Overview

Dataset statistics

Number of variables17
Number of observations224
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory31.4 KiB
Average record size in memory143.6 B

Variable types

Text1
Numeric7
DateTime2
Categorical5
Boolean2

Dataset

Description한국주택금융공사에서 발행한 주택연금부 업무 관련 공개 공공데이터 (해당 부서의 업무와 관련된 데이터베이스에서 공개 가능한 원천 데이터)에 대한 데이터 입니다. 공공데이터 개방 정책에 따라 등록되었습니다. 보증서번호,고객번호,품의번호,당초보증일자,보증기한일자,주택유형코드,대지면적,건물면적,기설정순위,설정율,소유권침해여부,제한물건설정여부,추가설정순위,설정권자,총설정율,비용부담자코드,대지면적2 와 관련된 정보가 포함되어있습니다.
Author한국주택금융공사
URLhttps://www.data.go.kr/data/15073247/fileData.do

Alerts

주택유형코드 has constant value ""Constant
기설정순위 has constant value ""Constant
설정권자 has constant value ""Constant
고객번호 is highly overall correlated with 품의번호High correlation
품의번호 is highly overall correlated with 고객번호High correlation
건물면적 is highly overall correlated with 대지면적2High correlation
설정율 is highly overall correlated with 총설정율High correlation
총설정율 is highly overall correlated with 설정율High correlation
대지면적2 is highly overall correlated with 건물면적High correlation
소유권침해여부 is highly imbalanced (95.9%)Imbalance
추가설정순위 is highly imbalanced (89.7%)Imbalance
비용부담자코드 is highly imbalanced (79.9%)Imbalance
보증서번호 has unique valuesUnique
고객번호 has unique valuesUnique
품의번호 has unique valuesUnique
설정율 has 3 (1.3%) zerosZeros
총설정율 has 3 (1.3%) zerosZeros

Reproduction

Analysis started2023-12-13 00:08:14.774629
Analysis finished2023-12-13 00:08:18.985971
Duration4.21 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

보증서번호
Text

UNIQUE 

Distinct224
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-13T09:08:19.104363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters3136
Distinct characters22
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique224 ?
Unique (%)100.0%

Sample

1st rowRTHO2015000280
2nd rowRTHO2015000391
3rd rowRTHO2019000113
4th rowRQAD2018000247
5th rowRTAC2018000430
ValueCountFrequency (%)
rtho2015000280 1
 
0.4%
rtho2015000391 1
 
0.4%
rtho2016000277 1
 
0.4%
rtho2016000064 1
 
0.4%
rtho2015000062 1
 
0.4%
rtab2014000167 1
 
0.4%
rtac2017000210 1
 
0.4%
rtho2016000725 1
 
0.4%
rtho2013000311 1
 
0.4%
rtho2016000489 1
 
0.4%
Other values (214) 214
95.5%
2023-12-13T09:08:19.362827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 988
31.5%
2 315
 
10.0%
1 314
 
10.0%
A 240
 
7.7%
R 224
 
7.1%
T 192
 
6.1%
3 108
 
3.4%
6 105
 
3.3%
7 99
 
3.2%
5 92
 
2.9%
Other values (12) 459
14.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2240
71.4%
Uppercase Letter 896
 
28.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 240
26.8%
R 224
25.0%
T 192
21.4%
H 89
 
9.9%
O 37
 
4.1%
D 37
 
4.1%
Q 36
 
4.0%
B 18
 
2.0%
C 13
 
1.5%
M 5
 
0.6%
Other values (2) 5
 
0.6%
Decimal Number
ValueCountFrequency (%)
0 988
44.1%
2 315
 
14.1%
1 314
 
14.0%
3 108
 
4.8%
6 105
 
4.7%
7 99
 
4.4%
5 92
 
4.1%
4 85
 
3.8%
9 69
 
3.1%
8 65
 
2.9%

Most occurring scripts

ValueCountFrequency (%)
Common 2240
71.4%
Latin 896
 
28.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 240
26.8%
R 224
25.0%
T 192
21.4%
H 89
 
9.9%
O 37
 
4.1%
D 37
 
4.1%
Q 36
 
4.0%
B 18
 
2.0%
C 13
 
1.5%
M 5
 
0.6%
Other values (2) 5
 
0.6%
Common
ValueCountFrequency (%)
0 988
44.1%
2 315
 
14.1%
1 314
 
14.0%
3 108
 
4.8%
6 105
 
4.7%
7 99
 
4.4%
5 92
 
4.1%
4 85
 
3.8%
9 69
 
3.1%
8 65
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3136
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 988
31.5%
2 315
 
10.0%
1 314
 
10.0%
A 240
 
7.7%
R 224
 
7.1%
T 192
 
6.1%
3 108
 
3.4%
6 105
 
3.3%
7 99
 
3.2%
5 92
 
2.9%
Other values (12) 459
14.6%

고객번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct224
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0273081 × 108
Minimum8139135
Maximum1.3724672 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T09:08:19.476883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8139135
5-th percentile52931274
Q193923212
median1.0960026 × 108
Q31.1595058 × 108
95-th percentile1.2692572 × 108
Maximum1.3724672 × 108
Range1.2910759 × 108
Interquartile range (IQR)22027370

Descriptive statistics

Standard deviation21934340
Coefficient of variation (CV)0.21351278
Kurtosis4.8987842
Mean1.0273081 × 108
Median Absolute Deviation (MAD)9914443
Skewness-1.9206787
Sum2.3011701 × 1010
Variance4.8111529 × 1014
MonotonicityNot monotonic
2023-12-13T09:08:19.582190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
105909539 1
 
0.4%
109135778 1
 
0.4%
101105573 1
 
0.4%
97199567 1
 
0.4%
114405202 1
 
0.4%
114083132 1
 
0.4%
95227868 1
 
0.4%
111940951 1
 
0.4%
106234287 1
 
0.4%
111664062 1
 
0.4%
Other values (214) 214
95.5%
ValueCountFrequency (%)
8139135 1
0.4%
10909120 1
0.4%
16463194 1
0.4%
17782751 1
0.4%
23922660 1
0.4%
36313949 1
0.4%
39822563 1
0.4%
47025750 1
0.4%
47871687 1
0.4%
52320504 1
0.4%
ValueCountFrequency (%)
137246723 1
0.4%
136250943 1
0.4%
136181520 1
0.4%
131148319 1
0.4%
131118682 1
0.4%
130911330 1
0.4%
130750656 1
0.4%
130635292 1
0.4%
130561641 1
0.4%
128393863 1
0.4%

품의번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct224
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0181107 × 1010
Minimum2.0117 × 1010
Maximum2.0207 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T09:08:19.689571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0117 × 1010
5-th percentile2.0137 × 1010
Q12.0167 × 1010
median2.0187 × 1010
Q32.0197 × 1010
95-th percentile2.0207 × 1010
Maximum2.0207 × 1010
Range90000048
Interquartile range (IQR)30000030

Descriptive statistics

Standard deviation22592261
Coefficient of variation (CV)0.0011194758
Kurtosis-0.57022322
Mean2.0181107 × 1010
Median Absolute Deviation (MAD)10000031
Skewness-0.68744186
Sum4.520568 × 1012
Variance5.1041027 × 1014
MonotonicityNot monotonic
2023-12-13T09:08:19.790049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20207000049 1
 
0.4%
20187000013 1
 
0.4%
20177000017 1
 
0.4%
20177000016 1
 
0.4%
20177000015 1
 
0.4%
20177000014 1
 
0.4%
20177000013 1
 
0.4%
20177000012 1
 
0.4%
20177000011 1
 
0.4%
20177000010 1
 
0.4%
Other values (214) 214
95.5%
ValueCountFrequency (%)
20117000001 1
0.4%
20127000001 1
0.4%
20127000002 1
0.4%
20127000003 1
0.4%
20137000001 1
0.4%
20137000002 1
0.4%
20137000003 1
0.4%
20137000004 1
0.4%
20137000005 1
0.4%
20137000006 1
0.4%
ValueCountFrequency (%)
20207000049 1
0.4%
20207000048 1
0.4%
20207000047 1
0.4%
20207000046 1
0.4%
20207000045 1
0.4%
20207000044 1
0.4%
20207000043 1
0.4%
20207000042 1
0.4%
20207000041 1
0.4%
20207000040 1
0.4%

당초보증일자
Date

Distinct211
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum2009-11-11 00:00:00
Maximum2019-12-19 00:00:00
2023-12-13T09:08:19.884898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:19.979741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

보증기한일자
Date

Distinct219
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum2020-03-12 00:00:00
Maximum2061-09-18 00:00:00
2023-12-13T09:08:20.101024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:20.235396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

주택유형코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
아파트
224 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
아파트 224
100.0%

Length

2023-12-13T09:08:20.329681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:08:20.396401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
아파트 224
100.0%

대지면적
Real number (ℝ)

Distinct36
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.6124554
Minimum0.01
Maximum73.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T09:08:20.472974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.01
Q11
median1
Q31
95-th percentile54.5675
Maximum73.08
Range73.07
Interquartile range (IQR)0

Descriptive statistics

Standard deviation16.905772
Coefficient of variation (CV)2.2208041
Kurtosis4.3213783
Mean7.6124554
Median Absolute Deviation (MAD)0
Skewness2.3900911
Sum1705.19
Variance285.80512
MonotonicityNot monotonic
2023-12-13T09:08:20.570064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
1.0 176
78.6%
0.01 14
 
6.2%
39.94 1
 
0.4%
51.74 1
 
0.4%
48.31 1
 
0.4%
53.76 1
 
0.4%
35.85 1
 
0.4%
18.86 1
 
0.4%
45.06 1
 
0.4%
66.0 1
 
0.4%
Other values (26) 26
 
11.6%
ValueCountFrequency (%)
0.01 14
 
6.2%
1.0 176
78.6%
10.0 1
 
0.4%
18.86 1
 
0.4%
23.37 1
 
0.4%
24.0 1
 
0.4%
25.0 1
 
0.4%
29.89 1
 
0.4%
30.0 1
 
0.4%
32.0 1
 
0.4%
ValueCountFrequency (%)
73.08 1
0.4%
66.0 1
0.4%
63.6 1
0.4%
63.04 1
0.4%
62.14 1
0.4%
60.39 1
0.4%
59.12 1
0.4%
59.0 1
0.4%
57.58 1
0.4%
57.21 1
0.4%

건물면적
Real number (ℝ)

HIGH CORRELATION 

Distinct127
Distinct (%)56.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83.634821
Minimum43.84
Maximum167.69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T09:08:20.673897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum43.84
5-th percentile59.125
Q173.9525
median84.875
Q384.99
95-th percentile123.0035
Maximum167.69
Range123.85
Interquartile range (IQR)11.0375

Descriptive statistics

Standard deviation19.996245
Coefficient of variation (CV)0.23908995
Kurtosis2.6181171
Mean83.634821
Median Absolute Deviation (MAD)9.935
Skewness1.1227189
Sum18734.2
Variance399.84983
MonotonicityNot monotonic
2023-12-13T09:08:20.785016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
84.98 13
 
5.8%
84.95 9
 
4.0%
84.97 8
 
3.6%
84.99 7
 
3.1%
84.94 6
 
2.7%
85.46 6
 
2.7%
84.79 5
 
2.2%
59.88 5
 
2.2%
59.99 4
 
1.8%
59.98 4
 
1.8%
Other values (117) 157
70.1%
ValueCountFrequency (%)
43.84 1
 
0.4%
49.93 1
 
0.4%
51.53 1
 
0.4%
51.56 2
0.9%
51.77 4
1.8%
53.98 1
 
0.4%
59.11 2
0.9%
59.21 1
 
0.4%
59.72 1
 
0.4%
59.73 1
 
0.4%
ValueCountFrequency (%)
167.69 1
0.4%
164.04 1
0.4%
150.77 1
0.4%
134.96 1
0.4%
134.91 1
0.4%
134.82 1
0.4%
133.96 1
0.4%
131.86 1
0.4%
131.3 1
0.4%
128.93 1
0.4%

기설정순위
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
선순위
224 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
선순위 224
100.0%

Length

2023-12-13T09:08:20.877362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:08:20.949360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
선순위 224
100.0%

설정율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct187
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7733929
Minimum0
Maximum28
Zeros3
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T09:08:21.029696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.4645
Q11.39
median2.36
Q34.6875
95-th percentile10.2635
Maximum28
Range28
Interquartile range (IQR)3.2975

Descriptive statistics

Standard deviation4.0447993
Coefficient of variation (CV)1.0719264
Kurtosis12.437003
Mean3.7733929
Median Absolute Deviation (MAD)1.235
Skewness2.9871044
Sum845.24
Variance16.360401
MonotonicityNot monotonic
2023-12-13T09:08:21.366874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3
 
1.3%
1.43 3
 
1.3%
1.39 3
 
1.3%
2.2 3
 
1.3%
5.45 3
 
1.3%
1.16 3
 
1.3%
10.13 2
 
0.9%
1.57 2
 
0.9%
2.87 2
 
0.9%
0.87 2
 
0.9%
Other values (177) 198
88.4%
ValueCountFrequency (%)
0.0 3
1.3%
0.26 1
 
0.4%
0.33 1
 
0.4%
0.36 2
0.9%
0.37 1
 
0.4%
0.39 1
 
0.4%
0.43 1
 
0.4%
0.44 1
 
0.4%
0.46 1
 
0.4%
0.49 1
 
0.4%
ValueCountFrequency (%)
28.0 1
0.4%
27.24 1
0.4%
22.55 1
0.4%
17.93 1
0.4%
17.2 1
0.4%
14.75 1
0.4%
13.63 1
0.4%
11.35 1
0.4%
10.91 1
0.4%
10.65 1
0.4%

소유권침해여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size356.0 B
False
223 
True
 
1
ValueCountFrequency (%)
False 223
99.6%
True 1
 
0.4%
2023-12-13T09:08:21.454441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

제한물건설정여부
Boolean

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size356.0 B
False
195 
True
29 
ValueCountFrequency (%)
False 195
87.1%
True 29
 
12.9%
2023-12-13T09:08:21.521713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

추가설정순위
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
선순위
221 
후순위
 
3

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row후순위
2nd row선순위
3rd row후순위
4th row선순위
5th row선순위

Common Values

ValueCountFrequency (%)
선순위 221
98.7%
후순위 3
 
1.3%

Length

2023-12-13T09:08:21.599889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:08:21.678176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
선순위 221
98.7%
후순위 3
 
1.3%

설정권자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
한국주택금융공사
224 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
한국주택금융공사 224
100.0%

Length

2023-12-13T09:08:21.755370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:08:21.825945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한국주택금융공사 224
100.0%

총설정율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct187
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7733929
Minimum0
Maximum28
Zeros3
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T09:08:21.903866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.4645
Q11.39
median2.36
Q34.6875
95-th percentile10.2635
Maximum28
Range28
Interquartile range (IQR)3.2975

Descriptive statistics

Standard deviation4.0447993
Coefficient of variation (CV)1.0719264
Kurtosis12.437003
Mean3.7733929
Median Absolute Deviation (MAD)1.235
Skewness2.9871044
Sum845.24
Variance16.360401
MonotonicityNot monotonic
2023-12-13T09:08:21.998509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3
 
1.3%
1.43 3
 
1.3%
1.39 3
 
1.3%
2.2 3
 
1.3%
5.45 3
 
1.3%
1.16 3
 
1.3%
10.13 2
 
0.9%
1.57 2
 
0.9%
2.87 2
 
0.9%
0.87 2
 
0.9%
Other values (177) 198
88.4%
ValueCountFrequency (%)
0.0 3
1.3%
0.26 1
 
0.4%
0.33 1
 
0.4%
0.36 2
0.9%
0.37 1
 
0.4%
0.39 1
 
0.4%
0.43 1
 
0.4%
0.44 1
 
0.4%
0.46 1
 
0.4%
0.49 1
 
0.4%
ValueCountFrequency (%)
28.0 1
0.4%
27.24 1
0.4%
22.55 1
0.4%
17.93 1
0.4%
17.2 1
0.4%
14.75 1
0.4%
13.63 1
0.4%
11.35 1
0.4%
10.91 1
0.4%
10.65 1
0.4%

비용부담자코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
소유자본인
217 
기타
 
7

Length

Max length5
Median length5
Mean length4.90625
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
소유자본인 217
96.9%
기타 7
 
3.1%

Length

2023-12-13T09:08:22.093015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:08:22.169608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소유자본인 217
96.9%
기타 7
 
3.1%

대지면적2
Real number (ℝ)

HIGH CORRELATION 

Distinct181
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55.009152
Minimum18.62
Maximum147.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T09:08:22.253755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18.62
5-th percentile34.12
Q144.665
median54.395
Q362.6875
95-th percentile81.081
Maximum147.3
Range128.68
Interquartile range (IQR)18.0225

Descriptive statistics

Standard deviation16.365596
Coefficient of variation (CV)0.2975068
Kurtosis4.7510714
Mean55.009152
Median Absolute Deviation (MAD)9.355
Skewness1.3087099
Sum12322.05
Variance267.83275
MonotonicityNot monotonic
2023-12-13T09:08:22.362857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60.96 5
 
2.2%
34.09 3
 
1.3%
44.5 3
 
1.3%
47.33 3
 
1.3%
63.04 3
 
1.3%
36.4 3
 
1.3%
32.17 3
 
1.3%
57.22 3
 
1.3%
68.8 2
 
0.9%
44.79 2
 
0.9%
Other values (171) 194
86.6%
ValueCountFrequency (%)
18.62 1
 
0.4%
18.86 1
 
0.4%
23.37 1
 
0.4%
27.35 1
 
0.4%
29.82 1
 
0.4%
30.89 1
 
0.4%
32.17 3
1.3%
34.09 3
1.3%
34.29 1
 
0.4%
35.06 1
 
0.4%
ValueCountFrequency (%)
147.3 1
0.4%
120.82 1
0.4%
97.93 1
0.4%
95.61 1
0.4%
91.9 1
0.4%
90.81 1
0.4%
90.38 1
0.4%
86.12 1
0.4%
85.57 1
0.4%
84.21 2
0.9%

Interactions

2023-12-13T09:08:18.249959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:15.238259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:15.699360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:16.165441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:16.675576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:17.356981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:17.802576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:18.322567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:15.303548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:15.766331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:16.253032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:16.754711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:17.422692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:17.866953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:18.383228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:15.365509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:15.824501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:16.332288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:16.817939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:17.485841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:17.930941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:18.449910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:15.438752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:15.891705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:16.419828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:16.889226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:17.550617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:17.994548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:18.514860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:15.501973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:15.956220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:16.485317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:16.951391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:17.615041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:18.058816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:18.581846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:15.567422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:16.016879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:16.549488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:17.013741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:17.678512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:18.123176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:18.645385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:15.632942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:16.087329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:16.612012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:17.074798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:17.738038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:08:18.186864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T09:08:22.439891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고객번호품의번호대지면적건물면적설정율소유권침해여부제한물건설정여부추가설정순위총설정율비용부담자코드대지면적2
고객번호1.0000.7400.2050.0000.0000.0000.0000.3070.0000.1990.000
품의번호0.7401.0000.2710.3240.3280.0000.0890.1050.3280.2020.295
대지면적0.2050.2711.0000.0000.2330.0000.0000.0000.2330.3600.327
건물면적0.0000.3240.0001.0000.1070.0000.3660.0000.1070.0000.811
설정율0.0000.3280.2330.1071.0000.0000.2970.0751.0000.0000.000
소유권침해여부0.0000.0000.0000.0000.0001.0000.0500.0000.0000.0000.000
제한물건설정여부0.0000.0890.0000.3660.2970.0501.0000.0000.2970.0000.093
추가설정순위0.3070.1050.0000.0000.0750.0000.0001.0000.0750.0000.000
총설정율0.0000.3280.2330.1071.0000.0000.2970.0751.0000.0000.000
비용부담자코드0.1990.2020.3600.0000.0000.0000.0000.0000.0001.0000.142
대지면적20.0000.2950.3270.8110.0000.0000.0930.0000.0000.1421.000
2023-12-13T09:08:22.537066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용부담자코드제한물건설정여부소유권침해여부추가설정순위
비용부담자코드1.0000.0000.0000.000
제한물건설정여부0.0001.0000.0310.000
소유권침해여부0.0000.0311.0000.000
추가설정순위0.0000.0000.0001.000
2023-12-13T09:08:22.613300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고객번호품의번호대지면적건물면적설정율총설정율대지면적2소유권침해여부제한물건설정여부추가설정순위비용부담자코드
고객번호1.0000.7040.103-0.030-0.005-0.005-0.1500.0000.0000.2510.196
품의번호0.7041.0000.023-0.0570.3440.344-0.0740.0000.0620.0790.188
대지면적0.1030.0231.000-0.044-0.041-0.041-0.1650.0000.0000.0000.271
건물면적-0.030-0.057-0.0441.000-0.070-0.0700.7120.0000.2750.0000.000
설정율-0.0050.344-0.041-0.0701.0001.000-0.0270.0000.2920.0730.000
총설정율-0.0050.344-0.041-0.0701.0001.000-0.0270.0000.2920.0730.000
대지면적2-0.150-0.074-0.1650.712-0.027-0.0271.0000.0000.0910.0000.139
소유권침해여부0.0000.0000.0000.0000.0000.0000.0001.0000.0310.0000.000
제한물건설정여부0.0000.0620.0000.2750.2920.2920.0910.0311.0000.0000.000
추가설정순위0.2510.0790.0000.0000.0730.0730.0000.0000.0001.0000.000
비용부담자코드0.1960.1880.2710.0000.0000.0000.1390.0000.0000.0001.000

Missing values

2023-12-13T09:08:18.762968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:08:18.919822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

보증서번호고객번호품의번호당초보증일자보증기한일자주택유형코드대지면적건물면적기설정순위설정율소유권침해여부제한물건설정여부추가설정순위설정권자총설정율비용부담자코드대지면적2
0RTHO2015000280105909539202070000492015-08-282044-08-21아파트1.059.93선순위6.28NN후순위한국주택금융공사6.28소유자본인36.53
1RTHO2015000391108655437202070000482015-12-172040-12-08아파트1.069.82선순위9.94NN선순위한국주택금융공사9.94소유자본인42.54
2RTHO2019000113126836746202070000472019-02-282041-02-15아파트1.084.94선순위7.34NN후순위한국주택금융공사7.34소유자본인54.71
3RQAD2018000247121371264202070000462018-04-252041-04-13아파트1.0123.08선순위4.62NN선순위한국주택금융공사4.62소유자본인63.96
4RTAC2018000430122246819202070000452018-05-292051-05-21아파트1.084.97선순위7.44NN선순위한국주택금융공사7.44소유자본인75.44
5RQAD2017000780118412741202070000442017-10-232047-10-16아파트1.075.79선순위3.85NN선순위한국주택금융공사3.85소유자본인46.53
6RTHA2019000992108847504202070000432019-12-112050-12-05아파트1.080.0선순위2.22NN선순위한국주택금융공사2.22소유자본인53.35
7RTHA2019000738130561641202070000422019-08-282056-08-13아파트1.060.37선순위17.2NY선순위한국주택금융공사17.2소유자본인43.5
8RTHA2019000246127035300202070000412019-03-142058-02-25아파트1.060.37선순위2.39NN선순위한국주택금융공사2.39소유자본인49.54
9RTHA2019000209126941424202070000402019-03-072061-02-20아파트1.0134.96선순위8.95NN선순위한국주택금융공사8.95소유자본인91.9
보증서번호고객번호품의번호당초보증일자보증기한일자주택유형코드대지면적건물면적기설정순위설정율소유권침해여부제한물건설정여부추가설정순위설정권자총설정율비용부담자코드대지면적2
214RQAD201200048985904612201370000062012-06-252041-05-31아파트1.084.85선순위4.4NN선순위한국주택금융공사4.4소유자본인52.52
215RQAD201200020785957135201370000052012-02-242042-02-06아파트0.0174.81선순위5.45NN선순위한국주택금융공사5.45소유자본인62.57
216RQAD201100052284357804201370000042011-10-242048-10-04아파트1.084.92선순위1.78NN선순위한국주택금융공사1.78소유자본인55.62
217RQAD201200067088545638201370000032012-08-212052-08-10아파트1.084.21선순위0.49NN선순위한국주택금융공사0.49소유자본인52.06
218RQAD201100002581269733201370000022011-02-102040-01-21아파트1.084.92선순위1.93NN선순위한국주택금융공사1.93소유자본인55.62
219RQAD201200078388909795201370000012012-09-212052-09-07아파트1.051.53선순위0.46NN선순위한국주택금융공사0.46소유자본인43.39
220RTAA201200075489158309201270000032012-10-252038-09-26아파트0.0183.45선순위0.51NN선순위한국주택금융공사0.51소유자본인76.86
221RTHO201000002678385206201270000022010-03-302020-03-12아파트1.0113.0선순위27.24NN선순위한국주택금융공사27.24소유자본인67.29
222RTAA201000002755957259201270000012010-03-092048-02-18아파트0.0171.84선순위0.86NN선순위한국주택금융공사0.86기타61.79
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