Overview

Dataset statistics

Number of variables8
Number of observations80
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.3 KiB
Average record size in memory67.7 B

Variable types

Text3
DateTime1
Categorical3
Numeric1

Dataset

Description대전광역시 유성구 관내에 있는 도시형생활주택인허가현황으로 건물명칭, 대지위치, 사용승인일, 주용도, 세대수, 동수, 층수, 연면적 등의 데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15118313/fileData.do

Alerts

동수 is highly imbalanced (87.8%)Imbalance

Reproduction

Analysis started2023-12-12 16:31:22.268775
Analysis finished2023-12-12 16:31:23.421283
Duration1.15 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

건물명칭
Text

Distinct76
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size772.0 B
2023-12-13T01:31:23.661745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length9.5
Mean length5.7
Min length2

Characters and Unicode

Total characters456
Distinct characters121
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)92.5%

Sample

1st row와이즈빌
2nd row유성 캠퍼스타워-1
3rd row스타빌
4th row하이랜드1차
5th row도시형 생활주택
ValueCountFrequency (%)
도시형 4
 
4.1%
생활주택 4
 
4.1%
벨포스토 3
 
3.1%
드림하우스 2
 
2.0%
레자미 2
 
2.0%
나이스타운 2
 
2.0%
더 2
 
2.0%
스카이뷰 2
 
2.0%
모나빌 1
 
1.0%
에이스타운3 1
 
1.0%
Other values (75) 75
76.5%
2023-12-13T01:31:24.180156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 39
 
8.6%
32
 
7.0%
리 22
 
4.8%
이 22
 
4.8%
빌 16
 
3.5%
타 16
 
3.5%
차 14
 
3.1%
하 12
 
2.6%
운 11
 
2.4%
팰 8
 
1.8%
Other values (111) 264
57.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 400
87.7%
Space Separator 32
 
7.0%
Decimal Number 19
 
4.2%
Letter Number 4
 
0.9%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 39
 
9.8%
리 22
 
5.5%
이 22
 
5.5%
빌 16
 
4.0%
타 16
 
4.0%
차 14
 
3.5%
하 12
 
3.0%
운 11
 
2.8%
팰 8
 
2.0%
나 8
 
2.0%
Other values (102) 232
58.0%
Decimal Number
ValueCountFrequency (%)
2 8
42.1%
3 5
26.3%
1 3
 
15.8%
4 3
 
15.8%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
50.0%
Ⅰ 1
25.0%
Ⅲ 1
25.0%
Space Separator
ValueCountFrequency (%)
32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 400
87.7%
Common 52
 
11.4%
Latin 4
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 39
 
9.8%
리 22
 
5.5%
이 22
 
5.5%
빌 16
 
4.0%
타 16
 
4.0%
차 14
 
3.5%
하 12
 
3.0%
운 11
 
2.8%
팰 8
 
2.0%
나 8
 
2.0%
Other values (102) 232
58.0%
Common
ValueCountFrequency (%)
32
61.5%
2 8
 
15.4%
3 5
 
9.6%
1 3
 
5.8%
4 3
 
5.8%
- 1
 
1.9%
Latin
ValueCountFrequency (%)
Ⅱ 2
50.0%
Ⅰ 1
25.0%
Ⅲ 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 400
87.7%
ASCII 52
 
11.4%
Number Forms 4
 
0.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 39
 
9.8%
리 22
 
5.5%
이 22
 
5.5%
빌 16
 
4.0%
타 16
 
4.0%
차 14
 
3.5%
하 12
 
3.0%
운 11
 
2.8%
팰 8
 
2.0%
나 8
 
2.0%
Other values (102) 232
58.0%
ASCII
ValueCountFrequency (%)
32
61.5%
2 8
 
15.4%
3 5
 
9.6%
1 3
 
5.8%
4 3
 
5.8%
- 1
 
1.9%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
50.0%
Ⅰ 1
25.0%
Ⅲ 1
25.0%

대지위치
Text

Distinct79
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size772.0 B
2023-12-13T01:31:24.491350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length28
Mean length25.3
Min length16

Characters and Unicode

Total characters2024
Distinct characters61
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)97.5%

Sample

1st row대전광역시 유성구 대학로76번길 29 (궁동)
2nd row대전광역시 유성구 문화원로 106 (봉명동)
3rd row대전광역시 유성구 대학로81번길 32-15 (궁동)
4th row대전광역시 유성구 문화원로 107 (봉명동)
5th row대전광역시 유성구 진잠로 162 (원내동)
ValueCountFrequency (%)
대전광역시 80
22.4%
유성구 76
21.3%
봉명동 27
 
7.6%
온천북로33번길 21
 
5.9%
문화원로 11
 
3.1%
온천북로 5
 
1.4%
대학로 4
 
1.1%
지족동 4
 
1.1%
33번길 3
 
0.8%
대학로76번길 3
 
0.8%
Other values (111) 123
34.5%
2023-12-13T01:31:24.943882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
279
 
13.8%
대 99
 
4.9%
구 83
 
4.1%
3 83
 
4.1%
유 82
 
4.1%
성 82
 
4.1%
광 80
 
4.0%
역 80
 
4.0%
시 80
 
4.0%
로 80
 
4.0%
Other values (51) 996
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1227
60.6%
Decimal Number 357
 
17.6%
Space Separator 279
 
13.8%
Open Punctuation 62
 
3.1%
Close Punctuation 62
 
3.1%
Dash Punctuation 37
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 99
 
8.1%
구 83
 
6.8%
유 82
 
6.7%
성 82
 
6.7%
광 80
 
6.5%
역 80
 
6.5%
시 80
 
6.5%
로 80
 
6.5%
전 80
 
6.5%
동 64
 
5.2%
Other values (37) 417
34.0%
Decimal Number
ValueCountFrequency (%)
3 83
23.2%
1 66
18.5%
2 57
16.0%
6 28
 
7.8%
7 27
 
7.6%
5 24
 
6.7%
4 24
 
6.7%
0 23
 
6.4%
9 13
 
3.6%
8 12
 
3.4%
Space Separator
ValueCountFrequency (%)
279
100.0%
Open Punctuation
ValueCountFrequency (%)
( 62
100.0%
Close Punctuation
ValueCountFrequency (%)
) 62
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1227
60.6%
Common 797
39.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 99
 
8.1%
구 83
 
6.8%
유 82
 
6.7%
성 82
 
6.7%
광 80
 
6.5%
역 80
 
6.5%
시 80
 
6.5%
로 80
 
6.5%
전 80
 
6.5%
동 64
 
5.2%
Other values (37) 417
34.0%
Common
ValueCountFrequency (%)
279
35.0%
3 83
 
10.4%
1 66
 
8.3%
( 62
 
7.8%
) 62
 
7.8%
2 57
 
7.2%
- 37
 
4.6%
6 28
 
3.5%
7 27
 
3.4%
5 24
 
3.0%
Other values (4) 72
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1227
60.6%
ASCII 797
39.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
279
35.0%
3 83
 
10.4%
1 66
 
8.3%
( 62
 
7.8%
) 62
 
7.8%
2 57
 
7.2%
- 37
 
4.6%
6 28
 
3.5%
7 27
 
3.4%
5 24
 
3.0%
Other values (4) 72
 
9.0%
Hangul
ValueCountFrequency (%)
대 99
 
8.1%
구 83
 
6.8%
유 82
 
6.7%
성 82
 
6.7%
광 80
 
6.5%
역 80
 
6.5%
시 80
 
6.5%
로 80
 
6.5%
전 80
 
6.5%
동 64
 
5.2%
Other values (37) 417
34.0%

사용승인일
Date

Distinct78
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size772.0 B
Minimum2009-10-23 00:00:00
Maximum2022-02-10 00:00:00
2023-12-13T01:31:25.094399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:31:25.231885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

주용도
Categorical

Distinct5
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size772.0 B
아파트
37 
원룸
19 
공동주택
15 
연립
5 
다세대
4 

Length

Max length4
Median length3
Mean length2.8875
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
아파트 37
46.2%
원룸 19
23.8%
공동주택 15
18.8%
연립 5
 
6.2%
다세대 4
 
5.0%

Length

2023-12-13T01:31:25.389042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:31:25.518737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
아파트 37
46.2%
원룸 19
23.8%
공동주택 15
18.8%
연립 5
 
6.2%
다세대 4
 
5.0%

세대수
Real number (ℝ)

Distinct51
Distinct (%)63.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean87.6875
Minimum8
Maximum299
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size852.0 B
2023-12-13T01:31:25.669554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile16
Q126.5
median55
Q3130.25
95-th percentile299
Maximum299
Range291
Interquartile range (IQR)103.75

Descriptive statistics

Standard deviation81.38743
Coefficient of variation (CV)0.92815316
Kurtosis1.2312007
Mean87.6875
Median Absolute Deviation (MAD)35
Skewness1.4100907
Sum7015
Variance6623.9138
MonotonicityNot monotonic
2023-12-13T01:31:25.858444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28 6
 
7.5%
299 5
 
6.2%
20 4
 
5.0%
42 3
 
3.8%
24 3
 
3.8%
54 3
 
3.8%
112 3
 
3.8%
143 2
 
2.5%
21 2
 
2.5%
96 2
 
2.5%
Other values (41) 47
58.8%
ValueCountFrequency (%)
8 1
 
1.2%
11 1
 
1.2%
14 1
 
1.2%
16 2
2.5%
17 1
 
1.2%
19 2
2.5%
20 4
5.0%
21 2
2.5%
22 1
 
1.2%
24 3
3.8%
ValueCountFrequency (%)
299 5
6.2%
293 1
 
1.2%
254 1
 
1.2%
240 1
 
1.2%
198 1
 
1.2%
162 1
 
1.2%
160 1
 
1.2%
156 1
 
1.2%
150 1
 
1.2%
149 1
 
1.2%

동수
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size772.0 B
1
78 
3
 
1
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)2.5%

Sample

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

Common Values

ValueCountFrequency (%)
1 78
97.5%
3 1
 
1.2%
2 1
 
1.2%

Length

2023-12-13T01:31:26.002733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:31:26.395346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 78
97.5%
3 1
 
1.2%
2 1
 
1.2%

층수(지하_지상)
Categorical

Distinct33
Distinct (%)41.2%
Missing0
Missing (%)0.0%
Memory size772.0 B
9
15 
5
7 
15
6 
4_15
5 
1_9
 
4
Other values (28)
43 

Length

Max length5
Median length4
Mean length2.425
Min length1

Unique

Unique19 ?
Unique (%)23.8%

Sample

1st row2_8
2nd row12
3rd row7
4th row15
5th row5

Common Values

ValueCountFrequency (%)
9 15
18.8%
5 7
 
8.8%
15 6
 
7.5%
4_15 5
 
6.2%
1_9 4
 
5.0%
8 4
 
5.0%
7 3
 
3.8%
10 3
 
3.8%
2_14 3
 
3.8%
3_10 3
 
3.8%
Other values (23) 27
33.8%

Length

2023-12-13T01:31:26.513156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
9 16
19.3%
5 7
 
8.4%
15 6
 
7.2%
4_15 5
 
6.0%
8 5
 
6.0%
1_9 4
 
4.8%
7 3
 
3.6%
10 3
 
3.6%
2_14 3
 
3.6%
3_10 3
 
3.6%
Other values (23) 28
33.7%

연면적(m2)
Text

Distinct57
Distinct (%)71.2%
Missing0
Missing (%)0.0%
Memory size772.0 B
2023-12-13T01:31:26.749110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length7.825
Min length4

Characters and Unicode

Total characters626
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)42.5%

Sample

1st row2272.0202
2nd row28145.434
3rd row4345.855
4th row2606.3632
5th row1031.625
ValueCountFrequency (%)
2272.0202 2
 
2.5%
12566.9122 2
 
2.5%
5506.62 2
 
2.5%
3541.74 2
 
2.5%
4835.25 2
 
2.5%
1310.69 2
 
2.5%
935.376 2
 
2.5%
9076.3758 2
 
2.5%
8174.0848 2
 
2.5%
4972.31 2
 
2.5%
Other values (46) 60
75.0%
2023-12-13T01:31:27.134621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 80
12.8%
5 77
12.3%
1 74
11.8%
2 64
10.2%
3 63
10.1%
4 55
8.8%
0 49
7.8%
9 48
7.7%
6 40
6.4%
7 39
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 546
87.2%
Other Punctuation 80
 
12.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 77
14.1%
1 74
13.6%
2 64
11.7%
3 63
11.5%
4 55
10.1%
0 49
9.0%
9 48
8.8%
6 40
7.3%
7 39
7.1%
8 37
6.8%
Other Punctuation
ValueCountFrequency (%)
. 80
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 626
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 80
12.8%
5 77
12.3%
1 74
11.8%
2 64
10.2%
3 63
10.1%
4 55
8.8%
0 49
7.8%
9 48
7.7%
6 40
6.4%
7 39
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 626
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 80
12.8%
5 77
12.3%
1 74
11.8%
2 64
10.2%
3 63
10.1%
4 55
8.8%
0 49
7.8%
9 48
7.7%
6 40
6.4%
7 39
6.2%

Interactions

2023-12-13T01:31:23.089761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:31:27.232729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건물명칭대지위치사용승인일주용도세대수동수층수(지하_지상)연면적(m2)
건물명칭1.0000.9950.9870.0001.0001.0000.9970.978
대지위치0.9951.0000.9961.0000.0001.0000.9470.982
사용승인일0.9870.9961.0001.0000.9920.0000.9990.991
주용도0.0001.0001.0001.0000.2210.5140.7860.000
세대수1.0000.0000.9920.2211.0000.0000.7460.743
동수1.0001.0000.0000.5140.0001.0000.0000.000
층수(지하_지상)0.9970.9470.9990.7860.7460.0001.0000.895
연면적(m2)0.9780.9820.9910.0000.7430.0000.8951.000
2023-12-13T01:31:27.352202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
층수(지하_지상)주용도동수
층수(지하_지상)1.0000.4030.000
주용도0.4031.0000.445
동수0.0000.4451.000
2023-12-13T01:31:27.452547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세대수주용도동수층수(지하_지상)
세대수1.0000.0820.0000.298
주용도0.0821.0000.4450.403
동수0.0000.4451.0000.000
층수(지하_지상)0.2980.4030.0001.000

Missing values

2023-12-13T01:31:23.216778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:31:23.357790image/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

건물명칭대지위치사용승인일주용도세대수동수층수(지하_지상)연면적(m2)
0와이즈빌대전광역시 유성구 대학로76번길 29 (궁동)2009-10-23다세대3312_82272.0202
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