 
1.8%
9 3
 
1.1%
Other values (6) 18
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 157
55.7%
Other Letter 80
28.4%
Dash Punctuation 40
 
14.2%
Space Separator 5
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 78
49.7%
2 46
29.3%
1 12
 
7.6%
9 3
 
1.9%
8 3
 
1.9%
7 3
 
1.9%
6 3
 
1.9%
5 3
 
1.9%
4 3
 
1.9%
3 3
 
1.9%
Other Letter
ValueCountFrequency (%)
거 21
26.2%
제 21
26.2%
경 19
23.8%
남 19
23.8%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 202
71.6%
Hangul 80
 
28.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 78
38.6%
2 46
22.8%
- 40
19.8%
1 12
 
5.9%
5
 
2.5%
9 3
 
1.5%
8 3
 
1.5%
7 3
 
1.5%
6 3
 
1.5%
5 3
 
1.5%
Other values (2) 6
 
3.0%
Hangul
ValueCountFrequency (%)
거 21
26.2%
제 21
26.2%
경 19
23.8%
남 19
23.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 202
71.6%
Hangul 80
 
28.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 78
38.6%
2 46
22.8%
- 40
19.8%
1 12
 
5.9%
5
 
2.5%
9 3
 
1.5%
8 3
 
1.5%
7 3
 
1.5%
6 3
 
1.5%
5 3
 
1.5%
Other values (2) 6
 
3.0%
Hangul
ValueCountFrequency (%)
거 21
26.2%
제 21
26.2%
경 19
23.8%
남 19
23.8%

상호
Text

Distinct17
Distinct (%)81.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-04-17T03:43:30.721677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length8.4285714
Min length3

Characters and Unicode

Total characters177
Distinct characters51
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)61.9%

Sample

1st row주식회사 신화엔피엘대부
2nd row주식회사 신화엔피엘대부
3rd row주식회사 더바른대부
4th row주식회사 더바른대부
5th row하나금융대부
ValueCountFrequency (%)
주식회사 8
24.2%
대부 4
12.1%
더바른대부 2
 
6.1%
티에스 2
 
6.1%
세풍캐피탈대부 2
 
6.1%
신화엔피엘대부 2
 
6.1%
하나금융대부 1
 
3.0%
신우대부 1
 
3.0%
bjk대부 1
 
3.0%
피움파이낸스대부중개 1
 
3.0%
Other values (9) 9
27.3%
2024-04-17T03:43:31.008221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 21
 
11.9%
부 21
 
11.9%
12
 
6.8%
식 8
 
4.5%
주 8
 
4.5%
사 8
 
4.5%
회 8
 
4.5%
피 7
 
4.0%
당 6
 
3.4%
스 6
 
3.4%
Other values (41) 72
40.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 162
91.5%
Space Separator 12
 
6.8%
Uppercase Letter 3
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 21
 
13.0%
부 21
 
13.0%
식 8
 
4.9%
주 8
 
4.9%
사 8
 
4.9%
회 8
 
4.9%
피 7
 
4.3%
당 6
 
3.7%
스 6
 
3.7%
포 5
 
3.1%
Other values (37) 64
39.5%
Uppercase Letter
ValueCountFrequency (%)
J 1
33.3%
B 1
33.3%
K 1
33.3%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 162
91.5%
Common 12
 
6.8%
Latin 3
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 21
 
13.0%
부 21
 
13.0%
식 8
 
4.9%
주 8
 
4.9%
사 8
 
4.9%
회 8
 
4.9%
피 7
 
4.3%
당 6
 
3.7%
스 6
 
3.7%
포 5
 
3.1%
Other values (37) 64
39.5%
Latin
ValueCountFrequency (%)
J 1
33.3%
B 1
33.3%
K 1
33.3%
Common
ValueCountFrequency (%)
12
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 162
91.5%
ASCII 15
 
8.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 21
 
13.0%
부 21
 
13.0%
식 8
 
4.9%
주 8
 
4.9%
사 8
 
4.9%
회 8
 
4.9%
피 7
 
4.3%
당 6
 
3.7%
스 6
 
3.7%
포 5
 
3.1%
Other values (37) 64
39.5%
ASCII
ValueCountFrequency (%)
12
80.0%
J 1
 
6.7%
B 1
 
6.7%
K 1
 
6.7%

사업자구분
Categorical

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
개인
13 
법인
8 

Length

Max length3
Median length3
Mean length2.6190476
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 13
61.9%
법인 8
38.1%

Length

2024-04-17T03:43:31.171533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T03:43:31.280864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 13
61.9%
법인 8
38.1%

전화번호
Text

MISSING 

Distinct6
Distinct (%)75.0%
Missing13
Missing (%)61.9%
Memory size300.0 B
2024-04-17T03:43:31.415847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters96
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)50.0%

Sample

1st row055-633-8323
2nd row055-633-8323
3rd row055-637-8301
4th row055-637-8301
5th row055-688-2250
ValueCountFrequency (%)
055-633-8323 2
25.0%
055-637-8301 2
25.0%
055-688-2250 1
12.5%
055-637-7369 1
12.5%
055-635-6767 1
12.5%
055-688-0474 1
12.5%
2024-04-17T03:43:31.680353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 18
18.8%
- 16
16.7%
3 15
15.6%
0 12
12.5%
6 11
11.5%
8 8
8.3%
7 7
 
7.3%
2 4
 
4.2%
1 2
 
2.1%
4 2
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80
83.3%
Dash Punctuation 16
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 18
22.5%
3 15
18.8%
0 12
15.0%
6 11
13.8%
8 8
10.0%
7 7
 
8.8%
2 4
 
5.0%
1 2
 
2.5%
4 2
 
2.5%
9 1
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 96
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 18
18.8%
- 16
16.7%
3 15
15.6%
0 12
12.5%
6 11
11.5%
8 8
8.3%
7 7
 
7.3%
2 4
 
4.2%
1 2
 
2.1%
4 2
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 18
18.8%
- 16
16.7%
3 15
15.6%
0 12
12.5%
6 11
11.5%
8 8
8.3%
7 7
 
7.3%
2 4
 
4.2%
1 2
 
2.1%
4 2
 
2.1%

소재지(지번)
Text

Distinct16
Distinct (%)76.2%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-04-17T03:43:31.896161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length26
Mean length23.428571
Min length18

Characters and Unicode

Total characters492
Distinct characters70
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)52.4%

Sample

1st row경상남도 거제시 장평동 95-96
2nd row경상남도 거제시 장평동 95-96
3rd row경상남도 거제시 연초면 송정리 206
4th row경상남도 거제시 연초면 송정리 206
5th row경상남도 거제시 고현동 755-13 성창노블레스
ValueCountFrequency (%)
경상남도 21
19.4%
거제시 21
19.4%
고현동 9
 
8.3%
옥포동 8
 
7.4%
연초면 2
 
1.9%
송정리 2
 
1.9%
206 2
 
1.9%
95-96 2
 
1.9%
763-4 2
 
1.9%
529-14 2
 
1.9%
Other values (33) 37
34.3%
2024-04-17T03:43:32.248275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
87
17.7%
상 24
 
4.9%
시 22
 
4.5%
경 21
 
4.3%
남 21
 
4.3%
도 21
 
4.3%
거 21
 
4.3%
제 21
 
4.3%
동 21
 
4.3%
5 17
 
3.5%
Other values (60) 216
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 298
60.6%
Decimal Number 95
 
19.3%
Space Separator 87
 
17.7%
Dash Punctuation 12
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 24
 
8.1%
시 22
 
7.4%
경 21
 
7.0%
남 21
 
7.0%
도 21
 
7.0%
거 21
 
7.0%
제 21
 
7.0%
동 21
 
7.0%
현 11
 
3.7%
호 9
 
3.0%
Other values (48) 106
35.6%
Decimal Number
ValueCountFrequency (%)
5 17
17.9%
9 13
13.7%
2 11
11.6%
1 11
11.6%
6 10
10.5%
0 9
9.5%
3 8
8.4%
4 8
8.4%
8 4
 
4.2%
7 4
 
4.2%
Space Separator
ValueCountFrequency (%)
87
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 298
60.6%
Common 194
39.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 24
 
8.1%
시 22
 
7.4%
경 21
 
7.0%
남 21
 
7.0%
도 21
 
7.0%
거 21
 
7.0%
제 21
 
7.0%
동 21
 
7.0%
현 11
 
3.7%
호 9
 
3.0%
Other values (48) 106
35.6%
Common
ValueCountFrequency (%)
87
44.8%
5 17
 
8.8%
9 13
 
6.7%
- 12
 
6.2%
2 11
 
5.7%
1 11
 
5.7%
6 10
 
5.2%
0 9
 
4.6%
3 8
 
4.1%
4 8
 
4.1%
Other values (2) 8
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 298
60.6%
ASCII 194
39.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
87
44.8%
5 17
 
8.8%
9 13
 
6.7%
- 12
 
6.2%
2 11
 
5.7%
1 11
 
5.7%
6 10
 
5.2%
0 9
 
4.6%
3 8
 
4.1%
4 8
 
4.1%
Other values (2) 8
 
4.1%
Hangul
ValueCountFrequency (%)
상 24
 
8.1%
시 22
 
7.4%
경 21
 
7.0%
남 21
 
7.0%
도 21
 
7.0%
거 21
 
7.0%
제 21
 
7.0%
동 21
 
7.0%
현 11
 
3.7%
호 9
 
3.0%
Other values (48) 106
35.6%

소재지(도로명)
Text

Distinct17
Distinct (%)81.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-04-17T03:43:32.490346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length39
Mean length33.190476
Min length22

Characters and Unicode

Total characters697
Distinct characters79
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)61.9%

Sample

1st row경상남도 거제시 장평로7길 11(장평동)
2nd row경상남도 거제시 장평로7길 11, 진들빌 1층 (장평동)
3rd row경상남도 거제시 연초면 송정5길 110, 엠오지빌딩 302호
4th row경상남도 거제시 연초면 송정5길 110, 엠오지빌딩 302호
5th row경상남도 거제시 거제중앙로19길 28, 503호 (고현동, 성창노블레스)
ValueCountFrequency (%)
경상남도 21
 
14.9%
거제시 21
 
14.9%
고현동 9
 
6.4%
옥포동 8
 
5.7%
101호 4
 
2.8%
연초면 2
 
1.4%
거제중앙로 2
 
1.4%
11 2
 
1.4%
1층 2
 
1.4%
옥포대첩로2길 2
 
1.4%
Other values (52) 68
48.2%
2024-04-17T03:43:32.849985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
120
 
17.2%
1 40
 
5.7%
거 25
 
3.6%
제 25
 
3.6%
, 24
 
3.4%
상 24
 
3.4%
시 22
 
3.2%
동 21
 
3.0%
0 21
 
3.0%
경 21
 
3.0%
Other values (69) 354
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 390
56.0%
Decimal Number 122
 
17.5%
Space Separator 120
 
17.2%
Other Punctuation 24
 
3.4%
Open Punctuation 19
 
2.7%
Close Punctuation 19
 
2.7%
Dash Punctuation 2
 
0.3%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
거 25
 
6.4%
제 25
 
6.4%
상 24
 
6.2%
시 22
 
5.6%
동 21
 
5.4%
경 21
 
5.4%
남 21
 
5.4%
도 21
 
5.4%
로 19
 
4.9%
옥 16
 
4.1%
Other values (53) 175
44.9%
Decimal Number
ValueCountFrequency (%)
1 40
32.8%
0 21
17.2%
2 16
 
13.1%
8 12
 
9.8%
7 9
 
7.4%
3 9
 
7.4%
5 6
 
4.9%
4 5
 
4.1%
9 3
 
2.5%
6 1
 
0.8%
Space Separator
ValueCountFrequency (%)
120
100.0%
Other Punctuation
ValueCountFrequency (%)
, 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 390
56.0%
Common 306
43.9%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
거 25
 
6.4%
제 25
 
6.4%
상 24
 
6.2%
시 22
 
5.6%
동 21
 
5.4%
경 21
 
5.4%
남 21
 
5.4%
도 21
 
5.4%
로 19
 
4.9%
옥 16
 
4.1%
Other values (53) 175
44.9%
Common
ValueCountFrequency (%)
120
39.2%
1 40
 
13.1%
, 24
 
7.8%
0 21
 
6.9%
( 19
 
6.2%
) 19
 
6.2%
2 16
 
5.2%
8 12
 
3.9%
7 9
 
2.9%
3 9
 
2.9%
Other values (5) 17
 
5.6%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 390
56.0%
ASCII 307
44.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
120
39.1%
1 40
 
13.0%
, 24
 
7.8%
0 21
 
6.8%
( 19
 
6.2%
) 19
 
6.2%
2 16
 
5.2%
8 12
 
3.9%
7 9
 
2.9%
3 9
 
2.9%
Other values (6) 18
 
5.9%
Hangul
ValueCountFrequency (%)
거 25
 
6.4%
제 25
 
6.4%
상 24
 
6.2%
시 22
 
5.6%
동 21
 
5.4%
경 21
 
5.4%
남 21
 
5.4%
도 21
 
5.4%
로 19
 
4.9%
옥 16
 
4.1%
Other values (53) 175
44.9%

등록일자
Date

Distinct16
Distinct (%)76.2%
Missing0
Missing (%)0.0%
Memory size300.0 B
Minimum2019-10-29 00:00:00
Maximum2022-07-27 00:00:00
2024-04-17T03:43:33.013895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:43:33.135621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
Minimum2022-09-05 00:00:00
Maximum2022-09-05 00:00:00
2024-04-17T03:43:33.249660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:43:33.342929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2024-04-17T03:43:33.433401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록신청사업등록증번호상호사업자구분전화번호소재지(지번)소재지(도로명)등록일자
등록신청사업1.0001.0000.0000.4580.0000.0000.0000.000
등록증번호1.0001.0001.0001.0001.0001.0001.0001.000
상호0.0001.0001.0001.0001.0001.0000.9961.000
사업자구분0.4581.0001.0001.0001.0001.0001.0001.000
전화번호0.0001.0001.0001.0001.0001.0001.0001.000
소재지(지번)0.0001.0001.0001.0001.0001.0001.0001.000
소재지(도로명)0.0001.0000.9961.0001.0001.0001.0001.000
등록일자0.0001.0001.0001.0001.0001.0001.0001.000
2024-04-17T03:43:33.545284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업자구분등록신청사업
사업자구분1.0000.299
등록신청사업0.2991.000
2024-04-17T03:43:33.624191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록신청사업사업자구분
등록신청사업1.0000.299
사업자구분0.2991.000

Missing values

2024-04-17T03:43:28.919368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T03:43:29.115478image/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.

Sample

시군구명등록신청사업영업구분등록증번호상호사업자구분전화번호소재지(지번)소재지(도로명)등록일자기준일자
0경상남도 거제시대부중개업영업중2022-경남거제-0009주식회사 신화엔피엘대부법인<NA>경상남도 거제시 장평동 95-96경상남도 거제시 장평로7길 11(장평동)2022-07-272022-09-05
1경상남도 거제시대부업영업중2022-경남거제-0008주식회사 신화엔피엘대부법인<NA>경상남도 거제시 장평동 95-96경상남도 거제시 장평로7길 11, 진들빌 1층 (장평동)2022-07-272022-09-05
2경상남도 거제시대부업영업중2022-경남거제-0007주식회사 더바른대부법인<NA>경상남도 거제시 연초면 송정리 206경상남도 거제시 연초면 송정5길 110, 엠오지빌딩 302호2022-07-222022-09-05
3경상남도 거제시대부중개업영업중2022-경남거제-0006주식회사 더바른대부법인<NA>경상남도 거제시 연초면 송정리 206경상남도 거제시 연초면 송정5길 110, 엠오지빌딩 302호2022-07-222022-09-05
4경상남도 거제시대부업영업중2022-경남거제-0005하나금융대부개인<NA>경상남도 거제시 고현동 755-13 성창노블레스경상남도 거제시 거제중앙로19길 28, 503호 (고현동, 성창노블레스)2022-06-022022-09-05
5경상남도 거제시대부업영업중2022-경남거제-0004신우대부개인<NA>경상남도 거제시 옥포동 550-25 우전퓨쳐오피스텔경상남도 거제시 옥포대첩로2길 52, 우전퓨쳐오피스텔 1층 201호 (옥포동)2022-05-062022-09-05
6경상남도 거제시대부중개업영업중2022-경남거제-0003주식회사 세풍캐피탈대부법인055-633-8323경상남도 거제시 고현동 763-4경상남도 거제시 계룡로 180, 4층 (고현동)2022-03-072022-09-05
7경상남도 거제시대부업영업중2022-경남거제-0002주식회사 세풍캐피탈대부법인055-633-8323경상남도 거제시 고현동 763-4경상남도 거제시 계룡로 180, 4층 (고현동)2022-03-072022-09-05
8경상남도 거제시대부업영업중2022-경남거제-0001BJK대부개인<NA>경상남도 거제시 옥포동 1293-1 옥현시장경상남도 거제시 옥포로 250, 옥현시장 126호 (옥포동)2022-01-102022-09-05
9경상남도 거제시대부중개업영업중2021-경남거제-0008피움파이낸스대부중개개인<NA>경상남도 거제시 옥포동 529-14경상남도 거제시 옥포대첩로 17, 8층 802호 (옥포동)2021-11-172022-09-05
시군구명등록신청사업영업구분등록증번호상호사업자구분전화번호소재지(지번)소재지(도로명)등록일자기준일자
11경상남도 거제시대부업영업중2021-경남거제-0004주식회사 티에스 대부법인055-637-8301경상남도 거제시 고현동 692 진성마인빌경상남도 거제시 고현로4길 27, 101호 (고현동, 진성마인빌)2021-08-202022-09-05
12경상남도 거제시대부중개업영업중2021-경남거제-0003주식회사 티에스 대부법인055-637-8301경상남도 거제시 고현동 692 진성마인빌경상남도 거제시 고현로4길 27, 101호 (고현동, 진성마인빌)2021-08-202022-09-05
13경상남도 거제시대부업영업중2021-경남 거제-0001거제시전당포대부개인<NA>경상남도 거제시 고현동 33-20 1층 2호경상남도 거제시 거제중앙로 1898-13 (고현동)2021-04-082022-09-05
14경상남도 거제시대부업영업중2020-경남거제-0005제이스대부개인<NA>경상남도 거제시 옥포동 548-7 서울상가 가동 101호경상남도 거제시 옥포로 178, 서울상가 가층 101호 (옥포동)2020-10-082022-09-05
15경상남도 거제시대부업영업중2020-경남 거제-0004천만스피드대부개인<NA>경상남도 거제시 고현동 959-8 화인아트빌라 304호경상남도 거제시 서문로3길 11, 화인아트빌라 304호 (고현동)2020-07-102022-09-05
16경상남도 거제시대부업영업중2019-경남 거제-0005유대부개인<NA>경상남도 거제시 옥포동 538번지 6호 백동마이웨이경상남도 거제시 옥포대첩로2길 18, 205호 (옥포동, 백동마이웨이)2019-10-292022-09-05
17경상남도 거제시대부업영업중2018-경남 거제-0003영화전당포 대부개인055-688-2250경상남도 거제시 옥포동 544번지 5호 현대상가아파트경상남도 거제시 옥포로10길 1, A동 101호 (옥포동, 현대상가아파트)2021-10-142022-09-05
18경상남도 거제시대부업영업중2017-경남 거제-0201신현전당포대부개인055-637-7369경상남도 거제시 고현동 106번지 5호경상남도 거제시 거제중앙로 1871-1, 3층 (고현동)2020-11-092022-09-05
19경상남도 거제시대부업영업중거제-106귀금당전당포 대부개인055-635-6767경상남도 거제시 고현동 29번지 8호 한양프라자 109호경상남도 거제시 고현로 121, 109호 (고현동)2021-10-212022-09-05
20경상남도 거제시대부업영업중거제-96한일전당포대부개인055-688-0474경상남도 거제시 옥포동 550번지 1호 영진상가경상남도 거제시 거제대로 3730, 영진상가 102호 (옥포동)2021-09-162022-09-05