Overview

Dataset statistics

Number of variables17
Number of observations25
Missing cells217
Missing cells (%)51.1%
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 : 23.11.30. 기준
Author주택도시보증공사
URLhttps://www.data.go.kr/data/15126173/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 12 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 14 other fieldsHigh correlation
9등급 is highly overall correlated with 1등급 and 13 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 12 other fieldsHigh correlation
13등급 is highly overall correlated with 1등급 and 14 other fieldsHigh correlation
14등급 is highly overall correlated with 1등급 and 14 other fieldsHigh correlation
15등급 is highly overall correlated with 1등급 and 11 other fieldsHigh correlation
무등급 is highly overall correlated with 1등급 and 13 other fieldsHigh correlation
1등급 has 14 (56.0%) missing valuesMissing
2등급 has 12 (48.0%) missing valuesMissing
3등급 has 14 (56.0%) missing valuesMissing
4등급 has 14 (56.0%) missing valuesMissing
5등급 has 12 (48.0%) missing valuesMissing
6등급 has 10 (40.0%) missing valuesMissing
7등급 has 7 (28.0%) missing valuesMissing
8등급 has 13 (52.0%) missing valuesMissing
9등급 has 14 (56.0%) missing valuesMissing
10등급 has 15 (60.0%) missing valuesMissing
11등급 has 16 (64.0%) missing valuesMissing
12등급 has 14 (56.0%) missing valuesMissing
13등급 has 15 (60.0%) missing valuesMissing
14등급 has 18 (72.0%) missing valuesMissing
15등급 has 14 (56.0%) missing valuesMissing
무등급 has 15 (60.0%) missing valuesMissing
상품명 has unique valuesUnique
15등급 has 1 (4.0%) zerosZeros

Reproduction

Analysis started2024-01-14 13:29:54.146471
Analysis finished2024-01-14 13:30:31.108878
Duration36.96 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
2024-01-14T22:30:31.337398image/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%
2024-01-14T22:30:31.949080image/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%
Mean10.619859
Minimum0.00028914
Maximum94.679065
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-01-14T22:30:32.101414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00028914
5-th percentile0.001582395
Q10.014630785
median0.17215263
Q34.660063
95-th percentile53.35361
Maximum94.679065
Range94.678776
Interquartile range (IQR)4.6454322

Descriptive statistics

Standard deviation28.183367
Coefficient of variation (CV)2.6538362
Kurtosis10.369086
Mean10.619859
Median Absolute Deviation (MAD)0.17186349
Skewness3.1931557
Sum116.81845
Variance794.30215
MonotonicityNot monotonic
2024-01-14T22:30:32.238001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.5617727 1
 
4.0%
0.00287565 1
 
4.0%
0.00028914 1
 
4.0%
0.01142225 1
 
4.0%
0.02475462 1
 
4.0%
94.67906549 1
 
4.0%
0.01783932 1
 
4.0%
0.17215263 1
 
4.0%
0.72074874 1
 
4.0%
8.59937732 1
 
4.0%
(Missing) 14
56.0%
ValueCountFrequency (%)
0.00028914 1
4.0%
0.00287565 1
4.0%
0.01142225 1
4.0%
0.01783932 1
4.0%
0.02475462 1
4.0%
0.17215263 1
4.0%
0.5617727 1
4.0%
0.72074874 1
4.0%
8.59937732 1
4.0%
12.02815382 1
4.0%
ValueCountFrequency (%)
94.67906549 1
4.0%
12.02815382 1
4.0%
8.59937732 1
4.0%
0.72074874 1
4.0%
0.5617727 1
4.0%
0.17215263 1
4.0%
0.02475462 1
4.0%
0.01783932 1
4.0%
0.01142225 1
4.0%
0.00287565 1
4.0%

2등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct13
Distinct (%)100.0%
Missing12
Missing (%)48.0%
Infinite0
Infinite (%)0.0%
Mean2.9629175
Minimum0.00136609
Maximum27.739944
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-01-14T22:30:32.341796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00136609
5-th percentile0.003192052
Q10.00871538
median0.1795311
Q30.56226283
95-th percentile15.924374
Maximum27.739944
Range27.738578
Interquartile range (IQR)0.55354745

Descriptive statistics

Standard deviation7.7590087
Coefficient of variation (CV)2.6187056
Kurtosis10.460493
Mean2.9629175
Median Absolute Deviation (MAD)0.17113536
Skewness3.1858043
Sum38.517928
Variance60.202215
MonotonicityNot monotonic
2024-01-14T22:30:32.477279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0.1795311 1
 
4.0%
0.00440936 1
 
4.0%
0.00136609 1
 
4.0%
0.00871538 1
 
4.0%
1.33317366 1
 
4.0%
0.00839574 1
 
4.0%
0.32944921 1
 
4.0%
27.73994395 1
 
4.0%
0.00999707 1
 
4.0%
0.07415992 1
 
4.0%
Other values (3) 3
 
12.0%
(Missing) 12
48.0%
ValueCountFrequency (%)
0.00136609 1
4.0%
0.00440936 1
4.0%
0.00839574 1
4.0%
0.00871538 1
4.0%
0.00999707 1
4.0%
0.07415992 1
4.0%
0.1795311 1
4.0%
0.21919711 1
4.0%
0.32944921 1
4.0%
0.56226283 1
4.0%
ValueCountFrequency (%)
27.73994395 1
4.0%
8.04732659 1
4.0%
1.33317366 1
4.0%
0.56226283 1
4.0%
0.32944921 1
4.0%
0.21919711 1
4.0%
0.1795311 1
4.0%
0.07415992 1
4.0%
0.00999707 1
4.0%
0.00871538 1
4.0%

3등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct11
Distinct (%)100.0%
Missing14
Missing (%)56.0%
Infinite0
Infinite (%)0.0%
Mean1.5609532
Minimum0.00018594
Maximum7.7249535
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-01-14T22:30:32.661331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00018594
5-th percentile0.00137448
Q10.009204205
median0.13170004
Q31.6028953
95-th percentile6.7583395
Maximum7.7249535
Range7.7247675
Interquartile range (IQR)1.5936911

Descriptive statistics

Standard deviation2.736086
Coefficient of variation (CV)1.7528303
Kurtosis1.7378002
Mean1.5609532
Median Absolute Deviation (MAD)0.12913702
Skewness1.7107184
Sum17.170485
Variance7.4861663
MonotonicityNot monotonic
2024-01-14T22:30:32.830332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.32986278 1
 
4.0%
0.00018594 1
 
4.0%
0.01028397 1
 
4.0%
0.13170004 1
 
4.0%
0.00812444 1
 
4.0%
7.72495347 1
 
4.0%
0.00256302 1
 
4.0%
0.10206404 1
 
4.0%
0.19309387 1
 
4.0%
2.87592791 1
 
4.0%
(Missing) 14
56.0%
ValueCountFrequency (%)
0.00018594 1
4.0%
0.00256302 1
4.0%
0.00812444 1
4.0%
0.01028397 1
4.0%
0.10206404 1
4.0%
0.13170004 1
4.0%
0.19309387 1
4.0%
0.32986278 1
4.0%
2.87592791 1
4.0%
5.79172547 1
4.0%
ValueCountFrequency (%)
7.72495347 1
4.0%
5.79172547 1
4.0%
2.87592791 1
4.0%
0.32986278 1
4.0%
0.19309387 1
4.0%
0.13170004 1
4.0%
0.10206404 1
4.0%
0.01028397 1
4.0%
0.00812444 1
4.0%
0.00256302 1
4.0%

4등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct11
Distinct (%)100.0%
Missing14
Missing (%)56.0%
Infinite0
Infinite (%)0.0%
Mean1.9978564
Minimum0.00045543
Maximum10.937309
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-01-14T22:30:32.993641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00045543
5-th percentile0.001622835
Q10.02439963
median0.08977576
Q32.6419486
95-th percentile8.1903774
Maximum10.937309
Range10.936853
Interquartile range (IQR)2.617549

Descriptive statistics

Standard deviation3.6275721
Coefficient of variation (CV)1.8157322
Kurtosis2.9640674
Mean1.9978564
Median Absolute Deviation (MAD)0.08137908
Skewness1.862104
Sum21.97642
Variance13.159279
MonotonicityNot monotonic
2024-01-14T22:30:33.150052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.08977576 1
 
4.0%
0.04040258 1
 
4.0%
0.00045543 1
 
4.0%
0.00839668 1
 
4.0%
0.0992593 1
 
4.0%
5.11766007 1
 
4.0%
0.00279024 1
 
4.0%
0.07068787 1
 
4.0%
0.16623719 1
 
4.0%
5.44344633 1
 
4.0%
(Missing) 14
56.0%
ValueCountFrequency (%)
0.00045543 1
4.0%
0.00279024 1
4.0%
0.00839668 1
4.0%
0.04040258 1
4.0%
0.07068787 1
4.0%
0.08977576 1
4.0%
0.0992593 1
4.0%
0.16623719 1
4.0%
5.11766007 1
4.0%
5.44344633 1
4.0%
ValueCountFrequency (%)
10.93730851 1
4.0%
5.44344633 1
4.0%
5.11766007 1
4.0%
0.16623719 1
4.0%
0.0992593 1
4.0%
0.08977576 1
4.0%
0.07068787 1
4.0%
0.04040258 1
4.0%
0.00839668 1
4.0%
0.00279024 1
4.0%

5등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct13
Distinct (%)100.0%
Missing12
Missing (%)48.0%
Infinite0
Infinite (%)0.0%
Mean3.0199084
Minimum0.00037181
Maximum19.830395
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-01-14T22:30:33.275737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00037181
5-th percentile0.003685334
Q10.01323948
median0.20510408
Q30.98945838
95-th percentile16.884791
Maximum19.830395
Range19.830024
Interquartile range (IQR)0.9762189

Descriptive statistics

Standard deviation6.4777305
Coefficient of variation (CV)2.145009
Kurtosis3.9479346
Mean3.0199084
Median Absolute Deviation (MAD)0.19920973
Skewness2.250481
Sum39.258809
Variance41.960993
MonotonicityNot monotonic
2024-01-14T22:30:33.423261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0.82447777 1
 
4.0%
0.98945838 1
 
4.0%
0.00589435 1
 
4.0%
0.00037181 1
 
4.0%
0.01028173 1
 
4.0%
0.20510408 1
 
4.0%
19.83039532 1
 
4.0%
0.01323948 1
 
4.0%
0.07703052 1
 
4.0%
0.2553086 1
 
4.0%
Other values (3) 3
 
12.0%
(Missing) 12
48.0%
ValueCountFrequency (%)
0.00037181 1
4.0%
0.00589435 1
4.0%
0.01028173 1
4.0%
0.01323948 1
4.0%
0.02030668 1
4.0%
0.07703052 1
4.0%
0.20510408 1
4.0%
0.2553086 1
4.0%
0.82447777 1
4.0%
0.98945838 1
4.0%
ValueCountFrequency (%)
19.83039532 1
4.0%
14.9210552 1
4.0%
2.10588511 1
4.0%
0.98945838 1
4.0%
0.82447777 1
4.0%
0.2553086 1
4.0%
0.20510408 1
4.0%
0.07703052 1
4.0%
0.02030668 1
4.0%
0.01323948 1
4.0%

6등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct15
Distinct (%)100.0%
Missing10
Missing (%)40.0%
Infinite0
Infinite (%)0.0%
Mean23.624455
Minimum0.00295845
Maximum269.31694
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-01-14T22:30:33.597003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00295845
5-th percentile0.010168583
Q10.04371564
median0.30283015
Q31.4874689
95-th percentile119.90972
Maximum269.31694
Range269.31398
Interquartile range (IQR)1.4437533

Descriptive statistics

Standard deviation69.632269
Coefficient of variation (CV)2.9474656
Kurtosis13.284918
Mean23.624455
Median Absolute Deviation (MAD)0.28957151
Skewness3.5918968
Sum354.36683
Variance4848.6529
MonotonicityNot monotonic
2024-01-14T22:30:33.799570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.80747731 1
 
4.0%
0.30283015 1
 
4.0%
0.01325864 1
 
4.0%
0.05966392 1
 
4.0%
0.03168928 1
 
4.0%
0.00295845 1
 
4.0%
0.03776148 1
 
4.0%
0.42468872 1
 
4.0%
0.11932784 1
 
4.0%
269.3169393 1
 
4.0%
Other values (5) 5
20.0%
(Missing) 10
40.0%
ValueCountFrequency (%)
0.00295845 1
4.0%
0.01325864 1
4.0%
0.03168928 1
4.0%
0.03776148 1
4.0%
0.0496698 1
4.0%
0.05966392 1
4.0%
0.11932784 1
4.0%
0.30283015 1
4.0%
0.42468872 1
4.0%
0.80747731 1
4.0%
ValueCountFrequency (%)
269.3169393 1
4.0%
55.8780611 1
4.0%
24.34756327 1
4.0%
2.08570057 1
4.0%
0.88923729 1
4.0%
0.80747731 1
4.0%
0.42468872 1
4.0%
0.30283015 1
4.0%
0.11932784 1
4.0%
0.05966392 1
4.0%

7등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct18
Distinct (%)100.0%
Missing7
Missing (%)28.0%
Infinite0
Infinite (%)0.0%
Mean5.0306277
Minimum0.00289234
Maximum41.881311
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-01-14T22:30:33.990988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00289234
5-th percentile0.003038064
Q10.10945934
median0.26524746
Q31.5430634
95-th percentile34.255703
Maximum41.881311
Range41.878418
Interquartile range (IQR)1.4336041

Descriptive statistics

Standard deviation11.980739
Coefficient of variation (CV)2.3815595
Kurtosis6.3761418
Mean5.0306277
Median Absolute Deviation (MAD)0.255602
Skewness2.7039495
Sum90.551298
Variance143.5381
MonotonicityNot monotonic
2024-01-14T22:30:34.230060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1.58823112 1
 
4.0%
0.24340704 1
 
4.0%
32.91000799 1
 
4.0%
5.16406014 1
 
4.0%
0.28708787 1
 
4.0%
0.11989912 1
 
4.0%
0.0223965 1
 
4.0%
41.88131079 1
 
4.0%
5.10603794 1
 
4.0%
0.96364061 1
 
4.0%
Other values (8) 8
32.0%
(Missing) 7
28.0%
ValueCountFrequency (%)
0.00289234 1
4.0%
0.00306378 1
4.0%
0.01622714 1
4.0%
0.0223965 1
4.0%
0.10597941 1
4.0%
0.11989912 1
4.0%
0.14604424 1
4.0%
0.16175586 1
4.0%
0.24340704 1
4.0%
0.28708787 1
4.0%
ValueCountFrequency (%)
41.88131079 1
4.0%
32.91000799 1
4.0%
5.16406014 1
4.0%
5.10603794 1
4.0%
1.58823112 1
4.0%
1.40756022 1
4.0%
0.96364061 1
4.0%
0.42169579 1
4.0%
0.28708787 1
4.0%
0.24340704 1
4.0%

8등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct12
Distinct (%)100.0%
Missing13
Missing (%)52.0%
Infinite0
Infinite (%)0.0%
Mean1.5368648
Minimum0.00102234
Maximum13.703917
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-01-14T22:30:34.475055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00102234
5-th percentile0.0034742565
Q10.01923321
median0.08136098
Q30.77380806
95-th percentile7.4137807
Maximum13.703917
Range13.702895
Interquartile range (IQR)0.75457485

Descriptive statistics

Standard deviation3.8909869
Coefficient of variation (CV)2.5317691
Kurtosis11.058627
Mean1.5368648
Median Absolute Deviation (MAD)0.078109625
Skewness3.2883845
Sum18.442378
Variance15.139779
MonotonicityNot monotonic
2024-01-14T22:30:34.642603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0.40304171 1
 
4.0%
2.26730539 1
 
4.0%
0.6449225 1
 
4.0%
0.00992682 1
 
4.0%
0.02233534 1
 
4.0%
0.00102234 1
 
4.0%
0.09424072 1
 
4.0%
1.16046473 1
 
4.0%
0.00548037 1
 
4.0%
0.06123957 1
 
4.0%
Other values (2) 2
 
8.0%
(Missing) 13
52.0%
ValueCountFrequency (%)
0.00102234 1
4.0%
0.00548037 1
4.0%
0.00992682 1
4.0%
0.02233534 1
4.0%
0.06123957 1
4.0%
0.06848124 1
4.0%
0.09424072 1
4.0%
0.40304171 1
4.0%
0.6449225 1
4.0%
1.16046473 1
4.0%
ValueCountFrequency (%)
13.70391712 1
4.0%
2.26730539 1
4.0%
1.16046473 1
4.0%
0.6449225 1
4.0%
0.40304171 1
4.0%
0.09424072 1
4.0%
0.06848124 1
4.0%
0.06123957 1
4.0%
0.02233534 1
4.0%
0.00992682 1
4.0%

9등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct11
Distinct (%)100.0%
Missing14
Missing (%)56.0%
Infinite0
Infinite (%)0.0%
Mean2.0487821
Minimum0.00208375
Maximum7.704997
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-01-14T22:30:34.818467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00208375
5-th percentile0.0024781
Q10.0332898
median0.08194737
Q33.5690054
95-th percentile6.9948261
Maximum7.704997
Range7.7029132
Interquartile range (IQR)3.5357156

Descriptive statistics

Standard deviation2.9287188
Coefficient of variation (CV)1.4294926
Kurtosis-0.27972942
Mean2.0487821
Median Absolute Deviation (MAD)0.07986362
Skewness1.1795883
Sum22.536603
Variance8.5773937
MonotonicityNot monotonic
2024-01-14T22:30:34.999232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
6.28465521 1
 
4.0%
5.32393074 1
 
4.0%
1.81408009 1
 
4.0%
0.08194737 1
 
4.0%
0.00208375 1
 
4.0%
0.0179466 1
 
4.0%
0.0576275 1
 
4.0%
1.1978293 1
 
4.0%
0.00287245 1
 
4.0%
0.048633 1
 
4.0%
(Missing) 14
56.0%
ValueCountFrequency (%)
0.00208375 1
4.0%
0.00287245 1
4.0%
0.0179466 1
4.0%
0.048633 1
4.0%
0.0576275 1
4.0%
0.08194737 1
4.0%
1.1978293 1
4.0%
1.81408009 1
4.0%
5.32393074 1
4.0%
6.28465521 1
4.0%
ValueCountFrequency (%)
7.70499698 1
4.0%
6.28465521 1
4.0%
5.32393074 1
4.0%
1.81408009 1
4.0%
1.1978293 1
4.0%
0.08194737 1
4.0%
0.0576275 1
4.0%
0.048633 1
4.0%
0.0179466 1
4.0%
0.00287245 1
4.0%

10등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct10
Distinct (%)100.0%
Missing15
Missing (%)60.0%
Infinite0
Infinite (%)0.0%
Mean1.3278712
Minimum0.00178301
Maximum10.682115
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-01-14T22:30:35.196285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00178301
5-th percentile0.0020340245
Q10.017654287
median0.10200174
Q30.31264594
95-th percentile6.6683298
Maximum10.682115
Range10.680332
Interquartile range (IQR)0.29499165

Descriptive statistics

Standard deviation3.3296026
Coefficient of variation (CV)2.5074742
Kurtosis9.2907486
Mean1.3278712
Median Absolute Deviation (MAD)0.099939825
Skewness3.0234796
Sum13.278712
Variance11.086254
MonotonicityNot monotonic
2024-01-14T22:30:35.349025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0.23373154 1
 
4.0%
0.00178301 1
 
4.0%
0.0704426 1
 
4.0%
1.76259201 1
 
4.0%
0.13356088 1
 
4.0%
0.33895074 1
 
4.0%
0.00234082 1
 
4.0%
0.04448331 1
 
4.0%
0.00871128 1
 
4.0%
10.68211533 1
 
4.0%
(Missing) 15
60.0%
ValueCountFrequency (%)
0.00178301 1
4.0%
0.00234082 1
4.0%
0.00871128 1
4.0%
0.04448331 1
4.0%
0.0704426 1
4.0%
0.13356088 1
4.0%
0.23373154 1
4.0%
0.33895074 1
4.0%
1.76259201 1
4.0%
10.68211533 1
4.0%
ValueCountFrequency (%)
10.68211533 1
4.0%
1.76259201 1
4.0%
0.33895074 1
4.0%
0.23373154 1
4.0%
0.13356088 1
4.0%
0.0704426 1
4.0%
0.04448331 1
4.0%
0.00871128 1
4.0%
0.00234082 1
4.0%
0.00178301 1
4.0%

11등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct9
Distinct (%)100.0%
Missing16
Missing (%)64.0%
Infinite0
Infinite (%)0.0%
Mean2.3103092
Minimum0.00062236
Maximum10.590579
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-01-14T22:30:35.481419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00062236
5-th percentile0.001517264
Q10.02117195
median0.23556255
Q33.9080563
95-th percentile8.3419066
Maximum10.590579
Range10.589957
Interquartile range (IQR)3.8868844

Descriptive statistics

Standard deviation3.6246932
Coefficient of variation (CV)1.5689213
Kurtosis3.0130831
Mean2.3103092
Median Absolute Deviation (MAD)0.23494019
Skewness1.7943235
Sum20.792782
Variance13.138401
MonotonicityNot monotonic
2024-01-14T22:30:35.655486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.23556255 1
 
4.0%
0.00062236 1
 
4.0%
0.08605525 1
 
4.0%
3.9080563 1
 
4.0%
0.97897752 1
 
4.0%
4.96889761 1
 
4.0%
0.00285962 1
 
4.0%
0.02117195 1
 
4.0%
10.59057919 1
 
4.0%
(Missing) 16
64.0%
ValueCountFrequency (%)
0.00062236 1
4.0%
0.00285962 1
4.0%
0.02117195 1
4.0%
0.08605525 1
4.0%
0.23556255 1
4.0%
0.97897752 1
4.0%
3.9080563 1
4.0%
4.96889761 1
4.0%
10.59057919 1
4.0%
ValueCountFrequency (%)
10.59057919 1
4.0%
4.96889761 1
4.0%
3.9080563 1
4.0%
0.97897752 1
4.0%
0.23556255 1
4.0%
0.08605525 1
4.0%
0.02117195 1
4.0%
0.00285962 1
4.0%
0.00062236 1
4.0%

12등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct11
Distinct (%)100.0%
Missing14
Missing (%)56.0%
Infinite0
Infinite (%)0.0%
Mean4.9424502
Minimum0.00174543
Maximum22.371674
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-01-14T22:30:35.876654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00174543
5-th percentile0.00220224
Q10.12832333
median0.7143451
Q38.5609399
95-th percentile17.363342
Maximum22.371674
Range22.369929
Interquartile range (IQR)8.4326165

Descriptive statistics

Standard deviation7.3661169
Coefficient of variation (CV)1.4903776
Kurtosis2.039632
Mean4.9424502
Median Absolute Deviation (MAD)0.71168605
Skewness1.5918117
Sum54.366952
Variance54.259678
MonotonicityNot monotonic
2024-01-14T22:30:36.066650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
12.3550098 1
 
4.0%
10.71609113 1
 
4.0%
1.29401855 1
 
4.0%
0.24897355 1
 
4.0%
0.00265905 1
 
4.0%
0.7143451 1
 
4.0%
6.40578857 1
 
4.0%
0.00174543 1
 
4.0%
0.21836529 1
 
4.0%
0.03828138 1
 
4.0%
(Missing) 14
56.0%
ValueCountFrequency (%)
0.00174543 1
4.0%
0.00265905 1
4.0%
0.03828138 1
4.0%
0.21836529 1
4.0%
0.24897355 1
4.0%
0.7143451 1
4.0%
1.29401855 1
4.0%
6.40578857 1
4.0%
10.71609113 1
4.0%
12.3550098 1
4.0%
ValueCountFrequency (%)
22.37167415 1
4.0%
12.3550098 1
4.0%
10.71609113 1
4.0%
6.40578857 1
4.0%
1.29401855 1
4.0%
0.7143451 1
4.0%
0.24897355 1
4.0%
0.21836529 1
4.0%
0.03828138 1
4.0%
0.00265905 1
4.0%

13등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct10
Distinct (%)100.0%
Missing15
Missing (%)60.0%
Infinite0
Infinite (%)0.0%
Mean3.4792265
Minimum0.00212879
Maximum30.454145
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-01-14T22:30:36.218848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00212879
5-th percentile0.0026302385
Q10.057126018
median0.1855255
Q30.36989977
95-th percentile18.169708
Maximum30.454145
Range30.452016
Interquartile range (IQR)0.31277376

Descriptive statistics

Standard deviation9.5258706
Coefficient of variation (CV)2.7379277
Kurtosis9.7211628
Mean3.4792265
Median Absolute Deviation (MAD)0.1639532
Skewness3.1060392
Sum34.792265
Variance90.742211
MonotonicityNot monotonic
2024-01-14T22:30:36.456294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0.24659988 1
 
4.0%
0.24292676 1
 
4.0%
0.00324312 1
 
4.0%
0.03990148 1
 
4.0%
0.12812425 1
 
4.0%
3.15539708 1
 
4.0%
0.41099974 1
 
4.0%
0.00212879 1
 
4.0%
0.10879963 1
 
4.0%
30.45414476 1
 
4.0%
(Missing) 15
60.0%
ValueCountFrequency (%)
0.00212879 1
4.0%
0.00324312 1
4.0%
0.03990148 1
4.0%
0.10879963 1
4.0%
0.12812425 1
4.0%
0.24292676 1
4.0%
0.24659988 1
4.0%
0.41099974 1
4.0%
3.15539708 1
4.0%
30.45414476 1
4.0%
ValueCountFrequency (%)
30.45414476 1
4.0%
3.15539708 1
4.0%
0.41099974 1
4.0%
0.24659988 1
4.0%
0.24292676 1
4.0%
0.12812425 1
4.0%
0.10879963 1
4.0%
0.03990148 1
4.0%
0.00324312 1
4.0%
0.00212879 1
4.0%

14등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7
Distinct (%)100.0%
Missing18
Missing (%)72.0%
Infinite0
Infinite (%)0.0%
Mean4.9111491
Minimum0.00112888
Maximum32.16288
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-01-14T22:30:36.632965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00112888
5-th percentile0.001568278
Q10.06024448
median0.3121914
Q30.89067714
95-th percentile22.823095
Maximum32.16288
Range32.161751
Interquartile range (IQR)0.83043266

Descriptive statistics

Standard deviation12.023256
Coefficient of variation (CV)2.4481554
Kurtosis6.9761867
Mean4.9111491
Median Absolute Deviation (MAD)0.31106252
Skewness2.6398964
Sum34.378044
Variance144.55869
MonotonicityNot monotonic
2024-01-14T22:30:36.810879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0.00112888 1
 
4.0%
0.3121914 1
 
4.0%
1.03026369 1
 
4.0%
0.75109059 1
 
4.0%
0.00259354 1
 
4.0%
0.11789542 1
 
4.0%
32.16288032 1
 
4.0%
(Missing) 18
72.0%
ValueCountFrequency (%)
0.00112888 1
4.0%
0.00259354 1
4.0%
0.11789542 1
4.0%
0.3121914 1
4.0%
0.75109059 1
4.0%
1.03026369 1
4.0%
32.16288032 1
4.0%
ValueCountFrequency (%)
32.16288032 1
4.0%
1.03026369 1
4.0%
0.75109059 1
4.0%
0.3121914 1
4.0%
0.11789542 1
4.0%
0.00259354 1
4.0%
0.00112888 1
4.0%

15등급
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct11
Distinct (%)100.0%
Missing14
Missing (%)56.0%
Infinite0
Infinite (%)0.0%
Mean8.4051873
Minimum0
Maximum61.454058
Zeros1
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-01-14T22:30:36.982420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.034961895
Q10.3052332
median1.8011314
Q34.3269287
95-th percentile39.003677
Maximum61.454058
Range61.454058
Interquartile range (IQR)4.0216955

Descriptive statistics

Standard deviation18.235519
Coefficient of variation (CV)2.1695553
Kurtosis9.0139618
Mean8.4051873
Median Absolute Deviation (MAD)1.6140885
Skewness2.9522198
Sum92.45706
Variance332.53415
MonotonicityNot monotonic
2024-01-14T22:30:37.129349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.0 1
 
4.0%
2.7 1
 
4.0%
3.04780001 1
 
4.0%
0.18704287 1
 
4.0%
16.55329485 1
 
4.0%
0.06992379 1
 
4.0%
0.61432809 1
 
4.0%
1.80113139 1
 
4.0%
0.42342352 1
 
4.0%
5.60605734 1
 
4.0%
(Missing) 14
56.0%
ValueCountFrequency (%)
0.0 1
4.0%
0.06992379 1
4.0%
0.18704287 1
4.0%
0.42342352 1
4.0%
0.61432809 1
4.0%
1.80113139 1
4.0%
2.7 1
4.0%
3.04780001 1
4.0%
5.60605734 1
4.0%
16.55329485 1
4.0%
ValueCountFrequency (%)
61.4540583 1
4.0%
16.55329485 1
4.0%
5.60605734 1
4.0%
3.04780001 1
4.0%
2.7 1
4.0%
1.80113139 1
4.0%
0.61432809 1
4.0%
0.42342352 1
4.0%
0.18704287 1
4.0%
0.06992379 1
4.0%

무등급
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct10
Distinct (%)100.0%
Missing15
Missing (%)60.0%
Infinite0
Infinite (%)0.0%
Mean71.043368
Minimum0.01923984
Maximum463.70353
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-01-14T22:30:37.305165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.01923984
5-th percentile0.04532121
Q16.6844989
median23.194207
Q361.470894
95-th percentile289.0526
Maximum463.70353
Range463.68429
Interquartile range (IQR)54.786395

Descriptive statistics

Standard deviation140.54783
Coefficient of variation (CV)1.9783385
Kurtosis9.0094259
Mean71.043368
Median Absolute Deviation (MAD)20.926859
Skewness2.9554352
Sum710.43368
Variance19753.693
MonotonicityNot monotonic
2024-01-14T22:30:37.456386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
4.45749725 1
 
4.0%
69.52581308 1
 
4.0%
75.59034038 1
 
4.0%
13.3655037 1
 
4.0%
0.07719844 1
 
4.0%
26.35083547 1
 
4.0%
463.7035316 1
 
4.0%
0.01923984 1
 
4.0%
20.03757898 1
 
4.0%
37.30613759 1
 
4.0%
(Missing) 15
60.0%
ValueCountFrequency (%)
0.01923984 1
4.0%
0.07719844 1
4.0%
4.45749725 1
4.0%
13.3655037 1
4.0%
20.03757898 1
4.0%
26.35083547 1
4.0%
37.30613759 1
4.0%
69.52581308 1
4.0%
75.59034038 1
4.0%
463.7035316 1
4.0%
ValueCountFrequency (%)
463.7035316 1
4.0%
75.59034038 1
4.0%
69.52581308 1
4.0%
37.30613759 1
4.0%
26.35083547 1
4.0%
20.03757898 1
4.0%
13.3655037 1
4.0%
4.45749725 1
4.0%
0.07719844 1
4.0%
0.01923984 1
4.0%

Interactions

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2024-01-14T22:29:55.950189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:29:57.992603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:00.449896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:02.583707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:04.724655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:06.799068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:09.163120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:11.011492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:13.205255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:16.250711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:18.365741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:20.235705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:22.135537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:24.405493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:26.978859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:29.420269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:29:56.074095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:29:58.119137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:00.571666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:02.732638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:04.848596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:07.296174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:09.258299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:11.150336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:13.333886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:16.452589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:18.482764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:20.362873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:22.253723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:24.521191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:27.165352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:29.566156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:29:56.198870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:29:58.238835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:00.694987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:02.877913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:04.979590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:07.452426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:09.347203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:11.295770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:13.475693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:16.598104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:18.585164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:20.474261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:22.371636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:24.647567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:27.304417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:29.712452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:29:56.418792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:29:58.387588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:00.826653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:03.014706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:05.102807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:07.594738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:09.488902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:11.424765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:13.642415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:16.745269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:18.703746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:20.585452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:22.498402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:24.787898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:30:27.496107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-14T22:30:37.613722image/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
1등급1.0001.0001.0001.0000.9751.0001.0001.0000.3961.0000.8881.0001.0000.8761.0001.0001.000
2등급1.0001.0001.0001.0000.9751.0001.0001.0000.3961.0000.8881.0001.0000.8881.0001.0001.000
3등급1.0001.0001.0001.0001.0001.0001.0000.9900.3961.0000.8960.9491.0000.8761.0000.8881.000
4등급1.0000.9750.9751.0001.0001.0000.9770.8201.0001.0000.8880.6811.0000.8881.0000.8960.263
5등급1.0001.0001.0001.0001.0001.0001.0000.9911.0001.0000.8880.9401.0000.8881.0000.9030.504
6등급1.0001.0001.0001.0000.9771.0001.0001.0001.0001.0000.9031.0001.0000.8961.0001.0001.000
7등급1.0001.0001.0000.9900.8200.9911.0001.0000.9111.0000.9030.9561.0000.8961.0000.9080.504
8등급1.0000.3960.3960.3961.0001.0001.0000.9111.0001.0001.0001.0001.0000.8880.0000.888NaN
9등급1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000NaN
10등급1.0000.8880.8880.8960.8880.8880.9030.9031.0001.0001.0001.0001.0001.0001.0001.0000.000
11등급1.0001.0001.0000.9490.6810.9401.0000.9561.0001.0001.0001.0001.0001.0001.0001.0001.000
12등급1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000NaN
13등급1.0000.8760.8880.8760.8880.8880.8960.8960.8881.0001.0001.0001.0001.0001.0001.0000.000
14등급1.0001.0001.0001.0001.0001.0001.0001.0000.0001.0001.0001.0001.0001.0001.0001.0000.000
15등급1.0001.0001.0000.8880.8960.9031.0000.9080.8881.0001.0001.0001.0001.0001.0001.0000.000
무등급1.0001.0001.0001.0000.2630.5041.0000.504NaNNaN0.0001.000NaN0.0000.0000.0001.000
2024-01-14T22:30:37.859678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1등급2등급3등급4등급5등급6등급7등급8등급9등급10등급11등급12등급13등급14등급15등급무등급
1등급1.0000.9450.9640.9150.9760.9910.9090.6190.8210.5950.7860.5710.6070.6790.5480.886
2등급0.9451.0000.9390.9390.9520.9360.9360.8100.8100.7620.7860.6670.6900.7860.8100.886
3등급0.9640.9391.0000.9270.9880.9270.8910.8330.9640.7000.8100.8100.7140.7500.5480.943
4등급0.9150.9390.9271.0000.8450.9270.8730.6670.8330.7860.7860.6170.7860.8210.7000.821
5등급0.9760.9520.9880.8451.0000.8640.9340.8330.9050.6670.7860.7830.6670.6790.4180.405
6등급0.9910.9360.9270.9270.8641.0000.8390.6640.7000.5880.7860.4670.7000.6790.5500.929
7등급0.9090.9360.8910.8730.9340.8391.0000.9300.9520.8060.8000.9270.8670.8570.5030.619
8등급0.6190.8100.8330.6670.8330.6640.9301.0000.8790.8331.0000.9000.8811.0000.6670.900
9등급0.8210.8100.9640.8330.9050.7000.9520.8791.0001.0000.9430.9640.9521.0000.3930.900
10등급0.5950.7620.7000.7860.6670.5880.8060.8331.0001.0000.9640.9520.9761.0000.7710.700
11등급0.7860.7860.8100.7860.7860.7860.8001.0000.9430.9641.0000.9430.8860.9430.9000.886
12등급0.5710.6670.8100.6170.7830.4670.9270.9000.9640.9520.9431.0000.9520.9430.3810.900
13등급0.6070.6900.7140.7860.6670.7000.8670.8810.9520.9760.8860.9521.0000.9640.9430.829
14등급0.6790.7860.7500.8210.6790.6790.8571.0001.0001.0000.9430.9430.9641.0000.9000.700
15등급0.5480.8100.5480.7000.4180.5500.5030.6670.3930.7710.9000.3810.9430.9001.0000.786
무등급0.8860.8860.9430.8210.4050.9290.6190.9000.9000.7000.8860.9000.8290.7000.7861.000

Missing values

2024-01-14T22:30:29.917220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-14T22:30:30.221838image/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.
2024-01-14T22:30:30.474599image/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
0PF보증0.5617730.1795310.3298630.0897760.8244780.8074775.1060380.4030426.284655<NA><NA>12.35501<NA><NA>0.0<NA>
1기금건설자금대출보증(주택,준주택)<NA><NA><NA>0.0404030.9894580.302830.9636412.2673055.323931<NA><NA>10.7160910.2466<NA>2.74.457497
2도시재생PF<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3도심주택 특약보증<NA><NA><NA><NA><NA><NA>0.4216960.6449221.81408<NA>0.2355631.294019<NA><NA><NA><NA>
4리모델링사업비보증<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>69.525813
5리츠회사채보증<NA><NA><NA><NA><NA>0.0132590.0162270.009927<NA><NA><NA><NA><NA><NA><NA><NA>
6모기지보증<NA><NA><NA><NA><NA>0.0596640.1460440.0223350.0819470.233732<NA>0.2489740.242927<NA><NA><NA>
7수요자중심형도시재생지원자금보증<NA><NA><NA><NA>0.005894<NA>0.105979<NA><NA><NA><NA><NA><NA><NA>3.047875.59034
8수요자중심형도시재생지원자금특례보증<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>13.365504
9오피스텔분양보증0.0028760.004409<NA><NA><NA>0.0316890.002892<NA><NA><NA><NA><NA><NA><NA><NA><NA>
상품명1등급2등급3등급4등급5등급6등급7등급8등급9등급10등급11등급12등급13등급14등급15등급무등급
15임대보증금보증(사용검사후)0.0247550.3294490.13170.0992590.2051040.4246891.407561.1604651.1978291.7625923.9080566.4057893.1553971.03026416.55329526.350835
16임대주택매입자금보증<NA><NA>0.008124<NA><NA>0.1193281.588231<NA><NA>0.1335610.978978<NA><NA><NA><NA><NA>
17조합사업비대출보증94.67906527.7399447.7249535.1176619.830395269.31693941.881311<NA><NA>0.3389514.968898<NA>0.4110.751091<NA>463.703532
18조합주택시공보증0.0178390.0099970.0025630.002790.0132390.049670.0223960.005480.0028720.0023410.002860.0017450.0021290.0025940.0699240.01924
19주상복합주택분양보증0.1721530.074160.1020640.0706880.0770310.8892370.1198990.061240.0486330.044483<NA>0.218365<NA><NA>0.614328<NA>
20주택분양보증0.7207490.2191970.1930940.1662370.2553092.0857010.2870880.068481<NA>0.008711<NA>0.0382810.10880.1178951.801131<NA>
21주택임대보증<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.423424<NA>
22하도급대금지급보증8.5993770.5622632.8759285.4434462.10588524.3475635.16406<NA><NA><NA>0.021172<NA><NA><NA>5.60605720.037579
23하자보수보증12.0281548.0473275.79172510.93730914.92105555.87806132.91000813.7039177.70499710.68211510.59057922.37167430.45414532.1628861.45405837.306138
24후분양대출보증<NA><NA><NA><NA>0.020307<NA>0.243407<NA><NA><NA><NA><NA><NA><NA><NA><NA>