Overview

Dataset statistics

Number of variables11
Number of observations108
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.9 KiB
Average record size in memory94.2 B

Variable types

Numeric5
Categorical2
Text2
DateTime2

Dataset

Description미추홀구 비상대피시설현황에 대한 데이터로 비상대피시설 시설명, 시설용도, 도로명주소, 확보면적, 대피가능인원, 시설구축연도,위도,경도 등을 제공합니다.
Author인천광역시 미추홀구
URLhttps://www.data.go.kr/data/15051610/fileData.do

Alerts

시설용도 has constant value ""Constant
연번 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
확보면적(제곱미터) is highly overall correlated with 대피 가능인원High correlation
대피 가능인원 is highly overall correlated with 확보면적(제곱미터)High correlation
위도 is highly overall correlated with 관할동High correlation
경도 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
관할동 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
연번 has unique valuesUnique
민방위대피시설명칭 has unique valuesUnique

Reproduction

Analysis started2024-03-30 06:31:58.522194
Analysis finished2024-03-30 06:32:08.781457
Duration10.26 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct108
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.5
Minimum1
Maximum108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-03-30T06:32:08.943608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.35
Q127.75
median54.5
Q381.25
95-th percentile102.65
Maximum108
Range107
Interquartile range (IQR)53.5

Descriptive statistics

Standard deviation31.32092
Coefficient of variation (CV)0.57469577
Kurtosis-1.2
Mean54.5
Median Absolute Deviation (MAD)27
Skewness0
Sum5886
Variance981
MonotonicityStrictly increasing
2024-03-30T06:32:09.414227image/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 (98) 98
90.7%
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 (%)
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%
99 1
0.9%

관할동
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Memory size996.0 B
용현5동
16 
학익2동
12 
관교동
10 
주안6동
10 
주안5동
9 
Other values (16)
51 

Length

Max length6
Median length4
Mean length4.1203704
Min length3

Unique

Unique6 ?
Unique (%)5.6%

Sample

1st row숭의1·3동
2nd row숭의1·3동
3rd row숭의1·3동
4th row숭의1·3동
5th row숭의1·3동

Common Values

ValueCountFrequency (%)
용현5동 16
14.8%
학익2동 12
11.1%
관교동 10
9.3%
주안6동 10
9.3%
주안5동 9
8.3%
학익1동 8
 
7.4%
도화2,3동 7
 
6.5%
도화1동 6
 
5.6%
주안4동 5
 
4.6%
숭의1·3동 5
 
4.6%
Other values (11) 20
18.5%

Length

2024-03-30T06:32:09.908859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
용현5동 16
14.8%
학익2동 12
11.1%
관교동 10
9.3%
주안6동 10
9.3%
주안5동 9
8.3%
학익1동 8
 
7.4%
도화2,3동 7
 
6.5%
도화1동 6
 
5.6%
주안4동 5
 
4.6%
숭의1·3동 5
 
4.6%
Other values (11) 20
18.5%

시설용도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size996.0 B
공공용시설
108 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공용시설 108
100.0%

Length

2024-03-30T06:32:10.298420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-30T06:32:10.575549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공용시설 108
100.0%

민방위대피시설명칭
Text

UNIQUE 

Distinct108
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size996.0 B
2024-03-30T06:32:11.101526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length25
Mean length17.648148
Min length7

Characters and Unicode

Total characters1906
Distinct characters194
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)100.0%

Sample

1st row햇살요양병원 지하1층
2nd row극동아파트 지하1층
3rd row로터리빌딩 지하1~2층
4th row숭의한화꿈에그린아파트 지하1층
5th row파란마을아파트 지하1~2층
ValueCountFrequency (%)
지하주차장 27
 
10.3%
지하1층 17
 
6.5%
더월드스테이트아파트 8
 
3.1%
주차장(지하1층 8
 
3.1%
주차장(지하1~2층 7
 
2.7%
금호2차아파트 5
 
1.9%
지하1~2층 5
 
1.9%
지하주차장(지하1~2층 5
 
1.9%
지하주차장(지하1층 5
 
1.9%
아파트 4
 
1.5%
Other values (148) 171
65.3%
2024-03-30T06:32:12.031639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
154
 
8.1%
1 131
 
6.9%
지 123
 
6.5%
하 120
 
6.3%
아 89
 
4.7%
차 85
 
4.5%
트 84
 
4.4%
파 76
 
4.0%
층 75
 
3.9%
주 71
 
3.7%
Other values (184) 898
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1298
68.1%
Decimal Number 273
 
14.3%
Space Separator 154
 
8.1%
Close Punctuation 52
 
2.7%
Open Punctuation 52
 
2.7%
Other Punctuation 32
 
1.7%
Math Symbol 29
 
1.5%
Lowercase Letter 8
 
0.4%
Uppercase Letter 6
 
0.3%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 123
 
9.5%
하 120
 
9.2%
아 89
 
6.9%
차 85
 
6.5%
트 84
 
6.5%
파 76
 
5.9%
층 75
 
5.8%
주 71
 
5.5%
장 70
 
5.4%
동 50
 
3.9%
Other values (159) 455
35.1%
Decimal Number
ValueCountFrequency (%)
1 131
48.0%
2 59
21.6%
0 30
 
11.0%
3 19
 
7.0%
4 10
 
3.7%
6 6
 
2.2%
9 6
 
2.2%
7 5
 
1.8%
5 4
 
1.5%
8 3
 
1.1%
Lowercase Letter
ValueCountFrequency (%)
e 4
50.0%
w 1
 
12.5%
i 1
 
12.5%
y 1
 
12.5%
k 1
 
12.5%
Uppercase Letter
ValueCountFrequency (%)
S 3
50.0%
T 1
 
16.7%
V 1
 
16.7%
K 1
 
16.7%
Space Separator
ValueCountFrequency (%)
154
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%
Other Punctuation
ValueCountFrequency (%)
, 32
100.0%
Math Symbol
ValueCountFrequency (%)
~ 29
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1298
68.1%
Common 594
31.2%
Latin 14
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 123
 
9.5%
하 120
 
9.2%
아 89
 
6.9%
차 85
 
6.5%
트 84
 
6.5%
파 76
 
5.9%
층 75
 
5.8%
주 71
 
5.5%
장 70
 
5.4%
동 50
 
3.9%
Other values (159) 455
35.1%
Common
ValueCountFrequency (%)
154
25.9%
1 131
22.1%
2 59
 
9.9%
) 52
 
8.8%
( 52
 
8.8%
, 32
 
5.4%
0 30
 
5.1%
~ 29
 
4.9%
3 19
 
3.2%
4 10
 
1.7%
Other values (6) 26
 
4.4%
Latin
ValueCountFrequency (%)
e 4
28.6%
S 3
21.4%
T 1
 
7.1%
w 1
 
7.1%
i 1
 
7.1%
V 1
 
7.1%
y 1
 
7.1%
k 1
 
7.1%
K 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1298
68.1%
ASCII 608
31.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
154
25.3%
1 131
21.5%
2 59
 
9.7%
) 52
 
8.6%
( 52
 
8.6%
, 32
 
5.3%
0 30
 
4.9%
~ 29
 
4.8%
3 19
 
3.1%
4 10
 
1.6%
Other values (15) 40
 
6.6%
Hangul
ValueCountFrequency (%)
지 123
 
9.5%
하 120
 
9.2%
아 89
 
6.9%
차 85
 
6.5%
트 84
 
6.5%
파 76
 
5.9%
층 75
 
5.8%
주 71
 
5.5%
장 70
 
5.4%
동 50
 
3.9%
Other values (159) 455
35.1%

도로명 주소
Text

Distinct99
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size996.0 B
2024-03-30T06:32:12.549278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length37
Mean length33.462963
Min length22

Characters and Unicode

Total characters3614
Distinct characters197
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

Unique94 ?
Unique (%)87.0%

Sample

1st row인천광역시 미추홀구 인중로 13(숭의동, 햇살병원)
2nd row인천광역시 미추홀구 석정로 126번길 12-33(숭의동, 극동아파트)
3rd row인천광역시 미추홀구 인중로 9(숭의동, 원흥빌딩)
4th row인천광역시 미추홀구 석정로126번길 23 (숭의동, 한화꿈에그린아파트)
5th row인천광역시 미추홀구 참외전로 302 (숭의동, 파란마을)
ValueCountFrequency (%)
인천광역시 108
 
18.4%
미추홀구 108
 
18.4%
주안동 16
 
2.7%
매소홀로 13
 
2.2%
경원대로 11
 
1.9%
주안더월드스테이트 8
 
1.4%
경인로 8
 
1.4%
관교동 8
 
1.4%
884 7
 
1.2%
주승로 6
 
1.0%
Other values (231) 294
50.1%
2024-03-30T06:32:13.458287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
484
 
13.4%
동 134
 
3.7%
인 128
 
3.5%
홀 127
 
3.5%
미 114
 
3.2%
천 112
 
3.1%
시 111
 
3.1%
광 111
 
3.1%
추 110
 
3.0%
로 110
 
3.0%
Other values (187) 2073
57.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2383
65.9%
Space Separator 484
 
13.4%
Decimal Number 407
 
11.3%
Open Punctuation 108
 
3.0%
Close Punctuation 108
 
3.0%
Other Punctuation 103
 
2.9%
Uppercase Letter 9
 
0.2%
Dash Punctuation 7
 
0.2%
Lowercase Letter 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 134
 
5.6%
인 128
 
5.4%
홀 127
 
5.3%
미 114
 
4.8%
천 112
 
4.7%
시 111
 
4.7%
광 111
 
4.7%
추 110
 
4.6%
로 110
 
4.6%
구 109
 
4.6%
Other values (162) 1217
51.1%
Decimal Number
ValueCountFrequency (%)
1 79
19.4%
3 65
16.0%
2 56
13.8%
8 46
11.3%
4 44
10.8%
6 39
9.6%
5 24
 
5.9%
0 21
 
5.2%
7 17
 
4.2%
9 16
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
I 2
22.2%
S 2
22.2%
W 1
11.1%
K 1
11.1%
V 1
11.1%
E 1
11.1%
T 1
11.1%
Lowercase Letter
ValueCountFrequency (%)
e 3
60.0%
k 1
 
20.0%
y 1
 
20.0%
Space Separator
ValueCountFrequency (%)
484
100.0%
Open Punctuation
ValueCountFrequency (%)
( 108
100.0%
Close Punctuation
ValueCountFrequency (%)
) 108
100.0%
Other Punctuation
ValueCountFrequency (%)
, 103
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2383
65.9%
Common 1217
33.7%
Latin 14
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 134
 
5.6%
인 128
 
5.4%
홀 127
 
5.3%
미 114
 
4.8%
천 112
 
4.7%
시 111
 
4.7%
광 111
 
4.7%
추 110
 
4.6%
로 110
 
4.6%
구 109
 
4.6%
Other values (162) 1217
51.1%
Common
ValueCountFrequency (%)
484
39.8%
( 108
 
8.9%
) 108
 
8.9%
, 103
 
8.5%
1 79
 
6.5%
3 65
 
5.3%
2 56
 
4.6%
8 46
 
3.8%
4 44
 
3.6%
6 39
 
3.2%
Other values (5) 85
 
7.0%
Latin
ValueCountFrequency (%)
e 3
21.4%
I 2
14.3%
S 2
14.3%
W 1
 
7.1%
K 1
 
7.1%
k 1
 
7.1%
y 1
 
7.1%
V 1
 
7.1%
E 1
 
7.1%
T 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2383
65.9%
ASCII 1231
34.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
484
39.3%
( 108
 
8.8%
) 108
 
8.8%
, 103
 
8.4%
1 79
 
6.4%
3 65
 
5.3%
2 56
 
4.5%
8 46
 
3.7%
4 44
 
3.6%
6 39
 
3.2%
Other values (15) 99
 
8.0%
Hangul
ValueCountFrequency (%)
동 134
 
5.6%
인 128
 
5.4%
홀 127
 
5.3%
미 114
 
4.8%
천 112
 
4.7%
시 111
 
4.7%
광 111
 
4.7%
추 110
 
4.6%
로 110
 
4.6%
구 109
 
4.6%
Other values (162) 1217
51.1%

확보면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct102
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8209.2685
Minimum165
Maximum160879
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-03-30T06:32:13.788924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum165
5-th percentile529.45
Q11956.25
median3224
Q35554
95-th percentile33361.95
Maximum160879
Range160714
Interquartile range (IQR)3597.75

Descriptive statistics

Standard deviation18493.816
Coefficient of variation (CV)2.252797
Kurtosis44.901012
Mean8209.2685
Median Absolute Deviation (MAD)1448
Skewness6.0425416
Sum886601
Variance3.4202121 × 108
MonotonicityNot monotonic
2024-03-30T06:32:14.238158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1980 3
 
2.8%
2970 2
 
1.9%
4620 2
 
1.9%
5313 2
 
1.9%
4424 2
 
1.9%
981 1
 
0.9%
1814 1
 
0.9%
3293 1
 
0.9%
1133 1
 
0.9%
2904 1
 
0.9%
Other values (92) 92
85.2%
ValueCountFrequency (%)
165 1
0.9%
264 1
0.9%
337 1
0.9%
429 1
0.9%
436 1
0.9%
443 1
0.9%
690 1
0.9%
819 1
0.9%
924 1
0.9%
981 1
0.9%
ValueCountFrequency (%)
160879 1
0.9%
73171 1
0.9%
46595 1
0.9%
46200 1
0.9%
43066 1
0.9%
34679 1
0.9%
30916 1
0.9%
26664 1
0.9%
23632 1
0.9%
19590 1
0.9%

대피 가능인원
Real number (ℝ)

HIGH CORRELATION 

Distinct102
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9950.2778
Minimum200
Maximum195004
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-03-30T06:32:14.681554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200
5-th percentile641
Q12371
median3907.5
Q36731.75
95-th percentile40438.3
Maximum195004
Range194804
Interquartile range (IQR)4360.75

Descriptive statistics

Standard deviation22416.704
Coefficient of variation (CV)2.2528722
Kurtosis44.900897
Mean9950.2778
Median Absolute Deviation (MAD)1755.5
Skewness6.0425356
Sum1074630
Variance5.0250861 × 108
MonotonicityNot monotonic
2024-03-30T06:32:15.137677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2400 3
 
2.8%
3600 2
 
1.9%
5600 2
 
1.9%
6440 2
 
1.9%
5362 2
 
1.9%
1189 1
 
0.9%
2198 1
 
0.9%
3991 1
 
0.9%
1373 1
 
0.9%
3520 1
 
0.9%
Other values (92) 92
85.2%
ValueCountFrequency (%)
200 1
0.9%
320 1
0.9%
408 1
0.9%
520 1
0.9%
528 1
0.9%
536 1
0.9%
836 1
0.9%
992 1
0.9%
1120 1
0.9%
1189 1
0.9%
ValueCountFrequency (%)
195004 1
0.9%
88692 1
0.9%
56478 1
0.9%
56000 1
0.9%
52201 1
0.9%
42035 1
0.9%
37473 1
0.9%
32320 1
0.9%
28644 1
0.9%
23745 1
0.9%

시설 구축연도
Date

Distinct59
Distinct (%)54.6%
Missing0
Missing (%)0.0%
Memory size996.0 B
Minimum1982-01-01 00:00:00
Maximum2023-02-08 00:00:00
2024-03-30T06:32:15.555459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T06:32:15.991328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

시설 지정연도
Date

Distinct63
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Memory size996.0 B
Minimum1982-01-01 00:00:00
Maximum2023-02-08 00:00:00
2024-03-30T06:32:16.397978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T06:32:16.870440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct93
Distinct (%)86.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.453406
Minimum37.436545
Maximum37.476905
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-03-30T06:32:17.280970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.436545
5-th percentile37.438757
Q137.44329
median37.451385
Q337.46236
95-th percentile37.471373
Maximum37.476905
Range0.04035963
Interquartile range (IQR)0.019070838

Descriptive statistics

Standard deviation0.010968123
Coefficient of variation (CV)0.00029284714
Kurtosis-1.2061627
Mean37.453406
Median Absolute Deviation (MAD)0.00924782
Skewness0.28595772
Sum4044.9679
Variance0.00012029971
MonotonicityNot monotonic
2024-03-30T06:32:17.758438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4623604 7
 
6.5%
37.44739422 5
 
4.6%
37.44515359 3
 
2.8%
37.44780405 2
 
1.9%
37.44103426 2
 
1.9%
37.44430913 2
 
1.9%
37.46247938 1
 
0.9%
37.46555194 1
 
0.9%
37.47362682 1
 
0.9%
37.47026207 1
 
0.9%
Other values (83) 83
76.9%
ValueCountFrequency (%)
37.43654516 1
0.9%
37.43713135 1
0.9%
37.43721956 1
0.9%
37.43851864 1
0.9%
37.43858226 1
0.9%
37.43862047 1
0.9%
37.43901058 1
0.9%
37.43918463 1
0.9%
37.43991286 1
0.9%
37.44042158 1
0.9%
ValueCountFrequency (%)
37.47690479 1
0.9%
37.474888 1
0.9%
37.473796 1
0.9%
37.47362682 1
0.9%
37.473449 1
0.9%
37.47197085 1
0.9%
37.47026207 1
0.9%
37.47019224 1
0.9%
37.46899087 1
0.9%
37.46789579 1
0.9%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct93
Distinct (%)86.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.66914
Minimum126.6316
Maximum126.70152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-03-30T06:32:18.293441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.6316
5-th percentile126.63412
Q1126.65349
median126.67262
Q3126.68559
95-th percentile126.69659
Maximum126.70152
Range0.069914
Interquartile range (IQR)0.032104425

Descriptive statistics

Standard deviation0.02032198
Coefficient of variation (CV)0.00016043354
Kurtosis-1.0487082
Mean126.66914
Median Absolute Deviation (MAD)0.0149182
Skewness-0.32230893
Sum13680.267
Variance0.00041298286
MonotonicityNot monotonic
2024-03-30T06:32:18.833009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.6944531 7
 
6.5%
126.6326813 5
 
4.6%
126.6421979 3
 
2.8%
126.6367798 2
 
1.9%
126.67557 2
 
1.9%
126.6965903 2
 
1.9%
126.6410163 1
 
0.9%
126.6855868 1
 
0.9%
126.67887 1
 
0.9%
126.6837701 1
 
0.9%
Other values (83) 83
76.9%
ValueCountFrequency (%)
126.6316047 1
 
0.9%
126.6326813 5
4.6%
126.6367798 2
 
1.9%
126.6375506 1
 
0.9%
126.6376058 1
 
0.9%
126.6380152 1
 
0.9%
126.638181 1
 
0.9%
126.6393371 1
 
0.9%
126.6396546 1
 
0.9%
126.6405051 1
 
0.9%
ValueCountFrequency (%)
126.7015187 1
0.9%
126.6996909 1
0.9%
126.6972576 1
0.9%
126.6968763 1
0.9%
126.6966793 1
0.9%
126.6965903 2
1.9%
126.6962681 1
0.9%
126.6961002 1
0.9%
126.6959808 1
0.9%
126.6950059 1
0.9%

Interactions

2024-03-30T06:32:06.434581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T06:32:00.751592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T06:32:02.128616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T06:32:03.889555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T06:32:05.051750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T06:32:06.702963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T06:32:00.940809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T06:32:02.427117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T06:32:04.154408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T06:32:05.212262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T06:32:06.986845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T06:32:01.198736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T06:32:02.823906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T06:32:04.420980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T06:32:05.397030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T06:32:07.303486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T06:32:01.505946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T06:32:03.121286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T06:32:04.635426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T06:32:05.632081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T06:32:07.597151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T06:32:01.767228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T06:32:03.517966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T06:32:04.872028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T06:32:05.847028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-30T06:32:19.161337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번관할동도로명 주소확보면적(제곱미터)대피 가능인원시설 구축연도시설 지정연도위도경도
연번1.0000.9510.9860.3010.3010.7530.8340.8230.870
관할동0.9511.0001.0000.0000.0000.9490.9790.9270.926
도로명 주소0.9861.0001.0001.0001.0000.9970.9951.0001.000
확보면적(제곱미터)0.3010.0001.0001.0001.0000.9840.9850.6450.297
대피 가능인원0.3010.0001.0001.0001.0000.9840.9850.6450.297
시설 구축연도0.7530.9490.9970.9840.9841.0000.9980.9020.862
시설 지정연도0.8340.9790.9950.9850.9850.9981.0000.8920.919
위도0.8230.9271.0000.6450.6450.9020.8921.0000.759
경도0.8700.9261.0000.2970.2970.8620.9190.7591.000
2024-03-30T06:32:19.663695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번확보면적(제곱미터)대피 가능인원위도경도관할동
연번1.000-0.002-0.002-0.0490.8970.714
확보면적(제곱미터)-0.0021.0001.0000.109-0.0280.000
대피 가능인원-0.0021.0001.0000.109-0.0280.000
위도-0.0490.1090.1091.000-0.0530.646
경도0.897-0.028-0.028-0.0531.0000.642
관할동0.7140.0000.0000.6460.6421.000

Missing values

2024-03-30T06:32:07.996069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-30T06:32:08.536300image/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

연번관할동시설용도민방위대피시설명칭도로명 주소확보면적(제곱미터)대피 가능인원시설 구축연도시설 지정연도위도경도
01숭의1·3동공공용시설햇살요양병원 지하1층인천광역시 미추홀구 인중로 13(숭의동, 햇살병원)2643201990-01-011990-01-0137.462479126.641016
12숭의1·3동공공용시설극동아파트 지하1층인천광역시 미추홀구 석정로 126번길 12-33(숭의동, 극동아파트)214526001999-04-261999-04-2637.467865126.648582
23숭의1·3동공공용시설로터리빌딩 지하1~2층인천광역시 미추홀구 인중로 9(숭의동, 원흥빌딩)148718022004-06-242004-06-2437.462242126.641324
34숭의1·3동공공용시설숭의한화꿈에그린아파트 지하1층인천광역시 미추홀구 석정로126번길 23 (숭의동, 한화꿈에그린아파트)10642128992007-07-092007-07-0937.467092126.649794
45숭의1·3동공공용시설파란마을아파트 지하1~2층인천광역시 미추홀구 참외전로 302 (숭의동, 파란마을)135616432005-01-012015-01-0137.465942126.647562
56숭의2동공공용시설동아시티월드 지하주차장1~4층인천광역시 미추홀구 독배로 443(숭의동, 삼화복합빌딩)11190135631998-05-071998-05-0737.458836126.648151
67숭의4동공공용시설제물포지하상가인천광역시 미추홀구 경인로 지하 125(숭의동)376145581982-01-011982-01-0137.466935126.6564
78용현1·4동공공용시설삼화아파트 지하주차장 1~2층인천광역시 미추홀구 한나루로489번길 49(용현동, 삼화아파트)92411201994-01-021994-01-0237.451476126.663997
89용현2동공공용시설동아아파트주차장 지하1층인천광역시 미추홀구 능해길 32(용현동, 동아아파트)198024001990-01-011990-01-0137.458106126.639337
910용현2동공공용시설용현대우아파트 지하1,2주차장인천광역시 미추홀구 아암대로29번길 13 (용현동, 대우아파트)679582362000-01-012000-01-0137.458527126.637551
연번관할동시설용도민방위대피시설명칭도로명 주소확보면적(제곱미터)대피 가능인원시설 구축연도시설 지정연도위도경도
9899관교동공공용시설삼환2차아파트 지하주차장 1층인천광역시 미추홀구 문화로 23 (관교동, 삼환아파트)198024001991-11-281991-11-2837.441327126.697258
99100관교동공공용시설동부아파트 지하1층(101,102,103동)인천광역시 미추홀구 주승로 253 (관교동, 동부아파트)221126801991-09-181991-09-1837.441224126.696268
100101관교동공공용시설쌍용아파트 지하1층(1,2,3,5,6동)인천광역시 미추홀구 주승로 231 (관교동, 쌍용아파트)297036001991-07-161991-07-1637.442361126.695006
101102관교동공공용시설삼환1차아파트 지하주차장인천광역시 미추홀구 주승로 223 (관교동, 삼환1차아파트)264032001992-04-011992-04-0137.443391126.6961
102103관교동공공용시설삼환1차아파트 지하1층(102,103,104동)인천광역시 미추홀구 주승로 223 (관교동, 삼환1차아파트)184822401999-01-011999-01-0137.444309126.69659
103104관교동공공용시설동아아파트 지하1층(1,2,3,5동)인천광역시 미추홀구 인하로430번길 15 (관교동, 동아아파트)320138801990-10-121990-10-1237.444309126.69659
104105관교동공공용시설신비마을아파트 지하1층(109,110,111,112동)인천광역시 미추홀구 주승로 160 (관교동, 신비마을아파트)201324401994-03-181994-03-1837.444942126.688195
105106문학동공공용시설문학경기장 내 야구장 지하주차장인천광역시 미추홀구 매소홀로 618 (문학동, 문학경기장)26664323202002-01-012002-01-0137.436545126.686461
106107문학동공공용시설호산아파트 지하주차장인천광역시 미추홀구 소성로318번길 5 (문학동, 호산아파트)204624801996-01-011996-01-0137.43722126.682841
107108문학동공공용시설국일아파트 지하주차장인천광역시 미추홀구 소성로 346 (문학동, 국일아파트)4295201994-01-011994-01-0137.437131126.685609