Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells19184
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
Text6
Numeric5

Dataset

Description등록신청사업,영업구분,등록증번호,상호,법인여부,사업장 전화번호,소재지,소재지(도로명),우편번호,등록일자,유효기간만료일자,폐쇄일자,지점설립일자,본점여부,최근수정일자
Author강서구
URLhttps://data.seoul.go.kr/dataList/OA-10019/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 (94.4%)Imbalance
등록증번호 has 179 (1.8%) missing valuesMissing
사업장 전화번호 has 3333 (33.3%) missing valuesMissing
소재지 has 301 (3.0%) missing valuesMissing
소재지(도로명) has 4805 (48.0%) missing valuesMissing
우편번호 has 5627 (56.3%) missing valuesMissing
유효기간만료일자 has 2072 (20.7%) missing valuesMissing
폐쇄일자 has 1615 (16.2%) missing valuesMissing
지점설립일자 has 1252 (12.5%) missing valuesMissing

Reproduction

Analysis started2024-05-11 08:00:08.753653
Analysis finished2024-05-11 08:00:22.190528
Duration13.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록신청사업
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
대부업
6219 
대부중개업
3360 
<NA>
 
421

Length

Max length5
Median length3
Mean length3.7141
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대부업 6219
62.2%
대부중개업 3360
33.6%
<NA> 421
 
4.2%

Length

2024-05-11T08:00:22.505548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:00:22.854560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대부업 6219
62.2%
대부중개업 3360
33.6%
na 421
 
4.2%

영업구분
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
3723 
<NA>
2903 
타시군구이관
1215 
영업중
836 
유효기간만료
826 
Other values (3)
497 

Length

Max length6
Median length4
Mean length3.5804
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3723
37.2%
<NA> 2903
29.0%
타시군구이관 1215
 
12.2%
영업중 836
 
8.4%
유효기간만료 826
 
8.3%
직권취소 494
 
4.9%
갱신등록불가 2
 
< 0.1%
영업정지 1
 
< 0.1%

Length

2024-05-11T08:00:23.260920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:00:23.650086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3723
37.2%
na 2903
29.0%
타시군구이관 1215
 
12.2%
영업중 836
 
8.4%
유효기간만료 826
 
8.3%
직권취소 494
 
4.9%
갱신등록불가 2
 
< 0.1%
영업정지 1
 
< 0.1%

등록증번호
Text

MISSING 

Distinct9773
Distinct (%)99.5%
Missing179
Missing (%)1.8%
Memory size156.2 KiB
2024-05-11T08:00:24.266187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length19.517463
Min length4

Characters and Unicode

Total characters191681
Distinct characters70
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

Unique9726 ?
Unique (%)99.0%

Sample

1st row2011-서울금천-00010
2nd row2014-서울중구-0154(대부중개)
3rd row2008-서울특별시-01945
4th row2018-서울금천-0004
5th row2018-서울서초-0006(대부중개업)
ValueCountFrequency (%)
2013-서울특별시 19
 
0.2%
2010-서울 14
 
0.1%
2011-서울특별시 14
 
0.1%
2015-서울특별시 11
 
0.1%
2014-서울특별시 9
 
0.1%
2016-서울특별시 8
 
0.1%
대부중개업 8
 
0.1%
2017-서울특별시 8
 
0.1%
2012-서울특별시 8
 
0.1%
2023-서울특별시 5
 
0.1%
Other values (9745) 9856
99.0%
2024-05-11T08:00:25.188350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 33894
17.7%
- 19625
 
10.2%
2 15792
 
8.2%
1 11954
 
6.2%
서 10876
 
5.7%
울 9801
 
5.1%
대 8518
 
4.4%
( 8217
 
4.3%
부 8185
 
4.3%
) 8164
 
4.3%
Other values (60) 56655
29.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82621
43.1%
Other Letter 72914
38.0%
Dash Punctuation 19625
 
10.2%
Open Punctuation 8217
 
4.3%
Close Punctuation 8164
 
4.3%
Space Separator 140
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 10876
14.9%
울 9801
13.4%
대 8518
11.7%
부 8185
11.2%
업 7952
10.9%
중 3500
 
4.8%
개 2872
 
3.9%
시 2503
 
3.4%
별 2493
 
3.4%
특 2493
 
3.4%
Other values (46) 13721
18.8%
Decimal Number
ValueCountFrequency (%)
0 33894
41.0%
2 15792
19.1%
1 11954
 
14.5%
3 3661
 
4.4%
4 3074
 
3.7%
8 3065
 
3.7%
9 2838
 
3.4%
7 2836
 
3.4%
6 2784
 
3.4%
5 2723
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 19625
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8217
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8164
100.0%
Space Separator
ValueCountFrequency (%)
140
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 118767
62.0%
Hangul 72914
38.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 10876
14.9%
울 9801
13.4%
대 8518
11.7%
부 8185
11.2%
업 7952
10.9%
중 3500
 
4.8%
개 2872
 
3.9%
시 2503
 
3.4%
별 2493
 
3.4%
특 2493
 
3.4%
Other values (46) 13721
18.8%
Common
ValueCountFrequency (%)
0 33894
28.5%
- 19625
16.5%
2 15792
13.3%
1 11954
 
10.1%
( 8217
 
6.9%
) 8164
 
6.9%
3 3661
 
3.1%
4 3074
 
2.6%
8 3065
 
2.6%
9 2838
 
2.4%
Other values (4) 8483
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 118767
62.0%
Hangul 72914
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 33894
28.5%
- 19625
16.5%
2 15792
13.3%
1 11954
 
10.1%
( 8217
 
6.9%
) 8164
 
6.9%
3 3661
 
3.1%
4 3074
 
2.6%
8 3065
 
2.6%
9 2838
 
2.4%
Other values (4) 8483
 
7.1%
Hangul
ValueCountFrequency (%)
서 10876
14.9%
울 9801
13.4%
대 8518
11.7%
부 8185
11.2%
업 7952
10.9%
중 3500
 
4.8%
개 2872
 
3.9%
시 2503
 
3.4%
별 2493
 
3.4%
특 2493
 
3.4%
Other values (46) 13721
18.8%

상호
Text

Distinct8653
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T08:00:25.819170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length33
Mean length7.7438
Min length2

Characters and Unicode

Total characters77438
Distinct characters757
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

Unique7575 ?
Unique (%)75.8%

Sample

1st row포마텍
2nd row보타니대부
3rd row다원
4th row(주)에스엘피대부중개
5th row(주)안녕펀딩대부
ValueCountFrequency (%)
주식회사 843
 
7.1%
대부중개 306
 
2.6%
대부 286
 
2.4%
유한회사 56
 
0.5%
캐피탈 22
 
0.2%
대부업 19
 
0.2%
미래 12
 
0.1%
money 11
 
0.1%
대부중개업 11
 
0.1%
주 10
 
0.1%
Other values (8679) 10361
86.8%
2024-05-11T08:00:26.943391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 8507
 
11.0%
부 8166
 
10.5%
주 2739
 
3.5%
이 2238
 
2.9%
개 2114
 
2.7%
중 2112
 
2.7%
1942
 
2.5%
) 1888
 
2.4%
( 1879
 
2.4%
스 1848
 
2.4%
Other values (747) 44005
56.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67664
87.4%
Uppercase Letter 2277
 
2.9%
Space Separator 1942
 
2.5%
Close Punctuation 1888
 
2.4%
Open Punctuation 1879
 
2.4%
Lowercase Letter 1219
 
1.6%
Other Punctuation 264
 
0.3%
Decimal Number 263
 
0.3%
Dash Punctuation 24
 
< 0.1%
Other Symbol 10
 
< 0.1%
Other values (3) 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 8507
 
12.6%
부 8166
 
12.1%
주 2739
 
4.0%
이 2238
 
3.3%
개 2114
 
3.1%
중 2112
 
3.1%
스 1848
 
2.7%
사 1393
 
2.1%
피 1115
 
1.6%
회 1077
 
1.6%
Other values (669) 36355
53.7%
Uppercase Letter
ValueCountFrequency (%)
S 287
 
12.6%
K 198
 
8.7%
M 174
 
7.6%
J 169
 
7.4%
C 164
 
7.2%
H 145
 
6.4%
B 114
 
5.0%
L 95
 
4.2%
G 89
 
3.9%
T 88
 
3.9%
Other values (16) 754
33.1%
Lowercase Letter
ValueCountFrequency (%)
e 162
13.3%
n 143
11.7%
o 121
9.9%
a 112
 
9.2%
i 82
 
6.7%
t 78
 
6.4%
s 62
 
5.1%
l 55
 
4.5%
c 54
 
4.4%
r 48
 
3.9%
Other values (14) 302
24.8%
Decimal Number
ValueCountFrequency (%)
1 92
35.0%
2 41
15.6%
4 38
14.4%
9 22
 
8.4%
3 21
 
8.0%
5 20
 
7.6%
6 12
 
4.6%
7 10
 
3.8%
0 5
 
1.9%
8 2
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 142
53.8%
& 102
38.6%
, 9
 
3.4%
? 5
 
1.9%
/ 2
 
0.8%
* 2
 
0.8%
' 1
 
0.4%
＆ 1
 
0.4%
Math Symbol
ValueCountFrequency (%)
~ 3
60.0%
> 1
 
20.0%
< 1
 
20.0%
Space Separator
ValueCountFrequency (%)
1942
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1888
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1879
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 10
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67656
87.4%
Common 6266
 
8.1%
Latin 3498
 
4.5%
Han 18
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 8507
 
12.6%
부 8166
 
12.1%
주 2739
 
4.0%
이 2238
 
3.3%
개 2114
 
3.1%
중 2112
 
3.1%
스 1848
 
2.7%
사 1393
 
2.1%
피 1115
 
1.6%
회 1077
 
1.6%
Other values (654) 36347
53.7%
Latin
ValueCountFrequency (%)
S 287
 
8.2%
K 198
 
5.7%
M 174
 
5.0%
J 169
 
4.8%
C 164
 
4.7%
e 162
 
4.6%
H 145
 
4.1%
n 143
 
4.1%
o 121
 
3.5%
B 114
 
3.3%
Other values (41) 1821
52.1%
Common
ValueCountFrequency (%)
1942
31.0%
) 1888
30.1%
( 1879
30.0%
. 142
 
2.3%
& 102
 
1.6%
1 92
 
1.5%
2 41
 
0.7%
4 38
 
0.6%
- 24
 
0.4%
9 22
 
0.4%
Other values (16) 96
 
1.5%
Han
ValueCountFrequency (%)
成 2
 
11.1%
大 2
 
11.1%
炅 1
 
5.6%
星 1
 
5.6%
宙 1
 
5.6%
多 1
 
5.6%
道 1
 
5.6%
福 1
 
5.6%
田 1
 
5.6%
去 1
 
5.6%
Other values (6) 6
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67644
87.4%
ASCII 9761
 
12.6%
CJK 18
 
< 0.1%
None 11
 
< 0.1%
Compat Jamo 2
 
< 0.1%
Number Forms 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 8507
 
12.6%
부 8166
 
12.1%
주 2739
 
4.0%
이 2238
 
3.3%
개 2114
 
3.1%
중 2112
 
3.1%
스 1848
 
2.7%
사 1393
 
2.1%
피 1115
 
1.6%
회 1077
 
1.6%
Other values (652) 36335
53.7%
ASCII
ValueCountFrequency (%)
1942
19.9%
) 1888
19.3%
( 1879
19.3%
S 287
 
2.9%
K 198
 
2.0%
M 174
 
1.8%
J 169
 
1.7%
C 164
 
1.7%
e 162
 
1.7%
H 145
 
1.5%
Other values (65) 2753
28.2%
None
ValueCountFrequency (%)
㈜ 10
90.9%
＆ 1
 
9.1%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
100.0%
CJK
ValueCountFrequency (%)
成 2
 
11.1%
大 2
 
11.1%
炅 1
 
5.6%
星 1
 
5.6%
宙 1
 
5.6%
多 1
 
5.6%
道 1
 
5.6%
福 1
 
5.6%
田 1
 
5.6%
去 1
 
5.6%
Other values (6) 6
33.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%

법인여부
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
개인
7145 
법인
2855 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 7145
71.5%
법인 2855
 
28.5%

Length

2024-05-11T08:00:27.414043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:00:27.818729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 7145
71.5%
법인 2855
 
28.5%

사업장 전화번호
Text

MISSING 

Distinct5875
Distinct (%)88.1%
Missing3333
Missing (%)33.3%
Memory size156.2 KiB
2024-05-11T08:00:28.632146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length37
Mean length10.571921
Min length1

Characters and Unicode

Total characters70483
Distinct characters26
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5234 ?
Unique (%)78.5%

Sample

1st row3283-0002
2nd row027372882
3rd row02-3390-8850
4th row02-6292-9377
5th row070-5143-2458
ValueCountFrequency (%)
02 293
 
3.9%
52
 
0.7%
070 47
 
0.6%
010 11
 
0.1%
1566 8
 
0.1%
2209 6
 
0.1%
024693344 6
 
0.1%
025117185 6
 
0.1%
2244 6
 
0.1%
02-563-1486 5
 
0.1%
Other values (6180) 7073
94.1%
2024-05-11T08:00:30.256279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11367
16.1%
2 10412
14.8%
- 7140
10.1%
5 5900
8.4%
7 5362
7.6%
6 5191
7.4%
1 5078
7.2%
3 5041
7.2%
8 4896
6.9%
4 4848
6.9%
Other values (16) 5248
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62111
88.1%
Dash Punctuation 7140
 
10.1%
Space Separator 940
 
1.3%
Other Punctuation 150
 
0.2%
Close Punctuation 72
 
0.1%
Open Punctuation 28
 
< 0.1%
Math Symbol 24
 
< 0.1%
Other Letter 14
 
< 0.1%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11367
18.3%
2 10412
16.8%
5 5900
9.5%
7 5362
8.6%
6 5191
8.4%
1 5078
8.2%
3 5041
8.1%
8 4896
7.9%
4 4848
7.8%
9 4016
 
6.5%
Other Letter
ValueCountFrequency (%)
미 4
28.6%
록 4
28.6%
등 4
28.6%
없 1
 
7.1%
음 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
* 100
66.7%
/ 36
 
24.0%
. 14
 
9.3%
Math Symbol
ValueCountFrequency (%)
~ 23
95.8%
× 1
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
K 2
50.0%
T 2
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 7140
100.0%
Space Separator
ValueCountFrequency (%)
940
100.0%
Close Punctuation
ValueCountFrequency (%)
) 72
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70465
> 99.9%
Hangul 14
 
< 0.1%
Latin 4
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11367
16.1%
2 10412
14.8%
- 7140
10.1%
5 5900
8.4%
7 5362
7.6%
6 5191
7.4%
1 5078
7.2%
3 5041
7.2%
8 4896
6.9%
4 4848
6.9%
Other values (9) 5230
7.4%
Hangul
ValueCountFrequency (%)
미 4
28.6%
록 4
28.6%
등 4
28.6%
없 1
 
7.1%
음 1
 
7.1%
Latin
ValueCountFrequency (%)
K 2
50.0%
T 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70468
> 99.9%
Hangul 14
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11367
16.1%
2 10412
14.8%
- 7140
10.1%
5 5900
8.4%
7 5362
7.6%
6 5191
7.4%
1 5078
7.2%
3 5041
7.2%
8 4896
6.9%
4 4848
6.9%
Other values (10) 5233
7.4%
Hangul
ValueCountFrequency (%)
미 4
28.6%
록 4
28.6%
등 4
28.6%
없 1
 
7.1%
음 1
 
7.1%
None
ValueCountFrequency (%)
× 1
100.0%

소재지
Text

MISSING 

Distinct8645
Distinct (%)89.1%
Missing301
Missing (%)3.0%
Memory size156.2 KiB
2024-05-11T08:00:31.207747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length49
Mean length31.497989
Min length15

Characters and Unicode

Total characters305499
Distinct characters616
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7893 ?
Unique (%)81.4%

Sample

1st row서울특별시 금천구 가산동 459번지 3호
2nd row서울특별시 중구 충무로3가 49번지 엘크루메트로시티-911
3rd row서울특별시 종로구 계동 14-9
4th row서울특별시 금천구 가산동 60번지 44호 이앤씨드림타워7차-410
5th row서울특별시 서초구 잠원동 35번지 25호 J빌딩 6층
ValueCountFrequency (%)
서울특별시 9695
 
16.9%
강남구 1631
 
2.9%
서초구 949
 
1.7%
역삼동 747
 
1.3%
1호 705
 
1.2%
송파구 603
 
1.1%
서초동 574
 
1.0%
중구 545
 
1.0%
2호 479
 
0.8%
영등포구 470
 
0.8%
Other values (9597) 40804
71.3%
2024-05-11T08:00:32.935219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
67706
22.2%
1 13570
 
4.4%
서 12035
 
3.9%
동 11105
 
3.6%
구 10522
 
3.4%
시 9943
 
3.3%
울 9750
 
3.2%
별 9707
 
3.2%
특 9695
 
3.2%
2 8769
 
2.9%
Other values (606) 142697
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 166985
54.7%
Space Separator 67706
22.2%
Decimal Number 63547
 
20.8%
Dash Punctuation 5520
 
1.8%
Uppercase Letter 1156
 
0.4%
Other Punctuation 253
 
0.1%
Lowercase Letter 132
 
< 0.1%
Open Punctuation 85
 
< 0.1%
Close Punctuation 85
 
< 0.1%
Letter Number 24
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 12035
 
7.2%
동 11105
 
6.7%
구 10522
 
6.3%
시 9943
 
6.0%
울 9750
 
5.8%
별 9707
 
5.8%
특 9695
 
5.8%
호 8551
 
5.1%
지 8431
 
5.0%
번 7909
 
4.7%
Other values (533) 69337
41.5%
Uppercase Letter
ValueCountFrequency (%)
B 275
23.8%
A 239
20.7%
D 85
 
7.4%
S 70
 
6.1%
T 54
 
4.7%
I 50
 
4.3%
K 46
 
4.0%
L 38
 
3.3%
G 36
 
3.1%
C 36
 
3.1%
Other values (16) 227
19.6%
Lowercase Letter
ValueCountFrequency (%)
e 27
20.5%
n 14
10.6%
i 13
9.8%
r 9
 
6.8%
k 8
 
6.1%
s 8
 
6.1%
t 7
 
5.3%
o 7
 
5.3%
l 6
 
4.5%
w 6
 
4.5%
Other values (11) 27
20.5%
Decimal Number
ValueCountFrequency (%)
1 13570
21.4%
2 8769
13.8%
0 8133
12.8%
3 7084
11.1%
4 5734
9.0%
5 4936
 
7.8%
6 4578
 
7.2%
7 4088
 
6.4%
9 3338
 
5.3%
8 3317
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 102
40.3%
/ 84
33.2%
. 62
24.5%
; 2
 
0.8%
？ 2
 
0.8%
# 1
 
0.4%
Letter Number
ValueCountFrequency (%)
Ⅱ 17
70.8%
Ⅰ 5
 
20.8%
Ⅲ 2
 
8.3%
Open Punctuation
ValueCountFrequency (%)
( 84
98.8%
[ 1
 
1.2%
Close Punctuation
ValueCountFrequency (%)
) 84
98.8%
] 1
 
1.2%
Space Separator
ValueCountFrequency (%)
67706
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5520
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 166984
54.7%
Common 137202
44.9%
Latin 1312
 
0.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 12035
 
7.2%
동 11105
 
6.7%
구 10522
 
6.3%
시 9943
 
6.0%
울 9750
 
5.8%
별 9707
 
5.8%
특 9695
 
5.8%
호 8551
 
5.1%
지 8431
 
5.0%
번 7909
 
4.7%
Other values (532) 69336
41.5%
Latin
ValueCountFrequency (%)
B 275
21.0%
A 239
18.2%
D 85
 
6.5%
S 70
 
5.3%
T 54
 
4.1%
I 50
 
3.8%
K 46
 
3.5%
L 38
 
2.9%
G 36
 
2.7%
C 36
 
2.7%
Other values (40) 383
29.2%
Common
ValueCountFrequency (%)
67706
49.3%
1 13570
 
9.9%
2 8769
 
6.4%
0 8133
 
5.9%
3 7084
 
5.2%
4 5734
 
4.2%
- 5520
 
4.0%
5 4936
 
3.6%
6 4578
 
3.3%
7 4088
 
3.0%
Other values (13) 7084
 
5.2%
Han
ValueCountFrequency (%)
內 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 166984
54.7%
ASCII 138488
45.3%
Number Forms 24
 
< 0.1%
None 2
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
67706
48.9%
1 13570
 
9.8%
2 8769
 
6.3%
0 8133
 
5.9%
3 7084
 
5.1%
4 5734
 
4.1%
- 5520
 
4.0%
5 4936
 
3.6%
6 4578
 
3.3%
7 4088
 
3.0%
Other values (59) 8370
 
6.0%
Hangul
ValueCountFrequency (%)
서 12035
 
7.2%
동 11105
 
6.7%
구 10522
 
6.3%
시 9943
 
6.0%
울 9750
 
5.8%
별 9707
 
5.8%
특 9695
 
5.8%
호 8551
 
5.1%
지 8431
 
5.0%
번 7909
 
4.7%
Other values (532) 69336
41.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 17
70.8%
Ⅰ 5
 
20.8%
Ⅲ 2
 
8.3%
None
ValueCountFrequency (%)
？ 2
100.0%
CJK
ValueCountFrequency (%)
內 1
100.0%

소재지(도로명)
Text

MISSING 

Distinct4740
Distinct (%)91.2%
Missing4805
Missing (%)48.0%
Memory size156.2 KiB
2024-05-11T08:00:33.711547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length54
Mean length37.146872
Min length19

Characters and Unicode

Total characters192978
Distinct characters618
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4336 ?
Unique (%)83.5%

Sample

1st row서울특별시 금천구 가산디지털1로 205-28 (가산동)
2nd row서울특별시 중구 충무로 13, 엘크루메트로시티 911호 (충무로3가)
3rd row서울특별시 금천구 디지털로9길 46, 이앤씨드림타워7차 410호 (가산동)
4th row서울특별시 서초구 신반포로45길 34, J빌딩 6층 (잠원동)
5th row서울특별시 강동구 천호대로 1073, 4층 411호 (천호동, 힐탑프라자)
ValueCountFrequency (%)
서울특별시 5193
 
14.1%
강남구 962
 
2.6%
서초구 562
 
1.5%
2층 471
 
1.3%
역삼동 447
 
1.2%
3층 380
 
1.0%
서초동 369
 
1.0%
송파구 334
 
0.9%
영등포구 332
 
0.9%
4층 292
 
0.8%
Other values (6561) 27401
74.6%
2024-05-11T08:00:34.871760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31563
 
16.4%
1 7431
 
3.9%
, 7135
 
3.7%
서 6870
 
3.6%
동 6744
 
3.5%
로 5809
 
3.0%
구 5739
 
3.0%
시 5378
 
2.8%
2 5298
 
2.7%
울 5250
 
2.7%
Other values (608) 105761
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 107479
55.7%
Decimal Number 34380
 
17.8%
Space Separator 31563
 
16.4%
Other Punctuation 7148
 
3.7%
Close Punctuation 5224
 
2.7%
Open Punctuation 5224
 
2.7%
Dash Punctuation 1017
 
0.5%
Uppercase Letter 782
 
0.4%
Lowercase Letter 125
 
0.1%
Letter Number 26
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 6870
 
6.4%
동 6744
 
6.3%
로 5809
 
5.4%
구 5739
 
5.3%
시 5378
 
5.0%
울 5250
 
4.9%
별 5201
 
4.8%
특 5193
 
4.8%
호 4179
 
3.9%
길 2715
 
2.5%
Other values (534) 54401
50.6%
Uppercase Letter
ValueCountFrequency (%)
B 159
20.3%
A 110
14.1%
S 67
 
8.6%
T 47
 
6.0%
I 40
 
5.1%
E 37
 
4.7%
C 35
 
4.5%
G 33
 
4.2%
L 32
 
4.1%
K 30
 
3.8%
Other values (16) 192
24.6%
Lowercase Letter
ValueCountFrequency (%)
e 20
16.0%
i 13
10.4%
n 12
9.6%
r 9
 
7.2%
w 9
 
7.2%
o 9
 
7.2%
c 8
 
6.4%
s 7
 
5.6%
l 6
 
4.8%
t 6
 
4.8%
Other values (10) 26
20.8%
Decimal Number
ValueCountFrequency (%)
1 7431
21.6%
2 5298
15.4%
0 4444
12.9%
3 4180
12.2%
4 2894
 
8.4%
5 2659
 
7.7%
6 2238
 
6.5%
7 1916
 
5.6%
8 1747
 
5.1%
9 1573
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 7135
99.8%
. 8
 
0.1%
@ 2
 
< 0.1%
/ 1
 
< 0.1%
？ 1
 
< 0.1%
# 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 18
69.2%
Ⅰ 6
 
23.1%
Ⅲ 2
 
7.7%
Math Symbol
ValueCountFrequency (%)
~ 8
80.0%
> 1
 
10.0%
< 1
 
10.0%
Close Punctuation
ValueCountFrequency (%)
) 5223
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 5223
> 99.9%
[ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
31563
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1017
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 107478
55.7%
Common 84566
43.8%
Latin 933
 
0.5%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 6870
 
6.4%
동 6744
 
6.3%
로 5809
 
5.4%
구 5739
 
5.3%
시 5378
 
5.0%
울 5250
 
4.9%
별 5201
 
4.8%
특 5193
 
4.8%
호 4179
 
3.9%
길 2715
 
2.5%
Other values (533) 54400
50.6%
Latin
ValueCountFrequency (%)
B 159
17.0%
A 110
 
11.8%
S 67
 
7.2%
T 47
 
5.0%
I 40
 
4.3%
E 37
 
4.0%
C 35
 
3.8%
G 33
 
3.5%
L 32
 
3.4%
K 30
 
3.2%
Other values (39) 343
36.8%
Common
ValueCountFrequency (%)
31563
37.3%
1 7431
 
8.8%
, 7135
 
8.4%
2 5298
 
6.3%
) 5223
 
6.2%
( 5223
 
6.2%
0 4444
 
5.3%
3 4180
 
4.9%
4 2894
 
3.4%
5 2659
 
3.1%
Other values (15) 8516
 
10.1%
Han
ValueCountFrequency (%)
家 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 107478
55.7%
ASCII 85472
44.3%
Number Forms 26
 
< 0.1%
CJK 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31563
36.9%
1 7431
 
8.7%
, 7135
 
8.3%
2 5298
 
6.2%
) 5223
 
6.1%
( 5223
 
6.1%
0 4444
 
5.2%
3 4180
 
4.9%
4 2894
 
3.4%
5 2659
 
3.1%
Other values (60) 9422
 
11.0%
Hangul
ValueCountFrequency (%)
서 6870
 
6.4%
동 6744
 
6.3%
로 5809
 
5.4%
구 5739
 
5.3%
시 5378
 
5.0%
울 5250
 
4.9%
별 5201
 
4.8%
특 5193
 
4.8%
호 4179
 
3.9%
길 2715
 
2.5%
Other values (533) 54400
50.6%
Number Forms
ValueCountFrequency (%)
Ⅱ 18
69.2%
Ⅰ 6
 
23.1%
Ⅲ 2
 
7.7%
CJK
ValueCountFrequency (%)
家 1
100.0%
None
ValueCountFrequency (%)
？ 1
100.0%

우편번호
Real number (ℝ)

MISSING 

Distinct1353
Distinct (%)30.9%
Missing5627
Missing (%)56.3%
Infinite0
Infinite (%)0.0%
Mean136657.45
Minimum3182
Maximum429842
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T08:00:35.250386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3182
5-th percentile110091.6
Q1132040
median136830
Q3143200
95-th percentile157035.8
Maximum429842
Range426660
Interquartile range (IQR)11160

Descriptive statistics

Standard deviation15977.498
Coefficient of variation (CV)0.11691641
Kurtosis68.961865
Mean136657.45
Median Absolute Deviation (MAD)5600
Skewness2.4387755
Sum5.9760302 × 108
Variance2.5528044 × 108
MonotonicityNot monotonic
2024-05-11T08:00:35.727000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
135080 169
 
1.7%
137070 149
 
1.5%
135010 72
 
0.7%
157010 62
 
0.6%
151015 55
 
0.5%
158070 51
 
0.5%
151050 50
 
0.5%
142070 48
 
0.5%
152050 47
 
0.5%
139200 43
 
0.4%
Other values (1343) 3627
36.3%
(Missing) 5627
56.3%
ValueCountFrequency (%)
3182 1
 
< 0.1%
4538 1
 
< 0.1%
4550 1
 
< 0.1%
4801 1
 
< 0.1%
5510 1
 
< 0.1%
7220 1
 
< 0.1%
100011 4
< 0.1%
100012 3
< 0.1%
100013 1
 
< 0.1%
100014 2
< 0.1%
ValueCountFrequency (%)
429842 1
 
< 0.1%
410762 1
 
< 0.1%
403866 1
 
< 0.1%
158864 4
< 0.1%
158863 1
 
< 0.1%
158860 5
0.1%
158859 4
< 0.1%
158857 1
 
< 0.1%
158856 1
 
< 0.1%
158845 1
 
< 0.1%

등록일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3533
Distinct (%)35.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20136412
Minimum20030519
Maximum20240510
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T08:00:36.160488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030519
5-th percentile20070807
Q120091127
median20130220
Q320170712
95-th percentile20230113
Maximum20240510
Range209991
Interquartile range (IQR)79585

Descriptive statistics

Standard deviation48730.754
Coefficient of variation (CV)0.0024200316
Kurtosis-0.8962017
Mean20136412
Median Absolute Deviation (MAD)39489
Skewness0.46494438
Sum2.0136412 × 1011
Variance2.3746864 × 109
MonotonicityNot monotonic
2024-05-11T08:00:36.707776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20080814 34
 
0.3%
20090611 24
 
0.2%
20080731 21
 
0.2%
20080818 20
 
0.2%
20080822 15
 
0.1%
20081222 15
 
0.1%
20120531 15
 
0.1%
20080926 13
 
0.1%
20090325 13
 
0.1%
20080806 13
 
0.1%
Other values (3523) 9817
98.2%
ValueCountFrequency (%)
20030519 1
 
< 0.1%
20060306 1
 
< 0.1%
20060308 1
 
< 0.1%
20060310 1
 
< 0.1%
20060324 3
< 0.1%
20060327 1
 
< 0.1%
20060329 2
< 0.1%
20060405 2
< 0.1%
20060410 2
< 0.1%
20060412 1
 
< 0.1%
ValueCountFrequency (%)
20240510 1
 
< 0.1%
20240508 1
 
< 0.1%
20240507 4
< 0.1%
20240503 3
< 0.1%
20240502 2
< 0.1%
20240430 2
< 0.1%
20240429 1
 
< 0.1%
20240425 2
< 0.1%
20240424 3
< 0.1%
20240423 1
 
< 0.1%

유효기간만료일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3288
Distinct (%)41.5%
Missing2072
Missing (%)20.7%
Infinite0
Infinite (%)0.0%
Mean20181174
Minimum20090907
Maximum20270509
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T08:00:37.150336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090907
5-th percentile20120410
Q120141012
median20171216
Q320211219
95-th percentile20260421
Maximum20270509
Range179602
Interquartile range (IQR)70207

Descriptive statistics

Standard deviation44283.33
Coefficient of variation (CV)0.0021942891
Kurtosis-0.97858306
Mean20181174
Median Absolute Deviation (MAD)30599
Skewness0.33656372
Sum1.5999635 × 1011
Variance1.9610133 × 109
MonotonicityNot monotonic
2024-05-11T08:00:37.628591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20140831 18
 
0.2%
20150531 15
 
0.1%
20110831 14
 
0.1%
20131102 13
 
0.1%
20140608 12
 
0.1%
20120611 12
 
0.1%
20140131 11
 
0.1%
20141108 11
 
0.1%
20140418 11
 
0.1%
20140719 10
 
0.1%
Other values (3278) 7801
78.0%
(Missing) 2072
 
20.7%
ValueCountFrequency (%)
20090907 1
< 0.1%
20100117 1
< 0.1%
20100122 1
< 0.1%
20100125 1
< 0.1%
20100208 1
< 0.1%
20100219 1
< 0.1%
20100308 1
< 0.1%
20100326 1
< 0.1%
20100411 1
< 0.1%
20100515 2
< 0.1%
ValueCountFrequency (%)
20270509 1
 
< 0.1%
20270508 1
 
< 0.1%
20270507 4
< 0.1%
20270503 3
< 0.1%
20270502 1
 
< 0.1%
20270501 1
 
< 0.1%
20270430 2
< 0.1%
20270429 1
 
< 0.1%
20270425 2
< 0.1%
20270424 3
< 0.1%

폐쇄일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3092
Distinct (%)36.9%
Missing1615
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean20141732
Minimum20050517
Maximum20240510
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T08:00:38.360012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20050517
5-th percentile20090914
Q120110404
median20130718
Q320170406
95-th percentile20220826
Maximum20240510
Range189993
Interquartile range (IQR)60002

Descriptive statistics

Standard deviation40688.61
Coefficient of variation (CV)0.0020201147
Kurtosis-0.5248392
Mean20141732
Median Absolute Deviation (MAD)29791
Skewness0.70216291
Sum1.6888843 × 1011
Variance1.655563 × 109
MonotonicityNot monotonic
2024-05-11T08:00:38.982040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091116 211
 
2.1%
20100927 77
 
0.8%
20160725 22
 
0.2%
20101213 21
 
0.2%
20110914 19
 
0.2%
20111108 16
 
0.2%
20170124 15
 
0.1%
20110420 15
 
0.1%
20110425 15
 
0.1%
20110125 14
 
0.1%
Other values (3082) 7960
79.6%
(Missing) 1615
 
16.2%
ValueCountFrequency (%)
20050517 1
 
< 0.1%
20060920 1
 
< 0.1%
20081212 1
 
< 0.1%
20090219 1
 
< 0.1%
20090305 1
 
< 0.1%
20090306 2
< 0.1%
20090307 1
 
< 0.1%
20090309 3
< 0.1%
20090311 1
 
< 0.1%
20090312 2
< 0.1%
ValueCountFrequency (%)
20240510 3
< 0.1%
20240509 1
 
< 0.1%
20240508 1
 
< 0.1%
20240507 1
 
< 0.1%
20240503 1
 
< 0.1%
20240430 1
 
< 0.1%
20240429 1
 
< 0.1%
20240426 1
 
< 0.1%
20240424 1
 
< 0.1%
20240423 3
< 0.1%

지점설립일자
Text

MISSING 

Distinct3540
Distinct (%)40.5%
Missing1252
Missing (%)12.5%
Memory size156.2 KiB
2024-05-11T08:00:39.970933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters69984
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1348 ?
Unique (%)15.4%

Sample

1st row20110509
2nd row20141210
3rd row20180118
4th row20180104
5th row20160620
ValueCountFrequency (%)
20090611 30
 
0.3%
20090820 29
 
0.3%
20090520 18
 
0.2%
20090605 15
 
0.2%
20090514 15
 
0.2%
20090528 15
 
0.2%
20120531 14
 
0.2%
20090511 14
 
0.2%
20090623 13
 
0.1%
20090507 13
 
0.1%
Other values (3530) 8572
98.0%
2024-05-11T08:00:41.434565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22788
32.6%
2 15840
22.6%
1 14024
20.0%
3 2882
 
4.1%
7 2631
 
3.8%
9 2617
 
3.7%
6 2447
 
3.5%
5 2336
 
3.3%
4 2211
 
3.2%
8 2202
 
3.1%
Other values (4) 6
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69978
> 99.9%
Space Separator 3
 
< 0.1%
Lowercase Letter 2
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 22788
32.6%
2 15840
22.6%
1 14024
20.0%
3 2882
 
4.1%
7 2631
 
3.8%
9 2617
 
3.7%
6 2447
 
3.5%
5 2336
 
3.3%
4 2211
 
3.2%
8 2202
 
3.1%
Lowercase Letter
ValueCountFrequency (%)
a 1
50.0%
y 1
50.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Uppercase Letter
ValueCountFrequency (%)
M 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69981
> 99.9%
Latin 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 22788
32.6%
2 15840
22.6%
1 14024
20.0%
3 2882
 
4.1%
7 2631
 
3.8%
9 2617
 
3.7%
6 2447
 
3.5%
5 2336
 
3.3%
4 2211
 
3.2%
8 2202
 
3.1%
Latin
ValueCountFrequency (%)
M 1
33.3%
a 1
33.3%
y 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69984
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 22788
32.6%
2 15840
22.6%
1 14024
20.0%
3 2882
 
4.1%
7 2631
 
3.8%
9 2617
 
3.7%
6 2447
 
3.5%
5 2336
 
3.3%
4 2211
 
3.2%
8 2202
 
3.1%
Other values (4) 6
 
< 0.1%

본점여부
Categorical

IMBALANCE 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
본점 9936
99.4%
지점 64
 
0.6%

Length

2024-05-11T08:00:42.007936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:00:42.398936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
본점 9936
99.4%
지점 64
 
0.6%

최근수정일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3168
Distinct (%)31.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20152700
Minimum20090518
Maximum20240510
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T08:00:42.982661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090518
5-th percentile20091118
Q120111007
median20140808
Q320190326
95-th percentile20231011
Maximum20240510
Range149992
Interquartile range (IQR)79318.75

Descriptive statistics

Standard deviation45724.625
Coefficient of variation (CV)0.0022689082
Kurtosis-1.0531398
Mean20152700
Median Absolute Deviation (MAD)30490.5
Skewness0.45140274
Sum2.01527 × 1011
Variance2.0907414 × 109
MonotonicityNot monotonic
2024-05-11T08:00:43.650471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091117 80
 
0.8%
20091118 56
 
0.6%
20100927 50
 
0.5%
20090609 46
 
0.5%
20100330 44
 
0.4%
20091116 39
 
0.4%
20090622 37
 
0.4%
20130621 35
 
0.4%
20091119 34
 
0.3%
20100517 30
 
0.3%
Other values (3158) 9549
95.5%
ValueCountFrequency (%)
20090518 2
 
< 0.1%
20090521 5
 
0.1%
20090601 2
 
< 0.1%
20090602 2
 
< 0.1%
20090603 6
 
0.1%
20090604 22
0.2%
20090605 1
 
< 0.1%
20090608 6
 
0.1%
20090609 46
0.5%
20090610 20
0.2%
ValueCountFrequency (%)
20240510 2
 
< 0.1%
20240509 5
0.1%
20240508 6
0.1%
20240507 10
0.1%
20240503 8
0.1%
20240502 3
 
< 0.1%
20240501 3
 
< 0.1%
20240430 6
0.1%
20240429 4
 
< 0.1%
20240426 3
 
< 0.1%

Interactions

2024-05-11T08:00:18.911892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:13.521574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:14.635067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:15.997336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:17.217981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:19.210328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:13.692597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:14.898906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:16.244260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:17.585544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:19.491328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:13.885275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:15.157972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:16.466127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:17.888680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:20.044375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:14.084980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:15.463607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:16.666018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:18.217964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:20.354114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:14.356120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:15.751968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:16.921131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:18.546470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T08:00:44.097676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록신청사업영업구분법인여부우편번호등록일자유효기간만료일자폐쇄일자본점여부최근수정일자
등록신청사업1.0000.0610.0000.0170.1680.1220.1990.0000.171
영업구분0.0611.0000.2000.0690.5640.5930.1720.0370.476
법인여부0.0000.2001.0000.0660.2740.2920.2650.1740.357
우편번호0.0170.0690.0661.0000.1720.1680.2670.0000.178
등록일자0.1680.5640.2740.1721.0000.9630.8620.0530.853
유효기간만료일자0.1220.5930.2920.1680.9631.0000.8480.0520.923
폐쇄일자0.1990.1720.2650.2670.8620.8481.0000.0560.984
본점여부0.0000.0370.1740.0000.0530.0520.0561.0000.099
최근수정일자0.1710.4760.3570.1780.8530.9230.9840.0991.000
2024-05-11T08:00:44.498237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
본점여부법인여부영업구분등록신청사업
본점여부1.0000.1110.0390.000
법인여부0.1111.0000.2140.000
영업구분0.0390.2141.0000.065
등록신청사업0.0000.0000.0651.000
2024-05-11T08:00:44.886317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호등록일자유효기간만료일자폐쇄일자최근수정일자등록신청사업영업구분법인여부본점여부
우편번호1.0000.0150.0330.0330.0220.0110.0570.0520.000
등록일자0.0151.0000.9960.9620.9660.1680.3410.2740.052
유효기간만료일자0.0330.9961.0000.9620.9660.0940.3520.2240.040
폐쇄일자0.0330.9620.9621.0000.9920.1530.1000.2030.043
최근수정일자0.0220.9660.9660.9921.0000.1310.2750.2740.076
등록신청사업0.0110.1680.0940.1530.1311.0000.0650.0000.000
영업구분0.0570.3410.3520.1000.2750.0651.0000.2140.039
법인여부0.0520.2740.2240.2030.2740.0000.2141.0000.111
본점여부0.0000.0520.0400.0430.0760.0000.0390.1111.000

Missing values

2024-05-11T08:00:20.819342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T08:00:21.418148image/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.
2024-05-11T08:00:21.863154image/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
16255대부업유효기간만료2011-서울금천-00010포마텍개인3283-0002서울특별시 금천구 가산동 459번지 3호서울특별시 금천구 가산디지털1로 205-28 (가산동)1530232011050920140509<NA>20110509본점20140513
7543대부중개업폐업2014-서울중구-0154(대부중개)보타니대부개인<NA>서울특별시 중구 충무로3가 49번지 엘크루메트로시티-911서울특별시 중구 충무로 13, 엘크루메트로시티 911호 (충무로3가)<NA>20171018202010192019071120141210본점20190711
30666<NA><NA>2008-서울특별시-01945다원개인027372882서울특별시 종로구 계동 14-9<NA>11027020080709<NA>20090701<NA>본점20090702
8009대부중개업폐업2018-서울금천-0004(주)에스엘피대부중개법인02-3390-8850서울특별시 금천구 가산동 60번지 44호 이앤씨드림타워7차-410서울특별시 금천구 디지털로9길 46, 이앤씨드림타워7차 410호 (가산동)<NA>20180118202101182019022020180118본점20190220
9329대부중개업<NA>2018-서울서초-0006(대부중개업)(주)안녕펀딩대부법인02-6292-9377서울특별시 서초구 잠원동 35번지 25호 J빌딩 6층서울특별시 서초구 신반포로45길 34, J빌딩 6층 (잠원동)<NA>2018010420210104<NA>20180104본점20180222
8656대부중개업폐업2017-서울강동-00014(주)디브이씨트리대부중개법인070-5143-2458서울특별시 강동구 천호동 449번지 49호 -411서울특별시 강동구 천호대로 1073, 4층 411호 (천호동, 힐탑프라자)<NA>20160621201906212018080620160620본점20180806
4877대부중개업유효기간만료2019-서울강남-0002(대부중개업)(주)프로미스대부법인02-6440-5110서울특별시 강남구 역삼동 815번지 점프밀라노-901서울특별시 강남구 강남대로 432, 점프밀라노 901호 (역삼동)<NA>2019010220220102<NA>20190102본점20220105
21077대부업폐업2012-서울관악구-00021(대부업)GNG대부개인02-843-2582서울특별시 관악구 신림동 651번지 46호<NA>15101320120403201504032012072420120403본점20120724
224대부중개업폐업2022-서울강동-00016행복금융컨설팅대부중개개인02-6013-9997서울특별시 강동구 길동 345번지 9호서울특별시 강동구 천중로 213, 3층 305호 (길동)<NA>20220705202507042024041920220705본점20240419
8551대부업직권취소2017-서울광진-0041(대부업)원클릭대부개인02-455-6344<NA>서울특별시 광진구 광나루로56길 85, 18층 12호 (구의동, 테크노마트)<NA>2017062820200628<NA>20170628본점20180903
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