Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells19115
Missing cells (%)12.7%
Duplicate rows2
Duplicate rows (%)< 0.1%
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
Author성북구
URLhttps://data.seoul.go.kr/dataList/OA-11174/S/1/datasetView.do

Alerts

Dataset has 2 (< 0.1%) duplicate rowsDuplicates
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 175 (1.8%) missing valuesMissing
사업장 전화번호 has 3358 (33.6%) missing valuesMissing
소재지 has 312 (3.1%) missing valuesMissing
소재지(도로명) has 4766 (47.7%) missing valuesMissing
우편번호 has 5631 (56.3%) missing valuesMissing
유효기간만료일자 has 2032 (20.3%) missing valuesMissing
폐쇄일자 has 1623 (16.2%) missing valuesMissing
지점설립일자 has 1218 (12.2%) missing valuesMissing

Reproduction

Analysis started2024-05-18 01:26:24.590431
Analysis finished2024-05-18 01:26:42.718568
Duration18.13 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
6135 
대부중개업
3437 
<NA>
 
428

Length

Max length5
Median length3
Mean length3.7302
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대부업 6135
61.4%
대부중개업 3437
34.4%
<NA> 428
 
4.3%

Length

2024-05-18T10:26:43.041947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:26:43.390256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대부업 6135
61.4%
대부중개업 3437
34.4%
na 428
 
4.3%

영업구분
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
3764 
<NA>
2896 
타시군구이관
1177 
영업중
851 
유효기간만료
799 
Other values (2)
513 

Length

Max length6
Median length4
Mean length3.5581
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3764
37.6%
<NA> 2896
29.0%
타시군구이관 1177
 
11.8%
영업중 851
 
8.5%
유효기간만료 799
 
8.0%
직권취소 509
 
5.1%
갱신등록불가 4
 
< 0.1%

Length

2024-05-18T10:26:43.783880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:26:44.162816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3764
37.6%
na 2896
29.0%
타시군구이관 1177
 
11.8%
영업중 851
 
8.5%
유효기간만료 799
 
8.0%
직권취소 509
 
5.1%
갱신등록불가 4
 
< 0.1%

등록증번호
Text

MISSING 

Distinct9777
Distinct (%)99.5%
Missing175
Missing (%)1.8%
Memory size156.2 KiB
2024-05-18T10:26:44.869662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length28
Mean length19.53201
Min length4

Characters and Unicode

Total characters191902
Distinct characters89
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

Unique9734 ?
Unique (%)99.1%

Sample

1st row2009-서울특별시-02731(대부업)
2nd row2006-서울특별시-00612(대부업)
3rd row2010-서울강남-0295
4th row2008-서울특별시-03408(대부중개업)
5th row2007-서울특별시-01538
ValueCountFrequency (%)
2011-서울특별시 22
 
0.2%
2010-서울 17
 
0.2%
2012-서울특별시 15
 
0.2%
2013-서울특별시 14
 
0.1%
2015-서울특별시 10
 
0.1%
2016-서울특별시 10
 
0.1%
2014-서울특별시 9
 
0.1%
2018-서울특별시 9
 
0.1%
성북구-00005 8
 
0.1%
대부중개업 7
 
0.1%
Other values (9732) 9859
98.8%
2024-05-18T10:26:45.928245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 33809
17.6%
- 19632
 
10.2%
2 15726
 
8.2%
1 11939
 
6.2%
서 10895
 
5.7%
울 9792
 
5.1%
대 8515
 
4.4%
( 8229
 
4.3%
부 8191
 
4.3%
) 8170
 
4.3%
Other values (79) 57004
29.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82610
43.0%
Other Letter 73106
38.1%
Dash Punctuation 19632
 
10.2%
Open Punctuation 8229
 
4.3%
Close Punctuation 8170
 
4.3%
Space Separator 155
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 10895
14.9%
울 9792
13.4%
대 8515
11.6%
부 8191
11.2%
업 7952
10.9%
중 3539
 
4.8%
개 2937
 
4.0%
시 2484
 
3.4%
별 2476
 
3.4%
특 2475
 
3.4%
Other values (65) 13850
18.9%
Decimal Number
ValueCountFrequency (%)
0 33809
40.9%
2 15726
19.0%
1 11939
 
14.5%
3 3694
 
4.5%
8 3112
 
3.8%
4 3103
 
3.8%
9 2894
 
3.5%
5 2802
 
3.4%
6 2796
 
3.4%
7 2735
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 19632
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8229
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8170
100.0%
Space Separator
ValueCountFrequency (%)
155
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 118796
61.9%
Hangul 73106
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 10895
14.9%
울 9792
13.4%
대 8515
11.6%
부 8191
11.2%
업 7952
10.9%
중 3539
 
4.8%
개 2937
 
4.0%
시 2484
 
3.4%
별 2476
 
3.4%
특 2475
 
3.4%
Other values (65) 13850
18.9%
Common
ValueCountFrequency (%)
0 33809
28.5%
- 19632
16.5%
2 15726
13.2%
1 11939
 
10.1%
( 8229
 
6.9%
) 8170
 
6.9%
3 3694
 
3.1%
8 3112
 
2.6%
4 3103
 
2.6%
9 2894
 
2.4%
Other values (4) 8488
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 118796
61.9%
Hangul 73106
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 33809
28.5%
- 19632
16.5%
2 15726
13.2%
1 11939
 
10.1%
( 8229
 
6.9%
) 8170
 
6.9%
3 3694
 
3.1%
8 3112
 
2.6%
4 3103
 
2.6%
9 2894
 
2.4%
Other values (4) 8488
 
7.1%
Hangul
ValueCountFrequency (%)
서 10895
14.9%
울 9792
13.4%
대 8515
11.6%
부 8191
11.2%
업 7952
10.9%
중 3539
 
4.8%
개 2937
 
4.0%
시 2484
 
3.4%
별 2476
 
3.4%
특 2475
 
3.4%
Other values (65) 13850
18.9%

상호
Text

Distinct8716
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T10:26:46.753745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length30
Mean length7.7883
Min length1

Characters and Unicode

Total characters77883
Distinct characters774
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

Unique7664 ?
Unique (%)76.6%

Sample

1st row수성대부금융
2nd row석봉미래산업대부
3rd row(주)나우에셋링크대부
4th row(주)캐쉬팡팡
5th row이지연
ValueCountFrequency (%)
주식회사 838
 
7.0%
대부중개 340
 
2.8%
대부 277
 
2.3%
유한회사 49
 
0.4%
캐피탈 19
 
0.2%
대부업 19
 
0.2%
컨설팅 15
 
0.1%
주 14
 
0.1%
대부중개업 13
 
0.1%
loan 10
 
0.1%
Other values (8742) 10364
86.7%
2024-05-18T10:26:48.600844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 8530
 
11.0%
부 8181
 
10.5%
주 2729
 
3.5%
이 2255
 
2.9%
개 2123
 
2.7%
중 2111
 
2.7%
1960
 
2.5%
스 1934
 
2.5%
) 1877
 
2.4%
( 1870
 
2.4%
Other values (764) 44313
56.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68112
87.5%
Uppercase Letter 2389
 
3.1%
Space Separator 1960
 
2.5%
Close Punctuation 1877
 
2.4%
Open Punctuation 1870
 
2.4%
Lowercase Letter 1109
 
1.4%
Other Punctuation 267
 
0.3%
Decimal Number 255
 
0.3%
Dash Punctuation 29
 
< 0.1%
Other Symbol 11
 
< 0.1%
Other values (3) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 8530
 
12.5%
부 8181
 
12.0%
주 2729
 
4.0%
이 2255
 
3.3%
개 2123
 
3.1%
중 2111
 
3.1%
스 1934
 
2.8%
사 1355
 
2.0%
피 1127
 
1.7%
회 1048
 
1.5%
Other values (688) 36719
53.9%
Uppercase Letter
ValueCountFrequency (%)
S 329
13.8%
K 219
 
9.2%
C 188
 
7.9%
J 178
 
7.5%
M 159
 
6.7%
H 136
 
5.7%
B 115
 
4.8%
A 108
 
4.5%
L 99
 
4.1%
E 90
 
3.8%
Other values (16) 768
32.1%
Lowercase Letter
ValueCountFrequency (%)
e 138
12.4%
n 123
11.1%
o 112
10.1%
a 111
10.0%
i 68
 
6.1%
s 65
 
5.9%
t 56
 
5.0%
c 56
 
5.0%
l 53
 
4.8%
d 50
 
4.5%
Other values (14) 277
25.0%
Decimal Number
ValueCountFrequency (%)
1 87
34.1%
2 48
18.8%
4 36
14.1%
9 27
 
10.6%
3 14
 
5.5%
0 12
 
4.7%
5 11
 
4.3%
6 10
 
3.9%
7 8
 
3.1%
8 2
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 147
55.1%
& 103
38.6%
? 6
 
2.2%
, 6
 
2.2%
' 2
 
0.7%
@ 1
 
0.4%
＆ 1
 
0.4%
* 1
 
0.4%
Space Separator
ValueCountFrequency (%)
1960
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1877
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1870
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68109
87.5%
Common 6261
 
8.0%
Latin 3499
 
4.5%
Han 14
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 8530
 
12.5%
부 8181
 
12.0%
주 2729
 
4.0%
이 2255
 
3.3%
개 2123
 
3.1%
중 2111
 
3.1%
스 1934
 
2.8%
사 1355
 
2.0%
피 1127
 
1.7%
회 1048
 
1.5%
Other values (678) 36716
53.9%
Latin
ValueCountFrequency (%)
S 329
 
9.4%
K 219
 
6.3%
C 188
 
5.4%
J 178
 
5.1%
M 159
 
4.5%
e 138
 
3.9%
H 136
 
3.9%
n 123
 
3.5%
B 115
 
3.3%
o 112
 
3.2%
Other values (41) 1802
51.5%
Common
ValueCountFrequency (%)
1960
31.3%
) 1877
30.0%
( 1870
29.9%
. 147
 
2.3%
& 103
 
1.6%
1 87
 
1.4%
2 48
 
0.8%
4 36
 
0.6%
- 29
 
0.5%
9 27
 
0.4%
Other values (14) 77
 
1.2%
Han
ValueCountFrequency (%)
大 2
14.3%
靑 2
14.3%
成 2
14.3%
松 1
7.1%
雲 1
7.1%
信 1
7.1%
正 1
7.1%
鄭 1
7.1%
元 1
7.1%
趙 1
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68097
87.4%
ASCII 9758
 
12.5%
CJK 14
 
< 0.1%
None 12
 
< 0.1%
Number Forms 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 8530
 
12.5%
부 8181
 
12.0%
주 2729
 
4.0%
이 2255
 
3.3%
개 2123
 
3.1%
중 2111
 
3.1%
스 1934
 
2.8%
사 1355
 
2.0%
피 1127
 
1.7%
회 1048
 
1.5%
Other values (676) 36704
53.9%
ASCII
ValueCountFrequency (%)
1960
20.1%
) 1877
19.2%
( 1870
19.2%
S 329
 
3.4%
K 219
 
2.2%
C 188
 
1.9%
J 178
 
1.8%
M 159
 
1.6%
. 147
 
1.5%
e 138
 
1.4%
Other values (63) 2693
27.6%
None
ValueCountFrequency (%)
㈜ 11
91.7%
＆ 1
 
8.3%
CJK
ValueCountFrequency (%)
大 2
14.3%
靑 2
14.3%
成 2
14.3%
松 1
7.1%
雲 1
7.1%
信 1
7.1%
正 1
7.1%
鄭 1
7.1%
元 1
7.1%
趙 1
7.1%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

법인여부
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
개인
7190 
법인
2810 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 7190
71.9%
법인 2810
 
28.1%

Length

2024-05-18T10:26:49.012980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:26:49.311967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 7190
71.9%
법인 2810
 
28.1%

사업장 전화번호
Text

MISSING 

Distinct5913
Distinct (%)89.0%
Missing3358
Missing (%)33.6%
Memory size156.2 KiB
2024-05-18T10:26:49.786158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length40
Mean length10.611563
Min length1

Characters and Unicode

Total characters70482
Distinct characters33
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5314 ?
Unique (%)80.0%

Sample

1st row028128466
2nd row024007911
3rd row027825951
4th row0226471358
5th row025665015
ValueCountFrequency (%)
02 283
 
3.8%
59
 
0.8%
070 49
 
0.7%
1566 8
 
0.1%
1599 8
 
0.1%
010 8
 
0.1%
02-6433-5821 7
 
0.1%
1644 7
 
0.1%
1661-1973 6
 
0.1%
2212 6
 
0.1%
Other values (6245) 7063
94.1%
2024-05-18T10:26:50.860852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11388
16.2%
2 10247
14.5%
- 7132
10.1%
5 5854
8.3%
7 5569
7.9%
6 5205
7.4%
1 5123
7.3%
3 4934
7.0%
4 4904
7.0%
8 4784
6.8%
Other values (23) 5342
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62097
88.1%
Dash Punctuation 7132
 
10.1%
Space Separator 968
 
1.4%
Other Punctuation 143
 
0.2%
Close Punctuation 66
 
0.1%
Math Symbol 30
 
< 0.1%
Open Punctuation 21
 
< 0.1%
Other Letter 19
 
< 0.1%
Uppercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
록 3
15.8%
등 3
15.8%
미 3
15.8%
메 1
 
5.3%
타 1
 
5.3%
허 1
 
5.3%
브 1
 
5.3%
대 1
 
5.3%
부 1
 
5.3%
주 1
 
5.3%
Other values (3) 3
15.8%
Decimal Number
ValueCountFrequency (%)
0 11388
18.3%
2 10247
16.5%
5 5854
9.4%
7 5569
9.0%
6 5205
8.4%
1 5123
8.2%
3 4934
7.9%
4 4904
7.9%
8 4784
7.7%
9 4089
 
6.6%
Other Punctuation
ValueCountFrequency (%)
* 74
51.7%
/ 50
35.0%
. 19
 
13.3%
Uppercase Letter
ValueCountFrequency (%)
K 3
50.0%
T 3
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 7132
100.0%
Space Separator
ValueCountFrequency (%)
968
100.0%
Close Punctuation
ValueCountFrequency (%)
) 66
100.0%
Math Symbol
ValueCountFrequency (%)
~ 30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70457
> 99.9%
Hangul 19
 
< 0.1%
Latin 6
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11388
16.2%
2 10247
14.5%
- 7132
10.1%
5 5854
8.3%
7 5569
7.9%
6 5205
7.4%
1 5123
7.3%
3 4934
7.0%
4 4904
7.0%
8 4784
6.8%
Other values (8) 5317
7.5%
Hangul
ValueCountFrequency (%)
록 3
15.8%
등 3
15.8%
미 3
15.8%
메 1
 
5.3%
타 1
 
5.3%
허 1
 
5.3%
브 1
 
5.3%
대 1
 
5.3%
부 1
 
5.3%
주 1
 
5.3%
Other values (3) 3
15.8%
Latin
ValueCountFrequency (%)
K 3
50.0%
T 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70463
> 99.9%
Hangul 19
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11388
16.2%
2 10247
14.5%
- 7132
10.1%
5 5854
8.3%
7 5569
7.9%
6 5205
7.4%
1 5123
7.3%
3 4934
7.0%
4 4904
7.0%
8 4784
6.8%
Other values (10) 5323
7.6%
Hangul
ValueCountFrequency (%)
록 3
15.8%
등 3
15.8%
미 3
15.8%
메 1
 
5.3%
타 1
 
5.3%
허 1
 
5.3%
브 1
 
5.3%
대 1
 
5.3%
부 1
 
5.3%
주 1
 
5.3%
Other values (3) 3
15.8%

소재지
Text

MISSING 

Distinct8631
Distinct (%)89.1%
Missing312
Missing (%)3.1%
Memory size156.2 KiB
2024-05-18T10:26:51.580655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length49
Mean length31.412882
Min length15

Characters and Unicode

Total characters304328
Distinct characters622
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7865 ?
Unique (%)81.2%

Sample

1st row서울특별시 동작구 대방동 41번지 신한토탈아파트 202호
2nd row서울특별시 송파구 문정동 삼성레미안(A)120/1001
3rd row서울특별시 강남구 신사동 586번지 12호 삼원빌딩603호
4th row서울특별시 구로구 신도림동 643번지 102 신도림1차동아아파트-1401
5th row서울특별시 도봉구 창동 810 신창아파트 105-904
ValueCountFrequency (%)
서울특별시 9682
 
17.0%
강남구 1593
 
2.8%
서초구 978
 
1.7%
1호 766
 
1.3%
역삼동 690
 
1.2%
서초동 586
 
1.0%
송파구 577
 
1.0%
중구 515
 
0.9%
영등포구 464
 
0.8%
2호 464
 
0.8%
Other values (9363) 40669
71.4%
2024-05-18T10:26:52.732189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
67511
22.2%
1 13563
 
4.5%
서 12075
 
4.0%
동 11051
 
3.6%
구 10527
 
3.5%
시 9942
 
3.3%
울 9727
 
3.2%
별 9695
 
3.2%
특 9682
 
3.2%
2 8785
 
2.9%
Other values (612) 141770
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 166408
54.7%
Space Separator 67511
22.2%
Decimal Number 63270
 
20.8%
Dash Punctuation 5446
 
1.8%
Uppercase Letter 1168
 
0.4%
Other Punctuation 218
 
0.1%
Lowercase Letter 96
 
< 0.1%
Open Punctuation 94
 
< 0.1%
Close Punctuation 93
 
< 0.1%
Letter Number 17
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 12075
 
7.3%
동 11051
 
6.6%
구 10527
 
6.3%
시 9942
 
6.0%
울 9727
 
5.8%
별 9695
 
5.8%
특 9682
 
5.8%
호 8590
 
5.2%
지 8463
 
5.1%
번 7985
 
4.8%
Other values (540) 68671
41.3%
Uppercase Letter
ValueCountFrequency (%)
B 267
22.9%
A 214
18.3%
S 87
 
7.4%
D 77
 
6.6%
C 55
 
4.7%
T 53
 
4.5%
K 52
 
4.5%
I 44
 
3.8%
E 40
 
3.4%
L 37
 
3.2%
Other values (16) 242
20.7%
Lowercase Letter
ValueCountFrequency (%)
e 13
13.5%
i 11
11.5%
n 11
11.5%
t 7
 
7.3%
r 7
 
7.3%
c 6
 
6.2%
k 5
 
5.2%
s 5
 
5.2%
b 4
 
4.2%
l 4
 
4.2%
Other values (9) 23
24.0%
Decimal Number
ValueCountFrequency (%)
1 13563
21.4%
2 8785
13.9%
0 8032
12.7%
3 7028
11.1%
4 5757
9.1%
5 4856
 
7.7%
6 4578
 
7.2%
7 4029
 
6.4%
9 3328
 
5.3%
8 3314
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 89
40.8%
/ 79
36.2%
. 46
21.1%
@ 1
 
0.5%
# 1
 
0.5%
？ 1
 
0.5%
& 1
 
0.5%
Letter Number
ValueCountFrequency (%)
Ⅱ 10
58.8%
Ⅰ 5
29.4%
Ⅲ 2
 
11.8%
Open Punctuation
ValueCountFrequency (%)
( 93
98.9%
[ 1
 
1.1%
Close Punctuation
ValueCountFrequency (%)
) 92
98.9%
] 1
 
1.1%
Space Separator
ValueCountFrequency (%)
67511
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5446
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 166406
54.7%
Common 136639
44.9%
Latin 1281
 
0.4%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 12075
 
7.3%
동 11051
 
6.6%
구 10527
 
6.3%
시 9942
 
6.0%
울 9727
 
5.8%
별 9695
 
5.8%
특 9682
 
5.8%
호 8590
 
5.2%
지 8463
 
5.1%
번 7985
 
4.8%
Other values (538) 68669
41.3%
Latin
ValueCountFrequency (%)
B 267
20.8%
A 214
16.7%
S 87
 
6.8%
D 77
 
6.0%
C 55
 
4.3%
T 53
 
4.1%
K 52
 
4.1%
I 44
 
3.4%
E 40
 
3.1%
L 37
 
2.9%
Other values (38) 355
27.7%
Common
ValueCountFrequency (%)
67511
49.4%
1 13563
 
9.9%
2 8785
 
6.4%
0 8032
 
5.9%
3 7028
 
5.1%
4 5757
 
4.2%
- 5446
 
4.0%
5 4856
 
3.6%
6 4578
 
3.4%
7 4029
 
2.9%
Other values (14) 7054
 
5.2%
Han
ValueCountFrequency (%)
金 1
50.0%
塘 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 166406
54.7%
ASCII 137902
45.3%
Number Forms 17
 
< 0.1%
None 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
67511
49.0%
1 13563
 
9.8%
2 8785
 
6.4%
0 8032
 
5.8%
3 7028
 
5.1%
4 5757
 
4.2%
- 5446
 
3.9%
5 4856
 
3.5%
6 4578
 
3.3%
7 4029
 
2.9%
Other values (58) 8317
 
6.0%
Hangul
ValueCountFrequency (%)
서 12075
 
7.3%
동 11051
 
6.6%
구 10527
 
6.3%
시 9942
 
6.0%
울 9727
 
5.8%
별 9695
 
5.8%
특 9682
 
5.8%
호 8590
 
5.2%
지 8463
 
5.1%
번 7985
 
4.8%
Other values (538) 68669
41.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 10
58.8%
Ⅰ 5
29.4%
Ⅲ 2
 
11.8%
None
ValueCountFrequency (%)
？ 1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
金 1
100.0%
CJK
ValueCountFrequency (%)
塘 1
100.0%

소재지(도로명)
Text

MISSING 

Distinct4760
Distinct (%)90.9%
Missing4766
Missing (%)47.7%
Memory size156.2 KiB
2024-05-18T10:26:53.729626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length55
Mean length37.152274
Min length20

Characters and Unicode

Total characters194455
Distinct characters604
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4329 ?
Unique (%)82.7%

Sample

1st row서울특별시 중구 명동7길 21, 명동아르누보센텀 518호 (을지로2가)
2nd row서울특별시 강남구 논현로 507, 1312호 (역삼동,성지하이츠3차)
3rd row서울특별시 광진구 아차산로 416, 1층층 (자양동, 광진전화국)
4th row서울특별시 종로구 보문로3길 2, 305호 (숭인동, 중앙빌딩)
5th row서울특별시 용산구 한강대로 95, 408호 (한강로2가, 래미안용산 더 센트럴)
ValueCountFrequency (%)
서울특별시 5231
 
14.1%
강남구 939
 
2.5%
서초구 583
 
1.6%
2층 479
 
1.3%
역삼동 402
 
1.1%
3층 389
 
1.1%
서초동 373
 
1.0%
영등포구 319
 
0.9%
송파구 306
 
0.8%
4층 304
 
0.8%
Other values (6547) 27714
74.8%
2024-05-18T10:26:55.143380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31818
 
16.4%
1 7461
 
3.8%
, 7203
 
3.7%
서 6915
 
3.6%
동 6812
 
3.5%
로 5785
 
3.0%
구 5784
 
3.0%
시 5424
 
2.8%
2 5376
 
2.8%
울 5281
 
2.7%
Other values (594) 106596
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 108218
55.7%
Decimal Number 34654
 
17.8%
Space Separator 31818
 
16.4%
Other Punctuation 7213
 
3.7%
Open Punctuation 5273
 
2.7%
Close Punctuation 5273
 
2.7%
Dash Punctuation 1025
 
0.5%
Uppercase Letter 860
 
0.4%
Lowercase Letter 95
 
< 0.1%
Letter Number 18
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 6915
 
6.4%
동 6812
 
6.3%
로 5785
 
5.3%
구 5784
 
5.3%
시 5424
 
5.0%
울 5281
 
4.9%
별 5246
 
4.8%
특 5231
 
4.8%
호 4276
 
4.0%
길 2753
 
2.5%
Other values (524) 54711
50.6%
Uppercase Letter
ValueCountFrequency (%)
B 156
18.1%
A 123
14.3%
S 83
 
9.7%
C 55
 
6.4%
T 52
 
6.0%
E 45
 
5.2%
I 38
 
4.4%
K 37
 
4.3%
L 31
 
3.6%
G 30
 
3.5%
Other values (15) 210
24.4%
Lowercase Letter
ValueCountFrequency (%)
e 10
10.5%
n 10
10.5%
i 9
9.5%
c 9
9.5%
r 7
 
7.4%
b 7
 
7.4%
t 7
 
7.4%
o 6
 
6.3%
s 6
 
6.3%
w 5
 
5.3%
Other values (9) 19
20.0%
Decimal Number
ValueCountFrequency (%)
1 7461
21.5%
2 5376
15.5%
0 4482
12.9%
3 4196
12.1%
4 2893
 
8.3%
5 2686
 
7.8%
6 2248
 
6.5%
7 1960
 
5.7%
8 1771
 
5.1%
9 1581
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 7203
99.9%
. 6
 
0.1%
/ 1
 
< 0.1%
？ 1
 
< 0.1%
# 1
 
< 0.1%
& 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 9
50.0%
Ⅰ 6
33.3%
Ⅲ 3
 
16.7%
Open Punctuation
ValueCountFrequency (%)
( 5272
> 99.9%
[ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 5272
> 99.9%
] 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
31818
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1025
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 108216
55.7%
Common 85264
43.8%
Latin 973
 
0.5%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 6915
 
6.4%
동 6812
 
6.3%
로 5785
 
5.3%
구 5784
 
5.3%
시 5424
 
5.0%
울 5281
 
4.9%
별 5246
 
4.8%
특 5231
 
4.8%
호 4276
 
4.0%
길 2753
 
2.5%
Other values (522) 54709
50.6%
Latin
ValueCountFrequency (%)
B 156
16.0%
A 123
 
12.6%
S 83
 
8.5%
C 55
 
5.7%
T 52
 
5.3%
E 45
 
4.6%
I 38
 
3.9%
K 37
 
3.8%
L 31
 
3.2%
G 30
 
3.1%
Other values (37) 323
33.2%
Common
ValueCountFrequency (%)
31818
37.3%
1 7461
 
8.8%
, 7203
 
8.4%
2 5376
 
6.3%
( 5272
 
6.2%
) 5272
 
6.2%
0 4482
 
5.3%
3 4196
 
4.9%
4 2893
 
3.4%
5 2686
 
3.2%
Other values (13) 8605
 
10.1%
Han
ValueCountFrequency (%)
塘 1
50.0%
金 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 108216
55.7%
ASCII 86218
44.3%
Number Forms 18
 
< 0.1%
None 1
 
< 0.1%
CJK 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31818
36.9%
1 7461
 
8.7%
, 7203
 
8.4%
2 5376
 
6.2%
( 5272
 
6.1%
) 5272
 
6.1%
0 4482
 
5.2%
3 4196
 
4.9%
4 2893
 
3.4%
5 2686
 
3.1%
Other values (56) 9559
 
11.1%
Hangul
ValueCountFrequency (%)
서 6915
 
6.4%
동 6812
 
6.3%
로 5785
 
5.3%
구 5784
 
5.3%
시 5424
 
5.0%
울 5281
 
4.9%
별 5246
 
4.8%
특 5231
 
4.8%
호 4276
 
4.0%
길 2753
 
2.5%
Other values (522) 54709
50.6%
Number Forms
ValueCountFrequency (%)
Ⅱ 9
50.0%
Ⅰ 6
33.3%
Ⅲ 3
 
16.7%
None
ValueCountFrequency (%)
？ 1
100.0%
CJK
ValueCountFrequency (%)
塘 1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
金 1
100.0%

우편번호
Real number (ℝ)

MISSING 

Distinct1359
Distinct (%)31.1%
Missing5631
Missing (%)56.3%
Infinite0
Infinite (%)0.0%
Mean136557.78
Minimum3182
Maximum423060
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T10:26:55.913882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3182
5-th percentile110070
Q1132040
median136818
Q3143220
95-th percentile157031
Maximum423060
Range419878
Interquartile range (IQR)11180

Descriptive statistics

Standard deviation15729.29
Coefficient of variation (CV)0.11518414
Kurtosis54.22106
Mean136557.78
Median Absolute Deviation (MAD)5598
Skewness1.0849698
Sum5.9662096 × 108
Variance2.4741057 × 108
MonotonicityNot monotonic
2024-05-18T10:26:56.511610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
135080 157
 
1.6%
137070 149
 
1.5%
157010 66
 
0.7%
135010 61
 
0.6%
152050 56
 
0.6%
151015 51
 
0.5%
142070 46
 
0.5%
158070 42
 
0.4%
151050 40
 
0.4%
142100 38
 
0.4%
Other values (1349) 3663
36.6%
(Missing) 5631
56.3%
ValueCountFrequency (%)
3182 1
 
< 0.1%
4526 1
 
< 0.1%
4536 1
 
< 0.1%
4538 1
 
< 0.1%
4801 1
 
< 0.1%
5510 1
 
< 0.1%
7238 1
 
< 0.1%
7326 1
 
< 0.1%
100011 5
0.1%
100012 2
 
< 0.1%
ValueCountFrequency (%)
423060 1
 
< 0.1%
410380 1
 
< 0.1%
158877 1
 
< 0.1%
158864 2
 
< 0.1%
158863 1
 
< 0.1%
158860 8
0.1%
158859 4
< 0.1%
158858 1
 
< 0.1%
158857 1
 
< 0.1%
158846 1
 
< 0.1%

등록일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3564
Distinct (%)35.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20137071
Minimum20060308
Maximum20240516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T10:26:57.126651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060308
5-th percentile20070810
Q120091210
median20130409
Q320170805
95-th percentile20230206
Maximum20240516
Range180208
Interquartile range (IQR)79594.75

Descriptive statistics

Standard deviation48880.421
Coefficient of variation (CV)0.0024273848
Kurtosis-0.90745914
Mean20137071
Median Absolute Deviation (MAD)39678
Skewness0.44504362
Sum2.0137071 × 1011
Variance2.3892956 × 109
MonotonicityNot monotonic
2024-05-18T10:26:57.625589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20080814 26
 
0.3%
20081222 24
 
0.2%
20080731 24
 
0.2%
20080818 21
 
0.2%
20090611 20
 
0.2%
20160720 17
 
0.2%
20090213 14
 
0.1%
20110330 13
 
0.1%
20090507 13
 
0.1%
20090528 13
 
0.1%
Other values (3554) 9815
98.2%
ValueCountFrequency (%)
20060308 1
 
< 0.1%
20060310 1
 
< 0.1%
20060320 3
< 0.1%
20060321 1
 
< 0.1%
20060323 2
< 0.1%
20060324 3
< 0.1%
20060329 2
< 0.1%
20060331 1
 
< 0.1%
20060405 3
< 0.1%
20060407 2
< 0.1%
ValueCountFrequency (%)
20240516 1
 
< 0.1%
20240514 2
< 0.1%
20240510 1
 
< 0.1%
20240508 1
 
< 0.1%
20240507 2
< 0.1%
20240503 1
 
< 0.1%
20240502 3
< 0.1%
20240430 2
< 0.1%
20240425 3
< 0.1%
20240424 2
< 0.1%

유효기간만료일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3358
Distinct (%)42.1%
Missing2032
Missing (%)20.3%
Infinite0
Infinite (%)0.0%
Mean20181607
Minimum20090514
Maximum20270516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T10:26:58.265867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090514
5-th percentile20120325
Q120141108
median20180120
Q320220121
95-th percentile20260510
Maximum20270516
Range180002
Interquartile range (IQR)79013.25

Descriptive statistics

Standard deviation44422.125
Coefficient of variation (CV)0.0022011193
Kurtosis-0.97233176
Mean20181607
Median Absolute Deviation (MAD)39092
Skewness0.31540027
Sum1.6080704 × 1011
Variance1.9733252 × 109
MonotonicityNot monotonic
2024-05-18T10:26:58.811452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190720 17
 
0.2%
20110831 14
 
0.1%
20140330 13
 
0.1%
20141108 13
 
0.1%
20170701 13
 
0.1%
20140711 11
 
0.1%
20190216 11
 
0.1%
20150425 11
 
0.1%
20190722 10
 
0.1%
20190718 10
 
0.1%
Other values (3348) 7845
78.5%
(Missing) 2032
 
20.3%
ValueCountFrequency (%)
20090514 1
< 0.1%
20091116 1
< 0.1%
20091220 1
< 0.1%
20100112 1
< 0.1%
20100117 2
< 0.1%
20100321 1
< 0.1%
20100326 1
< 0.1%
20100411 1
< 0.1%
20100418 1
< 0.1%
20100419 1
< 0.1%
ValueCountFrequency (%)
20270516 1
 
< 0.1%
20270514 2
< 0.1%
20270509 1
 
< 0.1%
20270508 1
 
< 0.1%
20270507 2
< 0.1%
20270503 1
 
< 0.1%
20270502 2
< 0.1%
20270501 1
 
< 0.1%
20270430 2
< 0.1%
20270425 3
< 0.1%

폐쇄일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3134
Distinct (%)37.4%
Missing1623
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean20142121
Minimum20071115
Maximum20240516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T10:26:59.384876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20071115
5-th percentile20090908
Q120110404
median20130801
Q320170501
95-th percentile20220924
Maximum20240516
Range169401
Interquartile range (IQR)60097

Descriptive statistics

Standard deviation40771.303
Coefficient of variation (CV)0.0020241812
Kurtosis-0.5730983
Mean20142121
Median Absolute Deviation (MAD)29874
Skewness0.6725533
Sum1.6873055 × 1011
Variance1.6622991 × 109
MonotonicityNot monotonic
2024-05-18T10:26:59.843981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091116 218
 
2.2%
20100927 81
 
0.8%
20170124 23
 
0.2%
20160725 22
 
0.2%
20110823 21
 
0.2%
20101213 20
 
0.2%
20110420 19
 
0.2%
20110425 19
 
0.2%
20111108 18
 
0.2%
20170125 16
 
0.2%
Other values (3124) 7920
79.2%
(Missing) 1623
 
16.2%
ValueCountFrequency (%)
20071115 1
 
< 0.1%
20090211 1
 
< 0.1%
20090305 1
 
< 0.1%
20090306 1
 
< 0.1%
20090309 2
< 0.1%
20090311 4
< 0.1%
20090312 4
< 0.1%
20090313 1
 
< 0.1%
20090316 2
< 0.1%
20090317 1
 
< 0.1%
ValueCountFrequency (%)
20240516 1
 
< 0.1%
20240513 3
< 0.1%
20240509 2
< 0.1%
20240507 1
 
< 0.1%
20240503 4
< 0.1%
20240501 2
< 0.1%
20240430 1
 
< 0.1%
20240429 1
 
< 0.1%
20240424 1
 
< 0.1%
20240423 1
 
< 0.1%

지점설립일자
Text

MISSING 

Distinct3595
Distinct (%)40.9%
Missing1218
Missing (%)12.2%
Memory size156.2 KiB
2024-05-18T10:27:00.833844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters70256
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

Unique1375 ?
Unique (%)15.7%

Sample

1st row20091128
2nd row20061130
3rd row20100825
4th row20090514
5th row20120424
ValueCountFrequency (%)
20090820 25
 
0.3%
20090611 23
 
0.3%
20160720 22
 
0.3%
20090512 18
 
0.2%
20090528 18
 
0.2%
20090511 16
 
0.2%
20090604 15
 
0.2%
20090514 15
 
0.2%
20090507 15
 
0.2%
20090722 14
 
0.2%
Other values (3585) 8601
97.9%
2024-05-18T10:27:02.104219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22777
32.4%
2 15939
22.7%
1 14157
20.2%
3 2878
 
4.1%
7 2653
 
3.8%
9 2639
 
3.8%
6 2506
 
3.6%
4 2287
 
3.3%
5 2271
 
3.2%
8 2143
 
3.1%
Other values (4) 6
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70250
> 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 22777
32.4%
2 15939
22.7%
1 14157
20.2%
3 2878
 
4.1%
7 2653
 
3.8%
9 2639
 
3.8%
6 2506
 
3.6%
4 2287
 
3.3%
5 2271
 
3.2%
8 2143
 
3.1%
Lowercase Letter
ValueCountFrequency (%)
p 1
50.0%
r 1
50.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70253
> 99.9%
Latin 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 22777
32.4%
2 15939
22.7%
1 14157
20.2%
3 2878
 
4.1%
7 2653
 
3.8%
9 2639
 
3.8%
6 2506
 
3.6%
4 2287
 
3.3%
5 2271
 
3.2%
8 2143
 
3.1%
Latin
ValueCountFrequency (%)
A 1
33.3%
p 1
33.3%
r 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70256
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 22777
32.4%
2 15939
22.7%
1 14157
20.2%
3 2878
 
4.1%
7 2653
 
3.8%
9 2639
 
3.8%
6 2506
 
3.6%
4 2287
 
3.3%
5 2271
 
3.2%
8 2143
 
3.1%
Other values (4) 6
 
< 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

2024-05-18T10:27:02.695859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:27:03.135391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
본점 9930
99.3%
지점 70
 
0.7%

최근수정일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3193
Distinct (%)31.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20153268
Minimum20090518
Maximum20240517
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T10:27:03.556964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090518
5-th percentile20091117
Q120111012
median20141008
Q320190515
95-th percentile20231017
Maximum20240517
Range149999
Interquartile range (IQR)79503

Descriptive statistics

Standard deviation45983.759
Coefficient of variation (CV)0.0022817024
Kurtosis-1.0774186
Mean20153268
Median Absolute Deviation (MAD)30697.5
Skewness0.42939727
Sum2.0153268 × 1011
Variance2.1145061 × 109
MonotonicityNot monotonic
2024-05-18T10:27:04.151486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091117 91
 
0.9%
20090609 64
 
0.6%
20100927 54
 
0.5%
20091118 50
 
0.5%
20100330 44
 
0.4%
20090622 42
 
0.4%
20110425 39
 
0.4%
20091116 37
 
0.4%
20160812 30
 
0.3%
20091119 30
 
0.3%
Other values (3183) 9519
95.2%
ValueCountFrequency (%)
20090518 1
 
< 0.1%
20090519 2
 
< 0.1%
20090521 3
 
< 0.1%
20090601 5
 
0.1%
20090602 1
 
< 0.1%
20090603 11
 
0.1%
20090604 15
 
0.1%
20090605 2
 
< 0.1%
20090608 3
 
< 0.1%
20090609 64
0.6%
ValueCountFrequency (%)
20240517 1
 
< 0.1%
20240516 7
0.1%
20240514 3
 
< 0.1%
20240513 6
0.1%
20240510 2
 
< 0.1%
20240509 4
 
< 0.1%
20240508 4
 
< 0.1%
20240507 4
 
< 0.1%
20240503 12
0.1%
20240502 3
 
< 0.1%

Interactions

2024-05-18T10:26:39.550514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:26:31.856153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:26:33.585662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:26:35.439818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:26:37.637555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:26:39.836811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:26:32.109258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:26:33.954434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:26:35.807716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:26:38.043957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:26:40.134746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:26:32.461378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:26:34.318733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:26:36.229081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:26:38.474456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:26:40.473602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:26:32.960913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:26:34.636122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:26:36.663034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:26:38.824144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:26:40.791822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:26:33.273933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:26:35.010308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:26:37.120623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T10:26:39.184243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T10:27:04.514619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록신청사업영업구분법인여부우편번호등록일자유효기간만료일자폐쇄일자본점여부최근수정일자
등록신청사업1.0000.0840.0110.0000.2300.1490.1680.0000.187
영업구분0.0841.0000.2770.1180.6180.6280.1950.0620.543
법인여부0.0110.2771.0000.0690.3560.2890.2110.1900.352
우편번호0.0000.1180.0691.0000.2280.2170.1710.0000.241
등록일자0.2300.6180.3560.2281.0001.0000.8580.1010.939
유효기간만료일자0.1490.6280.2890.2171.0001.0000.8580.0920.839
폐쇄일자0.1680.1950.2110.1710.8580.8581.0000.0650.953
본점여부0.0000.0620.1900.0000.1010.0920.0651.0000.097
최근수정일자0.1870.5430.3520.2410.9390.8390.9530.0971.000
2024-05-18T10:27:04.936999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록신청사업본점여부영업구분법인여부
등록신청사업1.0000.0000.0610.007
본점여부0.0001.0000.0450.122
영업구분0.0610.0451.0000.199
법인여부0.0070.1220.1991.000
2024-05-18T10:27:05.580500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호등록일자유효기간만료일자폐쇄일자최근수정일자등록신청사업영업구분법인여부본점여부
우편번호1.0000.0330.0290.0540.0370.0000.0960.0530.000
등록일자0.0331.0000.9950.9620.9650.1760.3850.2730.078
유효기간만료일자0.0290.9951.0000.9640.9650.1140.3940.2220.070
폐쇄일자0.0540.9620.9641.0000.9920.1680.1140.2100.064
최근수정일자0.0370.9650.9650.9921.0000.1430.3050.2700.074
등록신청사업0.0000.1760.1140.1680.1431.0000.0610.0070.000
영업구분0.0960.3850.3940.1140.3050.0611.0000.1990.045
법인여부0.0530.2730.2220.2100.2700.0070.1991.0000.122
본점여부0.0000.0780.0700.0640.0740.0000.0450.1221.000

Missing values

2024-05-18T10:26:41.249668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T10:26:41.891076image/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.
2024-05-18T10:26:42.386976image/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
21038대부업폐업2009-서울특별시-02731(대부업)수성대부금융개인028128466서울특별시 동작구 대방동 41번지 신한토탈아파트 202호<NA>15680720091128<NA>2012072620091128본점20120726
20659대부업유효기간만료2006-서울특별시-00612(대부업)석봉미래산업대부개인024007911서울특별시 송파구 문정동 삼성레미안(A)120/1001<NA><NA>20091006201210062012100820061130본점20121008
21714대부업폐업2010-서울강남-0295(주)나우에셋링크대부법인027825951서울특별시 강남구 신사동 586번지 12호 삼원빌딩603호<NA>13589220100825201308252012051020100825본점20120510
26606대부중개업<NA>2008-서울특별시-03408(대부중개업)(주)캐쉬팡팡법인0226471358서울특별시 구로구 신도림동 643번지 102 신도림1차동아아파트-1401<NA>15207020080723<NA>2010102020090514본점20101020
31209<NA><NA>2007-서울특별시-01538이지연개인<NA>서울특별시 도봉구 창동 810 신창아파트 105-904<NA>13204020070309<NA>20090420<NA>본점20090609
21018대부업폐업2012-서울중랑-0030(대부업)두리cash대부개인<NA>서울특별시 중랑구 상봉동 105번지 34호<NA>13122220120424201504242012073020120424본점20120730
3673대부업영업중2022-서울중구-0028(대부업)부연종합투자대부개인<NA>서울특별시 중구 을지로2가 199번지 40호 명동아르누보센텀-518서울특별시 중구 명동7길 21, 명동아르누보센텀 518호 (을지로2가)<NA>2022082220250822<NA>20220822본점20221108
14331대부업폐업2011-서울강남-0348(대부업)(주)새한캐피탈대부법인025665015서울특별시 강남구 역삼동 642번지 6호 성지하이츠3차-1312서울특별시 강남구 논현로 507, 1312호 (역삼동,성지하이츠3차)13508020140721201707212015062620110923본점20150626
15214대부업타시군구이관2012-서울광진-0031(대부업)엠플러스대부(유)법인447-6311서울특별시 광진구 자양동 680번지 63호 광진전화국 1층서울특별시 광진구 아차산로 416, 1층층 (자양동, 광진전화국)14319020120727201507272014121520120727본점20141215
25139대부업<NA>2010-서울강남-0380국민투자대부개인025661515서울특별시 강남구 역삼동 702번지 24호 -302<NA>13508020101122201311222011041120101122본점20110411
등록신청사업영업구분등록증번호상호법인여부사업장 전화번호소재지소재지(도로명)우편번호등록일자유효기간만료일자폐쇄일자지점설립일자본점여부최근수정일자
9187대부중개업폐업2018-서울송파-0022(대부중개업)엔케이대부개인*****서울특별시 송파구 잠실동 339번지 2호 삼우빌딩-13서울특별시 송파구 백제고분로20길 13-8, 삼우빌딩 5층 13호 (잠실동)<NA>20180202202102022018032620180201본점20180327
18698대부업폐업2013-서울강남-0066(대부업)리딩론대부개인<NA>서울특별시 강남구 청담동 5번지 경원하이츠텔 509호<NA>13594820130307201603082013053120130307본점20130531
22111대부업폐업2009-서울특별시-01629(대부업)(주)글로벌대부금융법인024146677서울특별시 송파구 방이동 44번지 3호 현대토픽스 504호<NA><NA>20090717<NA>2012032320090717본점20120323
17564대부중개업직권취소2011-서울광진-0035(대부중개업)SM어드바이스대부중개(대부중개업)개인02 2233 0066서울특별시 광진구 구의동 201번지 19호 -203<NA>14320020110706201407062013100720110706본점20131007
3198대부업타시군구이관2015-서울강북-0033(대부업)한그루캐피탈대부개인02-955-3773서울특별시 강북구 수유동 2번지 2호 -205서울특별시 강북구 노해로 21, 203호 (수유동)<NA>20210210202402102023021520150609본점20230215
11339대부업폐업2016-서울강북-0011(대부업)주식회사 산타클로스대부법인1644-6519서울특별시 강북구 번동 446번지 37호서울특별시 강북구 오패산로77길 18, 5층 502호 (번동, 동아빌딩)<NA>20160215201902152017012020160215본점20170120
30528<NA><NA>2008-서울특별시-02030세계금융개인029451717서울특별시 도봉구 쌍문동 158 한양7차상가 106호<NA>13203020080724<NA>20090728<NA>본점20090728
29615대부업<NA>2008-서울특별시-01616(대부업)이복숙개인027414543서울특별시 종로구 숭인동 201-28 3층 210호<NA><NA>20080501<NA>20091116<NA>본점20091119
5114대부업유효기간만료2020-서울중구-0006(대부업)(주)다옴펀딩대부법인02-6101-9872서울특별시 중구 서소문동 49번지 2호서울특별시 중구 서소문로 111, 삼영빌딩 1103호 (서소문동)<NA>20181029202110292021110220181029본점20211102
23593대부중개업<NA>2008-서울특별시-02833(대부중개업)샵캐피탈개인029419698서울특별시 성북구 동선동4가 303-5호<NA><NA>20081030<NA>20110930<NA>본점20110930

Duplicate rows

Most frequently occurring

등록신청사업영업구분등록증번호상호법인여부사업장 전화번호소재지소재지(도로명)우편번호등록일자유효기간만료일자폐쇄일자지점설립일자본점여부최근수정일자# duplicates
0대부업타시군구이관2014-서울동작-00014(대부업)캐시오토론대부개인<NA>서울특별시 동작구 흑석동 336번지 105 흑석한강푸르지오-803서울특별시 동작구 흑석한강로 27, 105동 803호 (흑석동, 흑석한강푸르지오)15678420141209201712092016072620120109본점201607262
1대부업<NA>2009-서울특별시-02231(대부업)한빛투자금융대부개인025638488서울특별시 은평구 구산동 177번지 2호 명성골든빌 A-502호<NA><NA>20090918<NA>2010021120090918본점201006042