Overview

Dataset statistics

Number of variables9
Number of observations70
Missing cells16
Missing cells (%)2.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.3 KiB
Average record size in memory76.9 B

Variable types

Numeric3
Text4
DateTime1
Categorical1

Dataset

Description주택법에 의해 승인된 포천시 공공주택 건축물 정보 제공
Author경기도 포천시
URLhttps://www.data.go.kr/data/3071305/fileData.do

Alerts

데이터기준일 has constant value ""Constant
번호 is highly overall correlated with 층수High correlation
층수 is highly overall correlated with 번호High correlation
전화번호 has 16 (22.9%) missing valuesMissing
번호 has unique valuesUnique
공동주택명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:15:17.850881
Analysis finished2023-12-12 14:15:19.443183
Duration1.59 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.5
Minimum1
Maximum70
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2023-12-12T23:15:19.523277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.45
Q118.25
median35.5
Q352.75
95-th percentile66.55
Maximum70
Range69
Interquartile range (IQR)34.5

Descriptive statistics

Standard deviation20.351085
Coefficient of variation (CV)0.57327
Kurtosis-1.2
Mean35.5
Median Absolute Deviation (MAD)17.5
Skewness0
Sum2485
Variance414.16667
MonotonicityStrictly increasing
2023-12-12T23:15:19.664396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.4%
46 1
 
1.4%
52 1
 
1.4%
51 1
 
1.4%
50 1
 
1.4%
49 1
 
1.4%
48 1
 
1.4%
47 1
 
1.4%
45 1
 
1.4%
54 1
 
1.4%
Other values (60) 60
85.7%
ValueCountFrequency (%)
1 1
1.4%
2 1
1.4%
3 1
1.4%
4 1
1.4%
5 1
1.4%
6 1
1.4%
7 1
1.4%
8 1
1.4%
9 1
1.4%
10 1
1.4%
ValueCountFrequency (%)
70 1
1.4%
69 1
1.4%
68 1
1.4%
67 1
1.4%
66 1
1.4%
65 1
1.4%
64 1
1.4%
63 1
1.4%
62 1
1.4%
61 1
1.4%

공동주택명
Text

UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size692.0 B
2023-12-12T23:15:20.239119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length7.1285714
Min length4

Characters and Unicode

Total characters499
Distinct characters119
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

Unique70 ?
Unique (%)100.0%

Sample

1st row일신건영아파트
2nd row원일1차아파트
3rd row한국개나리아파트
4th row원일2차아파트
5th row신포천아파트
ValueCountFrequency (%)
금용아파트 3
 
3.6%
천보아파트 3
 
3.6%
원일아파트 2
 
2.4%
1차 2
 
2.4%
3차 2
 
2.4%
리버아파트 1
 
1.2%
세명연립 1
 
1.2%
c동 1
 
1.2%
b동 1
 
1.2%
a동 1
 
1.2%
Other values (66) 66
79.5%
2023-12-12T23:15:20.695580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 43
 
8.6%
파 39
 
7.8%
트 38
 
7.6%
연 17
 
3.4%
( 16
 
3.2%
) 16
 
3.2%
립 16
 
3.2%
차 15
 
3.0%
13
 
2.6%
동 11
 
2.2%
Other values (109) 275
55.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 428
85.8%
Decimal Number 23
 
4.6%
Open Punctuation 16
 
3.2%
Close Punctuation 16
 
3.2%
Space Separator 13
 
2.6%
Uppercase Letter 3
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 43
 
10.0%
파 39
 
9.1%
트 38
 
8.9%
연 17
 
4.0%
립 16
 
3.7%
차 15
 
3.5%
동 11
 
2.6%
천 10
 
2.3%
일 10
 
2.3%
신 9
 
2.1%
Other values (98) 220
51.4%
Decimal Number
ValueCountFrequency (%)
2 9
39.1%
1 8
34.8%
3 3
 
13.0%
5 2
 
8.7%
4 1
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
C 1
33.3%
B 1
33.3%
A 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 428
85.8%
Common 68
 
13.6%
Latin 3
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 43
 
10.0%
파 39
 
9.1%
트 38
 
8.9%
연 17
 
4.0%
립 16
 
3.7%
차 15
 
3.5%
동 11
 
2.6%
천 10
 
2.3%
일 10
 
2.3%
신 9
 
2.1%
Other values (98) 220
51.4%
Common
ValueCountFrequency (%)
( 16
23.5%
) 16
23.5%
13
19.1%
2 9
13.2%
1 8
11.8%
3 3
 
4.4%
5 2
 
2.9%
4 1
 
1.5%
Latin
ValueCountFrequency (%)
C 1
33.3%
B 1
33.3%
A 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 428
85.8%
ASCII 71
 
14.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 43
 
10.0%
파 39
 
9.1%
트 38
 
8.9%
연 17
 
4.0%
립 16
 
3.7%
차 15
 
3.5%
동 11
 
2.6%
천 10
 
2.3%
일 10
 
2.3%
신 9
 
2.1%
Other values (98) 220
51.4%
ASCII
ValueCountFrequency (%)
( 16
22.5%
) 16
22.5%
13
18.3%
2 9
12.7%
1 8
11.3%
3 3
 
4.2%
5 2
 
2.8%
C 1
 
1.4%
B 1
 
1.4%
A 1
 
1.4%

도로명 주소
Text

Distinct66
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size692.0 B
2023-12-12T23:15:20.999290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length20.071429
Min length14

Characters and Unicode

Total characters1405
Distinct characters74
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)90.0%

Sample

1st row경기도 포천시 소흘읍 솔모루로 13-14, 16
2nd row경기도 포천시 소흘읍 봉솔로2길 15
3rd row경기도 포천시 소흘읍 솔모루로81번길 27
4th row경기도 포천시 소흘읍 봉솔로2길 5-9
5th row경기도 포천시 신북면 호국로 2135-11
ValueCountFrequency (%)
포천시 70
21.3%
경기도 69
21.0%
소흘읍 22
 
6.7%
신북면 9
 
2.7%
영북면 6
 
1.8%
호국로 6
 
1.8%
일동면 6
 
1.8%
솔모루로 6
 
1.8%
태봉로 5
 
1.5%
군내면 4
 
1.2%
Other values (98) 126
38.3%
2023-12-12T23:15:21.501947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
260
18.5%
1 78
 
5.6%
천 76
 
5.4%
포 72
 
5.1%
경 70
 
5.0%
시 70
 
5.0%
도 69
 
4.9%
기 69
 
4.9%
로 57
 
4.1%
2 37
 
2.6%
Other values (64) 547
38.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 841
59.9%
Decimal Number 275
 
19.6%
Space Separator 260
 
18.5%
Dash Punctuation 27
 
1.9%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 76
 
9.0%
포 72
 
8.6%
경 70
 
8.3%
시 70
 
8.3%
도 69
 
8.2%
기 69
 
8.2%
로 57
 
6.8%
길 36
 
4.3%
면 26
 
3.1%
소 24
 
2.9%
Other values (51) 272
32.3%
Decimal Number
ValueCountFrequency (%)
1 78
28.4%
2 37
13.5%
8 25
 
9.1%
4 25
 
9.1%
3 24
 
8.7%
6 21
 
7.6%
5 20
 
7.3%
9 17
 
6.2%
7 16
 
5.8%
0 12
 
4.4%
Space Separator
ValueCountFrequency (%)
260
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 841
59.9%
Common 564
40.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 76
 
9.0%
포 72
 
8.6%
경 70
 
8.3%
시 70
 
8.3%
도 69
 
8.2%
기 69
 
8.2%
로 57
 
6.8%
길 36
 
4.3%
면 26
 
3.1%
소 24
 
2.9%
Other values (51) 272
32.3%
Common
ValueCountFrequency (%)
260
46.1%
1 78
 
13.8%
2 37
 
6.6%
- 27
 
4.8%
8 25
 
4.4%
4 25
 
4.4%
3 24
 
4.3%
6 21
 
3.7%
5 20
 
3.5%
9 17
 
3.0%
Other values (3) 30
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 841
59.9%
ASCII 564
40.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
260
46.1%
1 78
 
13.8%
2 37
 
6.6%
- 27
 
4.8%
8 25
 
4.4%
4 25
 
4.4%
3 24
 
4.3%
6 21
 
3.7%
5 20
 
3.5%
9 17
 
3.0%
Other values (3) 30
 
5.3%
Hangul
ValueCountFrequency (%)
천 76
 
9.0%
포 72
 
8.6%
경 70
 
8.3%
시 70
 
8.3%
도 69
 
8.2%
기 69
 
8.2%
로 57
 
6.8%
길 36
 
4.3%
면 26
 
3.1%
소 24
 
2.9%
Other values (51) 272
32.3%

동수
Real number (ℝ)

Distinct14
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6
Minimum1
Maximum19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2023-12-12T23:15:21.663420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q34
95-th percentile11.1
Maximum19
Range18
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.5687858
Coefficient of variation (CV)0.99132938
Kurtosis6.3798434
Mean3.6
Median Absolute Deviation (MAD)1
Skewness2.4239935
Sum252
Variance12.736232
MonotonicityNot monotonic
2023-12-12T23:15:21.803308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
2 26
37.1%
1 15
21.4%
4 8
 
11.4%
3 7
 
10.0%
6 2
 
2.9%
5 2
 
2.9%
7 2
 
2.9%
9 2
 
2.9%
8 1
 
1.4%
12 1
 
1.4%
Other values (4) 4
 
5.7%
ValueCountFrequency (%)
1 15
21.4%
2 26
37.1%
3 7
 
10.0%
4 8
 
11.4%
5 2
 
2.9%
6 2
 
2.9%
7 2
 
2.9%
8 1
 
1.4%
9 2
 
2.9%
10 1
 
1.4%
ValueCountFrequency (%)
19 1
1.4%
16 1
1.4%
13 1
1.4%
12 1
1.4%
10 1
1.4%
9 2
2.9%
8 1
1.4%
7 2
2.9%
6 2
2.9%
5 2
2.9%

층수
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)32.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.185714
Minimum2
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2023-12-12T23:15:21.938948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q14
median11
Q315
95-th percentile22.55
Maximum26
Range24
Interquartile range (IQR)11

Descriptive statistics

Standard deviation7.1632979
Coefficient of variation (CV)0.640397
Kurtosis-1.2635629
Mean11.185714
Median Absolute Deviation (MAD)6.5
Skewness0.3169111
Sum783
Variance51.312836
MonotonicityNot monotonic
2023-12-12T23:15:22.061964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
15 15
21.4%
3 11
15.7%
4 8
11.4%
5 6
 
8.6%
20 5
 
7.1%
6 4
 
5.7%
22 3
 
4.3%
10 2
 
2.9%
16 2
 
2.9%
12 1
 
1.4%
Other values (13) 13
18.6%
ValueCountFrequency (%)
2 1
 
1.4%
3 11
15.7%
4 8
11.4%
5 6
8.6%
6 4
 
5.7%
7 1
 
1.4%
8 1
 
1.4%
9 1
 
1.4%
10 2
 
2.9%
12 1
 
1.4%
ValueCountFrequency (%)
26 1
 
1.4%
25 1
 
1.4%
24 1
 
1.4%
23 1
 
1.4%
22 3
4.3%
21 1
 
1.4%
20 5
7.1%
19 1
 
1.4%
18 1
 
1.4%
16 2
 
2.9%

세대수
Text

Distinct61
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Memory size692.0 B
2023-12-12T23:15:22.311309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.6
Min length2

Characters and Unicode

Total characters182
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

Unique52 ?
Unique (%)74.3%

Sample

1st row176
2nd row489
3rd row292
4th row160
5th row299
ValueCountFrequency (%)
36 2
 
2.9%
88 2
 
2.9%
24 2
 
2.9%
48 2
 
2.9%
156 2
 
2.9%
33 2
 
2.9%
60 2
 
2.9%
28 2
 
2.9%
40 2
 
2.9%
139 1
 
1.4%
Other values (51) 51
72.9%
2023-12-12T23:15:22.745587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 22
12.1%
8 22
12.1%
2 22
12.1%
1 22
12.1%
4 21
11.5%
9 20
11.0%
3 19
10.4%
0 15
8.2%
7 10
5.5%
5 7
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 180
98.9%
Other Punctuation 2
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 22
12.2%
8 22
12.2%
2 22
12.2%
1 22
12.2%
4 21
11.7%
9 20
11.1%
3 19
10.6%
0 15
8.3%
7 10
5.6%
5 7
 
3.9%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 182
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 22
12.1%
8 22
12.1%
2 22
12.1%
1 22
12.1%
4 21
11.5%
9 20
11.0%
3 19
10.4%
0 15
8.2%
7 10
5.5%
5 7
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 182
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 22
12.1%
8 22
12.1%
2 22
12.1%
1 22
12.1%
4 21
11.5%
9 20
11.0%
3 19
10.4%
0 15
8.2%
7 10
5.5%
5 7
 
3.8%

사용승인일
Date

Distinct63
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size692.0 B
Minimum1982-12-10 00:00:00
Maximum2020-02-07 00:00:00
2023-12-12T23:15:22.888345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:23.055062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

전화번호
Text

MISSING 

Distinct52
Distinct (%)96.3%
Missing16
Missing (%)22.9%
Memory size692.0 B
2023-12-12T23:15:23.319481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length12
Mean length12.259259
Min length11

Characters and Unicode

Total characters662
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)92.6%

Sample

1st row031-542-5527
2nd row031-542-9554
3rd row031-542-9117
4th row031-542-3889
5th row031-536-4407
ValueCountFrequency (%)
031-534-0220 2
 
3.6%
031-533-2626 2
 
3.6%
031-542-6361 1
 
1.8%
031-535-1767 1
 
1.8%
031-534-7177 1
 
1.8%
031-544-0466 1
 
1.8%
031-536-6710 1
 
1.8%
031-542-6747 1
 
1.8%
031-542-3882 1
 
1.8%
031-542-9924 1
 
1.8%
Other values (43) 43
78.2%
2023-12-12T23:15:23.706547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 108
16.3%
- 108
16.3%
1 85
12.8%
0 74
11.2%
5 74
11.2%
4 57
8.6%
2 48
7.3%
6 39
 
5.9%
7 22
 
3.3%
9 17
 
2.6%
Other values (2) 30
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 539
81.4%
Dash Punctuation 108
 
16.3%
Space Separator 15
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 108
20.0%
1 85
15.8%
0 74
13.7%
5 74
13.7%
4 57
10.6%
2 48
8.9%
6 39
 
7.2%
7 22
 
4.1%
9 17
 
3.2%
8 15
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 108
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 662
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 108
16.3%
- 108
16.3%
1 85
12.8%
0 74
11.2%
5 74
11.2%
4 57
8.6%
2 48
7.3%
6 39
 
5.9%
7 22
 
3.3%
9 17
 
2.6%
Other values (2) 30
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 662
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 108
16.3%
- 108
16.3%
1 85
12.8%
0 74
11.2%
5 74
11.2%
4 57
8.6%
2 48
7.3%
6 39
 
5.9%
7 22
 
3.3%
9 17
 
2.6%
Other values (2) 30
 
4.5%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size692.0 B
2020-09-15
70 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-09-15
2nd row2020-09-15
3rd row2020-09-15
4th row2020-09-15
5th row2020-09-15

Common Values

ValueCountFrequency (%)
2020-09-15 70
100.0%

Length

2023-12-12T23:15:23.881921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:15:24.006106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-09-15 70
100.0%

Interactions

2023-12-12T23:15:19.029037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:18.428790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:18.737542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:19.106166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:18.513456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:18.833034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:19.178952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:18.639301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:18.931819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:15:24.078868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호공동주택명도로명 주소동수층수세대수사용승인일전화번호
번호1.0001.0000.9880.4390.8220.9010.9820.980
공동주택명1.0001.0001.0001.0001.0001.0001.0001.000
도로명 주소0.9881.0001.0001.0001.0000.9340.9951.000
동수0.4391.0001.0001.0000.4100.9981.0001.000
층수0.8221.0001.0000.4101.0000.9890.9901.000
세대수0.9011.0000.9340.9980.9891.0000.8980.997
사용승인일0.9821.0000.9951.0000.9900.8981.0001.000
전화번호0.9801.0001.0001.0001.0000.9971.0001.000
2023-12-12T23:15:24.197375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호동수층수
번호1.000-0.479-0.620
동수-0.4791.0000.375
층수-0.6200.3751.000

Missing values

2023-12-12T23:15:19.271160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:15:19.391946image/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

번호공동주택명도로명 주소동수층수세대수사용승인일전화번호데이터기준일
01일신건영아파트경기도 포천시 소흘읍 솔모루로 13-14, 162121761993-05-10031-542-55272020-09-15
12원일1차아파트경기도 포천시 소흘읍 봉솔로2길 156154891993-07-30031-542-95542020-09-15
23한국개나리아파트경기도 포천시 소흘읍 솔모루로81번길 272202921994-12-31031-542-91172020-09-15
34원일2차아파트경기도 포천시 소흘읍 봉솔로2길 5-9281601995-08-08031-542-38892020-09-15
45신포천아파트경기도 포천시 신북면 호국로 2135-114152991995-12-01031-536-44072020-09-15
56산호그린빌아파트경기도 포천시 신북면 호국로 1886-275154792002-04-30031-532-00442020-09-15
67윤중아파트경기도 포천시 신북면 호국로 2135-146155782003-07-11031-533-35012020-09-15
78신아포미재아파트경기도 포천시 신북면 호국로 1886-434132262005-01-12031-531-31522020-09-15
89한국아파트경기도 포천시 호병골길 162152641993-03-17031-535-35122020-09-15
910현대아파트경기도 포천시 포천로 1642, 16442151701996-10-18031-535-99642020-09-15
번호공동주택명도로명 주소동수층수세대수사용승인일전화번호데이터기준일
6061다화연립경기도 포천시 영북면 운천안1길 25-113331988-12-30031-533-26982020-09-15
6162동영연립경기도 포천시 관인면 창동로 185414241990-01-08<NA>2020-09-15
6263학산아파트경기도 포천시 호국로1331번길 8-2424881986-06-23031-533-76762020-09-15
6364태봉연립경기도 포천시 소흘읍 솔모루로118번길 513241985-12-18031-542-63612020-09-15
6465홍익빌라(연립)경기도 포천시 일동면 운악청계로 171334482010-02-1102-475-31012020-09-15
6566호병일우테라스(1차)경기도 포천시 호병골길 41-1424472000-11-25<NA>2020-09-15
6667호병일우테라스(2차)경기도 포천시 호병골1길 3024402002-11-06<NA>2020-09-15
6768우리마을(연립)경기도 포천시 삼육사로 2186번길 1614401999-12-22<NA>2020-09-15
6869코아루더스카이아파트1단지경기도 포천시 원앙로 56-82261662020-02-07031-533-26262020-09-15
6970코아루더스카이아파트2단지경기도 포천시 원앙로 56-7124882020-02-07031-533-26262020-09-15