Overview

Dataset statistics

Number of variables13
Number of observations109
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.5 KiB
Average record size in memory108.2 B

Variable types

Numeric3
Categorical5
Text3
DateTime2

Dataset

Description인천광역시 서구 민방위 대피시설에 관한 데이터입니다. 민방위대피시설명칭, 도로명 주소, 시설용도, 시설종류, 대피 가능 인원 등의 항목을 제공합니다.
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15121222&srcSe=7661IVAWM27C61E190

Alerts

시도 has constant value ""Constant
시군구 has constant value ""Constant
시설종류 has constant value ""Constant
연번 is highly overall correlated with 확보면적_제곱미터 and 2 other fieldsHigh correlation
확보면적_제곱미터 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
대피 가능인원 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
읍면동 is highly overall correlated with 연번High correlation
시설용도 is highly imbalanced (60.7%)Imbalance
연번 has unique valuesUnique
도로명 주소 has unique valuesUnique
지번 주소 has unique valuesUnique
확보면적_제곱미터 has unique valuesUnique
대피 가능인원 has unique valuesUnique

Reproduction

Analysis started2024-01-28 08:54:02.602067
Analysis finished2024-01-28 08:54:04.031683
Duration1.43 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55
Minimum1
Maximum109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-01-28T17:54:04.098175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.4
Q128
median55
Q382
95-th percentile103.6
Maximum109
Range108
Interquartile range (IQR)54

Descriptive statistics

Standard deviation31.609598
Coefficient of variation (CV)0.57471996
Kurtosis-1.2
Mean55
Median Absolute Deviation (MAD)27
Skewness0
Sum5995
Variance999.16667
MonotonicityStrictly increasing
2024-01-28T17:54:04.222193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
70 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
75 1
 
0.9%
74 1
 
0.9%
Other values (99) 99
90.8%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
109 1
0.9%
108 1
0.9%
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%
101 1
0.9%
100 1
0.9%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1004.0 B
인천
109 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인천 109
100.0%

Length

2024-01-28T17:54:04.339840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T17:54:04.415508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천 109
100.0%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1004.0 B
서구
109 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서구 109
100.0%

Length

2024-01-28T17:54:04.487162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T17:54:04.554618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서구 109
100.0%

읍면동
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)21.1%
Missing0
Missing (%)0.0%
Memory size1004.0 B
연희동
9 
불로대곡동
9 
원당동
8 
석남3동
7 
검암경서동
7 
Other values (18)
69 

Length

Max length5
Median length4
Mean length3.8899083
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row석남1동
2nd row검암경서동
3rd row검암경서동
4th row검암경서동
5th row검암경서동

Common Values

ValueCountFrequency (%)
연희동 9
 
8.3%
불로대곡동 9
 
8.3%
원당동 8
 
7.3%
석남3동 7
 
6.4%
검암경서동 7
 
6.4%
석남1동 5
 
4.6%
검단동 5
 
4.6%
가좌3동 5
 
4.6%
가정3동 5
 
4.6%
마전동 4
 
3.7%
Other values (13) 45
41.3%

Length

2024-01-28T17:54:04.643856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연희동 9
 
8.3%
불로대곡동 9
 
8.3%
원당동 8
 
7.3%
석남3동 7
 
6.4%
검암경서동 7
 
6.4%
석남1동 5
 
4.6%
검단동 5
 
4.6%
가좌3동 5
 
4.6%
가정3동 5
 
4.6%
신현원창동 4
 
3.7%
Other values (13) 45
41.3%

시설종류
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1004.0 B
공공용
109 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공용 109
100.0%

Length

2024-01-28T17:54:04.740177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T17:54:04.818467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공용 109
100.0%

시설용도
Categorical

IMBALANCE 

Distinct6
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size1004.0 B
주거시설
88 
교통시설
12 
관공서
 
6
금융시설
 
1
종교시설
 
1

Length

Max length4
Median length4
Mean length3.9449541
Min length3

Unique

Unique3 ?
Unique (%)2.8%

Sample

1st row관공서
2nd row주거시설
3rd row주거시설
4th row주거시설
5th row주거시설

Common Values

ValueCountFrequency (%)
주거시설 88
80.7%
교통시설 12
 
11.0%
관공서 6
 
5.5%
금융시설 1
 
0.9%
종교시설 1
 
0.9%
상업시설 1
 
0.9%

Length

2024-01-28T17:54:04.893857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T17:54:04.977303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주거시설 88
80.7%
교통시설 12
 
11.0%
관공서 6
 
5.5%
금융시설 1
 
0.9%
종교시설 1
 
0.9%
상업시설 1
 
0.9%

민방위대피시설명칭
Text

Distinct108
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1004.0 B
2024-01-28T17:54:05.166584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length7.9449541
Min length3

Characters and Unicode

Total characters866
Distinct characters187
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)98.2%

Sample

1st row민방위교육장
2nd row서해그랑블아파트
3rd row풍림아이원2차아파트
4th row태평샹베르1차아파트
5th row아시아드대광로제비앙아파트
ValueCountFrequency (%)
현대아파트 2
 
1.8%
석남역 2
 
1.8%
아파트 2
 
1.8%
독정역 1
 
0.9%
신안실크밸리아파트 1
 
0.9%
청라자이아파트 1
 
0.9%
마전역 1
 
0.9%
인천가좌역 1
 
0.9%
검단2차아이파크아파트 1
 
0.9%
연희대동아파트 1
 
0.9%
Other values (101) 101
88.6%
2024-01-28T17:54:05.470932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 94
 
10.9%
트 86
 
9.9%
파 84
 
9.7%
단 19
 
2.2%
지 17
 
2.0%
차 16
 
1.8%
이 15
 
1.7%
스 14
 
1.6%
2 13
 
1.5%
신 13
 
1.5%
Other values (177) 495
57.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 820
94.7%
Decimal Number 30
 
3.5%
Uppercase Letter 6
 
0.7%
Space Separator 5
 
0.6%
Close Punctuation 2
 
0.2%
Open Punctuation 2
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 94
 
11.5%
트 86
 
10.5%
파 84
 
10.2%
단 19
 
2.3%
지 17
 
2.1%
차 16
 
2.0%
이 15
 
1.8%
스 14
 
1.7%
신 13
 
1.6%
역 12
 
1.5%
Other values (162) 450
54.9%
Decimal Number
ValueCountFrequency (%)
2 13
43.3%
1 6
20.0%
3 5
 
16.7%
4 3
 
10.0%
0 1
 
3.3%
7 1
 
3.3%
5 1
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
L 2
33.3%
H 2
33.3%
K 1
16.7%
S 1
16.7%
Space Separator
ValueCountFrequency (%)
5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 820
94.7%
Common 40
 
4.6%
Latin 6
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 94
 
11.5%
트 86
 
10.5%
파 84
 
10.2%
단 19
 
2.3%
지 17
 
2.1%
차 16
 
2.0%
이 15
 
1.8%
스 14
 
1.7%
신 13
 
1.6%
역 12
 
1.5%
Other values (162) 450
54.9%
Common
ValueCountFrequency (%)
2 13
32.5%
1 6
15.0%
5
 
12.5%
3 5
 
12.5%
4 3
 
7.5%
) 2
 
5.0%
( 2
 
5.0%
0 1
 
2.5%
7 1
 
2.5%
· 1
 
2.5%
Latin
ValueCountFrequency (%)
L 2
33.3%
H 2
33.3%
K 1
16.7%
S 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 820
94.7%
ASCII 45
 
5.2%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 94
 
11.5%
트 86
 
10.5%
파 84
 
10.2%
단 19
 
2.3%
지 17
 
2.1%
차 16
 
2.0%
이 15
 
1.8%
스 14
 
1.7%
신 13
 
1.6%
역 12
 
1.5%
Other values (162) 450
54.9%
ASCII
ValueCountFrequency (%)
2 13
28.9%
1 6
13.3%
5
 
11.1%
3 5
 
11.1%
4 3
 
6.7%
L 2
 
4.4%
H 2
 
4.4%
) 2
 
4.4%
( 2
 
4.4%
0 1
 
2.2%
Other values (4) 4
 
8.9%
None
ValueCountFrequency (%)
· 1
100.0%

도로명 주소
Text

UNIQUE 

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1004.0 B
2024-01-28T17:54:05.714611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length31
Mean length23.504587
Min length14

Characters and Unicode

Total characters2562
Distinct characters142
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)100.0%

Sample

1st row인천광역시 서구 가정로294번길 20 (석남동)
2nd row인천광역시 서구 승학로495번길 7 (검암동)
3rd row인천광역시 서구 검암로 53 (검암동)
4th row인천광역시 서구 도요지로 15 (경서동, 태평샹베르아파트)
5th row인천광역시 서구 인천시 서구 모월곶로 41(경서동)
ValueCountFrequency (%)
서구 110
21.5%
인천광역시 109
21.3%
석남동 11
 
2.1%
가좌동 10
 
2.0%
검단로 9
 
1.8%
가정동 8
 
1.6%
서곶로 7
 
1.4%
심곡동 6
 
1.2%
마전동 4
 
0.8%
심곡로 3
 
0.6%
Other values (196) 235
45.9%
2024-01-28T17:54:06.086720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
404
 
15.8%
서 130
 
5.1%
인 111
 
4.3%
천 111
 
4.3%
구 110
 
4.3%
로 110
 
4.3%
시 110
 
4.3%
역 110
 
4.3%
광 110
 
4.3%
동 81
 
3.2%
Other values (132) 1175
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1599
62.4%
Space Separator 404
 
15.8%
Decimal Number 377
 
14.7%
Open Punctuation 80
 
3.1%
Close Punctuation 80
 
3.1%
Other Punctuation 20
 
0.8%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 130
 
8.1%
인 111
 
6.9%
천 111
 
6.9%
구 110
 
6.9%
로 110
 
6.9%
시 110
 
6.9%
역 110
 
6.9%
광 110
 
6.9%
동 81
 
5.1%
길 47
 
2.9%
Other values (117) 569
35.6%
Decimal Number
ValueCountFrequency (%)
1 74
19.6%
3 59
15.6%
2 45
11.9%
4 37
9.8%
6 30
8.0%
9 28
 
7.4%
8 28
 
7.4%
0 27
 
7.2%
7 26
 
6.9%
5 23
 
6.1%
Space Separator
ValueCountFrequency (%)
404
100.0%
Open Punctuation
ValueCountFrequency (%)
( 80
100.0%
Close Punctuation
ValueCountFrequency (%)
) 80
100.0%
Other Punctuation
ValueCountFrequency (%)
, 20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1599
62.4%
Common 963
37.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 130
 
8.1%
인 111
 
6.9%
천 111
 
6.9%
구 110
 
6.9%
로 110
 
6.9%
시 110
 
6.9%
역 110
 
6.9%
광 110
 
6.9%
동 81
 
5.1%
길 47
 
2.9%
Other values (117) 569
35.6%
Common
ValueCountFrequency (%)
404
42.0%
( 80
 
8.3%
) 80
 
8.3%
1 74
 
7.7%
3 59
 
6.1%
2 45
 
4.7%
4 37
 
3.8%
6 30
 
3.1%
9 28
 
2.9%
8 28
 
2.9%
Other values (5) 98
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1599
62.4%
ASCII 963
37.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
404
42.0%
( 80
 
8.3%
) 80
 
8.3%
1 74
 
7.7%
3 59
 
6.1%
2 45
 
4.7%
4 37
 
3.8%
6 30
 
3.1%
9 28
 
2.9%
8 28
 
2.9%
Other values (5) 98
 
10.2%
Hangul
ValueCountFrequency (%)
서 130
 
8.1%
인 111
 
6.9%
천 111
 
6.9%
구 110
 
6.9%
로 110
 
6.9%
시 110
 
6.9%
역 110
 
6.9%
광 110
 
6.9%
동 81
 
5.1%
길 47
 
2.9%
Other values (117) 569
35.6%

지번 주소
Text

UNIQUE 

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1004.0 B
2024-01-28T17:54:06.340089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length21
Mean length17.779817
Min length15

Characters and Unicode

Total characters1938
Distinct characters59
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)100.0%

Sample

1st row인천광역시 서구 석남1동 483
2nd row인천광역시 서구 검암동 595-3
3rd row인천광역시 서구 검암동 501-1
4th row인천광역시 서구 경서동 722-1
5th row인천광역시 서구 경서동 994
ValueCountFrequency (%)
인천광역시 109
25.1%
서구 109
25.1%
가좌동 13
 
3.0%
석남동 12
 
2.8%
청라동 12
 
2.8%
가정동 10
 
2.3%
불로동 9
 
2.1%
마전동 8
 
1.8%
당하동 8
 
1.8%
원당동 7
 
1.6%
Other values (119) 138
31.7%
2024-01-28T17:54:06.716840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
326
16.8%
서 112
 
5.8%
인 109
 
5.6%
동 109
 
5.6%
광 109
 
5.6%
역 109
 
5.6%
시 109
 
5.6%
구 109
 
5.6%
천 109
 
5.6%
1 101
 
5.2%
Other values (49) 636
32.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1098
56.7%
Decimal Number 437
 
22.5%
Space Separator 326
 
16.8%
Dash Punctuation 73
 
3.8%
Other Punctuation 2
 
0.1%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 112
10.2%
인 109
9.9%
동 109
9.9%
광 109
9.9%
역 109
9.9%
시 109
9.9%
구 109
9.9%
천 109
9.9%
가 26
 
2.4%
석 16
 
1.5%
Other values (34) 181
16.5%
Decimal Number
ValueCountFrequency (%)
1 101
23.1%
3 49
11.2%
2 48
11.0%
0 43
9.8%
5 38
 
8.7%
6 34
 
7.8%
4 33
 
7.6%
9 33
 
7.6%
8 31
 
7.1%
7 27
 
6.2%
Space Separator
ValueCountFrequency (%)
326
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 73
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1098
56.7%
Common 840
43.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 112
10.2%
인 109
9.9%
동 109
9.9%
광 109
9.9%
역 109
9.9%
시 109
9.9%
구 109
9.9%
천 109
9.9%
가 26
 
2.4%
석 16
 
1.5%
Other values (34) 181
16.5%
Common
ValueCountFrequency (%)
326
38.8%
1 101
 
12.0%
- 73
 
8.7%
3 49
 
5.8%
2 48
 
5.7%
0 43
 
5.1%
5 38
 
4.5%
6 34
 
4.0%
4 33
 
3.9%
9 33
 
3.9%
Other values (5) 62
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1098
56.7%
ASCII 840
43.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
326
38.8%
1 101
 
12.0%
- 73
 
8.7%
3 49
 
5.8%
2 48
 
5.7%
0 43
 
5.1%
5 38
 
4.5%
6 34
 
4.0%
4 33
 
3.9%
9 33
 
3.9%
Other values (5) 62
 
7.4%
Hangul
ValueCountFrequency (%)
서 112
10.2%
인 109
9.9%
동 109
9.9%
광 109
9.9%
역 109
9.9%
시 109
9.9%
구 109
9.9%
천 109
9.9%
가 26
 
2.4%
석 16
 
1.5%
Other values (34) 181
16.5%

확보면적_제곱미터
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9487.1734
Minimum526
Maximum120369
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-01-28T17:54:06.831151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum526
5-th percentile832
Q12721
median4288
Q37790
95-th percentile35014.8
Maximum120369
Range119843
Interquartile range (IQR)5069

Descriptive statistics

Standard deviation15827.174
Coefficient of variation (CV)1.6682708
Kurtosis24.087648
Mean9487.1734
Median Absolute Deviation (MAD)2210
Skewness4.3287671
Sum1034101.9
Variance2.5049944 × 108
MonotonicityNot monotonic
2024-01-28T17:54:06.960872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
807.0 1
 
0.9%
58886.0 1
 
0.9%
3886.0 1
 
0.9%
5095.0 1
 
0.9%
1620.0 1
 
0.9%
4150.0 1
 
0.9%
120369.0 1
 
0.9%
3481.0 1
 
0.9%
6997.0 1
 
0.9%
4241.0 1
 
0.9%
Other values (99) 99
90.8%
ValueCountFrequency (%)
526.0 1
0.9%
604.4 1
0.9%
693.0 1
0.9%
807.0 1
0.9%
809.0 1
0.9%
826.0 1
0.9%
841.0 1
0.9%
860.0 1
0.9%
883.0 1
0.9%
893.0 1
0.9%
ValueCountFrequency (%)
120369.0 1
0.9%
69976.0 1
0.9%
58886.0 1
0.9%
41191.0 1
0.9%
40584.0 1
0.9%
36140.0 1
0.9%
33327.0 1
0.9%
32000.0 1
0.9%
29191.0 1
0.9%
28133.0 1
0.9%

대피 가능인원
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11499.128
Minimum637
Maximum145901
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-01-28T17:54:07.094167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum637
5-th percentile1008.2
Q13298
median5197
Q39442
95-th percentile42442
Maximum145901
Range145264
Interquartile range (IQR)6144

Descriptive statistics

Standard deviation19184.431
Coefficient of variation (CV)1.6683378
Kurtosis24.087515
Mean11499.128
Median Absolute Deviation (MAD)2679
Skewness4.328753
Sum1253405
Variance3.6804238 × 108
MonotonicityNot monotonic
2024-01-28T17:54:07.204477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
978 1
 
0.9%
71376 1
 
0.9%
4710 1
 
0.9%
6175 1
 
0.9%
1963 1
 
0.9%
5030 1
 
0.9%
145901 1
 
0.9%
4219 1
 
0.9%
8481 1
 
0.9%
5140 1
 
0.9%
Other values (99) 99
90.8%
ValueCountFrequency (%)
637 1
0.9%
732 1
0.9%
840 1
0.9%
978 1
0.9%
980 1
0.9%
1001 1
0.9%
1019 1
0.9%
1042 1
0.9%
1070 1
0.9%
1082 1
0.9%
ValueCountFrequency (%)
145901 1
0.9%
84819 1
0.9%
71376 1
0.9%
49928 1
0.9%
49192 1
0.9%
43806 1
0.9%
40396 1
0.9%
38787 1
0.9%
35383 1
0.9%
34100 1
0.9%

시설 구축 연도
Date

Distinct79
Distinct (%)72.5%
Missing0
Missing (%)0.0%
Memory size1004.0 B
Minimum1984-01-02 00:00:00
Maximum2022-02-22 00:00:00
2024-01-28T17:54:07.309852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:54:07.416718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

시설 지정연도
Date

Distinct47
Distinct (%)43.1%
Missing0
Missing (%)0.0%
Memory size1004.0 B
Minimum1985-01-01 00:00:00
Maximum2023-03-07 00:00:00
2024-01-28T17:54:07.520484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:54:07.872763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)

Interactions

2024-01-28T17:54:03.578076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:54:03.165418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:54:03.359605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:54:03.644603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:54:03.223912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:54:03.429026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:54:03.716233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:54:03.289817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:54:03.498504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T17:54:07.944517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면동시설용도확보면적_제곱미터대피 가능인원시설 구축 연도시설 지정연도
연번1.0000.9320.5360.4410.4410.9580.969
읍면동0.9321.0000.4580.6680.6680.7900.935
시설용도0.5360.4581.0000.0000.0000.4890.909
확보면적_제곱미터0.4410.6680.0001.0001.0000.9510.000
대피 가능인원0.4410.6680.0001.0001.0000.9510.000
시설 구축 연도0.9580.7900.4890.9510.9511.0000.999
시설 지정연도0.9690.9350.9090.0000.0000.9991.000
2024-01-28T17:54:08.031306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동시설용도
읍면동1.0000.203
시설용도0.2031.000
2024-01-28T17:54:08.110680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번확보면적_제곱미터대피 가능인원읍면동시설용도
연번1.0000.5220.5220.6620.311
확보면적_제곱미터0.5221.0001.0000.3340.000
대피 가능인원0.5221.0001.0000.3340.000
읍면동0.6620.3340.3341.0000.203
시설용도0.3110.0000.0000.2031.000

Missing values

2024-01-28T17:54:03.826854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T17:54:03.977442image/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

연번시도시군구읍면동시설종류시설용도민방위대피시설명칭도로명 주소지번 주소확보면적_제곱미터대피 가능인원시설 구축 연도시설 지정연도
01인천서구석남1동공공용관공서민방위교육장인천광역시 서구 가정로294번길 20 (석남동)인천광역시 서구 석남1동 483807.09781985-01-011985-01-01
12인천서구검암경서동공공용주거시설서해그랑블아파트인천광역시 서구 승학로495번길 7 (검암동)인천광역시 서구 검암동 595-33762.045602003-08-302005-10-30
23인천서구검암경서동공공용주거시설풍림아이원2차아파트인천광역시 서구 검암로 53 (검암동)인천광역시 서구 검암동 501-12843.034462004-05-282011-03-28
34인천서구검암경서동공공용주거시설태평샹베르1차아파트인천광역시 서구 도요지로 15 (경서동, 태평샹베르아파트)인천광역시 서구 경서동 722-12265.027452005-02-032011-03-28
45인천서구검암경서동공공용주거시설아시아드대광로제비앙아파트인천광역시 서구 인천시 서구 모월곶로 41(경서동)인천광역시 서구 경서동 9942800.033932017-12-182018-02-27
56인천서구검암경서동공공용주거시설풍림아이원3차아파트인천광역시 서구 검암로10번길39(검암동, 풍림아이원3차)인천광역시 서구 검암동 512-21350.016362004-07-012018-08-28
67인천서구연희동공공용관공서인천서구청인천광역시 서구 서곶로 307 (심곡동)인천광역시 서구 심곡동 244826.010011991-03-111992-10-01
78인천서구연희동공공용주거시설심곡광명아파트인천광역시 서구 심곡로 11 (심곡동, 광명아파트)인천광역시 서구 심곡동 336-12392.028991996-07-141996-10-01
89인천서구연희동공공용주거시설심곡한국아파트인천광역시 서구 탁옥로74번길 3 (심곡동, 한국아파트)인천광역시 서구 심곡동 3025316.064431994-03-081994-10-01
910인천서구연희동공공용주거시설연희동남아파트인천광역시 서구 심곡로132번길 17 (심곡동)인천광역시 서구 심곡동 2874628.056091995-11-161995-10-01
연번시도시군구읍면동시설종류시설용도민방위대피시설명칭도로명 주소지번 주소확보면적_제곱미터대피 가능인원시설 구축 연도시설 지정연도
99100인천서구아라동공공용주거시설푸르지오더베뉴아파트인천광역시 서구 이음6로 33 (원당동)인천광역시 서구 원당동 101828133.0341002019-03-012022-02-08
100101인천서구아라동공공용주거시설LH20단지아파트인천광역시 서구 이음3로 220인천광역시 서구 원당동 43422572.0273602018-08-122022-02-08
101102인천서구아라동공공용주거시설유승한내들아파트인천광역시 서구 이음3로 130 (당하동)인천광역시 서구 당하동 259-1614890.0180482018-08-032022-02-08
102103인천서구가좌1동공공용주거시설신명2차아파트인천광역시 서구 가정로125번길 4(가좌동)인천광역시 서구 가좌동 139-21322.016021990-12-012022-12-07
103104인천서구가좌3동공공용교통시설주안국가산단역인천광역시 서구 방축로 343(가좌동)인천광역시 서구 가좌동 606-114252.051532016-07-302022-12-07
104105인천서구불로대곡동공공용주거시설검단 대광로제비앙 센트럴포레인천광역시 서구 검단로768번길 46 (불로동)인천광역시 서구 불로동 803-123496.0284802022-02-222022-12-07
105106인천서구검암경서동공공용주거시설북청라하우스토리아파트인천광역시 서구 경서로31번길 15인천광역시 서구 경서동 103214147.0171472022-02-152023-02-01
106107인천서구청라3동공공용주거시설청라반도유보라2차 아파트인천광역시 서구 비즈니스로 10인천광역시 서구 청라동 102-1640584.0491922012-08-032023-02-01
107108인천서구청라3동공공용주거시설센텀대광로제비앙아파트인천광역시 서구 비즈니스로 166인천광역시 서구 청라동 83-127488.0333182018-12-182023-02-01
108109인천서구검암경서동공공용주거시설검암2차신명스카이뷰아파트인천광역시 서구 검암로10번길 54(검암동)인천광역시 서구 검암동 535-15300.064242003-10-232023-03-07