Overview

Dataset statistics

Number of variables17
Number of observations25
Missing cells205
Missing cells (%)48.2%
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 : 24.03.29. 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 14 other fieldsHigh correlation
7등급 is highly overall correlated with 1등급 and 14 other fieldsHigh correlation
8등급 is highly overall correlated with 1등급 and 14 other fieldsHigh correlation
9등급 is highly overall correlated with 1등급 and 14 other fieldsHigh correlation
10등급 is highly overall correlated with 1등급 and 14 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 13 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 15 (60.0%) missing valuesMissing
4등급 has 13 (52.0%) missing valuesMissing
5등급 has 14 (56.0%) missing valuesMissing
6등급 has 11 (44.0%) missing valuesMissing
7등급 has 15 (60.0%) missing valuesMissing
8등급 has 7 (28.0%) missing valuesMissing
9등급 has 8 (32.0%) missing valuesMissing
10등급 has 12 (48.0%) missing valuesMissing
11등급 has 18 (72.0%) missing valuesMissing
12등급 has 13 (52.0%) missing valuesMissing
13등급 has 14 (56.0%) 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 started2024-05-04 07:31:07.401454
Analysis finished2024-05-04 07:32:27.287186
Duration1 minute and 19.89 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
2024-05-04T07:32:27.799877image/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%
2024-05-04T07:32:29.029444image/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%
Mean1.2824551
Minimum7.582 × 10-5
Maximum7.3469095
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-05-04T07:32:29.597611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.582 × 10-5
5-th percentile0.002877745
Q10.024633915
median0.09915168
Q31.2956837
95-th percentile5.6028941
Maximum7.3469095
Range7.3468337
Interquartile range (IQR)1.2710498

Descriptive statistics

Standard deviation2.3840719
Coefficient of variation (CV)1.8589906
Kurtosis3.8736815
Mean1.2824551
Median Absolute Deviation (MAD)0.08835666
Skewness2.0466749
Sum14.107006
Variance5.683799
MonotonicityNot monotonic
2024-05-04T07:32:29.972901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.03847281 1
 
4.0%
0.13851408 1
 
4.0%
7.582e-05 1
 
4.0%
0.01079502 1
 
4.0%
0.09915168 1
 
4.0%
2.45285326 1
 
4.0%
0.00567967 1
 
4.0%
0.04381804 1
 
4.0%
0.11185711 1
 
4.0%
3.8588787 1
 
4.0%
(Missing) 14
56.0%
ValueCountFrequency (%)
7.582e-05 1
4.0%
0.00567967 1
4.0%
0.01079502 1
4.0%
0.03847281 1
4.0%
0.04381804 1
4.0%
0.09915168 1
4.0%
0.11185711 1
4.0%
0.13851408 1
4.0%
2.45285326 1
4.0%
3.8588787 1
4.0%
ValueCountFrequency (%)
7.3469095 1
4.0%
3.8588787 1
4.0%
2.45285326 1
4.0%
0.13851408 1
4.0%
0.11185711 1
4.0%
0.09915168 1
4.0%
0.04381804 1
4.0%
0.03847281 1
4.0%
0.01079502 1
4.0%
0.00567967 1
4.0%

2등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct12
Distinct (%)100.0%
Missing13
Missing (%)52.0%
Infinite0
Infinite (%)0.0%
Mean1.0775456
Minimum0.00018573
Maximum5.0658555
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-05-04T07:32:30.467201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00018573
5-th percentile0.0014260185
Q10.0075557475
median0.086040165
Q30.93274002
95-th percentile4.7009639
Maximum5.0658555
Range5.0656698
Interquartile range (IQR)0.92518428

Descriptive statistics

Standard deviation1.8835799
Coefficient of variation (CV)1.7480279
Kurtosis0.89129097
Mean1.0775456
Median Absolute Deviation (MAD)0.081881685
Skewness1.5651278
Sum12.930548
Variance3.5478732
MonotonicityNot monotonic
2024-05-04T07:32:30.844115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0.3141344 1
 
4.0%
0.00018573 1
 
4.0%
0.00587616 1
 
4.0%
0.10963073 1
 
4.0%
0.00811561 1
 
4.0%
5.06585551 1
 
4.0%
0.0024408 1
 
4.0%
0.0624496 1
 
4.0%
0.15736004 1
 
4.0%
2.78855689 1
 
4.0%
Other values (2) 2
 
8.0%
(Missing) 13
52.0%
ValueCountFrequency (%)
0.00018573 1
4.0%
0.0024408 1
4.0%
0.00587616 1
4.0%
0.00811561 1
4.0%
0.01352602 1
4.0%
0.0624496 1
4.0%
0.10963073 1
4.0%
0.15736004 1
4.0%
0.3141344 1
4.0%
2.78855689 1
4.0%
ValueCountFrequency (%)
5.06585551 1
4.0%
4.40241617 1
4.0%
2.78855689 1
4.0%
0.3141344 1
4.0%
0.15736004 1
4.0%
0.10963073 1
4.0%
0.0624496 1
4.0%
0.01352602 1
4.0%
0.00811561 1
4.0%
0.00587616 1
4.0%

3등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct10
Distinct (%)100.0%
Missing15
Missing (%)60.0%
Infinite0
Infinite (%)0.0%
Mean1.8483277
Minimum0.00141518
Maximum12.541789
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-05-04T07:32:31.194612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00141518
5-th percentile0.0028407935
Q10.0096727425
median0.07237559
Q30.50905259
95-th percentile9.0511322
Maximum12.541789
Range12.540374
Interquartile range (IQR)0.49937985

Descriptive statistics

Standard deviation4.0349457
Coefficient of variation (CV)2.183025
Kurtosis6.5485672
Mean1.8483277
Median Absolute Deviation (MAD)0.069376395
Skewness2.551739
Sum18.483277
Variance16.280787
MonotonicityNot monotonic
2024-05-04T07:32:31.681925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0.02564562 1
 
4.0%
0.00141518 1
 
4.0%
0.00719586 1
 
4.0%
0.45439348 1
 
4.0%
12.54178905 1
 
4.0%
0.00458321 1
 
4.0%
0.01710339 1
 
4.0%
0.11910556 1
 
4.0%
0.5272723 1
 
4.0%
4.78477385 1
 
4.0%
(Missing) 15
60.0%
ValueCountFrequency (%)
0.00141518 1
4.0%
0.00458321 1
4.0%
0.00719586 1
4.0%
0.01710339 1
4.0%
0.02564562 1
4.0%
0.11910556 1
4.0%
0.45439348 1
4.0%
0.5272723 1
4.0%
4.78477385 1
4.0%
12.54178905 1
4.0%
ValueCountFrequency (%)
12.54178905 1
4.0%
4.78477385 1
4.0%
0.5272723 1
4.0%
0.45439348 1
4.0%
0.11910556 1
4.0%
0.02564562 1
4.0%
0.01710339 1
4.0%
0.00719586 1
4.0%
0.00458321 1
4.0%
0.00141518 1
4.0%

4등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct12
Distinct (%)100.0%
Missing13
Missing (%)52.0%
Infinite0
Infinite (%)0.0%
Mean11.842213
Minimum0.00028885
Maximum121.32972
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-05-04T07:32:32.192987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00028885
5-th percentile0.0050876165
Q10.01514275
median0.13091169
Q32.5320408
95-th percentile60.846856
Maximum121.32972
Range121.32943
Interquartile range (IQR)2.5168981

Descriptive statistics

Standard deviation34.677145
Coefficient of variation (CV)2.9282657
Kurtosis11.644215
Mean11.842213
Median Absolute Deviation (MAD)0.12626033
Skewness3.3961192
Sum142.10655
Variance1202.5044
MonotonicityNot monotonic
2024-05-04T07:32:32.584515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0.58615928 1
 
4.0%
0.01692705 1
 
4.0%
0.00028885 1
 
4.0%
0.00978985 1
 
4.0%
0.02247981 1
 
4.0%
121.3297225 1
 
4.0%
0.0187059 1
 
4.0%
0.23934357 1
 
4.0%
0.80745772 1
 
4.0%
7.70579008 1
 
4.0%
Other values (2) 2
 
8.0%
(Missing) 13
52.0%
ValueCountFrequency (%)
0.00028885 1
4.0%
0.00901388 1
4.0%
0.00978985 1
4.0%
0.01692705 1
4.0%
0.0187059 1
4.0%
0.02247981 1
4.0%
0.23934357 1
4.0%
0.58615928 1
4.0%
0.80745772 1
4.0%
7.70579008 1
4.0%
ValueCountFrequency (%)
121.3297225 1
4.0%
11.3608752 1
4.0%
7.70579008 1
4.0%
0.80745772 1
4.0%
0.58615928 1
4.0%
0.23934357 1
4.0%
0.02247981 1
4.0%
0.0187059 1
4.0%
0.01692705 1
4.0%
0.00978985 1
4.0%

5등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct11
Distinct (%)100.0%
Missing14
Missing (%)56.0%
Infinite0
Infinite (%)0.0%
Mean1.1790303
Minimum0.00200628
Maximum9.3785068
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-05-04T07:32:32.943863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00200628
5-th percentile0.002020895
Q10.030342715
median0.13341576
Q30.53260207
95-th percentile5.7394207
Maximum9.3785068
Range9.3765005
Interquartile range (IQR)0.50225936

Descriptive statistics

Standard deviation2.7874815
Coefficient of variation (CV)2.3642153
Kurtosis9.5962496
Mean1.1790303
Median Absolute Deviation (MAD)0.13138025
Skewness3.0563872
Sum12.969334
Variance7.7700532
MonotonicityNot monotonic
2024-05-04T07:32:33.408701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.58102046 1
 
4.0%
0.1667697 1
 
4.0%
0.00203551 1
 
4.0%
0.0603754 1
 
4.0%
2.10033458 1
 
4.0%
0.13341576 1
 
4.0%
0.48418368 1
 
4.0%
0.00200628 1
 
4.0%
0.05095202 1
 
4.0%
0.00973341 1
 
4.0%
(Missing) 14
56.0%
ValueCountFrequency (%)
0.00200628 1
4.0%
0.00203551 1
4.0%
0.00973341 1
4.0%
0.05095202 1
4.0%
0.0603754 1
4.0%
0.13341576 1
4.0%
0.1667697 1
4.0%
0.48418368 1
4.0%
0.58102046 1
4.0%
2.10033458 1
4.0%
ValueCountFrequency (%)
9.3785068 1
4.0%
2.10033458 1
4.0%
0.58102046 1
4.0%
0.48418368 1
4.0%
0.1667697 1
4.0%
0.13341576 1
4.0%
0.0603754 1
4.0%
0.05095202 1
4.0%
0.00973341 1
4.0%
0.00203551 1
4.0%

6등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct14
Distinct (%)100.0%
Missing11
Missing (%)44.0%
Infinite0
Infinite (%)0.0%
Mean2.1826802
Minimum0.00228969
Maximum8.9560025
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-05-04T07:32:33.964826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00228969
5-th percentile0.0029350815
Q10.025793268
median0.20812385
Q33.7904118
95-th percentile7.9234487
Maximum8.9560025
Range8.9537128
Interquartile range (IQR)3.7646185

Descriptive statistics

Standard deviation3.153335
Coefficient of variation (CV)1.4447078
Kurtosis0.16137107
Mean2.1826802
Median Absolute Deviation (MAD)0.2053377
Skewness1.2652112
Sum30.557523
Variance9.9435216
MonotonicityNot monotonic
2024-05-04T07:32:34.423475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
6.02020031 1
 
4.0%
4.46800668 1
 
4.0%
1.75762722 1
 
4.0%
0.05457222 1
 
4.0%
0.00228969 1
 
4.0%
0.01792709 1
 
4.0%
0.0493918 1
 
4.0%
1.4346994 1
 
4.0%
7.36745817 1
 
4.0%
0.0032826 1
 
4.0%
Other values (4) 4
 
16.0%
(Missing) 11
44.0%
ValueCountFrequency (%)
0.00228969 1
4.0%
0.0032826 1
4.0%
0.00981732 1
4.0%
0.01792709 1
4.0%
0.0493918 1
4.0%
0.05457222 1
4.0%
0.09050879 1
4.0%
0.32573891 1
4.0%
1.4346994 1
4.0%
1.75762722 1
4.0%
ValueCountFrequency (%)
8.95600247 1
4.0%
7.36745817 1
4.0%
6.02020031 1
4.0%
4.46800668 1
4.0%
1.75762722 1
4.0%
1.4346994 1
4.0%
0.32573891 1
4.0%
0.09050879 1
4.0%
0.05457222 1
4.0%
0.0493918 1
4.0%

7등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct10
Distinct (%)100.0%
Missing15
Missing (%)60.0%
Infinite0
Infinite (%)0.0%
Mean1.3293737
Minimum0.00085101
Maximum9.6940675
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-05-04T07:32:34.891567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00085101
5-th percentile0.0022798095
Q10.018808498
median0.061962715
Q30.93142016
95-th percentile6.206212
Maximum9.6940675
Range9.6932165
Interquartile range (IQR)0.91261166

Descriptive statistics

Standard deviation3.0088371
Coefficient of variation (CV)2.2633493
Kurtosis8.7458589
Mean1.3293737
Median Absolute Deviation (MAD)0.05952415
Skewness2.9133416
Sum13.293737
Variance9.0531008
MonotonicityNot monotonic
2024-05-04T07:32:35.401603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0.34544172 1
 
4.0%
1.94327749 1
 
4.0%
0.00991604 1
 
4.0%
0.00085101 1
 
4.0%
0.07269525 1
 
4.0%
1.12674631 1
 
4.0%
0.00402612 1
 
4.0%
0.05123018 1
 
4.0%
0.04548587 1
 
4.0%
9.69406751 1
 
4.0%
(Missing) 15
60.0%
ValueCountFrequency (%)
0.00085101 1
4.0%
0.00402612 1
4.0%
0.00991604 1
4.0%
0.04548587 1
4.0%
0.05123018 1
4.0%
0.07269525 1
4.0%
0.34544172 1
4.0%
1.12674631 1
4.0%
1.94327749 1
4.0%
9.69406751 1
4.0%
ValueCountFrequency (%)
9.69406751 1
4.0%
1.94327749 1
4.0%
1.12674631 1
4.0%
0.34544172 1
4.0%
0.07269525 1
4.0%
0.05123018 1
4.0%
0.04548587 1
4.0%
0.00991604 1
4.0%
0.00402612 1
4.0%
0.00085101 1
4.0%

8등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct18
Distinct (%)100.0%
Missing7
Missing (%)28.0%
Infinite0
Infinite (%)0.0%
Mean3.5873482
Minimum0.00247898
Maximum32.666345
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-05-04T07:32:35.888055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00247898
5-th percentile0.0026185075
Q10.041342127
median0.28624623
Q31.5202598
95-th percentile24.52128
Maximum32.666345
Range32.663866
Interquartile range (IQR)1.4789176

Descriptive statistics

Standard deviation9.0132055
Coefficient of variation (CV)2.5124981
Kurtosis7.3263179
Mean3.5873482
Median Absolute Deviation (MAD)0.26758395
Skewness2.8457413
Sum64.572267
Variance81.237874
MonotonicityNot monotonic
2024-05-04T07:32:36.462274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1.4223846 1
 
4.0%
0.36471396 1
 
4.0%
23.08391566 1
 
4.0%
2.22424662 1
 
4.0%
0.20777849 1
 
4.0%
0.0225164 1
 
4.0%
0.01480815 1
 
4.0%
32.66634477 1
 
4.0%
1.55288481 1
 
4.0%
0.5082607 1
 
4.0%
Other values (8) 8
32.0%
(Missing) 7
28.0%
ValueCountFrequency (%)
0.00247898 1
4.0%
0.00264313 1
4.0%
0.01480815 1
4.0%
0.0225164 1
4.0%
0.02431425 1
4.0%
0.09242576 1
4.0%
0.10586434 1
4.0%
0.1276499 1
4.0%
0.20777849 1
4.0%
0.36471396 1
4.0%
ValueCountFrequency (%)
32.66634477 1
4.0%
23.08391566 1
4.0%
2.22424662 1
4.0%
1.60689209 1
4.0%
1.55288481 1
4.0%
1.4223846 1
4.0%
0.54214486 1
4.0%
0.5082607 1
4.0%
0.36471396 1
4.0%
0.20777849 1
4.0%

9등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct17
Distinct (%)100.0%
Missing8
Missing (%)32.0%
Infinite0
Infinite (%)0.0%
Mean13.436667
Minimum0.00261425
Maximum174.98111
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-05-04T07:32:37.039895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00261425
5-th percentile0.011118242
Q10.0313684
median0.13409793
Q30.86097252
95-th percentile59.43883
Maximum174.98111
Range174.9785
Interquartile range (IQR)0.82960412

Descriptive statistics

Standard deviation42.40808
Coefficient of variation (CV)3.1561459
Kurtosis15.532668
Mean13.436667
Median Absolute Deviation (MAD)0.13148368
Skewness3.8911487
Sum228.42333
Variance1798.4452
MonotonicityNot monotonic
2024-05-04T07:32:37.468440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0.10382069 1
 
4.0%
30.553259 1
 
4.0%
16.75107424 1
 
4.0%
0.86097252 1
 
4.0%
0.41857524 1
 
4.0%
0.0313684 1
 
4.0%
174.9811129 1
 
4.0%
0.13409793 1
 
4.0%
0.80742451 1
 
4.0%
0.03236484 1
 
4.0%
Other values (7) 7
28.0%
(Missing) 8
32.0%
ValueCountFrequency (%)
0.00261425 1
4.0%
0.01324424 1
4.0%
0.01358024 1
4.0%
0.0195783 1
4.0%
0.0313684 1
4.0%
0.03236484 1
4.0%
0.07449885 1
4.0%
0.10382069 1
4.0%
0.13409793 1
4.0%
0.41857524 1
4.0%
ValueCountFrequency (%)
174.9811129 1
4.0%
30.553259 1
4.0%
16.75107424 1
4.0%
3.17365149 1
4.0%
0.86097252 1
4.0%
0.80742451 1
4.0%
0.45209585 1
4.0%
0.41857524 1
4.0%
0.13409793 1
4.0%
0.10382069 1
4.0%

10등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct13
Distinct (%)100.0%
Missing12
Missing (%)48.0%
Infinite0
Infinite (%)0.0%
Mean2.6231188
Minimum0.0003714
Maximum18.55113
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-05-04T07:32:38.168617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0003714
5-th percentile0.003681324
Q10.01762468
median0.17452853
Q31.0600646
95-th percentile14.13767
Maximum18.55113
Range18.550759
Interquartile range (IQR)1.0424399

Descriptive statistics

Standard deviation5.6687761
Coefficient of variation (CV)2.1610825
Kurtosis5.4354579
Mean2.6231188
Median Absolute Deviation (MAD)0.16864059
Skewness2.447534
Sum34.100545
Variance32.135023
MonotonicityNot monotonic
2024-05-04T07:32:38.567367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0.80086881 1
 
4.0%
1.06006457 1
 
4.0%
0.00588794 1
 
4.0%
0.0003714 1
 
4.0%
0.01762468 1
 
4.0%
0.17452853 1
 
4.0%
18.55113027 1
 
4.0%
0.00988308 1
 
4.0%
0.13891641 1
 
4.0%
0.19258609 1
 
4.0%
Other values (3) 3
 
12.0%
(Missing) 12
48.0%
ValueCountFrequency (%)
0.0003714 1
4.0%
0.00588794 1
4.0%
0.00988308 1
4.0%
0.01762468 1
4.0%
0.02028462 1
4.0%
0.13891641 1
4.0%
0.17452853 1
4.0%
0.19258609 1
4.0%
0.80086881 1
4.0%
1.06006457 1
4.0%
ValueCountFrequency (%)
18.55113027 1
4.0%
11.19536359 1
4.0%
1.93303499 1
4.0%
1.06006457 1
4.0%
0.80086881 1
4.0%
0.19258609 1
4.0%
0.17452853 1
4.0%
0.13891641 1
4.0%
0.02028462 1
4.0%
0.01762468 1
4.0%

11등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7
Distinct (%)100.0%
Missing18
Missing (%)72.0%
Infinite0
Infinite (%)0.0%
Mean3.7910762
Minimum0.00112766
Maximum23.519676
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-05-04T07:32:39.195050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00112766
5-th percentile0.037744331
Q10.15412119
median0.26757519
Q31.2204561
95-th percentile17.002922
Maximum23.519676
Range23.518548
Interquartile range (IQR)1.0663349

Descriptive statistics

Standard deviation8.7209954
Coefficient of variation (CV)2.300401
Kurtosis6.8881005
Mean3.7910762
Median Absolute Deviation (MAD)0.26644753
Skewness2.6191165
Sum26.537533
Variance76.05576
MonotonicityNot monotonic
2024-05-04T07:32:39.570821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0.00112766 1
 
4.0%
0.26757519 1
 
4.0%
1.79716233 1
 
4.0%
0.64374984 1
 
4.0%
0.18505915 1
 
4.0%
23.51967574 1
 
4.0%
0.12318323 1
 
4.0%
(Missing) 18
72.0%
ValueCountFrequency (%)
0.00112766 1
4.0%
0.12318323 1
4.0%
0.18505915 1
4.0%
0.26757519 1
4.0%
0.64374984 1
4.0%
1.79716233 1
4.0%
23.51967574 1
4.0%
ValueCountFrequency (%)
23.51967574 1
4.0%
1.79716233 1
4.0%
0.64374984 1
4.0%
0.26757519 1
4.0%
0.18505915 1
4.0%
0.12318323 1
4.0%
0.00112766 1
4.0%

12등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct12
Distinct (%)100.0%
Missing13
Missing (%)52.0%
Infinite0
Infinite (%)0.0%
Mean2.904795
Minimum0.0027768
Maximum22.631956
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-05-04T07:32:40.057062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0027768
5-th percentile0.008274116
Q10.045100788
median0.16058554
Q31.3527493
95-th percentile13.865522
Maximum22.631956
Range22.629179
Interquartile range (IQR)1.3076485

Descriptive statistics

Standard deviation6.5797162
Coefficient of variation (CV)2.2651224
Kurtosis8.7634101
Mean2.904795
Median Absolute Deviation (MAD)0.131735
Skewness2.8872983
Sum34.85754
Variance43.292665
MonotonicityNot monotonic
2024-05-04T07:32:40.638189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0.23482134 1
 
4.0%
0.21135749 1
 
4.0%
0.30332853 1
 
4.0%
0.0027768 1
 
4.0%
0.03985852 1
 
4.0%
0.1098136 1
 
4.0%
4.50101161 1
 
4.0%
6.69298539 1
 
4.0%
0.01277192 1
 
4.0%
0.04684821 1
 
4.0%
Other values (2) 2
 
8.0%
(Missing) 13
52.0%
ValueCountFrequency (%)
0.0027768 1
4.0%
0.01277192 1
4.0%
0.03985852 1
4.0%
0.04684821 1
4.0%
0.070011 1
4.0%
0.1098136 1
4.0%
0.21135749 1
4.0%
0.23482134 1
4.0%
0.30332853 1
4.0%
4.50101161 1
4.0%
ValueCountFrequency (%)
22.63195587 1
4.0%
6.69298539 1
4.0%
4.50101161 1
4.0%
0.30332853 1
4.0%
0.23482134 1
4.0%
0.21135749 1
4.0%
0.1098136 1
4.0%
0.070011 1
4.0%
0.04684821 1
4.0%
0.03985852 1
4.0%

13등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct11
Distinct (%)100.0%
Missing14
Missing (%)56.0%
Infinite0
Infinite (%)0.0%
Mean3.9975145
Minimum0.00265617
Maximum16.10964
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-05-04T07:32:41.130902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00265617
5-th percentile0.002824065
Q10.056677325
median0.1989624
Q38.2091667
95-th percentile13.349478
Maximum16.10964
Range16.106984
Interquartile range (IQR)8.1524894

Descriptive statistics

Standard deviation5.7751774
Coefficient of variation (CV)1.4446921
Kurtosis0.10415147
Mean3.9975145
Median Absolute Deviation (MAD)0.19630623
Skewness1.165761
Sum43.972659
Variance33.352674
MonotonicityNot monotonic
2024-05-04T07:32:41.524226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
10.58931568 1
 
4.0%
9.35791479 1
 
4.0%
0.1232318 1
 
4.0%
0.1989624 1
 
4.0%
0.00265617 1
 
4.0%
0.41417296 1
 
4.0%
7.06041863 1
 
4.0%
0.00299196 1
 
4.0%
0.08054418 1
 
4.0%
0.03281047 1
 
4.0%
(Missing) 14
56.0%
ValueCountFrequency (%)
0.00265617 1
4.0%
0.00299196 1
4.0%
0.03281047 1
4.0%
0.08054418 1
4.0%
0.1232318 1
4.0%
0.1989624 1
4.0%
0.41417296 1
4.0%
7.06041863 1
4.0%
9.35791479 1
4.0%
10.58931568 1
4.0%
ValueCountFrequency (%)
16.10964019 1
4.0%
10.58931568 1
4.0%
9.35791479 1
4.0%
7.06041863 1
4.0%
0.41417296 1
4.0%
0.1989624 1
4.0%
0.1232318 1
4.0%
0.08054418 1
4.0%
0.03281047 1
4.0%
0.00299196 1
4.0%

14등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct10
Distinct (%)100.0%
Missing15
Missing (%)60.0%
Infinite0
Infinite (%)0.0%
Mean1.8215291
Minimum0.00062168
Maximum7.5619951
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-05-04T07:32:41.975994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00062168
5-th percentile0.001444847
Q10.014002915
median0.18830159
Q33.6160099
95-th percentile6.3044999
Maximum7.5619951
Range7.5613734
Interquartile range (IQR)3.602007

Descriptive statistics

Standard deviation2.74866
Coefficient of variation (CV)1.5089849
Kurtosis0.51933552
Mean1.8215291
Median Absolute Deviation (MAD)0.18676528
Skewness1.3415525
Sum18.215291
Variance7.5551318
MonotonicityNot monotonic
2024-05-04T07:32:42.553483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0.30284633 1
 
4.0%
0.00062168 1
 
4.0%
0.07375685 1
 
4.0%
4.76756128 1
 
4.0%
0.97791384 1
 
4.0%
4.49537523 1
 
4.0%
0.00245094 1
 
4.0%
0.0116209 1
 
4.0%
0.02114896 1
 
4.0%
7.5619951 1
 
4.0%
(Missing) 15
60.0%
ValueCountFrequency (%)
0.00062168 1
4.0%
0.00245094 1
4.0%
0.0116209 1
4.0%
0.02114896 1
4.0%
0.07375685 1
4.0%
0.30284633 1
4.0%
0.97791384 1
4.0%
4.49537523 1
4.0%
4.76756128 1
4.0%
7.5619951 1
4.0%
ValueCountFrequency (%)
7.5619951 1
4.0%
4.76756128 1
4.0%
4.49537523 1
4.0%
0.97791384 1
4.0%
0.30284633 1
4.0%
0.07375685 1
4.0%
0.02114896 1
4.0%
0.0116209 1
4.0%
0.00245094 1
4.0%
0.00062168 1
4.0%

15등급
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct13
Distinct (%)100.0%
Missing12
Missing (%)48.0%
Infinite0
Infinite (%)0.0%
Mean8.4827782
Minimum0
Maximum63.907289
Zeros1
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-05-04T07:32:43.081114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.04661586
Q10.84169295
median1.35
Q33
95-th percentile41.779533
Maximum63.907289
Range63.907289
Interquartile range (IQR)2.158307

Descriptive statistics

Standard deviation18.138267
Coefficient of variation (CV)2.138246
Kurtosis8.2818688
Mean8.4827782
Median Absolute Deviation (MAD)1.2723069
Skewness2.8499845
Sum110.27612
Variance328.99671
MonotonicityNot monotonic
2024-05-04T07:32:43.467510image/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%
1.30620001 1
 
4.0%
0.84169295 1
 
4.0%
27.02769584 1
 
4.0%
3.0 1
 
4.0%
0.0776931 1
 
4.0%
1.06535116 1
 
4.0%
2.03644206 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%
0.84169295 1
4.0%
1.06535116 1
4.0%
1.30620001 1
4.0%
1.35 1
4.0%
2.03644206 1
4.0%
2.7 1
4.0%
3.0 1
4.0%
ValueCountFrequency (%)
63.90728943 1
4.0%
27.02769584 1
4.0%
6.54032817 1
4.0%
3.0 1
4.0%
2.7 1
4.0%
2.03644206 1
4.0%
1.35 1
4.0%
1.30620001 1
4.0%
1.06535116 1
4.0%
0.84169295 1
4.0%

무등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct14
Distinct (%)100.0%
Missing11
Missing (%)44.0%
Infinite0
Infinite (%)0.0%
Mean48.887979
Minimum0.00418269
Maximum397.96479
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-05-04T07:32:43.829858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00418269
5-th percentile0.037192745
Q10.15038835
median10.380801
Q340.683938
95-th percentile194.52806
Maximum397.96479
Range397.96061
Interquartile range (IQR)40.533549

Descriptive statistics

Standard deviation104.493
Coefficient of variation (CV)2.1373965
Kurtosis11.443358
Mean48.887979
Median Absolute Deviation (MAD)10.351226
Skewness3.2857142
Sum684.43171
Variance10918.787
MonotonicityNot monotonic
2024-05-04T07:32:44.199201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
5.73069298 1
 
4.0%
84.98520219 1
 
4.0%
0.18276388 1
 
4.0%
76.03871436 1
 
4.0%
15.03090822 1
 
4.0%
0.00418269 1
 
4.0%
0.06616576 1
 
4.0%
37.86903194 1
 
4.0%
397.9647879 1
 
4.0%
0.05496739 1
 
4.0%
Other values (4) 4
 
16.0%
(Missing) 11
44.0%
ValueCountFrequency (%)
0.00418269 1
4.0%
0.05496739 1
4.0%
0.06616576 1
4.0%
0.13959651 1
4.0%
0.18276388 1
4.0%
0.2681519 1
4.0%
5.73069298 1
4.0%
15.03090822 1
4.0%
24.47430506 1
4.0%
37.86903194 1
4.0%
ValueCountFrequency (%)
397.9647879 1
4.0%
84.98520219 1
4.0%
76.03871436 1
4.0%
41.62223957 1
4.0%
37.86903194 1
4.0%
24.47430506 1
4.0%
15.03090822 1
4.0%
5.73069298 1
4.0%
0.2681519 1
4.0%
0.18276388 1
4.0%

Interactions

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2024-05-04T07:32:11.876145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:32:17.148230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:32:23.238844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:10.580389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:14.124866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:18.342078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:22.976865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:27.145118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:31.723553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:37.110480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:41.951581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:46.315065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:51.361320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:56.285593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:32:01.114016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:32:06.545977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:32:12.239206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:32:17.521059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:32:23.629196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:10.832142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:14.396156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:18.612194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:23.234339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:27.420015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:32.126815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:37.387384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:42.213089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:46.626847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:51.704985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:56.539341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:32:01.378405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:32:06.831073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:32:12.572479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:32:17.820660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:32:23.970948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:11.086222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:14.566870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:18.925681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:23.514515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:27.676082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:32.540463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:37.644984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:42.513707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:46.973344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:51.988684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:56.950301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:32:01.750512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:32:07.352120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:32:12.888580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:32:18.471830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:32:24.239230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:11.338199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:14.781701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:19.184180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:23.771053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:27.932953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:32.939229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:38.001286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:42.761801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:47.262284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:52.276418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:31:57.203461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:32:02.100925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:32:07.666149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:32:13.102322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:32:18.855426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T07:32:44.541788image/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
1등급1.0001.0001.0001.0001.0000.8960.8041.0001.0001.0001.0001.0001.0001.0000.9490.9601.000
2등급1.0001.0001.0001.0001.0000.8960.7421.0001.0001.0001.0001.0001.0001.0000.7230.9561.000
3등급1.0001.0001.0001.0001.0000.8881.0001.0001.0001.0001.0001.0001.0001.0001.0000.5311.000
4등급1.0001.0001.0001.0001.0000.0001.000NaN1.0001.0001.0000.0001.000NaN1.0000.0001.000
5등급1.0000.8960.8960.8880.0001.0001.0001.0000.9080.9080.8961.0001.0001.0001.0001.0000.903
6등급1.0000.8040.7421.0001.0001.0001.0001.0001.0001.0000.8041.0001.0000.9930.9870.8041.000
7등급1.0001.0001.0001.000NaN1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
8등급1.0001.0001.0001.0001.0000.9081.0001.0001.0001.0001.0001.0001.0001.0001.0000.5790.978
9등급1.0001.0001.0001.0001.0000.9081.0001.0001.0001.0001.0001.0001.0001.0001.0000.5671.000
10등급1.0001.0001.0001.0001.0000.8960.8041.0001.0001.0001.0001.0001.0001.0000.9490.9630.742
11등급1.0001.0001.0001.0000.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
12등급1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
13등급1.0001.0001.0001.000NaN1.0000.9931.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
14등급1.0000.9490.7231.0001.0001.0000.9871.0001.0001.0000.9491.0001.0001.0001.0000.9401.000
15등급1.0000.9600.9560.5310.0001.0000.8041.0000.5790.5670.9631.0001.0001.0000.9401.0000.000
무등급1.0001.0001.0001.0001.0000.9031.0001.0000.9781.0000.7421.0001.0001.0001.0000.0001.000
2024-05-04T07:32:45.071387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1등급2등급3등급4등급5등급6등급7등급8등급9등급10등급11등급12등급13등급14등급15등급무등급
1등급1.0000.8910.9390.9030.7670.7270.7830.8550.8550.9180.7140.7940.6830.6900.8420.879
2등급0.8911.0000.9520.9450.7000.8670.7860.8810.9911.0000.6790.8670.8330.6670.5500.950
3등급0.9390.9521.0000.9150.8100.8420.8330.9760.9640.9520.7710.9000.7860.7860.7830.983
4등급0.9030.9450.9151.0000.5480.7580.5710.7550.9640.9450.7500.7170.6190.6190.5330.883
5등급0.7670.7000.8100.5481.0000.9030.9520.8360.5910.7171.0000.9150.9500.9760.8670.830
6등급0.7270.8670.8420.7580.9031.0000.9330.8520.7580.8640.9430.8740.8910.9330.5180.900
7등급0.7830.7860.8330.5710.9520.9331.0000.9030.6970.8501.0000.9330.9501.0000.6430.881
8등급0.8550.8810.9760.7550.8360.8520.9031.0000.8750.8900.7500.9180.8270.8060.7480.839
9등급0.8550.9910.9640.9640.5910.7580.6970.8751.0000.9000.6000.7760.6360.6670.6270.918
10등급0.9181.0000.9520.9450.7170.8640.8500.8900.9001.0000.6790.8550.8670.6900.6000.618
11등급0.7140.6790.7710.7501.0000.9431.0000.7500.6000.6791.0000.9431.0001.0000.9000.771
12등급0.7940.8670.9000.7170.9150.8740.9330.9180.7760.8550.9431.0000.8550.9640.6970.903
13등급0.6830.8330.7860.6190.9500.8910.9500.8270.6360.8671.0000.8551.0000.9640.3670.833
14등급0.6900.6670.7860.6190.9760.9331.0000.8060.6670.6901.0000.9640.9641.0000.8210.857
15등급0.8420.5500.7830.5330.8670.5180.6430.7480.6270.6000.9000.6970.3670.8211.0000.727
무등급0.8790.9500.9830.8830.8300.9000.8810.8390.9180.6180.7710.9030.8330.8570.7271.000

Missing values

2024-05-04T07:32:24.867126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T07:32:25.844452image/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.
2024-05-04T07:32:26.645759image/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
0PF보증0.0384730.3141340.0256460.586159<NA>6.02020.3454421.5528850.8074250.800869<NA>0.23482110.589316<NA>0.0<NA>
1기금건설자금대출보증(주택,준주택)0.138514<NA><NA><NA>0.581024.4680071.9432770.5082610.1038211.060065<NA>0.2113579.357915<NA>2.75.730693
2도시재생PF<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3도심주택 특약보증<NA><NA><NA><NA><NA>1.757627<NA>0.542145<NA><NA><NA><NA>0.1232320.302846<NA><NA>
4리모델링사업비보증<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>84.985202
5리츠회사채보증<NA><NA><NA><NA><NA><NA>0.0099160.0243140.013244<NA><NA><NA><NA><NA><NA><NA>
6모기지보증<NA><NA><NA><NA>0.166770.054572<NA>0.127650.074499<NA><NA>0.3033290.198962<NA>1.350.182764
7수요자중심형도시재생지원자금보증<NA><NA><NA><NA><NA><NA><NA>0.105864<NA>0.005888<NA><NA><NA><NA>1.306276.038714
8수요자중심형도시재생지원자금특례보증<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>15.030908
9오피스텔분양보증<NA><NA><NA>0.016927<NA><NA><NA>0.0024790.01358<NA><NA><NA><NA><NA><NA><NA>
상품명1등급2등급3등급4등급5등급6등급7등급8등급9등급10등급11등급12등급13등급14등급15등급무등급
15임대보증금보증(사용검사후)0.0991520.1096310.4543930.022482.1003351.4346991.1267461.6068920.4520960.1745291.7971624.5010127.0604194.76756127.02769637.869032
16임대주택매입자금보증<NA>0.008116<NA><NA>0.133416<NA><NA>1.4223850.134098<NA><NA><NA><NA>0.977914<NA><NA>
17조합사업비대출보증2.4528535.06585612.541789121.3297230.4841847.367458<NA>32.666345174.98111318.551130.643756.692985<NA>4.4953753.0397.964788
18조합주택시공보증0.005680.0024410.0045830.0187060.0020060.0032830.0040260.0148080.0313680.009883<NA>0.0127720.0029920.0024510.0776930.054967
19주상복합주택분양보증0.0438180.062450.0171030.2393440.0509520.0905090.051230.0225160.4185750.138916<NA>0.0468480.080544<NA>1.0653510.139597
20주택분양보증0.1118570.157360.1191060.8074580.0097330.0098170.0454860.2077780.8609730.1925860.1850590.0700110.032810.0116212.0364420.268152
21주택임대보증<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.423424<NA>
22하도급대금지급보증3.8588792.7885570.5272727.70579<NA>0.325739<NA>2.22424716.7510741.933035<NA><NA><NA>0.0211496.54032824.474305
23하자보수보증7.3469094.4024164.78477411.3608759.3785078.9560029.69406823.08391630.55325911.19536423.51967622.63195616.109647.56199563.90728941.62224
24후분양대출보증<NA>0.013526<NA>0.009014<NA><NA><NA>0.364714<NA>0.0202850.123183<NA><NA><NA><NA><NA>