Overview

Dataset statistics

Number of variables3
Number of observations381
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.8 KiB
Average record size in memory26.3 B

Variable types

Categorical1
Text1
Numeric1

Dataset

Description한국주택금융공사 채권관리부 업무 관련 공개 공공데이터 (해당 부서의 업무와 관련된 데이터베이스에서 공개 가능한 원천 데이터)
Author한국주택금융공사
URLhttps://www.data.go.kr/data/15073177/fileData.do

Reproduction

Analysis started2023-12-12 17:56:45.027838
Analysis finished2023-12-12 17:56:45.534374
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

PTTN_KIND_CD
Categorical

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
29
184 
31
184 
30
 
12
49
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row29
2nd row31
3rd row29
4th row31
5th row29

Common Values

ValueCountFrequency (%)
29 184
48.3%
31 184
48.3%
30 12
 
3.1%
49 1
 
0.3%

Length

2023-12-13T02:56:45.615808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:56:45.763719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
29 184
48.3%
31 184
48.3%
30 12
 
3.1%
49 1
 
0.3%

CUST_NO
Text

Distinct182
Distinct (%)47.8%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2023-12-13T02:56:46.263653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.984252
Min length3

Characters and Unicode

Total characters3423
Distinct characters13
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

Unique9 ?
Unique (%)2.4%

Sample

1st row020711696
2nd row020711696
3rd row077568215
4th row077568215
5th row084893025
ValueCountFrequency (%)
020711696 4
 
1.0%
065202460 4
 
1.0%
064548455 4
 
1.0%
079117729 4
 
1.0%
069926632 4
 
1.0%
069196608 4
 
1.0%
064328785 4
 
1.0%
077977932 4
 
1.0%
050838730 4
 
1.0%
042585101 4
 
1.0%
Other values (172) 341
89.5%
2023-12-13T02:56:46.796232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 651
19.0%
7 416
12.2%
9 353
10.3%
8 337
9.8%
6 307
9.0%
3 299
8.7%
4 288
8.4%
1 263
7.7%
2 258
 
7.5%
5 248
 
7.2%
Other values (3) 3
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3420
99.9%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 651
19.0%
7 416
12.2%
9 353
10.3%
8 337
9.9%
6 307
9.0%
3 299
8.7%
4 288
8.4%
1 263
7.7%
2 258
 
7.5%
5 248
 
7.3%
Uppercase Letter
ValueCountFrequency (%)
T 1
33.3%
L 1
33.3%
A 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3420
99.9%
Latin 3
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 651
19.0%
7 416
12.2%
9 353
10.3%
8 337
9.9%
6 307
9.0%
3 299
8.7%
4 288
8.4%
1 263
7.7%
2 258
 
7.5%
5 248
 
7.3%
Latin
ValueCountFrequency (%)
T 1
33.3%
L 1
33.3%
A 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3423
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 651
19.0%
7 416
12.2%
9 353
10.3%
8 337
9.8%
6 307
9.0%
3 299
8.7%
4 288
8.4%
1 263
7.7%
2 258
 
7.5%
5 248
 
7.2%
Other values (3) 3
 
0.1%

BASIS_DY
Real number (ℝ)

Distinct50
Distinct (%)13.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20143871
Minimum20140822
Maximum20151231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-13T02:56:46.966114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20140822
5-th percentile20140923
Q120141125
median20141230
Q320151211
95-th percentile20151231
Maximum20151231
Range10409
Interquartile range (IQR)10086

Descriptive statistics

Standard deviation4482.4678
Coefficient of variation (CV)0.00022252266
Kurtosis-0.92757236
Mean20143871
Median Absolute Deviation (MAD)110
Skewness1.0369916
Sum7.6748149 × 109
Variance20092518
MonotonicityNot monotonic
2023-12-13T02:56:47.150151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20141231 70
18.4%
20141119 26
 
6.8%
20151230 26
 
6.8%
20141230 24
 
6.3%
20151231 24
 
6.3%
20141120 20
 
5.2%
20141128 20
 
5.2%
20141127 13
 
3.4%
20151217 12
 
3.1%
20141229 10
 
2.6%
Other values (40) 136
35.7%
ValueCountFrequency (%)
20140822 2
 
0.5%
20140901 4
 
1.0%
20140902 4
 
1.0%
20140905 2
 
0.5%
20140919 6
1.6%
20140923 2
 
0.5%
20140929 10
2.6%
20141008 2
 
0.5%
20141015 2
 
0.5%
20141016 2
 
0.5%
ValueCountFrequency (%)
20151231 24
6.3%
20151230 26
6.8%
20151229 6
 
1.6%
20151228 4
 
1.0%
20151224 2
 
0.5%
20151223 6
 
1.6%
20151218 4
 
1.0%
20151217 12
3.1%
20151215 1
 
0.3%
20151214 2
 
0.5%

Interactions

2023-12-13T02:56:45.168912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:56:47.292984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
PTTN_KIND_CDBASIS_DY
PTTN_KIND_CD1.0000.160
BASIS_DY0.1601.000
2023-12-13T02:56:47.434415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
BASIS_DYPTTN_KIND_CD
BASIS_DY1.0000.105
PTTN_KIND_CD0.1051.000

Missing values

2023-12-13T02:56:45.372670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:56:45.491827image/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

PTTN_KIND_CDCUST_NOBASIS_DY
02902071169620151231
13102071169620151231
22907756821520151231
33107756821520151231
42908489302520151231
53108489302520151231
62901665073220151231
73101665073220151231
82909246119320151231
93109246119320151231
PTTN_KIND_CDCUST_NOBASIS_DY
3713104194427720140902
3722904194427720140902
3733107797793220140902
3742907797793220140902
3753101882372920140901
3762901882372920140901
3773108533347420140901
3782908533347420140901
3793100844803320140822
3802900844803320140822