Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells19223
Missing cells (%)12.8%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory1.3 MiB
Average record size in memory133.0 B

Variable types

Categorical4
Text6
Numeric5

Dataset

Description등록신청사업,영업구분,등록증번호,상호,법인여부,사업장 전화번호,소재지,소재지(도로명),우편번호,등록일자,유효기간만료일자,폐쇄일자,지점설립일자,본점여부,최근수정일자
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-10866/S/1/datasetView.do

Alerts

Dataset has 1 (< 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 (94.9%)Imbalance
등록증번호 has 181 (1.8%) missing valuesMissing
사업장 전화번호 has 3425 (34.2%) missing valuesMissing
소재지 has 308 (3.1%) missing valuesMissing
소재지(도로명) has 4842 (48.4%) missing valuesMissing
우편번호 has 5590 (55.9%) missing valuesMissing
유효기간만료일자 has 2099 (21.0%) missing valuesMissing
폐쇄일자 has 1543 (15.4%) missing valuesMissing
지점설립일자 has 1235 (12.3%) missing valuesMissing

Reproduction

Analysis started2024-05-17 23:07:59.580030
Analysis finished2024-05-17 23:08:19.239705
Duration19.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
대부업
6113 
대부중개업
3438 
<NA>
 
449

Length

Max length5
Median length3
Mean length3.7325
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대부업 6113
61.1%
대부중개업 3438
34.4%
<NA> 449
 
4.5%

Length

2024-05-18T08:08:19.587294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:08:20.043196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대부업 6113
61.1%
대부중개업 3438
34.4%
na 449
 
4.5%

영업구분
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
3758 
<NA>
2896 
타시군구이관
1206 
영업중
805 
유효기간만료
774 
Other values (3)
561 

Length

Max length6
Median length4
Mean length3.5643
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3758
37.6%
<NA> 2896
29.0%
타시군구이관 1206
 
12.1%
영업중 805
 
8.1%
유효기간만료 774
 
7.7%
직권취소 557
 
5.6%
갱신등록불가 3
 
< 0.1%
휴업 1
 
< 0.1%

Length

2024-05-18T08:08:20.618455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:08:21.138286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3758
37.6%
na 2896
29.0%
타시군구이관 1206
 
12.1%
영업중 805
 
8.1%
유효기간만료 774
 
7.7%
직권취소 557
 
5.6%
갱신등록불가 3
 
< 0.1%
휴업 1
 
< 0.1%

등록증번호
Text

MISSING 

Distinct9763
Distinct (%)99.4%
Missing181
Missing (%)1.8%
Memory size156.2 KiB
2024-05-18T08:08:22.014627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length27
Mean length19.526123
Min length1

Characters and Unicode

Total characters191727
Distinct characters81
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

Unique9710 ?
Unique (%)98.9%

Sample

1st row2016-서울구로-034(대부업)
2nd row2008-서울관악-00032(대부업)
3rd row2008-서울특별시-02739(대부업)
4th row2019-서울성동-00014(대부업)
5th row2009-서울특별시-00124(대부업)
ValueCountFrequency (%)
2011-서울특별시 18
 
0.2%
2012-서울특별시 17
 
0.2%
2010-서울 17
 
0.2%
2013-서울특별시 16
 
0.2%
2014-서울특별시 16
 
0.2%
2015-서울특별시 13
 
0.1%
대부업 8
 
0.1%
2016-서울특별시 7
 
0.1%
대부중개업 7
 
0.1%
2017-서울특별시 7
 
0.1%
Other values (9716) 9860
98.7%
2024-05-18T08:08:23.467988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 33795
17.6%
- 19627
 
10.2%
2 15782
 
8.2%
1 11815
 
6.2%
10916
 
5.7%
9782
 
5.1%
8450
 
4.4%
( 8190
 
4.3%
8157
 
4.3%
) 8132
 
4.2%
Other values (71) 57081
29.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82560
43.1%
Other Letter 73051
38.1%
Dash Punctuation 19627
 
10.2%
Open Punctuation 8190
 
4.3%
Close Punctuation 8132
 
4.2%
Space Separator 167
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10916
14.9%
9782
13.4%
8450
11.6%
8157
11.2%
7919
10.8%
3549
 
4.9%
2935
 
4.0%
2541
 
3.5%
2531
 
3.5%
2530
 
3.5%
Other values (57) 13741
18.8%
Decimal Number
ValueCountFrequency (%)
0 33795
40.9%
2 15782
19.1%
1 11815
 
14.3%
3 3747
 
4.5%
8 3108
 
3.8%
4 2983
 
3.6%
9 2873
 
3.5%
6 2850
 
3.5%
7 2850
 
3.5%
5 2757
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 19627
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8190
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8132
100.0%
Space Separator
ValueCountFrequency (%)
167
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 118676
61.9%
Hangul 73051
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10916
14.9%
9782
13.4%
8450
11.6%
8157
11.2%
7919
10.8%
3549
 
4.9%
2935
 
4.0%
2541
 
3.5%
2531
 
3.5%
2530
 
3.5%
Other values (57) 13741
18.8%
Common
ValueCountFrequency (%)
0 33795
28.5%
- 19627
16.5%
2 15782
13.3%
1 11815
 
10.0%
( 8190
 
6.9%
) 8132
 
6.9%
3 3747
 
3.2%
8 3108
 
2.6%
4 2983
 
2.5%
9 2873
 
2.4%
Other values (4) 8624
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 118676
61.9%
Hangul 73051
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 33795
28.5%
- 19627
16.5%
2 15782
13.3%
1 11815
 
10.0%
( 8190
 
6.9%
) 8132
 
6.9%
3 3747
 
3.2%
8 3108
 
2.6%
4 2983
 
2.5%
9 2873
 
2.4%
Other values (4) 8624
 
7.3%
Hangul
ValueCountFrequency (%)
10916
14.9%
9782
13.4%
8450
11.6%
8157
11.2%
7919
10.8%
3549
 
4.9%
2935
 
4.0%
2541
 
3.5%
2531
 
3.5%
2530
 
3.5%
Other values (57) 13741
18.8%

상호
Text

Distinct8702
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T08:08:24.349618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length32
Mean length7.714
Min length1

Characters and Unicode

Total characters77140
Distinct characters794
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7646 ?
Unique (%)76.5%

Sample

1st row언제나대부
2nd row썬기획대부
3rd rowHybrid Money
4th rowABC론대부
5th row우선
ValueCountFrequency (%)
주식회사 793
 
6.7%
대부중개 327
 
2.7%
대부 283
 
2.4%
유한회사 59
 
0.5%
대부업 22
 
0.2%
캐피탈 16
 
0.1%
미래 15
 
0.1%
13
 
0.1%
대부중개업 12
 
0.1%
the 10
 
0.1%
Other values (8739) 10365
87.0%
2024-05-18T08:08:25.752939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8482
 
11.0%
8112
 
10.5%
2672
 
3.5%
2252
 
2.9%
2153
 
2.8%
2144
 
2.8%
1927
 
2.5%
1916
 
2.5%
) 1872
 
2.4%
( 1867
 
2.4%
Other values (784) 43743
56.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67576
87.6%
Uppercase Letter 2253
 
2.9%
Space Separator 1916
 
2.5%
Close Punctuation 1872
 
2.4%
Open Punctuation 1867
 
2.4%
Lowercase Letter 1125
 
1.5%
Decimal Number 262
 
0.3%
Other Punctuation 233
 
0.3%
Dash Punctuation 22
 
< 0.1%
Other Symbol 12
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8482
 
12.6%
8112
 
12.0%
2672
 
4.0%
2252
 
3.3%
2153
 
3.2%
2144
 
3.2%
1927
 
2.9%
1304
 
1.9%
1119
 
1.7%
1011
 
1.5%
Other values (708) 36400
53.9%
Uppercase Letter
ValueCountFrequency (%)
S 282
 
12.5%
K 211
 
9.4%
J 197
 
8.7%
C 177
 
7.9%
M 164
 
7.3%
H 138
 
6.1%
L 102
 
4.5%
B 95
 
4.2%
G 86
 
3.8%
N 86
 
3.8%
Other values (16) 715
31.7%
Lowercase Letter
ValueCountFrequency (%)
e 134
11.9%
o 128
11.4%
n 123
10.9%
a 112
10.0%
i 74
 
6.6%
s 69
 
6.1%
t 62
 
5.5%
l 57
 
5.1%
c 52
 
4.6%
m 44
 
3.9%
Other values (15) 270
24.0%
Decimal Number
ValueCountFrequency (%)
1 86
32.8%
2 37
14.1%
4 35
13.4%
9 23
 
8.8%
3 22
 
8.4%
5 21
 
8.0%
6 13
 
5.0%
0 12
 
4.6%
7 10
 
3.8%
8 3
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 126
54.1%
& 89
38.2%
, 7
 
3.0%
? 6
 
2.6%
* 2
 
0.9%
@ 1
 
0.4%
1
 
0.4%
/ 1
 
0.4%
Space Separator
ValueCountFrequency (%)
1916
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1872
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1867
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Other Symbol
ValueCountFrequency (%)
12
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67571
87.6%
Common 6173
 
8.0%
Latin 3379
 
4.4%
Han 17
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8482
 
12.6%
8112
 
12.0%
2672
 
4.0%
2252
 
3.3%
2153
 
3.2%
2144
 
3.2%
1927
 
2.9%
1304
 
1.9%
1119
 
1.7%
1011
 
1.5%
Other values (692) 36395
53.9%
Latin
ValueCountFrequency (%)
S 282
 
8.3%
K 211
 
6.2%
J 197
 
5.8%
C 177
 
5.2%
M 164
 
4.9%
H 138
 
4.1%
e 134
 
4.0%
o 128
 
3.8%
n 123
 
3.6%
a 112
 
3.3%
Other values (42) 1713
50.7%
Common
ValueCountFrequency (%)
1916
31.0%
) 1872
30.3%
( 1867
30.2%
. 126
 
2.0%
& 89
 
1.4%
1 86
 
1.4%
2 37
 
0.6%
4 35
 
0.6%
9 23
 
0.4%
- 22
 
0.4%
Other values (13) 100
 
1.6%
Han
ValueCountFrequency (%)
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Other values (7) 7
41.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67558
87.6%
ASCII 9550
 
12.4%
CJK 17
 
< 0.1%
None 13
 
< 0.1%
Compat Jamo 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
8482
 
12.6%
8112
 
12.0%
2672
 
4.0%
2252
 
3.3%
2153
 
3.2%
2144
 
3.2%
1927
 
2.9%
1304
 
1.9%
1119
 
1.7%
1011
 
1.5%
Other values (690) 36382
53.9%
ASCII
ValueCountFrequency (%)
1916
20.1%
) 1872
19.6%
( 1867
19.5%
S 282
 
3.0%
K 211
 
2.2%
J 197
 
2.1%
C 177
 
1.9%
M 164
 
1.7%
H 138
 
1.4%
e 134
 
1.4%
Other values (63) 2592
27.1%
None
ValueCountFrequency (%)
12
92.3%
1
 
7.7%
CJK
ValueCountFrequency (%)
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Other values (7) 7
41.2%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

법인여부
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
개인
7229 
법인
2771 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 7229
72.3%
법인 2771
 
27.7%

Length

2024-05-18T08:08:26.155022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:08:26.457298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 7229
72.3%
법인 2771
 
27.7%
Distinct5867
Distinct (%)89.2%
Missing3425
Missing (%)34.2%
Memory size156.2 KiB
2024-05-18T08:08:26.891920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length41
Mean length10.642129
Min length1

Characters and Unicode

Total characters69972
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

Unique5285 ?
Unique (%)80.4%

Sample

1st row0260121239
2nd row024615340
3rd row02-922-0309
4th row023333983
5th row02-6974-0049
ValueCountFrequency (%)
02 295
 
4.0%
64
 
0.9%
070 35
 
0.5%
010 10
 
0.1%
2209 7
 
0.1%
1566 6
 
0.1%
2244 5
 
0.1%
02-558-7117 5
 
0.1%
1599 5
 
0.1%
703 5
 
0.1%
Other values (6193) 6964
94.1%
2024-05-18T08:08:27.681352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11319
16.2%
2 10250
14.6%
- 7043
10.1%
5 5907
8.4%
7 5511
7.9%
1 5147
7.4%
6 5117
7.3%
3 4821
6.9%
8 4795
6.9%
4 4765
6.8%
Other values (16) 5297
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61700
88.2%
Dash Punctuation 7043
 
10.1%
Space Separator 936
 
1.3%
Other Punctuation 165
 
0.2%
Close Punctuation 65
 
0.1%
Math Symbol 32
 
< 0.1%
Open Punctuation 22
 
< 0.1%
Other Letter 7
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11319
18.3%
2 10250
16.6%
5 5907
9.6%
7 5511
8.9%
1 5147
8.3%
6 5117
8.3%
3 4821
7.8%
8 4795
7.8%
4 4765
7.7%
9 4068
 
6.6%
Other Letter
ValueCountFrequency (%)
2
28.6%
2
28.6%
1
14.3%
1
14.3%
1
14.3%
Other Punctuation
ValueCountFrequency (%)
* 92
55.8%
/ 43
26.1%
. 30
 
18.2%
Math Symbol
ValueCountFrequency (%)
~ 31
96.9%
× 1
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 7043
100.0%
Space Separator
ValueCountFrequency (%)
936
100.0%
Close Punctuation
ValueCountFrequency (%)
) 65
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69963
> 99.9%
Hangul 7
 
< 0.1%
Latin 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11319
16.2%
2 10250
14.7%
- 7043
10.1%
5 5907
8.4%
7 5511
7.9%
1 5147
7.4%
6 5117
7.3%
3 4821
6.9%
8 4795
6.9%
4 4765
6.8%
Other values (9) 5288
7.6%
Hangul
ValueCountFrequency (%)
2
28.6%
2
28.6%
1
14.3%
1
14.3%
1
14.3%
Latin
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69964
> 99.9%
Hangul 7
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11319
16.2%
2 10250
14.7%
- 7043
10.1%
5 5907
8.4%
7 5511
7.9%
1 5147
7.4%
6 5117
7.3%
3 4821
6.9%
8 4795
6.9%
4 4765
6.8%
Other values (10) 5289
7.6%
Hangul
ValueCountFrequency (%)
2
28.6%
2
28.6%
1
14.3%
1
14.3%
1
14.3%
None
ValueCountFrequency (%)
× 1
100.0%

소재지
Text

MISSING 

Distinct8671
Distinct (%)89.5%
Missing308
Missing (%)3.1%
Memory size156.2 KiB
2024-05-18T08:08:28.386924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length51
Mean length31.5
Min length15

Characters and Unicode

Total characters305298
Distinct characters618
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7959 ?
Unique (%)82.1%

Sample

1st row서울특별시 구로구 구로동 1266번지
2nd row서울특별시 관악구 봉천동 910번지 13호 -202
3rd row서울특별시 동대문구 장안4동 291-5 정풍연립 다동 103호
4th row서울특별시 성동구 성수동2가 314번지 5호 광명타워
5th row서울특별시 광진구 중곡동 255-17
ValueCountFrequency (%)
서울특별시 9686
 
16.9%
강남구 1618
 
2.8%
서초구 1003
 
1.8%
1호 714
 
1.2%
역삼동 689
 
1.2%
송파구 597
 
1.0%
서초동 585
 
1.0%
중구 546
 
1.0%
영등포구 492
 
0.9%
2호 436
 
0.8%
Other values (9534) 40798
71.4%
2024-05-18T08:08:29.555467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
67637
22.2%
1 13640
 
4.5%
12119
 
4.0%
11091
 
3.6%
10507
 
3.4%
9942
 
3.3%
9746
 
3.2%
9694
 
3.2%
9689
 
3.2%
2 8912
 
2.9%
Other values (608) 142321
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 166920
54.7%
Space Separator 67637
22.2%
Decimal Number 63460
 
20.8%
Dash Punctuation 5438
 
1.8%
Uppercase Letter 1192
 
0.4%
Other Punctuation 248
 
0.1%
Lowercase Letter 135
 
< 0.1%
Close Punctuation 115
 
< 0.1%
Open Punctuation 112
 
< 0.1%
Letter Number 28
 
< 0.1%
Other values (2) 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12119
 
7.3%
11091
 
6.6%
10507
 
6.3%
9942
 
6.0%
9746
 
5.8%
9694
 
5.8%
9689
 
5.8%
8639
 
5.2%
8384
 
5.0%
7888
 
4.7%
Other values (533) 69221
41.5%
Uppercase Letter
ValueCountFrequency (%)
B 284
23.8%
A 229
19.2%
S 83
 
7.0%
D 77
 
6.5%
T 56
 
4.7%
K 51
 
4.3%
I 45
 
3.8%
L 40
 
3.4%
E 37
 
3.1%
G 36
 
3.0%
Other values (16) 254
21.3%
Lowercase Letter
ValueCountFrequency (%)
e 28
20.7%
r 13
9.6%
i 11
 
8.1%
n 11
 
8.1%
o 10
 
7.4%
w 10
 
7.4%
l 8
 
5.9%
t 7
 
5.2%
c 6
 
4.4%
a 6
 
4.4%
Other values (12) 25
18.5%
Decimal Number
ValueCountFrequency (%)
1 13640
21.5%
2 8912
14.0%
0 7955
12.5%
3 6960
11.0%
4 5696
9.0%
5 4954
 
7.8%
6 4481
 
7.1%
7 4085
 
6.4%
9 3397
 
5.4%
8 3380
 
5.3%
Other Punctuation
ValueCountFrequency (%)
. 88
35.5%
/ 84
33.9%
, 71
28.6%
3
 
1.2%
@ 1
 
0.4%
# 1
 
0.4%
Letter Number
ValueCountFrequency (%)
15
53.6%
7
25.0%
6
 
21.4%
Math Symbol
ValueCountFrequency (%)
~ 8
66.7%
< 2
 
16.7%
> 2
 
16.7%
Space Separator
ValueCountFrequency (%)
67637
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5438
100.0%
Close Punctuation
ValueCountFrequency (%)
) 115
100.0%
Open Punctuation
ValueCountFrequency (%)
( 112
100.0%
Other Number
ValueCountFrequency (%)
½ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 166918
54.7%
Common 137023
44.9%
Latin 1355
 
0.4%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12119
 
7.3%
11091
 
6.6%
10507
 
6.3%
9942
 
6.0%
9746
 
5.8%
9694
 
5.8%
9689
 
5.8%
8639
 
5.2%
8384
 
5.0%
7888
 
4.7%
Other values (531) 69219
41.5%
Latin
ValueCountFrequency (%)
B 284
21.0%
A 229
16.9%
S 83
 
6.1%
D 77
 
5.7%
T 56
 
4.1%
K 51
 
3.8%
I 45
 
3.3%
L 40
 
3.0%
E 37
 
2.7%
G 36
 
2.7%
Other values (41) 417
30.8%
Common
ValueCountFrequency (%)
67637
49.4%
1 13640
 
10.0%
2 8912
 
6.5%
0 7955
 
5.8%
3 6960
 
5.1%
4 5696
 
4.2%
- 5438
 
4.0%
5 4954
 
3.6%
6 4481
 
3.3%
7 4085
 
3.0%
Other values (14) 7265
 
5.3%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 166918
54.7%
ASCII 138346
45.3%
Number Forms 28
 
< 0.1%
None 4
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
67637
48.9%
1 13640
 
9.9%
2 8912
 
6.4%
0 7955
 
5.8%
3 6960
 
5.0%
4 5696
 
4.1%
- 5438
 
3.9%
5 4954
 
3.6%
6 4481
 
3.2%
7 4085
 
3.0%
Other values (60) 8588
 
6.2%
Hangul
ValueCountFrequency (%)
12119
 
7.3%
11091
 
6.6%
10507
 
6.3%
9942
 
6.0%
9746
 
5.8%
9694
 
5.8%
9689
 
5.8%
8639
 
5.2%
8384
 
5.0%
7888
 
4.7%
Other values (531) 69219
41.5%
Number Forms
ValueCountFrequency (%)
15
53.6%
7
25.0%
6
 
21.4%
None
ValueCountFrequency (%)
3
75.0%
½ 1
 
25.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
100.0%

소재지(도로명)
Text

MISSING 

Distinct4743
Distinct (%)92.0%
Missing4842
Missing (%)48.4%
Memory size156.2 KiB
2024-05-18T08:08:30.484385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length56
Mean length37.342381
Min length21

Characters and Unicode

Total characters192612
Distinct characters604
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

Unique4368 ?
Unique (%)84.7%

Sample

1st row서울특별시 구로구 도림로 59, 201동 217호 (구로동, 구로두산아파트)
2nd row서울특별시 성동구 아차산로 92, 광명타워 10층 1066호 (성수동2가)
3rd row서울특별시 양천구 신정중앙로 68, 4층 403호 (신정동, 해풍빌딩)
4th row서울특별시 성동구 왕십리로2길 20, 3층 (성수동1가)
5th row서울특별시 서초구 신반포로45길 18, 501호 (잠원동)
ValueCountFrequency (%)
서울특별시 5156
 
14.1%
강남구 951
 
2.6%
서초구 592
 
1.6%
2층 438
 
1.2%
역삼동 397
 
1.1%
서초동 381
 
1.0%
3층 377
 
1.0%
송파구 335
 
0.9%
영등포구 328
 
0.9%
4층 303
 
0.8%
Other values (6537) 27405
74.7%
2024-05-18T08:08:31.846188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31519
 
16.4%
1 7384
 
3.8%
, 7080
 
3.7%
6851
 
3.6%
6680
 
3.5%
5757
 
3.0%
5723
 
3.0%
5361
 
2.8%
2 5264
 
2.7%
5210
 
2.7%
Other values (594) 105783
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 107172
55.6%
Decimal Number 34337
 
17.8%
Space Separator 31519
 
16.4%
Other Punctuation 7097
 
3.7%
Close Punctuation 5201
 
2.7%
Open Punctuation 5200
 
2.7%
Dash Punctuation 995
 
0.5%
Uppercase Letter 923
 
0.5%
Lowercase Letter 121
 
0.1%
Letter Number 31
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6851
 
6.4%
6680
 
6.2%
5757
 
5.4%
5723
 
5.3%
5361
 
5.0%
5210
 
4.9%
5163
 
4.8%
5158
 
4.8%
4235
 
4.0%
2770
 
2.6%
Other values (524) 54264
50.6%
Uppercase Letter
ValueCountFrequency (%)
B 178
19.3%
A 133
14.4%
S 77
 
8.3%
T 58
 
6.3%
E 47
 
5.1%
C 43
 
4.7%
I 42
 
4.6%
L 42
 
4.6%
K 40
 
4.3%
G 40
 
4.3%
Other values (15) 223
24.2%
Lowercase Letter
ValueCountFrequency (%)
e 24
19.8%
r 16
13.2%
w 14
11.6%
o 12
9.9%
n 9
 
7.4%
i 8
 
6.6%
t 6
 
5.0%
l 5
 
4.1%
c 4
 
3.3%
b 4
 
3.3%
Other values (10) 19
15.7%
Decimal Number
ValueCountFrequency (%)
1 7384
21.5%
2 5264
15.3%
0 4465
13.0%
3 4040
11.8%
4 2906
 
8.5%
5 2736
 
8.0%
6 2241
 
6.5%
7 1932
 
5.6%
8 1831
 
5.3%
9 1538
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 7080
99.8%
. 11
 
0.2%
/ 3
 
< 0.1%
@ 2
 
< 0.1%
# 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
15
48.4%
8
25.8%
8
25.8%
Math Symbol
ValueCountFrequency (%)
~ 10
62.5%
< 3
 
18.8%
> 3
 
18.8%
Space Separator
ValueCountFrequency (%)
31519
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5201
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5200
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 995
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 107171
55.6%
Common 84365
43.8%
Latin 1075
 
0.6%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6851
 
6.4%
6680
 
6.2%
5757
 
5.4%
5723
 
5.3%
5361
 
5.0%
5210
 
4.9%
5163
 
4.8%
5158
 
4.8%
4235
 
4.0%
2770
 
2.6%
Other values (523) 54263
50.6%
Latin
ValueCountFrequency (%)
B 178
16.6%
A 133
 
12.4%
S 77
 
7.2%
T 58
 
5.4%
E 47
 
4.4%
C 43
 
4.0%
I 42
 
3.9%
L 42
 
3.9%
K 40
 
3.7%
G 40
 
3.7%
Other values (38) 375
34.9%
Common
ValueCountFrequency (%)
31519
37.4%
1 7384
 
8.8%
, 7080
 
8.4%
2 5264
 
6.2%
) 5201
 
6.2%
( 5200
 
6.2%
0 4465
 
5.3%
3 4040
 
4.8%
4 2906
 
3.4%
5 2736
 
3.2%
Other values (12) 8570
 
10.2%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 107171
55.6%
ASCII 85409
44.3%
Number Forms 31
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31519
36.9%
1 7384
 
8.6%
, 7080
 
8.3%
2 5264
 
6.2%
) 5201
 
6.1%
( 5200
 
6.1%
0 4465
 
5.2%
3 4040
 
4.7%
4 2906
 
3.4%
5 2736
 
3.2%
Other values (57) 9614
 
11.3%
Hangul
ValueCountFrequency (%)
6851
 
6.4%
6680
 
6.2%
5757
 
5.4%
5723
 
5.3%
5361
 
5.0%
5210
 
4.9%
5163
 
4.8%
5158
 
4.8%
4235
 
4.0%
2770
 
2.6%
Other values (523) 54263
50.6%
Number Forms
ValueCountFrequency (%)
15
48.4%
8
25.8%
8
25.8%
CJK
ValueCountFrequency (%)
1
100.0%

우편번호
Real number (ℝ)

MISSING 

Distinct1384
Distinct (%)31.4%
Missing5590
Missing (%)55.9%
Infinite0
Infinite (%)0.0%
Mean136331.15
Minimum2519
Maximum410380
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T08:08:32.296878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2519
5-th percentile100845
Q1132040
median136431
Q3143220
95-th percentile157030
Maximum410380
Range407861
Interquartile range (IQR)11180

Descriptive statistics

Standard deviation15582.87
Coefficient of variation (CV)0.11430161
Kurtosis32.103563
Mean136331.15
Median Absolute Deviation (MAD)5608
Skewness-0.57743579
Sum6.0122038 × 108
Variance2.4282583 × 108
MonotonicityNot monotonic
2024-05-18T08:08:32.794655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
135080 153
 
1.5%
137070 127
 
1.3%
157010 77
 
0.8%
135010 66
 
0.7%
151015 56
 
0.6%
151050 52
 
0.5%
152050 48
 
0.5%
142070 41
 
0.4%
139200 38
 
0.4%
137060 38
 
0.4%
Other values (1374) 3714
37.1%
(Missing) 5590
55.9%
ValueCountFrequency (%)
2519 1
< 0.1%
4534 1
< 0.1%
4536 1
< 0.1%
4537 1
< 0.1%
4538 1
< 0.1%
4554 1
< 0.1%
5510 1
< 0.1%
7238 1
< 0.1%
7327 1
< 0.1%
14538 1
< 0.1%
ValueCountFrequency (%)
410380 1
 
< 0.1%
158881 1
 
< 0.1%
158877 2
 
< 0.1%
158871 1
 
< 0.1%
158865 1
 
< 0.1%
158864 2
 
< 0.1%
158863 1
 
< 0.1%
158860 8
0.1%
158859 3
 
< 0.1%
158856 1
 
< 0.1%

등록일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3545
Distinct (%)35.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20136339
Minimum20060124
Maximum20240516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T08:08:33.341644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060124
5-th percentile20070720
Q120091121
median20130218
Q320170726
95-th percentile20221212
Maximum20240516
Range180392
Interquartile range (IQR)79605

Descriptive statistics

Standard deviation48851.552
Coefficient of variation (CV)0.0024260394
Kurtosis-0.91902968
Mean20136339
Median Absolute Deviation (MAD)39497.5
Skewness0.44636463
Sum2.0136339 × 1011
Variance2.3864741 × 109
MonotonicityNot monotonic
2024-05-18T08:08:34.003353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20080814 28
 
0.3%
20080731 25
 
0.2%
20080806 21
 
0.2%
20090520 20
 
0.2%
20080818 19
 
0.2%
20081222 18
 
0.2%
20090514 16
 
0.2%
20080926 16
 
0.2%
20080708 15
 
0.1%
20090511 15
 
0.1%
Other values (3535) 9807
98.1%
ValueCountFrequency (%)
20060124 1
 
< 0.1%
20060306 1
 
< 0.1%
20060308 1
 
< 0.1%
20060310 2
< 0.1%
20060320 4
< 0.1%
20060321 1
 
< 0.1%
20060323 3
< 0.1%
20060324 1
 
< 0.1%
20060327 1
 
< 0.1%
20060329 2
< 0.1%
ValueCountFrequency (%)
20240516 2
< 0.1%
20240514 1
 
< 0.1%
20240510 3
< 0.1%
20240508 2
< 0.1%
20240507 3
< 0.1%
20240503 1
 
< 0.1%
20240502 1
 
< 0.1%
20240430 1
 
< 0.1%
20240426 1
 
< 0.1%
20240425 3
< 0.1%

유효기간만료일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3291
Distinct (%)41.7%
Missing2099
Missing (%)21.0%
Infinite0
Infinite (%)0.0%
Mean20181276
Minimum20090310
Maximum20270517
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T08:08:34.428092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090310
5-th percentile20120330
Q120141026
median20180102
Q320220125
95-th percentile20260412
Maximum20270517
Range180207
Interquartile range (IQR)79099

Descriptive statistics

Standard deviation44234.682
Coefficient of variation (CV)0.0021918674
Kurtosis-0.9869055
Mean20181276
Median Absolute Deviation (MAD)39088
Skewness0.31180389
Sum1.5945226 × 1011
Variance1.9567071 × 109
MonotonicityNot monotonic
2024-05-18T08:08:34.888376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110831 15
 
0.1%
20140418 12
 
0.1%
20140831 12
 
0.1%
20120520 11
 
0.1%
20140721 11
 
0.1%
20140622 11
 
0.1%
20140701 11
 
0.1%
20170602 11
 
0.1%
20180622 11
 
0.1%
20140816 11
 
0.1%
Other values (3281) 7785
77.8%
(Missing) 2099
 
21.0%
ValueCountFrequency (%)
20090310 1
< 0.1%
20091116 1
< 0.1%
20091220 1
< 0.1%
20100112 1
< 0.1%
20100117 1
< 0.1%
20100125 1
< 0.1%
20100411 2
< 0.1%
20100418 2
< 0.1%
20100419 1
< 0.1%
20100427 1
< 0.1%
ValueCountFrequency (%)
20270517 1
< 0.1%
20270516 1
< 0.1%
20270514 1
< 0.1%
20270510 2
< 0.1%
20270509 1
< 0.1%
20270508 2
< 0.1%
20270507 2
< 0.1%
20270506 1
< 0.1%
20270503 1
< 0.1%
20270502 1
< 0.1%

폐쇄일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3123
Distinct (%)36.9%
Missing1543
Missing (%)15.4%
Infinite0
Infinite (%)0.0%
Mean20141943
Minimum20060920
Maximum20240514
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T08:08:35.314055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060920
5-th percentile20090909
Q120110322
median20130723
Q320170420
95-th percentile20220928
Maximum20240514
Range179594
Interquartile range (IQR)60098

Descriptive statistics

Standard deviation41061.531
Coefficient of variation (CV)0.0020386083
Kurtosis-0.57049468
Mean20141943
Median Absolute Deviation (MAD)29796
Skewness0.68619084
Sum1.7034041 × 1011
Variance1.6860493 × 109
MonotonicityNot monotonic
2024-05-18T08:08:35.964465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091116 227
 
2.3%
20100927 71
 
0.7%
20101213 28
 
0.3%
20160725 19
 
0.2%
20110420 18
 
0.2%
20170125 16
 
0.2%
20110729 15
 
0.1%
20170124 15
 
0.1%
20110914 15
 
0.1%
20110125 14
 
0.1%
Other values (3113) 8019
80.2%
(Missing) 1543
 
15.4%
ValueCountFrequency (%)
20060920 2
 
< 0.1%
20080730 1
 
< 0.1%
20090125 1
 
< 0.1%
20090220 1
 
< 0.1%
20090307 1
 
< 0.1%
20090309 6
0.1%
20090311 5
0.1%
20090312 2
 
< 0.1%
20090313 1
 
< 0.1%
20090316 5
0.1%
ValueCountFrequency (%)
20240514 1
 
< 0.1%
20240513 2
< 0.1%
20240510 1
 
< 0.1%
20240509 2
< 0.1%
20240507 3
< 0.1%
20240503 3
< 0.1%
20240502 1
 
< 0.1%
20240501 1
 
< 0.1%
20240430 1
 
< 0.1%
20240429 2
< 0.1%

지점설립일자
Text

MISSING 

Distinct3609
Distinct (%)41.2%
Missing1235
Missing (%)12.3%
Memory size156.2 KiB
2024-05-18T08:08:37.007968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters70120
Distinct characters17
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

Unique1403 ?
Unique (%)16.0%

Sample

1st row20160526
2nd row20050921
3rd row20110915
4th row20110816
5th row20090504
ValueCountFrequency (%)
20090520 23
 
0.3%
20090511 21
 
0.2%
20090514 20
 
0.2%
20090820 18
 
0.2%
20090611 17
 
0.2%
20090528 17
 
0.2%
20090512 15
 
0.2%
20090722 15
 
0.2%
20120413 13
 
0.1%
20110622 12
 
0.1%
Other values (3599) 8594
98.0%
2024-05-18T08:08:38.590932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22741
32.4%
2 16029
22.9%
1 14006
20.0%
3 2831
 
4.0%
9 2674
 
3.8%
7 2602
 
3.7%
6 2532
 
3.6%
5 2297
 
3.3%
8 2211
 
3.2%
4 2179
 
3.1%
Other values (7) 18
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70102
> 99.9%
Space Separator 9
 
< 0.1%
Lowercase Letter 6
 
< 0.1%
Uppercase Letter 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 22741
32.4%
2 16029
22.9%
1 14006
20.0%
3 2831
 
4.0%
9 2674
 
3.8%
7 2602
 
3.7%
6 2532
 
3.6%
5 2297
 
3.3%
8 2211
 
3.2%
4 2179
 
3.1%
Lowercase Letter
ValueCountFrequency (%)
r 2
33.3%
a 2
33.3%
p 1
16.7%
y 1
16.7%
Uppercase Letter
ValueCountFrequency (%)
M 2
66.7%
A 1
33.3%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70111
> 99.9%
Latin 9
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 22741
32.4%
2 16029
22.9%
1 14006
20.0%
3 2831
 
4.0%
9 2674
 
3.8%
7 2602
 
3.7%
6 2532
 
3.6%
5 2297
 
3.3%
8 2211
 
3.2%
4 2179
 
3.1%
Latin
ValueCountFrequency (%)
r 2
22.2%
M 2
22.2%
a 2
22.2%
A 1
11.1%
p 1
11.1%
y 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70120
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 22741
32.4%
2 16029
22.9%
1 14006
20.0%
3 2831
 
4.0%
9 2674
 
3.8%
7 2602
 
3.7%
6 2532
 
3.6%
5 2297
 
3.3%
8 2211
 
3.2%
4 2179
 
3.1%
Other values (7) 18
 
< 0.1%

본점여부
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
본점
9942 
지점
 
58

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 9942
99.4%
지점 58
 
0.6%

Length

2024-05-18T08:08:39.224343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:08:39.672006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
본점 9942
99.4%
지점 58
 
0.6%

최근수정일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3199
Distinct (%)32.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20152577
Minimum20090518
Maximum20240517
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T08:08:40.316601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090518
5-th percentile20091118
Q120110922
median20140731
Q320190415
95-th percentile20231004
Maximum20240517
Range149999
Interquartile range (IQR)79493

Descriptive statistics

Standard deviation45874.044
Coefficient of variation (CV)0.0022763364
Kurtosis-1.0579225
Mean20152577
Median Absolute Deviation (MAD)30491
Skewness0.4530844
Sum2.0152577 × 1011
Variance2.1044279 × 109
MonotonicityNot monotonic
2024-05-18T08:08:40.895753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091117 74
 
0.7%
20090609 62
 
0.6%
20100330 56
 
0.6%
20091116 48
 
0.5%
20100927 45
 
0.4%
20091118 41
 
0.4%
20091119 37
 
0.4%
20110425 34
 
0.3%
20160812 33
 
0.3%
20130621 31
 
0.3%
Other values (3189) 9539
95.4%
ValueCountFrequency (%)
20090518 1
 
< 0.1%
20090519 1
 
< 0.1%
20090521 3
 
< 0.1%
20090601 5
 
0.1%
20090602 1
 
< 0.1%
20090603 7
 
0.1%
20090604 17
 
0.2%
20090605 3
 
< 0.1%
20090608 5
 
0.1%
20090609 62
0.6%
ValueCountFrequency (%)
20240517 2
 
< 0.1%
20240516 8
0.1%
20240514 3
 
< 0.1%
20240513 6
0.1%
20240510 5
0.1%
20240509 4
< 0.1%
20240508 6
0.1%
20240507 6
0.1%
20240503 7
0.1%
20240502 4
< 0.1%

Interactions

2024-05-18T08:08:15.039500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:08:06.126661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:08:08.633925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:08:10.535790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:08:12.965981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:08:15.523230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:08:06.551161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:08:09.067405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:08:11.167922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:08:13.333819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:08:15.931289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:08:07.051358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:08:09.372114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:08:11.732703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:08:13.707828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:08:16.351014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:08:07.602504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:08:09.649291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:08:12.160746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:08:14.073850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:08:16.718379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:08:08.111508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:08:10.134088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:08:12.555897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:08:14.486710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T08:08:41.253789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록신청사업영업구분법인여부우편번호등록일자유효기간만료일자폐쇄일자본점여부최근수정일자
등록신청사업1.0000.0730.0000.0000.2170.1430.1640.0130.166
영업구분0.0731.0000.1910.0460.5830.5930.2000.0410.471
법인여부0.0000.1911.0000.0840.3330.2730.1950.1810.334
우편번호0.0000.0460.0841.0000.2750.2740.4410.0000.333
등록일자0.2170.5830.3330.2751.0001.0000.8540.0730.939
유효기간만료일자0.1430.5930.2730.2741.0001.0000.8350.0730.838
폐쇄일자0.1640.2000.1950.4410.8540.8351.0000.0270.960
본점여부0.0130.0410.1810.0000.0730.0730.0271.0000.085
최근수정일자0.1660.4710.3340.3330.9390.8380.9600.0851.000
2024-05-18T08:08:41.574387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
본점여부법인여부등록신청사업영업구분
본점여부1.0000.1160.0080.044
법인여부0.1161.0000.0000.204
등록신청사업0.0080.0001.0000.079
영업구분0.0440.2040.0791.000
2024-05-18T08:08:42.043881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호등록일자유효기간만료일자폐쇄일자최근수정일자등록신청사업영업구분법인여부본점여부
우편번호1.0000.005-0.0030.0200.0070.0000.0360.0500.000
등록일자0.0051.0000.9970.9630.9670.1670.3440.2560.056
유효기간만료일자-0.0030.9971.0000.9650.9670.1100.3520.2090.056
폐쇄일자0.0200.9630.9651.0000.9920.1640.1160.1950.024
최근수정일자0.0070.9670.9670.9921.0000.1270.2720.2560.065
등록신청사업0.0000.1670.1100.1640.1271.0000.0790.0000.008
영업구분0.0360.3440.3520.1160.2720.0791.0000.2040.044
법인여부0.0500.2560.2090.1950.2560.0000.2041.0000.116
본점여부0.0000.0560.0560.0240.0650.0080.0440.1161.000

Missing values

2024-05-18T08:08:17.172106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T08:08:18.012332image/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.
2024-05-18T08:08:18.745642image/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
10489대부업폐업2016-서울구로-034(대부업)언제나대부개인<NA>서울특별시 구로구 구로동 1266번지서울특별시 구로구 도림로 59, 201동 217호 (구로동, 구로두산아파트)<NA>20160526201905262017062720160526본점20170627
24029대부업<NA>2008-서울관악-00032(대부업)썬기획대부개인<NA>서울특별시 관악구 봉천동 910번지 13호 -202<NA>15105020080724201107242011030820050921본점20110809
26430대부업<NA>2008-서울특별시-02739(대부업)Hybrid Money개인0260121239서울특별시 동대문구 장안4동 291-5 정풍연립 다동 103호<NA>13010420081021<NA>20101115<NA>본점20101115
6490대부업유효기간만료2019-서울성동-00014(대부업)ABC론대부개인<NA>서울특별시 성동구 성수동2가 314번지 5호 광명타워서울특별시 성동구 아차산로 92, 광명타워 10층 1066호 (성수동2가)<NA>2017072520200725<NA>20110915본점20200727
24791대부업<NA>2009-서울특별시-00124(대부업)우선개인024615340서울특별시 광진구 중곡동 255-17<NA><NA>200901132012011320110511<NA>본점20110512
22156대부중개업폐업2011-서울특별시 성북구-00031LS대부중개개인02-922-0309서울특별시 성북구 안암동5가 134번지 94호 2층<NA>13607520110816201408162012031520110816본점20120315
30900<NA><NA>2009-서울특별시-00322선우C&T개인<NA>서울특별시 관악구 남현동 1061-18 르메이에르강남타운Ⅱ 205동 2호<NA>15108020090210<NA>20090527<NA>본점20090618
24209대부업<NA>2008-서울특별시-02726(대부업)한신기획개인023333983서울특별시 양천구 신월동 599-10 1층<NA><NA>20081020<NA>20110721<NA>본점20110721
30395대부업<NA>2009-서울특별시-00517(대부업)어니스트론컴퍼니(대부)개인<NA>서울특별시 도봉구 창동 825 북한산아이파크 510-304<NA><NA>20090420<NA>2009090220090504본점20090903
1092대부중개업폐업2023-서울양천-00002장수대부중개개인<NA>서울특별시 양천구 신정동 905번지 2호 해풍빌딩서울특별시 양천구 신정중앙로 68, 4층 403호 (신정동, 해풍빌딩)<NA>20230206202602062024010820230206본점20240108
등록신청사업영업구분등록증번호상호법인여부사업장 전화번호소재지소재지(도로명)우편번호등록일자유효기간만료일자폐쇄일자지점설립일자본점여부최근수정일자
20464대부업타시군구이관2012-서울광진-0009(대부업)제이대부개인070-4084-7612서울특별시 광진구 중곡동 54번지 29호<NA>14388620120312201503122012091220120312본점20121109
18557대부중개업폐업2012-서울동대문-00270(대부중개업)푸른론 대부중개개인02 878 6181서울특별시 동대문구 휘경동 57번지 105 주공아파트-704<NA>13009020120511201505112013061820120510본점20130618
16467대부중개업직권취소2012-서울성동-0046BL 대부 중개업개인<NA>서울특별시 성동구 용답동 234번지 비 -13서울특별시 성동구 자동차시장1길 82, 비동 2층 13호 (용답동)13384720121109201511092014040420121109본점20140407
29533<NA><NA>2008-서울특별시-02182천향개인0264036107서울특별시 강동구 성내동 413-20 삼덕빌딩 401호<NA>13403020080818<NA>20091116<NA>본점20091123
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0대부업폐업2006-서울특별시-00394(대부업)JSM캐피탈개인0222348157서울특별시 중구 신당동 236번지 89호<NA><NA>20090818201208182006092020060907본점201201172