Overview

Dataset statistics

Number of variables3
Number of observations7292
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory185.3 KiB
Average record size in memory26.0 B

Variable types

Categorical1
Text1
Numeric1

Dataset

Description한국자산관리공사 행복기금 은행 사이트 접속 사용자 수 데이터
Author한국자산관리공사
URLhttps://www.data.go.kr/data/15069817/fileData.do

Alerts

기준년 has constant value ""Constant
기관명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:05:29.619679
Analysis finished2023-12-12 09:05:30.195585
Duration0.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.1 KiB
2013
7292 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2013
2nd row2013
3rd row2013
4th row2013
5th row2013

Common Values

ValueCountFrequency (%)
2013 7292
100.0%

Length

2023-12-12T18:05:30.259188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:05:30.357409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2013 7292
100.0%

기관명
Text

UNIQUE 

Distinct7292
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size57.1 KiB
2023-12-12T18:05:30.556724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length11.326248
Min length4

Characters and Unicode

Total characters82591
Distinct characters580
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7292 ?
Unique (%)100.0%

Sample

1st row(유)가온아이엔디대부
2nd row(유)국민자산관리대부
3rd row(유)대부로자산관리
4th row(유)대한자산관리대부
5th row(유)믿음자산관리대부
ValueCountFrequency (%)
농협(지역 4241
29.3%
새마을금고 1285
 
8.9%
신용협동조합 933
 
6.4%
산림조합중앙회 157
 
1.1%
대부업협회 135
 
0.9%
본점 129
 
0.9%
수협(지역 123
 
0.8%
기술신용보증기금 46
 
0.3%
서울<본 28
 
0.2%
본부총괄 18
 
0.1%
Other values (7015) 7383
51.0%
2023-12-12T18:05:30.888572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7187
 
8.7%
협 6457
 
7.8%
농 5192
 
6.3%
( 4646
 
5.6%
) 4640
 
5.6%
지 4596
 
5.6%
역 4474
 
5.4%
동 2180
 
2.6%
금 1538
 
1.9%
산 1528
 
1.9%
Other values (570) 40153
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 65528
79.3%
Space Separator 7187
 
8.7%
Open Punctuation 4647
 
5.6%
Close Punctuation 4641
 
5.6%
Decimal Number 219
 
0.3%
Math Symbol 156
 
0.2%
Uppercase Letter 132
 
0.2%
Other Symbol 31
 
< 0.1%
Other Punctuation 24
 
< 0.1%
Lowercase Letter 20
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
협 6457
 
9.9%
농 5192
 
7.9%
지 4596
 
7.0%
역 4474
 
6.8%
동 2180
 
3.3%
금 1538
 
2.3%
산 1528
 
2.3%
고 1459
 
2.2%
신 1397
 
2.1%
마 1394
 
2.1%
Other values (518) 35313
53.9%
Uppercase Letter
ValueCountFrequency (%)
S 19
14.4%
K 15
11.4%
C 14
10.6%
B 14
10.6%
I 13
9.8%
G 8
 
6.1%
L 8
 
6.1%
H 7
 
5.3%
M 7
 
5.3%
T 6
 
4.5%
Other values (8) 21
15.9%
Lowercase Letter
ValueCountFrequency (%)
e 3
15.0%
l 2
10.0%
n 2
10.0%
o 2
10.0%
k 2
10.0%
t 2
10.0%
h 1
 
5.0%
y 1
 
5.0%
b 1
 
5.0%
s 1
 
5.0%
Other values (3) 3
15.0%
Decimal Number
ValueCountFrequency (%)
2 68
31.1%
1 63
28.8%
3 40
18.3%
4 31
14.2%
5 10
 
4.6%
6 5
 
2.3%
0 1
 
0.5%
8 1
 
0.5%
Other Punctuation
ValueCountFrequency (%)
, 10
41.7%
. 9
37.5%
& 4
 
16.7%
; 1
 
4.2%
Open Punctuation
ValueCountFrequency (%)
( 4646
> 99.9%
[ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 4640
> 99.9%
] 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
> 78
50.0%
< 78
50.0%
Space Separator
ValueCountFrequency (%)
7187
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 65559
79.4%
Common 16880
 
20.4%
Latin 152
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
협 6457
 
9.8%
농 5192
 
7.9%
지 4596
 
7.0%
역 4474
 
6.8%
동 2180
 
3.3%
금 1538
 
2.3%
산 1528
 
2.3%
고 1459
 
2.2%
신 1397
 
2.1%
마 1394
 
2.1%
Other values (519) 35344
53.9%
Latin
ValueCountFrequency (%)
S 19
12.5%
K 15
 
9.9%
C 14
 
9.2%
B 14
 
9.2%
I 13
 
8.6%
G 8
 
5.3%
L 8
 
5.3%
H 7
 
4.6%
M 7
 
4.6%
T 6
 
3.9%
Other values (21) 41
27.0%
Common
ValueCountFrequency (%)
7187
42.6%
( 4646
27.5%
) 4640
27.5%
> 78
 
0.5%
< 78
 
0.5%
2 68
 
0.4%
1 63
 
0.4%
3 40
 
0.2%
4 31
 
0.2%
, 10
 
0.1%
Other values (10) 39
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 65528
79.3%
ASCII 17032
 
20.6%
None 31
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7187
42.2%
( 4646
27.3%
) 4640
27.2%
> 78
 
0.5%
< 78
 
0.5%
2 68
 
0.4%
1 63
 
0.4%
3 40
 
0.2%
4 31
 
0.2%
S 19
 
0.1%
Other values (41) 182
 
1.1%
Hangul
ValueCountFrequency (%)
협 6457
 
9.9%
농 5192
 
7.9%
지 4596
 
7.0%
역 4474
 
6.8%
동 2180
 
3.3%
금 1538
 
2.3%
산 1528
 
2.3%
고 1459
 
2.2%
신 1397
 
2.1%
마 1394
 
2.1%
Other values (518) 35313
53.9%
None
ValueCountFrequency (%)
㈜ 31
100.0%

접속사용자
Real number (ℝ)

Distinct15
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0954471
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size64.2 KiB
2023-12-12T18:05:31.017354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q32
95-th percentile3
Maximum30
Range29
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.93011672
Coefficient of variation (CV)0.44387507
Kurtosis190.37066
Mean2.0954471
Median Absolute Deviation (MAD)0
Skewness8.8170636
Sum15280
Variance0.86511711
MonotonicityNot monotonic
2023-12-12T18:05:31.208672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2 5120
70.2%
1 1015
 
13.9%
3 914
 
12.5%
4 129
 
1.8%
5 58
 
0.8%
6 17
 
0.2%
7 12
 
0.2%
8 10
 
0.1%
9 8
 
0.1%
10 4
 
0.1%
Other values (5) 5
 
0.1%
ValueCountFrequency (%)
1 1015
 
13.9%
2 5120
70.2%
3 914
 
12.5%
4 129
 
1.8%
5 58
 
0.8%
6 17
 
0.2%
7 12
 
0.2%
8 10
 
0.1%
9 8
 
0.1%
10 4
 
0.1%
ValueCountFrequency (%)
30 1
 
< 0.1%
25 1
 
< 0.1%
19 1
 
< 0.1%
14 1
 
< 0.1%
11 1
 
< 0.1%
10 4
 
0.1%
9 8
0.1%
8 10
0.1%
7 12
0.2%
6 17
0.2%

Interactions

2023-12-12T18:05:29.949710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T18:05:30.074706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:05:30.161260image/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.

Sample

기준년기관명접속사용자
02013(유)가온아이엔디대부1
12013(유)국민자산관리대부1
22013(유)대부로자산관리1
32013(유)대한자산관리대부1
42013(유)믿음자산관리대부1
52013(유)비엔케이에셋대부1
62013(유)씨드파트너스대부1
72013(유)에이치케이에셋대부2
82013(유)엠콜대부1
92013(유)유니스한국자산관리대부2
기준년기관명접속사용자
72822013현대캐피탈(주) Collection기획팀1
72832013현대커머셜3
72842013현대하이카다이렉트자 본사1
72852013현대해상화재 서울<본>3
72862013호수대부1
72872013화승상호저축은행 본점3
72882013효성캐피탈 본점3
72892013흥국상호저축은행 본점3
72902013흥국생명 서울<본>3
72912013흥국쌍용화재보험 서울<본>1