Overview

Dataset statistics

Number of variables20
Number of observations8670
Missing cells21443
Missing cells (%)12.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 MiB
Average record size in memory167.0 B

Variable types

Categorical7
Numeric5
DateTime7
Boolean1

Dataset

Description대구도시개발공사 전세임대 보험가입 데이터 입니다. 메타데이터기반 공공데이터 개방자료이기 때문에 가공되지 않은 원본 테이블의 데이터가 등록되었습니다.
URLhttps://www.data.go.kr/data/15120620/fileData.do

Alerts

보험구분 is highly overall correlated with 가격결정방법 and 2 other fieldsHigh correlation
정산금액 is highly overall correlated with 가격결정방법 and 2 other fieldsHigh correlation
수정자번호 is highly overall correlated with 처리여부 and 1 other fieldsHigh correlation
가격결정방법 is highly overall correlated with 보험구분 and 2 other fieldsHigh correlation
보험계약회차 is highly overall correlated with 가격결정방법 and 3 other fieldsHigh correlation
등록자번호 is highly overall correlated with 보험계약회차 and 2 other fieldsHigh correlation
처리여부 is highly overall correlated with 보험구분 and 4 other fieldsHigh correlation
해약신청일자 is highly overall correlated with 부동산결정가격 and 6 other fieldsHigh correlation
부동산결정가격 is highly overall correlated with 해약신청일자High correlation
담보비율 is highly overall correlated with 해약신청일자High correlation
가격결정방법 is highly imbalanced (71.9%)Imbalance
정산금액 is highly imbalanced (99.7%)Imbalance
보험계약회차 is highly imbalanced (66.0%)Imbalance
해약신청일자 is highly imbalanced (97.8%)Imbalance
가격결정일자 has 7571 (87.3%) missing valuesMissing
부동산결정가격 has 340 (3.9%) missing valuesMissing
보험금액 has 96 (1.1%) missing valuesMissing
해지일자 has 3494 (40.3%) missing valuesMissing
처리여부 has 4777 (55.1%) missing valuesMissing
가입신청일자 has 5155 (59.5%) missing valuesMissing
계약횟수 has 2998 (34.6%) zerosZeros
부동산결정가격 has 7080 (81.7%) zerosZeros
담보비율 has 8628 (99.5%) zerosZeros

Reproduction

Analysis started2023-12-12 02:48:35.030018
Analysis finished2023-12-12 02:48:40.448315
Duration5.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

보험구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.9 KiB
화재보험
4777 
보증보험
3893 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
화재보험 4777
55.1%
보증보험 3893
44.9%

Length

2023-12-12T11:48:40.502088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:40.593832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
화재보험 4777
55.1%
보증보험 3893
44.9%

계약자번호
Real number (ℝ)

Distinct1376
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50574512
Minimum12015001
Maximum82023005
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size76.3 KiB
2023-12-12T11:48:40.703125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12015001
5-th percentile12019018
Q142019003
median52014120
Q362017014
95-th percentile82015018
Maximum82023005
Range70008004
Interquartile range (IQR)19998011

Descriptive statistics

Standard deviation20439366
Coefficient of variation (CV)0.40414361
Kurtosis-0.61398389
Mean50574512
Median Absolute Deviation (MAD)9999116.5
Skewness-0.25583051
Sum4.3848102 × 1011
Variance4.1776766 × 1014
MonotonicityNot monotonic
2023-12-12T11:48:40.842139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
52013071 19
 
0.2%
82014015 15
 
0.2%
52015045 15
 
0.2%
52014032 14
 
0.2%
52014111 14
 
0.2%
52014112 14
 
0.2%
52014007 14
 
0.2%
52014104 14
 
0.2%
82014025 14
 
0.2%
12016002 14
 
0.2%
Other values (1366) 8523
98.3%
ValueCountFrequency (%)
12015001 11
0.1%
12015002 2
 
< 0.1%
12016001 8
0.1%
12016002 14
0.2%
12016003 5
 
0.1%
12016004 12
0.1%
12016006 3
 
< 0.1%
12016007 10
0.1%
12016008 10
0.1%
12016009 10
0.1%
ValueCountFrequency (%)
82023005 2
< 0.1%
82023004 2
< 0.1%
82023003 2
< 0.1%
82023002 2
< 0.1%
82023001 2
< 0.1%
82022003 2
< 0.1%
82022002 2
< 0.1%
82022001 2
< 0.1%
82021003 2
< 0.1%
82021002 2
< 0.1%

계약횟수
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3316032
Minimum0
Maximum8
Zeros2998
Zeros (%)34.6%
Negative0
Negative (%)0.0%
Memory size76.3 KiB
2023-12-12T11:48:40.952533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile4
Maximum8
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3202086
Coefficient of variation (CV)0.99144295
Kurtosis0.11516511
Mean1.3316032
Median Absolute Deviation (MAD)1
Skewness0.85781522
Sum11545
Variance1.7429508
MonotonicityNot monotonic
2023-12-12T11:48:41.047175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 2998
34.6%
1 2317
26.7%
2 1703
19.6%
3 966
 
11.1%
4 528
 
6.1%
5 144
 
1.7%
6 8
 
0.1%
7 4
 
< 0.1%
8 2
 
< 0.1%
ValueCountFrequency (%)
0 2998
34.6%
1 2317
26.7%
2 1703
19.6%
3 966
 
11.1%
4 528
 
6.1%
5 144
 
1.7%
6 8
 
0.1%
7 4
 
< 0.1%
8 2
 
< 0.1%
ValueCountFrequency (%)
8 2
 
< 0.1%
7 4
 
< 0.1%
6 8
 
0.1%
5 144
 
1.7%
4 528
 
6.1%
3 966
 
11.1%
2 1703
19.6%
1 2317
26.7%
0 2998
34.6%

계약시작일자
Date

Distinct1824
Distinct (%)21.1%
Missing5
Missing (%)0.1%
Memory size67.9 KiB
Minimum2013-01-01 00:00:00
Maximum2023-12-24 00:00:00
2023-12-12T11:48:41.174112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:41.330347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

계약종료일자
Date

Distinct2121
Distinct (%)24.5%
Missing5
Missing (%)0.1%
Memory size67.9 KiB
Minimum2014-05-08 00:00:00
Maximum2025-12-23 00:00:00
2023-12-12T11:48:41.476866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:41.626995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

가격결정방법
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.9 KiB
<NA>
7416 
개별주택공시
1052 
공동주택공시
 
94
KB부동산
 
52
부동산등기부등본
 
51

Length

Max length8
Median length4
Mean length4.293887
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row개별주택공시
2nd row개별주택공시
3rd row개별주택공시
4th row개별주택공시
5th rowKB부동산

Common Values

ValueCountFrequency (%)
<NA> 7416
85.5%
개별주택공시 1052
 
12.1%
공동주택공시 94
 
1.1%
KB부동산 52
 
0.6%
부동산등기부등본 51
 
0.6%
감정평가 5
 
0.1%

Length

2023-12-12T11:48:41.821175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:41.976366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7416
85.5%
개별주택공시 1052
 
12.1%
공동주택공시 94
 
1.1%
kb부동산 52
 
0.6%
부동산등기부등본 51
 
0.6%
감정평가 5
 
0.1%

가격결정일자
Date

MISSING 

Distinct417
Distinct (%)37.9%
Missing7571
Missing (%)87.3%
Memory size67.9 KiB
Minimum2013-07-01 00:00:00
Maximum2018-06-16 00:00:00
2023-12-12T11:48:42.117259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:42.254912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

부동산결정가격
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct692
Distinct (%)8.3%
Missing340
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean58569415
Minimum0
Maximum7.7436 × 109
Zeros7080
Zeros (%)81.7%
Negative0
Negative (%)0.0%
Memory size76.3 KiB
2023-12-12T11:48:42.445055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4.5176699 × 108
Maximum7.7436 × 109
Range7.7436 × 109
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.1425045 × 108
Coefficient of variation (CV)3.6580603
Kurtosis406.13715
Mean58569415
Median Absolute Deviation (MAD)0
Skewness13.447149
Sum4.8788323 × 1011
Variance4.5903256 × 1016
MonotonicityNot monotonic
2023-12-12T11:48:42.965509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 7080
81.7%
149760000 8
 
0.1%
56700000 8
 
0.1%
77760000 7
 
0.1%
93960000 7
 
0.1%
183060000 6
 
0.1%
178200000 6
 
0.1%
390240000 6
 
0.1%
131220000 6
 
0.1%
124740000 6
 
0.1%
Other values (682) 1190
 
13.7%
(Missing) 340
 
3.9%
ValueCountFrequency (%)
0 7080
81.7%
111294 1
 
< 0.1%
42120000 1
 
< 0.1%
44640000 2
 
< 0.1%
48000000 3
 
< 0.1%
49896000 1
 
< 0.1%
50832000 1
 
< 0.1%
51200000 5
 
0.1%
51354000 1
 
< 0.1%
51840000 2
 
< 0.1%
ValueCountFrequency (%)
7743600000 2
< 0.1%
2413800000 1
< 0.1%
1762812000 2
< 0.1%
1603800000 1
< 0.1%
1458000000 2
< 0.1%
1433003313 1
< 0.1%
1362240000 2
< 0.1%
1339740000 1
< 0.1%
1332000000 1
< 0.1%
1329301293 1
< 0.1%

담보비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct43
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.25270242
Minimum0
Maximum79.72
Zeros8628
Zeros (%)99.5%
Negative0
Negative (%)0.0%
Memory size76.3 KiB
2023-12-12T11:48:43.138112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum79.72
Range79.72
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.8173975
Coefficient of variation (CV)15.106295
Kurtosis275.09229
Mean0.25270242
Median Absolute Deviation (MAD)0
Skewness16.208211
Sum2190.93
Variance14.572523
MonotonicityNot monotonic
2023-12-12T11:48:43.317666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
0.0 8628
99.5%
16.5 1
 
< 0.1%
68.42 1
 
< 0.1%
50.3 1
 
< 0.1%
79.66 1
 
< 0.1%
53.66 1
 
< 0.1%
31.56 1
 
< 0.1%
67.05 1
 
< 0.1%
37.46 1
 
< 0.1%
54.13 1
 
< 0.1%
Other values (33) 33
 
0.4%
ValueCountFrequency (%)
0.0 8628
99.5%
16.5 1
 
< 0.1%
21.79 1
 
< 0.1%
24.92 1
 
< 0.1%
28.29 1
 
< 0.1%
28.67 1
 
< 0.1%
31.56 1
 
< 0.1%
32.64 1
 
< 0.1%
33.75 1
 
< 0.1%
37.0 1
 
< 0.1%
ValueCountFrequency (%)
79.72 1
< 0.1%
79.66 1
< 0.1%
78.44 1
< 0.1%
78.13 1
< 0.1%
76.92 1
< 0.1%
76.14 1
< 0.1%
72.61 1
< 0.1%
68.51 1
< 0.1%
68.42 1
< 0.1%
67.31 1
< 0.1%

보험금액
Real number (ℝ)

MISSING 

Distinct191
Distinct (%)2.2%
Missing96
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean55336892
Minimum0
Maximum6.5 × 108
Zeros46
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size76.3 KiB
2023-12-12T11:48:43.491924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile28500000
Q147500000
median57000000
Q365000000
95-th percentile80000000
Maximum6.5 × 108
Range6.5 × 108
Interquartile range (IQR)17500000

Descriptive statistics

Standard deviation19502074
Coefficient of variation (CV)0.35242446
Kurtosis102.76777
Mean55336892
Median Absolute Deviation (MAD)9500000
Skewness3.0341373
Sum4.7445851 × 1011
Variance3.8033089 × 1014
MonotonicityNot monotonic
2023-12-12T11:48:43.659173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
57000000 812
 
9.4%
60000000 700
 
8.1%
66500000 608
 
7.0%
70000000 572
 
6.6%
61750000 538
 
6.2%
47500000 480
 
5.5%
52250000 443
 
5.1%
50000000 400
 
4.6%
65000000 332
 
3.8%
38000000 305
 
3.5%
Other values (181) 3384
39.0%
ValueCountFrequency (%)
0 46
0.5%
13050 1
 
< 0.1%
14355 1
 
< 0.1%
23100 1
 
< 0.1%
24080 1
 
< 0.1%
24640 1
 
< 0.1%
26180 1
 
< 0.1%
30100 1
 
< 0.1%
30800 2
 
< 0.1%
33110 2
 
< 0.1%
ValueCountFrequency (%)
650000000 1
 
< 0.1%
150000000 6
 
0.1%
145000000 5
 
0.1%
140000000 6
 
0.1%
130000000 12
0.1%
125000000 6
 
0.1%
120000000 18
0.2%
115000000 1
 
< 0.1%
110000000 12
0.1%
105000000 1
 
< 0.1%

정산금액
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.9 KiB
0
8666 
9700
 
1
14400
 
1
2500
 
1
9200
 
1

Length

Max length5
Median length1
Mean length1.0014994
Min length1

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 8666
> 99.9%
9700 1
 
< 0.1%
14400 1
 
< 0.1%
2500 1
 
< 0.1%
9200 1
 
< 0.1%

Length

2023-12-12T11:48:43.806940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:43.928792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 8666
> 99.9%
9700 1
 
< 0.1%
14400 1
 
< 0.1%
2500 1
 
< 0.1%
9200 1
 
< 0.1%

등록자번호
Categorical

HIGH CORRELATION 

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size67.9 KiB
20200305
1194 
20159042
836 
20150230
731 
20190293
695 
19920113
645 
Other values (23)
4569 

Length

Max length8
Median length8
Mean length7.9733564
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20139023
2nd row20139023
3rd row20139023
4th row20139023
5th row20139024

Common Values

ValueCountFrequency (%)
20200305 1194
13.8%
20159042 836
 
9.6%
20150230 731
 
8.4%
20190293 695
 
8.0%
19920113 645
 
7.4%
20090219 620
 
7.2%
20080209 415
 
4.8%
20090218 379
 
4.4%
20050190 373
 
4.3%
20179076 369
 
4.3%
Other values (18) 2413
27.8%

Length

2023-12-12T11:48:44.099187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20200305 1194
13.8%
20159042 836
 
9.6%
20150230 731
 
8.4%
20190293 695
 
8.0%
19920113 645
 
7.4%
20090219 620
 
7.2%
20080209 415
 
4.8%
20090218 379
 
4.4%
20050190 373
 
4.3%
20179076 369
 
4.3%
Other values (18) 2413
27.8%

등록일시
Date

Distinct4721
Distinct (%)54.5%
Missing0
Missing (%)0.0%
Memory size67.9 KiB
Minimum2013-07-02 16:14:43
Maximum2023-08-28 14:42:25
2023-12-12T11:48:44.243243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:44.381062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수정자번호
Categorical

HIGH CORRELATION 

Distinct29
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size67.9 KiB
20200305
1332 
20150230
956 
20190293
936 
20090219
669 
20159042
661 
Other values (24)
4116 

Length

Max length8
Median length8
Mean length7.8698962
Min length4

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row20159042
2nd row20159042
3rd row20159042
4th row20159042
5th row20159042

Common Values

ValueCountFrequency (%)
20200305 1332
15.4%
20150230 956
11.0%
20190293 936
10.8%
20090219 669
 
7.7%
20159042 661
 
7.6%
20050190 617
 
7.1%
20080209 488
 
5.6%
19920107 471
 
5.4%
19920113 425
 
4.9%
19880040 390
 
4.5%
Other values (19) 1725
19.9%

Length

2023-12-12T11:48:44.542355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20200305 1332
15.4%
20150230 956
11.0%
20190293 936
10.8%
20090219 669
 
7.7%
20159042 661
 
7.6%
20050190 617
 
7.1%
20080209 488
 
5.6%
19920107 471
 
5.4%
19920113 425
 
4.9%
19880040 390
 
4.5%
Other values (19) 1725
19.9%

수정일시
Date

Distinct3828
Distinct (%)44.2%
Missing0
Missing (%)0.0%
Memory size67.9 KiB
Minimum2014-02-20 15:17:08
Maximum2023-08-28 14:43:50
2023-12-12T11:48:44.684610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:44.817922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

해지일자
Date

MISSING 

Distinct1535
Distinct (%)29.7%
Missing3494
Missing (%)40.3%
Memory size67.9 KiB
Minimum2014-02-20 00:00:00
Maximum2024-10-17 00:00:00
2023-12-12T11:48:44.976110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:45.146240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

보험계약회차
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.9 KiB
1
7641 
2
1013 
3
 
16

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 7641
88.1%
2 1013
 
11.7%
3 16
 
0.2%

Length

2023-12-12T11:48:45.269645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:45.388622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 7641
88.1%
2 1013
 
11.7%
3 16
 
0.2%

처리여부
Boolean

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)0.1%
Missing4777
Missing (%)55.1%
Memory size17.1 KiB
True
2532 
False
1361 
(Missing)
4777 
ValueCountFrequency (%)
True 2532
29.2%
False 1361
 
15.7%
(Missing) 4777
55.1%
2023-12-12T11:48:45.491405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

가입신청일자
Date

MISSING 

Distinct111
Distinct (%)3.2%
Missing5155
Missing (%)59.5%
Memory size67.9 KiB
Minimum2017-01-01 00:00:00
Maximum2023-07-06 00:00:00
2023-12-12T11:48:45.616547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:45.745974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

해약신청일자
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.9 KiB
<NA>
8630 
2021-03-05
 
36
2023-07-06
 
3
2018-12-27
 
1

Length

Max length10
Median length4
Mean length4.0276817
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 8630
99.5%
2021-03-05 36
 
0.4%
2023-07-06 3
 
< 0.1%
2018-12-27 1
 
< 0.1%

Length

2023-12-12T11:48:45.904662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:46.069582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8630
99.5%
2021-03-05 36
 
0.4%
2023-07-06 3
 
< 0.1%
2018-12-27 1
 
< 0.1%

Interactions

2023-12-12T11:48:39.332114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:36.933469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:37.499748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:38.337350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:38.853627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:39.420073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:37.038636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:37.649345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:38.460400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:38.945969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:39.520800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:37.140351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:37.777085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:38.568999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:39.038516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:39.617838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:37.257820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:38.124152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:38.665466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:39.140548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:39.733546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:37.376456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:38.231548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:38.759531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:39.239001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:48:46.156748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
보험구분계약자번호계약횟수가격결정방법부동산결정가격담보비율보험금액정산금액등록자번호수정자번호보험계약회차처리여부해약신청일자
보험구분1.0000.0000.043NaN0.1100.0710.1760.0000.4710.4920.202NaN1.000
계약자번호0.0001.0000.2370.1180.0620.0000.4170.0000.4680.3840.0670.2630.000
계약횟수0.0430.2371.0000.0000.0520.0470.0910.0000.6950.5300.2460.3280.000
가격결정방법NaN0.1180.0001.0000.1230.0000.075NaN0.0990.169NaN0.083NaN
부동산결정가격0.1100.0620.0520.1231.0000.0000.0300.0000.2870.1680.0350.093NaN
담보비율0.0710.0000.0470.0000.0001.0000.0000.0000.3110.3920.0000.135NaN
보험금액0.1760.4170.0910.0750.0300.0001.0000.0000.5390.4580.1510.0820.294
정산금액0.0000.0000.000NaN0.0000.0000.0001.0000.0000.0000.000NaNNaN
등록자번호0.4710.4680.6950.0990.2870.3110.5390.0001.0000.9220.7810.9261.000
수정자번호0.4920.3840.5300.1690.1680.3920.4580.0000.9221.0000.5430.9001.000
보험계약회차0.2020.0670.246NaN0.0350.0000.1510.0000.7810.5431.000NaNNaN
처리여부NaN0.2630.3280.0830.0930.1350.082NaN0.9260.900NaN1.0000.367
해약신청일자1.0000.0000.000NaNNaNNaN0.294NaN1.0001.000NaN0.3671.000
2023-12-12T11:48:46.330921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
보험구분정산금액수정자번호가격결정방법보험계약회차등록자번호처리여부해약신청일자
보험구분1.0000.0000.4221.0000.3310.3741.0000.987
정산금액0.0001.0000.0001.0000.0000.0001.0001.000
수정자번호0.4220.0001.0000.0840.3290.4860.7660.987
가격결정방법1.0001.0000.0841.0001.0000.0500.101NaN
보험계약회차0.3310.0000.3291.0001.0000.5731.0001.000
등록자번호0.3740.0000.4860.0500.5731.0000.7990.986
처리여부1.0001.0000.7660.1011.0000.7991.0000.238
해약신청일자0.9871.0000.987NaN1.0000.9860.2381.000
2023-12-12T11:48:46.505334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
계약자번호계약횟수부동산결정가격담보비율보험금액보험구분가격결정방법정산금액등록자번호수정자번호보험계약회차처리여부해약신청일자
계약자번호1.0000.0720.061-0.004-0.1290.0000.0750.0000.2000.1620.0420.1970.000
계약횟수0.0721.000-0.269-0.082-0.0260.0430.0000.0000.3420.2290.1110.3280.000
부동산결정가격0.061-0.2691.0000.164-0.2290.1340.0460.0000.1420.0800.0260.1141.000
담보비율-0.004-0.0820.1641.000-0.1140.0710.0000.0000.1210.1580.0000.1351.000
보험금액-0.129-0.026-0.229-0.1141.0000.1170.0560.0000.2830.2550.1430.1350.091
보험구분0.0000.0430.1340.0710.1171.0001.0000.0000.3740.4220.3311.0000.987
가격결정방법0.0750.0000.0460.0000.0561.0001.0001.0000.0500.0841.0000.1010.000
정산금액0.0000.0000.0000.0000.0000.0001.0001.0000.0000.0000.0001.0001.000
등록자번호0.2000.3420.1420.1210.2830.3740.0500.0001.0000.4860.5730.7990.986
수정자번호0.1620.2290.0800.1580.2550.4220.0840.0000.4861.0000.3290.7660.987
보험계약회차0.0420.1110.0260.0000.1430.3311.0000.0000.5730.3291.0001.0001.000
처리여부0.1970.3280.1140.1350.1351.0000.1011.0000.7990.7661.0001.0000.238
해약신청일자0.0000.0001.0001.0000.0910.9870.0001.0000.9860.9871.0000.2381.000

Missing values

2023-12-12T11:48:39.904208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:48:40.145784image/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.
2023-12-12T11:48:40.334707image/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

보험구분계약자번호계약횟수계약시작일자계약종료일자가격결정방법가격결정일자부동산결정가격담보비율보험금액정산금액등록자번호등록일시수정자번호수정일시해지일자보험계약회차처리여부가입신청일자해약신청일자
0보증보험5201308302013-11-072015-11-06개별주택공시2013-11-073758400000.0338800201390232013-10-30 14:41:48201590422015-10-05 11:05:372015-10-051N<NA><NA>
1보증보험5201308402013-01-012015-12-31개별주택공시2013-11-071598400000.0770000201390232013-10-30 14:54:34201590422015-11-09 11:19:582015-11-061N<NA><NA>
2보증보험5201308502013-01-012015-12-31개별주택공시2013-11-073988800000.0462000201390232013-10-30 15:26:15201590422015-11-09 10:58:102015-11-061N<NA><NA>
3보증보험5201308602013-01-012015-12-31개별주택공시2013-11-072448000000.0770000201390232013-10-30 15:39:44201590422015-11-13 14:07:422015-11-061N<NA><NA>
4보증보험5201308702013-01-012015-12-31KB부동산2013-11-12900000000.01001000201390242013-11-07 14:08:45201590422015-11-23 15:34:222015-11-111N<NA><NA>
5보증보험5201308802013-01-012015-12-31개별주택공시2013-11-125356800000.0770000201390242013-11-07 14:18:20201590422015-11-30 13:36:542015-11-111N<NA><NA>
6보증보험5201308902013-01-012015-12-31개별주택공시2013-11-121497600000.0539000201390242013-11-07 15:09:54201590422015-11-23 15:58:462015-11-111N<NA><NA>
7보증보험5201309002013-01-012015-12-31개별주택공시2013-11-142289600000.0770000201390242013-11-07 15:20:50201590422015-11-13 14:23:512015-11-131N<NA><NA>
8보증보험8201303502013-01-012015-12-31개별주택공시2013-11-203153600000.0770000201390242013-11-13 13:28:18201590422015-11-23 16:04:032015-11-191N<NA><NA>
9보증보험5201309302013-01-012015-12-31개별주택공시2013-11-222030400000.0847000201390242013-11-13 14:15:01201590422015-11-30 09:58:37<NA>1N<NA><NA>
보험구분계약자번호계약횟수계약시작일자계약종료일자가격결정방법가격결정일자부동산결정가격담보비율보험금액정산금액등록자번호등록일시수정자번호수정일시해지일자보험계약회차처리여부가입신청일자해약신청일자
8660화재보험7201901822023-08-092024-08-09<NA><NA>00.0665000000202003052023-04-20 10:59:46202003052023-04-20 10:59:46<NA>1<NA><NA><NA>
8661보증보험5201901622023-09-062025-09-05<NA><NA>00.0600000000202003052023-04-25 11:47:50202003052023-04-25 11:47:50<NA>1N<NA><NA>
8662화재보험5201901622023-09-062024-09-06<NA><NA>00.0570000000202003052023-04-25 11:47:50202003052023-04-25 11:47:50<NA>1<NA><NA><NA>
8663보증보험2201902312021-07-292023-07-28<NA><NA>00.0600000000200902182021-07-12 18:19:34202003052023-05-08 15:08:492023-07-291Y2021-11-08<NA>
8664보증보험2201902322023-07-292025-07-28<NA><NA>00.0600000000202003052023-05-08 15:08:49202003052023-05-08 15:08:49<NA>1N<NA><NA>
8665화재보험2201902322023-07-292024-07-29<NA><NA>00.0570000000202003052023-05-08 15:08:49202003052023-05-08 15:08:49<NA>1<NA><NA><NA>
8666보증보험8201301752023-06-282025-06-27<NA><NA>00.0700000000202003052023-05-18 16:31:54202003052023-05-18 16:31:54<NA>1N<NA><NA>
8667화재보험8201301752023-06-282024-06-28<NA><NA>00.0665000000202003052023-05-18 16:31:54202003052023-05-18 16:31:54<NA>1<NA><NA><NA>
8668보증보험5201600452023-08-022025-08-01<NA><NA>00.0800000000202003052023-06-15 17:47:15202003052023-06-15 17:47:15<NA>1N<NA><NA>
8669화재보험5201600452023-08-022024-08-02<NA><NA>00.0760000000202003052023-06-15 17:47:15202003052023-06-15 17:47:15<NA>1<NA><NA><NA>