Overview

Dataset statistics

Number of variables6
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.1 KiB
Average record size in memory52.3 B

Variable types

Text1
Numeric2
Categorical2
DateTime1

Dataset

Description한국주택금융공사 주택연금부 업무 관련 공개 공공데이터 (해당 부서의 업무와 관련된 데이터베이스에서 공개 가능한 원천 데이터)
Author한국주택금융공사
URLhttps://www.data.go.kr/data/15073131/fileData.do

Alerts

순번 has constant value ""Constant
등록일시 has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:52:36.848285
Analysis finished2023-12-12 09:52:38.130524
Duration1.28 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

보증번호
Text

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-12T18:52:38.372606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters1400
Distinct characters22
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)94.0%

Sample

1st rowRQAD2016000448
2nd rowRTBA2018000532
3rd rowRTAA2012000182
4th rowRQAD2019000228
5th rowRTAB2019000994
ValueCountFrequency (%)
rtad2015000314 2
 
2.0%
rtba2011000032 2
 
2.0%
rtba2018000424 2
 
2.0%
rtqa2018000359 1
 
1.0%
rtab2015000611 1
 
1.0%
rtqa2019000346 1
 
1.0%
rtha2007000003 1
 
1.0%
rtha2018000006 1
 
1.0%
rtho2018000425 1
 
1.0%
rtha2019000556 1
 
1.0%
Other values (87) 87
87.0%
2023-12-12T18:52:39.053074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 441
31.5%
2 142
 
10.1%
1 137
 
9.8%
R 100
 
7.1%
T 90
 
6.4%
A 89
 
6.4%
9 53
 
3.8%
8 48
 
3.4%
6 42
 
3.0%
B 39
 
2.8%
Other values (12) 219
15.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
71.4%
Uppercase Letter 400
 
28.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 100
25.0%
T 90
22.5%
A 89
22.2%
B 39
 
9.8%
H 24
 
6.0%
D 18
 
4.5%
Q 14
 
3.5%
C 9
 
2.2%
O 8
 
2.0%
P 4
 
1.0%
Other values (2) 5
 
1.2%
Decimal Number
ValueCountFrequency (%)
0 441
44.1%
2 142
 
14.2%
1 137
 
13.7%
9 53
 
5.3%
8 48
 
4.8%
6 42
 
4.2%
4 38
 
3.8%
3 35
 
3.5%
7 33
 
3.3%
5 31
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
71.4%
Latin 400
 
28.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 100
25.0%
T 90
22.5%
A 89
22.2%
B 39
 
9.8%
H 24
 
6.0%
D 18
 
4.5%
Q 14
 
3.5%
C 9
 
2.2%
O 8
 
2.0%
P 4
 
1.0%
Other values (2) 5
 
1.2%
Common
ValueCountFrequency (%)
0 441
44.1%
2 142
 
14.2%
1 137
 
13.7%
9 53
 
5.3%
8 48
 
4.8%
6 42
 
4.2%
4 38
 
3.8%
3 35
 
3.5%
7 33
 
3.3%
5 31
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 441
31.5%
2 142
 
10.1%
1 137
 
9.8%
R 100
 
7.1%
T 90
 
6.4%
A 89
 
6.4%
9 53
 
3.8%
8 48
 
3.4%
6 42
 
3.0%
B 39
 
2.8%
Other values (12) 219
15.6%

개별순번
Real number (ℝ)

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.23
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-12T18:52:39.293754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile5.05
Maximum12
Range11
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.9840526
Coefficient of variation (CV)0.88970968
Kurtosis11.711834
Mean2.23
Median Absolute Deviation (MAD)1
Skewness3.1024893
Sum223
Variance3.9364646
MonotonicityNot monotonic
2023-12-12T18:52:39.529503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 45
45.0%
2 29
29.0%
3 13
 
13.0%
4 5
 
5.0%
5 3
 
3.0%
12 2
 
2.0%
6 1
 
1.0%
7 1
 
1.0%
9 1
 
1.0%
ValueCountFrequency (%)
1 45
45.0%
2 29
29.0%
3 13
 
13.0%
4 5
 
5.0%
5 3
 
3.0%
6 1
 
1.0%
7 1
 
1.0%
9 1
 
1.0%
12 2
 
2.0%
ValueCountFrequency (%)
12 2
 
2.0%
9 1
 
1.0%
7 1
 
1.0%
6 1
 
1.0%
5 3
 
3.0%
4 5
 
5.0%
3 13
 
13.0%
2 29
29.0%
1 45
45.0%

순번
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1
100 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 100
100.0%

Length

2023-12-12T18:52:39.742934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:52:39.891236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 100
100.0%

사용일자
Categorical

Distinct18
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2019-12-30
12 
2019-12-17
10 
2019-12-24
10 
2019-12-27
8 
2019-12-23
7 
Other values (13)
53 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique4 ?
Unique (%)4.0%

Sample

1st row2020-01-07
2nd row2020-01-07
3rd row2020-01-06
4th row2020-01-07
5th row2020-01-07

Common Values

ValueCountFrequency (%)
2019-12-30 12
12.0%
2019-12-17 10
10.0%
2019-12-24 10
10.0%
2019-12-27 8
 
8.0%
2019-12-23 7
 
7.0%
2019-12-26 7
 
7.0%
2020-01-07 7
 
7.0%
2020-01-03 7
 
7.0%
2019-12-16 6
 
6.0%
2020-01-02 5
 
5.0%
Other values (8) 21
21.0%

Length

2023-12-12T18:52:40.037091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2019-12-30 12
12.0%
2019-12-24 10
10.0%
2019-12-17 10
10.0%
2019-12-27 8
 
8.0%
2019-12-23 7
 
7.0%
2019-12-26 7
 
7.0%
2020-01-07 7
 
7.0%
2020-01-03 7
 
7.0%
2019-12-16 6
 
6.0%
2019-12-31 5
 
5.0%
Other values (8) 21
21.0%

등록사번
Real number (ℝ)

Distinct35
Distinct (%)35.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1687.87
Minimum1174
Maximum1937
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-12T18:52:40.204775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1174
5-th percentile1406
Q11535
median1681
Q31859
95-th percentile1932
Maximum1937
Range763
Interquartile range (IQR)324

Descriptive statistics

Standard deviation176.57205
Coefficient of variation (CV)0.10461235
Kurtosis-0.79649394
Mean1687.87
Median Absolute Deviation (MAD)149
Skewness-0.24013416
Sum168787
Variance31177.69
MonotonicityNot monotonic
2023-12-12T18:52:40.388806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
1859 10
 
10.0%
1406 6
 
6.0%
1773 6
 
6.0%
1917 6
 
6.0%
1547 6
 
6.0%
1650 6
 
6.0%
1535 6
 
6.0%
1721 5
 
5.0%
1532 4
 
4.0%
1656 4
 
4.0%
Other values (25) 41
41.0%
ValueCountFrequency (%)
1174 1
 
1.0%
1406 6
6.0%
1410 3
3.0%
1476 1
 
1.0%
1497 1
 
1.0%
1513 4
4.0%
1532 4
4.0%
1535 6
6.0%
1547 6
6.0%
1569 4
4.0%
ValueCountFrequency (%)
1937 2
 
2.0%
1932 4
 
4.0%
1921 2
 
2.0%
1917 6
6.0%
1914 1
 
1.0%
1913 1
 
1.0%
1901 2
 
2.0%
1874 1
 
1.0%
1866 1
 
1.0%
1859 10
10.0%

등록일시
Date

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2019-12-12 19:48:00
Maximum2020-01-06 16:36:00
2023-12-12T18:52:40.559512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:52:40.685561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-12T18:52:37.382141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:52:37.099715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:52:37.577109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:52:37.205582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:52:40.778006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
보증번호개별순번사용일자등록사번등록일시
보증번호1.0000.0000.9511.0001.000
개별순번0.0001.0000.0000.0661.000
사용일자0.9510.0001.0000.0001.000
등록사번1.0000.0660.0001.0001.000
등록일시1.0001.0001.0001.0001.000
2023-12-12T18:52:40.886314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
개별순번등록사번사용일자
개별순번1.0000.1460.000
등록사번0.1461.0000.000
사용일자0.0000.0001.000

Missing values

2023-12-12T18:52:37.857429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:52:38.048849image/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

보증번호개별순번순번사용일자등록사번등록일시
0RQAD2016000448112020-01-0714062020-01-06 16:36
1RTBA2018000532312020-01-0718592020-01-06 16:17
2RTAA2012000182112020-01-0615352020-01-06 15:45
3RQAD2019000228312020-01-0714062020-01-06 15:33
4RTAB2019000994112020-01-0715322020-01-06 15:19
5RTAC2016001069112020-01-0719322020-01-06 15:14
6RTBA2019000893112020-01-0718592020-01-06 15:10
7RTBA2018000424512020-01-0719012020-01-06 15:01
8RTPA2007000031112020-01-0817932020-01-06 13:45
9RTBA2016000028212020-01-0618592020-01-03 17:20
보증번호개별순번순번사용일자등록사번등록일시
90RTHB2011000222412019-12-1717732019-12-16 13:09
91RTHO2010000008112019-12-1615352019-12-16 10:56
92RTHO2018000464312019-12-1719172019-12-16 10:37
93RTHO2019000397212019-12-1719172019-12-16 10:36
94RTHB2017000524212019-12-1615472019-12-13 16:24
95RQAD2018000798212019-12-1616862019-12-13 15:22
96RTAC2018000121112019-12-1615352019-12-13 14:18
97RTAD2015000314212019-12-1616502019-12-13 11:21
98RTAD2019000910112019-12-1616502019-12-13 11:20
99RTBA2014000373112019-12-1318592019-12-12 19:48