Overview

Dataset statistics

Number of variables10
Number of observations743
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory60.4 KiB
Average record size in memory83.2 B

Variable types

Numeric3
Categorical3
Text4

Dataset

Description경상북도 지역내 전시 적의 예측된 공중 미사일 공격등에 대해 신속하게 주변 대피로 인명을 보호 할 수 있는 민방위대피시설명칭, 주소, 대피가능면적, 대피가능인원 등의 현황입니다.
Author경상북도
URLhttps://www.data.go.kr/data/3083902/fileData.do

Alerts

시설종류 has constant value ""Constant
연번 is highly overall correlated with 시군High correlation
대피가능면적(제곱미터) is highly overall correlated with 대피 가능인원(명)High correlation
대피 가능인원(명) is highly overall correlated with 대피가능면적(제곱미터)High correlation
시군 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:54:57.932415
Analysis finished2023-12-12 12:55:00.022955
Duration2.09 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct743
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean372
Minimum1
Maximum743
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2023-12-12T21:55:00.109852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile38.1
Q1186.5
median372
Q3557.5
95-th percentile705.9
Maximum743
Range742
Interquartile range (IQR)371

Descriptive statistics

Standard deviation214.62991
Coefficient of variation (CV)0.57696213
Kurtosis-1.2
Mean372
Median Absolute Deviation (MAD)186
Skewness0
Sum276396
Variance46066
MonotonicityStrictly increasing
2023-12-12T21:55:00.282043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
500 1
 
0.1%
491 1
 
0.1%
492 1
 
0.1%
493 1
 
0.1%
494 1
 
0.1%
495 1
 
0.1%
496 1
 
0.1%
497 1
 
0.1%
498 1
 
0.1%
Other values (733) 733
98.7%
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 (%)
743 1
0.1%
742 1
0.1%
741 1
0.1%
740 1
0.1%
739 1
0.1%
738 1
0.1%
737 1
0.1%
736 1
0.1%
735 1
0.1%
734 1
0.1%

시군
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
구미시
168 
포항시
118 
안동시
73 
경주시
58 
영주시
48 
Other values (18)
278 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row경산시
2nd row상주시
3rd row상주시
4th row포항시
5th row포항시

Common Values

ValueCountFrequency (%)
구미시 168
22.6%
포항시 118
15.9%
안동시 73
9.8%
경주시 58
 
7.8%
영주시 48
 
6.5%
경산시 45
 
6.1%
김천시 44
 
5.9%
상주시 39
 
5.2%
예천군 23
 
3.1%
칠곡군 19
 
2.6%
Other values (13) 108
14.5%

Length

2023-12-12T21:55:00.460780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
구미시 168
22.6%
포항시 118
15.9%
안동시 73
9.8%
경주시 58
 
7.8%
영주시 48
 
6.5%
경산시 45
 
6.1%
김천시 44
 
5.9%
상주시 39
 
5.2%
예천군 23
 
3.1%
칠곡군 19
 
2.6%
Other values (13) 108
14.5%

읍면동
Text

Distinct139
Distinct (%)18.7%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
2023-12-12T21:55:01.068897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.2207268
Min length2

Characters and Unicode

Total characters2393
Distinct characters122
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

Unique27 ?
Unique (%)3.6%

Sample

1st row서부2동
2nd row남원동
3rd row남원동
4th row연일읍
5th row연일읍
ValueCountFrequency (%)
송정동 18
 
2.4%
양포동 18
 
2.4%
장량동 18
 
2.4%
연일읍 15
 
2.0%
형곡2동 15
 
2.0%
대신동 15
 
2.0%
신흥동 14
 
1.9%
형곡1동 14
 
1.9%
예천읍 14
 
1.9%
선주원남동 13
 
1.7%
Other values (129) 589
79.3%
2023-12-12T21:55:01.540395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 554
23.2%
읍 192
 
8.0%
곡 62
 
2.6%
양 51
 
2.1%
1 50
 
2.1%
2 50
 
2.1%
천 45
 
1.9%
남 44
 
1.8%
흥 38
 
1.6%
량 36
 
1.5%
Other values (112) 1271
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2280
95.3%
Decimal Number 113
 
4.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 554
24.3%
읍 192
 
8.4%
곡 62
 
2.7%
양 51
 
2.2%
천 45
 
2.0%
남 44
 
1.9%
흥 38
 
1.7%
량 36
 
1.6%
면 33
 
1.4%
대 33
 
1.4%
Other values (107) 1192
52.3%
Decimal Number
ValueCountFrequency (%)
1 50
44.2%
2 50
44.2%
5 7
 
6.2%
3 5
 
4.4%
4 1
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2280
95.3%
Common 113
 
4.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 554
24.3%
읍 192
 
8.4%
곡 62
 
2.7%
양 51
 
2.2%
천 45
 
2.0%
남 44
 
1.9%
흥 38
 
1.7%
량 36
 
1.6%
면 33
 
1.4%
대 33
 
1.4%
Other values (107) 1192
52.3%
Common
ValueCountFrequency (%)
1 50
44.2%
2 50
44.2%
5 7
 
6.2%
3 5
 
4.4%
4 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2280
95.3%
ASCII 113
 
4.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 554
24.3%
읍 192
 
8.4%
곡 62
 
2.7%
양 51
 
2.2%
천 45
 
2.0%
남 44
 
1.9%
흥 38
 
1.7%
량 36
 
1.6%
면 33
 
1.4%
대 33
 
1.4%
Other values (107) 1192
52.3%
ASCII
ValueCountFrequency (%)
1 50
44.2%
2 50
44.2%
5 7
 
6.2%
3 5
 
4.4%
4 1
 
0.9%

시설종류
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
공공용
743 

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 743
100.0%

Length

2023-12-12T21:55:01.707386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:55:01.814665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공용 743
100.0%

시설용도(공공용 시설건물 주용도)
Categorical

Distinct12
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
주거시설
435 
관공서
86 
주차장
60 
상업시설
56 
편의시설
 
31
Other values (7)
75 

Length

Max length4
Median length4
Mean length3.7792732
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타
2nd row주차장
3rd row주거시설
4th row주거시설
5th row주거시설

Common Values

ValueCountFrequency (%)
주거시설 435
58.5%
관공서 86
 
11.6%
주차장 60
 
8.1%
상업시설 56
 
7.5%
편의시설 31
 
4.2%
교육시설 24
 
3.2%
의료시설 21
 
2.8%
기타 9
 
1.2%
금융시설 8
 
1.1%
교통시설 7
 
0.9%
Other values (2) 6
 
0.8%

Length

2023-12-12T21:55:01.929641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
주거시설 435
58.5%
관공서 86
 
11.6%
주차장 60
 
8.1%
상업시설 56
 
7.5%
편의시설 31
 
4.2%
교육시설 24
 
3.2%
의료시설 21
 
2.8%
기타 9
 
1.2%
금융시설 8
 
1.1%
교통시설 7
 
0.9%
Other values (2) 6
 
0.8%

민방위대피시설명칭
Text

Distinct725
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
2023-12-12T21:55:02.256400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length22
Mean length8.7187079
Min length2

Characters and Unicode

Total characters6478
Distinct characters387
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique713 ?
Unique (%)96.0%

Sample

1st row경남신성 지하주차장
2nd row공영유료주차장 지하 주차장
3rd row대림아크로빌 지하 주차장
4th row대림한숲 3차
5th row대림한숲1차 1P
ValueCountFrequency (%)
지하주차장 89
 
8.6%
주차장 25
 
2.4%
지하 20
 
1.9%
아파트 10
 
1.0%
그린빌라 5
 
0.5%
apt 5
 
0.5%
대림한숲1차 5
 
0.5%
아이유쉘 4
 
0.4%
현대아파트 4
 
0.4%
우방 4
 
0.4%
Other values (798) 861
83.4%
2023-12-12T21:55:02.710345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
300
 
4.6%
차 262
 
4.0%
주 257
 
4.0%
아 241
 
3.7%
지 239
 
3.7%
파 206
 
3.2%
트 203
 
3.1%
장 194
 
3.0%
하 176
 
2.7%
동 154
 
2.4%
Other values (377) 4246
65.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5484
84.7%
Decimal Number 376
 
5.8%
Space Separator 300
 
4.6%
Uppercase Letter 96
 
1.5%
Open Punctuation 93
 
1.4%
Close Punctuation 92
 
1.4%
Other Punctuation 12
 
0.2%
Dash Punctuation 10
 
0.2%
Lowercase Letter 9
 
0.1%
Math Symbol 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
차 262
 
4.8%
주 257
 
4.7%
아 241
 
4.4%
지 239
 
4.4%
파 206
 
3.8%
트 203
 
3.7%
장 194
 
3.5%
하 176
 
3.2%
동 154
 
2.8%
대 105
 
1.9%
Other values (340) 3447
62.9%
Uppercase Letter
ValueCountFrequency (%)
A 24
25.0%
P 22
22.9%
T 22
22.9%
K 10
10.4%
B 4
 
4.2%
C 3
 
3.1%
L 2
 
2.1%
I 2
 
2.1%
V 1
 
1.0%
E 1
 
1.0%
Other values (5) 5
 
5.2%
Decimal Number
ValueCountFrequency (%)
1 139
37.0%
2 74
19.7%
0 60
16.0%
3 37
 
9.8%
4 20
 
5.3%
6 13
 
3.5%
5 12
 
3.2%
7 8
 
2.1%
9 7
 
1.9%
8 6
 
1.6%
Other Punctuation
ValueCountFrequency (%)
, 8
66.7%
. 3
 
25.0%
@ 1
 
8.3%
Lowercase Letter
ValueCountFrequency (%)
e 7
77.8%
t 1
 
11.1%
k 1
 
11.1%
Space Separator
ValueCountFrequency (%)
300
100.0%
Open Punctuation
ValueCountFrequency (%)
( 93
100.0%
Close Punctuation
ValueCountFrequency (%)
) 92
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5486
84.7%
Common 887
 
13.7%
Latin 105
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
차 262
 
4.8%
주 257
 
4.7%
아 241
 
4.4%
지 239
 
4.4%
파 206
 
3.8%
트 203
 
3.7%
장 194
 
3.5%
하 176
 
3.2%
동 154
 
2.8%
대 105
 
1.9%
Other values (341) 3449
62.9%
Common
ValueCountFrequency (%)
300
33.8%
1 139
15.7%
( 93
 
10.5%
) 92
 
10.4%
2 74
 
8.3%
0 60
 
6.8%
3 37
 
4.2%
4 20
 
2.3%
6 13
 
1.5%
5 12
 
1.4%
Other values (8) 47
 
5.3%
Latin
ValueCountFrequency (%)
A 24
22.9%
P 22
21.0%
T 22
21.0%
K 10
9.5%
e 7
 
6.7%
B 4
 
3.8%
C 3
 
2.9%
L 2
 
1.9%
I 2
 
1.9%
V 1
 
1.0%
Other values (8) 8
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5484
84.7%
ASCII 992
 
15.3%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
300
30.2%
1 139
14.0%
( 93
 
9.4%
) 92
 
9.3%
2 74
 
7.5%
0 60
 
6.0%
3 37
 
3.7%
A 24
 
2.4%
P 22
 
2.2%
T 22
 
2.2%
Other values (26) 129
13.0%
Hangul
ValueCountFrequency (%)
차 262
 
4.8%
주 257
 
4.7%
아 241
 
4.4%
지 239
 
4.4%
파 206
 
3.8%
트 203
 
3.7%
장 194
 
3.5%
하 176
 
3.2%
동 154
 
2.8%
대 105
 
1.9%
Other values (340) 3447
62.9%
None
ValueCountFrequency (%)
㈜ 2
100.0%

주소(도로명 주소)
Text

Distinct699
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
2023-12-12T21:55:03.137473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length34
Mean length20.664872
Min length8

Characters and Unicode

Total characters15354
Distinct characters342
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

Unique671 ?
Unique (%)90.3%

Sample

1st row경산시 성암로21길 69(중산동)
2nd row상주시 상산로 250(남성동)
3rd row상서문로 5(낙양동)
4th row포항시 남구 연일읍 유강길10번길 33-4, 37
5th row포항시 남구 연일읍 유강길9번길 61, 62
ValueCountFrequency (%)
경상북도 269
 
8.3%
구미시 169
 
5.2%
포항시 95
 
2.9%
안동시 74
 
2.3%
북구 64
 
2.0%
남구 53
 
1.6%
영주시 48
 
1.5%
경북 48
 
1.5%
경산시 45
 
1.4%
김천시 44
 
1.4%
Other values (1225) 2348
72.1%
2023-12-12T21:55:03.737216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2545
 
16.6%
시 625
 
4.1%
동 600
 
3.9%
로 525
 
3.4%
1 508
 
3.3%
경 465
 
3.0%
북 414
 
2.7%
( 382
 
2.5%
) 382
 
2.5%
상 365
 
2.4%
Other values (332) 8543
55.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9313
60.7%
Space Separator 2545
 
16.6%
Decimal Number 2405
 
15.7%
Open Punctuation 382
 
2.5%
Close Punctuation 382
 
2.5%
Other Punctuation 167
 
1.1%
Dash Punctuation 144
 
0.9%
Uppercase Letter 13
 
0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 625
 
6.7%
동 600
 
6.4%
로 525
 
5.6%
경 465
 
5.0%
북 414
 
4.4%
상 365
 
3.9%
길 353
 
3.8%
구 342
 
3.7%
도 330
 
3.5%
미 208
 
2.2%
Other values (306) 5086
54.6%
Decimal Number
ValueCountFrequency (%)
1 508
21.1%
2 345
14.3%
3 288
12.0%
5 224
9.3%
4 208
8.6%
0 183
 
7.6%
6 172
 
7.2%
7 166
 
6.9%
9 161
 
6.7%
8 150
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
S 2
15.4%
A 2
15.4%
G 2
15.4%
P 1
7.7%
B 1
7.7%
T 1
7.7%
W 1
7.7%
L 1
7.7%
I 1
7.7%
D 1
7.7%
Space Separator
ValueCountFrequency (%)
2545
100.0%
Open Punctuation
ValueCountFrequency (%)
( 382
100.0%
Close Punctuation
ValueCountFrequency (%)
) 382
100.0%
Other Punctuation
ValueCountFrequency (%)
, 167
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 144
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9313
60.7%
Common 6025
39.2%
Latin 16
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 625
 
6.7%
동 600
 
6.4%
로 525
 
5.6%
경 465
 
5.0%
북 414
 
4.4%
상 365
 
3.9%
길 353
 
3.8%
구 342
 
3.7%
도 330
 
3.5%
미 208
 
2.2%
Other values (306) 5086
54.6%
Common
ValueCountFrequency (%)
2545
42.2%
1 508
 
8.4%
( 382
 
6.3%
) 382
 
6.3%
2 345
 
5.7%
3 288
 
4.8%
5 224
 
3.7%
4 208
 
3.5%
0 183
 
3.0%
6 172
 
2.9%
Other values (5) 788
 
13.1%
Latin
ValueCountFrequency (%)
e 3
18.8%
S 2
12.5%
A 2
12.5%
G 2
12.5%
P 1
 
6.2%
B 1
 
6.2%
T 1
 
6.2%
W 1
 
6.2%
L 1
 
6.2%
I 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9313
60.7%
ASCII 6041
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2545
42.1%
1 508
 
8.4%
( 382
 
6.3%
) 382
 
6.3%
2 345
 
5.7%
3 288
 
4.8%
5 224
 
3.7%
4 208
 
3.4%
0 183
 
3.0%
6 172
 
2.8%
Other values (16) 804
 
13.3%
Hangul
ValueCountFrequency (%)
시 625
 
6.7%
동 600
 
6.4%
로 525
 
5.6%
경 465
 
5.0%
북 414
 
4.4%
상 365
 
3.9%
길 353
 
3.8%
구 342
 
3.7%
도 330
 
3.5%
미 208
 
2.2%
Other values (306) 5086
54.6%

주소(지번 주소)
Text

Distinct691
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
2023-12-12T21:55:04.135848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length27
Mean length15.788694
Min length7

Characters and Unicode

Total characters11731
Distinct characters187
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

Unique658 ?
Unique (%)88.6%

Sample

1st row경산시 중산동 35번지 3호
2nd row경상북도 상주시 남성동 85번지 49호
3rd row경상북도 상주시 낙양동 171번지 3호
4th row연일읍 594-3번지
5th row연일읍 581-1번지
ValueCountFrequency (%)
경상북도 301
 
11.0%
구미시 168
 
6.2%
안동시 73
 
2.7%
1호 72
 
2.6%
경주시 51
 
1.9%
경북 48
 
1.8%
영주시 48
 
1.8%
경산시 45
 
1.6%
김천시 44
 
1.6%
상주시 38
 
1.4%
Other values (908) 1843
67.5%
2023-12-12T21:55:04.591653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1989
 
17.0%
동 609
 
5.2%
1 572
 
4.9%
시 506
 
4.3%
지 505
 
4.3%
번 487
 
4.2%
경 463
 
3.9%
북 370
 
3.2%
상 365
 
3.1%
도 338
 
2.9%
Other values (177) 5527
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6836
58.3%
Decimal Number 2688
 
22.9%
Space Separator 1989
 
17.0%
Dash Punctuation 218
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 609
 
8.9%
시 506
 
7.4%
지 505
 
7.4%
번 487
 
7.1%
경 463
 
6.8%
북 370
 
5.4%
상 365
 
5.3%
도 338
 
4.9%
호 210
 
3.1%
읍 202
 
3.0%
Other values (165) 2781
40.7%
Decimal Number
ValueCountFrequency (%)
1 572
21.3%
3 310
11.5%
2 288
10.7%
4 266
9.9%
5 264
9.8%
6 214
 
8.0%
0 209
 
7.8%
8 193
 
7.2%
7 191
 
7.1%
9 181
 
6.7%
Space Separator
ValueCountFrequency (%)
1989
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 218
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6836
58.3%
Common 4895
41.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 609
 
8.9%
시 506
 
7.4%
지 505
 
7.4%
번 487
 
7.1%
경 463
 
6.8%
북 370
 
5.4%
상 365
 
5.3%
도 338
 
4.9%
호 210
 
3.1%
읍 202
 
3.0%
Other values (165) 2781
40.7%
Common
ValueCountFrequency (%)
1989
40.6%
1 572
 
11.7%
3 310
 
6.3%
2 288
 
5.9%
4 266
 
5.4%
5 264
 
5.4%
- 218
 
4.5%
6 214
 
4.4%
0 209
 
4.3%
8 193
 
3.9%
Other values (2) 372
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6836
58.3%
ASCII 4895
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1989
40.6%
1 572
 
11.7%
3 310
 
6.3%
2 288
 
5.9%
4 266
 
5.4%
5 264
 
5.4%
- 218
 
4.5%
6 214
 
4.4%
0 209
 
4.3%
8 193
 
3.9%
Other values (2) 372
 
7.6%
Hangul
ValueCountFrequency (%)
동 609
 
8.9%
시 506
 
7.4%
지 505
 
7.4%
번 487
 
7.1%
경 463
 
6.8%
북 370
 
5.4%
상 365
 
5.3%
도 338
 
4.9%
호 210
 
3.1%
읍 202
 
3.0%
Other values (165) 2781
40.7%

대피가능면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct618
Distinct (%)83.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3813.8143
Minimum40
Maximum57316
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2023-12-12T21:55:04.737840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40
5-th percentile149
Q1500.5
median1507
Q34309.5
95-th percentile14264.2
Maximum57316
Range57276
Interquartile range (IQR)3809

Descriptive statistics

Standard deviation6359.3355
Coefficient of variation (CV)1.6674476
Kurtosis21.991165
Mean3813.8143
Median Absolute Deviation (MAD)1208
Skewness4.0068204
Sum2833664
Variance40441148
MonotonicityNot monotonic
2023-12-12T21:55:04.870300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
661 13
 
1.7%
8250 5
 
0.7%
552 5
 
0.7%
165 4
 
0.5%
8970 4
 
0.5%
7900 4
 
0.5%
13800 4
 
0.5%
331 4
 
0.5%
14300 3
 
0.4%
198 3
 
0.4%
Other values (608) 694
93.4%
ValueCountFrequency (%)
40 1
0.1%
69 1
0.1%
75 1
0.1%
76 1
0.1%
82 1
0.1%
83 1
0.1%
91 1
0.1%
92 1
0.1%
93 1
0.1%
100 2
0.3%
ValueCountFrequency (%)
57316 1
0.1%
57305 1
0.1%
45849 1
0.1%
39579 1
0.1%
39130 1
0.1%
38830 1
0.1%
36215 1
0.1%
34848 1
0.1%
31950 1
0.1%
30741 1
0.1%

대피 가능인원(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct622
Distinct (%)83.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4622.323
Minimum48
Maximum69473
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2023-12-12T21:55:05.004489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum48
5-th percentile180
Q1606.5
median1826
Q35223.5
95-th percentile17289.6
Maximum69473
Range69425
Interquartile range (IQR)4617

Descriptive statistics

Standard deviation7708.2772
Coefficient of variation (CV)1.6676198
Kurtosis21.991007
Mean4622.323
Median Absolute Deviation (MAD)1464
Skewness4.0068121
Sum3434386
Variance59417537
MonotonicityNot monotonic
2023-12-12T21:55:05.135513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
801 13
 
1.7%
10000 5
 
0.7%
669 5
 
0.7%
9575 4
 
0.5%
16727 4
 
0.5%
200 4
 
0.5%
10872 4
 
0.5%
17333 3
 
0.4%
236 3
 
0.4%
240 3
 
0.4%
Other values (612) 695
93.5%
ValueCountFrequency (%)
48 1
0.1%
83 1
0.1%
90 1
0.1%
92 1
0.1%
99 1
0.1%
100 1
0.1%
110 1
0.1%
111 1
0.1%
112 1
0.1%
121 2
0.3%
ValueCountFrequency (%)
69473 1
0.1%
69460 1
0.1%
55574 1
0.1%
47974 1
0.1%
47430 1
0.1%
47066 1
0.1%
43896 1
0.1%
42240 1
0.1%
38727 1
0.1%
37261 1
0.1%

Interactions

2023-12-12T21:54:59.386974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:54:58.679403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:54:59.009587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:54:59.503594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:54:58.779613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:54:59.124958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:54:59.617140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:54:58.878958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:54:59.247287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:55:05.218578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군시설용도(공공용 시설건물 주용도)대피가능면적(제곱미터)대피 가능인원(명)
연번1.0000.9330.3670.1820.182
시군0.9331.0000.4730.1760.176
시설용도(공공용 시설건물 주용도)0.3670.4731.0000.0570.057
대피가능면적(제곱미터)0.1820.1760.0571.0001.000
대피 가능인원(명)0.1820.1760.0571.0001.000
2023-12-12T21:55:05.320055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설용도(공공용 시설건물 주용도)시군
시설용도(공공용 시설건물 주용도)1.0000.177
시군0.1771.000
2023-12-12T21:55:05.396654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번대피가능면적(제곱미터)대피 가능인원(명)시군시설용도(공공용 시설건물 주용도)
연번1.000-0.110-0.1100.7000.163
대피가능면적(제곱미터)-0.1101.0001.0000.0680.024
대피 가능인원(명)-0.1101.0001.0000.0680.024
시군0.7000.0680.0681.0000.177
시설용도(공공용 시설건물 주용도)0.1630.0240.0240.1771.000

Missing values

2023-12-12T21:54:59.775649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:54:59.957561image/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

연번시군읍면동시설종류시설용도(공공용 시설건물 주용도)민방위대피시설명칭주소(도로명 주소)주소(지번 주소)대피가능면적(제곱미터)대피 가능인원(명)
01경산시서부2동공공용기타경남신성 지하주차장경산시 성암로21길 69(중산동)경산시 중산동 35번지 3호1434417386
12상주시남원동공공용주차장공영유료주차장 지하 주차장상주시 상산로 250(남성동)경상북도 상주시 남성동 85번지 49호14241726
23상주시남원동공공용주거시설대림아크로빌 지하 주차장상서문로 5(낙양동)경상북도 상주시 낙양동 171번지 3호15931930
34포항시연일읍공공용주거시설대림한숲 3차포항시 남구 연일읍 유강길10번길 33-4, 37연일읍 594-3번지17382106
45포항시연일읍공공용주거시설대림한숲1차 1P포항시 남구 연일읍 유강길9번길 61, 62연일읍 581-1번지16532003
56포항시연일읍공공용주거시설대림한숲1차 3P포항시 남구 연일읍 유강길9번길 61, 62연일읍 581-1번지1380016727
67포항시연일읍공공용주거시설대림한숲1차 5P포항시 남구 연일읍 유강길9번길 61, 62연일읍 581-1번지1380016727
78포항시연일읍공공용주거시설대림한숲1차 7P포항시 남구 연일읍 유강길9번길 61, 62연일읍 581-1번지1380016727
89포항시연일읍공공용주거시설대림한숲1차 9P포항시 남구 연일읍 유강길9번길 61, 62연일읍 581-1번지1380016727
910경주시선도동공공용주거시설대우1차지하주차장경상북도 경주시 충효녹지길 142-9경주시 충효동 2927번지40864952
연번시군읍면동시설종류시설용도(공공용 시설건물 주용도)민방위대피시설명칭주소(도로명 주소)주소(지번 주소)대피가능면적(제곱미터)대피 가능인원(명)
733734안동시송하동공공용주거시설청구하이츠1차안동시 송현길84-28안동시 송현동 516-254256575
734735안동시송하동공공용주거시설청구하이츠2차안동시 송현길 84-8안동시 송현동 515495600
735736포항시중앙동공공용주차장청운우방지하주차장포항시 북구 중앙동 학전로 37(학산동)두호동 6-2번지59017152
736737구미시원평1동공공용주차장카사노바 유흥주점(주차장)경상북도 구미시 송원서로8길 33 (원평동)경상북도 구미시 원평동 1052번지 7호545660
737738경산시동부동공공용주거시설태왕드림하이츠 지하주차장경산시 삼풍로13-7(삼풍동)경산시 삼풍동 500번지 1호2094925392
738739봉화군봉화읍공공용주거시설톱텍씨티파크 지하주차장경상북도 봉화군 봉화읍 교통1길 2경상북도 봉화군 봉화읍 내성리 490-410671293
739740경산시서부2동공공용주차장펜타힐즈더샵1차 지하주차장경산시 펜타힐즈2로 60경산시 중산동 643번지3913047430
740741경산시서부2동공공용주거시설한서신혼하이츠 지하주차장경산시 대학로13길 26(정평동)경산시 정평동 255번지 39호79149592
741742경주시황성동공공용주차장현대5차경주시 황성로 62경주시 황성동 277-6917411120
742743영주시휴천1동공공용주거시설화성라온빌 주차장경상북도 영주시 남간로 71번길 46 (휴천동, 화성라온빌)경상북도 영주시 휴천동 1980번지557675