Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells19243
Missing cells (%)12.8%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory1.3 MiB
Average record size in memory133.0 B

Variable types

Categorical4
Text5
Numeric6

Dataset

Description등록신청사업,영업구분,등록증번호,상호,법인여부,사업장 전화번호,소재지,소재지(도로명),우편번호,등록일자,유효기간만료일자,폐쇄일자,지점설립일자,본점여부,최근수정일자
Author강북구
URLhttps://data.seoul.go.kr/dataList/OA-10943/S/1/datasetView.do

Alerts

Dataset has 1 (< 0.1%) duplicate rowsDuplicates
등록일자 is highly overall correlated with 유효기간만료일자 and 3 other fieldsHigh correlation
유효기간만료일자 is highly overall correlated with 등록일자 and 3 other fieldsHigh correlation
폐쇄일자 is highly overall correlated with 등록일자 and 3 other fieldsHigh correlation
지점설립일자 is highly overall correlated with 등록일자 and 3 other fieldsHigh correlation
최근수정일자 is highly overall correlated with 등록일자 and 3 other fieldsHigh correlation
본점여부 is highly imbalanced (94.9%)Imbalance
등록증번호 has 176 (1.8%) missing valuesMissing
사업장 전화번호 has 3458 (34.6%) missing valuesMissing
소재지 has 301 (3.0%) missing valuesMissing
소재지(도로명) has 4762 (47.6%) missing valuesMissing
우편번호 has 5647 (56.5%) missing valuesMissing
유효기간만료일자 has 2051 (20.5%) missing valuesMissing
폐쇄일자 has 1612 (16.1%) missing valuesMissing
지점설립일자 has 1236 (12.4%) missing valuesMissing

Reproduction

Analysis started2024-05-03 22:18:33.290232
Analysis finished2024-05-03 22:20:04.216656
Duration1 minute and 30.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
대부업
6175 
대부중개업
3390 
<NA>
 
435

Length

Max length5
Median length3
Mean length3.7215
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대부업
2nd row대부업
3rd row대부업
4th row<NA>
5th row대부중개업

Common Values

ValueCountFrequency (%)
대부업 6175
61.8%
대부중개업 3390
33.9%
<NA> 435
 
4.3%

Length

2024-05-03T22:20:04.402218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T22:20:04.749534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대부업 6175
61.8%
대부중개업 3390
33.9%
na 435
 
4.3%

영업구분
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
3750 
<NA>
2878 
타시군구이관
1175 
영업중
867 
유효기간만료
791 
Other values (2)
539 

Length

Max length6
Median length4
Mean length3.5573
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3750
37.5%
<NA> 2878
28.8%
타시군구이관 1175
 
11.8%
영업중 867
 
8.7%
유효기간만료 791
 
7.9%
직권취소 535
 
5.3%
갱신등록불가 4
 
< 0.1%

Length

2024-05-03T22:20:05.144408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T22:20:05.525382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3750
37.5%
na 2878
28.8%
타시군구이관 1175
 
11.8%
영업중 867
 
8.7%
유효기간만료 791
 
7.9%
직권취소 535
 
5.3%
갱신등록불가 4
 
< 0.1%

등록증번호
Text

MISSING 

Distinct9782
Distinct (%)99.6%
Missing176
Missing (%)1.8%
Memory size156.2 KiB
2024-05-03T22:20:06.235490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length27
Mean length19.503257
Min length4

Characters and Unicode

Total characters191600
Distinct characters67
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

Unique9741 ?
Unique (%)99.2%

Sample

1st row2010-서울성동-0031
2nd row2006-서울특별시-00305
3rd row2012-서울서초-0179(대부업)
4th row2007-서울특별시-00941
5th row2015-서울강동-00047
ValueCountFrequency (%)
2011-서울특별시 23
 
0.2%
2013-서울특별시 19
 
0.2%
2012-서울특별시 13
 
0.1%
2014-서울특별시 12
 
0.1%
2015-서울특별시 11
 
0.1%
2010-서울 9
 
0.1%
대부업 9
 
0.1%
2016-서울특별시 8
 
0.1%
대부중개업 8
 
0.1%
성북구-00010 6
 
0.1%
Other values (9735) 9854
98.8%
2024-05-03T22:20:07.391851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 33998
17.7%
- 19640
 
10.3%
2 15801
 
8.2%
1 11808
 
6.2%
10925
 
5.7%
9795
 
5.1%
8437
 
4.4%
( 8174
 
4.3%
8140
 
4.2%
) 8117
 
4.2%
Other values (57) 56765
29.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82644
43.1%
Other Letter 72876
38.0%
Dash Punctuation 19640
 
10.3%
Open Punctuation 8174
 
4.3%
Close Punctuation 8117
 
4.2%
Space Separator 149
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10925
15.0%
9795
13.4%
8437
11.6%
8140
11.2%
7896
10.8%
3547
 
4.9%
2917
 
4.0%
2503
 
3.4%
2495
 
3.4%
2495
 
3.4%
Other values (43) 13726
18.8%
Decimal Number
ValueCountFrequency (%)
0 33998
41.1%
2 15801
19.1%
1 11808
 
14.3%
3 3686
 
4.5%
8 3103
 
3.8%
4 3035
 
3.7%
7 2867
 
3.5%
9 2866
 
3.5%
6 2792
 
3.4%
5 2688
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 19640
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8174
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8117
100.0%
Space Separator
ValueCountFrequency (%)
149
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 118724
62.0%
Hangul 72876
38.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10925
15.0%
9795
13.4%
8437
11.6%
8140
11.2%
7896
10.8%
3547
 
4.9%
2917
 
4.0%
2503
 
3.4%
2495
 
3.4%
2495
 
3.4%
Other values (43) 13726
18.8%
Common
ValueCountFrequency (%)
0 33998
28.6%
- 19640
16.5%
2 15801
13.3%
1 11808
 
9.9%
( 8174
 
6.9%
) 8117
 
6.8%
3 3686
 
3.1%
8 3103
 
2.6%
4 3035
 
2.6%
7 2867
 
2.4%
Other values (4) 8495
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 118724
62.0%
Hangul 72876
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 33998
28.6%
- 19640
16.5%
2 15801
13.3%
1 11808
 
9.9%
( 8174
 
6.9%
) 8117
 
6.8%
3 3686
 
3.1%
8 3103
 
2.6%
4 3035
 
2.6%
7 2867
 
2.4%
Other values (4) 8495
 
7.2%
Hangul
ValueCountFrequency (%)
10925
15.0%
9795
13.4%
8437
11.6%
8140
11.2%
7896
10.8%
3547
 
4.9%
2917
 
4.0%
2503
 
3.4%
2495
 
3.4%
2495
 
3.4%
Other values (43) 13726
18.8%

상호
Text

Distinct8705
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-03T22:20:08.077217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length25
Mean length7.7304
Min length1

Characters and Unicode

Total characters77304
Distinct characters779
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7639 ?
Unique (%)76.4%

Sample

1st row(주)나이스대부
2nd row크로버
3rd row(주)투예스대부
4th row청솔금융컨설팅
5th row하이캐피탈대부중개
ValueCountFrequency (%)
주식회사 830
 
7.0%
대부중개 294
 
2.5%
대부 291
 
2.4%
유한회사 52
 
0.4%
캐피탈 17
 
0.1%
대부업 16
 
0.1%
전당포 13
 
0.1%
서울대부 12
 
0.1%
money 12
 
0.1%
미래 11
 
0.1%
Other values (8757) 10379
87.0%
2024-05-03T22:20:09.509557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8501
 
11.0%
8142
 
10.5%
2690
 
3.5%
2290
 
3.0%
2088
 
2.7%
2086
 
2.7%
1952
 
2.5%
1929
 
2.5%
) 1859
 
2.4%
( 1854
 
2.4%
Other values (769) 43913
56.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67775
87.7%
Uppercase Letter 2301
 
3.0%
Space Separator 1929
 
2.5%
Close Punctuation 1859
 
2.4%
Open Punctuation 1854
 
2.4%
Lowercase Letter 1061
 
1.4%
Decimal Number 250
 
0.3%
Other Punctuation 240
 
0.3%
Dash Punctuation 27
 
< 0.1%
Other Symbol 5
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8501
 
12.5%
8142
 
12.0%
2690
 
4.0%
2290
 
3.4%
2088
 
3.1%
2086
 
3.1%
1952
 
2.9%
1336
 
2.0%
1064
 
1.6%
1033
 
1.5%
Other values (694) 36593
54.0%
Uppercase Letter
ValueCountFrequency (%)
S 301
 
13.1%
K 220
 
9.6%
J 175
 
7.6%
C 171
 
7.4%
M 163
 
7.1%
H 127
 
5.5%
B 122
 
5.3%
L 91
 
4.0%
O 89
 
3.9%
E 87
 
3.8%
Other values (16) 755
32.8%
Lowercase Letter
ValueCountFrequency (%)
e 134
12.6%
n 130
12.3%
o 115
10.8%
a 92
 
8.7%
i 69
 
6.5%
t 64
 
6.0%
r 51
 
4.8%
c 50
 
4.7%
s 49
 
4.6%
l 47
 
4.4%
Other values (15) 260
24.5%
Decimal Number
ValueCountFrequency (%)
1 73
29.2%
2 40
16.0%
4 40
16.0%
3 23
 
9.2%
5 23
 
9.2%
0 15
 
6.0%
9 15
 
6.0%
6 13
 
5.2%
8 6
 
2.4%
7 2
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 141
58.8%
& 85
35.4%
, 6
 
2.5%
? 4
 
1.7%
* 2
 
0.8%
1
 
0.4%
1
 
0.4%
Space Separator
ValueCountFrequency (%)
1929
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1859
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1854
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Other Symbol
ValueCountFrequency (%)
5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67770
87.7%
Common 6161
 
8.0%
Latin 3363
 
4.4%
Han 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8501
 
12.5%
8142
 
12.0%
2690
 
4.0%
2290
 
3.4%
2088
 
3.1%
2086
 
3.1%
1952
 
2.9%
1336
 
2.0%
1064
 
1.6%
1033
 
1.5%
Other values (685) 36588
54.0%
Latin
ValueCountFrequency (%)
S 301
 
9.0%
K 220
 
6.5%
J 175
 
5.2%
C 171
 
5.1%
M 163
 
4.8%
e 134
 
4.0%
n 130
 
3.9%
H 127
 
3.8%
B 122
 
3.6%
o 115
 
3.4%
Other values (42) 1705
50.7%
Common
ValueCountFrequency (%)
1929
31.3%
) 1859
30.2%
( 1854
30.1%
. 141
 
2.3%
& 85
 
1.4%
1 73
 
1.2%
2 40
 
0.6%
4 40
 
0.6%
- 27
 
0.4%
3 23
 
0.4%
Other values (12) 90
 
1.5%
Han
ValueCountFrequency (%)
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67765
87.7%
ASCII 9521
 
12.3%
CJK 10
 
< 0.1%
None 7
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
8501
 
12.5%
8142
 
12.0%
2690
 
4.0%
2290
 
3.4%
2088
 
3.1%
2086
 
3.1%
1952
 
2.9%
1336
 
2.0%
1064
 
1.6%
1033
 
1.5%
Other values (684) 36583
54.0%
ASCII
ValueCountFrequency (%)
1929
20.3%
) 1859
19.5%
( 1854
19.5%
S 301
 
3.2%
K 220
 
2.3%
J 175
 
1.8%
C 171
 
1.8%
M 163
 
1.7%
. 141
 
1.5%
e 134
 
1.4%
Other values (61) 2574
27.0%
None
ValueCountFrequency (%)
5
71.4%
1
 
14.3%
1
 
14.3%
Number Forms
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%

법인여부
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
개인
7199 
법인
2801 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 7199
72.0%
법인 2801
 
28.0%

Length

2024-05-03T22:20:09.951666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T22:20:10.258358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 7199
72.0%
법인 2801
 
28.0%
Distinct5816
Distinct (%)88.9%
Missing3458
Missing (%)34.6%
Memory size156.2 KiB
2024-05-03T22:20:10.930350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length41
Mean length10.574442
Min length1

Characters and Unicode

Total characters69178
Distinct characters30
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5233 ?
Unique (%)80.0%

Sample

1st row02-563-0860
2nd row22136201
3rd row02-521-8100
4th row0226525676
5th row02-1661-2018
ValueCountFrequency (%)
02 297
 
4.0%
54
 
0.7%
070 35
 
0.5%
010 14
 
0.2%
0 10
 
0.1%
02-734-6901 7
 
0.1%
357 6
 
0.1%
02-830-2228 6
 
0.1%
1566 6
 
0.1%
703 6
 
0.1%
Other values (6155) 6964
94.0%
2024-05-03T22:20:12.295940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11190
16.2%
2 10244
14.8%
- 6941
10.0%
5 5798
8.4%
7 5295
7.7%
6 5073
7.3%
3 4987
7.2%
1 4987
7.2%
4 4766
6.9%
8 4722
6.8%
Other values (20) 5175
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61003
88.2%
Dash Punctuation 6941
 
10.0%
Space Separator 950
 
1.4%
Other Punctuation 143
 
0.2%
Close Punctuation 75
 
0.1%
Math Symbol 28
 
< 0.1%
Open Punctuation 26
 
< 0.1%
Other Letter 9
 
< 0.1%
Uppercase Letter 2
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11190
18.3%
2 10244
16.8%
5 5798
9.5%
7 5295
8.7%
6 5073
8.3%
3 4987
8.2%
1 4987
8.2%
4 4766
7.8%
8 4722
7.7%
9 3941
 
6.5%
Other Letter
ValueCountFrequency (%)
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
Other Punctuation
ValueCountFrequency (%)
* 86
60.1%
/ 35
24.5%
. 22
 
15.4%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 6941
100.0%
Space Separator
ValueCountFrequency (%)
950
100.0%
Close Punctuation
ValueCountFrequency (%)
) 75
100.0%
Math Symbol
ValueCountFrequency (%)
~ 28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69167
> 99.9%
Hangul 9
 
< 0.1%
Latin 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11190
16.2%
2 10244
14.8%
- 6941
10.0%
5 5798
8.4%
7 5295
7.7%
6 5073
7.3%
3 4987
7.2%
1 4987
7.2%
4 4766
6.9%
8 4722
6.8%
Other values (9) 5164
7.5%
Hangul
ValueCountFrequency (%)
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
Latin
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69169
> 99.9%
Hangul 9
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11190
16.2%
2 10244
14.8%
- 6941
10.0%
5 5798
8.4%
7 5295
7.7%
6 5073
7.3%
3 4987
7.2%
1 4987
7.2%
4 4766
6.9%
8 4722
6.8%
Other values (11) 5166
7.5%
Hangul
ValueCountFrequency (%)
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%

소재지
Text

MISSING 

Distinct8602
Distinct (%)88.7%
Missing301
Missing (%)3.0%
Memory size156.2 KiB
2024-05-03T22:20:13.293618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length51
Mean length31.427467
Min length15

Characters and Unicode

Total characters304815
Distinct characters629
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7829 ?
Unique (%)80.7%

Sample

1st row서울특별시 성동구 성수동1가 656번지 281호 삼일빌딩 5층
2nd row서울특별시 동대문구 전농동 127-186
3rd row서울특별시 서초구 방배동 880번지 8호 우진빌딩 2층
4th row서울특별시 양천구 신정2동 294-58 성지빌딩
5th row서울특별시 강동구 성내동 320번지 8호 오피스나인-310
ValueCountFrequency (%)
서울특별시 9696
 
17.0%
강남구 1577
 
2.8%
서초구 973
 
1.7%
1호 698
 
1.2%
역삼동 668
 
1.2%
서초동 599
 
1.0%
송파구 583
 
1.0%
중구 564
 
1.0%
2호 465
 
0.8%
영등포구 451
 
0.8%
Other values (9466) 40855
71.5%
2024-05-03T22:20:14.871210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
67732
22.2%
1 13436
 
4.4%
12099
 
4.0%
11100
 
3.6%
10441
 
3.4%
9969
 
3.3%
9750
 
3.2%
9705
 
3.2%
9698
 
3.2%
2 8688
 
2.9%
Other values (619) 142197
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 166938
54.8%
Space Separator 67732
22.2%
Decimal Number 63043
 
20.7%
Dash Punctuation 5388
 
1.8%
Uppercase Letter 1164
 
0.4%
Other Punctuation 213
 
0.1%
Lowercase Letter 120
 
< 0.1%
Close Punctuation 92
 
< 0.1%
Open Punctuation 91
 
< 0.1%
Letter Number 22
 
< 0.1%
Other values (3) 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12099
 
7.2%
11100
 
6.6%
10441
 
6.3%
9969
 
6.0%
9750
 
5.8%
9705
 
5.8%
9698
 
5.8%
8554
 
5.1%
8433
 
5.1%
7946
 
4.8%
Other values (544) 69243
41.5%
Uppercase Letter
ValueCountFrequency (%)
B 248
21.3%
A 215
18.5%
S 85
 
7.3%
D 64
 
5.5%
T 55
 
4.7%
E 50
 
4.3%
K 49
 
4.2%
C 49
 
4.2%
L 46
 
4.0%
I 41
 
3.5%
Other values (16) 262
22.5%
Lowercase Letter
ValueCountFrequency (%)
e 20
16.7%
n 13
10.8%
i 11
9.2%
t 10
 
8.3%
r 10
 
8.3%
o 7
 
5.8%
a 6
 
5.0%
u 6
 
5.0%
c 6
 
5.0%
w 5
 
4.2%
Other values (10) 26
21.7%
Decimal Number
ValueCountFrequency (%)
1 13436
21.3%
2 8688
13.8%
0 7914
12.6%
3 6973
11.1%
4 5749
9.1%
5 4990
 
7.9%
6 4558
 
7.2%
7 4044
 
6.4%
9 3395
 
5.4%
8 3296
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 74
34.7%
/ 68
31.9%
. 64
30.0%
3
 
1.4%
& 2
 
0.9%
; 1
 
0.5%
@ 1
 
0.5%
Letter Number
ValueCountFrequency (%)
14
63.6%
6
27.3%
2
 
9.1%
Close Punctuation
ValueCountFrequency (%)
) 91
98.9%
] 1
 
1.1%
Open Punctuation
ValueCountFrequency (%)
( 90
98.9%
[ 1
 
1.1%
Space Separator
ValueCountFrequency (%)
67732
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5388
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Other Number
ValueCountFrequency (%)
½ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 166937
54.8%
Common 136570
44.8%
Latin 1306
 
0.4%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12099
 
7.2%
11100
 
6.6%
10441
 
6.3%
9969
 
6.0%
9750
 
5.8%
9705
 
5.8%
9698
 
5.8%
8554
 
5.1%
8433
 
5.1%
7946
 
4.8%
Other values (543) 69242
41.5%
Latin
ValueCountFrequency (%)
B 248
19.0%
A 215
16.5%
S 85
 
6.5%
D 64
 
4.9%
T 55
 
4.2%
E 50
 
3.8%
K 49
 
3.8%
C 49
 
3.8%
L 46
 
3.5%
I 41
 
3.1%
Other values (39) 404
30.9%
Common
ValueCountFrequency (%)
67732
49.6%
1 13436
 
9.8%
2 8688
 
6.4%
0 7914
 
5.8%
3 6973
 
5.1%
4 5749
 
4.2%
- 5388
 
3.9%
5 4990
 
3.7%
6 4558
 
3.3%
7 4044
 
3.0%
Other values (15) 7098
 
5.2%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 166936
54.8%
ASCII 137850
45.2%
Number Forms 22
 
< 0.1%
None 5
 
< 0.1%
CJK 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
67732
49.1%
1 13436
 
9.7%
2 8688
 
6.3%
0 7914
 
5.7%
3 6973
 
5.1%
4 5749
 
4.2%
- 5388
 
3.9%
5 4990
 
3.6%
6 4558
 
3.3%
7 4044
 
2.9%
Other values (59) 8378
 
6.1%
Hangul
ValueCountFrequency (%)
12099
 
7.2%
11100
 
6.6%
10441
 
6.3%
9969
 
6.0%
9750
 
5.8%
9705
 
5.8%
9698
 
5.8%
8554
 
5.1%
8433
 
5.1%
7946
 
4.8%
Other values (542) 69241
41.5%
Number Forms
ValueCountFrequency (%)
14
63.6%
6
27.3%
2
 
9.1%
None
ValueCountFrequency (%)
3
60.0%
1
 
20.0%
½ 1
 
20.0%
CJK
ValueCountFrequency (%)
1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%

소재지(도로명)
Text

MISSING 

Distinct4789
Distinct (%)91.4%
Missing4762
Missing (%)47.6%
Memory size156.2 KiB
2024-05-03T22:20:15.913633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length53
Mean length37.235204
Min length19

Characters and Unicode

Total characters195038
Distinct characters611
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4382 ?
Unique (%)83.7%

Sample

1st row서울특별시 성동구 아차산로 33, 4층 (성수동1가, 삼일빌딩)
2nd row서울특별시 서초구 서초대로33길 9, 2층 (방배동, 우진빌딩)
3rd row서울특별시 강동구 천호옛길 19, 310호 (성내동, 오피스나인)
4th row서울특별시 종로구 종로5길 38-1, 청일빌딩 301호 (청진동)
5th row서울특별시 강남구 학동로3길 7, 우영빌딩 3층 (논현동)
ValueCountFrequency (%)
서울특별시 5236
 
14.1%
강남구 926
 
2.5%
서초구 601
 
1.6%
2층 472
 
1.3%
서초동 407
 
1.1%
역삼동 382
 
1.0%
3층 358
 
1.0%
4층 336
 
0.9%
영등포구 327
 
0.9%
송파구 299
 
0.8%
Other values (6718) 27751
74.8%
2024-05-03T22:20:17.711343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31866
 
16.3%
1 7439
 
3.8%
, 7147
 
3.7%
6999
 
3.6%
6862
 
3.5%
5806
 
3.0%
5771
 
3.0%
5459
 
2.8%
2 5377
 
2.8%
5285
 
2.7%
Other values (601) 107027
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 108509
55.6%
Decimal Number 34781
 
17.8%
Space Separator 31866
 
16.3%
Other Punctuation 7166
 
3.7%
Close Punctuation 5282
 
2.7%
Open Punctuation 5282
 
2.7%
Dash Punctuation 1082
 
0.6%
Uppercase Letter 911
 
0.5%
Lowercase Letter 118
 
0.1%
Letter Number 24
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6999
 
6.5%
6862
 
6.3%
5806
 
5.4%
5771
 
5.3%
5459
 
5.0%
5285
 
4.9%
5246
 
4.8%
5237
 
4.8%
4223
 
3.9%
2778
 
2.6%
Other values (528) 54843
50.5%
Uppercase Letter
ValueCountFrequency (%)
B 157
17.2%
A 136
14.9%
S 82
 
9.0%
E 60
 
6.6%
T 57
 
6.3%
C 48
 
5.3%
L 44
 
4.8%
I 42
 
4.6%
K 40
 
4.4%
G 32
 
3.5%
Other values (16) 213
23.4%
Lowercase Letter
ValueCountFrequency (%)
e 16
13.6%
n 15
12.7%
r 10
8.5%
t 10
8.5%
c 9
 
7.6%
i 9
 
7.6%
o 8
 
6.8%
u 7
 
5.9%
s 6
 
5.1%
w 5
 
4.2%
Other values (8) 23
19.5%
Decimal Number
ValueCountFrequency (%)
1 7439
21.4%
2 5377
15.5%
0 4451
12.8%
3 4136
11.9%
4 3026
8.7%
5 2782
 
8.0%
6 2239
 
6.4%
7 1949
 
5.6%
8 1730
 
5.0%
9 1652
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 7147
99.7%
. 8
 
0.1%
@ 4
 
0.1%
& 2
 
< 0.1%
2
 
< 0.1%
/ 2
 
< 0.1%
? 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
14
58.3%
7
29.2%
3
 
12.5%
Math Symbol
ValueCountFrequency (%)
~ 13
76.5%
< 2
 
11.8%
> 2
 
11.8%
Close Punctuation
ValueCountFrequency (%)
) 5281
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 5281
> 99.9%
[ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
31866
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1082
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 108509
55.6%
Common 85476
43.8%
Latin 1053
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6999
 
6.5%
6862
 
6.3%
5806
 
5.4%
5771
 
5.3%
5459
 
5.0%
5285
 
4.9%
5246
 
4.8%
5237
 
4.8%
4223
 
3.9%
2778
 
2.6%
Other values (528) 54843
50.5%
Latin
ValueCountFrequency (%)
B 157
14.9%
A 136
 
12.9%
S 82
 
7.8%
E 60
 
5.7%
T 57
 
5.4%
C 48
 
4.6%
L 44
 
4.2%
I 42
 
4.0%
K 40
 
3.8%
G 32
 
3.0%
Other values (37) 355
33.7%
Common
ValueCountFrequency (%)
31866
37.3%
1 7439
 
8.7%
, 7147
 
8.4%
2 5377
 
6.3%
) 5281
 
6.2%
( 5281
 
6.2%
0 4451
 
5.2%
3 4136
 
4.8%
4 3026
 
3.5%
5 2782
 
3.3%
Other values (16) 8690
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 108509
55.6%
ASCII 86503
44.4%
Number Forms 24
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31866
36.8%
1 7439
 
8.6%
, 7147
 
8.3%
2 5377
 
6.2%
) 5281
 
6.1%
( 5281
 
6.1%
0 4451
 
5.1%
3 4136
 
4.8%
4 3026
 
3.5%
5 2782
 
3.2%
Other values (59) 9717
 
11.2%
Hangul
ValueCountFrequency (%)
6999
 
6.5%
6862
 
6.3%
5806
 
5.4%
5771
 
5.3%
5459
 
5.0%
5285
 
4.9%
5246
 
4.8%
5237
 
4.8%
4223
 
3.9%
2778
 
2.6%
Other values (528) 54843
50.5%
Number Forms
ValueCountFrequency (%)
14
58.3%
7
29.2%
3
 
12.5%
None
ValueCountFrequency (%)
2
100.0%

우편번호
Real number (ℝ)

MISSING 

Distinct1350
Distinct (%)31.0%
Missing5647
Missing (%)56.5%
Infinite0
Infinite (%)0.0%
Mean136341.76
Minimum4526
Maximum429842
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T22:20:18.728562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4526
5-th percentile100851
Q1132040
median136086
Q3143150
95-th percentile157030
Maximum429842
Range425316
Interquartile range (IQR)11110

Descriptive statistics

Standard deviation15994.958
Coefficient of variation (CV)0.11731518
Kurtosis70.993336
Mean136341.76
Median Absolute Deviation (MAD)4966
Skewness2.8471381
Sum5.9349569 × 108
Variance2.5583869 × 108
MonotonicityNot monotonic
2024-05-03T22:20:19.432487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
135080 163
 
1.6%
137070 135
 
1.4%
157010 67
 
0.7%
135010 58
 
0.6%
151015 54
 
0.5%
152050 50
 
0.5%
151050 47
 
0.5%
158070 40
 
0.4%
142070 40
 
0.4%
138160 37
 
0.4%
Other values (1340) 3662
36.6%
(Missing) 5647
56.5%
ValueCountFrequency (%)
4526 1
 
< 0.1%
4554 1
 
< 0.1%
4801 1
 
< 0.1%
7220 1
 
< 0.1%
100011 3
 
< 0.1%
100012 2
 
< 0.1%
100014 1
 
< 0.1%
100015 3
 
< 0.1%
100021 31
0.3%
100022 6
 
0.1%
ValueCountFrequency (%)
429842 1
 
< 0.1%
423060 1
 
< 0.1%
403866 1
 
< 0.1%
158881 1
 
< 0.1%
158877 1
 
< 0.1%
158864 2
< 0.1%
158863 2
< 0.1%
158860 4
< 0.1%
158859 1
 
< 0.1%
158858 1
 
< 0.1%

등록일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3547
Distinct (%)35.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20137267
Minimum20060306
Maximum20240502
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T22:20:20.292793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060306
5-th percentile20070828
Q120091127
median20130325
Q320171108
95-th percentile20230214
Maximum20240502
Range180196
Interquartile range (IQR)79981

Descriptive statistics

Standard deviation49258.101
Coefficient of variation (CV)0.0024461165
Kurtosis-0.96586162
Mean20137267
Median Absolute Deviation (MAD)39714
Skewness0.43550067
Sum2.0137267 × 1011
Variance2.4263605 × 109
MonotonicityNot monotonic
2024-05-03T22:20:21.105907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20080814 35
 
0.4%
20080731 25
 
0.2%
20080926 23
 
0.2%
20080818 22
 
0.2%
20080806 22
 
0.2%
20090611 21
 
0.2%
20090514 20
 
0.2%
20081222 18
 
0.2%
20080822 16
 
0.2%
20090520 16
 
0.2%
Other values (3537) 9782
97.8%
ValueCountFrequency (%)
20060306 2
< 0.1%
20060308 1
 
< 0.1%
20060310 1
 
< 0.1%
20060320 3
< 0.1%
20060323 3
< 0.1%
20060324 2
< 0.1%
20060327 1
 
< 0.1%
20060405 1
 
< 0.1%
20060407 2
< 0.1%
20060410 2
< 0.1%
ValueCountFrequency (%)
20240502 1
 
< 0.1%
20240430 3
< 0.1%
20240425 2
< 0.1%
20240424 4
< 0.1%
20240423 1
 
< 0.1%
20240422 3
< 0.1%
20240418 1
 
< 0.1%
20240411 3
< 0.1%
20240409 1
 
< 0.1%
20240408 2
< 0.1%

유효기간만료일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3329
Distinct (%)41.9%
Missing2051
Missing (%)20.5%
Infinite0
Infinite (%)0.0%
Mean20182266
Minimum20090310
Maximum22180428
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T22:20:21.835637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090310
5-th percentile20120330
Q120141020
median20180123
Q320220409
95-th percentile20260502
Maximum22180428
Range2090118
Interquartile range (IQR)79389

Descriptive statistics

Standard deviation50084.965
Coefficient of variation (CV)0.0024816324
Kurtosis317.2301
Mean20182266
Median Absolute Deviation (MAD)39218
Skewness8.1824879
Sum1.6042883 × 1011
Variance2.5085037 × 109
MonotonicityNot monotonic
2024-05-03T22:20:22.442164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110831 15
 
0.1%
20160530 14
 
0.1%
20120611 13
 
0.1%
20140831 12
 
0.1%
20120514 12
 
0.1%
20180428 11
 
0.1%
20140721 10
 
0.1%
20240728 10
 
0.1%
20131102 10
 
0.1%
20141108 10
 
0.1%
Other values (3319) 7832
78.3%
(Missing) 2051
 
20.5%
ValueCountFrequency (%)
20090310 1
< 0.1%
20090514 1
< 0.1%
20091116 1
< 0.1%
20100112 1
< 0.1%
20100117 1
< 0.1%
20100125 1
< 0.1%
20100216 1
< 0.1%
20100219 1
< 0.1%
20100308 1
< 0.1%
20100410 1
< 0.1%
ValueCountFrequency (%)
22180428 1
 
< 0.1%
20270502 1
 
< 0.1%
20270430 3
< 0.1%
20270425 2
< 0.1%
20270424 4
< 0.1%
20270423 1
 
< 0.1%
20270422 2
< 0.1%
20270421 1
 
< 0.1%
20270418 1
 
< 0.1%
20270411 3
< 0.1%

폐쇄일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3120
Distinct (%)37.2%
Missing1612
Missing (%)16.1%
Infinite0
Infinite (%)0.0%
Mean20142404
Minimum20090219
Maximum20240503
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T22:20:23.005294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090219
5-th percentile20090904
Q120110412
median20130730
Q320170603
95-th percentile20220929
Maximum20240503
Range150284
Interquartile range (IQR)60190.75

Descriptive statistics

Standard deviation41201.751
Coefficient of variation (CV)0.002045523
Kurtosis-0.61302929
Mean20142404
Median Absolute Deviation (MAD)29803.5
Skewness0.6704006
Sum1.6895448 × 1011
Variance1.6975843 × 109
MonotonicityNot monotonic
2024-05-03T22:20:23.602042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091116 199
 
2.0%
20100927 81
 
0.8%
20101213 24
 
0.2%
20160725 19
 
0.2%
20110425 18
 
0.2%
20110420 17
 
0.2%
20110914 16
 
0.2%
20170124 15
 
0.1%
20110901 13
 
0.1%
20111108 13
 
0.1%
Other values (3110) 7973
79.7%
(Missing) 1612
 
16.1%
ValueCountFrequency (%)
20090219 1
 
< 0.1%
20090220 1
 
< 0.1%
20090305 1
 
< 0.1%
20090307 2
< 0.1%
20090309 2
< 0.1%
20090311 3
< 0.1%
20090312 4
< 0.1%
20090313 3
< 0.1%
20090316 2
< 0.1%
20090317 2
< 0.1%
ValueCountFrequency (%)
20240503 3
< 0.1%
20240501 2
 
< 0.1%
20240430 3
< 0.1%
20240429 2
 
< 0.1%
20240425 1
 
< 0.1%
20240423 3
< 0.1%
20240419 3
< 0.1%
20240418 1
 
< 0.1%
20240417 5
0.1%
20240415 1
 
< 0.1%

지점설립일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3590
Distinct (%)41.0%
Missing1236
Missing (%)12.4%
Infinite0
Infinite (%)0.0%
Mean20135658
Minimum19050627
Maximum20240502
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T22:20:24.300070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19050627
5-th percentile20061228
Q120100413
median20130514
Q320170717
95-th percentile20220518
Maximum20240502
Range1189875
Interquartile range (IQR)70304.25

Descriptive statistics

Standard deviation49478.207
Coefficient of variation (CV)0.0024572431
Kurtosis26.020224
Mean20135658
Median Absolute Deviation (MAD)39302.5
Skewness-1.0814452
Sum1.7646891 × 1011
Variance2.448093 × 109
MonotonicityNot monotonic
2024-05-03T22:20:24.794443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20090514 24
 
0.2%
20090611 23
 
0.2%
20090820 19
 
0.2%
20090528 18
 
0.2%
20090821 16
 
0.2%
20090520 15
 
0.1%
20090512 14
 
0.1%
20100201 13
 
0.1%
20130530 13
 
0.1%
20090511 13
 
0.1%
Other values (3580) 8596
86.0%
(Missing) 1236
 
12.4%
ValueCountFrequency (%)
19050627 1
< 0.1%
19770919 1
< 0.1%
19840618 1
< 0.1%
19880322 1
< 0.1%
19930107 1
< 0.1%
19940223 1
< 0.1%
19940418 1
< 0.1%
19950501 1
< 0.1%
19951229 1
< 0.1%
19960712 1
< 0.1%
ValueCountFrequency (%)
20240502 1
 
< 0.1%
20240430 3
< 0.1%
20240425 2
< 0.1%
20240423 1
 
< 0.1%
20240422 2
< 0.1%
20240419 1
 
< 0.1%
20240418 1
 
< 0.1%
20240411 2
< 0.1%
20240408 1
 
< 0.1%
20240404 2
< 0.1%

본점여부
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
본점
9943 
지점
 
57

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 9943
99.4%
지점 57
 
0.6%

Length

2024-05-03T22:20:25.245241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T22:20:25.548341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
본점 9943
99.4%
지점 57
 
0.6%

최근수정일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3171
Distinct (%)31.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20153447
Minimum20090518
Maximum20240503
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T22:20:25.971557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090518
5-th percentile20091117
Q120111013
median20140930
Q320190708
95-th percentile20231013
Maximum20240503
Range149985
Interquartile range (IQR)79695

Descriptive statistics

Standard deviation46217.47
Coefficient of variation (CV)0.0022932787
Kurtosis-1.1061226
Mean20153447
Median Absolute Deviation (MAD)30709.5
Skewness0.4204903
Sum2.0153447 × 1011
Variance2.1360545 × 109
MonotonicityNot monotonic
2024-05-03T22:20:26.518725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091117 91
 
0.9%
20090609 54
 
0.5%
20100927 49
 
0.5%
20091116 46
 
0.5%
20090622 43
 
0.4%
20091118 42
 
0.4%
20110425 38
 
0.4%
20100330 37
 
0.4%
20091119 37
 
0.4%
20130621 35
 
0.4%
Other values (3161) 9528
95.3%
ValueCountFrequency (%)
20090518 2
 
< 0.1%
20090521 4
 
< 0.1%
20090601 6
 
0.1%
20090603 10
 
0.1%
20090604 15
 
0.1%
20090605 5
 
0.1%
20090608 4
 
< 0.1%
20090609 54
0.5%
20090610 22
0.2%
20090611 21
 
0.2%
ValueCountFrequency (%)
20240503 8
0.1%
20240502 5
0.1%
20240501 5
0.1%
20240430 6
0.1%
20240429 5
0.1%
20240425 6
0.1%
20240424 4
< 0.1%
20240423 7
0.1%
20240422 8
0.1%
20240419 3
 
< 0.1%

Interactions

2024-05-03T22:19:51.382329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:18:42.819951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:18:49.797419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:18:58.426004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:19:05.814968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:19:14.091439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:19:51.654443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:18:43.083563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:18:50.094329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:18:58.695617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:19:05.986818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:19:17.196268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:19:51.940430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:18:43.381647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:18:50.377725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:18:58.924363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:19:06.183759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:19:22.511681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:19:52.220811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:18:43.703305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:18:50.655319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:18:59.117200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:19:06.378076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:19:27.542922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:19:52.516997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:18:44.076503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:18:50.976521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:18:59.328384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:19:06.609588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:19:32.450312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:20:02.355637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:18:49.510268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:18:58.135446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:19:05.529991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:19:13.822108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:19:44.684452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-03T22:20:26.836804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록신청사업영업구분법인여부우편번호등록일자유효기간만료일자폐쇄일자지점설립일자본점여부최근수정일자
등록신청사업1.0000.1030.0180.0410.2310.0000.2200.1730.0000.178
영업구분0.1031.0000.2830.1070.6130.0020.2650.2260.0460.539
법인여부0.0180.2831.0000.1070.3440.0000.2590.2810.1680.349
우편번호0.0410.1070.1071.0000.225NaN0.2500.0550.0000.195
등록일자0.2310.6130.3440.2251.0000.0000.9380.6930.0790.939
유효기간만료일자0.0000.0020.000NaN0.0001.0000.0000.0000.0000.000
폐쇄일자0.2200.2650.2590.2500.9380.0001.0000.6920.0450.999
지점설립일자0.1730.2260.2810.0550.6930.0000.6921.0000.1210.687
본점여부0.0000.0460.1680.0000.0790.0000.0450.1211.0000.078
최근수정일자0.1780.5390.3490.1950.9390.0000.9990.6870.0781.000
2024-05-03T22:20:27.227033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록신청사업본점여부법인여부영업구분
등록신청사업1.0000.0000.0120.074
본점여부0.0001.0000.1080.033
법인여부0.0120.1081.0000.203
영업구분0.0740.0330.2031.000
2024-05-03T22:20:27.700449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호등록일자유효기간만료일자폐쇄일자지점설립일자최근수정일자등록신청사업영업구분법인여부본점여부
우편번호1.0000.0070.0020.0390.0510.0190.0280.1300.0680.000
등록일자0.0071.0000.9950.9610.9250.9650.1770.3810.2640.060
유효기간만료일자0.0020.9951.0000.9640.8970.9660.0000.0010.0000.000
폐쇄일자0.0390.9610.9641.0000.9050.9910.1690.1130.1990.035
지점설립일자0.0510.9250.8970.9051.0000.8950.1290.1210.3340.235
최근수정일자0.0190.9650.9660.9910.8951.0000.1360.3020.2680.060
등록신청사업0.0280.1770.0000.1690.1290.1361.0000.0740.0120.000
영업구분0.1300.3810.0010.1130.1210.3020.0741.0000.2030.033
법인여부0.0680.2640.0000.1990.3340.2680.0120.2031.0000.108
본점여부0.0000.0600.0000.0350.2350.0600.0000.0330.1081.000

Missing values

2024-05-03T22:20:02.762636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-03T22:20:03.444979image/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.
2024-05-03T22:20:03.927763image/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
14845대부업타시군구이관2010-서울성동-0031(주)나이스대부법인02-563-0860서울특별시 성동구 성수동1가 656번지 281호 삼일빌딩 5층서울특별시 성동구 아차산로 33, 4층 (성수동1가, 삼일빌딩)13311120130717201607172015022720101005본점20150227
28992대부업<NA>2006-서울특별시-00305크로버개인22136201서울특별시 동대문구 전농동 127-186<NA>13002220060817<NA>2009081820060801본점20100211
12074대부업폐업2012-서울서초-0179(대부업)(주)투예스대부법인02-521-8100서울특별시 서초구 방배동 880번지 8호 우진빌딩 2층서울특별시 서초구 서초대로33길 9, 2층 (방배동, 우진빌딩)<NA>20150722201807222016092120121004본점20160921
30729<NA><NA>2007-서울특별시-00941청솔금융컨설팅개인0226525676서울특별시 양천구 신정2동 294-58 성지빌딩<NA>15807220070716<NA>2009062320070706본점20090623
10872대부중개업직권취소2015-서울강동-00047하이캐피탈대부중개개인02-1661-2018서울특별시 강동구 성내동 320번지 8호 오피스나인-310서울특별시 강동구 천호옛길 19, 310호 (성내동, 오피스나인)<NA>20150916201809162017031320150916본점20170313
313대부중개업유효기간만료2021-서울종로-00004(대부중개업)플러스머니대부(주)법인<NA>서울특별시 종로구 청진동 3번지 2호 청일빌딩서울특별시 종로구 종로5길 38-1, 청일빌딩 301호 (청진동)<NA>2021032420240324<NA>20200220본점20240403
22145대부중개업폐업2010-서울관악-00016(대부중개업)케이엘시스템스대부중개법인0231411052서울특별시 관악구 봉천동 33번지 3호 협동빌딩-405<NA>15105020090828201208282010080620090828본점20120315
27602대부중개업<NA><NA>다산스피드웨이개인<NA>서울특별시 영등포구 도림동 152-12<NA><NA>20071113<NA>2010071520071106본점20100716
4077대부업<NA>2017-서울강남-0264(대부업)엔알자산대부주식회사법인02-544-1344서울특별시 강남구 논현동 51번지 11호서울특별시 강남구 학동로3길 7, 우영빌딩 3층 (논현동)<NA>2020080420230804<NA>20171026본점20220722
14472대부업직권취소2014-서울영등포-0606(대부업)황제대부개인<NA><NA>서울특별시 영등포구 영중로 65, 361호 (영등포동6가, 영월빌딩)<NA>20140703201707032015060120140703본점20150602
등록신청사업영업구분등록증번호상호법인여부사업장 전화번호소재지소재지(도로명)우편번호등록일자유효기간만료일자폐쇄일자지점설립일자본점여부최근수정일자
9429대부중개업폐업2015-서울강북-0078(대부중개업)이에스캐피탈대부중개개인1833-8043서울특별시 강북구 미아동 159번지 50호 금강빌딩, 2층서울특별시 강북구 덕릉로28길 15, 2층 (미아동, 금강빌딩)<NA>20151209201812092018020220151209본점20180205
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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>2010021120090918본점201006042