Overview

Dataset statistics

Number of variables6
Number of observations144
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.3 KiB
Average record size in memory51.9 B

Variable types

Numeric3
Text1
DateTime1
Categorical1

Dataset

Description이행(하자)보증보험증권 예치현황(대지위치, 연면적, 세대수, 사용승인일, 보증사) 등의 항목을 제공합니다.
Author부산광역시 사상구
URLhttps://www.data.go.kr/data/3044355/fileData.do

Alerts

연면적(제곱미터) is highly overall correlated with 세대수High correlation
세대수 is highly overall correlated with 연면적(제곱미터)High correlation
연번 has unique valuesUnique
대지위치 has unique valuesUnique
연면적(제곱미터) has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:52:46.044712
Analysis finished2023-12-12 05:52:47.386759
Duration1.34 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct144
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.5
Minimum1
Maximum144
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T14:52:47.462153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.15
Q136.75
median72.5
Q3108.25
95-th percentile136.85
Maximum144
Range143
Interquartile range (IQR)71.5

Descriptive statistics

Standard deviation41.713307
Coefficient of variation (CV)0.57535596
Kurtosis-1.2
Mean72.5
Median Absolute Deviation (MAD)36
Skewness0
Sum10440
Variance1740
MonotonicityStrictly increasing
2023-12-12T14:52:47.664136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
74 1
 
0.7%
94 1
 
0.7%
95 1
 
0.7%
96 1
 
0.7%
97 1
 
0.7%
98 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
101 1
 
0.7%
Other values (134) 134
93.1%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
144 1
0.7%
143 1
0.7%
142 1
0.7%
141 1
0.7%
140 1
0.7%
139 1
0.7%
138 1
0.7%
137 1
0.7%
136 1
0.7%
135 1
0.7%

대지위치
Text

UNIQUE 

Distinct144
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-12T14:52:48.088621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length34
Mean length27.465278
Min length11

Characters and Unicode

Total characters3955
Distinct characters155
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique144 ?
Unique (%)100.0%

Sample

1st row주례동 92-17/ 주례로34번길 47 (금천빌)
2nd row덕포동 387-5/ 사상로342번길 17
3rd row주례동 55-150/ 가야대로366번길 19-5 (제이에스원룸)
4th row주례동 143-5/ 냉정로 92 (영동뷰2차)
5th row주례동 55-89/ 가야대로378번길 52 (토담하우스)
ValueCountFrequency (%)
주례동 68
 
9.4%
괘법동 37
 
5.1%
외 31
 
4.3%
23
 
3.2%
1필지 16
 
2.2%
모라동 16
 
2.2%
덕포동 10
 
1.4%
2필지 10
 
1.4%
사상로 9
 
1.2%
광장로 8
 
1.1%
Other values (384) 497
68.6%
2023-12-12T14:52:48.645844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
593
 
15.0%
1 214
 
5.4%
2 190
 
4.8%
- 188
 
4.8%
5 165
 
4.2%
동 163
 
4.1%
번 161
 
4.1%
3 159
 
4.0%
로 139
 
3.5%
/ 136
 
3.4%
Other values (145) 1847
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1583
40.0%
Decimal Number 1314
33.2%
Space Separator 593
 
15.0%
Dash Punctuation 188
 
4.8%
Other Punctuation 136
 
3.4%
Open Punctuation 62
 
1.6%
Close Punctuation 62
 
1.6%
Uppercase Letter 9
 
0.2%
Lowercase Letter 8
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 163
 
10.3%
번 161
 
10.2%
로 139
 
8.8%
길 113
 
7.1%
주 87
 
5.5%
례 85
 
5.4%
지 80
 
5.1%
대 55
 
3.5%
사 43
 
2.7%
상 39
 
2.5%
Other values (118) 618
39.0%
Decimal Number
ValueCountFrequency (%)
1 214
16.3%
2 190
14.5%
5 165
12.6%
3 159
12.1%
4 114
8.7%
7 109
8.3%
6 99
7.5%
0 98
7.5%
8 92
7.0%
9 74
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
S 3
33.3%
L 2
22.2%
B 1
 
11.1%
A 1
 
11.1%
K 1
 
11.1%
C 1
 
11.1%
Lowercase Letter
ValueCountFrequency (%)
s 2
25.0%
e 2
25.0%
t 1
12.5%
o 1
12.5%
u 1
12.5%
h 1
12.5%
Space Separator
ValueCountFrequency (%)
593
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 188
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 136
100.0%
Open Punctuation
ValueCountFrequency (%)
( 62
100.0%
Close Punctuation
ValueCountFrequency (%)
) 62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2355
59.5%
Hangul 1583
40.0%
Latin 17
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 163
 
10.3%
번 161
 
10.2%
로 139
 
8.8%
길 113
 
7.1%
주 87
 
5.5%
례 85
 
5.4%
지 80
 
5.1%
대 55
 
3.5%
사 43
 
2.7%
상 39
 
2.5%
Other values (118) 618
39.0%
Common
ValueCountFrequency (%)
593
25.2%
1 214
 
9.1%
2 190
 
8.1%
- 188
 
8.0%
5 165
 
7.0%
3 159
 
6.8%
/ 136
 
5.8%
4 114
 
4.8%
7 109
 
4.6%
6 99
 
4.2%
Other values (5) 388
16.5%
Latin
ValueCountFrequency (%)
S 3
17.6%
s 2
11.8%
L 2
11.8%
e 2
11.8%
t 1
 
5.9%
o 1
 
5.9%
u 1
 
5.9%
B 1
 
5.9%
A 1
 
5.9%
K 1
 
5.9%
Other values (2) 2
11.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2372
60.0%
Hangul 1583
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
593
25.0%
1 214
 
9.0%
2 190
 
8.0%
- 188
 
7.9%
5 165
 
7.0%
3 159
 
6.7%
/ 136
 
5.7%
4 114
 
4.8%
7 109
 
4.6%
6 99
 
4.2%
Other values (17) 405
17.1%
Hangul
ValueCountFrequency (%)
동 163
 
10.3%
번 161
 
10.2%
로 139
 
8.8%
길 113
 
7.1%
주 87
 
5.5%
례 85
 
5.4%
지 80
 
5.1%
대 55
 
3.5%
사 43
 
2.7%
상 39
 
2.5%
Other values (118) 618
39.0%

연면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct144
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2133.2981
Minimum217.5
Maximum37100.11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T14:52:48.815003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum217.5
5-th percentile301.943
Q1498.7
median713.18
Q31386.98
95-th percentile10280.341
Maximum37100.11
Range36882.61
Interquartile range (IQR)888.28

Descriptive statistics

Standard deviation4531.0923
Coefficient of variation (CV)2.1239846
Kurtosis29.058752
Mean2133.2981
Median Absolute Deviation (MAD)271.655
Skewness4.8794446
Sum307194.93
Variance20530798
MonotonicityNot monotonic
2023-12-12T14:52:49.219392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
463.12 1
 
0.7%
8731.51 1
 
0.7%
988.285 1
 
0.7%
317.94 1
 
0.7%
5608.44 1
 
0.7%
2092.46 1
 
0.7%
1712.85 1
 
0.7%
1485.74 1
 
0.7%
659.86 1
 
0.7%
665.7 1
 
0.7%
Other values (134) 134
93.1%
ValueCountFrequency (%)
217.5 1
0.7%
243.5 1
0.7%
243.69 1
0.7%
244.99 1
0.7%
265.5625 1
0.7%
271.29 1
0.7%
284.74 1
0.7%
299.12 1
0.7%
317.94 1
0.7%
323.59 1
0.7%
ValueCountFrequency (%)
37100.11 1
0.7%
22920.84 1
0.7%
19110.7 1
0.7%
17255.84 1
0.7%
12746.33 1
0.7%
11688.77 1
0.7%
11625.52 1
0.7%
10429.17 1
0.7%
9436.98 1
0.7%
8731.51 1
0.7%

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct38
Distinct (%)26.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.104167
Minimum4
Maximum234
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T14:52:49.337109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile8
Q112
median16
Q320
95-th percentile90
Maximum234
Range230
Interquartile range (IQR)8

Descriptive statistics

Standard deviation33.932413
Coefficient of variation (CV)1.3516646
Kurtosis18.204265
Mean25.104167
Median Absolute Deviation (MAD)4
Skewness4.0488764
Sum3615
Variance1151.4087
MonotonicityNot monotonic
2023-12-12T14:52:49.443525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
16 26
18.1%
20 17
11.8%
12 15
 
10.4%
8 15
 
10.4%
9 7
 
4.9%
15 7
 
4.9%
24 6
 
4.2%
19 5
 
3.5%
10 4
 
2.8%
14 4
 
2.8%
Other values (28) 38
26.4%
ValueCountFrequency (%)
4 1
 
0.7%
6 2
 
1.4%
7 2
 
1.4%
8 15
10.4%
9 7
4.9%
10 4
 
2.8%
11 1
 
0.7%
12 15
10.4%
13 1
 
0.7%
14 4
 
2.8%
ValueCountFrequency (%)
234 1
0.7%
213 1
0.7%
150 1
0.7%
143 1
0.7%
125 1
0.7%
119 1
0.7%
112 1
0.7%
90 2
1.4%
66 1
0.7%
61 1
0.7%

사용승인일
Date

Distinct135
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2010-02-19 00:00:00
Maximum2023-02-17 00:00:00
2023-12-12T14:52:49.560264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:52:49.672643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

보증사
Categorical

Distinct4
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
서울보증보험
99 
건설공제조합
38 
서울보증보험주식회사
 
5
주택도시보증공사
 
2

Length

Max length10
Median length6
Mean length6.1666667
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울보증보험
2nd row건설공제조합
3rd row서울보증보험
4th row서울보증보험
5th row서울보증보험

Common Values

ValueCountFrequency (%)
서울보증보험 99
68.8%
건설공제조합 38
 
26.4%
서울보증보험주식회사 5
 
3.5%
주택도시보증공사 2
 
1.4%

Length

2023-12-12T14:52:49.791749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:52:49.897343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울보증보험 99
68.8%
건설공제조합 38
 
26.4%
서울보증보험주식회사 5
 
3.5%
주택도시보증공사 2
 
1.4%

Interactions

2023-12-12T14:52:46.856843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:52:46.259434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:52:46.545434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:52:46.962629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:52:46.374358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:52:46.637947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:52:47.083895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:52:46.462107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:52:46.735889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:52:49.968721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번연면적(제곱미터)세대수보증사
연번1.0000.0000.0840.457
연면적(제곱미터)0.0001.0000.9630.810
세대수0.0840.9631.0000.762
보증사0.4570.8100.7621.000
2023-12-12T14:52:50.060232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번연면적(제곱미터)세대수보증사
연번1.0000.298-0.2090.283
연면적(제곱미터)0.2981.0000.5590.469
세대수-0.2090.5591.0000.423
보증사0.2830.4690.4231.000

Missing values

2023-12-12T14:52:47.208724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:52:47.340535image/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

연번대지위치연면적(제곱미터)세대수사용승인일보증사
01주례동 92-17/ 주례로34번길 47 (금천빌)463.12162010-02-19서울보증보험
12덕포동 387-5/ 사상로342번길 171493.76422010-06-09건설공제조합
23주례동 55-150/ 가야대로366번길 19-5 (제이에스원룸)423.04202010-08-24서울보증보험
34주례동 143-5/ 냉정로 92 (영동뷰2차)705.42232010-12-15서울보증보험
45주례동 55-89/ 가야대로378번길 52 (토담하우스)560.89152011-02-17서울보증보험
56괘법동 525-20/ 사상로233번길 15-5 (베스트빌)483.82162011-04-27서울보증보험
67주례동 54-318/ 주례로9번길 52-4328.92162011-05-18서울보증보험
78주례동 54-64/ 주례로9번길 50474.64182011-05-20서울보증보험
89괘법동 532-5/ 사상로211번길 55 (스카이빌)500.61192011-05-26서울보증보험
910주례동 92-54/ 가야대로330번길 78-7505.56162011-06-02건설공제조합
연번대지위치연면적(제곱미터)세대수사용승인일보증사
134135감전동 276-1번지 / 백양대로561번길 28659.8582022-02-11건설공제조합
135136주례동 88-5번지 / 가야대로306번길 87658.0122022-04-18건설공제조합
136137주례동 166번지 외 2필지1170.5162022-09-02서울보증보험
137138주례동 92-209번지 외 1필지463.5692022-09-29서울보증보험
138139주례동 91번지 외 1필지659.8882022-11-02서울보증보험
139140괘법동 532-47번지568.9582022-11-16서울보증보험
140141주례동 92-233번지 / 주례로28번길 41476.9492023-01-17건설공제조합
141142괘법동 550-2번지 / 사상로170번길 3417255.841502023-01-27건설공제조합
142143주례동 92-40번지 외 1필지398.5792023-02-08건설공제조합
143144주례동 92-38번지 외 1필지408.0392023-02-17건설공제조합