Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells19181
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
Author동작구
URLhttps://data.seoul.go.kr/dataList/OA-10635/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 (94.0%)Imbalance
등록증번호 has 192 (1.9%) missing valuesMissing
사업장 전화번호 has 3424 (34.2%) missing valuesMissing
소재지 has 303 (3.0%) missing valuesMissing
소재지(도로명) has 4778 (47.8%) missing valuesMissing
우편번호 has 5612 (56.1%) missing valuesMissing
유효기간만료일자 has 2066 (20.7%) missing valuesMissing
폐쇄일자 has 1573 (15.7%) missing valuesMissing
지점설립일자 has 1233 (12.3%) missing valuesMissing

Reproduction

Analysis started2024-05-04 03:30:20.550667
Analysis finished2024-05-04 03:30:39.141745
Duration18.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
대부업
6256 
대부중개업
3305 
<NA>
 
439

Length

Max length5
Median length3
Mean length3.7049
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대부업 6256
62.6%
대부중개업 3305
33.1%
<NA> 439
 
4.4%

Length

2024-05-04T03:30:39.400661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T03:30:39.723565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대부업 6256
62.6%
대부중개업 3305
33.1%
na 439
 
4.4%

영업구분
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
3781 
<NA>
2896 
타시군구이관
1197 
영업중
806 
유효기간만료
790 
Other values (2)
530 

Length

Max length6
Median length4
Mean length3.5614
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3781
37.8%
<NA> 2896
29.0%
타시군구이관 1197
 
12.0%
영업중 806
 
8.1%
유효기간만료 790
 
7.9%
직권취소 526
 
5.3%
갱신등록불가 4
 
< 0.1%

Length

2024-05-04T03:30:40.148644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T03:30:40.524558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3781
37.8%
na 2896
29.0%
타시군구이관 1197
 
12.0%
영업중 806
 
8.1%
유효기간만료 790
 
7.9%
직권취소 526
 
5.3%
갱신등록불가 4
 
< 0.1%

등록증번호
Text

MISSING 

Distinct9763
Distinct (%)99.5%
Missing192
Missing (%)1.9%
Memory size156.2 KiB
2024-05-04T03:30:40.963262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length28
Mean length19.507647
Min length1

Characters and Unicode

Total characters191331
Distinct characters85
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

Unique9719 ?
Unique (%)99.1%

Sample

1st row2018-서울서초-0106(대부업)
2nd row2016-서울구로-044(대부업)
3rd row2010-서울관악-00025(대부중개업)
4th row2010-서울동작-00043(대부업)
5th row2008-서울특별시-01935(대부업)
ValueCountFrequency (%)
2015-서울특별시 18
 
0.2%
2012-서울특별시 17
 
0.2%
2013-서울특별시 15
 
0.2%
2010-서울 14
 
0.1%
2014-서울특별시 12
 
0.1%
2011-서울특별시 12
 
0.1%
2016-서울특별시 10
 
0.1%
대부업 9
 
0.1%
성북구-00003 7
 
0.1%
성북구-00013 5
 
0.1%
Other values (9722) 9844
98.8%
2024-05-04T03:30:41.855167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 33886
17.7%
- 19607
 
10.2%
2 15703
 
8.2%
1 11785
 
6.2%
10850
 
5.7%
9779
 
5.1%
8440
 
4.4%
( 8181
 
4.3%
8131
 
4.2%
) 8128
 
4.2%
Other values (75) 56841
29.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82535
43.1%
Other Letter 72724
38.0%
Dash Punctuation 19607
 
10.2%
Open Punctuation 8181
 
4.3%
Close Punctuation 8128
 
4.2%
Space Separator 156
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10850
14.9%
9779
13.4%
8440
11.6%
8131
11.2%
7924
10.9%
3447
 
4.7%
2820
 
3.9%
2539
 
3.5%
2530
 
3.5%
2529
 
3.5%
Other values (61) 13735
18.9%
Decimal Number
ValueCountFrequency (%)
0 33886
41.1%
2 15703
19.0%
1 11785
 
14.3%
3 3745
 
4.5%
8 3116
 
3.8%
4 3051
 
3.7%
7 2906
 
3.5%
6 2816
 
3.4%
9 2791
 
3.4%
5 2736
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 19607
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8181
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8128
100.0%
Space Separator
ValueCountFrequency (%)
156
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 118607
62.0%
Hangul 72724
38.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10850
14.9%
9779
13.4%
8440
11.6%
8131
11.2%
7924
10.9%
3447
 
4.7%
2820
 
3.9%
2539
 
3.5%
2530
 
3.5%
2529
 
3.5%
Other values (61) 13735
18.9%
Common
ValueCountFrequency (%)
0 33886
28.6%
- 19607
16.5%
2 15703
13.2%
1 11785
 
9.9%
( 8181
 
6.9%
) 8128
 
6.9%
3 3745
 
3.2%
8 3116
 
2.6%
4 3051
 
2.6%
7 2906
 
2.5%
Other values (4) 8499
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 118607
62.0%
Hangul 72724
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 33886
28.6%
- 19607
16.5%
2 15703
13.2%
1 11785
 
9.9%
( 8181
 
6.9%
) 8128
 
6.9%
3 3745
 
3.2%
8 3116
 
2.6%
4 3051
 
2.6%
7 2906
 
2.5%
Other values (4) 8499
 
7.2%
Hangul
ValueCountFrequency (%)
10850
14.9%
9779
13.4%
8440
11.6%
8131
11.2%
7924
10.9%
3447
 
4.7%
2820
 
3.9%
2539
 
3.5%
2530
 
3.5%
2529
 
3.5%
Other values (61) 13735
18.9%

상호
Text

Distinct8675
Distinct (%)86.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T03:30:42.392823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length32
Mean length7.7413
Min length1

Characters and Unicode

Total characters77413
Distinct characters781
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

Unique7592 ?
Unique (%)75.9%

Sample

1st row거성아이앤지대부(주)
2nd row무지개캐피탈대부
3rd row브이지에프대부중개
4th rowYes 대부
5th row코드론
ValueCountFrequency (%)
주식회사 832
 
7.0%
대부중개 309
 
2.6%
대부 302
 
2.5%
유한회사 64
 
0.5%
18
 
0.2%
캐피탈 17
 
0.1%
대부업 14
 
0.1%
미래 13
 
0.1%
전당포 10
 
0.1%
the 9
 
0.1%
Other values (8705) 10378
86.7%
2024-05-04T03:30:43.745125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8493
 
11.0%
8131
 
10.5%
2722
 
3.5%
2210
 
2.9%
2027
 
2.6%
2012
 
2.6%
1969
 
2.5%
1921
 
2.5%
) 1913
 
2.5%
( 1904
 
2.5%
Other values (771) 44111
57.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67806
87.6%
Uppercase Letter 2265
 
2.9%
Space Separator 1969
 
2.5%
Close Punctuation 1913
 
2.5%
Open Punctuation 1904
 
2.5%
Lowercase Letter 1020
 
1.3%
Decimal Number 272
 
0.4%
Other Punctuation 221
 
0.3%
Dash Punctuation 26
 
< 0.1%
Other Symbol 14
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8493
 
12.5%
8131
 
12.0%
2722
 
4.0%
2210
 
3.3%
2027
 
3.0%
2012
 
3.0%
1921
 
2.8%
1393
 
2.1%
1114
 
1.6%
1055
 
1.6%
Other values (695) 36728
54.2%
Uppercase Letter
ValueCountFrequency (%)
S 310
13.7%
K 210
 
9.3%
J 185
 
8.2%
C 163
 
7.2%
M 159
 
7.0%
H 136
 
6.0%
L 100
 
4.4%
A 98
 
4.3%
N 88
 
3.9%
O 84
 
3.7%
Other values (16) 732
32.3%
Lowercase Letter
ValueCountFrequency (%)
e 144
14.1%
n 113
11.1%
o 99
 
9.7%
a 83
 
8.1%
s 69
 
6.8%
t 65
 
6.4%
i 54
 
5.3%
r 52
 
5.1%
m 42
 
4.1%
c 38
 
3.7%
Other values (15) 261
25.6%
Decimal Number
ValueCountFrequency (%)
1 94
34.6%
2 45
16.5%
4 28
 
10.3%
9 26
 
9.6%
3 26
 
9.6%
5 20
 
7.4%
0 15
 
5.5%
6 12
 
4.4%
8 3
 
1.1%
7 3
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 127
57.5%
& 78
35.3%
? 6
 
2.7%
, 5
 
2.3%
* 2
 
0.9%
1
 
0.5%
@ 1
 
0.5%
/ 1
 
0.5%
Space Separator
ValueCountFrequency (%)
1969
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1913
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1904
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%
Other Symbol
ValueCountFrequency (%)
14
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67804
87.6%
Common 6308
 
8.1%
Latin 3285
 
4.2%
Han 16
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8493
 
12.5%
8131
 
12.0%
2722
 
4.0%
2210
 
3.3%
2027
 
3.0%
2012
 
3.0%
1921
 
2.8%
1393
 
2.1%
1114
 
1.6%
1055
 
1.6%
Other values (681) 36726
54.2%
Latin
ValueCountFrequency (%)
S 310
 
9.4%
K 210
 
6.4%
J 185
 
5.6%
C 163
 
5.0%
M 159
 
4.8%
e 144
 
4.4%
H 136
 
4.1%
n 113
 
3.4%
L 100
 
3.0%
o 99
 
3.0%
Other values (41) 1666
50.7%
Common
ValueCountFrequency (%)
1969
31.2%
) 1913
30.3%
( 1904
30.2%
. 127
 
2.0%
1 94
 
1.5%
& 78
 
1.2%
2 45
 
0.7%
4 28
 
0.4%
- 26
 
0.4%
9 26
 
0.4%
Other values (14) 98
 
1.6%
Han
ValueCountFrequency (%)
2
 
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (5) 5
31.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67789
87.6%
ASCII 9592
 
12.4%
CJK 16
 
< 0.1%
None 15
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
8493
 
12.5%
8131
 
12.0%
2722
 
4.0%
2210
 
3.3%
2027
 
3.0%
2012
 
3.0%
1921
 
2.8%
1393
 
2.1%
1114
 
1.6%
1055
 
1.6%
Other values (679) 36711
54.2%
ASCII
ValueCountFrequency (%)
1969
20.5%
) 1913
19.9%
( 1904
19.8%
S 310
 
3.2%
K 210
 
2.2%
J 185
 
1.9%
C 163
 
1.7%
M 159
 
1.7%
e 144
 
1.5%
H 136
 
1.4%
Other values (64) 2499
26.1%
None
ValueCountFrequency (%)
14
93.3%
1
 
6.7%
CJK
ValueCountFrequency (%)
2
 
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (5) 5
31.2%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

법인여부
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
개인
7139 
법인
2861 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 7139
71.4%
법인 2861
28.6%

Length

2024-05-04T03:30:44.142841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T03:30:44.447716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 7139
71.4%
법인 2861
28.6%
Distinct5805
Distinct (%)88.3%
Missing3424
Missing (%)34.2%
Memory size156.2 KiB
2024-05-04T03:30:44.922731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length40
Mean length10.585462
Min length1

Characters and Unicode

Total characters69610
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

Unique5180 ?
Unique (%)78.8%

Sample

1st row02-535-0131
2nd row0263403201
3rd row1566-8781
4th row023255879
5th row1599-6627
ValueCountFrequency (%)
02 272
 
3.7%
63
 
0.9%
070 40
 
0.5%
010 11
 
0.1%
435 6
 
0.1%
434 6
 
0.1%
1599 5
 
0.1%
2212 5
 
0.1%
025117185 5
 
0.1%
1566 5
 
0.1%
Other values (6100) 6934
94.3%
2024-05-04T03:30:45.816603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11369
16.3%
2 10228
14.7%
- 7073
10.2%
5 5909
8.5%
7 5397
7.8%
6 5057
7.3%
1 4999
7.2%
8 4868
7.0%
3 4853
7.0%
4 4697
6.7%
Other values (20) 5160
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61375
88.2%
Dash Punctuation 7073
 
10.2%
Space Separator 859
 
1.2%
Other Punctuation 167
 
0.2%
Close Punctuation 67
 
0.1%
Math Symbol 35
 
0.1%
Open Punctuation 18
 
< 0.1%
Other Letter 13
 
< 0.1%
Uppercase Letter 2
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11369
18.5%
2 10228
16.7%
5 5909
9.6%
7 5397
8.8%
6 5057
8.2%
1 4999
8.1%
8 4868
7.9%
3 4853
7.9%
4 4697
7.7%
9 3998
 
6.5%
Other Letter
ValueCountFrequency (%)
3
23.1%
3
23.1%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
* 103
61.7%
/ 38
 
22.8%
. 26
 
15.6%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 7073
100.0%
Space Separator
ValueCountFrequency (%)
859
100.0%
Close Punctuation
ValueCountFrequency (%)
) 67
100.0%
Math Symbol
ValueCountFrequency (%)
~ 35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69595
> 99.9%
Hangul 13
 
< 0.1%
Latin 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11369
16.3%
2 10228
14.7%
- 7073
10.2%
5 5909
8.5%
7 5397
7.8%
6 5057
7.3%
1 4999
7.2%
8 4868
7.0%
3 4853
7.0%
4 4697
6.7%
Other values (9) 5145
7.4%
Hangul
ValueCountFrequency (%)
3
23.1%
3
23.1%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
Latin
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69597
> 99.9%
Hangul 13
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11369
16.3%
2 10228
14.7%
- 7073
10.2%
5 5909
8.5%
7 5397
7.8%
6 5057
7.3%
1 4999
7.2%
8 4868
7.0%
3 4853
7.0%
4 4697
6.7%
Other values (11) 5147
7.4%
Hangul
ValueCountFrequency (%)
3
23.1%
3
23.1%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%

소재지
Text

MISSING 

Distinct8669
Distinct (%)89.4%
Missing303
Missing (%)3.0%
Memory size156.2 KiB
2024-05-04T03:30:46.521563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length48
Mean length31.449727
Min length15

Characters and Unicode

Total characters304968
Distinct characters611
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7905 ?
Unique (%)81.5%

Sample

1st row서울특별시 서초구 서초동 1307번지 7호 센터프라자-811
2nd row서울특별시 구로구 구로동 1267번지 108 -1402
3rd row서울특별시 관악구 신림동 1734번지 102 신림동부센트레빌-1104
4th row서울특별시 동작구 사당동 141번지 177호 -202
5th row서울특별시 영등포구 양평동3가 15-1 월드메르디앙비즈센타 1010호
ValueCountFrequency (%)
서울특별시 9696
 
17.0%
강남구 1603
 
2.8%
서초구 948
 
1.7%
1호 727
 
1.3%
역삼동 697
 
1.2%
송파구 574
 
1.0%
서초동 568
 
1.0%
중구 545
 
1.0%
영등포구 467
 
0.8%
2호 459
 
0.8%
Other values (9403) 40827
71.5%
2024-05-04T03:30:47.623292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
67701
22.2%
1 13626
 
4.5%
12068
 
4.0%
11065
 
3.6%
10500
 
3.4%
9947
 
3.3%
9747
 
3.2%
9706
 
3.2%
9697
 
3.2%
2 8796
 
2.9%
Other values (601) 142115
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 166503
54.6%
Space Separator 67701
22.2%
Decimal Number 63573
 
20.8%
Dash Punctuation 5458
 
1.8%
Uppercase Letter 1133
 
0.4%
Other Punctuation 221
 
0.1%
Lowercase Letter 152
 
< 0.1%
Close Punctuation 96
 
< 0.1%
Open Punctuation 94
 
< 0.1%
Letter Number 28
 
< 0.1%
Other values (2) 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12068
 
7.2%
11065
 
6.6%
10500
 
6.3%
9947
 
6.0%
9747
 
5.9%
9706
 
5.8%
9697
 
5.8%
8538
 
5.1%
8465
 
5.1%
7932
 
4.8%
Other values (533) 68838
41.3%
Uppercase Letter
ValueCountFrequency (%)
B 257
22.7%
A 219
19.3%
D 70
 
6.2%
S 68
 
6.0%
T 55
 
4.9%
C 52
 
4.6%
K 45
 
4.0%
I 43
 
3.8%
L 40
 
3.5%
E 36
 
3.2%
Other values (15) 248
21.9%
Lowercase Letter
ValueCountFrequency (%)
e 25
16.4%
i 17
11.2%
n 16
10.5%
r 12
 
7.9%
t 11
 
7.2%
s 10
 
6.6%
o 9
 
5.9%
l 7
 
4.6%
u 7
 
4.6%
w 7
 
4.6%
Other values (9) 31
20.4%
Decimal Number
ValueCountFrequency (%)
1 13626
21.4%
2 8796
13.8%
0 8082
12.7%
3 7101
11.2%
4 5636
8.9%
5 4952
 
7.8%
6 4556
 
7.2%
7 4155
 
6.5%
9 3364
 
5.3%
8 3305
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 89
40.3%
/ 67
30.3%
. 63
28.5%
1
 
0.5%
# 1
 
0.5%
Letter Number
ValueCountFrequency (%)
20
71.4%
5
 
17.9%
3
 
10.7%
Space Separator
ValueCountFrequency (%)
67701
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5458
100.0%
Close Punctuation
ValueCountFrequency (%)
) 96
100.0%
Open Punctuation
ValueCountFrequency (%)
( 94
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 166504
54.6%
Common 137151
45.0%
Latin 1313
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12068
 
7.2%
11065
 
6.6%
10500
 
6.3%
9947
 
6.0%
9747
 
5.9%
9706
 
5.8%
9697
 
5.8%
8538
 
5.1%
8465
 
5.1%
7932
 
4.8%
Other values (534) 68839
41.3%
Latin
ValueCountFrequency (%)
B 257
19.6%
A 219
16.7%
D 70
 
5.3%
S 68
 
5.2%
T 55
 
4.2%
C 52
 
4.0%
K 45
 
3.4%
I 43
 
3.3%
L 40
 
3.0%
E 36
 
2.7%
Other values (37) 428
32.6%
Common
ValueCountFrequency (%)
67701
49.4%
1 13626
 
9.9%
2 8796
 
6.4%
0 8082
 
5.9%
3 7101
 
5.2%
4 5636
 
4.1%
- 5458
 
4.0%
5 4952
 
3.6%
6 4556
 
3.3%
7 4155
 
3.0%
Other values (10) 7088
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 166503
54.6%
ASCII 138435
45.4%
Number Forms 28
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
67701
48.9%
1 13626
 
9.8%
2 8796
 
6.4%
0 8082
 
5.8%
3 7101
 
5.1%
4 5636
 
4.1%
- 5458
 
3.9%
5 4952
 
3.6%
6 4556
 
3.3%
7 4155
 
3.0%
Other values (53) 8372
 
6.0%
Hangul
ValueCountFrequency (%)
12068
 
7.2%
11065
 
6.6%
10500
 
6.3%
9947
 
6.0%
9747
 
5.9%
9706
 
5.8%
9697
 
5.8%
8538
 
5.1%
8465
 
5.1%
7932
 
4.8%
Other values (533) 68838
41.3%
Number Forms
ValueCountFrequency (%)
20
71.4%
5
 
17.9%
3
 
10.7%
None
ValueCountFrequency (%)
1
50.0%
1
50.0%

소재지(도로명)
Text

MISSING 

Distinct4735
Distinct (%)90.7%
Missing4778
Missing (%)47.8%
Memory size156.2 KiB
2024-05-04T03:30:48.233683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length54
Mean length37.080046
Min length22

Characters and Unicode

Total characters193632
Distinct characters605
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4296 ?
Unique (%)82.3%

Sample

1st row서울특별시 서초구 강남대로61길 10, 센터프라자 811호 (서초동)
2nd row서울특별시 구로구 새말로 93, 108동 1402호 (구로동, 신도림태영타운)
3rd row서울특별시 은평구 녹번로 45-11 (녹번동, 옥탑)
4th row서울특별시 마포구 마포대로 52, 고려아카데미텔Ⅱ 지하1층 38호 (도화동)
5th row서울특별시 서초구 효령로 304, 7층 55호 (서초동, 국제전자센터)
ValueCountFrequency (%)
서울특별시 5222
 
14.2%
강남구 942
 
2.6%
서초구 573
 
1.6%
2층 458
 
1.2%
역삼동 398
 
1.1%
서초동 374
 
1.0%
3층 372
 
1.0%
영등포구 335
 
0.9%
송파구 305
 
0.8%
4층 288
 
0.8%
Other values (6580) 27606
74.9%
2024-05-04T03:30:49.352873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31661
 
16.4%
1 7483
 
3.9%
, 7170
 
3.7%
6900
 
3.6%
6815
 
3.5%
5799
 
3.0%
5751
 
3.0%
5429
 
2.8%
5279
 
2.7%
) 5263
 
2.7%
Other values (595) 106082
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 107835
55.7%
Decimal Number 34388
 
17.8%
Space Separator 31661
 
16.4%
Other Punctuation 7181
 
3.7%
Close Punctuation 5263
 
2.7%
Open Punctuation 5262
 
2.7%
Dash Punctuation 1022
 
0.5%
Uppercase Letter 832
 
0.4%
Lowercase Letter 148
 
0.1%
Letter Number 32
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6900
 
6.4%
6815
 
6.3%
5799
 
5.4%
5751
 
5.3%
5429
 
5.0%
5279
 
4.9%
5232
 
4.9%
5223
 
4.8%
4176
 
3.9%
2734
 
2.5%
Other values (528) 54497
50.5%
Uppercase Letter
ValueCountFrequency (%)
B 161
19.4%
A 104
12.5%
S 67
 
8.1%
C 54
 
6.5%
T 50
 
6.0%
L 42
 
5.0%
E 41
 
4.9%
G 39
 
4.7%
I 37
 
4.4%
K 36
 
4.3%
Other values (15) 201
24.2%
Lowercase Letter
ValueCountFrequency (%)
e 25
16.9%
n 15
10.1%
i 15
10.1%
r 14
9.5%
o 10
 
6.8%
c 10
 
6.8%
t 10
 
6.8%
w 9
 
6.1%
s 7
 
4.7%
u 7
 
4.7%
Other values (11) 26
17.6%
Decimal Number
ValueCountFrequency (%)
1 7483
21.8%
2 5215
15.2%
0 4544
13.2%
3 4070
11.8%
4 2862
 
8.3%
5 2744
 
8.0%
6 2232
 
6.5%
7 1940
 
5.6%
8 1742
 
5.1%
9 1556
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 7170
99.8%
. 10
 
0.1%
/ 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
21
65.6%
7
 
21.9%
4
 
12.5%
Space Separator
ValueCountFrequency (%)
31661
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5263
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5262
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1022
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 107834
55.7%
Common 84785
43.8%
Latin 1012
 
0.5%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6900
 
6.4%
6815
 
6.3%
5799
 
5.4%
5751
 
5.3%
5429
 
5.0%
5279
 
4.9%
5232
 
4.9%
5223
 
4.8%
4176
 
3.9%
2734
 
2.5%
Other values (527) 54496
50.5%
Latin
ValueCountFrequency (%)
B 161
15.9%
A 104
 
10.3%
S 67
 
6.6%
C 54
 
5.3%
T 50
 
4.9%
L 42
 
4.2%
E 41
 
4.1%
G 39
 
3.9%
I 37
 
3.7%
K 36
 
3.6%
Other values (39) 381
37.6%
Common
ValueCountFrequency (%)
31661
37.3%
1 7483
 
8.8%
, 7170
 
8.5%
) 5263
 
6.2%
( 5262
 
6.2%
2 5215
 
6.2%
0 4544
 
5.4%
3 4070
 
4.8%
4 2862
 
3.4%
5 2744
 
3.2%
Other values (8) 8511
 
10.0%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 107834
55.7%
ASCII 85765
44.3%
Number Forms 32
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31661
36.9%
1 7483
 
8.7%
, 7170
 
8.4%
) 5263
 
6.1%
( 5262
 
6.1%
2 5215
 
6.1%
0 4544
 
5.3%
3 4070
 
4.7%
4 2862
 
3.3%
5 2744
 
3.2%
Other values (54) 9491
 
11.1%
Hangul
ValueCountFrequency (%)
6900
 
6.4%
6815
 
6.3%
5799
 
5.4%
5751
 
5.3%
5429
 
5.0%
5279
 
4.9%
5232
 
4.9%
5223
 
4.8%
4176
 
3.9%
2734
 
2.5%
Other values (527) 54496
50.5%
Number Forms
ValueCountFrequency (%)
21
65.6%
7
 
21.9%
4
 
12.5%
CJK
ValueCountFrequency (%)
1
100.0%

우편번호
Real number (ℝ)

MISSING 

Distinct1370
Distinct (%)31.2%
Missing5612
Missing (%)56.1%
Infinite0
Infinite (%)0.0%
Mean136234.81
Minimum2519
Maximum158877
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T03:30:49.757435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2519
5-th percentile110065
Q1132010
median136110
Q3143200
95-th percentile157200.65
Maximum158877
Range156358
Interquartile range (IQR)11190

Descriptive statistics

Standard deviation14871.423
Coefficient of variation (CV)0.10916023
Kurtosis13.080281
Mean136234.81
Median Absolute Deviation (MAD)5268.5
Skewness-2.0168911
Sum5.9779835 × 108
Variance2.2115923 × 108
MonotonicityNot monotonic
2024-05-04T03:30:50.198277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
135080 159
 
1.6%
137070 136
 
1.4%
135010 67
 
0.7%
157010 55
 
0.5%
151015 53
 
0.5%
152050 51
 
0.5%
151050 45
 
0.4%
158070 45
 
0.4%
142070 41
 
0.4%
158090 39
 
0.4%
Other values (1360) 3697
37.0%
(Missing) 5612
56.1%
ValueCountFrequency (%)
2519 1
< 0.1%
3163 1
< 0.1%
4526 1
< 0.1%
4536 1
< 0.1%
4537 1
< 0.1%
4538 1
< 0.1%
4801 1
< 0.1%
7220 1
< 0.1%
7326 1
< 0.1%
14538 1
< 0.1%
ValueCountFrequency (%)
158877 1
 
< 0.1%
158871 1
 
< 0.1%
158864 3
< 0.1%
158860 7
0.1%
158859 4
< 0.1%
158858 1
 
< 0.1%
158857 1
 
< 0.1%
158856 1
 
< 0.1%
158849 1
 
< 0.1%
158842 1
 
< 0.1%

등록일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3537
Distinct (%)35.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20136476
Minimum20051216
Maximum20240503
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T03:30:50.625265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20051216
5-th percentile20070905
Q120091118
median20130227
Q320170726
95-th percentile20230117
Maximum20240503
Range189287
Interquartile range (IQR)79608

Descriptive statistics

Standard deviation48752.057
Coefficient of variation (CV)0.0024210819
Kurtosis-0.91836408
Mean20136476
Median Absolute Deviation (MAD)39598
Skewness0.45314499
Sum2.0136476 × 1011
Variance2.3767631 × 109
MonotonicityNot monotonic
2024-05-04T03:30:51.071277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20080814 32
 
0.3%
20080731 28
 
0.3%
20081222 23
 
0.2%
20090611 21
 
0.2%
20080818 19
 
0.2%
20080822 17
 
0.2%
20080805 14
 
0.1%
20080721 14
 
0.1%
20090226 13
 
0.1%
20090520 13
 
0.1%
Other values (3527) 9806
98.1%
ValueCountFrequency (%)
20051216 1
 
< 0.1%
20060306 1
 
< 0.1%
20060320 4
< 0.1%
20060321 1
 
< 0.1%
20060323 1
 
< 0.1%
20060324 4
< 0.1%
20060329 2
< 0.1%
20060331 1
 
< 0.1%
20060405 1
 
< 0.1%
20060407 2
< 0.1%
ValueCountFrequency (%)
20240503 2
 
< 0.1%
20240502 1
 
< 0.1%
20240430 1
 
< 0.1%
20240426 1
 
< 0.1%
20240425 2
 
< 0.1%
20240424 5
0.1%
20240423 1
 
< 0.1%
20240422 4
< 0.1%
20240418 1
 
< 0.1%
20240415 2
 
< 0.1%

유효기간만료일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3303
Distinct (%)41.6%
Missing2066
Missing (%)20.7%
Infinite0
Infinite (%)0.0%
Mean20181037
Minimum20100208
Maximum20270503
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T03:30:51.412915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100208
5-th percentile20120224
Q120141020
median20180106
Q320211216
95-th percentile20260420
Maximum20270503
Range170295
Interquartile range (IQR)70195.75

Descriptive statistics

Standard deviation44348.115
Coefficient of variation (CV)0.0021975142
Kurtosis-0.98321238
Mean20181037
Median Absolute Deviation (MAD)39079.5
Skewness0.31199208
Sum1.6011635 × 1011
Variance1.9667553 × 109
MonotonicityNot monotonic
2024-05-04T03:30:51.796420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110831 13
 
0.1%
20140608 12
 
0.1%
20140721 12
 
0.1%
20180914 12
 
0.1%
20161203 11
 
0.1%
20150831 11
 
0.1%
20180622 11
 
0.1%
20110731 11
 
0.1%
20131102 11
 
0.1%
20140711 10
 
0.1%
Other values (3293) 7820
78.2%
(Missing) 2066
 
20.7%
ValueCountFrequency (%)
20100208 1
< 0.1%
20100216 1
< 0.1%
20100308 1
< 0.1%
20100410 1
< 0.1%
20100411 1
< 0.1%
20100418 2
< 0.1%
20100426 1
< 0.1%
20100514 1
< 0.1%
20100515 2
< 0.1%
20100613 1
< 0.1%
ValueCountFrequency (%)
20270503 2
 
< 0.1%
20270501 1
 
< 0.1%
20270430 1
 
< 0.1%
20270426 1
 
< 0.1%
20270425 2
 
< 0.1%
20270424 5
0.1%
20270423 1
 
< 0.1%
20270422 2
 
< 0.1%
20270421 2
 
< 0.1%
20270417 1
 
< 0.1%

폐쇄일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3112
Distinct (%)36.9%
Missing1573
Missing (%)15.7%
Infinite0
Infinite (%)0.0%
Mean20141891
Minimum20060920
Maximum20240503
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T03:30:52.119591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060920
5-th percentile20090902
Q120110324
median20130731
Q320170405
95-th percentile20220927
Maximum20240503
Range179583
Interquartile range (IQR)60081.5

Descriptive statistics

Standard deviation40949.457
Coefficient of variation (CV)0.0020330493
Kurtosis-0.56592244
Mean20141891
Median Absolute Deviation (MAD)29804
Skewness0.68689506
Sum1.6973571 × 1011
Variance1.676858 × 109
MonotonicityNot monotonic
2024-05-04T03:30:52.386570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091116 210
 
2.1%
20100927 66
 
0.7%
20101213 24
 
0.2%
20170124 20
 
0.2%
20111108 17
 
0.2%
20160725 17
 
0.2%
20110420 16
 
0.2%
20110914 16
 
0.2%
20110901 15
 
0.1%
20110503 15
 
0.1%
Other values (3102) 8011
80.1%
(Missing) 1573
 
15.7%
ValueCountFrequency (%)
20060920 1
< 0.1%
20080730 1
< 0.1%
20081217 1
< 0.1%
20090211 1
< 0.1%
20090219 1
< 0.1%
20090220 1
< 0.1%
20090305 1
< 0.1%
20090306 1
< 0.1%
20090307 1
< 0.1%
20090309 2
< 0.1%
ValueCountFrequency (%)
20240503 2
< 0.1%
20240502 2
< 0.1%
20240501 3
< 0.1%
20240425 2
< 0.1%
20240424 1
 
< 0.1%
20240423 4
< 0.1%
20240422 2
< 0.1%
20240419 2
< 0.1%
20240418 2
< 0.1%
20240417 1
 
< 0.1%

지점설립일자
Text

MISSING 

Distinct3585
Distinct (%)40.9%
Missing1233
Missing (%)12.3%
Memory size156.2 KiB
2024-05-04T03:30:52.936876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters70136
Distinct characters15
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

Unique1371 ?
Unique (%)15.6%

Sample

1st row20180907
2nd row20160627
3rd row20091111
4th row20101005
5th row20110210
ValueCountFrequency (%)
20090611 22
 
0.3%
20090520 18
 
0.2%
20090605 17
 
0.2%
20090820 17
 
0.2%
20090528 17
 
0.2%
20090821 17
 
0.2%
20090511 15
 
0.2%
20090514 15
 
0.2%
20090512 13
 
0.1%
20090623 13
 
0.1%
Other values (3575) 8603
98.1%
2024-05-04T03:30:53.985469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22637
32.3%
2 16003
22.8%
1 14105
20.1%
3 2787
 
4.0%
9 2665
 
3.8%
7 2620
 
3.7%
6 2508
 
3.6%
5 2309
 
3.3%
8 2263
 
3.2%
4 2227
 
3.2%
Other values (5) 12
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70124
> 99.9%
Space Separator 6
 
< 0.1%
Lowercase Letter 4
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 22637
32.3%
2 16003
22.8%
1 14105
20.1%
3 2787
 
4.0%
9 2665
 
3.8%
7 2620
 
3.7%
6 2508
 
3.6%
5 2309
 
3.3%
8 2263
 
3.2%
4 2227
 
3.2%
Lowercase Letter
ValueCountFrequency (%)
a 2
50.0%
y 1
25.0%
r 1
25.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Uppercase Letter
ValueCountFrequency (%)
M 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70130
> 99.9%
Latin 6
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 22637
32.3%
2 16003
22.8%
1 14105
20.1%
3 2787
 
4.0%
9 2665
 
3.8%
7 2620
 
3.7%
6 2508
 
3.6%
5 2309
 
3.3%
8 2263
 
3.2%
4 2227
 
3.2%
Latin
ValueCountFrequency (%)
M 2
33.3%
a 2
33.3%
y 1
16.7%
r 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70136
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 22637
32.3%
2 16003
22.8%
1 14105
20.1%
3 2787
 
4.0%
9 2665
 
3.8%
7 2620
 
3.7%
6 2508
 
3.6%
5 2309
 
3.3%
8 2263
 
3.2%
4 2227
 
3.2%
Other values (5) 12
 
< 0.1%

본점여부
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
본점
9930 
지점
 
70

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 9930
99.3%
지점 70
 
0.7%

Length

2024-05-04T03:30:54.317851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T03:30:54.502586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
본점 9930
99.3%
지점 70
 
0.7%

최근수정일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3177
Distinct (%)31.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20152762
Minimum20090518
Maximum20240503
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T03:30:54.755688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090518
5-th percentile20091117
Q120110930
median20140818
Q320190415
95-th percentile20230926
Maximum20240503
Range149985
Interquartile range (IQR)79485

Descriptive statistics

Standard deviation45806.262
Coefficient of variation (CV)0.0022729521
Kurtosis-1.0651335
Mean20152762
Median Absolute Deviation (MAD)30510.5
Skewness0.44127285
Sum2.0152762 × 1011
Variance2.0982137 × 109
MonotonicityNot monotonic
2024-05-04T03:30:55.252012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091117 77
 
0.8%
20090609 61
 
0.6%
20091118 55
 
0.5%
20091116 45
 
0.4%
20100927 42
 
0.4%
20100330 40
 
0.4%
20130621 36
 
0.4%
20110425 33
 
0.3%
20160812 31
 
0.3%
20090622 30
 
0.3%
Other values (3167) 9550
95.5%
ValueCountFrequency (%)
20090518 2
 
< 0.1%
20090519 1
 
< 0.1%
20090521 4
 
< 0.1%
20090601 5
 
0.1%
20090602 1
 
< 0.1%
20090603 11
 
0.1%
20090604 13
 
0.1%
20090605 4
 
< 0.1%
20090608 4
 
< 0.1%
20090609 61
0.6%
ValueCountFrequency (%)
20240503 8
0.1%
20240502 4
 
< 0.1%
20240501 4
 
< 0.1%
20240430 3
 
< 0.1%
20240429 2
 
< 0.1%
20240426 2
 
< 0.1%
20240425 6
0.1%
20240424 6
0.1%
20240423 10
0.1%
20240422 5
0.1%

Interactions

2024-05-04T03:30:34.701844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:30:26.570054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:30:28.756467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:30:30.775141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:30:32.571648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:30:35.083865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:30:27.133536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:30:29.174087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:30:31.217050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:30:33.029273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:30:35.447373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:30:27.566503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:30:29.476770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:30:31.487405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:30:33.401094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:30:35.837284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:30:28.017802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:30:29.936722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:30:31.797749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:30:33.798895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:30:36.350980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:30:28.377550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:30:30.314382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:30:32.149889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:30:34.254297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T03:30:55.502600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록신청사업영업구분법인여부우편번호등록일자유효기간만료일자폐쇄일자본점여부최근수정일자
등록신청사업1.0000.1060.0000.0000.2100.1320.1600.0000.157
영업구분0.1061.0000.2770.1960.6300.6120.1960.0410.537
법인여부0.0000.2771.0000.0710.3540.2840.2100.1960.360
우편번호0.0000.1960.0711.0000.3870.3940.1990.0000.299
등록일자0.2100.6300.3540.3871.0000.9780.8640.1030.938
유효기간만료일자0.1320.6120.2840.3940.9781.0000.8520.0960.846
폐쇄일자0.1600.1960.2100.1990.8640.8521.0000.0550.959
본점여부0.0000.0410.1960.0000.1030.0960.0551.0000.131
최근수정일자0.1570.5370.3600.2990.9380.8460.9590.1311.000
2024-05-04T03:30:55.834753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록신청사업법인여부영업구분본점여부
등록신청사업1.0000.0000.0760.000
법인여부0.0001.0000.1990.126
영업구분0.0760.1991.0000.030
본점여부0.0000.1260.0301.000
2024-05-04T03:30:56.108501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호등록일자유효기간만료일자폐쇄일자최근수정일자등록신청사업영업구분법인여부본점여부
우편번호1.000-0.0060.0020.012-0.0020.0000.0710.0850.000
등록일자-0.0061.0000.9970.9610.9660.1610.3730.2720.079
유효기간만료일자0.0020.9971.0000.9640.9660.1020.3800.2180.073
폐쇄일자0.0120.9610.9641.0000.9910.1590.1130.2090.054
최근수정일자-0.0020.9660.9660.9911.0000.1200.3010.2760.101
등록신청사업0.0000.1610.1020.1590.1201.0000.0760.0000.000
영업구분0.0710.3730.3800.1130.3010.0761.0000.1990.030
법인여부0.0850.2720.2180.2090.2760.0000.1991.0000.126
본점여부0.0000.0790.0730.0540.1010.0000.0300.1261.000

Missing values

2024-05-04T03:30:37.065888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T03:30:38.006888image/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.
2024-05-04T03:30:38.751507image/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
5785대부업폐업2018-서울서초-0106(대부업)거성아이앤지대부(주)법인02-535-0131서울특별시 서초구 서초동 1307번지 7호 센터프라자-811서울특별시 서초구 강남대로61길 10, 센터프라자 811호 (서초동)<NA>20180907202109072021041320180907본점20210413
10663대부업타시군구이관2016-서울구로-044(대부업)무지개캐피탈대부개인<NA>서울특별시 구로구 구로동 1267번지 108 -1402서울특별시 구로구 새말로 93, 108동 1402호 (구로동, 신도림태영타운)<NA>20160627201906272017051020160627본점20170510
22583대부중개업폐업2010-서울관악-00025(대부중개업)브이지에프대부중개개인<NA>서울특별시 관악구 신림동 1734번지 102 신림동부센트레빌-1104<NA>15101520091111201211112012011920091111본점20120119
24566대부업<NA>2010-서울동작-00043(대부업)Yes 대부개인<NA>서울특별시 동작구 사당동 141번지 177호 -202<NA>15609020101005201310052011061320101005본점20110613
29605대부업<NA>2008-서울특별시-01935(대부업)코드론개인0263403201서울특별시 영등포구 양평동3가 15-1 월드메르디앙비즈센타 1010호<NA><NA>20080708<NA>20091009<NA>본점20091119
14574대부중개업타시군구이관2014-서울은평-0023(대부중개업)리드캐싱 대부중개개인1566-8781서울특별시 은평구 녹번동 96번지 3호서울특별시 은평구 녹번로 45-11 (녹번동, 옥탑)122830201503042018030420150507<NA>본점20150507
22877대부업유효기간만료2008-서울특별시-03182(대부업)에이스개인023255879서울특별시 마포구 서교동 394-25 동양한강트레벨오피스텔 3층 314호<NA><NA>200812112011121120111214<NA>본점20111217
19352대부중개업폐업2011-서울강북-0006조이론대부중개개인1599-6627서울특별시 강북구 번동 446-13 가든타워 805호<NA>14206020110210201402102013031520110210본점20130319
197대부업영업중2022-서울마포-0024(대부업)지인금융대부주식회사법인02-2088-2990서울특별시 마포구 도화동 36번지 고려아카데미텔Ⅱ서울특별시 마포구 마포대로 52, 고려아카데미텔Ⅱ 지하1층 38호 (도화동)<NA>2022072520250725<NA>20220725본점20240417
15387대부업폐업2013-서울서초-0162(대부업)대부단지개인02-1661-7858서울특별시 서초구 서초동 1445번지 3호 국제전자센터 7층-55서울특별시 서초구 효령로 304, 7층 55호 (서초동, 국제전자센터)13772820131126201611262014110620131126본점20141106
등록신청사업영업구분등록증번호상호법인여부사업장 전화번호소재지소재지(도로명)우편번호등록일자유효기간만료일자폐쇄일자지점설립일자본점여부최근수정일자
13368대부업타시군구이관2013-서울광진-0037(대부업)배가자산관리대부(주)법인3437-7470서울특별시 광진구 능동 236번지 15호서울특별시 광진구 능동로36길 47 (능동)<NA>20150813201808132016012920120918본점20160129
17268대부업직권취소2012-서울양천-00053(대부업)월드컵대부개인<NA>서울특별시 양천구 신월동 984번지 8호 -302<NA>15809020120628201506282013111420120628본점20131114
30794<NA><NA>2008-서울특별시-01142월드개인<NA>서울특별시 노원구 중계동 목련A 302-304호<NA>13922320080130<NA>2009052820080124본점20090622
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