Overview

Dataset statistics

Number of variables8
Number of observations135
Missing cells30
Missing cells (%)2.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.0 KiB
Average record size in memory68.0 B

Variable types

Numeric3
Text4
DateTime1

Dataset

Description경기도 광주시 소재 아파트 현황에 대한 데이터로 아파트명, 주소, 연면적, 세대수, 관리사무소(전화번호, 팩스) 등을 제공합니다.
URLhttps://www.data.go.kr/data/3079946/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연면적 is highly overall correlated with 세대수High correlation
세대수 is highly overall correlated with 연면적High correlation
연면적 has 15 (11.1%) missing valuesMissing
팩스번호 has 15 (11.1%) missing valuesMissing
연번 has unique valuesUnique
아파트명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 10:46:13.133046
Analysis finished2023-12-12 10:46:15.886870
Duration2.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct135
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68
Minimum1
Maximum135
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-12T19:46:16.020496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.7
Q134.5
median68
Q3101.5
95-th percentile128.3
Maximum135
Range134
Interquartile range (IQR)67

Descriptive statistics

Standard deviation39.115214
Coefficient of variation (CV)0.57522374
Kurtosis-1.2
Mean68
Median Absolute Deviation (MAD)34
Skewness0
Sum9180
Variance1530
MonotonicityStrictly increasing
2023-12-12T19:46:16.261510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
94 1
 
0.7%
88 1
 
0.7%
89 1
 
0.7%
90 1
 
0.7%
91 1
 
0.7%
92 1
 
0.7%
93 1
 
0.7%
95 1
 
0.7%
2 1
 
0.7%
Other values (125) 125
92.6%
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 (%)
135 1
0.7%
134 1
0.7%
133 1
0.7%
132 1
0.7%
131 1
0.7%
130 1
0.7%
129 1
0.7%
128 1
0.7%
127 1
0.7%
126 1
0.7%

아파트명
Text

UNIQUE 

Distinct135
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T19:46:16.650122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length13.97037
Min length7

Characters and Unicode

Total characters1886
Distinct characters189
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique135 ?
Unique (%)100.0%

Sample

1st row탄벌동 산호아파트
2nd row송정동 나산아파트
3rd row경안동 두진아파트
4th row탄벌동 동보아파트
5th row곤지암리 엘지아파트
ValueCountFrequency (%)
태전동 26
 
7.4%
신현리 12
 
3.4%
양벌리 12
 
3.4%
e편한세상 9
 
2.6%
송정동 8
 
2.3%
역동 8
 
2.3%
탄벌동 7
 
2.0%
광주역 7
 
2.0%
쌍령동 7
 
2.0%
힐스테이트 6
 
1.7%
Other values (148) 247
70.8%
2023-12-12T19:46:17.247906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
214
 
11.3%
트 123
 
6.5%
아 120
 
6.4%
파 116
 
6.2%
동 81
 
4.3%
리 68
 
3.6%
지 61
 
3.2%
단 46
 
2.4%
태 44
 
2.3%
전 42
 
2.2%
Other values (179) 971
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1552
82.3%
Space Separator 214
 
11.3%
Decimal Number 80
 
4.2%
Lowercase Letter 21
 
1.1%
Uppercase Letter 10
 
0.5%
Dash Punctuation 5
 
0.3%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
트 123
 
7.9%
아 120
 
7.7%
파 116
 
7.5%
동 81
 
5.2%
리 68
 
4.4%
지 61
 
3.9%
단 46
 
3.0%
태 44
 
2.8%
전 42
 
2.7%
스 30
 
1.9%
Other values (159) 821
52.9%
Decimal Number
ValueCountFrequency (%)
1 30
37.5%
2 28
35.0%
3 8
 
10.0%
5 4
 
5.0%
4 4
 
5.0%
6 2
 
2.5%
8 1
 
1.2%
0 1
 
1.2%
9 1
 
1.2%
7 1
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
B 3
30.0%
C 3
30.0%
L 2
20.0%
A 1
 
10.0%
K 1
 
10.0%
Space Separator
ValueCountFrequency (%)
214
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1552
82.3%
Common 303
 
16.1%
Latin 31
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
트 123
 
7.9%
아 120
 
7.7%
파 116
 
7.5%
동 81
 
5.2%
리 68
 
4.4%
지 61
 
3.9%
단 46
 
3.0%
태 44
 
2.8%
전 42
 
2.7%
스 30
 
1.9%
Other values (159) 821
52.9%
Common
ValueCountFrequency (%)
214
70.6%
1 30
 
9.9%
2 28
 
9.2%
3 8
 
2.6%
- 5
 
1.7%
5 4
 
1.3%
4 4
 
1.3%
6 2
 
0.7%
) 2
 
0.7%
( 2
 
0.7%
Other values (4) 4
 
1.3%
Latin
ValueCountFrequency (%)
e 21
67.7%
B 3
 
9.7%
C 3
 
9.7%
L 2
 
6.5%
A 1
 
3.2%
K 1
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1552
82.3%
ASCII 334
 
17.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
214
64.1%
1 30
 
9.0%
2 28
 
8.4%
e 21
 
6.3%
3 8
 
2.4%
- 5
 
1.5%
5 4
 
1.2%
4 4
 
1.2%
B 3
 
0.9%
C 3
 
0.9%
Other values (10) 14
 
4.2%
Hangul
ValueCountFrequency (%)
트 123
 
7.9%
아 120
 
7.7%
파 116
 
7.5%
동 81
 
5.2%
리 68
 
4.4%
지 61
 
3.9%
단 46
 
3.0%
태 44
 
2.8%
전 42
 
2.7%
스 30
 
1.9%
Other values (159) 821
52.9%

주소
Text

Distinct134
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T19:46:17.755244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length24
Mean length17.518519
Min length14

Characters and Unicode

Total characters2365
Distinct characters68
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

Unique133 ?
Unique (%)98.5%

Sample

1st row경기도 광주시 탄벌동 37
2nd row경기도 광주시 송정동 580
3rd row경기도 광주시 경안동 127
4th row경기도 광주시 탄벌동 45
5th row경기도 광주시 곤지암읍 곤지암리 337-12
ValueCountFrequency (%)
경기도 135
22.4%
광주시 135
22.4%
오포읍 37
 
6.1%
태전동 27
 
4.5%
초월읍 20
 
3.3%
양벌리 12
 
2.0%
신현리 12
 
2.0%
역동 8
 
1.3%
송정동 8
 
1.3%
탄벌동 7
 
1.2%
Other values (158) 203
33.6%
2023-12-12T19:46:18.502709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
469
19.8%
경 140
 
5.9%
도 140
 
5.9%
광 135
 
5.7%
주 135
 
5.7%
시 135
 
5.7%
기 135
 
5.7%
동 76
 
3.2%
1 64
 
2.7%
읍 63
 
2.7%
Other values (58) 873
36.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1417
59.9%
Space Separator 469
 
19.8%
Decimal Number 446
 
18.9%
Dash Punctuation 33
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 140
 
9.9%
도 140
 
9.9%
광 135
 
9.5%
주 135
 
9.5%
시 135
 
9.5%
기 135
 
9.5%
동 76
 
5.4%
읍 63
 
4.4%
리 63
 
4.4%
포 37
 
2.6%
Other values (46) 358
25.3%
Decimal Number
ValueCountFrequency (%)
1 64
14.3%
2 59
13.2%
6 51
11.4%
5 48
10.8%
3 46
10.3%
4 45
10.1%
7 41
9.2%
9 35
7.8%
8 29
6.5%
0 28
6.3%
Space Separator
ValueCountFrequency (%)
469
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1417
59.9%
Common 948
40.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 140
 
9.9%
도 140
 
9.9%
광 135
 
9.5%
주 135
 
9.5%
시 135
 
9.5%
기 135
 
9.5%
동 76
 
5.4%
읍 63
 
4.4%
리 63
 
4.4%
포 37
 
2.6%
Other values (46) 358
25.3%
Common
ValueCountFrequency (%)
469
49.5%
1 64
 
6.8%
2 59
 
6.2%
6 51
 
5.4%
5 48
 
5.1%
3 46
 
4.9%
4 45
 
4.7%
7 41
 
4.3%
9 35
 
3.7%
- 33
 
3.5%
Other values (2) 57
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1417
59.9%
ASCII 948
40.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
469
49.5%
1 64
 
6.8%
2 59
 
6.2%
6 51
 
5.4%
5 48
 
5.1%
3 46
 
4.9%
4 45
 
4.7%
7 41
 
4.3%
9 35
 
3.7%
- 33
 
3.5%
Other values (2) 57
 
6.0%
Hangul
ValueCountFrequency (%)
경 140
 
9.9%
도 140
 
9.9%
광 135
 
9.5%
주 135
 
9.5%
시 135
 
9.5%
기 135
 
9.5%
동 76
 
5.4%
읍 63
 
4.4%
리 63
 
4.4%
포 37
 
2.6%
Other values (46) 358
25.3%

연면적
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct120
Distinct (%)100.0%
Missing15
Missing (%)11.1%
Infinite0
Infinite (%)0.0%
Mean54663.967
Minimum9619
Maximum205557
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-12T19:46:18.793978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9619
5-th percentile23709.2
Q135241.75
median49364.5
Q368660
95-th percentile91487.85
Maximum205557
Range195938
Interquartile range (IQR)33418.25

Descriptive statistics

Standard deviation26800.147
Coefficient of variation (CV)0.49027081
Kurtosis8.7862273
Mean54663.967
Median Absolute Deviation (MAD)16100.5
Skewness2.0598123
Sum6559676
Variance7.182479 × 108
MonotonicityNot monotonic
2023-12-12T19:46:19.059317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49783 1
 
0.7%
58794 1
 
0.7%
31786 1
 
0.7%
91481 1
 
0.7%
78718 1
 
0.7%
72947 1
 
0.7%
74850 1
 
0.7%
83454 1
 
0.7%
19652 1
 
0.7%
59976 1
 
0.7%
Other values (110) 110
81.5%
(Missing) 15
 
11.1%
ValueCountFrequency (%)
9619 1
0.7%
16646 1
0.7%
19062 1
0.7%
19652 1
0.7%
20082 1
0.7%
23618 1
0.7%
23714 1
0.7%
24214 1
0.7%
24749 1
0.7%
25115 1
0.7%
ValueCountFrequency (%)
205557 1
0.7%
160188 1
0.7%
103906 1
0.7%
102500 1
0.7%
95892 1
0.7%
91618 1
0.7%
91481 1
0.7%
87984 1
0.7%
87574 1
0.7%
87529 1
0.7%

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct119
Distinct (%)88.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean412.93333
Minimum76
Maximum1425
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-12T19:46:19.322621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum76
5-th percentile161.7
Q1289.5
median368
Q3477
95-th percentile832.4
Maximum1425
Range1349
Interquartile range (IQR)187.5

Descriptive statistics

Standard deviation221.49449
Coefficient of variation (CV)0.53639286
Kurtosis6.6446156
Mean412.93333
Median Absolute Deviation (MAD)98
Skewness2.17215
Sum55746
Variance49059.809
MonotonicityNot monotonic
2023-12-12T19:46:19.566533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
477 3
 
2.2%
296 3
 
2.2%
338 2
 
1.5%
300 2
 
1.5%
435 2
 
1.5%
448 2
 
1.5%
390 2
 
1.5%
409 2
 
1.5%
261 2
 
1.5%
236 2
 
1.5%
Other values (109) 113
83.7%
ValueCountFrequency (%)
76 1
0.7%
80 1
0.7%
116 1
0.7%
135 2
1.5%
144 1
0.7%
147 1
0.7%
168 1
0.7%
173 1
0.7%
181 1
0.7%
183 1
0.7%
ValueCountFrequency (%)
1425 1
0.7%
1396 1
0.7%
1152 1
0.7%
1108 1
0.7%
1031 1
0.7%
1028 1
0.7%
873 1
0.7%
815 1
0.7%
706 1
0.7%
702 1
0.7%

관리사무소전화
Text

Distinct128
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T19:46:19.986446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length12
Mean length12.325926
Min length12

Characters and Unicode

Total characters1664
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique122 ?
Unique (%)90.4%

Sample

1st row031-763-0988
2nd row031-762-0136
3rd row031-764-7905
4th row031-797-5332
5th row031-761-4668
ValueCountFrequency (%)
031-769-3900 3
 
2.2%
031-726-9214 2
 
1.5%
031-798-7674 2
 
1.5%
031-798-4800 2
 
1.5%
031-798-0690 2
 
1.5%
031-766-4182(4183 2
 
1.5%
031-719-0223 1
 
0.7%
031-763-7356 1
 
0.7%
031-765-7132 1
 
0.7%
031-768-6532 1
 
0.7%
Other values (118) 118
87.4%
2023-12-12T19:46:20.740340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 270
16.2%
0 221
13.3%
1 218
13.1%
3 211
12.7%
7 205
12.3%
6 141
8.5%
9 96
 
5.8%
8 88
 
5.3%
2 72
 
4.3%
4 70
 
4.2%
Other values (3) 72
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1382
83.1%
Dash Punctuation 270
 
16.2%
Open Punctuation 6
 
0.4%
Close Punctuation 6
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 221
16.0%
1 218
15.8%
3 211
15.3%
7 205
14.8%
6 141
10.2%
9 96
6.9%
8 88
 
6.4%
2 72
 
5.2%
4 70
 
5.1%
5 60
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 270
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1664
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 270
16.2%
0 221
13.3%
1 218
13.1%
3 211
12.7%
7 205
12.3%
6 141
8.5%
9 96
 
5.8%
8 88
 
5.3%
2 72
 
4.3%
4 70
 
4.2%
Other values (3) 72
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1664
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 270
16.2%
0 221
13.3%
1 218
13.1%
3 211
12.7%
7 205
12.3%
6 141
8.5%
9 96
 
5.8%
8 88
 
5.3%
2 72
 
4.3%
4 70
 
4.2%
Other values (3) 72
 
4.3%

팩스번호
Text

MISSING 

Distinct114
Distinct (%)95.0%
Missing15
Missing (%)11.1%
Memory size1.2 KiB
2023-12-12T19:46:21.138892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.05
Min length12

Characters and Unicode

Total characters1446
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

Unique109 ?
Unique (%)90.8%

Sample

1st row031-764-3628
2nd row031-762-0196
3rd row031-766-1113
4th row031-797-5032
5th row031-762-4668
ValueCountFrequency (%)
031-8028-7775 3
 
2.5%
031-798-4893 2
 
1.7%
031-766-4184 2
 
1.7%
031-726-9215 2
 
1.7%
031-798-7675 2
 
1.7%
031-797-6043 1
 
0.8%
031-713-1209 1
 
0.8%
031-765-2338 1
 
0.8%
031-761-0740 1
 
0.8%
031-797-4813 1
 
0.8%
Other values (104) 104
86.7%
2023-12-12T19:46:21.710783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 240
16.6%
1 190
13.1%
3 182
12.6%
0 174
12.0%
7 172
11.9%
6 135
9.3%
9 94
 
6.5%
8 77
 
5.3%
2 72
 
5.0%
4 59
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1206
83.4%
Dash Punctuation 240
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 190
15.8%
3 182
15.1%
0 174
14.4%
7 172
14.3%
6 135
11.2%
9 94
7.8%
8 77
6.4%
2 72
 
6.0%
4 59
 
4.9%
5 51
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 240
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1446
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 240
16.6%
1 190
13.1%
3 182
12.6%
0 174
12.0%
7 172
11.9%
6 135
9.3%
9 94
 
6.5%
8 77
 
5.3%
2 72
 
5.0%
4 59
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1446
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 240
16.6%
1 190
13.1%
3 182
12.6%
0 174
12.0%
7 172
11.9%
6 135
9.3%
9 94
 
6.5%
8 77
 
5.3%
2 72
 
5.0%
4 59
 
4.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2023-08-24 00:00:00
Maximum2023-08-24 00:00:00
2023-12-12T19:46:21.894322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:46:22.010624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T19:46:14.862460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:46:13.568727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:46:14.395786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:46:15.020101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:46:13.723743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:46:14.535841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:46:15.170551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:46:14.250631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:46:14.703517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:46:22.107160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번연면적세대수
연번1.0000.2930.238
연면적0.2931.0000.829
세대수0.2380.8291.000
2023-12-12T19:46:22.241720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번연면적세대수
연번1.0000.0580.144
연면적0.0581.0000.914
세대수0.1440.9141.000

Missing values

2023-12-12T19:46:15.346266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:46:15.623523image/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.
2023-12-12T19:46:15.800110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번아파트명주소연면적세대수관리사무소전화팩스번호데이터기준일자
01탄벌동 산호아파트경기도 광주시 탄벌동 3720082183031-763-0988031-764-36282023-08-24
12송정동 나산아파트경기도 광주시 송정동 58024214236031-762-0136031-762-01962023-08-24
23경안동 두진아파트경기도 광주시 경안동 12723714236031-764-7905031-766-11132023-08-24
34탄벌동 동보아파트경기도 광주시 탄벌동 4587574815031-797-5332031-797-50322023-08-24
45곤지암리 엘지아파트경기도 광주시 곤지암읍 곤지암리 337-1224749222031-761-4668031-762-46682023-08-24
56고산리 우림아파트경기도 광주시 오포읍 고산리 182-425797238031-766-5410031-767-54152023-08-24
67곤지암리 쌍용1차아파트경기도 광주시 곤지암읍 곤지암리 45953133440031-769-5238031-769-53222023-08-24
78양벌리 쌍용1차아파트경기도 광주시 오포읍 양벌리 28539539313031-769-7938031-769-79982023-08-24
89태전동 미진아파트경기도 광주시 태전동 66725732243031-768-1577031-768-15762023-08-24
910태전동 성원아파트경기도 광주시 태전동 22883532654031-768-0776031-768-40492023-08-24
연번아파트명주소연면적세대수관리사무소전화팩스번호데이터기준일자
125126초월읍 쌍동리 모아미래도 아파트경기도 광주시 초월읍 쌍동리 252-7<NA>587031-761-1340<NA>2023-08-24
126127경안동 경기광주역 금호리첸시아경기도 광주시 경안동 447<NA>447031-761-0204<NA>2023-08-24
127128역동 광주역 자연앤자이경기도 광주시 역동 169-15<NA>1031031-8027-9553<NA>2023-08-24
128129역동 경기광주역 행복주택경기도 광주시 역동 169-11<NA>500031-8027-9225<NA>2023-08-24
129130대쌍령리 쌍용 더플래티넘 광주경기도 광주시 초월읍 대쌍령리 산7-2<NA>873031-761-7770<NA>2023-08-24
130131장지동 태전 경남아너스빌 시그니처경기도 광주시 장지동 692-63<NA>624031-798-8441<NA>2023-08-24
131132고산리 오포 더샵 센트럴포레경기도 광주시 오포읍 고산리 656번지<NA>1396031-8027-2458<NA>2023-08-24
132133라시에라 태전경기도 광주시 태전동 744<NA>76031-763-2777<NA>2023-08-24
133134초월역 한라비발디 아파트경기도 광주시 초월읍 경충대로1127번길 58<NA>1108031-761-6705<NA>2023-08-24
134135힐스테이트 삼동역 아파트경기도 광주시 고불로 461-26<NA>565031-762-4155<NA>2023-08-24