Overview

Dataset statistics

Number of variables17
Number of observations25
Missing cells209
Missing cells (%)49.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory157.3 B

Variable types

Text1
Numeric16

Dataset

Description주택도시보증공사에서 발급된 각 보증상품별 단위당 VaR의 월말 기준 값 각 보증상품별로 예상되는 최대손실 정도를 나타내는 수치 제공- 데이터 기간 : 24.02.29. 기준
Author주택도시보증공사
URLhttps://www.data.go.kr/data/3047681/fileData.do

Alerts

1등급 is highly overall correlated with 2등급 and 14 other fieldsHigh correlation
2등급 is highly overall correlated with 1등급 and 14 other fieldsHigh correlation
3등급 is highly overall correlated with 1등급 and 14 other fieldsHigh correlation
4등급 is highly overall correlated with 1등급 and 14 other fieldsHigh correlation
5등급 is highly overall correlated with 1등급 and 14 other fieldsHigh correlation
6등급 is highly overall correlated with 1등급 and 13 other fieldsHigh correlation
7등급 is highly overall correlated with 1등급 and 14 other fieldsHigh correlation
8등급 is highly overall correlated with 1등급 and 13 other fieldsHigh correlation
9등급 is highly overall correlated with 1등급 and 14 other fieldsHigh correlation
10등급 is highly overall correlated with 1등급 and 13 other fieldsHigh correlation
11등급 is highly overall correlated with 1등급 and 14 other fieldsHigh correlation
12등급 is highly overall correlated with 1등급 and 14 other fieldsHigh correlation
13등급 is highly overall correlated with 1등급 and 13 other fieldsHigh correlation
14등급 is highly overall correlated with 1등급 and 14 other fieldsHigh correlation
15등급 is highly overall correlated with 1등급 and 10 other fieldsHigh correlation
무등급 is highly overall correlated with 1등급 and 14 other fieldsHigh correlation
1등급 has 14 (56.0%) missing valuesMissing
2등급 has 13 (52.0%) missing valuesMissing
3등급 has 12 (48.0%) missing valuesMissing
4등급 has 14 (56.0%) missing valuesMissing
5등급 has 14 (56.0%) missing valuesMissing
6등급 has 12 (48.0%) missing valuesMissing
7등급 has 15 (60.0%) missing valuesMissing
8등급 has 7 (28.0%) missing valuesMissing
9등급 has 10 (40.0%) missing valuesMissing
10등급 has 12 (48.0%) missing valuesMissing
11등급 has 19 (76.0%) missing valuesMissing
12등급 has 14 (56.0%) missing valuesMissing
13등급 has 15 (60.0%) missing valuesMissing
14등급 has 15 (60.0%) missing valuesMissing
15등급 has 12 (48.0%) missing valuesMissing
무등급 has 11 (44.0%) missing valuesMissing
상품명 has unique valuesUnique
15등급 has 1 (4.0%) zerosZeros

Reproduction

Analysis started2024-04-06 08:18:28.408309
Analysis finished2024-04-06 08:19:20.537488
Duration52.13 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상품명
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2024-04-06T17:19:20.839463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length9.24
Min length4

Characters and Unicode

Total characters231
Distinct characters68
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st rowPF보증
2nd row기금건설자금대출보증(주택,준주택)
3rd row도시재생PF
4th row도심주택 특약보증
5th row리모델링사업비보증
ValueCountFrequency (%)
pf보증 1
 
3.8%
기금건설자금대출보증(주택,준주택 1
 
3.8%
하자보수보증 1
 
3.8%
하도급대금지급보증 1
 
3.8%
주택임대보증 1
 
3.8%
주택분양보증 1
 
3.8%
주상복합주택분양보증 1
 
3.8%
조합주택시공보증 1
 
3.8%
조합사업비대출보증 1
 
3.8%
임대주택매입자금보증 1
 
3.8%
Other values (16) 16
61.5%
2024-04-06T17:19:21.587580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
27
 
11.7%
26
 
11.3%
13
 
5.6%
9
 
3.9%
9
 
3.9%
9
 
3.9%
8
 
3.5%
7
 
3.0%
7
 
3.0%
5
 
2.2%
Other values (58) 111
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 216
93.5%
Uppercase Letter 6
 
2.6%
Close Punctuation 3
 
1.3%
Open Punctuation 3
 
1.3%
Other Punctuation 2
 
0.9%
Space Separator 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
27
 
12.5%
26
 
12.0%
13
 
6.0%
9
 
4.2%
9
 
4.2%
9
 
4.2%
8
 
3.7%
7
 
3.2%
7
 
3.2%
5
 
2.3%
Other values (51) 96
44.4%
Uppercase Letter
ValueCountFrequency (%)
P 3
50.0%
F 3
50.0%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
. 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 216
93.5%
Common 9
 
3.9%
Latin 6
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
27
 
12.5%
26
 
12.0%
13
 
6.0%
9
 
4.2%
9
 
4.2%
9
 
4.2%
8
 
3.7%
7
 
3.2%
7
 
3.2%
5
 
2.3%
Other values (51) 96
44.4%
Common
ValueCountFrequency (%)
) 3
33.3%
( 3
33.3%
, 1
 
11.1%
1
 
11.1%
. 1
 
11.1%
Latin
ValueCountFrequency (%)
P 3
50.0%
F 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 216
93.5%
ASCII 15
 
6.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
27
 
12.5%
26
 
12.0%
13
 
6.0%
9
 
4.2%
9
 
4.2%
9
 
4.2%
8
 
3.7%
7
 
3.2%
7
 
3.2%
5
 
2.3%
Other values (51) 96
44.4%
ASCII
ValueCountFrequency (%)
P 3
20.0%
) 3
20.0%
( 3
20.0%
F 3
20.0%
, 1
 
6.7%
1
 
6.7%
. 1
 
6.7%

1등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct11
Distinct (%)100.0%
Missing14
Missing (%)56.0%
Infinite0
Infinite (%)0.0%
Mean1.9605024
Minimum0.00048311
Maximum9.5056232
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-04-06T17:19:21.824782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00048311
5-th percentile0.002313155
Q10.031111425
median0.11406461
Q32.3996303
95-th percentile8.1724299
Maximum9.5056232
Range9.5051401
Interquartile range (IQR)2.3685189

Descriptive statistics

Standard deviation3.4082519
Coefficient of variation (CV)1.7384585
Kurtosis1.2109576
Mean1.9605024
Median Absolute Deviation (MAD)0.10409011
Skewness1.5760451
Sum21.565526
Variance11.616181
MonotonicityNot monotonic
2024-04-06T17:19:22.025245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.10664556 1
 
4.0%
0.19197856 1
 
4.0%
0.00048311 1
 
4.0%
0.0099745 1
 
4.0%
0.11406461 1
 
4.0%
6.83923653 1
 
4.0%
0.0041432 1
 
4.0%
0.05224835 1
 
4.0%
0.13384645 1
 
4.0%
4.60728205 1
 
4.0%
(Missing) 14
56.0%
ValueCountFrequency (%)
0.00048311 1
4.0%
0.0041432 1
4.0%
0.0099745 1
4.0%
0.05224835 1
4.0%
0.10664556 1
4.0%
0.11406461 1
4.0%
0.13384645 1
4.0%
0.19197856 1
4.0%
4.60728205 1
4.0%
6.83923653 1
4.0%
ValueCountFrequency (%)
9.50562323 1
4.0%
6.83923653 1
4.0%
4.60728205 1
4.0%
0.19197856 1
4.0%
0.13384645 1
4.0%
0.11406461 1
4.0%
0.10664556 1
4.0%
0.05224835 1
4.0%
0.0099745 1
4.0%
0.0041432 1
4.0%

2등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct12
Distinct (%)100.0%
Missing13
Missing (%)52.0%
Infinite0
Infinite (%)0.0%
Mean1.3402221
Minimum0.00019723
Maximum6.7926082
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-04-06T17:19:22.225941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00019723
5-th percentile0.0019493485
Q10.00849963
median0.10696186
Q31.0310565
95-th percentile6.1131651
Maximum6.7926082
Range6.792411
Interquartile range (IQR)1.0225569

Descriptive statistics

Standard deviation2.4059764
Coefficient of variation (CV)1.7952073
Kurtosis1.7385344
Mean1.3402221
Median Absolute Deviation (MAD)0.1051718
Skewness1.7435927
Sum16.082665
Variance5.7887224
MonotonicityNot monotonic
2024-04-06T17:19:22.493728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0.435386 1
 
4.0%
0.00019723 1
 
4.0%
0.00814428 1
 
4.0%
0.11462745 1
 
4.0%
0.00861808 1
 
4.0%
6.79260825 1
 
4.0%
0.0033829 1
 
4.0%
0.09929627 1
 
4.0%
0.23071577 1
 
4.0%
2.8180681 1
 
4.0%
Other values (2) 2
 
8.0%
(Missing) 13
52.0%
ValueCountFrequency (%)
0.00019723 1
4.0%
0.0033829 1
4.0%
0.00814428 1
4.0%
0.00861808 1
4.0%
0.01436347 1
4.0%
0.09929627 1
4.0%
0.11462745 1
4.0%
0.23071577 1
4.0%
0.435386 1
4.0%
2.8180681 1
4.0%
ValueCountFrequency (%)
6.79260825 1
4.0%
5.55725704 1
4.0%
2.8180681 1
4.0%
0.435386 1
4.0%
0.23071577 1
4.0%
0.11462745 1
4.0%
0.09929627 1
4.0%
0.01436347 1
4.0%
0.00861808 1
4.0%
0.00814428 1
4.0%

3등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct13
Distinct (%)100.0%
Missing12
Missing (%)48.0%
Infinite0
Infinite (%)0.0%
Mean3.2715598
Minimum0.00150277
Maximum32.046105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-04-06T17:19:22.722167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00150277
5-th percentile0.00374386
Q10.0096663
median0.0681927
Q30.60324289
95-th percentile17.359991
Maximum32.046105
Range32.044603
Interquartile range (IQR)0.59357659

Descriptive statistics

Standard deviation8.8879648
Coefficient of variation (CV)2.7167362
Kurtosis11.249031
Mean3.2715598
Median Absolute Deviation (MAD)0.06668993
Skewness3.3086814
Sum42.530277
Variance78.995919
MonotonicityNot monotonic
2024-04-06T17:19:22.927423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0.03554447 1
 
4.0%
0.00523792 1
 
4.0%
0.00150277 1
 
4.0%
0.00924492 1
 
4.0%
1.48453492 1
 
4.0%
0.00997338 1
 
4.0%
0.47521508 1
 
4.0%
32.04610543 1
 
4.0%
0.0096663 1
 
4.0%
0.0681927 1
 
4.0%
Other values (3) 3
 
12.0%
(Missing) 12
48.0%
ValueCountFrequency (%)
0.00150277 1
4.0%
0.00523792 1
4.0%
0.00924492 1
4.0%
0.0096663 1
4.0%
0.00997338 1
4.0%
0.03554447 1
4.0%
0.0681927 1
4.0%
0.21256847 1
4.0%
0.47521508 1
4.0%
0.60324289 1
4.0%
ValueCountFrequency (%)
32.04610543 1
4.0%
7.56924823 1
4.0%
1.48453492 1
4.0%
0.60324289 1
4.0%
0.47521508 1
4.0%
0.21256847 1
4.0%
0.0681927 1
4.0%
0.03554447 1
4.0%
0.00997338 1
4.0%
0.0096663 1
4.0%

4등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct11
Distinct (%)100.0%
Missing14
Missing (%)56.0%
Infinite0
Infinite (%)0.0%
Mean15.603969
Minimum0.0003067
Maximum147.53015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-04-06T17:19:23.142665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0003067
5-th percentile0.00693765
Q10.02086272
median0.28869149
Q34.8099169
95-th percentile80.458586
Maximum147.53015
Range147.52984
Interquartile range (IQR)4.7890541

Descriptive statistics

Standard deviation43.978123
Coefficient of variation (CV)2.8183933
Kurtosis10.701508
Mean15.603969
Median Absolute Deviation (MAD)0.28838479
Skewness3.2573654
Sum171.64366
Variance1934.0753
MonotonicityNot monotonic
2024-04-06T17:19:23.381577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.72536475 1
 
4.0%
0.01963232 1
 
4.0%
0.0003067 1
 
4.0%
0.0135686 1
 
4.0%
0.037001 1
 
4.0%
147.530149 1
 
4.0%
0.02209312 1
 
4.0%
0.28869149 1
 
4.0%
1.07922183 1
 
4.0%
8.5406119 1
 
4.0%
(Missing) 14
56.0%
ValueCountFrequency (%)
0.0003067 1
4.0%
0.0135686 1
4.0%
0.01963232 1
4.0%
0.02209312 1
4.0%
0.037001 1
4.0%
0.28869149 1
4.0%
0.72536475 1
4.0%
1.07922183 1
4.0%
8.5406119 1
4.0%
13.38702294 1
4.0%
ValueCountFrequency (%)
147.530149 1
4.0%
13.38702294 1
4.0%
8.5406119 1
4.0%
1.07922183 1
4.0%
0.72536475 1
4.0%
0.28869149 1
4.0%
0.037001 1
4.0%
0.02209312 1
4.0%
0.01963232 1
4.0%
0.0135686 1
4.0%

5등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct11
Distinct (%)100.0%
Missing14
Missing (%)56.0%
Infinite0
Infinite (%)0.0%
Mean1.580985
Minimum0.00216156
Maximum13.418164
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-04-06T17:19:23.608223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00216156
5-th percentile0.00247112
Q10.038645905
median0.14167608
Q30.6218599
95-th percentile7.8021865
Maximum13.418164
Range13.416003
Interquartile range (IQR)0.583214

Descriptive statistics

Standard deviation3.9773282
Coefficient of variation (CV)2.515728
Kurtosis10.244908
Mean1.580985
Median Absolute Deviation (MAD)0.1388954
Skewness3.1723892
Sum17.390835
Variance15.81914
MonotonicityNot monotonic
2024-04-06T17:19:23.830833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.57264794 1
 
4.0%
0.21251411 1
 
4.0%
0.00216156 1
 
4.0%
0.0669436 1
 
4.0%
2.18620872 1
 
4.0%
0.14167608 1
 
4.0%
0.67107187 1
 
4.0%
0.00278068 1
 
4.0%
0.10631775 1
 
4.0%
0.01034821 1
 
4.0%
(Missing) 14
56.0%
ValueCountFrequency (%)
0.00216156 1
4.0%
0.00278068 1
4.0%
0.01034821 1
4.0%
0.0669436 1
4.0%
0.10631775 1
4.0%
0.14167608 1
4.0%
0.21251411 1
4.0%
0.57264794 1
4.0%
0.67107187 1
4.0%
2.18620872 1
4.0%
ValueCountFrequency (%)
13.41816434 1
4.0%
2.18620872 1
4.0%
0.67107187 1
4.0%
0.57264794 1
4.0%
0.21251411 1
4.0%
0.14167608 1
4.0%
0.10631775 1
4.0%
0.0669436 1
4.0%
0.01034821 1
4.0%
0.00278068 1
4.0%

6등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct13
Distinct (%)100.0%
Missing12
Missing (%)48.0%
Infinite0
Infinite (%)0.0%
Mean2.0170954
Minimum0.0013262
Maximum8.051145
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-04-06T17:19:24.051266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0013262
5-th percentile0.002072792
Q10.01903705
median0.0998451
Q32.3423528
95-th percentile7.4990894
Maximum8.051145
Range8.0498188
Interquartile range (IQR)2.3233157

Descriptive statistics

Standard deviation3.1257118
Coefficient of variation (CV)1.5496103
Kurtosis-0.062934429
Mean2.0170954
Median Absolute Deviation (MAD)0.0985189
Skewness1.3080445
Sum26.222241
Variance9.7700745
MonotonicityNot monotonic
2024-04-06T17:19:24.285674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
8.05114497 1
 
4.0%
6.85138195 1
 
4.0%
2.34235278 1
 
4.0%
0.02897551 1
 
4.0%
0.0013262 1
 
4.0%
0.01903705 1
 
4.0%
0.0684563 1
 
4.0%
1.40308996 1
 
4.0%
0.2195956 1
 
4.0%
0.00341223 1
 
4.0%
Other values (3) 3
 
12.0%
(Missing) 12
48.0%
ValueCountFrequency (%)
0.0013262 1
4.0%
0.00257052 1
4.0%
0.00341223 1
4.0%
0.01903705 1
4.0%
0.02897551 1
4.0%
0.0684563 1
4.0%
0.0998451 1
4.0%
0.2195956 1
4.0%
1.40308996 1
4.0%
2.34235278 1
4.0%
ValueCountFrequency (%)
8.05114497 1
4.0%
7.13105235 1
4.0%
6.85138195 1
4.0%
2.34235278 1
4.0%
1.40308996 1
4.0%
0.2195956 1
4.0%
0.0998451 1
4.0%
0.0684563 1
4.0%
0.02897551 1
4.0%
0.01903705 1
4.0%

7등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct10
Distinct (%)100.0%
Missing15
Missing (%)60.0%
Infinite0
Infinite (%)0.0%
Mean1.7036803
Minimum0.0009037
Maximum12.476484
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-04-06T17:19:24.501295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0009037
5-th percentile0.003008089
Q10.02339087
median0.10804694
Q30.93952314
95-th percentile8.0740762
Maximum12.476484
Range12.47558
Interquartile range (IQR)0.91613227

Descriptive statistics

Standard deviation3.8779006
Coefficient of variation (CV)2.2761903
Kurtosis8.7059557
Mean1.7036803
Median Absolute Deviation (MAD)0.10480503
Skewness2.9101012
Sum17.036803
Variance15.038113
MonotonicityNot monotonic
2024-04-06T17:19:24.734625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0.47877744 1
 
4.0%
2.69335567 1
 
4.0%
0.01052998 1
 
4.0%
0.0009037 1
 
4.0%
0.1119496 1
 
4.0%
1.09310504 1
 
4.0%
0.00558012 1
 
4.0%
0.10414428 1
 
4.0%
0.06197354 1
 
4.0%
12.47648399 1
 
4.0%
(Missing) 15
60.0%
ValueCountFrequency (%)
0.0009037 1
4.0%
0.00558012 1
4.0%
0.01052998 1
4.0%
0.06197354 1
4.0%
0.10414428 1
4.0%
0.1119496 1
4.0%
0.47877744 1
4.0%
1.09310504 1
4.0%
2.69335567 1
4.0%
12.47648399 1
4.0%
ValueCountFrequency (%)
12.47648399 1
4.0%
2.69335567 1
4.0%
1.09310504 1
4.0%
0.47877744 1
4.0%
0.1119496 1
4.0%
0.10414428 1
4.0%
0.06197354 1
4.0%
0.01052998 1
4.0%
0.00558012 1
4.0%
0.0009037 1
4.0%

8등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct18
Distinct (%)100.0%
Missing7
Missing (%)28.0%
Infinite0
Infinite (%)0.0%
Mean5.0092903
Minimum0.00280686
Maximum49.531106
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-04-06T17:19:24.980694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00280686
5-th percentile0.003341493
Q10.051510267
median0.30654505
Q31.5306281
95-th percentile32.499007
Maximum49.531106
Range49.528299
Interquartile range (IQR)1.4791179

Descriptive statistics

Standard deviation13.047509
Coefficient of variation (CV)2.6046621
Kurtosis8.8111794
Mean5.0092903
Median Absolute Deviation (MAD)0.30342369
Skewness3.0233077
Sum90.167226
Variance170.23748
MonotonicityNot monotonic
2024-04-06T17:19:25.250916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1.51044973 1
 
4.0%
0.3227457 1
 
4.0%
29.49334253 1
 
4.0%
2.3921148 1
 
4.0%
0.29034439 1
 
4.0%
0.03120744 1
 
4.0%
0.0190035 1
 
4.0%
49.53110561 1
 
4.0%
3.32624745 1
 
4.0%
0.61638688 1
 
4.0%
Other values (8) 8
32.0%
(Missing) 7
28.0%
ValueCountFrequency (%)
0.00280686 1
4.0%
0.00343584 1
4.0%
0.0190035 1
4.0%
0.02581965 1
4.0%
0.03120744 1
4.0%
0.11241875 1
4.0%
0.12810084 1
4.0%
0.13555318 1
4.0%
0.29034439 1
4.0%
0.3227457 1
4.0%
ValueCountFrequency (%)
49.53110561 1
4.0%
29.49334253 1
4.0%
3.32624745 1
4.0%
2.3921148 1
4.0%
1.53735425 1
4.0%
1.51044973 1
4.0%
0.6887881 1
4.0%
0.61638688 1
4.0%
0.3227457 1
4.0%
0.29034439 1
4.0%

9등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct15
Distinct (%)100.0%
Missing10
Missing (%)40.0%
Infinite0
Infinite (%)0.0%
Mean21.885011
Minimum0.00265538
Maximum262.78647
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-04-06T17:19:25.487658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00265538
5-th percentile0.010641582
Q10.044143645
median0.14389403
Q31.2257809
95-th percentile108.01023
Maximum262.78647
Range262.78381
Interquartile range (IQR)1.1816373

Descriptive statistics

Standard deviation67.616062
Coefficient of variation (CV)3.089606
Kurtosis13.951079
Mean21.885011
Median Absolute Deviation (MAD)0.14123865
Skewness3.6972361
Sum328.27517
Variance4571.9318
MonotonicityNot monotonic
2024-04-06T17:19:25.730384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1.11907905 1
 
4.0%
0.14389403 1
 
4.0%
0.01406424 1
 
4.0%
0.0791114 1
 
4.0%
0.00265538 1
 
4.0%
0.02990484 1
 
4.0%
0.43733936 1
 
4.0%
0.14240052 1
 
4.0%
262.7864678 1
 
4.0%
0.05838245 1
 
4.0%
Other values (5) 5
20.0%
(Missing) 10
40.0%
ValueCountFrequency (%)
0.00265538 1
4.0%
0.01406424 1
4.0%
0.02637046 1
4.0%
0.02990484 1
4.0%
0.05838245 1
4.0%
0.0791114 1
4.0%
0.14240052 1
4.0%
0.14389403 1
4.0%
0.43733936 1
4.0%
0.57599456 1
4.0%
ValueCountFrequency (%)
262.7864678 1
4.0%
41.67756198 1
4.0%
19.84946305 1
4.0%
1.33248274 1
4.0%
1.11907905 1
4.0%
0.57599456 1
4.0%
0.43733936 1
4.0%
0.14389403 1
4.0%
0.14240052 1
4.0%
0.0791114 1
4.0%

10등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct13
Distinct (%)100.0%
Missing12
Missing (%)48.0%
Infinite0
Infinite (%)0.0%
Mean3.6362474
Minimum0.00039439
Maximum26.691099
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-04-06T17:19:25.919699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00039439
5-th percentile0.00390925
Q10.01420524
median0.18802016
Q31.4104654
95-th percentile19.670304
Maximum26.691099
Range26.690705
Interquartile range (IQR)1.3962601

Descriptive statistics

Standard deviation8.0318983
Coefficient of variation (CV)2.2088427
Kurtosis6.0275912
Mean3.6362474
Median Absolute Deviation (MAD)0.18176767
Skewness2.5337561
Sum47.271216
Variance64.51139
MonotonicityNot monotonic
2024-04-06T17:19:26.193587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1.10999299 1
 
4.0%
1.41046537 1
 
4.0%
0.00625249 1
 
4.0%
0.00039439 1
 
4.0%
0.01221378 1
 
4.0%
0.18802016 1
 
4.0%
26.69109909 1
 
4.0%
0.01420524 1
 
4.0%
0.18682722 1
 
4.0%
0.28584287 1
 
4.0%
Other values (3) 3
 
12.0%
(Missing) 12
48.0%
ValueCountFrequency (%)
0.00039439 1
4.0%
0.00625249 1
4.0%
0.01221378 1
4.0%
0.01420524 1
4.0%
0.02154052 1
4.0%
0.18682722 1
4.0%
0.18802016 1
4.0%
0.28584287 1
4.0%
1.10999299 1
4.0%
1.41046537 1
4.0%
ValueCountFrequency (%)
26.69109909 1
4.0%
14.9897747 1
4.0%
2.35458682 1
4.0%
1.41046537 1
4.0%
1.10999299 1
4.0%
0.28584287 1
4.0%
0.18802016 1
4.0%
0.18682722 1
4.0%
0.02154052 1
4.0%
0.01420524 1
4.0%

11등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct6
Distinct (%)100.0%
Missing19
Missing (%)76.0%
Infinite0
Infinite (%)0.0%
Mean5.5260666
Minimum0.00119748
Maximum30.264349
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-04-06T17:19:26.390667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00119748
5-th percentile0.04898987
Q10.23698915
median0.6315419
Q31.2996086
95-th percentile23.057112
Maximum30.264349
Range30.263152
Interquartile range (IQR)1.0626194

Descriptive statistics

Standard deviation12.130436
Coefficient of variation (CV)2.1951302
Kurtosis5.9610282
Mean5.5260666
Median Absolute Deviation (MAD)0.53475964
Skewness2.4393893
Sum33.156399
Variance147.14747
MonotonicityNot monotonic
2024-04-06T17:19:26.602617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0.00119748 1
 
4.0%
0.37085549 1
 
4.0%
1.43540202 1
 
4.0%
0.89222832 1
 
4.0%
0.19236704 1
 
4.0%
30.26434913 1
 
4.0%
(Missing) 19
76.0%
ValueCountFrequency (%)
0.00119748 1
4.0%
0.19236704 1
4.0%
0.37085549 1
4.0%
0.89222832 1
4.0%
1.43540202 1
4.0%
30.26434913 1
4.0%
ValueCountFrequency (%)
30.26434913 1
4.0%
1.43540202 1
4.0%
0.89222832 1
4.0%
0.37085549 1
4.0%
0.19236704 1
4.0%
0.00119748 1
4.0%

12등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct11
Distinct (%)100.0%
Missing14
Missing (%)56.0%
Infinite0
Infinite (%)0.0%
Mean4.1049628
Minimum0.00344016
Maximum30.973084
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-04-06T17:19:27.236686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00344016
5-th percentile0.010570915
Q10.11248305
median0.19326528
Q32.237944
95-th percentile19.880619
Maximum30.973084
Range30.969644
Interquartile range (IQR)2.1254609

Descriptive statistics

Standard deviation9.3205717
Coefficient of variation (CV)2.2705618
Kurtosis8.5521621
Mean4.1049628
Median Absolute Deviation (MAD)0.15093935
Skewness2.8686683
Sum45.154591
Variance86.873058
MonotonicityNot monotonic
2024-04-06T17:19:27.447403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.32545911 1
 
4.0%
0.29293854 1
 
4.0%
0.19326528 1
 
4.0%
0.00344016 1
 
4.0%
0.04232593 1
 
4.0%
0.18264018 1
 
4.0%
4.15042887 1
 
4.0%
8.78815402 1
 
4.0%
0.01770167 1
 
4.0%
0.18515302 1
 
4.0%
(Missing) 14
56.0%
ValueCountFrequency (%)
0.00344016 1
4.0%
0.01770167 1
4.0%
0.04232593 1
4.0%
0.18264018 1
4.0%
0.18515302 1
4.0%
0.19326528 1
4.0%
0.29293854 1
4.0%
0.32545911 1
4.0%
4.15042887 1
4.0%
8.78815402 1
4.0%
ValueCountFrequency (%)
30.9730841 1
4.0%
8.78815402 1
4.0%
4.15042887 1
4.0%
0.32545911 1
4.0%
0.29293854 1
4.0%
0.19326528 1
4.0%
0.18515302 1
4.0%
0.18264018 1
4.0%
0.04232593 1
4.0%
0.01770167 1
4.0%

13등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct10
Distinct (%)100.0%
Missing15
Missing (%)60.0%
Infinite0
Infinite (%)0.0%
Mean5.702222
Minimum0.00207341
Maximum20.720617
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-04-06T17:19:27.657521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00207341
5-th percentile0.0022283315
Q10.062014418
median0.48146512
Q311.610078
95-th percentile18.000829
Maximum20.720617
Range20.718543
Interquartile range (IQR)11.548063

Descriptive statistics

Standard deviation7.7824215
Coefficient of variation (CV)1.3648051
Kurtosis-0.42580806
Mean5.702222
Median Absolute Deviation (MAD)0.47921958
Skewness1.0277861
Sum57.02222
Variance60.566084
MonotonicityNot monotonic
2024-04-06T17:19:27.871379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
14.67664422 1
 
4.0%
12.96994004 1
 
4.0%
0.2641012 1
 
4.0%
0.00241768 1
 
4.0%
0.69882904 1
 
4.0%
7.53049039 1
 
4.0%
0.00207341 1
 
4.0%
0.11163312 1
 
4.0%
0.04547485 1
 
4.0%
20.72061651 1
 
4.0%
(Missing) 15
60.0%
ValueCountFrequency (%)
0.00207341 1
4.0%
0.00241768 1
4.0%
0.04547485 1
4.0%
0.11163312 1
4.0%
0.2641012 1
4.0%
0.69882904 1
4.0%
7.53049039 1
4.0%
12.96994004 1
4.0%
14.67664422 1
4.0%
20.72061651 1
4.0%
ValueCountFrequency (%)
20.72061651 1
4.0%
14.67664422 1
4.0%
12.96994004 1
4.0%
7.53049039 1
4.0%
0.69882904 1
4.0%
0.2641012 1
4.0%
0.11163312 1
4.0%
0.04547485 1
4.0%
0.00241768 1
4.0%
0.00207341 1
4.0%

14등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct10
Distinct (%)100.0%
Missing15
Missing (%)60.0%
Infinite0
Infinite (%)0.0%
Mean2.2698545
Minimum0.00066017
Maximum9.7375844
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-04-06T17:19:28.118031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00066017
5-th percentile0.002656055
Q10.017694392
median0.26098338
Q34.1038794
95-th percentile8.1594089
Maximum9.7375844
Range9.7369243
Interquartile range (IQR)4.086185

Descriptive statistics

Standard deviation3.4905604
Coefficient of variation (CV)1.5377903
Kurtosis0.89877438
Mean2.2698545
Median Absolute Deviation (MAD)0.25810555
Skewness1.4284055
Sum22.698545
Variance12.184012
MonotonicityNot monotonic
2024-04-06T17:19:28.337933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0.4197408 1
 
4.0%
0.00066017 1
 
4.0%
0.10222595 1
 
4.0%
5.12568573 1
 
4.0%
1.03846032 1
 
4.0%
6.23052759 1
 
4.0%
0.00509547 1
 
4.0%
0.0161064 1
 
4.0%
0.02245837 1
 
4.0%
9.73758443 1
 
4.0%
(Missing) 15
60.0%
ValueCountFrequency (%)
0.00066017 1
4.0%
0.00509547 1
4.0%
0.0161064 1
4.0%
0.02245837 1
4.0%
0.10222595 1
4.0%
0.4197408 1
4.0%
1.03846032 1
4.0%
5.12568573 1
4.0%
6.23052759 1
4.0%
9.73758443 1
4.0%
ValueCountFrequency (%)
9.73758443 1
4.0%
6.23052759 1
4.0%
5.12568573 1
4.0%
1.03846032 1
4.0%
0.4197408 1
4.0%
0.10222595 1
4.0%
0.02245837 1
4.0%
0.0161064 1
4.0%
0.00509547 1
4.0%
0.00066017 1
4.0%

15등급
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct13
Distinct (%)100.0%
Missing12
Missing (%)48.0%
Infinite0
Infinite (%)0.0%
Mean8.3987521
Minimum0
Maximum63.778165
Zeros1
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-04-06T17:19:28.569422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.04661586
Q10.65465007
median2.3784812
Q35.0071001
95-th percentile38.866128
Maximum63.778165
Range63.778165
Interquartile range (IQR)4.35245

Descriptive statistics

Standard deviation17.652508
Coefficient of variation (CV)2.1018013
Kurtosis9.517994
Mean8.3987521
Median Absolute Deviation (MAD)1.9550577
Skewness3.0258684
Sum109.18378
Variance311.61104
MonotonicityNot monotonic
2024-04-06T17:19:28.768834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0.0 1
 
4.0%
2.7 1
 
4.0%
1.35 1
 
4.0%
5.00710008 1
 
4.0%
0.65465007 1
 
4.0%
22.25810245 1
 
4.0%
3.0 1
 
4.0%
0.0776931 1
 
4.0%
1.01583354 1
 
4.0%
2.37848124 1
 
4.0%
Other values (3) 3
 
12.0%
(Missing) 12
48.0%
ValueCountFrequency (%)
0.0 1
4.0%
0.0776931 1
4.0%
0.42342352 1
4.0%
0.65465007 1
4.0%
1.01583354 1
4.0%
1.35 1
4.0%
2.37848124 1
4.0%
2.7 1
4.0%
3.0 1
4.0%
5.00710008 1
4.0%
ValueCountFrequency (%)
63.77816547 1
4.0%
22.25810245 1
4.0%
6.54032817 1
4.0%
5.00710008 1
4.0%
3.0 1
4.0%
2.7 1
4.0%
2.37848124 1
4.0%
1.35 1
4.0%
1.01583354 1
4.0%
0.65465007 1
4.0%

무등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct14
Distinct (%)100.0%
Missing11
Missing (%)44.0%
Infinite0
Infinite (%)0.0%
Mean58.601036
Minimum0.00444164
Maximum532.45244
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-04-06T17:19:28.995703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00444164
5-th percentile0.036218294
Q10.193629
median11.623477
Q339.527398
95-th percentile242.70611
Maximum532.45244
Range532.448
Interquartile range (IQR)39.333769

Descriptive statistics

Standard deviation139.48446
Coefficient of variation (CV)2.3802388
Kurtosis12.48528
Mean58.601036
Median Absolute Deviation (MAD)11.55096
Skewness3.4705287
Sum820.4145
Variance19455.914
MonotonicityNot monotonic
2024-04-06T17:19:29.250946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
7.94266076 1
 
4.0%
86.68885187 1
 
4.0%
0.19407952 1
 
4.0%
79.15042217 1
 
4.0%
15.30429239 1
 
4.0%
0.00444164 1
 
4.0%
0.09170482 1
 
4.0%
36.82554587 1
 
4.0%
532.4524438 1
 
4.0%
0.0533288 1
 
4.0%
Other values (4) 4
 
16.0%
(Missing) 11
44.0%
ValueCountFrequency (%)
0.00444164 1
4.0%
0.0533288 1
4.0%
0.09170482 1
4.0%
0.19347883 1
4.0%
0.19407952 1
4.0%
0.33384599 1
4.0%
7.94266076 1
4.0%
15.30429239 1
4.0%
20.75139217 1
4.0%
36.82554587 1
4.0%
ValueCountFrequency (%)
532.4524438 1
4.0%
86.68885187 1
4.0%
79.15042217 1
4.0%
40.42801584 1
4.0%
36.82554587 1
4.0%
20.75139217 1
4.0%
15.30429239 1
4.0%
7.94266076 1
4.0%
0.33384599 1
4.0%
0.19407952 1
4.0%

Interactions

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2024-04-06T17:19:18.604293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:31.849130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:34.733134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:37.814729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:40.600198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:44.129230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:47.209148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:50.099900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:53.180462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:55.991669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:58.789743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:19:02.341228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:19:05.950627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:19:09.035728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:19:11.973730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:19:15.074136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:19:18.777467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:32.000561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:34.952488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:37.972473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:40.759869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:44.298005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:47.384449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:50.256203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:53.418846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:56.137727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:58.936426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:19:02.487784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:19:06.235980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:19:09.227432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:19:12.154545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:19:15.269505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:19:18.956965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:32.143857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:35.137731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:38.142863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:40.934600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:44.455240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:47.584169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:50.404420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:53.568897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:56.302425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:59.109347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:19:02.740999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:19:06.395016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:19:09.441489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:19:12.312660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:19:15.466474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:19:19.124830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:32.308110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:35.392422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:38.351300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:41.490476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:44.618320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:47.740397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:50.583906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:53.745913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:56.549673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:18:59.382492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:19:02.935591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:19:06.573274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:19:09.621700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:19:12.497441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:19:16.086008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:19:29.449818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상품명1등급2등급3등급4등급5등급6등급7등급8등급9등급10등급11등급12등급13등급14등급15등급무등급
상품명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
1등급1.0001.0001.0001.0001.0000.8880.0001.0001.0001.0001.0001.0001.0001.0000.9490.9601.000
2등급1.0001.0001.0001.0001.0000.8960.5310.3961.0001.0001.0001.0001.0001.0000.7230.9561.000
3등급1.0001.0001.0001.0001.0000.8880.5520.3961.0001.0001.0001.0001.0001.0001.0000.5311.000
4등급1.0001.0001.0001.0001.0000.0000.000NaN1.0001.0001.0000.0001.000NaN1.0000.0000.455
5등급1.0000.8880.8960.8880.0001.0001.0001.0000.9080.9030.8881.0001.0001.0001.0001.0000.000
6등급1.0000.0000.5310.5520.0001.0001.0000.5010.0000.0000.0001.0000.8781.0000.9490.7290.000
7등급1.0001.0000.3960.396NaN1.0000.5011.0001.0001.0001.0000.0000.8881.0001.0000.888NaN
8등급1.0001.0001.0001.0001.0000.9080.0001.0001.0001.0001.0001.0001.0001.0001.0000.5790.911
9등급1.0001.0001.0001.0001.0000.9030.0001.0001.0001.0001.0001.0001.0001.0001.0000.5671.000
10등급1.0001.0001.0001.0001.0000.8880.0001.0001.0001.0001.0001.0001.0001.0001.0000.5670.908
11등급1.0001.0001.0001.0000.0001.0001.0000.0001.0001.0001.0001.0001.0001.0001.0001.0000.000
12등급1.0001.0001.0001.0001.0001.0000.8780.8881.0001.0001.0001.0001.0001.0001.0001.0001.000
13등급1.0001.0001.0001.000NaN1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000NaN
14등급1.0000.9490.7231.0001.0001.0000.9491.0001.0001.0001.0001.0001.0001.0001.0000.9401.000
15등급1.0000.9600.9560.5310.0001.0000.7290.8880.5790.5670.5671.0001.0001.0000.9401.0000.000
무등급1.0001.0001.0001.0000.4550.0000.000NaN0.9111.0000.9080.0001.000NaN1.0000.0001.000
2024-04-06T17:19:29.804985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1등급2등급3등급4등급5등급6등급7등급8등급9등급10등급11등급12등급13등급14등급15등급무등급
1등급1.0000.9520.9640.9390.8100.6120.8170.8640.8640.9550.7140.8670.7330.8100.7940.915
2등급0.9521.0000.9150.9640.7500.7000.7860.8880.9370.9910.6000.9050.8100.7330.5500.950
3등급0.9640.9151.0000.9090.8570.6120.7860.8910.9030.9030.7710.9500.6900.8570.8330.983
4등급0.9390.9640.9091.0000.6670.5330.5710.8731.0000.9760.6000.8570.5710.7140.5330.883
5등급0.8100.7500.8570.6671.0000.9150.9640.8730.6480.7141.0000.9520.9050.9670.8570.850
6등급0.6120.7000.6120.5330.9151.0000.8670.7620.5270.6971.0000.8180.9150.8810.2610.758
7등급0.8170.7860.7860.5710.9640.8671.0000.9150.6120.8001.0000.9050.9331.0000.6430.881
8등급0.8640.8880.8910.8730.8730.7620.9151.0000.7930.8850.7710.9640.8910.8420.4760.783
9등급0.8640.9370.9031.0000.6480.5270.6120.7931.0000.8950.6000.8420.5270.6830.5640.864
10등급0.9550.9910.9030.9760.7140.6970.8000.8850.8951.0000.6000.8500.7830.7140.3910.609
11등급0.7140.6000.7710.6001.0001.0001.0000.7710.6000.6001.0000.8861.0000.9430.9000.771
12등급0.8670.9050.9500.8570.9520.8180.9050.9640.8420.8500.8861.0000.8830.9640.7170.967
13등급0.7330.8100.6900.5710.9050.9150.9330.8910.5270.7831.0000.8831.0000.9430.3670.817
14등급0.8100.7330.8570.7140.9670.8811.0000.8420.6830.7140.9430.9640.9431.0000.7500.905
15등급0.7940.5500.8330.5330.8570.2610.6430.4760.5640.3910.9000.7170.3670.7501.0000.855
무등급0.9150.9500.9830.8830.8500.7580.8810.7830.8640.6090.7710.9670.8170.9050.8551.000

Missing values

2024-04-06T17:19:19.382210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:19:19.783709image/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.
2024-04-06T17:19:20.150731image/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

상품명1등급2등급3등급4등급5등급6등급7등급8등급9등급10등급11등급12등급13등급14등급15등급무등급
0PF보증0.1066460.4353860.0355440.725365<NA>8.0511450.4787773.3262471.1190791.109993<NA>0.32545914.676644<NA>0.0<NA>
1기금건설자금대출보증(주택,준주택)0.191979<NA><NA><NA><NA>6.8513822.6933560.6163870.1438941.410465<NA>0.29293912.96994<NA>2.77.942661
2도시재생PF<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3도심주택 특약보증<NA><NA><NA><NA>0.5726482.342353<NA>0.688788<NA><NA><NA><NA><NA>0.419741<NA><NA>
4리모델링사업비보증<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>86.688852
5리츠회사채보증<NA><NA><NA><NA><NA><NA>0.010530.025820.014064<NA><NA><NA><NA><NA><NA><NA>
6모기지보증<NA><NA><NA><NA>0.2125140.028976<NA>0.1355530.079111<NA><NA>0.1932650.264101<NA>1.350.19408
7수요자중심형도시재생지원자금보증<NA><NA><NA><NA><NA><NA><NA>0.112419<NA>0.006252<NA><NA><NA><NA>5.007179.150422
8수요자중심형도시재생지원자금특례보증<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>15.304292
9오피스텔분양보증<NA><NA>0.0052380.019632<NA><NA><NA>0.003436<NA><NA><NA><NA><NA><NA><NA><NA>
상품명1등급2등급3등급4등급5등급6등급7등급8등급9등급10등급11등급12등급13등급14등급15등급무등급
15임대보증금보증(사용검사후)0.1140650.1146270.4752150.0370012.1862091.403091.0931051.5373540.4373390.188021.4354024.1504297.530495.12568622.25810236.825546
16임대주택매입자금보증<NA>0.008618<NA><NA>0.141676<NA><NA>1.510450.142401<NA><NA><NA><NA>1.03846<NA><NA>
17조합사업비대출보증6.8392376.79260832.046105147.5301490.6710720.219596<NA>49.531106262.78646826.6910990.8922288.788154<NA>6.2305283.0532.452444
18조합주택시공보증0.0041430.0033830.0096660.0220930.0027810.0034120.005580.0190030.0583820.014205<NA>0.0177020.0020730.0050950.0776930.053329
19주상복합주택분양보증0.0522480.0992960.0681930.2886910.1063180.0998450.1041440.0312070.5759950.186827<NA><NA>0.111633<NA>1.0158340.193479
20주택분양보증0.1338460.2307160.2125681.0792220.0103480.0025710.0619740.2903441.3324830.2858430.1923670.1851530.0454750.0161062.3784810.333846
21주택임대보증<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.423424<NA>
22하도급대금지급보증4.6072822.8180680.6032438.540612<NA><NA><NA>2.39211519.8494632.354587<NA><NA><NA>0.0224586.54032820.751392
23하자보수보증9.5056235.5572577.56924813.38702313.4181647.13105212.47648429.49334341.67756214.98977530.26434930.97308420.7206179.73758463.77816540.428016
24후분양대출보증<NA>0.014363<NA><NA><NA><NA><NA>0.3227460.026370.021541<NA><NA><NA><NA><NA><NA>