Overview

Dataset statistics

Number of variables3
Number of observations1001
Missing cells3
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory23.6 KiB
Average record size in memory24.1 B

Variable types

DateTime1
Text2

Dataset

Description한국주택금융공사 주택연금부 업무 관련 공개 공공데이터 (해당 부서의 업무와 관련된 데이터베이스에서 공개 가능한 원천 데이터) 기산일자,보증번호,등록일시에 관한 데이터가 포함되어있습니다.
Author한국주택금융공사
URLhttps://www.data.go.kr/data/15073005/fileData.do

Reproduction

Analysis started2023-12-12 16:23:43.145014
Analysis finished2023-12-12 16:23:43.760026
Duration0.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기산일자
Date

Distinct235
Distinct (%)23.5%
Missing1
Missing (%)0.1%
Memory size7.9 KiB
Minimum2017-01-26 00:00:00
Maximum2020-10-14 00:00:00
2023-12-13T01:23:43.820082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:23:43.933463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

보증번호
Text

Distinct945
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-12-13T01:23:44.188889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length14.001998
Min length14

Characters and Unicode

Total characters14016
Distinct characters27
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique909 ?
Unique (%)90.8%

Sample

1st rowRTNA2014000084
2nd rowRTAC2019000175
3rd rowRTAD2019000401
4th rowRTLA2020000099
5th rowRTNA2020000171
ValueCountFrequency (%)
rtna2018000176 7
 
0.7%
rtpa2016000197 5
 
0.5%
rqad2010000072 4
 
0.4%
rtqa2012000017 4
 
0.4%
rtqa2014000095 3
 
0.3%
rtqa2017000212 3
 
0.3%
rtac2019000098 3
 
0.3%
rtpa2018000235 3
 
0.3%
rtqa2013000027 3
 
0.3%
rtpb2017000071 3
 
0.3%
Other values (936) 964
96.2%
2023-12-13T01:23:44.664205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4533
32.3%
2 1441
 
10.3%
1 1421
 
10.1%
R 1002
 
7.1%
A 941
 
6.7%
T 883
 
6.3%
6 440
 
3.1%
3 413
 
2.9%
4 396
 
2.8%
5 369
 
2.6%
Other values (17) 2177
15.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10012
71.4%
Uppercase Letter 4000
 
28.5%
Dash Punctuation 2
 
< 0.1%
Space Separator 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 1002
25.1%
A 941
23.5%
T 883
22.1%
B 275
 
6.9%
H 234
 
5.9%
Q 179
 
4.5%
D 174
 
4.3%
O 80
 
2.0%
C 73
 
1.8%
P 49
 
1.2%
Other values (4) 110
 
2.8%
Decimal Number
ValueCountFrequency (%)
0 4533
45.3%
2 1441
 
14.4%
1 1421
 
14.2%
6 440
 
4.4%
3 413
 
4.1%
4 396
 
4.0%
5 369
 
3.7%
8 365
 
3.6%
7 358
 
3.6%
9 276
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10016
71.5%
Latin 4000
 
28.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 1002
25.1%
A 941
23.5%
T 883
22.1%
B 275
 
6.9%
H 234
 
5.9%
Q 179
 
4.5%
D 174
 
4.3%
O 80
 
2.0%
C 73
 
1.8%
P 49
 
1.2%
Other values (4) 110
 
2.8%
Common
ValueCountFrequency (%)
0 4533
45.3%
2 1441
 
14.4%
1 1421
 
14.2%
6 440
 
4.4%
3 413
 
4.1%
4 396
 
4.0%
5 369
 
3.7%
8 365
 
3.6%
7 358
 
3.6%
9 276
 
2.8%
Other values (3) 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14016
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4533
32.3%
2 1441
 
10.3%
1 1421
 
10.1%
R 1002
 
7.1%
A 941
 
6.7%
T 883
 
6.3%
6 440
 
3.1%
3 413
 
2.9%
4 396
 
2.8%
5 369
 
2.6%
Other values (17) 2177
15.5%

등록일시
Text

Distinct297
Distinct (%)29.7%
Missing2
Missing (%)0.2%
Memory size7.9 KiB
2023-12-13T01:23:45.028134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length16
Mean length16.002002
Min length7

Characters and Unicode

Total characters15986
Distinct characters84
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique284 ?
Unique (%)28.4%

Sample

1st row2020-10-16 14:18
2nd row2020-10-15 9:19
3rd row2020-10-07 16:13
4th row2020-10-05 13:05
5th row2020-09-23 14:30
ValueCountFrequency (%)
2019-03-05 447
22.1%
13:40 445
22.0%
13:35 246
12.2%
2017-02-23 244
12.1%
2019-12-23 15
 
0.7%
2020-06-17 6
 
0.3%
9:24 6
 
0.3%
9:25 5
 
0.2%
2018-06-18 5
 
0.2%
2017-06-19 5
 
0.2%
Other values (448) 595
29.5%
2023-12-13T01:23:45.524162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3129
19.6%
1 2199
13.8%
- 1976
12.4%
3 1832
11.5%
2 1793
11.2%
1030
 
6.4%
: 988
 
6.2%
5 852
 
5.3%
9 668
 
4.2%
4 609
 
3.8%
Other values (74) 910
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11802
73.8%
Dash Punctuation 1976
 
12.4%
Space Separator 1030
 
6.4%
Other Punctuation 988
 
6.2%
Other Letter 176
 
1.1%
Close Punctuation 10
 
0.1%
Open Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 12
 
6.8%
기 12
 
6.8%
산 10
 
5.7%
사 9
 
5.1%
일 9
 
5.1%
래 8
 
4.5%
거 8
 
4.5%
요 8
 
4.5%
청 8
 
4.5%
부 5
 
2.8%
Other values (59) 87
49.4%
Decimal Number
ValueCountFrequency (%)
0 3129
26.5%
1 2199
18.6%
3 1832
15.5%
2 1793
15.2%
5 852
 
7.2%
9 668
 
5.7%
4 609
 
5.2%
7 417
 
3.5%
8 183
 
1.6%
6 120
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 1976
100.0%
Space Separator
ValueCountFrequency (%)
1030
100.0%
Other Punctuation
ValueCountFrequency (%)
: 988
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15810
98.9%
Hangul 176
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 12
 
6.8%
기 12
 
6.8%
산 10
 
5.7%
사 9
 
5.1%
일 9
 
5.1%
래 8
 
4.5%
거 8
 
4.5%
요 8
 
4.5%
청 8
 
4.5%
부 5
 
2.8%
Other values (59) 87
49.4%
Common
ValueCountFrequency (%)
0 3129
19.8%
1 2199
13.9%
- 1976
12.5%
3 1832
11.6%
2 1793
11.3%
1030
 
6.5%
: 988
 
6.2%
5 852
 
5.4%
9 668
 
4.2%
4 609
 
3.9%
Other values (5) 734
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15810
98.9%
Hangul 176
 
1.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3129
19.8%
1 2199
13.9%
- 1976
12.5%
3 1832
11.6%
2 1793
11.3%
1030
 
6.5%
: 988
 
6.2%
5 852
 
5.4%
9 668
 
4.2%
4 609
 
3.9%
Other values (5) 734
 
4.6%
Hangul
ValueCountFrequency (%)
지 12
 
6.8%
기 12
 
6.8%
산 10
 
5.7%
사 9
 
5.1%
일 9
 
5.1%
래 8
 
4.5%
거 8
 
4.5%
요 8
 
4.5%
청 8
 
4.5%
부 5
 
2.8%
Other values (59) 87
49.4%

Missing values

2023-12-13T01:23:43.287207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:23:43.360455image/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.
2023-12-13T01:23:43.721871image/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

기산일자보증번호등록일시
02020-09-22RTNA20140000842020-10-16 14:18
12020-10-14RTAC20190001752020-10-15 9:19
22020-10-05RTAD20190004012020-10-07 16:13
32020-09-29RTLA20200000992020-10-05 13:05
42020-09-14RTNA20200001712020-09-23 14:30
52020-09-11RTAB20160003172020-09-17 9:47
62020-09-11RTPA20200002152020-09-14 15:40
72020-08-28RTAD20170008902020-08-31 10:47
82020-08-20RTOA20170000492020-08-21 16:06
92020-08-07RTAC20120006042020-08-19 15:44
기산일자보증번호등록일시
9912017-02-22RTHA20120000632017-02-23 13:35
9922017-02-22RTHO20160006332017-02-23 13:35
9932017-02-22RTBA20160000202017-02-23 13:35
9942017-02-22RTHO20110002222017-02-23 13:35
9952017-02-22RQAD20110001992017-02-23 13:35
9962017-02-22RTMA20110000972017-02-23 13:35
9972017-02-22RTAB20130001852017-02-23 13:35
9982017-02-22RQAD20110006832017-02-23 13:35
9992017-02-22RQAD20140004252017-02-23 13:35
10002017-02-22RTAA20140000042017-02-23 13:35