Overview

Dataset statistics

Number of variables9
Number of observations76
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.7 KiB
Average record size in memory76.7 B

Variable types

Numeric3
Text2
Categorical3
DateTime1

Dataset

Description경상남도 하동군에 있는 공동주택 현황 (연번, 건물명, 대지위치, 연면적, 세대수, 동수, 층수, 사용승인일, 비고)의 정보를 제공하고 있습니다.
Author경상남도 하동군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15086629

Alerts

연번 is highly overall correlated with 세대수 and 1 other fieldsHigh correlation
세대수 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
동수 is highly overall correlated with 세대수 and 1 other fieldsHigh correlation
대지위치 is highly overall correlated with 동수High correlation
비고 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-10 22:39:36.761108
Analysis finished2023-12-10 22:39:39.179399
Duration2.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct76
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.5
Minimum1
Maximum76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2023-12-11T07:39:39.235991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.75
Q119.75
median38.5
Q357.25
95-th percentile72.25
Maximum76
Range75
Interquartile range (IQR)37.5

Descriptive statistics

Standard deviation22.083176
Coefficient of variation (CV)0.57358899
Kurtosis-1.2
Mean38.5
Median Absolute Deviation (MAD)19
Skewness0
Sum2926
Variance487.66667
MonotonicityStrictly increasing
2023-12-11T07:39:39.347720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.3%
50 1
 
1.3%
57 1
 
1.3%
56 1
 
1.3%
55 1
 
1.3%
54 1
 
1.3%
53 1
 
1.3%
52 1
 
1.3%
51 1
 
1.3%
49 1
 
1.3%
Other values (66) 66
86.8%
ValueCountFrequency (%)
1 1
1.3%
2 1
1.3%
3 1
1.3%
4 1
1.3%
5 1
1.3%
6 1
1.3%
7 1
1.3%
8 1
1.3%
9 1
1.3%
10 1
1.3%
ValueCountFrequency (%)
76 1
1.3%
75 1
1.3%
74 1
1.3%
73 1
1.3%
72 1
1.3%
71 1
1.3%
70 1
1.3%
69 1
1.3%
68 1
1.3%
67 1
1.3%

건물명
Text

Distinct71
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Memory size740.0 B
2023-12-11T07:39:39.536473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length4
Mean length5.1184211
Min length3

Characters and Unicode

Total characters389
Distinct characters116
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)86.8%

Sample

1st row흥한로얄맨션
2nd row대망파크맨션
3rd row미도빌라
4th row강변타운(한영아파트)
5th row무지개맨션
ValueCountFrequency (%)
대근하버빌타운 2
 
2.6%
연화빌라 2
 
2.6%
금오빌라 2
 
2.6%
성우빌라 2
 
2.6%
흥룡빌라 2
 
2.6%
흥한로얄맨션 1
 
1.3%
동우빌라 1
 
1.3%
노블리앙 1
 
1.3%
동원샤인빌 1
 
1.3%
연화연립 1
 
1.3%
Other values (62) 62
80.5%
2023-12-11T07:39:39.818779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
빌 47
 
12.1%
라 35
 
9.0%
아 14
 
3.6%
파 12
 
3.1%
트 12
 
3.1%
동 11
 
2.8%
하 8
 
2.1%
연 8
 
2.1%
금 8
 
2.1%
대 7
 
1.8%
Other values (106) 227
58.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 376
96.7%
Open Punctuation 4
 
1.0%
Close Punctuation 4
 
1.0%
Decimal Number 2
 
0.5%
Uppercase Letter 2
 
0.5%
Space Separator 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
빌 47
 
12.5%
라 35
 
9.3%
아 14
 
3.7%
파 12
 
3.2%
트 12
 
3.2%
동 11
 
2.9%
하 8
 
2.1%
연 8
 
2.1%
금 8
 
2.1%
대 7
 
1.9%
Other values (99) 214
56.9%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
L 1
50.0%
H 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 376
96.7%
Common 11
 
2.8%
Latin 2
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
빌 47
 
12.5%
라 35
 
9.3%
아 14
 
3.7%
파 12
 
3.2%
트 12
 
3.2%
동 11
 
2.9%
하 8
 
2.1%
연 8
 
2.1%
금 8
 
2.1%
대 7
 
1.9%
Other values (99) 214
56.9%
Common
ValueCountFrequency (%)
( 4
36.4%
) 4
36.4%
2 1
 
9.1%
1 1
 
9.1%
1
 
9.1%
Latin
ValueCountFrequency (%)
L 1
50.0%
H 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 376
96.7%
ASCII 13
 
3.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
빌 47
 
12.5%
라 35
 
9.3%
아 14
 
3.7%
파 12
 
3.2%
트 12
 
3.2%
동 11
 
2.9%
하 8
 
2.1%
연 8
 
2.1%
금 8
 
2.1%
대 7
 
1.9%
Other values (99) 214
56.9%
ASCII
ValueCountFrequency (%)
( 4
30.8%
) 4
30.8%
2 1
 
7.7%
1 1
 
7.7%
1
 
7.7%
L 1
 
7.7%
H 1
 
7.7%

대지위치
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)21.1%
Missing0
Missing (%)0.0%
Memory size740.0 B
하동읍 읍내리
24 
진교면 진교리
18 
하동읍 비파리
8 
하동읍 광평리
8 
옥종면 청룡리
3 
Other values (11)
15 

Length

Max length14
Median length7
Mean length7.0789474
Min length6

Unique

Unique7 ?
Unique (%)9.2%

Sample

1st row하동읍 비파리
2nd row하동읍 두곡리
3rd row하동읍 읍내리
4th row하동읍 신기리
5th row하동읍 비파리

Common Values

ValueCountFrequency (%)
하동읍 읍내리 24
31.6%
진교면 진교리 18
23.7%
하동읍 비파리 8
 
10.5%
하동읍 광평리 8
 
10.5%
옥종면 청룡리 3
 
3.9%
하동읍 두곡리 2
 
2.6%
금남면 계천리 2
 
2.6%
고전면 전도리 2
 
2.6%
금남면 송문리 2
 
2.6%
하동읍 신기리 1
 
1.3%
Other values (6) 6
 
7.9%

Length

2023-12-11T07:39:39.949821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
하동읍 43
28.1%
읍내리 24
15.7%
진교면 19
12.4%
진교리 18
11.8%
비파리 8
 
5.2%
광평리 8
 
5.2%
금남면 5
 
3.3%
옥종면 3
 
2.0%
청룡리 3
 
2.0%
금성면 2
 
1.3%
Other values (15) 20
13.1%

연면적(제곱미터)
Text

Distinct75
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size740.0 B
2023-12-11T07:39:40.155055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length6.1710526
Min length3

Characters and Unicode

Total characters469
Distinct characters12
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

Unique74 ?
Unique (%)97.4%

Sample

1st row13740.97
2nd row6500.5
3rd row5083.35
4th row5506.41
5th row4048.98
ValueCountFrequency (%)
657.36 2
 
2.6%
831.68 1
 
1.3%
1,311,75 1
 
1.3%
651.02 1
 
1.3%
390 1
 
1.3%
658.065 1
 
1.3%
639.68 1
 
1.3%
160.38 1
 
1.3%
285.92 1
 
1.3%
1640.25 1
 
1.3%
Other values (65) 65
85.5%
2023-12-11T07:39:40.461493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 62
13.2%
1 62
13.2%
5 54
11.5%
6 48
10.2%
2 44
9.4%
4 40
8.5%
0 36
7.7%
3 32
6.8%
9 32
6.8%
8 30
6.4%
Other values (2) 29
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 405
86.4%
Other Punctuation 64
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 62
15.3%
5 54
13.3%
6 48
11.9%
2 44
10.9%
4 40
9.9%
0 36
8.9%
3 32
7.9%
9 32
7.9%
8 30
7.4%
7 27
6.7%
Other Punctuation
ValueCountFrequency (%)
. 62
96.9%
, 2
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
Common 469
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 62
13.2%
1 62
13.2%
5 54
11.5%
6 48
10.2%
2 44
9.4%
4 40
8.5%
0 36
7.7%
3 32
6.8%
9 32
6.8%
8 30
6.4%
Other values (2) 29
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 469
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 62
13.2%
1 62
13.2%
5 54
11.5%
6 48
10.2%
2 44
9.4%
4 40
8.5%
0 36
7.7%
3 32
6.8%
9 32
6.8%
8 30
6.4%
Other values (2) 29
6.2%

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct36
Distinct (%)47.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.236842
Minimum2
Maximum420
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2023-12-11T07:39:40.570432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile6
Q18
median15.5
Q325
95-th percentile199.25
Maximum420
Range418
Interquartile range (IQR)17

Descriptive statistics

Standard deviation71.185929
Coefficient of variation (CV)1.7691729
Kurtosis12.95109
Mean40.236842
Median Absolute Deviation (MAD)7.5
Skewness3.4060895
Sum3058
Variance5067.4365
MonotonicityNot monotonic
2023-12-11T07:39:40.674885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
8 12
 
15.8%
12 6
 
7.9%
16 6
 
7.9%
24 4
 
5.3%
7 4
 
5.3%
19 4
 
5.3%
6 3
 
3.9%
14 3
 
3.9%
15 2
 
2.6%
18 2
 
2.6%
Other values (26) 30
39.5%
ValueCountFrequency (%)
2 1
 
1.3%
4 2
 
2.6%
6 3
 
3.9%
7 4
 
5.3%
8 12
15.8%
9 2
 
2.6%
10 1
 
1.3%
11 2
 
2.6%
12 6
7.9%
14 3
 
3.9%
ValueCountFrequency (%)
420 1
1.3%
306 1
1.3%
219 1
1.3%
200 1
1.3%
199 1
1.3%
173 1
1.3%
144 1
1.3%
95 1
1.3%
80 1
1.3%
71 1
1.3%

동수
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5394737
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2023-12-11T07:39:40.774189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31.25
95-th percentile4
Maximum7
Range6
Interquartile range (IQR)0.25

Descriptive statistics

Standard deviation1.2695489
Coefficient of variation (CV)0.82466424
Kurtosis9.6556964
Mean1.5394737
Median Absolute Deviation (MAD)0
Skewness3.0612397
Sum117
Variance1.6117544
MonotonicityNot monotonic
2023-12-11T07:39:40.864446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 57
75.0%
2 11
 
14.5%
4 3
 
3.9%
7 2
 
2.6%
3 2
 
2.6%
6 1
 
1.3%
ValueCountFrequency (%)
1 57
75.0%
2 11
 
14.5%
3 2
 
2.6%
4 3
 
3.9%
6 1
 
1.3%
7 2
 
2.6%
ValueCountFrequency (%)
7 2
 
2.6%
6 1
 
1.3%
4 3
 
3.9%
3 2
 
2.6%
2 11
 
14.5%
1 57
75.0%

층수
Categorical

Distinct19
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size740.0 B
4
27 
5
12 
3
10 
6
3 
지하1 지상15
3 
Other values (14)
21 

Length

Max length11
Median length1
Mean length2.3947368
Min length1

Unique

Unique9 ?
Unique (%)11.8%

Sample

1st row6
2nd row6
3rd row5
4th row6
5th row5

Common Values

ValueCountFrequency (%)
4 27
35.5%
5 12
15.8%
3 10
 
13.2%
6 3
 
3.9%
지하1 지상15 3
 
3.9%
2 3
 
3.9%
지하1 지상8 3
 
3.9%
15 2
 
2.6%
지하1 지상4 2
 
2.6%
지하1 지상5 2
 
2.6%
Other values (9) 9
 
11.8%

Length

2023-12-11T07:39:40.964545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
4 27
29.3%
지하1 13
14.1%
5 13
14.1%
3 10
 
10.9%
지상8 4
 
4.3%
6 3
 
3.3%
지상15 3
 
3.3%
2 3
 
3.3%
지상4 2
 
2.2%
지상5 2
 
2.2%
Other values (11) 12
13.0%

사용승인일
Date

Distinct74
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size740.0 B
Minimum1905-06-13 00:00:00
Maximum2020-01-31 00:00:00
2023-12-11T07:39:41.075388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:41.193367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

비고
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size740.0 B
다세대
32 
아파트
25 
연립주택
19 

Length

Max length4
Median length3
Mean length3.25
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
다세대 32
42.1%
아파트 25
32.9%
연립주택 19
25.0%

Length

2023-12-11T07:39:41.294995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:39:41.374748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
다세대 32
42.1%
아파트 25
32.9%
연립주택 19
25.0%

Interactions

2023-12-11T07:39:38.776746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:38.348676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:38.589031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:38.842324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:38.462159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:38.657271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:38.903727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:38.523311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:38.714706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:39:41.435084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번건물명대지위치연면적(제곱미터)세대수동수층수사용승인일비고
연번1.0000.5920.3350.9370.4620.2030.6060.9740.940
건물명0.5921.0000.9750.9971.0000.9140.9910.9980.882
대지위치0.3350.9751.0000.9930.8690.8740.6450.6470.000
연면적(제곱미터)0.9370.9970.9931.0001.0001.0000.9970.9951.000
세대수0.4621.0000.8691.0001.0000.8000.7830.0000.578
동수0.2030.9140.8741.0000.8001.0000.8120.0000.422
층수0.6060.9910.6450.9970.7830.8121.0001.0000.738
사용승인일0.9740.9980.6470.9950.0000.0001.0001.0001.000
비고0.9400.8820.0001.0000.5780.4220.7381.0001.000
2023-12-11T07:39:41.748172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
층수비고대지위치
층수1.0000.4770.248
비고0.4771.0000.000
대지위치0.2480.0001.000
2023-12-11T07:39:41.817944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번세대수동수대지위치층수비고
연번1.000-0.718-0.1940.0740.2830.876
세대수-0.7181.0000.5490.4720.4320.428
동수-0.1940.5491.0000.6140.4910.187
대지위치0.0740.4720.6141.0000.2480.000
층수0.2830.4320.4910.2481.0000.477
비고0.8760.4280.1870.0000.4771.000

Missing values

2023-12-11T07:39:38.997513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:39:39.138419image/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

연번건물명대지위치연면적(제곱미터)세대수동수층수사용승인일비고
01흥한로얄맨션하동읍 비파리13740.97144461991-10-14아파트
12대망파크맨션하동읍 두곡리6500.580261992-06-04아파트
23미도빌라하동읍 읍내리5083.3560251991-06-14아파트
34강변타운(한영아파트)하동읍 신기리5506.4171161991-10-14아파트
45무지개맨션하동읍 비파리4048.9850251990-04-06아파트
56한다사아파트하동읍 읍내리1694.420151990-12-12아파트
67대경송림타운하동읍 광평리21082.261992지하1 지상151992-12-30아파트
78진교맨션(아파트)진교면 진교리4600.59521지하1 지상91992-04-16아파트
89대산빌라옥종면 청룡리151019151993-10-16아파트
910삼화아파트금남면 계천리2046191지하1 지상51997-09-29아파트
연번건물명대지위치연면적(제곱미터)세대수동수층수사용승인일비고
6667사랑의주택하동읍 읍내리524.9415131997-09-01다세대
6768금성빌라진교면 진교리359.136131997-11-20다세대
6869금오빌라금남면 덕천리1047.612241998-04-10다세대
6970한성빌라진교면 진교리494.556141998-05-30다세대
7071문화빌라진교면 진교리652.138141999-12-28다세대
7172우인레드빌진교면 진교리656.687142002-09-12다세대
7273활도주택청암면 상이리2096.6918612002-04-17다세대
7374하이빌고전면 전도리615.3810132010-08-09다세대
7475어울림빌하동읍 읍내리821.0781지하1 지상42012-12-24다세대
7576태영금빛고을하동읍 두곡리1317.9216252014-08-22다세대