Overview

Dataset statistics

Number of variables10
Number of observations32
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory88.1 B

Variable types

Numeric4
Text3
DateTime3

Dataset

Description홍성군내 아파트 현황으로 아파트명, 소재지 도로명주소, 승인일, 준공일 동수, 세대수, 데이터 기준일 등을 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=443&beforeMenuCd=DOM_000000201001001000&publicdatapk=3073568

Alerts

데이터기준일자 has constant value ""Constant
동수 is highly overall correlated with 세대수 and 1 other fieldsHigh correlation
세대수 is highly overall correlated with 동수 and 1 other fieldsHigh correlation
연면적(제곱미터) is highly overall correlated with 동수 and 1 other fieldsHigh correlation
연번 has unique valuesUnique
아파트명 has unique valuesUnique
소재지도로명주소 has unique valuesUnique
연면적(제곱미터) has unique valuesUnique

Reproduction

Analysis started2024-01-09 21:37:24.209267
Analysis finished2024-01-09 21:37:25.659364
Duration1.45 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.5
Minimum1
Maximum32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-01-10T06:37:25.707263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.55
Q18.75
median16.5
Q324.25
95-th percentile30.45
Maximum32
Range31
Interquartile range (IQR)15.5

Descriptive statistics

Standard deviation9.3808315
Coefficient of variation (CV)0.56853524
Kurtosis-1.2
Mean16.5
Median Absolute Deviation (MAD)8
Skewness0
Sum528
Variance88
MonotonicityStrictly increasing
2024-01-10T06:37:26.028462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 1
 
3.1%
18 1
 
3.1%
32 1
 
3.1%
31 1
 
3.1%
30 1
 
3.1%
29 1
 
3.1%
28 1
 
3.1%
27 1
 
3.1%
26 1
 
3.1%
25 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
1 1
3.1%
2 1
3.1%
3 1
3.1%
4 1
3.1%
5 1
3.1%
6 1
3.1%
7 1
3.1%
8 1
3.1%
9 1
3.1%
10 1
3.1%
ValueCountFrequency (%)
32 1
3.1%
31 1
3.1%
30 1
3.1%
29 1
3.1%
28 1
3.1%
27 1
3.1%
26 1
3.1%
25 1
3.1%
24 1
3.1%
23 1
3.1%

아파트명
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-01-10T06:37:26.208798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length10
Mean length7.65625
Min length3

Characters and Unicode

Total characters245
Distinct characters100
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

Unique32 ?
Unique (%)100.0%

Sample

1st row대우
2nd row현광
3rd row청솔
4th row경성
5th row현대
ValueCountFrequency (%)
한울마을 2
 
4.4%
충남꿈비채홍성내포 2
 
4.4%
lh2단지 2
 
4.4%
rl9bl 1
 
2.2%
중흥s클래스 1
 
2.2%
모아엘가 1
 
2.2%
상록아파트 1
 
2.2%
주공4단지 1
 
2.2%
lh천년나무4단지 1
 
2.2%
이안아파트 1
 
2.2%
Other values (32) 32
71.1%
2024-01-10T06:37:26.492862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
26
 
10.6%
L 12
 
4.9%
단 7
 
2.9%
스 7
 
2.9%
지 7
 
2.9%
H 6
 
2.4%
2 6
 
2.4%
아 6
 
2.4%
성 5
 
2.0%
공 5
 
2.0%
Other values (90) 158
64.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 175
71.4%
Space Separator 26
 
10.6%
Uppercase Letter 25
 
10.2%
Decimal Number 15
 
6.1%
Close Punctuation 2
 
0.8%
Open Punctuation 2
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
단 7
 
4.0%
스 7
 
4.0%
지 7
 
4.0%
아 6
 
3.4%
성 5
 
2.9%
공 5
 
2.9%
파 5
 
2.9%
주 5
 
2.9%
트 4
 
2.3%
차 4
 
2.3%
Other values (76) 120
68.6%
Decimal Number
ValueCountFrequency (%)
2 6
40.0%
1 4
26.7%
4 2
 
13.3%
9 1
 
6.7%
8 1
 
6.7%
3 1
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
L 12
48.0%
H 6
24.0%
B 4
 
16.0%
R 2
 
8.0%
S 1
 
4.0%
Space Separator
ValueCountFrequency (%)
26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 175
71.4%
Common 45
 
18.4%
Latin 25
 
10.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
단 7
 
4.0%
스 7
 
4.0%
지 7
 
4.0%
아 6
 
3.4%
성 5
 
2.9%
공 5
 
2.9%
파 5
 
2.9%
주 5
 
2.9%
트 4
 
2.3%
차 4
 
2.3%
Other values (76) 120
68.6%
Common
ValueCountFrequency (%)
26
57.8%
2 6
 
13.3%
1 4
 
8.9%
4 2
 
4.4%
) 2
 
4.4%
( 2
 
4.4%
9 1
 
2.2%
8 1
 
2.2%
3 1
 
2.2%
Latin
ValueCountFrequency (%)
L 12
48.0%
H 6
24.0%
B 4
 
16.0%
R 2
 
8.0%
S 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 175
71.4%
ASCII 70
 
28.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
26
37.1%
L 12
17.1%
H 6
 
8.6%
2 6
 
8.6%
B 4
 
5.7%
1 4
 
5.7%
4 2
 
2.9%
R 2
 
2.9%
) 2
 
2.9%
( 2
 
2.9%
Other values (4) 4
 
5.7%
Hangul
ValueCountFrequency (%)
단 7
 
4.0%
스 7
 
4.0%
지 7
 
4.0%
아 6
 
3.4%
성 5
 
2.9%
공 5
 
2.9%
파 5
 
2.9%
주 5
 
2.9%
트 4
 
2.3%
차 4
 
2.3%
Other values (76) 120
68.6%

소재지도로명주소
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-01-10T06:37:26.669389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length21.375
Min length19

Characters and Unicode

Total characters684
Distinct characters47
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row충청남도 홍성읍 문화로72번길 41
2nd row충청남도 홍성읍 도청대로96번길 85-17
3rd row충청남도 홍성군 홍성읍 내포로146번길 46
4th row충청남도 홍성군 홍성읍 문화로 80번길 32-14
5th row충청남도 홍성군 홍성읍 월계천길 41-11
ValueCountFrequency (%)
충청남도 32
20.1%
홍성군 30
18.9%
홍북읍 15
 
9.4%
홍성읍 15
 
9.4%
홍예로 5
 
3.1%
문화로72번길 4
 
2.5%
홍학로 3
 
1.9%
신대로 3
 
1.9%
자경로 2
 
1.3%
월산로30번길 2
 
1.3%
Other values (47) 48
30.2%
2024-01-10T06:37:26.953428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
127
18.6%
홍 68
 
9.9%
성 45
 
6.6%
충 35
 
5.1%
청 35
 
5.1%
남 34
 
5.0%
도 34
 
5.0%
로 31
 
4.5%
읍 31
 
4.5%
군 30
 
4.4%
Other values (37) 214
31.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 441
64.5%
Space Separator 127
 
18.6%
Decimal Number 112
 
16.4%
Dash Punctuation 4
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
홍 68
15.4%
성 45
10.2%
충 35
7.9%
청 35
7.9%
남 34
7.7%
도 34
7.7%
로 31
 
7.0%
읍 31
 
7.0%
군 30
 
6.8%
북 15
 
3.4%
Other values (25) 83
18.8%
Decimal Number
ValueCountFrequency (%)
1 21
18.8%
2 17
15.2%
3 15
13.4%
4 12
10.7%
8 10
8.9%
0 9
8.0%
6 8
 
7.1%
7 8
 
7.1%
5 7
 
6.2%
9 5
 
4.5%
Space Separator
ValueCountFrequency (%)
127
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 441
64.5%
Common 243
35.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
홍 68
15.4%
성 45
10.2%
충 35
7.9%
청 35
7.9%
남 34
7.7%
도 34
7.7%
로 31
 
7.0%
읍 31
 
7.0%
군 30
 
6.8%
북 15
 
3.4%
Other values (25) 83
18.8%
Common
ValueCountFrequency (%)
127
52.3%
1 21
 
8.6%
2 17
 
7.0%
3 15
 
6.2%
4 12
 
4.9%
8 10
 
4.1%
0 9
 
3.7%
6 8
 
3.3%
7 8
 
3.3%
5 7
 
2.9%
Other values (2) 9
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 441
64.5%
ASCII 243
35.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
127
52.3%
1 21
 
8.6%
2 17
 
7.0%
3 15
 
6.2%
4 12
 
4.9%
8 10
 
4.1%
0 9
 
3.7%
6 8
 
3.3%
7 8
 
3.3%
5 7
 
2.9%
Other values (2) 9
 
3.7%
Hangul
ValueCountFrequency (%)
홍 68
15.4%
성 45
10.2%
충 35
7.9%
청 35
7.9%
남 34
7.7%
도 34
7.7%
로 31
 
7.0%
읍 31
 
7.0%
군 30
 
6.8%
북 15
 
3.4%
Other values (25) 83
18.8%

승인일
Date

Distinct28
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Memory size388.0 B
Minimum1993-01-14 00:00:00
Maximum2021-05-10 00:00:00
2024-01-10T06:37:27.059894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:37:27.149523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)

준공일
Date

Distinct29
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Memory size388.0 B
Minimum1995-03-30 00:00:00
Maximum2023-07-19 00:00:00
2024-01-10T06:37:27.243318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:37:27.359946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)

동수
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)56.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.9375
Minimum1
Maximum28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-01-10T06:37:27.471163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.55
Q14
median8
Q312.25
95-th percentile20.05
Maximum28
Range27
Interquartile range (IQR)8.25

Descriptive statistics

Standard deviation6.3496888
Coefficient of variation (CV)0.7104547
Kurtosis2.0246795
Mean8.9375
Median Absolute Deviation (MAD)4
Skewness1.2650515
Sum286
Variance40.318548
MonotonicityNot monotonic
2024-01-10T06:37:27.559573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
4 5
15.6%
13 3
 
9.4%
12 3
 
9.4%
2 2
 
6.2%
6 2
 
6.2%
8 2
 
6.2%
5 2
 
6.2%
9 2
 
6.2%
1 2
 
6.2%
28 1
 
3.1%
Other values (8) 8
25.0%
ValueCountFrequency (%)
1 2
 
6.2%
2 2
 
6.2%
3 1
 
3.1%
4 5
15.6%
5 2
 
6.2%
6 2
 
6.2%
7 1
 
3.1%
8 2
 
6.2%
9 2
 
6.2%
10 1
 
3.1%
ValueCountFrequency (%)
28 1
 
3.1%
25 1
 
3.1%
16 1
 
3.1%
15 1
 
3.1%
14 1
 
3.1%
13 3
9.4%
12 3
9.4%
11 1
 
3.1%
10 1
 
3.1%
9 2
6.2%

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean688.625
Minimum30
Maximum2127
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-01-10T06:37:27.652315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile156.65
Q1328.5
median588.5
Q3920.75
95-th percentile1517
Maximum2127
Range2097
Interquartile range (IQR)592.25

Descriptive statistics

Standard deviation471.01995
Coefficient of variation (CV)0.68400065
Kurtosis1.6273947
Mean688.625
Median Absolute Deviation (MAD)300.5
Skewness1.1638298
Sum22036
Variance221859.79
MonotonicityNot monotonic
2024-01-10T06:37:27.742385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
684 2
 
6.2%
260 1
 
3.1%
915 1
 
3.1%
831 1
 
3.1%
822 1
 
3.1%
1196 1
 
3.1%
1400 1
 
3.1%
30 1
 
3.1%
45 1
 
3.1%
394 1
 
3.1%
Other values (21) 21
65.6%
ValueCountFrequency (%)
30 1
3.1%
45 1
3.1%
248 1
3.1%
250 1
3.1%
260 1
3.1%
270 1
3.1%
284 1
3.1%
297 1
3.1%
339 1
3.1%
394 1
3.1%
ValueCountFrequency (%)
2127 1
3.1%
1660 1
3.1%
1400 1
3.1%
1260 1
3.1%
1196 1
3.1%
996 1
3.1%
990 1
3.1%
938 1
3.1%
915 1
3.1%
885 1
3.1%

연면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean84639.068
Minimum3798.93
Maximum311816.04
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-01-10T06:37:27.830221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3798.93
5-th percentile12096.672
Q133304.312
median67800.28
Q3122020.7
95-th percentile223943.88
Maximum311816.04
Range308017.11
Interquartile range (IQR)88716.383

Descriptive statistics

Standard deviation72304.092
Coefficient of variation (CV)0.85426381
Kurtosis2.5510833
Mean84639.068
Median Absolute Deviation (MAD)36850.43
Skewness1.5363131
Sum2708450.2
Variance5.2278817 × 109
MonotonicityNot monotonic
2024-01-10T06:37:27.924645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
25390.42 1
 
3.1%
141973.26 1
 
3.1%
148184.09 1
 
3.1%
67414.53 1
 
3.1%
94508.27 1
 
3.1%
101922.64 1
 
3.1%
3798.93 1
 
3.1%
5829.62 1
 
3.1%
51696.26 1
 
3.1%
28843.78 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
3798.93 1
3.1%
5829.62 1
3.1%
17224.26 1
3.1%
17415.08 1
3.1%
19836.56 1
3.1%
25390.42 1
3.1%
28843.78 1
3.1%
33055.92 1
3.1%
33387.11 1
3.1%
34325.63 1
3.1%
ValueCountFrequency (%)
311816.04 1
3.1%
264525.56 1
3.1%
190740.69 1
3.1%
148184.09 1
3.1%
147537.28 1
3.1%
143879.09 1
3.1%
141973.26 1
3.1%
136842.06 1
3.1%
117080.24 1
3.1%
101922.64 1
3.1%

관리사무소연락처
Text

Distinct31
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-01-10T06:37:28.083608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters384
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

Unique30 ?
Unique (%)93.8%

Sample

1st row041-634-8615
2nd row041-634-6034
3rd row041-634-4844
4th row041-634-8048
5th row041-633-5324
ValueCountFrequency (%)
041-631-2983 2
 
6.2%
041-634-8615 1
 
3.1%
041-641-6009 1
 
3.1%
041-634-2340 1
 
3.1%
041-631-2208 1
 
3.1%
041-634-6161 1
 
3.1%
041-632-2984 1
 
3.1%
041-631-6404 1
 
3.1%
041-634-2985 1
 
3.1%
041-631-8936 1
 
3.1%
Other values (21) 21
65.6%
2024-01-10T06:37:28.349610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 64
16.7%
4 61
15.9%
1 60
15.6%
3 48
12.5%
6 47
12.2%
0 44
11.5%
9 16
 
4.2%
2 15
 
3.9%
8 14
 
3.6%
5 13
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 320
83.3%
Dash Punctuation 64
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 61
19.1%
1 60
18.8%
3 48
15.0%
6 47
14.7%
0 44
13.8%
9 16
 
5.0%
2 15
 
4.7%
8 14
 
4.4%
5 13
 
4.1%
7 2
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 64
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 384
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 64
16.7%
4 61
15.9%
1 60
15.6%
3 48
12.5%
6 47
12.2%
0 44
11.5%
9 16
 
4.2%
2 15
 
3.9%
8 14
 
3.6%
5 13
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 384
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 64
16.7%
4 61
15.9%
1 60
15.6%
3 48
12.5%
6 47
12.2%
0 44
11.5%
9 16
 
4.2%
2 15
 
3.9%
8 14
 
3.6%
5 13
 
3.4%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
Minimum2023-09-27 00:00:00
Maximum2023-09-27 00:00:00
2024-01-10T06:37:28.439408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:37:28.511372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-10T06:37:25.233497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:37:24.499678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:37:24.743551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:37:24.999456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:37:25.298981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:37:24.561901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:37:24.806948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:37:25.059305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:37:25.363200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:37:24.621413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:37:24.868407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:37:25.118152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:37:25.421708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:37:24.680441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:37:24.934811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:37:25.170688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:37:28.570676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번아파트명소재지도로명주소승인일준공일동수세대수연면적(제곱미터)관리사무소연락처
연번1.0001.0001.0000.9801.0000.6830.6470.5211.000
아파트명1.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
승인일0.9801.0001.0001.0000.9910.9730.8280.8321.000
준공일1.0001.0001.0000.9911.0001.0000.8320.9331.000
동수0.6831.0001.0000.9731.0001.0000.8080.9431.000
세대수0.6471.0001.0000.8280.8320.8081.0000.8831.000
연면적(제곱미터)0.5211.0001.0000.8320.9330.9430.8831.0001.000
관리사무소연락처1.0001.0001.0001.0001.0001.0001.0001.0001.000
2024-01-10T06:37:28.695946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번동수세대수연면적(제곱미터)
연번1.0000.3570.3650.286
동수0.3571.0000.8240.855
세대수0.3650.8241.0000.918
연면적(제곱미터)0.2860.8550.9181.000

Missing values

2024-01-10T06:37:25.509995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:37:25.617066image/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

연번아파트명소재지도로명주소승인일준공일동수세대수연면적(제곱미터)관리사무소연락처데이터기준일자
01대우충청남도 홍성읍 문화로72번길 411993-01-141995-03-30226025390.42041-634-86152023-09-27
12현광충청남도 홍성읍 도청대로96번길 85-171994-10-291997-05-01333933387.11041-634-60342023-09-27
23청솔충청남도 홍성군 홍성읍 내포로146번길 461994-12-291997-05-01229734325.63041-634-48442023-09-27
34경성충청남도 홍성군 홍성읍 문화로 80번길 32-141995-02-171997-01-10427033055.92041-634-80482023-09-27
45현대충청남도 홍성군 홍성읍 월계천길 41-111995-03-311997-04-11443446076.36041-633-53242023-09-27
56동진충청남도 홍성군 홍북읍 도청대로 2111996-09-241998-01-10424817224.26041-634-94972023-09-27
67주공 1차(남장주공그린빌)충청남도 홍성군 홍성읍 문화로72번길 921998-06-012001-09-081399683641.37041-631-61622023-09-27
78부영1차충청남도 홍성군 홍성읍 월산로30번길 392001-09-182003-05-26668468186.03041-631-56522023-09-27
89부영2차충청남도 홍성군 홍성읍 월산로30번길 382001-09-182004-08-23868472747.29041-631-56112023-09-27
910코오롱하늘채충청남도 홍성군 홍성읍 문화로33번길 112004-08-042006-10-181350979298.5041-631-44502023-09-27
연번아파트명소재지도로명주소승인일준공일동수세대수연면적(제곱미터)관리사무소연락처데이터기준일자
2223모아엘가충청남도 홍성군 홍북읍 홍학로 882013-02-182016-04-08151260190740.69041-631-89362023-09-27
2324상록아파트충청남도 홍성군 홍북읍 홍학로 252013-11-132016-07-251649764920.6041-634-29852023-09-27
2425주공4단지 (LH천년나무4단지)충청남도 홍성군 홍성읍 남장중로 372013-12-242016-11-30451828843.78041-631-64042023-09-27
2526이안아파트충청남도 홍성군 홍성읍 문화로72번길 502008-03-282017-05-30839451696.26041-632-29842023-09-27
2627충남꿈비채홍성내포 RL8BL충청남도 홍성군 홍북읍 홍예로 2882021-05-102022-10-261455829.62041-631-29832023-09-27
2728충남꿈비채홍성내포 RL9BL충청남도 홍성군 홍북읍 홍예로 2902021-05-102022-10-261303798.93041-631-29832023-09-27
2829한울마을 LH2단지 1BL충청남도 홍성군 홍북읍 홍학로 1242019-06-282022-11-08141400101922.64041-634-61612023-09-27
2930한울마을 LH2단지 2BL충청남도 홍성군 홍북읍 홍예로 1632019-06-282022-11-0812119694508.27041-631-22082023-09-27
3031가람마을 LH1단지충청남도 홍성군 홍북읍 홍예로 1642019-12-262023-07-18582267414.53041-634-23402023-09-27
31322차 대방 엘리움 더센트럴충청남도 홍성군 홍북읍 자경로 182020-05-012023-07-1913831148184.09041-631-55112023-09-27