Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells19242
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
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-10481/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 (93.2%)Imbalance
등록증번호 has 187 (1.9%) missing valuesMissing
사업장 전화번호 has 3454 (34.5%) missing valuesMissing
소재지 has 304 (3.0%) missing valuesMissing
소재지(도로명) has 4752 (47.5%) missing valuesMissing
우편번호 has 5620 (56.2%) missing valuesMissing
유효기간만료일자 has 2041 (20.4%) missing valuesMissing
폐쇄일자 has 1616 (16.2%) missing valuesMissing
지점설립일자 has 1268 (12.7%) missing valuesMissing

Reproduction

Analysis started2024-05-04 04:47:25.175161
Analysis finished2024-05-04 04:47:43.161050
Duration17.99 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
6240 
대부중개업
3374 
<NA>
 
386

Length

Max length5
Median length3
Mean length3.7134
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대부업 6240
62.4%
대부중개업 3374
33.7%
<NA> 386
 
3.9%

Length

2024-05-04T04:47:43.389486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T04:47:43.871285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대부업 6240
62.4%
대부중개업 3374
33.7%
na 386
 
3.9%

영업구분
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
3757 
<NA>
2863 
타시군구이관
1182 
영업중
864 
유효기간만료
807 
Other values (3)
527 

Length

Max length6
Median length4
Mean length3.5602
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3757
37.6%
<NA> 2863
28.6%
타시군구이관 1182
 
11.8%
영업중 864
 
8.6%
유효기간만료 807
 
8.1%
직권취소 524
 
5.2%
갱신등록불가 2
 
< 0.1%
휴업 1
 
< 0.1%

Length

2024-05-04T04:47:44.383185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T04:47:44.823148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3757
37.6%
na 2863
28.6%
타시군구이관 1182
 
11.8%
영업중 864
 
8.6%
유효기간만료 807
 
8.1%
직권취소 524
 
5.2%
갱신등록불가 2
 
< 0.1%
휴업 1
 
< 0.1%

등록증번호
Text

MISSING 

Distinct9754
Distinct (%)99.4%
Missing187
Missing (%)1.9%
Memory size156.2 KiB
2024-05-04T04:47:45.407042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length19.502599
Min length1

Characters and Unicode

Total characters191379
Distinct characters68
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

Unique9695 ?
Unique (%)98.8%

Sample

1st row2011-서울송파-0158(대부업)
2nd row2008-서울특별시-01879(대부업)
3rd row2010-서울구로-00068(대부업)
4th row2018-서울송파-0046(대부업)
5th row2008-서울특별시-00901(대부업)
ValueCountFrequency (%)
2013-서울특별시 20
 
0.2%
2010-서울 20
 
0.2%
2011-서울특별시 19
 
0.2%
2012-서울특별시 17
 
0.2%
대부업 11
 
0.1%
2016-서울특별시 10
 
0.1%
2014-서울특별시 9
 
0.1%
2018-서울특별시 7
 
0.1%
2017-서울특별시 7
 
0.1%
성북구-00005 6
 
0.1%
Other values (9712) 9847
98.7%
2024-05-04T04:47:46.378964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 33935
17.7%
- 19615
 
10.2%
2 15722
 
8.2%
1 11853
 
6.2%
서 10899
 
5.7%
울 9784
 
5.1%
대 8472
 
4.4%
( 8169
 
4.3%
부 8137
 
4.3%
) 8115
 
4.2%
Other values (58) 56678
29.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82550
43.1%
Other Letter 72769
38.0%
Dash Punctuation 19615
 
10.2%
Open Punctuation 8169
 
4.3%
Close Punctuation 8115
 
4.2%
Space Separator 161
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 10899
15.0%
울 9784
13.4%
대 8472
11.6%
부 8137
11.2%
업 7904
10.9%
중 3472
 
4.8%
개 2872
 
3.9%
시 2476
 
3.4%
별 2468
 
3.4%
특 2468
 
3.4%
Other values (44) 13817
19.0%
Decimal Number
ValueCountFrequency (%)
0 33935
41.1%
2 15722
19.0%
1 11853
 
14.4%
3 3698
 
4.5%
4 3100
 
3.8%
8 3055
 
3.7%
6 2893
 
3.5%
7 2788
 
3.4%
9 2770
 
3.4%
5 2736
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 19615
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8169
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8115
100.0%
Space Separator
ValueCountFrequency (%)
161
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 118610
62.0%
Hangul 72769
38.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 10899
15.0%
울 9784
13.4%
대 8472
11.6%
부 8137
11.2%
업 7904
10.9%
중 3472
 
4.8%
개 2872
 
3.9%
시 2476
 
3.4%
별 2468
 
3.4%
특 2468
 
3.4%
Other values (44) 13817
19.0%
Common
ValueCountFrequency (%)
0 33935
28.6%
- 19615
16.5%
2 15722
13.3%
1 11853
 
10.0%
( 8169
 
6.9%
) 8115
 
6.8%
3 3698
 
3.1%
4 3100
 
2.6%
8 3055
 
2.6%
6 2893
 
2.4%
Other values (4) 8455
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 118610
62.0%
Hangul 72769
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 33935
28.6%
- 19615
16.5%
2 15722
13.3%
1 11853
 
10.0%
( 8169
 
6.9%
) 8115
 
6.8%
3 3698
 
3.1%
4 3100
 
2.6%
8 3055
 
2.6%
6 2893
 
2.4%
Other values (4) 8455
 
7.1%
Hangul
ValueCountFrequency (%)
서 10899
15.0%
울 9784
13.4%
대 8472
11.6%
부 8137
11.2%
업 7904
10.9%
중 3472
 
4.8%
개 2872
 
3.9%
시 2476
 
3.4%
별 2468
 
3.4%
특 2468
 
3.4%
Other values (44) 13817
19.0%

상호
Text

Distinct8672
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T04:47:47.267237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length25
Mean length7.7212
Min length1

Characters and Unicode

Total characters77212
Distinct characters757
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7610 ?
Unique (%)76.1%

Sample

1st row얼바인대부
2nd row상영디지탈(주)
3rd row(주)덕원대부기업
4th row주식회사 티에스신용투자대부
5th row(주)이스트브릿지캐피탈
ValueCountFrequency (%)
주식회사 787
 
6.6%
대부중개 311
 
2.6%
대부 311
 
2.6%
유한회사 56
 
0.5%
대부업 20
 
0.2%
캐피탈 17
 
0.1%
전당포 15
 
0.1%
전당포대부 10
 
0.1%
주 10
 
0.1%
the 9
 
0.1%
Other values (8703) 10351
87.0%
2024-05-04T04:47:48.431448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 8498
 
11.0%
부 8136
 
10.5%
주 2672
 
3.5%
이 2229
 
2.9%
개 2116
 
2.7%
중 2087
 
2.7%
스 1922
 
2.5%
1902
 
2.5%
) 1858
 
2.4%
( 1851
 
2.4%
Other values (747) 43941
56.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67770
87.8%
Uppercase Letter 2301
 
3.0%
Space Separator 1902
 
2.5%
Close Punctuation 1858
 
2.4%
Open Punctuation 1851
 
2.4%
Lowercase Letter 1030
 
1.3%
Decimal Number 242
 
0.3%
Other Punctuation 217
 
0.3%
Dash Punctuation 29
 
< 0.1%
Other Symbol 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 8498
 
12.5%
부 8136
 
12.0%
주 2672
 
3.9%
이 2229
 
3.3%
개 2116
 
3.1%
중 2087
 
3.1%
스 1922
 
2.8%
사 1351
 
2.0%
피 1121
 
1.7%
회 1009
 
1.5%
Other values (675) 36629
54.0%
Uppercase Letter
ValueCountFrequency (%)
S 290
 
12.6%
K 197
 
8.6%
M 175
 
7.6%
J 172
 
7.5%
C 162
 
7.0%
H 129
 
5.6%
B 113
 
4.9%
L 97
 
4.2%
A 94
 
4.1%
E 93
 
4.0%
Other values (16) 779
33.9%
Lowercase Letter
ValueCountFrequency (%)
e 131
12.7%
n 118
11.5%
o 117
11.4%
a 89
 
8.6%
t 69
 
6.7%
i 68
 
6.6%
s 55
 
5.3%
l 53
 
5.1%
r 45
 
4.4%
c 44
 
4.3%
Other values (13) 241
23.4%
Decimal Number
ValueCountFrequency (%)
1 67
27.7%
2 48
19.8%
4 36
14.9%
9 22
 
9.1%
5 21
 
8.7%
3 18
 
7.4%
6 14
 
5.8%
0 10
 
4.1%
7 3
 
1.2%
8 3
 
1.2%
Other Punctuation
ValueCountFrequency (%)
. 115
53.0%
& 83
38.2%
? 7
 
3.2%
, 5
 
2.3%
* 4
 
1.8%
/ 1
 
0.5%
？ 1
 
0.5%
＆ 1
 
0.5%
Space Separator
ValueCountFrequency (%)
1902
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1858
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1851
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67774
87.8%
Common 6099
 
7.9%
Latin 3331
 
4.3%
Han 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 8498
 
12.5%
부 8136
 
12.0%
주 2672
 
3.9%
이 2229
 
3.3%
개 2116
 
3.1%
중 2087
 
3.1%
스 1922
 
2.8%
사 1351
 
2.0%
피 1121
 
1.7%
회 1009
 
1.5%
Other values (671) 36633
54.1%
Latin
ValueCountFrequency (%)
S 290
 
8.7%
K 197
 
5.9%
M 175
 
5.3%
J 172
 
5.2%
C 162
 
4.9%
e 131
 
3.9%
H 129
 
3.9%
n 118
 
3.5%
o 117
 
3.5%
B 113
 
3.4%
Other values (39) 1727
51.8%
Common
ValueCountFrequency (%)
1902
31.2%
) 1858
30.5%
( 1851
30.3%
. 115
 
1.9%
& 83
 
1.4%
1 67
 
1.1%
2 48
 
0.8%
4 36
 
0.6%
- 29
 
0.5%
9 22
 
0.4%
Other values (12) 88
 
1.4%
Han
ValueCountFrequency (%)
成 2
25.0%
正 2
25.0%
信 2
25.0%
大 1
12.5%
宙 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67761
87.8%
ASCII 9428
 
12.2%
None 14
 
< 0.1%
CJK 8
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 8498
 
12.5%
부 8136
 
12.0%
주 2672
 
3.9%
이 2229
 
3.3%
개 2116
 
3.1%
중 2087
 
3.1%
스 1922
 
2.8%
사 1351
 
2.0%
피 1121
 
1.7%
회 1009
 
1.5%
Other values (669) 36620
54.0%
ASCII
ValueCountFrequency (%)
1902
20.2%
) 1858
19.7%
( 1851
19.6%
S 290
 
3.1%
K 197
 
2.1%
M 175
 
1.9%
J 172
 
1.8%
C 162
 
1.7%
e 131
 
1.4%
H 129
 
1.4%
Other values (59) 2561
27.2%
None
ValueCountFrequency (%)
㈜ 12
85.7%
？ 1
 
7.1%
＆ 1
 
7.1%
CJK
ValueCountFrequency (%)
成 2
25.0%
正 2
25.0%
信 2
25.0%
大 1
12.5%
宙 1
12.5%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

법인여부
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
개인
7236 
법인
2764 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 7236
72.4%
법인 2764
 
27.6%

Length

2024-05-04T04:47:48.901601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T04:47:49.196567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 7236
72.4%
법인 2764
 
27.6%

사업장 전화번호
Text

MISSING 

Distinct5765
Distinct (%)88.1%
Missing3454
Missing (%)34.5%
Memory size156.2 KiB
2024-05-04T04:47:49.792250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length36
Mean length10.60495
Min length1

Characters and Unicode

Total characters69420
Distinct characters25
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

Unique5122 ?
Unique (%)78.2%

Sample

1st row070-7516-9821
2nd row027425586
3rd row02)2625-9662
4th row02-2203-9987
5th row025589105
ValueCountFrequency (%)
02 283
 
3.8%
070 50
 
0.7%
49
 
0.7%
010 7
 
0.1%
495 6
 
0.1%
6212 5
 
0.1%
2209 5
 
0.1%
025117185 5
 
0.1%
02-2238-1590 5
 
0.1%
024693344 5
 
0.1%
Other values (6071) 6933
94.3%
2024-05-04T04:47:51.281263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11306
16.3%
2 10288
14.8%
- 7085
10.2%
5 5766
8.3%
7 5316
7.7%
1 5147
7.4%
6 4968
7.2%
3 4881
7.0%
8 4780
6.9%
4 4718
6.8%
Other values (15) 5165
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61191
88.1%
Dash Punctuation 7085
 
10.2%
Space Separator 895
 
1.3%
Other Punctuation 126
 
0.2%
Close Punctuation 65
 
0.1%
Math Symbol 32
 
< 0.1%
Open Punctuation 17
 
< 0.1%
Other Letter 5
 
< 0.1%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11306
18.5%
2 10288
16.8%
5 5766
9.4%
7 5316
8.7%
1 5147
8.4%
6 4968
8.1%
3 4881
8.0%
8 4780
7.8%
4 4718
7.7%
9 4021
 
6.6%
Other Letter
ValueCountFrequency (%)
미 1
20.0%
등 1
20.0%
록 1
20.0%
없 1
20.0%
음 1
20.0%
Other Punctuation
ValueCountFrequency (%)
* 65
51.6%
/ 40
31.7%
. 21
 
16.7%
Uppercase Letter
ValueCountFrequency (%)
K 2
50.0%
T 2
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 7085
100.0%
Space Separator
ValueCountFrequency (%)
895
100.0%
Close Punctuation
ValueCountFrequency (%)
) 65
100.0%
Math Symbol
ValueCountFrequency (%)
~ 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69411
> 99.9%
Hangul 5
 
< 0.1%
Latin 4
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11306
16.3%
2 10288
14.8%
- 7085
10.2%
5 5766
8.3%
7 5316
7.7%
1 5147
7.4%
6 4968
7.2%
3 4881
7.0%
8 4780
6.9%
4 4718
6.8%
Other values (8) 5156
7.4%
Hangul
ValueCountFrequency (%)
미 1
20.0%
등 1
20.0%
록 1
20.0%
없 1
20.0%
음 1
20.0%
Latin
ValueCountFrequency (%)
K 2
50.0%
T 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69415
> 99.9%
Hangul 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11306
16.3%
2 10288
14.8%
- 7085
10.2%
5 5766
8.3%
7 5316
7.7%
1 5147
7.4%
6 4968
7.2%
3 4881
7.0%
8 4780
6.9%
4 4718
6.8%
Other values (10) 5160
7.4%
Hangul
ValueCountFrequency (%)
미 1
20.0%
등 1
20.0%
록 1
20.0%
없 1
20.0%
음 1
20.0%

소재지
Text

MISSING 

Distinct8593
Distinct (%)88.6%
Missing304
Missing (%)3.0%
Memory size156.2 KiB
2024-05-04T04:47:52.014156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length51
Mean length31.396246
Min length15

Characters and Unicode

Total characters304418
Distinct characters627
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

Unique7846 ?
Unique (%)80.9%

Sample

1st row서울특별시 송파구 거여동 17번지 9호 1층
2nd row서울특별시 종로구 충신동 60번지 예일빌딩 404호
3rd row서울특별시 구로구 고척동 182번지 4호
4th row서울특별시 송파구 신천동 7번지 23호 대한제당
5th row서울특별시 강남구 역삼동 723-17 삼영빌딩 202호
ValueCountFrequency (%)
서울특별시 9689
 
17.0%
강남구 1598
 
2.8%
서초구 951
 
1.7%
1호 754
 
1.3%
역삼동 680
 
1.2%
송파구 573
 
1.0%
서초동 566
 
1.0%
중구 510
 
0.9%
영등포구 461
 
0.8%
2호 454
 
0.8%
Other values (9359) 40808
71.5%
2024-05-04T04:47:53.532232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
67611
22.2%
1 13471
 
4.4%
서 12087
 
4.0%
동 11104
 
3.6%
구 10474
 
3.4%
시 9962
 
3.3%
울 9744
 
3.2%
별 9698
 
3.2%
특 9691
 
3.2%
2 8705
 
2.9%
Other values (617) 141871
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 166543
54.7%
Space Separator 67611
22.2%
Decimal Number 63153
 
20.7%
Dash Punctuation 5356
 
1.8%
Uppercase Letter 1173
 
0.4%
Other Punctuation 233
 
0.1%
Lowercase Letter 112
 
< 0.1%
Close Punctuation 106
 
< 0.1%
Open Punctuation 105
 
< 0.1%
Letter Number 21
 
< 0.1%
Other values (2) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 12087
 
7.3%
동 11104
 
6.7%
구 10474
 
6.3%
시 9962
 
6.0%
울 9744
 
5.9%
별 9698
 
5.8%
특 9691
 
5.8%
호 8616
 
5.2%
지 8448
 
5.1%
번 7956
 
4.8%
Other values (542) 68763
41.3%
Uppercase Letter
ValueCountFrequency (%)
B 260
22.2%
A 223
19.0%
S 85
 
7.2%
D 74
 
6.3%
K 58
 
4.9%
T 54
 
4.6%
I 50
 
4.3%
E 44
 
3.8%
C 43
 
3.7%
G 36
 
3.1%
Other values (15) 246
21.0%
Lowercase Letter
ValueCountFrequency (%)
e 22
19.6%
n 15
13.4%
c 9
 
8.0%
r 9
 
8.0%
i 9
 
8.0%
t 6
 
5.4%
s 5
 
4.5%
k 4
 
3.6%
b 4
 
3.6%
o 4
 
3.6%
Other values (12) 25
22.3%
Decimal Number
ValueCountFrequency (%)
1 13471
21.3%
2 8705
13.8%
0 7981
12.6%
3 6919
11.0%
4 5708
9.0%
5 4980
 
7.9%
6 4529
 
7.2%
7 4024
 
6.4%
9 3436
 
5.4%
8 3400
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 83
35.6%
/ 81
34.8%
. 62
26.6%
？ 3
 
1.3%
@ 2
 
0.9%
# 1
 
0.4%
* 1
 
0.4%
Letter Number
ValueCountFrequency (%)
Ⅱ 13
61.9%
Ⅲ 4
 
19.0%
Ⅰ 4
 
19.0%
Close Punctuation
ValueCountFrequency (%)
) 105
99.1%
] 1
 
0.9%
Open Punctuation
ValueCountFrequency (%)
( 104
99.0%
[ 1
 
1.0%
Space Separator
ValueCountFrequency (%)
67611
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5356
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 166541
54.7%
Common 136568
44.9%
Latin 1306
 
0.4%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 12087
 
7.3%
동 11104
 
6.7%
구 10474
 
6.3%
시 9962
 
6.0%
울 9744
 
5.9%
별 9698
 
5.8%
특 9691
 
5.8%
호 8616
 
5.2%
지 8448
 
5.1%
번 7956
 
4.8%
Other values (540) 68761
41.3%
Latin
ValueCountFrequency (%)
B 260
19.9%
A 223
17.1%
S 85
 
6.5%
D 74
 
5.7%
K 58
 
4.4%
T 54
 
4.1%
I 50
 
3.8%
E 44
 
3.4%
C 43
 
3.3%
G 36
 
2.8%
Other values (40) 379
29.0%
Common
ValueCountFrequency (%)
67611
49.5%
1 13471
 
9.9%
2 8705
 
6.4%
0 7981
 
5.8%
3 6919
 
5.1%
4 5708
 
4.2%
- 5356
 
3.9%
5 4980
 
3.6%
6 4529
 
3.3%
7 4024
 
2.9%
Other values (14) 7284
 
5.3%
Han
ValueCountFrequency (%)
塘 1
33.3%
金 1
33.3%
內 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 166540
54.7%
ASCII 137850
45.3%
Number Forms 21
 
< 0.1%
None 4
 
< 0.1%
CJK 2
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
67611
49.0%
1 13471
 
9.8%
2 8705
 
6.3%
0 7981
 
5.8%
3 6919
 
5.0%
4 5708
 
4.1%
- 5356
 
3.9%
5 4980
 
3.6%
6 4529
 
3.3%
7 4024
 
2.9%
Other values (60) 8566
 
6.2%
Hangul
ValueCountFrequency (%)
서 12087
 
7.3%
동 11104
 
6.7%
구 10474
 
6.3%
시 9962
 
6.0%
울 9744
 
5.9%
별 9698
 
5.8%
특 9691
 
5.8%
호 8616
 
5.2%
지 8448
 
5.1%
번 7956
 
4.8%
Other values (539) 68760
41.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 13
61.9%
Ⅲ 4
 
19.0%
Ⅰ 4
 
19.0%
None
ValueCountFrequency (%)
？ 3
75.0%
㈜ 1
 
25.0%
CJK
ValueCountFrequency (%)
塘 1
50.0%
內 1
50.0%
CJK Compat Ideographs
ValueCountFrequency (%)
金 1
100.0%

소재지(도로명)
Text

MISSING 

Distinct4781
Distinct (%)91.1%
Missing4752
Missing (%)47.5%
Memory size156.2 KiB
2024-05-04T04:47:54.607934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length55
Mean length37.090701
Min length22

Characters and Unicode

Total characters194652
Distinct characters602
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4371 ?
Unique (%)83.3%

Sample

1st row서울특별시 송파구 올림픽로 299, 대한제당 14층 (신천동)
2nd row서울특별시 중구 퇴계로51길 11, 202호 (충무로5가)
3rd row서울특별시 영등포구 선유로 265 (양평동4가)
4th row서울특별시 영등포구 영중로 65, 334호 (영등포동6가, 영원빌딩)
5th row서울특별시 마포구 월드컵로36길 14, 상암 두산위브센티움 702호 (성산동)
ValueCountFrequency (%)
서울특별시 5246
 
14.2%
강남구 944
 
2.6%
서초구 569
 
1.5%
2층 465
 
1.3%
역삼동 407
 
1.1%
3층 374
 
1.0%
서초동 362
 
1.0%
영등포구 343
 
0.9%
송파구 295
 
0.8%
4층 282
 
0.8%
Other values (6559) 27732
74.9%
2024-05-04T04:47:56.315208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31793
 
16.3%
1 7475
 
3.8%
, 7177
 
3.7%
서 6926
 
3.6%
동 6847
 
3.5%
로 5842
 
3.0%
구 5807
 
3.0%
시 5462
 
2.8%
2 5339
 
2.7%
울 5295
 
2.7%
Other values (592) 106689
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 108429
55.7%
Decimal Number 34652
 
17.8%
Space Separator 31793
 
16.3%
Other Punctuation 7192
 
3.7%
Close Punctuation 5292
 
2.7%
Open Punctuation 5292
 
2.7%
Dash Punctuation 1026
 
0.5%
Uppercase Letter 882
 
0.5%
Lowercase Letter 65
 
< 0.1%
Letter Number 25
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 6926
 
6.4%
동 6847
 
6.3%
로 5842
 
5.4%
구 5807
 
5.4%
시 5462
 
5.0%
울 5295
 
4.9%
별 5254
 
4.8%
특 5248
 
4.8%
호 4221
 
3.9%
길 2757
 
2.5%
Other values (527) 54770
50.5%
Uppercase Letter
ValueCountFrequency (%)
B 173
19.6%
A 128
14.5%
S 79
 
9.0%
E 52
 
5.9%
T 49
 
5.6%
I 48
 
5.4%
C 44
 
5.0%
K 44
 
5.0%
G 31
 
3.5%
R 25
 
2.8%
Other values (15) 209
23.7%
Lowercase Letter
ValueCountFrequency (%)
e 10
15.4%
n 10
15.4%
r 7
10.8%
w 6
9.2%
b 5
7.7%
o 5
7.7%
s 4
 
6.2%
c 4
 
6.2%
t 3
 
4.6%
i 3
 
4.6%
Other values (5) 8
12.3%
Decimal Number
ValueCountFrequency (%)
1 7475
21.6%
2 5339
15.4%
0 4470
12.9%
3 4203
12.1%
4 2867
 
8.3%
5 2704
 
7.8%
6 2284
 
6.6%
7 1896
 
5.5%
8 1809
 
5.2%
9 1605
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 7177
99.8%
. 10
 
0.1%
？ 2
 
< 0.1%
/ 2
 
< 0.1%
@ 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 15
60.0%
Ⅲ 5
 
20.0%
Ⅰ 5
 
20.0%
Close Punctuation
ValueCountFrequency (%)
) 5291
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 5291
> 99.9%
[ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
31793
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1026
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 108429
55.7%
Common 85251
43.8%
Latin 972
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 6926
 
6.4%
동 6847
 
6.3%
로 5842
 
5.4%
구 5807
 
5.4%
시 5462
 
5.0%
울 5295
 
4.9%
별 5254
 
4.8%
특 5248
 
4.8%
호 4221
 
3.9%
길 2757
 
2.5%
Other values (527) 54770
50.5%
Latin
ValueCountFrequency (%)
B 173
17.8%
A 128
13.2%
S 79
 
8.1%
E 52
 
5.3%
T 49
 
5.0%
I 48
 
4.9%
C 44
 
4.5%
K 44
 
4.5%
G 31
 
3.2%
R 25
 
2.6%
Other values (33) 299
30.8%
Common
ValueCountFrequency (%)
31793
37.3%
1 7475
 
8.8%
, 7177
 
8.4%
2 5339
 
6.3%
) 5291
 
6.2%
( 5291
 
6.2%
0 4470
 
5.2%
3 4203
 
4.9%
4 2867
 
3.4%
5 2704
 
3.2%
Other values (12) 8641
 
10.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 108429
55.7%
ASCII 86196
44.3%
Number Forms 25
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31793
36.9%
1 7475
 
8.7%
, 7177
 
8.3%
2 5339
 
6.2%
) 5291
 
6.1%
( 5291
 
6.1%
0 4470
 
5.2%
3 4203
 
4.9%
4 2867
 
3.3%
5 2704
 
3.1%
Other values (51) 9586
 
11.1%
Hangul
ValueCountFrequency (%)
서 6926
 
6.4%
동 6847
 
6.3%
로 5842
 
5.4%
구 5807
 
5.4%
시 5462
 
5.0%
울 5295
 
4.9%
별 5254
 
4.8%
특 5248
 
4.8%
호 4221
 
3.9%
길 2757
 
2.5%
Other values (527) 54770
50.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 15
60.0%
Ⅲ 5
 
20.0%
Ⅰ 5
 
20.0%
None
ValueCountFrequency (%)
？ 2
100.0%

우편번호
Real number (ℝ)

MISSING 

Distinct1388
Distinct (%)31.7%
Missing5620
Missing (%)56.2%
Infinite0
Infinite (%)0.0%
Mean136357.31
Minimum3182
Maximum423060
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T04:47:56.777272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3182
5-th percentile110089.05
Q1132017.75
median136100
Q3142867
95-th percentile157030
Maximum423060
Range419878
Interquartile range (IQR)10849.25

Descriptive statistics

Standard deviation15697.09
Coefficient of variation (CV)0.11511734
Kurtosis69.527774
Mean136357.31
Median Absolute Deviation (MAD)4980
Skewness2.7564891
Sum5.97245 × 108
Variance2.4639863 × 108
MonotonicityNot monotonic
2024-05-04T04:47:57.296601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
135080 157
 
1.6%
137070 139
 
1.4%
157010 63
 
0.6%
135010 62
 
0.6%
142070 49
 
0.5%
151015 45
 
0.4%
158070 43
 
0.4%
100021 39
 
0.4%
151050 39
 
0.4%
138050 39
 
0.4%
Other values (1378) 3705
37.0%
(Missing) 5620
56.2%
ValueCountFrequency (%)
3182 1
 
< 0.1%
4536 1
 
< 0.1%
7238 1
 
< 0.1%
7327 1
 
< 0.1%
100011 7
 
0.1%
100012 2
 
< 0.1%
100013 1
 
< 0.1%
100015 2
 
< 0.1%
100021 39
0.4%
100022 7
 
0.1%
ValueCountFrequency (%)
423060 1
 
< 0.1%
410762 1
 
< 0.1%
403866 1
 
< 0.1%
158877 1
 
< 0.1%
158864 1
 
< 0.1%
158863 1
 
< 0.1%
158860 5
0.1%
158859 3
< 0.1%
158857 1
 
< 0.1%
158849 1
 
< 0.1%

등록일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3531
Distinct (%)35.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20136610
Minimum20030519
Maximum20240502
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T04:47:57.920811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030519
5-th percentile20070829
Q120091128
median20130401
Q320170607
95-th percentile20230201
Maximum20240502
Range209983
Interquartile range (IQR)79479.25

Descriptive statistics

Standard deviation48591.135
Coefficient of variation (CV)0.0024130742
Kurtosis-0.88291663
Mean20136610
Median Absolute Deviation (MAD)39499
Skewness0.46259011
Sum2.013661 × 1011
Variance2.3610984 × 109
MonotonicityNot monotonic
2024-05-04T04:47:58.367675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20080814 27
 
0.3%
20080818 23
 
0.2%
20081222 21
 
0.2%
20080731 20
 
0.2%
20080806 20
 
0.2%
20090520 17
 
0.2%
20090611 17
 
0.2%
20080728 16
 
0.2%
20090507 16
 
0.2%
20140701 15
 
0.1%
Other values (3521) 9808
98.1%
ValueCountFrequency (%)
20030519 1
< 0.1%
20060127 1
< 0.1%
20060306 1
< 0.1%
20060320 2
< 0.1%
20060321 1
< 0.1%
20060323 1
< 0.1%
20060327 2
< 0.1%
20060329 2
< 0.1%
20060331 1
< 0.1%
20060405 2
< 0.1%
ValueCountFrequency (%)
20240502 1
 
< 0.1%
20240430 2
< 0.1%
20240429 1
 
< 0.1%
20240425 2
< 0.1%
20240424 4
< 0.1%
20240423 1
 
< 0.1%
20240422 2
< 0.1%
20240419 1
 
< 0.1%
20240418 1
 
< 0.1%
20240415 4
< 0.1%

유효기간만료일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3296
Distinct (%)41.4%
Missing2041
Missing (%)20.4%
Infinite0
Infinite (%)0.0%
Mean20181007
Minimum20090514
Maximum20270502
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T04:47:58.868078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090514
5-th percentile20120310
Q120141101
median20171215
Q320211127
95-th percentile20260428
Maximum20270502
Range179988
Interquartile range (IQR)70026

Descriptive statistics

Standard deviation44216.84
Coefficient of variation (CV)0.0021910126
Kurtosis-0.94922297
Mean20181007
Median Absolute Deviation (MAD)30508
Skewness0.3329342
Sum1.6062063 × 1011
Variance1.9551289 × 109
MonotonicityNot monotonic
2024-05-04T04:47:59.339533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110831 17
 
0.2%
20170701 16
 
0.2%
20140831 15
 
0.1%
20140816 13
 
0.1%
20141108 13
 
0.1%
20140711 13
 
0.1%
20140822 11
 
0.1%
20180428 11
 
0.1%
20170602 11
 
0.1%
20120520 10
 
0.1%
Other values (3286) 7829
78.3%
(Missing) 2041
 
20.4%
ValueCountFrequency (%)
20090514 1
< 0.1%
20091116 1
< 0.1%
20100117 2
< 0.1%
20100216 1
< 0.1%
20100405 1
< 0.1%
20100410 1
< 0.1%
20100419 1
< 0.1%
20100427 1
< 0.1%
20100514 1
< 0.1%
20100515 1
< 0.1%
ValueCountFrequency (%)
20270502 1
 
< 0.1%
20270430 2
< 0.1%
20270429 1
 
< 0.1%
20270425 2
< 0.1%
20270424 4
< 0.1%
20270423 1
 
< 0.1%
20270421 2
< 0.1%
20270419 1
 
< 0.1%
20270418 1
 
< 0.1%
20270415 4
< 0.1%

폐쇄일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3125
Distinct (%)37.3%
Missing1616
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean20141791
Minimum20050517
Maximum20240503
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T04:47:59.895249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20050517
5-th percentile20090909
Q120110412
median20130805
Q320170314
95-th percentile20220812
Maximum20240503
Range189986
Interquartile range (IQR)59902.25

Descriptive statistics

Standard deviation40281.318
Coefficient of variation (CV)0.0019998877
Kurtosis-0.53080429
Mean20141791
Median Absolute Deviation (MAD)29798
Skewness0.68425025
Sum1.6886877 × 1011
Variance1.6225846 × 109
MonotonicityNot monotonic
2024-05-04T04:48:00.687710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091116 180
 
1.8%
20100927 74
 
0.7%
20101213 26
 
0.3%
20170124 20
 
0.2%
20101126 19
 
0.2%
20110901 18
 
0.2%
20110425 18
 
0.2%
20110420 16
 
0.2%
20160725 16
 
0.2%
20120420 16
 
0.2%
Other values (3115) 7981
79.8%
(Missing) 1616
 
16.2%
ValueCountFrequency (%)
20050517 1
 
< 0.1%
20081212 1
 
< 0.1%
20090128 1
 
< 0.1%
20090211 1
 
< 0.1%
20090305 1
 
< 0.1%
20090307 1
 
< 0.1%
20090309 2
< 0.1%
20090311 3
< 0.1%
20090312 1
 
< 0.1%
20090313 2
< 0.1%
ValueCountFrequency (%)
20240503 3
< 0.1%
20240502 2
< 0.1%
20240501 1
 
< 0.1%
20240430 3
< 0.1%
20240429 1
 
< 0.1%
20240426 1
 
< 0.1%
20240424 1
 
< 0.1%
20240423 1
 
< 0.1%
20240422 1
 
< 0.1%
20240419 2
< 0.1%

지점설립일자
Text

MISSING 

Distinct3546
Distinct (%)40.6%
Missing1268
Missing (%)12.7%
Memory size156.2 KiB
2024-05-04T04:48:01.791251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters69856
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

Unique1335 ?
Unique (%)15.3%

Sample

1st row20111017
2nd row20070522
3rd row20101118
4th row20180406
5th row20040410
ValueCountFrequency (%)
20090520 26
 
0.3%
20090611 20
 
0.2%
20090507 20
 
0.2%
20090514 19
 
0.2%
20090623 17
 
0.2%
20090820 16
 
0.2%
20090529 16
 
0.2%
20111108 14
 
0.2%
20090512 14
 
0.2%
20090528 14
 
0.2%
Other values (3536) 8556
98.0%
2024-05-04T04:48:03.294182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22581
32.3%
2 15841
22.7%
1 14103
20.2%
3 2852
 
4.1%
9 2653
 
3.8%
7 2579
 
3.7%
6 2452
 
3.5%
5 2362
 
3.4%
4 2245
 
3.2%
8 2182
 
3.1%
Other values (4) 6
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69850
> 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 22581
32.3%
2 15841
22.7%
1 14103
20.2%
3 2852
 
4.1%
9 2653
 
3.8%
7 2579
 
3.7%
6 2452
 
3.5%
5 2362
 
3.4%
4 2245
 
3.2%
8 2182
 
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 69853
> 99.9%
Latin 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 22581
32.3%
2 15841
22.7%
1 14103
20.2%
3 2852
 
4.1%
9 2653
 
3.8%
7 2579
 
3.7%
6 2452
 
3.5%
5 2362
 
3.4%
4 2245
 
3.2%
8 2182
 
3.1%
Latin
ValueCountFrequency (%)
A 1
33.3%
p 1
33.3%
r 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69856
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 22581
32.3%
2 15841
22.7%
1 14103
20.2%
3 2852
 
4.1%
9 2653
 
3.8%
7 2579
 
3.7%
6 2452
 
3.5%
5 2362
 
3.4%
4 2245
 
3.2%
8 2182
 
3.1%
Other values (4) 6
 
< 0.1%

본점여부
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
본점
9919 
지점
 
81

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 9919
99.2%
지점 81
 
0.8%

Length

2024-05-04T04:48:03.873384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T04:48:04.300358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
본점 9919
99.2%
지점 81
 
0.8%

최근수정일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3155
Distinct (%)31.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20152887
Minimum20090518
Maximum20240503
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T04:48:04.803408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090518
5-th percentile20091118
Q120111021
median20140966
Q320190212
95-th percentile20230926
Maximum20240503
Range149985
Interquartile range (IQR)79191

Descriptive statistics

Standard deviation45459.671
Coefficient of variation (CV)0.0022557398
Kurtosis-1.0360502
Mean20152887
Median Absolute Deviation (MAD)30546.5
Skewness0.4501269
Sum2.0152887 × 1011
Variance2.0665816 × 109
MonotonicityNot monotonic
2024-05-04T04:48:05.513435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091117 72
 
0.7%
20090609 54
 
0.5%
20091118 45
 
0.4%
20100927 45
 
0.4%
20130621 39
 
0.4%
20100330 38
 
0.4%
20091116 34
 
0.3%
20090622 30
 
0.3%
20091119 28
 
0.3%
20110425 28
 
0.3%
Other values (3145) 9587
95.9%
ValueCountFrequency (%)
20090518 2
 
< 0.1%
20090519 1
 
< 0.1%
20090521 1
 
< 0.1%
20090602 2
 
< 0.1%
20090603 8
 
0.1%
20090604 18
 
0.2%
20090605 1
 
< 0.1%
20090608 3
 
< 0.1%
20090609 54
0.5%
20090610 20
 
0.2%
ValueCountFrequency (%)
20240503 7
0.1%
20240502 5
0.1%
20240501 3
< 0.1%
20240430 7
0.1%
20240429 4
< 0.1%
20240426 3
< 0.1%
20240425 3
< 0.1%
20240424 7
0.1%
20240423 3
< 0.1%
20240422 5
0.1%

Interactions

2024-05-04T04:47:38.765095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:47:31.699636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:47:33.529674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:47:35.204292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:47:36.926115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:47:39.191927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:47:31.978822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:47:33.889480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:47:35.543664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:47:37.221294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:47:39.590137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:47:32.302681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:47:34.183604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:47:35.941802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:47:37.606077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:47:39.956856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:47:32.813408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:47:34.523776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:47:36.271389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:47:38.042323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:47:40.632020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:47:33.213865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:47:34.876286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:47:36.643286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:47:38.411125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T04:48:05.939761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록신청사업영업구분법인여부우편번호등록일자유효기간만료일자폐쇄일자본점여부최근수정일자
등록신청사업1.0000.0560.0140.0000.1670.1500.1520.0000.169
영업구분0.0561.0000.1970.0000.5720.6080.1850.0330.491
법인여부0.0140.1971.0000.0660.2790.3040.2040.2020.362
우편번호0.0000.0000.0661.0000.2140.1640.2700.0000.144
등록일자0.1670.5720.2790.2141.0000.9610.9470.0760.856
유효기간만료일자0.1500.6080.3040.1640.9611.0000.8580.1010.926
폐쇄일자0.1520.1850.2040.2700.9470.8581.0000.0440.951
본점여부0.0000.0330.2020.0000.0760.1010.0441.0000.104
최근수정일자0.1690.4910.3620.1440.8560.9260.9510.1041.000
2024-05-04T04:48:06.392373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록신청사업영업구분법인여부본점여부
등록신청사업1.0000.0600.0090.000
영업구분0.0601.0000.2110.035
법인여부0.0090.2111.0000.130
본점여부0.0000.0350.1301.000
2024-05-04T04:48:06.761351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호등록일자유효기간만료일자폐쇄일자최근수정일자등록신청사업영업구분법인여부본점여부
우편번호1.0000.0200.0150.0450.0300.0000.0000.0520.000
등록일자0.0201.0000.9960.9610.9650.1670.3480.2780.076
유효기간만료일자0.0150.9961.0000.9640.9660.1150.3640.2330.078
폐쇄일자0.0450.9610.9641.0000.9910.1520.1140.2040.042
최근수정일자0.0300.9650.9660.9911.0000.1290.2860.2780.079
등록신청사업0.0000.1670.1150.1520.1291.0000.0600.0090.000
영업구분0.0000.3480.3640.1140.2860.0601.0000.2110.035
법인여부0.0520.2780.2330.2040.2780.0090.2111.0000.130
본점여부0.0000.0760.0780.0420.0790.0000.0350.1301.000

Missing values

2024-05-04T04:47:41.218090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T04:47:42.106729image/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.
2024-05-04T04:47:42.824393image/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
17572대부업폐업2011-서울송파-0158(대부업)얼바인대부개인070-7516-9821서울특별시 송파구 거여동 17번지 9호 1층<NA>13811020111017201410172013100120111017본점20131001
24465대부업<NA>2008-서울특별시-01879(대부업)상영디지탈(주)법인027425586서울특별시 종로구 충신동 60번지 예일빌딩 404호<NA><NA>20080626201106262011062720070522본점20110627
21175대부업폐업2010-서울구로-00068(대부업)(주)덕원대부기업법인02)2625-9662서울특별시 구로구 고척동 182번지 4호<NA>15208020101118201311182012071720101118본점20120717
598대부업영업중2018-서울송파-0046(대부업)주식회사 티에스신용투자대부법인02-2203-9987서울특별시 송파구 신천동 7번지 23호 대한제당서울특별시 송파구 올림픽로 299, 대한제당 14층 (신천동)<NA>2024022620270225<NA>20180406본점20240226
26289대부업<NA>2008-서울특별시-00901(대부업)(주)이스트브릿지캐피탈법인025589105서울특별시 강남구 역삼동 723-17 삼영빌딩 202호<NA>13508020080926<NA>2010112920040410본점20101129
20496대부중개업폐업2012-서울도봉-0038(대부중개업)주식회사 천산대부중개법인1688-9348서울특별시 도봉구 창동 13번지 1호 이큐빌딩-403<NA>13289820120629201506292012103120120629본점20121031
4278대부업영업중2019-서울중구-0061(대부업)대부한빛개인02-2277-6004서울특별시 중구 충무로5가 2번지 1호 -202서울특별시 중구 퇴계로51길 11, 202호 (충무로5가)<NA>2022060320250603<NA>20190725본점20220603
12430대부중개업<NA>2011-서울영등포-0257(대부중개업)한국이지론(주)법인1644-1110서울특별시 영등포구 양평동4가 153번지 11호서울특별시 영등포구 선유로 265 (양평동4가)<NA>2014100720171007<NA>20111103본점20160818
17714대부업타시군구이관2012-서울특별시 성북구-00036예스파이낸셜대부개인<NA>서울특별시 성북구 석관동 10번지 두산아파트 117-1402<NA>13615020120810201508102013090420120810본점20130905
10263대부업타시군구이관2017-서울영등포-0938(대부업)SSE캐피탈대부개인<NA>서울특별시 영등포구 영등포동6가 10번지서울특별시 영등포구 영중로 65, 334호 (영등포동6가, 영원빌딩)<NA>20161123201911222017081120161123본점20170811
등록신청사업영업구분등록증번호상호법인여부사업장 전화번호소재지소재지(도로명)우편번호등록일자유효기간만료일자폐쇄일자지점설립일자본점여부최근수정일자
10353대부업유효기간만료2014-서울중랑-0030(대부업)M.B대부개인<NA>서울특별시 중랑구 면목동 50번지 47호서울특별시 중랑구 용마산로 405 (면목동)13181220140722201707222017072420140722본점20170725
1469대부업유효기간만료2020-서울강남-0142(대부업)디케이파이낸셜대부개인02-6953-3323서울특별시 강남구 역삼동 735번지 36호서울특별시 강남구 테헤란로20길 18, 2층 65호 (역삼동)<NA>20201014202310142023101420201014본점20231025
11222대부업폐업2015-서울서초-0125(대부업)(주)코리아에이엠씨대부법인02-3482-7728서울특별시 서초구 서초동 1697번지 38호 주원빌-503서울특별시 서초구 서초대로55길 15, 503호 (서초동, 주원빌)<NA>20160302201903022017012520130327본점20170125
20429대부중개업타시군구이관2009-서울특별시-02357(대부중개업)미래교회대부중개개인024554504서울특별시 광진구 광장동 246번지 20호 4층-401<NA>14380520091008201210082012013020091008본점20121109
575대부업영업중2021-서울특별시 성북구-00002재경대부개인02-566-2775서울특별시 성북구 장위동 66번지 9호 청마빌딩 2층 16-1호서울특별시 성북구 화랑로33길 39, 청마빌딩 2층 16-1호 (장위동)<NA>2024022720270227<NA>20210331본점20240227
26721대부업<NA>2010-서울송파-0040(대부업)소비자대부금융개인024074494서울특별시 송파구 마천동 88번지 1호 -102<NA>13812020100326<NA>2010100420100326본점20101004
21362대부업폐업2011-서울마포-0073(대부업)WB파이낸셜대부개인<NA>서울특별시 마포구 용강동 494번지 47호 -301<NA>12107020110609201406092012062820110608본점20120628
30045대부업<NA>2007-서울특별시-00742(대부업)한국기업투자금융개인025358555서울특별시 강남구 청담동 88-10<NA><NA>20070530<NA>2009111620070525본점20091117
18991대부업폐업2011-서울도봉-0073(대부업)영실업대부개인<NA>서울특별시 도봉구 창동 819번지 107 태영데시앙아파트-1002<NA><NA>201108032014080320130429<NA>본점20130429
3840대부업영업중2022-서울마포-0034(대부업)미인캐피탈대부개인<NA>서울특별시 마포구 합정동 440번지 10호서울특별시 마포구 희우정로 50, B01호 (합정동)<NA>2022091520250915<NA>20220915본점20220916

Duplicate rows

Most frequently occurring

등록신청사업영업구분등록증번호상호법인여부사업장 전화번호소재지소재지(도로명)우편번호등록일자유효기간만료일자폐쇄일자지점설립일자본점여부최근수정일자# duplicates
0대부업<NA>2009-서울특별시-00046(대부업)오리엔트론개인0260817960서울특별시 서초구 방배동 852-21 학촌빌딩 3층<NA><NA>20090211<NA>2010121320060313본점201101122