Overview

Dataset statistics

Number of variables10
Number of observations101
Missing cells46
Missing cells (%)4.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.0 KiB
Average record size in memory81.3 B

Variable types

Categorical4
Text4
DateTime2

Dataset

Description성남시 관내 대부업 현황으로 시군구명,구별,동별, 등록신청사업(대부업/대부중개업), 등록증번호, 상호명, 소재지주소, 등록일자, 전화번호, 데이터기준일자 의 항목으로 구성되어 있습니다. ※ 대부업 등의 등록 및 금융이용자 보호에 관한 법률 제3조 제2항에 따라 금융감독원의 허가를 받은 대부(중개)업은 해당 현황에 해당되지 않으며, 등록대부업체 통합조회(fines.fss.or.kr)에서 확인이 가능합니다.
URLhttps://www.data.go.kr/data/15043665/fileData.do

Alerts

시군구명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
구별 is highly overall correlated with 동별High correlation
동별 is highly overall correlated with 구별High correlation
전화번호 has 46 (45.5%) missing valuesMissing
등록번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:10:10.618835
Analysis finished2023-12-12 02:10:11.810977
Duration1.19 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size940.0 B
경기도 성남시
101 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 성남시
2nd row경기도 성남시
3rd row경기도 성남시
4th row경기도 성남시
5th row경기도 성남시

Common Values

ValueCountFrequency (%)
경기도 성남시 101
100.0%

Length

2023-12-12T11:10:11.886578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:10:11.980487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 101
50.0%
성남시 101
50.0%

구별
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size940.0 B
분당구
61 
중원구
20 
수정구
20 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중원구
2nd row중원구
3rd row분당구
4th row분당구
5th row중원구

Common Values

ValueCountFrequency (%)
분당구 61
60.4%
중원구 20
 
19.8%
수정구 20
 
19.8%

Length

2023-12-12T11:10:12.093816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:10:12.215005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분당구 61
60.4%
중원구 20
 
19.8%
수정구 20
 
19.8%

동별
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)17.8%
Missing0
Missing (%)0.0%
Memory size940.0 B
서현동
17 
정자동
15 
야탑동
11 
성남동
10 
수내동
8 
Other values (13)
40 

Length

Max length4
Median length3
Mean length3.029703
Min length3

Unique

Unique3 ?
Unique (%)3.0%

Sample

1st row상대원동
2nd row성남동
3rd row구미동
4th row구미동
5th row성남동

Common Values

ValueCountFrequency (%)
서현동 17
16.8%
정자동 15
14.9%
야탑동 11
10.9%
성남동 10
9.9%
수내동 8
7.9%
구미동 7
6.9%
신흥동 6
 
5.9%
창곡동 5
 
5.0%
여수동 4
 
4.0%
상대원동 3
 
3.0%
Other values (8) 15
14.9%

Length

2023-12-12T11:10:12.373598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서현동 17
16.8%
정자동 15
14.9%
야탑동 11
10.9%
성남동 10
9.9%
수내동 8
7.9%
구미동 7
6.9%
신흥동 6
 
5.9%
창곡동 5
 
5.0%
여수동 4
 
4.0%
복정동 3
 
3.0%
Other values (8) 15
14.9%

등록신청사업
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size940.0 B
대부업
78 
대부중개업
23 

Length

Max length5
Median length3
Mean length3.4554455
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대부업 78
77.2%
대부중개업 23
 
22.8%

Length

2023-12-12T11:10:12.506578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:10:12.612156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대부업 78
77.2%
대부중개업 23
 
22.8%

등록번호
Text

UNIQUE 

Distinct101
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size940.0 B
2023-12-12T11:10:12.827965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length14
Mean length15.455446
Min length14

Characters and Unicode

Total characters1561
Distinct characters21
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique101 ?
Unique (%)100.0%

Sample

1st row2017-경기성남-0007
2nd row2017-경기성남-0015
3rd row2017-경기성남-0020
4th row2017-경기성남-0021
5th row2017-경기성남-0036
ValueCountFrequency (%)
2017-경기성남-0007 1
 
1.0%
2020-경기성남-0032 1
 
1.0%
2022-경기성남-0009-대부 1
 
1.0%
2022-경기성남-0006-대부 1
 
1.0%
2022-경기성남-0005-대부 1
 
1.0%
2021-경기성남-0044-대부 1
 
1.0%
2021-경기성남-0042-중개 1
 
1.0%
2021-경기성남-0041-대부 1
 
1.0%
2021-경기성남-0038-대부 1
 
1.0%
2021-경기성남-0034-중개 1
 
1.0%
Other values (91) 91
90.1%
2023-12-12T11:10:13.220916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 342
21.9%
- 249
16.0%
2 197
12.6%
기 101
 
6.5%
성 101
 
6.5%
남 101
 
6.5%
경 101
 
6.5%
1 96
 
6.1%
3 47
 
3.0%
부 34
 
2.2%
Other values (11) 192
12.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 808
51.8%
Other Letter 502
32.2%
Dash Punctuation 249
 
16.0%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 342
42.3%
2 197
24.4%
1 96
 
11.9%
3 47
 
5.8%
9 30
 
3.7%
8 26
 
3.2%
7 22
 
2.7%
4 20
 
2.5%
6 15
 
1.9%
5 13
 
1.6%
Other Letter
ValueCountFrequency (%)
기 101
20.1%
성 101
20.1%
남 101
20.1%
경 101
20.1%
부 34
 
6.8%
대 34
 
6.8%
개 15
 
3.0%
중 15
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 249
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1059
67.8%
Hangul 502
32.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 342
32.3%
- 249
23.5%
2 197
18.6%
1 96
 
9.1%
3 47
 
4.4%
9 30
 
2.8%
8 26
 
2.5%
7 22
 
2.1%
4 20
 
1.9%
6 15
 
1.4%
Other values (3) 15
 
1.4%
Hangul
ValueCountFrequency (%)
기 101
20.1%
성 101
20.1%
남 101
20.1%
경 101
20.1%
부 34
 
6.8%
대 34
 
6.8%
개 15
 
3.0%
중 15
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1059
67.8%
Hangul 502
32.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 342
32.3%
- 249
23.5%
2 197
18.6%
1 96
 
9.1%
3 47
 
4.4%
9 30
 
2.8%
8 26
 
2.5%
7 22
 
2.1%
4 20
 
1.9%
6 15
 
1.4%
Other values (3) 15
 
1.4%
Hangul
ValueCountFrequency (%)
기 101
20.1%
성 101
20.1%
남 101
20.1%
경 101
20.1%
부 34
 
6.8%
대 34
 
6.8%
개 15
 
3.0%
중 15
 
3.0%

상호
Text

Distinct84
Distinct (%)83.2%
Missing0
Missing (%)0.0%
Memory size940.0 B
2023-12-12T11:10:13.548073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length8.2277228
Min length3

Characters and Unicode

Total characters831
Distinct characters171
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)66.3%

Sample

1st row성남사전당포대부
2nd row터미널전당포대부
3rd row한강대부(주)
4th row오복대부캐피탈
5th row한일투자대출대부
ValueCountFrequency (%)
주 3
 
2.8%
주식회사 3
 
2.8%
주)하모니자산관리대부 2
 
1.9%
골드론파이낸셜대부 2
 
1.9%
다빈치대부(주 2
 
1.9%
주)큐비컨설팅대부 2
 
1.9%
미소캐피탈대부 2
 
1.9%
럭스펀딩대부 2
 
1.9%
제이앤씨파이낸셜대부 2
 
1.9%
주)미소대부금융 2
 
1.9%
Other values (76) 85
79.4%
2023-12-12T11:10:14.320643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 105
 
12.6%
부 102
 
12.3%
주 43
 
5.2%
( 38
 
4.6%
) 38
 
4.6%
당 18
 
2.2%
이 17
 
2.0%
전 15
 
1.8%
포 15
 
1.8%
캐 15
 
1.8%
Other values (161) 425
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 736
88.6%
Open Punctuation 38
 
4.6%
Close Punctuation 38
 
4.6%
Decimal Number 8
 
1.0%
Space Separator 6
 
0.7%
Uppercase Letter 4
 
0.5%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 105
 
14.3%
부 102
 
13.9%
주 43
 
5.8%
당 18
 
2.4%
이 17
 
2.3%
전 15
 
2.0%
포 15
 
2.0%
캐 15
 
2.0%
피 13
 
1.8%
탈 12
 
1.6%
Other values (151) 381
51.8%
Uppercase Letter
ValueCountFrequency (%)
B 1
25.0%
H 1
25.0%
J 1
25.0%
S 1
25.0%
Decimal Number
ValueCountFrequency (%)
4 4
50.0%
2 4
50.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 737
88.7%
Common 90
 
10.8%
Latin 4
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 105
 
14.2%
부 102
 
13.8%
주 43
 
5.8%
당 18
 
2.4%
이 17
 
2.3%
전 15
 
2.0%
포 15
 
2.0%
캐 15
 
2.0%
피 13
 
1.8%
탈 12
 
1.6%
Other values (152) 382
51.8%
Common
ValueCountFrequency (%)
( 38
42.2%
) 38
42.2%
6
 
6.7%
4 4
 
4.4%
2 4
 
4.4%
Latin
ValueCountFrequency (%)
B 1
25.0%
H 1
25.0%
J 1
25.0%
S 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 736
88.6%
ASCII 94
 
11.3%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 105
 
14.3%
부 102
 
13.9%
주 43
 
5.8%
당 18
 
2.4%
이 17
 
2.3%
전 15
 
2.0%
포 15
 
2.0%
캐 15
 
2.0%
피 13
 
1.8%
탈 12
 
1.6%
Other values (151) 381
51.8%
ASCII
ValueCountFrequency (%)
( 38
40.4%
) 38
40.4%
6
 
6.4%
4 4
 
4.3%
2 4
 
4.3%
B 1
 
1.1%
H 1
 
1.1%
J 1
 
1.1%
S 1
 
1.1%
None
ValueCountFrequency (%)
㈜ 1
100.0%

소재지
Text

Distinct83
Distinct (%)82.2%
Missing0
Missing (%)0.0%
Memory size940.0 B
2023-12-12T11:10:14.675852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length51
Mean length43.09901
Min length28

Characters and Unicode

Total characters4353
Distinct characters207
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

Unique67 ?
Unique (%)66.3%

Sample

1st row경기도 성남시 중원구 금상로 2, 2층 (상대원동)
2nd row경기도 성남시 중원구 성남대로 1150 (성남동,(1층))
3rd row경기도 성남시 분당구 돌마로 46, 422-35호 (구미동)
4th row경기도 성남시 분당구 성남대로43번길 10, 하나EZ타워 6층 601호내 R634호 (구미동)
5th row경기도 성남시 중원구 성남대로 1157, 2층 (성남동)
ValueCountFrequency (%)
경기도 101
 
11.2%
성남시 101
 
11.2%
분당구 61
 
6.8%
중원구 20
 
2.2%
수정구 20
 
2.2%
서현동 17
 
1.9%
정자동 15
 
1.7%
5층 14
 
1.6%
1층 11
 
1.2%
성남동 11
 
1.2%
Other values (284) 527
58.7%
2023-12-12T11:10:15.281576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
797
 
18.3%
1 192
 
4.4%
성 147
 
3.4%
남 140
 
3.2%
동 132
 
3.0%
시 114
 
2.6%
, 114
 
2.6%
구 112
 
2.6%
로 107
 
2.5%
도 105
 
2.4%
Other values (197) 2393
55.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2400
55.1%
Space Separator 797
 
18.3%
Decimal Number 763
 
17.5%
Other Punctuation 114
 
2.6%
Open Punctuation 104
 
2.4%
Close Punctuation 104
 
2.4%
Uppercase Letter 42
 
1.0%
Dash Punctuation 23
 
0.5%
Lowercase Letter 5
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 147
 
6.1%
남 140
 
5.8%
동 132
 
5.5%
시 114
 
4.8%
구 112
 
4.7%
로 107
 
4.5%
도 105
 
4.4%
경 102
 
4.2%
기 101
 
4.2%
호 96
 
4.0%
Other values (161) 1244
51.8%
Uppercase Letter
ValueCountFrequency (%)
A 11
26.2%
B 4
 
9.5%
L 4
 
9.5%
E 3
 
7.1%
C 3
 
7.1%
R 3
 
7.1%
G 3
 
7.1%
D 2
 
4.8%
H 2
 
4.8%
I 2
 
4.8%
Other values (5) 5
11.9%
Decimal Number
ValueCountFrequency (%)
1 192
25.2%
0 96
12.6%
2 93
12.2%
3 70
 
9.2%
4 67
 
8.8%
5 66
 
8.7%
6 52
 
6.8%
7 47
 
6.2%
9 42
 
5.5%
8 38
 
5.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
20.0%
r 1
20.0%
w 1
20.0%
o 1
20.0%
t 1
20.0%
Space Separator
ValueCountFrequency (%)
797
100.0%
Other Punctuation
ValueCountFrequency (%)
, 114
100.0%
Open Punctuation
ValueCountFrequency (%)
( 104
100.0%
Close Punctuation
ValueCountFrequency (%)
) 104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2400
55.1%
Common 1905
43.8%
Latin 48
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 147
 
6.1%
남 140
 
5.8%
동 132
 
5.5%
시 114
 
4.8%
구 112
 
4.7%
로 107
 
4.5%
도 105
 
4.4%
경 102
 
4.2%
기 101
 
4.2%
호 96
 
4.0%
Other values (161) 1244
51.8%
Latin
ValueCountFrequency (%)
A 11
22.9%
B 4
 
8.3%
L 4
 
8.3%
E 3
 
6.2%
C 3
 
6.2%
R 3
 
6.2%
G 3
 
6.2%
D 2
 
4.2%
H 2
 
4.2%
I 2
 
4.2%
Other values (11) 11
22.9%
Common
ValueCountFrequency (%)
797
41.8%
1 192
 
10.1%
, 114
 
6.0%
( 104
 
5.5%
) 104
 
5.5%
0 96
 
5.0%
2 93
 
4.9%
3 70
 
3.7%
4 67
 
3.5%
5 66
 
3.5%
Other values (5) 202
 
10.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2400
55.1%
ASCII 1952
44.8%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
797
40.8%
1 192
 
9.8%
, 114
 
5.8%
( 104
 
5.3%
) 104
 
5.3%
0 96
 
4.9%
2 93
 
4.8%
3 70
 
3.6%
4 67
 
3.4%
5 66
 
3.4%
Other values (25) 249
 
12.8%
Hangul
ValueCountFrequency (%)
성 147
 
6.1%
남 140
 
5.8%
동 132
 
5.5%
시 114
 
4.8%
구 112
 
4.7%
로 107
 
4.5%
도 105
 
4.4%
경 102
 
4.2%
기 101
 
4.2%
호 96
 
4.0%
Other values (161) 1244
51.8%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

등록일자
Date

Distinct72
Distinct (%)71.3%
Missing0
Missing (%)0.0%
Memory size940.0 B
Minimum2020-06-29 00:00:00
Maximum2023-05-31 00:00:00
2023-12-12T11:10:15.472171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:10:15.653561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

전화번호
Text

MISSING 

Distinct47
Distinct (%)85.5%
Missing46
Missing (%)45.5%
Memory size940.0 B
2023-12-12T11:10:15.960917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.909091
Min length9

Characters and Unicode

Total characters655
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

Unique39 ?
Unique (%)70.9%

Sample

1st row031-734-2639
2nd row031-752-5511
3rd row031-757-0999
4th row031-705-1177
5th row031-781-2925
ValueCountFrequency (%)
031-783-7787 2
 
3.6%
031-714-7459 2
 
3.6%
1800-7681 2
 
3.6%
031-709-9494 2
 
3.6%
031-778-7440 2
 
3.6%
02-558-9832 2
 
3.6%
070-4647-2178 2
 
3.6%
031-704-4578 2
 
3.6%
031-778-8910 1
 
1.8%
031-723-0084 1
 
1.8%
Other values (37) 37
67.3%
2023-12-12T11:10:16.448596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 109
16.6%
- 107
16.3%
1 91
13.9%
7 86
13.1%
3 77
11.8%
8 43
 
6.6%
5 37
 
5.6%
4 34
 
5.2%
9 26
 
4.0%
2 24
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 548
83.7%
Dash Punctuation 107
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 109
19.9%
1 91
16.6%
7 86
15.7%
3 77
14.1%
8 43
 
7.8%
5 37
 
6.8%
4 34
 
6.2%
9 26
 
4.7%
2 24
 
4.4%
6 21
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 107
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 655
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 109
16.6%
- 107
16.3%
1 91
13.9%
7 86
13.1%
3 77
11.8%
8 43
 
6.6%
5 37
 
5.6%
4 34
 
5.2%
9 26
 
4.0%
2 24
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 655
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 109
16.6%
- 107
16.3%
1 91
13.9%
7 86
13.1%
3 77
11.8%
8 43
 
6.6%
5 37
 
5.6%
4 34
 
5.2%
9 26
 
4.0%
2 24
 
3.7%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size940.0 B
Minimum2023-06-09 00:00:00
Maximum2023-06-09 00:00:00
2023-12-12T11:10:16.606412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:10:16.736375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-12T11:10:16.845413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구별동별등록신청사업상호소재지등록일자전화번호
구별1.0001.0000.0001.0001.0000.8651.000
동별1.0001.0000.0001.0001.0000.9471.000
등록신청사업0.0000.0001.0000.0000.0000.0000.000
상호1.0001.0000.0001.0001.0001.0001.000
소재지1.0001.0000.0001.0001.0000.9991.000
등록일자0.8650.9470.0001.0000.9991.0001.000
전화번호1.0001.0000.0001.0001.0001.0001.000
2023-12-12T11:10:16.985322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구별등록신청사업동별
구별1.0000.0000.920
등록신청사업0.0001.0000.000
동별0.9200.0001.000
2023-12-12T11:10:17.097721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구별동별등록신청사업
구별1.0000.9200.000
동별0.9201.0000.000
등록신청사업0.0000.0001.000

Missing values

2023-12-12T11:10:11.511852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:10:11.735553image/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

시군구명구별동별등록신청사업등록번호상호소재지등록일자전화번호데이터기준일자
0경기도 성남시중원구상대원동대부업2017-경기성남-0007성남사전당포대부경기도 성남시 중원구 금상로 2, 2층 (상대원동)2022-12-30031-734-26392023-06-09
1경기도 성남시중원구성남동대부업2017-경기성남-0015터미널전당포대부경기도 성남시 중원구 성남대로 1150 (성남동,(1층))2023-01-06031-752-55112023-06-09
2경기도 성남시분당구구미동대부업2017-경기성남-0020한강대부(주)경기도 성남시 분당구 돌마로 46, 422-35호 (구미동)2021-01-14<NA>2023-06-09
3경기도 성남시분당구구미동대부업2017-경기성남-0021오복대부캐피탈경기도 성남시 분당구 성남대로43번길 10, 하나EZ타워 6층 601호내 R634호 (구미동)2023-02-08<NA>2023-06-09
4경기도 성남시중원구성남동대부업2017-경기성남-0036한일투자대출대부경기도 성남시 중원구 성남대로 1157, 2층 (성남동)2023-03-07031-757-09992023-06-09
5경기도 성남시분당구서현동대부업2017-경기성남-0039삼원대부경기도 성남시 분당구 황새울로342번길 19, 유성그린빌딩 7층 724호 (서현동)2023-03-06<NA>2023-06-09
6경기도 성남시분당구야탑동대부업2017-경기성남-0042강남파이낸스전당포대부경기도 성남시 분당구 야탑로 103, 303호 (야탑동,노블리치2 오피스텔)2023-03-14031-705-11772023-06-09
7경기도 성남시분당구서현동대부업2017-경기성남-0045분당명품전당포대부경기도 성남시 분당구 서현로180번길 29, 지하1층 1호 (서현동)2023-05-04031-781-29252023-06-09
8경기도 성남시분당구정자동대부업2017-경기성남-0048성진기획대부경기도 성남시 분당구 정자일로 197, 1108호 (정자동)2023-05-15031-701-93822023-06-09
9경기도 성남시중원구도촌동대부업2017-경기성남-0062(주)영인투자대부경기도 성남시 중원구 도촌남로 27, 405호 (도촌동, 동강프라자)2020-09-08031-712-62892023-06-09
시군구명구별동별등록신청사업등록번호상호소재지등록일자전화번호데이터기준일자
91경기도 성남시분당구삼평동대부업2023-경기성남-0008-대부(주)오케이대부캐피탈판교경기도 성남시 분당구 대왕판교로606번길 31, 호반메트로큐브 8층 858호 (삼평동)2023-03-31031-706-71662023-06-09
92경기도 성남시분당구서현동대부업2023-경기성남-0009-대부(주)백현대부경기도 성남시 분당구 황새울로319번길 6, 텍스타워 7층 701호 (서현동)2023-04-18031-704-45782023-06-09
93경기도 성남시분당구서현동대부중개업2023-경기성남-0010-중개(주)백현대부경기도 성남시 분당구 황새울로319번길 6, 텍스타워 7층 701호 (서현동)2023-04-18031-704-45782023-06-09
94경기도 성남시수정구창곡동대부업2023-경기성남-0011-대부머니24대부경기도 성남시 수정구 위례광장로 300, 위례중앙타워 5층 514-11호 (창곡동)2023-05-04<NA>2023-06-09
95경기도 성남시수정구창곡동대부중개업2023-경기성남-0012-중개머니24대부경기도 성남시 수정구 위례광장로 300, 위례중앙타워 5층 514-11호 (창곡동)2023-05-04<NA>2023-06-09
96경기도 성남시수정구창곡동대부업2023-경기성남-0013-대부(주)오아시스캐피탈대부경기도 성남시 수정구 위례광장로 300, 위례중앙타워 5층 514-13호 (창곡동)2021-09-17<NA>2023-06-09
97경기도 성남시수정구창곡동대부업2023-경기성남-0014-대부브릿지론대부경기도 성남시 수정구 위례광장로 300, 위례중앙타워 5층 514-25호 (창곡동)2023-05-16<NA>2023-06-09
98경기도 성남시분당구야탑동대부중개업2023-경기성남-0015-중개대환24시대부중개경기도 성남시 분당구 성남대로916번길 11, 글라스타워 4층 401호내 30호 (야탑동)2023-05-30<NA>2023-06-09
99경기도 성남시분당구야탑동대부업2023-경기성남-0016-대부24시한마음행복대부경기도 성남시 분당구 성남대로916번길 11, 글라스타워 4층 401호내 4-6호 (야탑동)2023-05-30<NA>2023-06-09
100경기도 성남시중원구도촌동대부업2023-경기성남-0017-대부(주)해천자산대부경기도 성남시 중원구 도촌로 8, 스마트시티 4층 406호 (도촌동)2023-05-31031-756-09102023-06-09