Overview

Dataset statistics

Number of variables4
Number of observations41
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory38.2 B

Variable types

Numeric3
Categorical1

Dataset

Description한국주택금융공사 채권관리부 업무 관련 공개 공공데이터 (해당 부서의 업무와 관련된 데이터베이스에서 공개 가능한 원천 데이터)
Author한국주택금융공사
URLhttps://www.data.go.kr/data/15072902/fileData.do

Reproduction

Analysis started2023-12-12 04:52:14.974568
Analysis finished2023-12-12 04:52:16.202136
Duration1.23 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

접수품의번호
Real number (ℝ)

Distinct25
Distinct (%)61.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0160844 × 1010
Minimum2.01106 × 1010
Maximum2.02006 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T13:52:16.316347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.01106 × 1010
5-th percentile2.01206 × 1010
Q12.01406 × 1010
median2.01406 × 1010
Q32.01906 × 1010
95-th percentile2.02006 × 1010
Maximum2.02006 × 1010
Range90000008
Interquartile range (IQR)50000001

Descriptive statistics

Standard deviation29705876
Coefficient of variation (CV)0.0014734441
Kurtosis-1.5508993
Mean2.0160844 × 1010
Median Absolute Deviation (MAD)19999995
Skewness0.27589023
Sum8.265946 × 1011
Variance8.8243906 × 1014
MonotonicityNot monotonic
2023-12-12T13:52:16.506242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
20140600004 6
 
14.6%
20140600003 6
 
14.6%
20130600001 3
 
7.3%
20200600001 2
 
4.9%
20190600001 2
 
4.9%
20200600008 2
 
4.9%
20140600006 2
 
4.9%
20200600009 1
 
2.4%
20160600002 1
 
2.4%
20110600001 1
 
2.4%
Other values (15) 15
36.6%
ValueCountFrequency (%)
20110600001 1
 
2.4%
20120600001 1
 
2.4%
20120600002 1
 
2.4%
20130600001 3
7.3%
20140600001 1
 
2.4%
20140600002 1
 
2.4%
20140600003 6
14.6%
20140600004 6
14.6%
20140600006 2
 
4.9%
20150600002 1
 
2.4%
ValueCountFrequency (%)
20200600009 1
2.4%
20200600008 2
4.9%
20200600007 1
2.4%
20200600005 1
2.4%
20200600004 1
2.4%
20200600003 1
2.4%
20200600002 1
2.4%
20200600001 2
4.9%
20190600004 1
2.4%
20190600003 1
2.4%

소송대상자순번
Real number (ℝ)

Distinct6
Distinct (%)14.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.902439
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T13:52:16.655869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile5
Maximum6
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.4629572
Coefficient of variation (CV)0.76899035
Kurtosis1.8824978
Mean1.902439
Median Absolute Deviation (MAD)0
Skewness1.68797
Sum78
Variance2.1402439
MonotonicityNot monotonic
2023-12-12T13:52:16.823573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 25
61.0%
2 7
 
17.1%
3 3
 
7.3%
6 2
 
4.9%
5 2
 
4.9%
4 2
 
4.9%
ValueCountFrequency (%)
1 25
61.0%
2 7
 
17.1%
3 3
 
7.3%
4 2
 
4.9%
5 2
 
4.9%
6 2
 
4.9%
ValueCountFrequency (%)
6 2
 
4.9%
5 2
 
4.9%
4 2
 
4.9%
3 3
 
7.3%
2 7
 
17.1%
1 25
61.0%

주채무자고객번호
Real number (ℝ)

Distinct17
Distinct (%)41.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean88678754
Minimum64588826
Maximum1.2514079 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T13:52:16.997486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum64588826
5-th percentile65008415
Q174329486
median89061797
Q397837492
95-th percentile1.2138938 × 108
Maximum1.2514079 × 108
Range60551966
Interquartile range (IQR)23508006

Descriptive statistics

Standard deviation17346066
Coefficient of variation (CV)0.19560565
Kurtosis-0.43051664
Mean88678754
Median Absolute Deviation (MAD)10638707
Skewness0.5196048
Sum3.6358289 × 109
Variance3.0088599 × 1014
MonotonicityNot monotonic
2023-12-12T13:52:17.145428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
89061797 12
29.3%
108978020 4
 
9.8%
74253293 3
 
7.3%
80953943 3
 
7.3%
66081800 3
 
7.3%
65008415 2
 
4.9%
125140792 2
 
4.9%
115882109 2
 
4.9%
64588826 2
 
4.9%
98234492 1
 
2.4%
Other values (7) 7
17.1%
ValueCountFrequency (%)
64588826 2
4.9%
65008415 2
4.9%
66081800 3
7.3%
74253293 3
7.3%
74329486 1
 
2.4%
78423090 1
 
2.4%
80232570 1
 
2.4%
80953943 3
7.3%
87124490 1
 
2.4%
88496868 1
 
2.4%
ValueCountFrequency (%)
125140792 2
 
4.9%
121389379 1
 
2.4%
115882109 2
 
4.9%
108978020 4
 
9.8%
98234492 1
 
2.4%
97837492 1
 
2.4%
89061797 12
29.3%
88496868 1
 
2.4%
87124490 1
 
2.4%
80953943 3
 
7.3%

채무관계자구분코드
Categorical

Distinct3
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size460.0 B
<NA>
22 
피보증인
17 
상속인
 
2

Length

Max length4
Median length4
Mean length3.9512195
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row피보증인
2nd row상속인
3rd row피보증인
4th row피보증인
5th row상속인

Common Values

ValueCountFrequency (%)
<NA> 22
53.7%
피보증인 17
41.5%
상속인 2
 
4.9%

Length

2023-12-12T13:52:17.330373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:52:17.472889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 22
53.7%
피보증인 17
41.5%
상속인 2
 
4.9%

Interactions

2023-12-12T13:52:15.718441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:52:15.136050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:52:15.435007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:52:15.801233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:52:15.234529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:52:15.550098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:52:15.893221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:52:15.332417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:52:15.628746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:52:17.578023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
접수품의번호소송대상자순번주채무자고객번호채무관계자구분코드
접수품의번호1.0000.0000.8640.000
소송대상자순번0.0001.0000.0000.314
주채무자고객번호0.8640.0001.000NaN
채무관계자구분코드0.0000.314NaN1.000
2023-12-12T13:52:17.720465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
접수품의번호소송대상자순번주채무자고객번호채무관계자구분코드
접수품의번호1.000-0.2910.2330.000
소송대상자순번-0.2911.0000.0280.196
주채무자고객번호0.2330.0281.0000.000
채무관계자구분코드0.0000.1960.0001.000

Missing values

2023-12-12T13:52:16.042422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:52:16.160605image/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

접수품의번호소송대상자순번주채무자고객번호채무관계자구분코드
020200600009174253293피보증인
120200600008264588826상속인
2202006000071121389379피보증인
3202006000051108978020피보증인
420200600008164588826상속인
5202006000031108978020피보증인
6202006000021108978020피보증인
720200600001274253293<NA>
820200600001174253293<NA>
920190600004180232570피보증인
접수품의번호소송대상자순번주채무자고객번호채무관계자구분코드
3120140600004189061797피보증인
3220140600002188496868<NA>
3320140600001187124490<NA>
3420130600001380953943<NA>
3520130600001280953943<NA>
3620130600001180953943<NA>
3720120600002165008415피보증인
3820140600003189061797피보증인
3920120600001166081800피보증인
4020110600001165008415피보증인