Overview

Dataset statistics

Number of variables7
Number of observations804
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory46.5 KiB
Average record size in memory59.2 B

Variable types

Numeric3
Categorical1
Text3

Dataset

Description전라남도 민방위 주민대피시설(총 804개소)에 대한 정보(시군별, 읍면동별, 민방위 주민대피시설 명칭, 도로명 주소, 확보면적, 대피 가능인원)를 조회할 수 있습니다.
Author전라남도
URLhttps://www.data.go.kr/data/15105960/fileData.do

Alerts

연번 is highly overall correlated with 시군High correlation
확보면적(제곱미터) is highly overall correlated with 대피 가능인원(명)High correlation
대피 가능인원(명) is highly overall correlated with 확보면적(제곱미터)High correlation
시군 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:14:44.613411
Analysis finished2023-12-12 14:14:47.013005
Duration2.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct804
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean402.5
Minimum1
Maximum804
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-12-12T23:14:47.105381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile41.15
Q1201.75
median402.5
Q3603.25
95-th percentile763.85
Maximum804
Range803
Interquartile range (IQR)401.5

Descriptive statistics

Standard deviation232.2391
Coefficient of variation (CV)0.57699156
Kurtosis-1.2
Mean402.5
Median Absolute Deviation (MAD)201
Skewness0
Sum323610
Variance53935
MonotonicityStrictly increasing
2023-12-12T23:14:47.265746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
542 1
 
0.1%
532 1
 
0.1%
533 1
 
0.1%
534 1
 
0.1%
535 1
 
0.1%
536 1
 
0.1%
537 1
 
0.1%
538 1
 
0.1%
539 1
 
0.1%
Other values (794) 794
98.8%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
804 1
0.1%
803 1
0.1%
802 1
0.1%
801 1
0.1%
800 1
0.1%
799 1
0.1%
798 1
0.1%
797 1
0.1%
796 1
0.1%
795 1
0.1%

시군
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
목포시
148 
여수시
127 
순천시
81 
광양시
80 
무안군
46 
Other values (17)
322 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
목포시 148
18.4%
여수시 127
15.8%
순천시 81
10.1%
광양시 80
10.0%
무안군 46
 
5.7%
나주시 45
 
5.6%
장흥군 34
 
4.2%
영광군 26
 
3.2%
강진군 23
 
2.9%
진도군 23
 
2.9%
Other values (12) 171
21.3%

Length

2023-12-12T23:14:47.410207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
목포시 148
18.4%
여수시 127
15.8%
순천시 81
10.1%
광양시 80
10.0%
무안군 46
 
5.7%
나주시 45
 
5.6%
장흥군 34
 
4.2%
영광군 26
 
3.2%
강진군 23
 
2.9%
진도군 23
 
2.9%
Other values (12) 171
21.3%

읍면동
Text

Distinct114
Distinct (%)14.2%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2023-12-12T23:14:47.708900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0062189
Min length2

Characters and Unicode

Total characters2417
Distinct characters118
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)3.5%

Sample

1st row강진읍
2nd row강진읍
3rd row강진읍
4th row강진읍
5th row강진읍
ValueCountFrequency (%)
장흥읍 31
 
3.9%
삼향읍 30
 
3.7%
영광읍 23
 
2.9%
쌍봉동 22
 
2.7%
금호동 22
 
2.7%
광양읍 21
 
2.6%
담양읍 21
 
2.6%
신흥동 21
 
2.6%
강진읍 21
 
2.6%
진도읍 20
 
2.5%
Other values (104) 572
71.1%
2023-12-12T23:14:48.215892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 424
 
17.5%
읍 336
 
13.9%
흥 69
 
2.9%
광 67
 
2.8%
영 59
 
2.4%
삼 58
 
2.4%
장 50
 
2.1%
면 50
 
2.1%
성 46
 
1.9%
양 45
 
1.9%
Other values (108) 1213
50.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2398
99.2%
Decimal Number 19
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 424
 
17.7%
읍 336
 
14.0%
흥 69
 
2.9%
광 67
 
2.8%
영 59
 
2.5%
삼 58
 
2.4%
장 50
 
2.1%
면 50
 
2.1%
성 46
 
1.9%
양 45
 
1.9%
Other values (105) 1194
49.8%
Decimal Number
ValueCountFrequency (%)
1 9
47.4%
2 9
47.4%
3 1
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2398
99.2%
Common 19
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 424
 
17.7%
읍 336
 
14.0%
흥 69
 
2.9%
광 67
 
2.8%
영 59
 
2.5%
삼 58
 
2.4%
장 50
 
2.1%
면 50
 
2.1%
성 46
 
1.9%
양 45
 
1.9%
Other values (105) 1194
49.8%
Common
ValueCountFrequency (%)
1 9
47.4%
2 9
47.4%
3 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2398
99.2%
ASCII 19
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 424
 
17.7%
읍 336
 
14.0%
흥 69
 
2.9%
광 67
 
2.8%
영 59
 
2.5%
삼 58
 
2.4%
장 50
 
2.1%
면 50
 
2.1%
성 46
 
1.9%
양 45
 
1.9%
Other values (105) 1194
49.8%
ASCII
ValueCountFrequency (%)
1 9
47.4%
2 9
47.4%
3 1
 
5.3%

민방위 주민대피시설 명칭
Text

Distinct791
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2023-12-12T23:14:48.566637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length17
Mean length8.3768657
Min length3

Characters and Unicode

Total characters6735
Distinct characters378
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique781 ?
Unique (%)97.1%

Sample

1st row강진의료원
2nd row참마트
3rd rowKT강진지점
4th row강진경찰서
5th row한국전력공사강진지사
ValueCountFrequency (%)
현대아파트 22
 
1.9%
아파트 20
 
1.7%
101동 20
 
1.7%
102동 15
 
1.3%
쌍봉동 14
 
1.2%
103동 13
 
1.1%
주공아파트 13
 
1.1%
지하 12
 
1.0%
신흥동 10
 
0.9%
돌산청솔아파트 9
 
0.8%
Other values (782) 1028
87.4%
2023-12-12T23:14:49.424000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
434
 
6.4%
아 339
 
5.0%
파 311
 
4.6%
트 308
 
4.6%
동 287
 
4.3%
1 210
 
3.1%
지 130
 
1.9%
2 126
 
1.9%
0 115
 
1.7%
차 107
 
1.6%
Other values (368) 4368
64.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5558
82.5%
Decimal Number 581
 
8.6%
Space Separator 434
 
6.4%
Uppercase Letter 83
 
1.2%
Open Punctuation 27
 
0.4%
Close Punctuation 27
 
0.4%
Dash Punctuation 10
 
0.1%
Lowercase Letter 9
 
0.1%
Other Punctuation 4
 
0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 339
 
6.1%
파 311
 
5.6%
트 308
 
5.5%
동 287
 
5.2%
지 130
 
2.3%
차 107
 
1.9%
스 79
 
1.4%
영 76
 
1.4%
대 74
 
1.3%
공 67
 
1.2%
Other values (334) 3780
68.0%
Uppercase Letter
ValueCountFrequency (%)
K 14
16.9%
T 14
16.9%
S 11
13.3%
A 11
13.3%
B 9
10.8%
H 8
9.6%
L 8
9.6%
C 2
 
2.4%
O 1
 
1.2%
Q 1
 
1.2%
Other values (4) 4
 
4.8%
Decimal Number
ValueCountFrequency (%)
1 210
36.1%
2 126
21.7%
0 115
19.8%
3 58
 
10.0%
5 25
 
4.3%
4 14
 
2.4%
6 12
 
2.1%
7 10
 
1.7%
8 6
 
1.0%
9 5
 
0.9%
Lowercase Letter
ValueCountFrequency (%)
e 4
44.4%
k 2
22.2%
t 2
22.2%
s 1
 
11.1%
Space Separator
ValueCountFrequency (%)
434
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5560
82.6%
Common 1083
 
16.1%
Latin 92
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 339
 
6.1%
파 311
 
5.6%
트 308
 
5.5%
동 287
 
5.2%
지 130
 
2.3%
차 107
 
1.9%
스 79
 
1.4%
영 76
 
1.4%
대 74
 
1.3%
공 67
 
1.2%
Other values (335) 3782
68.0%
Latin
ValueCountFrequency (%)
K 14
15.2%
T 14
15.2%
S 11
12.0%
A 11
12.0%
B 9
9.8%
H 8
8.7%
L 8
8.7%
e 4
 
4.3%
k 2
 
2.2%
t 2
 
2.2%
Other values (8) 9
9.8%
Common
ValueCountFrequency (%)
434
40.1%
1 210
19.4%
2 126
 
11.6%
0 115
 
10.6%
3 58
 
5.4%
( 27
 
2.5%
) 27
 
2.5%
5 25
 
2.3%
4 14
 
1.3%
6 12
 
1.1%
Other values (5) 35
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5558
82.5%
ASCII 1175
 
17.4%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
434
36.9%
1 210
17.9%
2 126
 
10.7%
0 115
 
9.8%
3 58
 
4.9%
( 27
 
2.3%
) 27
 
2.3%
5 25
 
2.1%
K 14
 
1.2%
T 14
 
1.2%
Other values (23) 125
 
10.6%
Hangul
ValueCountFrequency (%)
아 339
 
6.1%
파 311
 
5.6%
트 308
 
5.5%
동 287
 
5.2%
지 130
 
2.3%
차 107
 
1.9%
스 79
 
1.4%
영 76
 
1.4%
대 74
 
1.3%
공 67
 
1.2%
Other values (334) 3780
68.0%
None
ValueCountFrequency (%)
㈜ 2
100.0%

도로명 주소
Text

Distinct679
Distinct (%)84.5%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2023-12-12T23:14:49.814239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length37
Mean length25.263682
Min length14

Characters and Unicode

Total characters20312
Distinct characters355
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique611 ?
Unique (%)76.0%

Sample

1st row전라남도 강진군 강진읍 탐진로 5
2nd row전라남도 강진군 강진읍 평동2길 30
3rd row전라남도 강진군 강진읍 영랑로 8-0
4th row전라남도 강진군 강진읍 탐진로 119
5th row전라남도 강진군 강진읍 목리길 50-0
ValueCountFrequency (%)
전라남도 792
 
18.5%
목포시 148
 
3.5%
여수시 127
 
3.0%
순천시 81
 
1.9%
광양시 80
 
1.9%
무안군 46
 
1.1%
나주시 45
 
1.1%
상동 34
 
0.8%
장흥군 34
 
0.8%
장흥읍 31
 
0.7%
Other values (1165) 2857
66.8%
2023-12-12T23:14:50.321764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3477
 
17.1%
남 931
 
4.6%
도 887
 
4.4%
전 825
 
4.1%
라 824
 
4.1%
로 553
 
2.7%
1 549
 
2.7%
시 529
 
2.6%
( 425
 
2.1%
) 425
 
2.1%
Other values (345) 10887
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13185
64.9%
Space Separator 3477
 
17.1%
Decimal Number 2390
 
11.8%
Open Punctuation 425
 
2.1%
Close Punctuation 425
 
2.1%
Other Punctuation 273
 
1.3%
Dash Punctuation 124
 
0.6%
Uppercase Letter 9
 
< 0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 931
 
7.1%
도 887
 
6.7%
전 825
 
6.3%
라 824
 
6.2%
로 553
 
4.2%
시 529
 
4.0%
동 415
 
3.1%
군 342
 
2.6%
길 334
 
2.5%
읍 330
 
2.5%
Other values (322) 7215
54.7%
Decimal Number
ValueCountFrequency (%)
1 549
23.0%
2 379
15.9%
3 307
12.8%
4 207
 
8.7%
5 199
 
8.3%
6 178
 
7.4%
0 175
 
7.3%
7 154
 
6.4%
8 133
 
5.6%
9 109
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
K 3
33.3%
T 3
33.3%
G 1
 
11.1%
L 1
 
11.1%
S 1
 
11.1%
Lowercase Letter
ValueCountFrequency (%)
e 2
50.0%
t 1
25.0%
k 1
25.0%
Space Separator
ValueCountFrequency (%)
3477
100.0%
Open Punctuation
ValueCountFrequency (%)
( 425
100.0%
Close Punctuation
ValueCountFrequency (%)
) 425
100.0%
Other Punctuation
ValueCountFrequency (%)
, 273
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 124
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13185
64.9%
Common 7114
35.0%
Latin 13
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 931
 
7.1%
도 887
 
6.7%
전 825
 
6.3%
라 824
 
6.2%
로 553
 
4.2%
시 529
 
4.0%
동 415
 
3.1%
군 342
 
2.6%
길 334
 
2.5%
읍 330
 
2.5%
Other values (322) 7215
54.7%
Common
ValueCountFrequency (%)
3477
48.9%
1 549
 
7.7%
( 425
 
6.0%
) 425
 
6.0%
2 379
 
5.3%
3 307
 
4.3%
, 273
 
3.8%
4 207
 
2.9%
5 199
 
2.8%
6 178
 
2.5%
Other values (5) 695
 
9.8%
Latin
ValueCountFrequency (%)
K 3
23.1%
T 3
23.1%
e 2
15.4%
G 1
 
7.7%
L 1
 
7.7%
S 1
 
7.7%
t 1
 
7.7%
k 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13185
64.9%
ASCII 7127
35.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3477
48.8%
1 549
 
7.7%
( 425
 
6.0%
) 425
 
6.0%
2 379
 
5.3%
3 307
 
4.3%
, 273
 
3.8%
4 207
 
2.9%
5 199
 
2.8%
6 178
 
2.5%
Other values (13) 708
 
9.9%
Hangul
ValueCountFrequency (%)
남 931
 
7.1%
도 887
 
6.7%
전 825
 
6.3%
라 824
 
6.2%
로 553
 
4.2%
시 529
 
4.0%
동 415
 
3.1%
군 342
 
2.6%
길 334
 
2.5%
읍 330
 
2.5%
Other values (322) 7215
54.7%

확보면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct611
Distinct (%)76.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2890.7139
Minimum35
Maximum64212
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-12-12T23:14:50.519036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35
5-th percentile132
Q1395
median835
Q32401.75
95-th percentile11694.85
Maximum64212
Range64177
Interquartile range (IQR)2006.75

Descriptive statistics

Standard deviation6243.7426
Coefficient of variation (CV)2.159931
Kurtosis30.072862
Mean2890.7139
Median Absolute Deviation (MAD)581.5
Skewness4.8779848
Sum2324134
Variance38984321
MonotonicityNot monotonic
2023-12-12T23:14:50.670089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
165 9
 
1.1%
132 9
 
1.1%
752 8
 
1.0%
198 7
 
0.9%
572 5
 
0.6%
527 5
 
0.6%
565 5
 
0.6%
545 5
 
0.6%
331 5
 
0.6%
172 5
 
0.6%
Other values (601) 741
92.2%
ValueCountFrequency (%)
35 1
 
0.1%
50 3
0.4%
66 2
0.2%
69 1
 
0.1%
83 3
0.4%
86 4
0.5%
97 1
 
0.1%
99 4
0.5%
100 1
 
0.1%
103 1
 
0.1%
ValueCountFrequency (%)
64212 1
0.1%
51369 1
0.1%
49373 1
0.1%
44321 1
0.1%
43860 1
0.1%
42618 1
0.1%
34424 2
0.2%
32733 1
0.1%
31488 1
0.1%
30749 1
0.1%

대피 가능인원(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct613
Distinct (%)76.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3503.5199
Minimum42
Maximum77832
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-12-12T23:14:50.804212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum42
5-th percentile160
Q1479
median1011.5
Q32911.25
95-th percentile14174.75
Maximum77832
Range77790
Interquartile range (IQR)2432.25

Descriptive statistics

Standard deviation7568.152
Coefficient of variation (CV)2.1601567
Kurtosis30.073006
Mean3503.5199
Median Absolute Deviation (MAD)704.5
Skewness4.8779999
Sum2816830
Variance57276925
MonotonicityNot monotonic
2023-12-12T23:14:50.973280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
160 9
 
1.1%
200 9
 
1.1%
911 8
 
1.0%
400 7
 
0.9%
240 7
 
0.9%
684 5
 
0.6%
208 5
 
0.6%
638 5
 
0.6%
693 5
 
0.6%
408 4
 
0.5%
Other values (603) 740
92.0%
ValueCountFrequency (%)
42 1
 
0.1%
60 3
0.4%
80 2
0.2%
84 1
 
0.1%
100 3
0.4%
104 4
0.5%
117 1
 
0.1%
120 4
0.5%
121 1
 
0.1%
124 1
 
0.1%
ValueCountFrequency (%)
77832 1
0.1%
62265 1
0.1%
59846 1
0.1%
53722 1
0.1%
53163 1
0.1%
51658 1
0.1%
41726 2
0.2%
39676 1
0.1%
38167 1
0.1%
37271 1
0.1%

Interactions

2023-12-12T23:14:46.361414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:45.408108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:45.907752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:46.501874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:45.570168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:46.069259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:46.617239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:45.729537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:46.222745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:14:51.081380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군확보면적(제곱미터)대피 가능인원(명)
연번1.0000.9560.2660.266
시군0.9561.0000.1790.179
확보면적(제곱미터)0.2660.1791.0001.000
대피 가능인원(명)0.2660.1791.0001.000
2023-12-12T23:14:51.174290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번확보면적(제곱미터)대피 가능인원(명)시군
연번1.0000.0280.0280.775
확보면적(제곱미터)0.0281.0001.0000.069
대피 가능인원(명)0.0281.0001.0000.069
시군0.7750.0690.0691.000

Missing values

2023-12-12T23:14:46.783376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:14:46.950735image/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

연번시군읍면동민방위 주민대피시설 명칭도로명 주소확보면적(제곱미터)대피 가능인원(명)
01강진군강진읍강진의료원전라남도 강진군 강진읍 탐진로 5698846
12강진군강진읍참마트전라남도 강진군 강진읍 평동2길 3012581524
23강진군강진읍KT강진지점전라남도 강진군 강진읍 영랑로 8-08281003
34강진군강진읍강진경찰서전라남도 강진군 강진읍 탐진로 119274332
45강진군강진읍한국전력공사강진지사전라남도 강진군 강진읍 목리길 50-0543658
56강진군강진읍씨엔에스2차아파트전라남도 강진군 강진읍 탐진로 6012231482
67강진군강진읍강진군청전라남도 강진군 강진읍 탐진로 110-0436528
78강진군강진읍대아아파트전라남도 강진군 강진읍 중앙동길 6-099120
89강진군강진읍강진교육지원청전라남도 강진군 강진읍 금릉6길 8-083100
910강진군강진읍건우 1차아파트전라남도 강진군 강진읍 고성길 399120
연번시군읍면동민방위 주민대피시설 명칭도로명 주소확보면적(제곱미터)대피 가능인원(명)
794795화순군화순읍화순군민회관전라남도 화순군 화순읍 진각로 85172208
795796화순군화순읍화순읍사무소전라남도 화순군 화순읍 중앙로 20-4155187
796797화순군화순읍금호아파트전라남도 화순군 화순읍 광덕로 20356006787
797798화순군화순읍부영5차아파트전라남도 화순군 화순읍 광덕로 20261057400
798799화순군화순읍부영3차아파트전라남도 화순군 화순읍 광덕로 180830410065
799800화순군화순읍부영2차아파트전라남도 화순군 화순읍 광덕로 15524372953
800801화순군화순읍부영6차아파트전라남도 화순군 화순읍 광덕로 21578369498
801802화순군화순읍화순군의회전라남도 화순군 화순읍 동헌길 2310501272
802803화순군화순읍하니움 문화스포츠센터전라남도 화순군 화순읍 학포로 269862297550
803804화순군화순읍광덕택지지하공영주차장전라남도 화순군 화순읍 만연로 4046365619