Overview

Dataset statistics

Number of variables8
Number of observations86
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.7 KiB
Average record size in memory67.5 B

Variable types

Text3
Categorical3
Numeric2

Dataset

Description전라북도 군산시에 소재한 비상대피시설(시설명, 대피시설 주소, 구분, 시설규모, 활용가능인원, 지정일자 등) 목록을 제공합니다.
URLhttps://www.data.go.kr/data/15116911/fileData.do

Alerts

시설규모(제곱미터) is highly overall correlated with 활용가능인원High correlation
활용가능인원 is highly overall correlated with 시설규모(제곱미터)High correlation
구분 is highly overall correlated with 지정일자High correlation
관할읍면동 is highly overall correlated with 지정일자High correlation
지정일자 is highly overall correlated with 구분 and 1 other fieldsHigh correlation
구분 is highly imbalanced (84.1%)Imbalance
시설명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:37:30.359407
Analysis finished2023-12-12 23:37:31.544453
Duration1.19 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

UNIQUE 

Distinct86
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size820.0 B
2023-12-13T08:37:31.687541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length9.5
Min length3

Characters and Unicode

Total characters817
Distinct characters144
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique86 ?
Unique (%)100.0%

Sample

1st row군산소방서
2nd row금호 2차아파트
3rd row새한아파트
4th row부향하나로아파트101동
5th row부향하나로아파트102,103동
ValueCountFrequency (%)
아파트 20
 
11.6%
수송 10
 
5.8%
현대 8
 
4.7%
조촌현대아파트 5
 
2.9%
나운 4
 
2.3%
현대아파트 3
 
1.7%
세풍아파트 3
 
1.7%
102동 2
 
1.2%
디오션시티 2
 
1.2%
삼성아파트 2
 
1.2%
Other values (100) 113
65.7%
2023-12-13T08:37:32.085013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
87
 
10.6%
파 75
 
9.2%
아 74
 
9.1%
트 74
 
9.1%
대 25
 
3.1%
동 24
 
2.9%
1 23
 
2.8%
현 20
 
2.4%
0 14
 
1.7%
나 13
 
1.6%
Other values (134) 388
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 659
80.7%
Space Separator 87
 
10.6%
Decimal Number 63
 
7.7%
Uppercase Letter 4
 
0.5%
Other Punctuation 2
 
0.2%
Lowercase Letter 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 75
 
11.4%
아 74
 
11.2%
트 74
 
11.2%
대 25
 
3.8%
동 24
 
3.6%
현 20
 
3.0%
나 13
 
2.0%
차 12
 
1.8%
송 11
 
1.7%
하 11
 
1.7%
Other values (119) 320
48.6%
Decimal Number
ValueCountFrequency (%)
1 23
36.5%
0 14
22.2%
2 9
 
14.3%
3 8
 
12.7%
4 4
 
6.3%
5 2
 
3.2%
6 2
 
3.2%
7 1
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
L 2
50.0%
H 2
50.0%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
87
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 659
80.7%
Common 153
 
18.7%
Latin 5
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 75
 
11.4%
아 74
 
11.2%
트 74
 
11.2%
대 25
 
3.8%
동 24
 
3.6%
현 20
 
3.0%
나 13
 
2.0%
차 12
 
1.8%
송 11
 
1.7%
하 11
 
1.7%
Other values (119) 320
48.6%
Common
ValueCountFrequency (%)
87
56.9%
1 23
 
15.0%
0 14
 
9.2%
2 9
 
5.9%
3 8
 
5.2%
4 4
 
2.6%
5 2
 
1.3%
6 2
 
1.3%
. 1
 
0.7%
- 1
 
0.7%
Other values (2) 2
 
1.3%
Latin
ValueCountFrequency (%)
L 2
40.0%
H 2
40.0%
e 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 659
80.7%
ASCII 158
 
19.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
87
55.1%
1 23
 
14.6%
0 14
 
8.9%
2 9
 
5.7%
3 8
 
5.1%
4 4
 
2.5%
5 2
 
1.3%
L 2
 
1.3%
6 2
 
1.3%
H 2
 
1.3%
Other values (5) 5
 
3.2%
Hangul
ValueCountFrequency (%)
파 75
 
11.4%
아 74
 
11.2%
트 74
 
11.2%
대 25
 
3.8%
동 24
 
3.6%
현 20
 
3.0%
나 13
 
2.0%
차 12
 
1.8%
송 11
 
1.7%
하 11
 
1.7%
Other values (119) 320
48.6%

대피시설 도로명주소
Text

Distinct73
Distinct (%)84.9%
Missing0
Missing (%)0.0%
Memory size820.0 B
2023-12-13T08:37:32.432135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length35
Mean length30.139535
Min length21

Characters and Unicode

Total characters2592
Distinct characters180
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

Unique68 ?
Unique (%)79.1%

Sample

1st row전라북도 군산시 번영로 308 (사정동, 군산소방서)
2nd row전라북도 군산시 두란뜸2길 8 (사정동, 금호타운2단지)
3rd row전라북도 군산시 경촌3길 23 (경암동, 새한아파트)
4th row전라북도 군산시 경촌1길 56 (경암동, 경암동부향하나로아파트)
5th row전라북도 군산시 경촌1길 56 (경암동, 경암동부향하나로아파트)
ValueCountFrequency (%)
전라북도 86
 
16.7%
군산시 86
 
16.7%
나운동 16
 
3.1%
조촌동 14
 
2.7%
현대아파트 13
 
2.5%
수송동 12
 
2.3%
구암동 8
 
1.6%
10 7
 
1.4%
양안로 7
 
1.4%
진포1길 6
 
1.2%
Other values (197) 260
50.5%
2023-12-13T08:37:32.969690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
430
 
16.6%
동 106
 
4.1%
산 101
 
3.9%
군 97
 
3.7%
시 93
 
3.6%
북 89
 
3.4%
도 89
 
3.4%
전 88
 
3.4%
라 88
 
3.4%
( 87
 
3.4%
Other values (170) 1324
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1673
64.5%
Space Separator 430
 
16.6%
Decimal Number 230
 
8.9%
Open Punctuation 87
 
3.4%
Close Punctuation 87
 
3.4%
Other Punctuation 76
 
2.9%
Dash Punctuation 4
 
0.2%
Uppercase Letter 4
 
0.2%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 106
 
6.3%
산 101
 
6.0%
군 97
 
5.8%
시 93
 
5.6%
북 89
 
5.3%
도 89
 
5.3%
전 88
 
5.3%
라 88
 
5.3%
아 62
 
3.7%
파 60
 
3.6%
Other values (152) 800
47.8%
Decimal Number
ValueCountFrequency (%)
1 55
23.9%
2 38
16.5%
3 30
13.0%
6 22
 
9.6%
0 21
 
9.1%
4 17
 
7.4%
5 15
 
6.5%
8 13
 
5.7%
7 12
 
5.2%
9 7
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
H 2
50.0%
L 2
50.0%
Space Separator
ValueCountFrequency (%)
430
100.0%
Open Punctuation
ValueCountFrequency (%)
( 87
100.0%
Close Punctuation
ValueCountFrequency (%)
) 87
100.0%
Other Punctuation
ValueCountFrequency (%)
, 76
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1673
64.5%
Common 914
35.3%
Latin 5
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 106
 
6.3%
산 101
 
6.0%
군 97
 
5.8%
시 93
 
5.6%
북 89
 
5.3%
도 89
 
5.3%
전 88
 
5.3%
라 88
 
5.3%
아 62
 
3.7%
파 60
 
3.6%
Other values (152) 800
47.8%
Common
ValueCountFrequency (%)
430
47.0%
( 87
 
9.5%
) 87
 
9.5%
, 76
 
8.3%
1 55
 
6.0%
2 38
 
4.2%
3 30
 
3.3%
6 22
 
2.4%
0 21
 
2.3%
4 17
 
1.9%
Other values (5) 51
 
5.6%
Latin
ValueCountFrequency (%)
H 2
40.0%
L 2
40.0%
e 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1673
64.5%
ASCII 919
35.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
430
46.8%
( 87
 
9.5%
) 87
 
9.5%
, 76
 
8.3%
1 55
 
6.0%
2 38
 
4.1%
3 30
 
3.3%
6 22
 
2.4%
0 21
 
2.3%
4 17
 
1.8%
Other values (8) 56
 
6.1%
Hangul
ValueCountFrequency (%)
동 106
 
6.3%
산 101
 
6.0%
군 97
 
5.8%
시 93
 
5.6%
북 89
 
5.3%
도 89
 
5.3%
전 88
 
5.3%
라 88
 
5.3%
아 62
 
3.7%
파 60
 
3.6%
Other values (152) 800
47.8%

대피시설 지번주소
Text

Distinct73
Distinct (%)84.9%
Missing0
Missing (%)0.0%
Memory size820.0 B
2023-12-13T08:37:33.284248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length34
Mean length20.372093
Min length16

Characters and Unicode

Total characters1752
Distinct characters84
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

Unique68 ?
Unique (%)79.1%

Sample

1st row전라북도 군산시 사정동 171번지
2nd row전라북도 군산시 사정동 100번지
3rd row전라북도 군산시 경암동 539번지 9호
4th row전라북도 군산시 경암동 540번지 8호
5th row전라북도 군산시 경암동 540번지 8호
ValueCountFrequency (%)
전라북도 86
21.3%
군산시 86
21.3%
1호 16
 
4.0%
나운동 15
 
3.7%
조촌동 14
 
3.5%
2호 13
 
3.2%
수송동 12
 
3.0%
69번지 6
 
1.5%
소룡동 5
 
1.2%
155번지 5
 
1.2%
Other values (108) 145
36.0%
2023-12-13T08:37:33.773048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
317
18.1%
산 92
 
5.3%
북 90
 
5.1%
도 88
 
5.0%
군 87
 
5.0%
라 87
 
5.0%
전 86
 
4.9%
시 86
 
4.9%
동 83
 
4.7%
지 79
 
4.5%
Other values (74) 657
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1120
63.9%
Space Separator 317
 
18.1%
Decimal Number 312
 
17.8%
Dash Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 92
 
8.2%
북 90
 
8.0%
도 88
 
7.9%
군 87
 
7.8%
라 87
 
7.8%
전 86
 
7.7%
시 86
 
7.7%
동 83
 
7.4%
지 79
 
7.1%
번 77
 
6.9%
Other values (62) 265
23.7%
Decimal Number
ValueCountFrequency (%)
1 63
20.2%
5 42
13.5%
0 34
10.9%
3 32
10.3%
6 29
9.3%
9 27
8.7%
2 26
8.3%
8 26
8.3%
7 20
 
6.4%
4 13
 
4.2%
Space Separator
ValueCountFrequency (%)
317
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1120
63.9%
Common 632
36.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 92
 
8.2%
북 90
 
8.0%
도 88
 
7.9%
군 87
 
7.8%
라 87
 
7.8%
전 86
 
7.7%
시 86
 
7.7%
동 83
 
7.4%
지 79
 
7.1%
번 77
 
6.9%
Other values (62) 265
23.7%
Common
ValueCountFrequency (%)
317
50.2%
1 63
 
10.0%
5 42
 
6.6%
0 34
 
5.4%
3 32
 
5.1%
6 29
 
4.6%
9 27
 
4.3%
2 26
 
4.1%
8 26
 
4.1%
7 20
 
3.2%
Other values (2) 16
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1120
63.9%
ASCII 632
36.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
317
50.2%
1 63
 
10.0%
5 42
 
6.6%
0 34
 
5.4%
3 32
 
5.1%
6 29
 
4.6%
9 27
 
4.3%
2 26
 
4.1%
8 26
 
4.1%
7 20
 
3.2%
Other values (2) 16
 
2.5%
Hangul
ValueCountFrequency (%)
산 92
 
8.2%
북 90
 
8.0%
도 88
 
7.9%
군 87
 
7.8%
라 87
 
7.8%
전 86
 
7.7%
시 86
 
7.7%
동 83
 
7.4%
지 79
 
7.1%
번 77
 
6.9%
Other values (62) 265
23.7%

구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size820.0 B
지하
84 
지상
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지하 84
97.7%
지상 2
 
2.3%

Length

2023-12-13T08:37:33.932304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:37:34.036369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지하 84
97.7%
지상 2
 
2.3%

시설규모(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct84
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5322.8488
Minimum83
Maximum49645
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size906.0 B
2023-12-13T08:37:34.158228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum83
5-th percentile378.75
Q11576.25
median3596
Q35868.25
95-th percentile15401
Maximum49645
Range49562
Interquartile range (IQR)4292

Descriptive statistics

Standard deviation8028.3153
Coefficient of variation (CV)1.5082741
Kurtosis16.242504
Mean5322.8488
Median Absolute Deviation (MAD)2078.5
Skewness3.8587046
Sum457765
Variance64453847
MonotonicityNot monotonic
2023-12-13T08:37:34.315215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
426 2
 
2.3%
1712 2
 
2.3%
6972 1
 
1.2%
3877 1
 
1.2%
7132 1
 
1.2%
6628 1
 
1.2%
5542 1
 
1.2%
7519 1
 
1.2%
8028 1
 
1.2%
9923 1
 
1.2%
Other values (74) 74
86.0%
ValueCountFrequency (%)
83 1
1.2%
337 1
1.2%
341 1
1.2%
360 1
1.2%
363 1
1.2%
426 2
2.3%
495 1
1.2%
528 1
1.2%
604 1
1.2%
634 1
1.2%
ValueCountFrequency (%)
49645 1
1.2%
39793 1
1.2%
35005 1
1.2%
28474 1
1.2%
17227 1
1.2%
9923 1
1.2%
9401 1
1.2%
8110 1
1.2%
8028 1
1.2%
7637 1
1.2%

활용가능인원
Real number (ℝ)

HIGH CORRELATION 

Distinct84
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6454.3023
Minimum100
Maximum60175
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size906.0 B
2023-12-13T08:37:34.445517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile459
Q11910.25
median4358.5
Q37112.5
95-th percentile18667.5
Maximum60175
Range60075
Interquartile range (IQR)5202.25

Descriptive statistics

Standard deviation9730.8472
Coefficient of variation (CV)1.5076528
Kurtosis16.240884
Mean6454.3023
Median Absolute Deviation (MAD)2519.5
Skewness3.8582716
Sum555070
Variance94689387
MonotonicityNot monotonic
2023-12-13T08:37:34.572458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
516 2
 
2.3%
2075 2
 
2.3%
8450 1
 
1.2%
4966 1
 
1.2%
8644 1
 
1.2%
8033 1
 
1.2%
6717 1
 
1.2%
9113 1
 
1.2%
9730 1
 
1.2%
12027 1
 
1.2%
Other values (74) 74
86.0%
ValueCountFrequency (%)
100 1
1.2%
408 1
1.2%
413 1
1.2%
436 1
1.2%
440 1
1.2%
516 2
2.3%
600 1
1.2%
640 1
1.2%
710 1
1.2%
768 1
1.2%
ValueCountFrequency (%)
60175 1
1.2%
48233 1
1.2%
42430 1
1.2%
34513 1
1.2%
20881 1
1.2%
12027 1
1.2%
11395 1
1.2%
9830 1
1.2%
9730 1
1.2%
9256 1
1.2%

관할읍면동
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)19.8%
Missing0
Missing (%)0.0%
Memory size820.0 B
수송동
16 
조촌동
15 
나운3동
10 
구암동
8 
소룡동
7 
Other values (12)
30 

Length

Max length4
Median length3
Mean length3.2093023
Min length3

Unique

Unique2 ?
Unique (%)2.3%

Sample

1st row개정동
2nd row개정동
3rd row경암동
4th row경암동
5th row경암동

Common Values

ValueCountFrequency (%)
수송동 16
18.6%
조촌동 15
17.4%
나운3동 10
11.6%
구암동 8
9.3%
소룡동 7
8.1%
나운1동 4
 
4.7%
나운2동 4
 
4.7%
흥남동 3
 
3.5%
경암동 3
 
3.5%
월명동 3
 
3.5%
Other values (7) 13
15.1%

Length

2023-12-13T08:37:34.683204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수송동 16
18.6%
조촌동 15
17.4%
나운3동 10
11.6%
구암동 8
9.3%
소룡동 7
8.1%
나운1동 4
 
4.7%
나운2동 4
 
4.7%
월명동 3
 
3.5%
삼학동 3
 
3.5%
경암동 3
 
3.5%
Other values (7) 13
15.1%

지정일자
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)29.1%
Missing0
Missing (%)0.0%
Memory size820.0 B
2002-12-30
21 
2003-01-08
14 
2010-12-13
7 
2003-01-02
6 
2023-01-03
4 
Other values (20)
34 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique11 ?
Unique (%)12.8%

Sample

1st row2003-01-08
2nd row2003-01-08
3rd row2003-01-02
4th row2003-01-02
5th row2003-01-02

Common Values

ValueCountFrequency (%)
2002-12-30 21
24.4%
2003-01-08 14
16.3%
2010-12-13 7
 
8.1%
2003-01-02 6
 
7.0%
2023-01-03 4
 
4.7%
2010-12-31 4
 
4.7%
2003-01-06 4
 
4.7%
2004-01-01 3
 
3.5%
2017-12-04 2
 
2.3%
2021-06-18 2
 
2.3%
Other values (15) 19
22.1%

Length

2023-12-13T08:37:34.785720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2002-12-30 21
24.4%
2003-01-08 14
16.3%
2010-12-13 7
 
8.1%
2003-01-02 6
 
7.0%
2023-01-03 4
 
4.7%
2010-12-31 4
 
4.7%
2003-01-06 4
 
4.7%
2004-01-01 3
 
3.5%
2018-04-02 2
 
2.3%
2019-07-16 2
 
2.3%
Other values (15) 19
22.1%

Interactions

2023-12-13T08:37:31.110256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:37:30.904005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:37:31.207280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:37:31.002304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:37:34.867541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명대피시설 도로명주소대피시설 지번주소구분시설규모(제곱미터)활용가능인원관할읍면동지정일자
시설명1.0001.0001.0001.0001.0001.0001.0001.000
대피시설 도로명주소1.0001.0001.0001.0000.9990.9991.0001.000
대피시설 지번주소1.0001.0001.0001.0000.9990.9991.0001.000
구분1.0001.0001.0001.0000.0000.0000.5130.766
시설규모(제곱미터)1.0000.9990.9990.0001.0001.0000.5670.778
활용가능인원1.0000.9990.9990.0001.0001.0000.5670.778
관할읍면동1.0001.0001.0000.5130.5670.5671.0000.920
지정일자1.0001.0001.0000.7660.7780.7780.9201.000
2023-12-13T08:37:34.964779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정일자구분관할읍면동
지정일자1.0000.5810.536
구분0.5811.0000.417
관할읍면동0.5360.4171.000
2023-12-13T08:37:35.043115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설규모(제곱미터)활용가능인원구분관할읍면동지정일자
시설규모(제곱미터)1.0001.0000.0000.2740.412
활용가능인원1.0001.0000.0000.2740.412
구분0.0000.0001.0000.4170.581
관할읍면동0.2740.2740.4171.0000.536
지정일자0.4120.4120.5810.5361.000

Missing values

2023-12-13T08:37:31.332913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:37:31.484561image/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

시설명대피시설 도로명주소대피시설 지번주소구분시설규모(제곱미터)활용가능인원관할읍면동지정일자
0군산소방서전라북도 군산시 번영로 308 (사정동, 군산소방서)전라북도 군산시 사정동 171번지지하363440개정동2003-01-08
1금호 2차아파트전라북도 군산시 두란뜸2길 8 (사정동, 금호타운2단지)전라북도 군산시 사정동 100번지지하37824584개정동2003-01-08
2새한아파트전라북도 군산시 경촌3길 23 (경암동, 새한아파트)전라북도 군산시 경암동 539번지 9호지하21882652경암동2003-01-02
3부향하나로아파트101동전라북도 군산시 경촌1길 56 (경암동, 경암동부향하나로아파트)전라북도 군산시 경암동 540번지 8호지하27693356경암동2003-01-02
4부향하나로아파트102,103동전라북도 군산시 경촌1길 56 (경암동, 경암동부향하나로아파트)전라북도 군산시 경암동 540번지 8호지하70798580경암동2003-01-02
5구암동 현대아파트 1차전라북도 군산시 서당길 11 (구암동, 현대아파트)전라북도 군산시 구암동 65번지지하10771305구암동2002-12-30
6구암동 현대아파트 2차전라북도 군산시 서당길 11 (구암동, 현대아파트)전라북도 군산시 구암동 65번지지하17232088구암동2002-12-30
7세풍아파트 제1지하주차장전라북도 군산시 영명길 6 (구암동, 세풍아파트)전라북도 군산시 구암동 377번지지하12001454구암동2002-12-30
8세풍아파트 제2지하주차장전라북도 군산시 영명길 6 (구암동, 세풍아파트)전라북도 군산시 구암동 377번지지하20432476구암동2002-12-30
9세풍아파트 제3지하주차장전라북도 군산시 영명길 6 (구암동, 세풍아파트)전라북도 군산시 구암동 377번지지하25453084구암동2002-12-30
시설명대피시설 도로명주소대피시설 지번주소구분시설규모(제곱미터)활용가능인원관할읍면동지정일자
76조촌세경아파트전라북도 군산시 양안로 123 (조촌동, 세경아파트)전라북도 군산시 조촌동 907번지 1호지하360436조촌동2010-12-31
77타워써미트아파트전라북도 군산시 공단대로 54 (조촌동, 타워써미트)전라북도 군산시 조촌동 3931번지지하23102800조촌동2012-06-29
78군산 디오션시티 푸르지오전라북도 군산시 궁포2로 20 (조촌동, 군산디오션시티푸르지오)전라북도 군산시 조촌동 3943번지지하4964560175조촌동2019-07-16
79군산 디오션시티 e-편한세상전라북도 군산시 궁포2로 25 (조촌동, e편한세상디오션시티)전라북도 군산시 조촌동 3963번지지하2847434513조촌동2019-07-16
80하나리움레비뉴스테이아파트전라북도 군산시 대명4길 9 (금암동, 레비뉴스테이)전라북도 군산시 금암동 309 레비뉴스테이지하3500542430중앙동2021-06-18
81해망굴전라북도 군산시 군산창2길 21 (해망동)전라북도 군산시 해망동 1000번지 21호지상8261001해신동1999-01-04
82희망루아파트전라북도 군산시 월명로 584(해망동, 희망루)전라북도 군산시 해망동 1017 희망루지하14851800해신동2017-12-04
83현대세솔아파트전라북도 군산시 풍문2길 35 (장재동, 현대세솔아파트)전라북도 군산시 장재동 212번지지하47395744흥남동2003-01-08
84동흥남동 주공아파트전라북도 군산시 동흥남길 9 (동흥남동)전라북도 군산시 동흥남동 100번지지하39104739흥남동2007-02-01
85현대 메트로타워 아파트전라북도 군산시 대명길 3 (대명동, 현대메트로타워)전라북도 군산시 대명동 385번지 60호지하56446841흥남동2012-02-29