Overview

Dataset statistics

Number of variables9
Number of observations89
Missing cells89
Missing cells (%)11.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.6 KiB
Average record size in memory75.5 B

Variable types

Numeric1
Text1
DateTime3
Categorical3
Unsupported1

Dataset

Description부평구 월별 공동주택 이행보증보험증권 현황입니다.(위치, 건축주, 보증기간 등)ex) 1,인천광역시 부평구 부평동 408-4,이보현, 황정순,2012-11-30,93,2012-11-30,2022-11-29,대한주택보증(서울중앙지점),02-3771-6464
Author인천광역시 부평구
URLhttps://www.data.go.kr/data/3047317/fileData.do

Alerts

전화번호 is highly overall correlated with 보증가입기관High correlation
보증가입기관 is highly overall correlated with 전화번호High correlation
Unnamed: 8 has 89 (100.0%) missing valuesMissing
연번 has unique valuesUnique
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 12:06:55.703266
Analysis finished2023-12-12 12:06:56.753070
Duration1.05 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct89
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45
Minimum1
Maximum89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size933.0 B
2023-12-12T21:06:56.833287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.4
Q123
median45
Q367
95-th percentile84.6
Maximum89
Range88
Interquartile range (IQR)44

Descriptive statistics

Standard deviation25.836021
Coefficient of variation (CV)0.57413381
Kurtosis-1.2
Mean45
Median Absolute Deviation (MAD)22
Skewness0
Sum4005
Variance667.5
MonotonicityStrictly increasing
2023-12-12T21:06:56.991390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.1%
68 1
 
1.1%
66 1
 
1.1%
65 1
 
1.1%
64 1
 
1.1%
63 1
 
1.1%
62 1
 
1.1%
61 1
 
1.1%
60 1
 
1.1%
59 1
 
1.1%
Other values (79) 79
88.8%
ValueCountFrequency (%)
1 1
1.1%
2 1
1.1%
3 1
1.1%
4 1
1.1%
5 1
1.1%
6 1
1.1%
7 1
1.1%
8 1
1.1%
9 1
1.1%
10 1
1.1%
ValueCountFrequency (%)
89 1
1.1%
88 1
1.1%
87 1
1.1%
86 1
1.1%
85 1
1.1%
84 1
1.1%
83 1
1.1%
82 1
1.1%
81 1
1.1%
80 1
1.1%

위치
Text

Distinct87
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size844.0 B
2023-12-12T21:06:57.343124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length18.314607
Min length14

Characters and Unicode

Total characters1630
Distinct characters36
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique86 ?
Unique (%)96.6%

Sample

1st row인천광역시 부평구 부개동 296
2nd row인천광역시 부평구 십정동 181-4
3rd row인천광역시 부평구 부평동 798-16
4th row인천광역시 부평구 갈산동 29-14 외1필지
5th row인천광역시 부평구 십정동 352-5
ValueCountFrequency (%)
인천광역시 89
27.0%
부평동 29
 
8.8%
외1필지 18
 
5.5%
십정동 17
 
5.2%
부개동 17
 
5.2%
외 13
 
3.9%
일신동 9
 
2.7%
부평구 8
 
2.4%
산곡동 8
 
2.4%
외2필지 5
 
1.5%
Other values (101) 117
35.5%
2023-12-12T21:06:57.884136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
241
14.8%
1 130
 
8.0%
천 93
 
5.7%
동 91
 
5.6%
인 89
 
5.5%
광 89
 
5.5%
역 89
 
5.5%
시 89
 
5.5%
- 87
 
5.3%
2 56
 
3.4%
Other values (26) 576
35.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 852
52.3%
Decimal Number 445
27.3%
Space Separator 241
 
14.8%
Dash Punctuation 87
 
5.3%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%
Modifier Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 93
10.9%
동 91
10.7%
인 89
10.4%
광 89
10.4%
역 89
10.4%
시 89
10.4%
부 54
 
6.3%
외 48
 
5.6%
평 37
 
4.3%
필 33
 
3.9%
Other values (11) 140
16.4%
Decimal Number
ValueCountFrequency (%)
1 130
29.2%
2 56
12.6%
4 43
 
9.7%
3 43
 
9.7%
6 36
 
8.1%
5 34
 
7.6%
7 30
 
6.7%
9 25
 
5.6%
0 25
 
5.6%
8 23
 
5.2%
Space Separator
ValueCountFrequency (%)
241
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 87
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 852
52.3%
Common 778
47.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 93
10.9%
동 91
10.7%
인 89
10.4%
광 89
10.4%
역 89
10.4%
시 89
10.4%
부 54
 
6.3%
외 48
 
5.6%
평 37
 
4.3%
필 33
 
3.9%
Other values (11) 140
16.4%
Common
ValueCountFrequency (%)
241
31.0%
1 130
16.7%
- 87
 
11.2%
2 56
 
7.2%
4 43
 
5.5%
3 43
 
5.5%
6 36
 
4.6%
5 34
 
4.4%
7 30
 
3.9%
9 25
 
3.2%
Other values (5) 53
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 852
52.3%
ASCII 778
47.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
241
31.0%
1 130
16.7%
- 87
 
11.2%
2 56
 
7.2%
4 43
 
5.5%
3 43
 
5.5%
6 36
 
4.6%
5 34
 
4.4%
7 30
 
3.9%
9 25
 
3.2%
Other values (5) 53
 
6.8%
Hangul
ValueCountFrequency (%)
천 93
10.9%
동 91
10.7%
인 89
10.4%
광 89
10.4%
역 89
10.4%
시 89
10.4%
부 54
 
6.3%
외 48
 
5.6%
평 37
 
4.3%
필 33
 
3.9%
Other values (11) 140
16.4%

승인일자
Date

Distinct75
Distinct (%)84.3%
Missing0
Missing (%)0.0%
Memory size844.0 B
Minimum2019-09-06 00:00:00
Maximum2023-08-16 00:00:00
2023-12-12T21:06:58.045033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:06:58.247830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

세대수
Categorical

Distinct30
Distinct (%)33.7%
Missing0
Missing (%)0.0%
Memory size844.0 B
8
25 
10
10 
12
6 
11
5 
9
5 
Other values (25)
38 

Length

Max length9
Median length2
Mean length1.6741573
Min length1

Unique

Unique18 ?
Unique (%)20.2%

Sample

1st row28
2nd row8
3rd row25
4th row21
5th row12

Common Values

ValueCountFrequency (%)
8 25
28.1%
10 10
 
11.2%
12 6
 
6.7%
11 5
 
5.6%
9 5
 
5.6%
6 4
 
4.5%
16 4
 
4.5%
23 3
 
3.4%
19 3
 
3.4%
40 2
 
2.2%
Other values (20) 22
24.7%

Length

2023-12-12T21:06:58.445621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
8 25
28.1%
10 10
 
11.2%
12 6
 
6.7%
11 5
 
5.6%
9 5
 
5.6%
6 4
 
4.5%
16 4
 
4.5%
23 3
 
3.4%
19 3
 
3.4%
82 2
 
2.2%
Other values (20) 22
24.7%

보증기간 시작일
Date

Distinct79
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Memory size844.0 B
Minimum2019-08-30 00:00:00
Maximum2023-08-16 00:00:00
2023-12-12T21:06:58.613767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:06:58.780201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

보증기간 종료일
Date

Distinct80
Distinct (%)89.9%
Missing0
Missing (%)0.0%
Memory size844.0 B
Minimum2020-08-06 00:00:00
Maximum2033-08-15 00:00:00
2023-12-12T21:06:58.974560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:06:59.171633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

보증가입기관
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)28.1%
Missing0
Missing (%)0.0%
Memory size844.0 B
서울보증보험주식회사(부평지점)
18 
서울보증보험주식회사(인천지점)
17 
서울보증(부평지점)
10 
서울보증(인천지점)
8 
건설공제조합(인천지점)
5 
Other values (20)
31 

Length

Max length19
Median length18
Mean length14.325843
Min length10

Unique

Unique13 ?
Unique (%)14.6%

Sample

1st row서울보증(인천지점)
2nd row서울보증(부평지점)
3rd row건설공제조합(삼성지점)
4th row서울보증(부평지점)
5th row서울보증(부평지점)

Common Values

ValueCountFrequency (%)
서울보증보험주식회사(부평지점) 18
20.2%
서울보증보험주식회사(인천지점) 17
19.1%
서울보증(부평지점) 10
11.2%
서울보증(인천지점) 8
9.0%
건설공제조합(인천지점) 5
 
5.6%
서울보증(부평지점) 4
 
4.5%
주택도시보증공사(서울동부지사) 3
 
3.4%
건설공제조합(인천지점) 3
 
3.4%
서울보증(송도지점) 2
 
2.2%
서울보증보험주식회사(남대문지점) 2
 
2.2%
Other values (15) 17
19.1%

Length

2023-12-12T21:06:59.346126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울보증보험주식회사(부평지점 18
20.2%
서울보증보험주식회사(인천지점 17
19.1%
서울보증(부평지점 14
15.7%
서울보증(인천지점 9
10.1%
건설공제조합(인천지점 8
9.0%
주택도시보증공사(서울동부지사 3
 
3.4%
서울보증(송도지점 3
 
3.4%
서울보증보험주식회사(남대문지점 2
 
2.2%
서울보증보험주식회사(송도지점 2
 
2.2%
서울보증보험주식회사(부천지점 2
 
2.2%
Other values (10) 11
12.4%

전화번호
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Memory size844.0 B
032-521-0021
32 
032-428-0021
27 
032-859-0021
6 
032-439-7197
5 
032-439-7198
 
3
Other values (10)
16 

Length

Max length12
Median length12
Mean length11.932584
Min length11

Unique

Unique5 ?
Unique (%)5.6%

Sample

1st row032-428-0021
2nd row032-428-0021
3rd row02-3449-2160
4th row032-521-0021
5th row032-521-0021

Common Values

ValueCountFrequency (%)
032-521-0021 32
36.0%
032-428-0021 27
30.3%
032-859-0021 6
 
6.7%
032-439-7197 5
 
5.6%
032-439-7198 3
 
3.4%
02-2050-7838 3
 
3.4%
032-324-0384 2
 
2.2%
02-363-0021 2
 
2.2%
02-777-0021 2
 
2.2%
032-651-0021 2
 
2.2%
Other values (5) 5
 
5.6%

Length

2023-12-12T21:06:59.520315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
032-521-0021 32
36.0%
032-428-0021 27
30.3%
032-859-0021 6
 
6.7%
032-439-7197 5
 
5.6%
032-439-7198 3
 
3.4%
02-2050-7838 3
 
3.4%
032-324-0384 2
 
2.2%
02-363-0021 2
 
2.2%
02-777-0021 2
 
2.2%
032-651-0021 2
 
2.2%
Other values (5) 5
 
5.6%

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing89
Missing (%)100.0%
Memory size933.0 B

Interactions

2023-12-12T21:06:56.330010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:06:59.627878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위치승인일자세대수보증기간 시작일보증기간 종료일보증가입기관전화번호
연번1.0001.0000.9890.0090.9800.9930.8150.477
위치1.0001.0001.0000.0001.0001.0001.0001.000
승인일자0.9891.0001.0000.7350.9991.0000.9960.992
세대수0.0090.0000.7351.0000.0000.0000.8440.844
보증기간 시작일0.9801.0000.9990.0001.0001.0000.9930.992
보증기간 종료일0.9931.0001.0000.0001.0001.0000.9920.991
보증가입기관0.8151.0000.9960.8440.9930.9921.0001.000
전화번호0.4771.0000.9920.8440.9920.9911.0001.000
2023-12-12T21:06:59.812940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전화번호세대수보증가입기관
전화번호1.0000.3330.928
세대수0.3331.0000.340
보증가입기관0.9280.3401.000
2023-12-12T21:06:59.951238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번세대수보증가입기관전화번호
연번1.0000.0000.3970.193
세대수0.0001.0000.3400.333
보증가입기관0.3970.3401.0000.928
전화번호0.1930.3330.9281.000

Missing values

2023-12-12T21:06:56.472846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:06:56.692016image/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

연번위치승인일자세대수보증기간 시작일보증기간 종료일보증가입기관전화번호Unnamed: 8
01인천광역시 부평구 부개동 2962019-09-06282019-09-182029-09-17서울보증(인천지점)032-428-0021<NA>
12인천광역시 부평구 십정동 181-42019-09-1182019-08-302029-08-29서울보증(부평지점)032-428-0021<NA>
23인천광역시 부평구 부평동 798-162019-10-07252019-10-072024-10-06건설공제조합(삼성지점)02-3449-2160<NA>
34인천광역시 부평구 갈산동 29-14 외1필지2019-10-16212019-10-162029-10-15서울보증(부평지점)032-521-0021<NA>
45인천광역시 부평구 십정동 352-52019-12-17122019-12-212029-12-20서울보증(부평지점)032-521-0021<NA>
56인천광역시 부평구 일신동 126-442019-12-1782019-12-212029-12-20서울보증(부평지점)032-521-0021<NA>
67인천광역시 부평구 산곡동 369-227 외1필지2019-12-31402019-12-302029-12-29서울보증(송도지점)032-859-0021<NA>
78인천광역시 십정동 181-112 외 22020-02-0772020-02-102030-02-09서울보증(구로디지털점)02-846-0021<NA>
89인천광역시 십정동 581-32020-02-20192020-02-212030-02-20서울보증(인천지점)032-428-0021<NA>
910인천광역시 십정동 181-122 외 12020-03-13102020-03-102030-03-09서울보증(인천지점)032-428-0021<NA>
연번위치승인일자세대수보증기간 시작일보증기간 종료일보증가입기관전화번호Unnamed: 8
7980인천광역시 십정동 315-49 외1필지2022-11-15102022-11-182032-11-17서울보증보험주식회사(인천지점)032-428-0021<NA>
8081인천광역시 십정동 444-5 외1필지2022-12-0892022-12-122032-12-11건설공제조합(인천지점)032-439-7197<NA>
8182인천광역시 부평동 760-1162022-12-0882022-12-092032-12-08서울보증보험주식회사(부평지점)032-521-0021<NA>
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8384인천광역시 부개동 404-62023-01-1282023-01-132033-01-12서울보증보험주식회사(인천지점)032-428-0021<NA>
8485인천광역시 십정동 493-6 외1필지2023-05-11162023-05-172033-05-16서울보증보험주식회사(인천지점)032-428-0021<NA>
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