Overview

Dataset statistics

Number of variables6
Number of observations252
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.9 KiB
Average record size in memory52.5 B

Variable types

Categorical3
Numeric3

Dataset

Description주택도시보증공사의 융자업무 현황에 대한 정보로서 융자연월, 지점, 잔액(건수 및 금액), 융자금이자수입에 관한 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15010901/fileData.do

Alerts

연월 has constant value ""Constant
융자잔액(건수) is highly overall correlated with 융자잔액(억원) and 2 other fieldsHigh correlation
융자잔액(억원) is highly overall correlated with 융자잔액(건수) and 2 other fieldsHigh correlation
융자금이자 수입실적(천원) is highly overall correlated with 융자잔액(건수) and 2 other fieldsHigh correlation
지점 is highly overall correlated with 융자잔액(건수) and 2 other fieldsHigh correlation
융자잔액(억원) has 12 (4.8%) zerosZeros
융자금이자 수입실적(천원) has 59 (23.4%) zerosZeros

Reproduction

Analysis started2023-12-12 07:54:59.400719
Analysis finished2023-12-12 07:55:01.105225
Duration1.7 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연월
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2022
252 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 252
100.0%

Length

2023-12-12T16:55:01.211483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:55:01.362544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 252
100.0%

월
Categorical

Distinct12
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
1월
21 
2월
21 
3월
21 
4월
21 
5월
21 
Other values (7)
147 

Length

Max length3
Median length2
Mean length2.25
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1월
2nd row2월
3rd row3월
4th row4월
5th row5월

Common Values

ValueCountFrequency (%)
1월 21
8.3%
2월 21
8.3%
3월 21
8.3%
4월 21
8.3%
5월 21
8.3%
6월 21
8.3%
7월 21
8.3%
8월 21
8.3%
9월 21
8.3%
10월 21
8.3%
Other values (2) 42
16.7%

Length

2023-12-12T16:55:01.490601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1월 21
8.3%
2월 21
8.3%
3월 21
8.3%
4월 21
8.3%
5월 21
8.3%
6월 21
8.3%
7월 21
8.3%
8월 21
8.3%
9월 21
8.3%
10월 21
8.3%
Other values (2) 42
16.7%

지점
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
서울북부지사
 
12
서울동부지사
 
12
서울서부지사
 
12
서울남부지사
 
12
인천지사
 
12
Other values (16)
192 

Length

Max length8
Median length6
Mean length5.7619048
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울북부지사 12
 
4.8%
서울동부지사 12
 
4.8%
서울서부지사 12
 
4.8%
서울남부지사 12
 
4.8%
인천지사 12
 
4.8%
경기북부지사 12
 
4.8%
경기남부지사 12
 
4.8%
부산울산지사 12
 
4.8%
대구경북지사 12
 
4.8%
광주전남지사 12
 
4.8%
Other values (11) 132
52.4%

Length

2023-12-12T16:55:01.703041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울북부지사 12
 
4.8%
강원지사 12
 
4.8%
영남관리센터 12
 
4.8%
서울서부관리센터 12
 
4.8%
서울동부관리센터 12
 
4.8%
서울북부관리센터 12
 
4.8%
경남지사 12
 
4.8%
제주출장소 12
 
4.8%
전북지사 12
 
4.8%
충북지사 12
 
4.8%
Other values (11) 132
52.4%

융자잔액(건수)
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.075397
Minimum1
Maximum37
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-12T16:55:01.876255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.55
Q15
median11
Q315
95-th percentile32
Maximum37
Range36
Interquartile range (IQR)10

Descriptive statistics

Standard deviation9.5370044
Coefficient of variation (CV)0.72938546
Kurtosis0.22991729
Mean13.075397
Median Absolute Deviation (MAD)6
Skewness1.0199417
Sum3295
Variance90.954452
MonotonicityNot monotonic
2023-12-12T16:55:02.028184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
5 45
17.9%
13 22
 
8.7%
9 16
 
6.3%
8 14
 
5.6%
15 14
 
5.6%
1 13
 
5.2%
14 13
 
5.2%
26 12
 
4.8%
21 12
 
4.8%
37 12
 
4.8%
Other values (10) 79
31.3%
ValueCountFrequency (%)
1 13
 
5.2%
2 11
 
4.4%
4 3
 
1.2%
5 45
17.9%
7 10
 
4.0%
8 14
 
5.6%
9 16
 
6.3%
10 8
 
3.2%
11 12
 
4.8%
12 11
 
4.4%
ValueCountFrequency (%)
37 12
4.8%
32 9
3.6%
31 3
 
1.2%
26 12
4.8%
24 10
4.0%
23 2
 
0.8%
21 12
4.8%
15 14
5.6%
14 13
5.2%
13 22
8.7%

융자잔액(억원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct76
Distinct (%)30.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean81.980159
Minimum0
Maximum425
Zeros12
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-12T16:55:02.200541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.65
Q113
median41
Q398
95-th percentile310
Maximum425
Range425
Interquartile range (IQR)85

Descriptive statistics

Standard deviation108.78014
Coefficient of variation (CV)1.3269082
Kurtosis2.5523677
Mean81.980159
Median Absolute Deviation (MAD)34
Skewness1.8823804
Sum20659
Variance11833.119
MonotonicityNot monotonic
2023-12-12T16:55:02.340264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24 18
 
7.1%
5 14
 
5.6%
31 12
 
4.8%
0 12
 
4.8%
15 11
 
4.4%
108 9
 
3.6%
11 9
 
3.6%
7 9
 
3.6%
4 9
 
3.6%
54 8
 
3.2%
Other values (66) 141
56.0%
ValueCountFrequency (%)
0 12
4.8%
1 1
 
0.4%
4 9
3.6%
5 14
5.6%
7 9
3.6%
8 3
 
1.2%
11 9
3.6%
12 3
 
1.2%
13 4
 
1.6%
14 3
 
1.2%
ValueCountFrequency (%)
425 3
1.2%
420 4
1.6%
414 1
 
0.4%
403 1
 
0.4%
402 1
 
0.4%
399 1
 
0.4%
390 1
 
0.4%
310 2
0.8%
308 1
 
0.4%
303 1
 
0.4%

융자금이자 수입실적(천원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct140
Distinct (%)55.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1715.1151
Minimum0
Maximum11449
Zeros59
Zeros (%)23.4%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-12T16:55:02.517537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q117
median234
Q31755.5
95-th percentile7478.6
Maximum11449
Range11449
Interquartile range (IQR)1738.5

Descriptive statistics

Standard deviation2682.1954
Coefficient of variation (CV)1.5638574
Kurtosis1.2530864
Mean1715.1151
Median Absolute Deviation (MAD)234
Skewness1.5975881
Sum432209
Variance7194172.2
MonotonicityNot monotonic
2023-12-12T16:55:02.690609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 59
23.4%
17 8
 
3.2%
24 7
 
2.8%
98 7
 
2.8%
23 5
 
2.0%
20 5
 
2.0%
1273 4
 
1.6%
95 4
 
1.6%
407 3
 
1.2%
234 3
 
1.2%
Other values (130) 147
58.3%
ValueCountFrequency (%)
0 59
23.4%
2 1
 
0.4%
17 8
 
3.2%
18 1
 
0.4%
19 1
 
0.4%
20 5
 
2.0%
21 2
 
0.8%
22 1
 
0.4%
23 5
 
2.0%
24 7
 
2.8%
ValueCountFrequency (%)
11449 1
0.4%
9445 1
0.4%
9359 1
0.4%
9098 1
0.4%
8859 1
0.4%
8600 1
0.4%
8557 1
0.4%
8517 1
0.4%
8378 1
0.4%
8372 1
0.4%

Interactions

2023-12-12T16:55:00.093553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:59.597657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:59.844301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:55:00.188116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:59.681954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:59.933128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:55:00.619424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:59.754148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:55:00.001534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:55:02.779022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
월지점융자잔액(건수)융자잔액(억원)융자금이자 수입실적(천원)
월1.0000.0000.0000.0000.000
지점0.0001.0000.9970.9860.891
융자잔액(건수)0.0000.9971.0000.8110.781
융자잔액(억원)0.0000.9860.8111.0000.761
융자금이자 수입실적(천원)0.0000.8910.7810.7611.000
2023-12-12T16:55:02.891030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
월지점
월1.0000.000
지점0.0001.000
2023-12-12T16:55:03.001148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
융자잔액(건수)융자잔액(억원)융자금이자 수입실적(천원)월지점
융자잔액(건수)1.0000.8440.7980.0000.964
융자잔액(억원)0.8441.0000.5910.0000.800
융자금이자 수입실적(천원)0.7980.5911.0000.0000.586
월0.0000.0000.0001.0000.000
지점0.9640.8000.5860.0001.000

Missing values

2023-12-12T16:55:00.785884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:55:01.032954image/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

연월월지점융자잔액(건수)융자잔액(억원)융자금이자 수입실적(천원)
020221월서울북부지사264254844
120222월서울북부지사264257136
220223월서울북부지사264259098
320224월서울북부지사264204453
420225월서울북부지사264209359
520226월서울북부지사264206914
620227월서울북부지사264204110
720228월서울북부지사264149445
820229월서울북부지사264036844
9202210월서울북부지사264025978
연월월지점융자잔액(건수)융자잔액(억원)융자금이자 수입실적(천원)
24220223월중부관리센터5240
24320224월중부관리센터5240
24420225월중부관리센터5240
24520226월중부관리센터5240
24620227월중부관리센터5240
24720228월중부관리센터5240
24820229월중부관리센터5240
249202210월중부관리센터5240
250202211월중부관리센터5240
251202212월중부관리센터4240