Overview

Dataset statistics

Number of variables17
Number of observations582
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory79.7 KiB
Average record size in memory140.2 B

Variable types

Numeric3
Categorical8
Text4
DateTime2

Dataset

Description전북특별자치도 민방위 비상 대피시설 현황(시군구, 읍면동, 지정,운영, 대피시설명, 평시활용 유형, 설치년도, 위치, 수용인원 등)
Author전북특별자치도
URLhttps://www.data.go.kr/data/15055712/fileData.do

Alerts

연번 is highly overall correlated with 시군구 and 2 other fieldsHigh correlation
수용인원 is highly overall correlated with 대피시설 면적High correlation
대피시설 면적 is highly overall correlated with 수용인원High correlation
시군구 is highly overall correlated with 연번 and 3 other fieldsHigh correlation
지정 운영 여부 is highly overall correlated with 시군구High correlation
급수시설 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
비상용품함 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
지정 운영 여부 is highly imbalanced (85.9%)Imbalance
방송시설 is highly imbalanced (57.0%)Imbalance
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 16:59:17.351022
Analysis finished2024-03-14 16:59:21.841117
Duration4.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct582
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean291.5
Minimum1
Maximum582
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-03-15T01:59:22.031304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile30.05
Q1146.25
median291.5
Q3436.75
95-th percentile552.95
Maximum582
Range581
Interquartile range (IQR)290.5

Descriptive statistics

Standard deviation168.1532
Coefficient of variation (CV)0.5768549
Kurtosis-1.2
Mean291.5
Median Absolute Deviation (MAD)145.5
Skewness0
Sum169653
Variance28275.5
MonotonicityStrictly increasing
2024-03-15T01:59:22.513721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
366 1
 
0.2%
386 1
 
0.2%
387 1
 
0.2%
388 1
 
0.2%
389 1
 
0.2%
390 1
 
0.2%
391 1
 
0.2%
392 1
 
0.2%
393 1
 
0.2%
Other values (572) 572
98.3%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
582 1
0.2%
581 1
0.2%
580 1
0.2%
579 1
0.2%
578 1
0.2%
577 1
0.2%
576 1
0.2%
575 1
0.2%
574 1
0.2%
573 1
0.2%

시군구
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
전주시 완산구
111 
전주시 덕진구
99 
익산시
92 
군산시
83 
정읍시
32 
Other values (11)
165 

Length

Max length7
Median length3
Mean length4.4364261
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전주시 완산구
2nd row전주시 완산구
3rd row전주시 완산구
4th row전주시 완산구
5th row전주시 완산구

Common Values

ValueCountFrequency (%)
전주시 완산구 111
19.1%
전주시 덕진구 99
17.0%
익산시 92
15.8%
군산시 83
14.3%
정읍시 32
 
5.5%
남원시 31
 
5.3%
완주군 30
 
5.2%
고창군 19
 
3.3%
김제시 17
 
2.9%
부안군 15
 
2.6%
Other values (6) 53
9.1%

Length

2024-03-15T01:59:22.939379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 210
26.5%
완산구 111
14.0%
덕진구 99
12.5%
익산시 92
11.6%
군산시 83
 
10.5%
정읍시 32
 
4.0%
남원시 31
 
3.9%
완주군 30
 
3.8%
고창군 19
 
2.4%
김제시 17
 
2.1%
Other values (7) 68
 
8.6%

읍면동
Text

Distinct100
Distinct (%)17.2%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
2024-03-15T01:59:23.900229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.3041237
Min length1

Characters and Unicode

Total characters1923
Distinct characters102
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)2.1%

Sample

1st row중앙동
2nd row중앙동
3rd row중앙동
4th row중앙동
5th row중앙동
ValueCountFrequency (%)
조촌동 19
 
3.3%
고창읍 19
 
3.3%
평화2동 18
 
3.1%
수송동 16
 
2.7%
모현동 15
 
2.6%
순창읍 14
 
2.4%
동산동 14
 
2.4%
진안읍 14
 
2.4%
우아1동 13
 
2.2%
송학동 13
 
2.2%
Other values (90) 427
73.4%
2024-03-15T01:59:25.393607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 485
25.2%
읍 104
 
5.4%
2 69
 
3.6%
1 58
 
3.0%
송 48
 
2.5%
삼 35
 
1.8%
산 35
 
1.8%
창 33
 
1.7%
서 33
 
1.7%
화 33
 
1.7%
Other values (92) 990
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1757
91.4%
Decimal Number 164
 
8.5%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 485
27.6%
읍 104
 
5.9%
송 48
 
2.7%
삼 35
 
2.0%
산 35
 
2.0%
창 33
 
1.9%
서 33
 
1.9%
화 33
 
1.9%
자 30
 
1.7%
수 30
 
1.7%
Other values (86) 891
50.7%
Decimal Number
ValueCountFrequency (%)
2 69
42.1%
1 58
35.4%
3 28
17.1%
4 5
 
3.0%
5 4
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1757
91.4%
Common 166
 
8.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 485
27.6%
읍 104
 
5.9%
송 48
 
2.7%
삼 35
 
2.0%
산 35
 
2.0%
창 33
 
1.9%
서 33
 
1.9%
화 33
 
1.9%
자 30
 
1.7%
수 30
 
1.7%
Other values (86) 891
50.7%
Common
ValueCountFrequency (%)
2 69
41.6%
1 58
34.9%
3 28
16.9%
4 5
 
3.0%
5 4
 
2.4%
- 2
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1757
91.4%
ASCII 166
 
8.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 485
27.6%
읍 104
 
5.9%
송 48
 
2.7%
삼 35
 
2.0%
산 35
 
2.0%
창 33
 
1.9%
서 33
 
1.9%
화 33
 
1.9%
자 30
 
1.7%
수 30
 
1.7%
Other values (86) 891
50.7%
ASCII
ValueCountFrequency (%)
2 69
41.6%
1 58
34.9%
3 28
16.9%
4 5
 
3.0%
5 4
 
2.4%
- 2
 
1.2%

지정 운영 여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
지정운영
563 
신규지정
 
17
-
 
2

Length

Max length4
Median length4
Mean length3.9896907
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지정운영 563
96.7%
신규지정 17
 
2.9%
- 2
 
0.3%

Length

2024-03-15T01:59:25.649444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:59:25.845183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지정운영 563
96.7%
신규지정 17
 
2.9%
2
 
0.3%

대피시설명
Text

Distinct553
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
2024-03-15T01:59:26.505882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length8.1838488
Min length2

Characters and Unicode

Total characters4763
Distinct characters329
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique533 ?
Unique (%)91.6%

Sample

1st row다가
2nd row하나금융투자
3rd row성원오피스텔
4th row앤씨웨이브
5th row전주태평SK뷰아파트
ValueCountFrequency (%)
아파트 56
 
6.4%
현대 16
 
1.8%
101동 12
 
1.4%
수송 11
 
1.3%
현대아파트 10
 
1.2%
부영2차아파트 9
 
1.0%
103동 8
 
0.9%
102동 8
 
0.9%
조촌 7
 
0.8%
부영1차아파트 6
 
0.7%
Other values (584) 726
83.5%
2024-03-15T01:59:27.671438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 399
 
8.4%
트 370
 
7.8%
파 369
 
7.7%
292
 
6.1%
동 163
 
3.4%
1 119
 
2.5%
차 103
 
2.2%
2 82
 
1.7%
대 80
 
1.7%
0 73
 
1.5%
Other values (319) 2713
57.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4059
85.2%
Decimal Number 370
 
7.8%
Space Separator 292
 
6.1%
Uppercase Letter 22
 
0.5%
Open Punctuation 6
 
0.1%
Close Punctuation 6
 
0.1%
Lowercase Letter 6
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 399
 
9.8%
트 370
 
9.1%
파 369
 
9.1%
동 163
 
4.0%
차 103
 
2.5%
대 80
 
2.0%
지 71
 
1.7%
주 59
 
1.5%
영 54
 
1.3%
현 53
 
1.3%
Other values (292) 2338
57.6%
Decimal Number
ValueCountFrequency (%)
1 119
32.2%
2 82
22.2%
0 73
19.7%
3 39
 
10.5%
5 23
 
6.2%
4 14
 
3.8%
6 8
 
2.2%
7 7
 
1.9%
9 3
 
0.8%
8 2
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
K 5
22.7%
L 4
18.2%
S 4
18.2%
H 2
 
9.1%
T 2
 
9.1%
B 2
 
9.1%
C 1
 
4.5%
A 1
 
4.5%
G 1
 
4.5%
Lowercase Letter
ValueCountFrequency (%)
e 3
50.0%
t 1
 
16.7%
k 1
 
16.7%
i 1
 
16.7%
Space Separator
ValueCountFrequency (%)
292
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4059
85.2%
Common 676
 
14.2%
Latin 28
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 399
 
9.8%
트 370
 
9.1%
파 369
 
9.1%
동 163
 
4.0%
차 103
 
2.5%
대 80
 
2.0%
지 71
 
1.7%
주 59
 
1.5%
영 54
 
1.3%
현 53
 
1.3%
Other values (292) 2338
57.6%
Common
ValueCountFrequency (%)
292
43.2%
1 119
17.6%
2 82
 
12.1%
0 73
 
10.8%
3 39
 
5.8%
5 23
 
3.4%
4 14
 
2.1%
6 8
 
1.2%
7 7
 
1.0%
( 6
 
0.9%
Other values (4) 13
 
1.9%
Latin
ValueCountFrequency (%)
K 5
17.9%
L 4
14.3%
S 4
14.3%
e 3
10.7%
H 2
 
7.1%
T 2
 
7.1%
B 2
 
7.1%
t 1
 
3.6%
k 1
 
3.6%
C 1
 
3.6%
Other values (3) 3
10.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4059
85.2%
ASCII 704
 
14.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 399
 
9.8%
트 370
 
9.1%
파 369
 
9.1%
동 163
 
4.0%
차 103
 
2.5%
대 80
 
2.0%
지 71
 
1.7%
주 59
 
1.5%
영 54
 
1.3%
현 53
 
1.3%
Other values (292) 2338
57.6%
ASCII
ValueCountFrequency (%)
292
41.5%
1 119
16.9%
2 82
 
11.6%
0 73
 
10.4%
3 39
 
5.5%
5 23
 
3.3%
4 14
 
2.0%
6 8
 
1.1%
7 7
 
1.0%
( 6
 
0.9%
Other values (17) 41
 
5.8%

평시활용 유형
Categorical

Distinct11
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
아파트 지하주차장
400 
관공서
63 
아파트 지하공간
 
31
상가시설
 
30
편의시설
 
15
Other values (6)
43 

Length

Max length9
Median length9
Mean length7.524055
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타
2nd row상가시설
3rd row주거시설
4th row상가시설
5th row아파트 지하공간

Common Values

ValueCountFrequency (%)
아파트 지하주차장 400
68.7%
관공서 63
 
10.8%
아파트 지하공간 31
 
5.3%
상가시설 30
 
5.2%
편의시설 15
 
2.6%
교육시설 14
 
2.4%
의료시설 10
 
1.7%
교통시설 7
 
1.2%
기타 5
 
0.9%
종교시설 4
 
0.7%

Length

2024-03-15T01:59:28.107006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
아파트 431
42.5%
지하주차장 400
39.5%
관공서 63
 
6.2%
지하공간 31
 
3.1%
상가시설 30
 
3.0%
편의시설 15
 
1.5%
교육시설 14
 
1.4%
의료시설 10
 
1.0%
교통시설 7
 
0.7%
기타 5
 
0.5%
Other values (2) 7
 
0.7%

도로명 주소
Text

Distinct534
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
2024-03-15T01:59:29.355794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length13.728522
Min length9

Characters and Unicode

Total characters7990
Distinct characters230
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique502 ?
Unique (%)86.3%

Sample

1st row전주시 완산구 전주천동로 224
2nd row전주시 완산구 팔달로 229
3rd row전주시 완산구 풍남문4길 25-26
4th row전주시 완산구 전주객사5길 35
5th row전주시 완산구 태평2길 22
ValueCountFrequency (%)
전주시 212
 
10.3%
완산구 111
 
5.4%
덕진구 101
 
4.9%
익산시 92
 
4.5%
군산시 84
 
4.1%
정읍시 32
 
1.6%
남원시 31
 
1.5%
완주군 30
 
1.5%
10 23
 
1.1%
고창읍 19
 
0.9%
Other values (670) 1318
64.2%
2024-03-15T01:59:31.010834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1531
19.2%
시 473
 
5.9%
1 418
 
5.2%
로 406
 
5.1%
산 353
 
4.4%
주 265
 
3.3%
2 225
 
2.8%
구 220
 
2.8%
길 220
 
2.8%
전 217
 
2.7%
Other values (220) 3662
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4690
58.7%
Decimal Number 1686
 
21.1%
Space Separator 1531
 
19.2%
Dash Punctuation 81
 
1.0%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 473
 
10.1%
로 406
 
8.7%
산 353
 
7.5%
주 265
 
5.7%
구 220
 
4.7%
길 220
 
4.7%
전 217
 
4.6%
군 198
 
4.2%
진 150
 
3.2%
완 144
 
3.1%
Other values (206) 2044
43.6%
Decimal Number
ValueCountFrequency (%)
1 418
24.8%
2 225
13.3%
3 171
10.1%
5 155
 
9.2%
0 142
 
8.4%
4 134
 
7.9%
6 130
 
7.7%
7 115
 
6.8%
9 104
 
6.2%
8 92
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
1531
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 81
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4690
58.7%
Common 3298
41.3%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 473
 
10.1%
로 406
 
8.7%
산 353
 
7.5%
주 265
 
5.7%
구 220
 
4.7%
길 220
 
4.7%
전 217
 
4.6%
군 198
 
4.2%
진 150
 
3.2%
완 144
 
3.1%
Other values (206) 2044
43.6%
Common
ValueCountFrequency (%)
1531
46.4%
1 418
 
12.7%
2 225
 
6.8%
3 171
 
5.2%
5 155
 
4.7%
0 142
 
4.3%
4 134
 
4.1%
6 130
 
3.9%
7 115
 
3.5%
9 104
 
3.2%
Other values (2) 173
 
5.2%
Latin
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4690
58.7%
ASCII 3300
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1531
46.4%
1 418
 
12.7%
2 225
 
6.8%
3 171
 
5.2%
5 155
 
4.7%
0 142
 
4.3%
4 134
 
4.1%
6 130
 
3.9%
7 115
 
3.5%
9 104
 
3.2%
Other values (4) 175
 
5.3%
Hangul
ValueCountFrequency (%)
시 473
 
10.1%
로 406
 
8.7%
산 353
 
7.5%
주 265
 
5.7%
구 220
 
4.7%
길 220
 
4.7%
전 217
 
4.6%
군 198
 
4.2%
진 150
 
3.2%
완 144
 
3.1%
Other values (206) 2044
43.6%

지번주소
Text

Distinct516
Distinct (%)88.7%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
2024-03-15T01:59:32.248342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length22
Mean length16.111684
Min length10

Characters and Unicode

Total characters9377
Distinct characters154
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique481 ?
Unique (%)82.6%

Sample

1st row전주시 완산구 다가동3가 185
2nd row전주시 완산구 고사동 2-1
3rd row전주시 완산구 중앙동4가 31-18
4th row전주시 완산구 고사동 96-1
5th row전주시 완산구 태평동 291
ValueCountFrequency (%)
전주시 212
 
9.8%
완산구 111
 
5.1%
덕진구 101
 
4.7%
익산시 92
 
4.2%
군산시 83
 
3.8%
1호 37
 
1.7%
정읍시 32
 
1.5%
남원시 31
 
1.4%
완주군 30
 
1.4%
나운동 22
 
1.0%
Other values (673) 1418
65.4%
2024-03-15T01:59:33.843106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1629
 
17.4%
동 480
 
5.1%
시 475
 
5.1%
1 471
 
5.0%
산 329
 
3.5%
2 311
 
3.3%
지 298
 
3.2%
번 295
 
3.1%
주 255
 
2.7%
6 222
 
2.4%
Other values (144) 4612
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5325
56.8%
Decimal Number 2261
24.1%
Space Separator 1629
 
17.4%
Dash Punctuation 161
 
1.7%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 480
 
9.0%
시 475
 
8.9%
산 329
 
6.2%
지 298
 
5.6%
번 295
 
5.5%
주 255
 
4.8%
구 219
 
4.1%
전 212
 
4.0%
군 210
 
3.9%
가 180
 
3.4%
Other values (131) 2372
44.5%
Decimal Number
ValueCountFrequency (%)
1 471
20.8%
2 311
13.8%
6 222
9.8%
3 219
9.7%
5 206
9.1%
7 180
 
8.0%
4 174
 
7.7%
8 169
 
7.5%
0 157
 
6.9%
9 152
 
6.7%
Space Separator
ValueCountFrequency (%)
1629
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 161
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5325
56.8%
Common 4051
43.2%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 480
 
9.0%
시 475
 
8.9%
산 329
 
6.2%
지 298
 
5.6%
번 295
 
5.5%
주 255
 
4.8%
구 219
 
4.1%
전 212
 
4.0%
군 210
 
3.9%
가 180
 
3.4%
Other values (131) 2372
44.5%
Common
ValueCountFrequency (%)
1629
40.2%
1 471
 
11.6%
2 311
 
7.7%
6 222
 
5.5%
3 219
 
5.4%
5 206
 
5.1%
7 180
 
4.4%
4 174
 
4.3%
8 169
 
4.2%
- 161
 
4.0%
Other values (2) 309
 
7.6%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5325
56.8%
ASCII 4052
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1629
40.2%
1 471
 
11.6%
2 311
 
7.7%
6 222
 
5.5%
3 219
 
5.4%
5 206
 
5.1%
7 180
 
4.4%
4 174
 
4.3%
8 169
 
4.2%
- 161
 
4.0%
Other values (3) 310
 
7.7%
Hangul
ValueCountFrequency (%)
동 480
 
9.0%
시 475
 
8.9%
산 329
 
6.2%
지 298
 
5.6%
번 295
 
5.5%
주 255
 
4.8%
구 219
 
4.1%
전 212
 
4.0%
군 210
 
3.9%
가 180
 
3.4%
Other values (131) 2372
44.5%

수용인원
Real number (ℝ)

HIGH CORRELATION 

Distinct507
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3679.7302
Minimum0
Maximum60176
Zeros2
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-03-15T01:59:34.526470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile284
Q11015.25
median2526
Q35204
95-th percentile9927.45
Maximum60176
Range60176
Interquartile range (IQR)4188.75

Descriptive statistics

Standard deviation4458.2342
Coefficient of variation (CV)1.2115655
Kurtosis54.691535
Mean3679.7302
Median Absolute Deviation (MAD)1780
Skewness5.6423729
Sum2141603
Variance19875852
MonotonicityNot monotonic
2024-03-15T01:59:34.817833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12120 10
 
1.7%
970 5
 
0.9%
6061 5
 
0.9%
2287 4
 
0.7%
747 3
 
0.5%
958 3
 
0.5%
2424 3
 
0.5%
1600 3
 
0.5%
2412 3
 
0.5%
80 3
 
0.5%
Other values (497) 540
92.8%
ValueCountFrequency (%)
0 2
0.3%
29 1
 
0.2%
80 3
0.5%
85 1
 
0.2%
97 1
 
0.2%
101 1
 
0.2%
124 1
 
0.2%
126 1
 
0.2%
160 1
 
0.2%
170 1
 
0.2%
ValueCountFrequency (%)
60176 1
 
0.2%
34514 1
 
0.2%
31634 3
 
0.5%
19200 1
 
0.2%
12120 10
1.7%
12028 1
 
0.2%
11395 1
 
0.2%
11303 1
 
0.2%
10960 1
 
0.2%
10915 1
 
0.2%

대피시설 면적
Real number (ℝ)

HIGH CORRELATION 

Distinct511
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3535.8041
Minimum0
Maximum53088
Zeros2
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-03-15T01:59:35.118859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile234
Q1838.5
median2130
Q34580
95-th percentile9999
Maximum53088
Range53088
Interquartile range (IQR)3741.5

Descriptive statistics

Standard deviation5009.9028
Coefficient of variation (CV)1.4169062
Kurtosis36.788059
Mean3535.8041
Median Absolute Deviation (MAD)1535
Skewness5.0589622
Sum2057838
Variance25099126
MonotonicityNot monotonic
2024-03-15T01:59:35.583258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9999 10
 
1.7%
5000 5
 
0.9%
800 5
 
0.9%
1887 4
 
0.7%
790 3
 
0.5%
2000 3
 
0.5%
1320 3
 
0.5%
66 3
 
0.5%
1990 3
 
0.5%
616 3
 
0.5%
Other values (501) 540
92.8%
ValueCountFrequency (%)
0 2
0.3%
24 1
 
0.2%
66 3
0.5%
70 1
 
0.2%
80 1
 
0.2%
83 1
 
0.2%
102 1
 
0.2%
104 1
 
0.2%
132 1
 
0.2%
140 1
 
0.2%
ValueCountFrequency (%)
53088 1
0.2%
49645 1
0.2%
39598 1
0.2%
28474 1
0.2%
27954 1
0.2%
27830 1
0.2%
26098 1
0.2%
24777 1
0.2%
23867 1
0.2%
23065 1
0.2%

건축연도
Date

Distinct399
Distinct (%)68.6%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
Minimum1977-10-12 00:00:00
Maximum2019-01-11 00:00:00
2024-03-15T01:59:35.945655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:59:36.217428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

지정연도
Date

Distinct221
Distinct (%)38.0%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
Minimum1977-10-12 00:00:00
Maximum2020-08-03 00:00:00
2024-03-15T01:59:36.625725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:59:37.035710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

방송시설
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
방송시설
487 
라디오
59 
없음
 
18
<NA>
 
18

Length

Max length4
Median length4
Mean length3.8367698
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row라디오
2nd row방송시설
3rd row방송시설
4th row방송시설
5th row방송시설

Common Values

ValueCountFrequency (%)
방송시설 487
83.7%
라디오 59
 
10.1%
없음 18
 
3.1%
<NA> 18
 
3.1%

Length

2024-03-15T01:59:37.292665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:59:37.550207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
방송시설 487
83.7%
라디오 59
 
10.1%
없음 18
 
3.1%
na 18
 
3.1%

급수시설
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
여
289 
부
264 
<NA>
29 

Length

Max length4
Median length1
Mean length1.1494845
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여 289
49.7%
부 264
45.4%
<NA> 29
 
5.0%

Length

2024-03-15T01:59:37.822576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:59:38.026395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여 289
49.7%
부 264
45.4%
na 29
 
5.0%

자가발전기
Categorical

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
여
456 
부
97 
<NA>
 
29

Length

Max length4
Median length1
Mean length1.1494845
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부
2nd row여
3rd row여
4th row여
5th row여

Common Values

ValueCountFrequency (%)
여 456
78.4%
부 97
 
16.7%
<NA> 29
 
5.0%

Length

2024-03-15T01:59:38.328069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:59:38.610048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여 456
78.4%
부 97
 
16.7%
na 29
 
5.0%

내진설계
Categorical

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
여
476 
부
77 
<NA>
 
29

Length

Max length4
Median length1
Mean length1.1494845
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부
2nd row부
3rd row여
4th row여
5th row여

Common Values

ValueCountFrequency (%)
여 476
81.8%
부 77
 
13.2%
<NA> 29
 
5.0%

Length

2024-03-15T01:59:38.927720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:59:39.172071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여 476
81.8%
부 77
 
13.2%
na 29
 
5.0%

비상용품함
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
1
268 
0
136 
3
114 
2
33 
<NA>
30 

Length

Max length4
Median length1
Mean length1.1546392
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row3
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
1 268
46.0%
0 136
23.4%
3 114
19.6%
2 33
 
5.7%
<NA> 30
 
5.2%
4 1
 
0.2%

Length

2024-03-15T01:59:39.556950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:59:39.905352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 268
46.0%
0 136
23.4%
3 114
19.6%
2 33
 
5.7%
na 30
 
5.2%
4 1
 
0.2%

Interactions

2024-03-15T01:59:20.575062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:59:19.325742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:59:19.918379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:59:20.741544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:59:19.590282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:59:20.085156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:59:20.906024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:59:19.760556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:59:20.279495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T01:59:40.150021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군구읍면동지정 운영 여부평시활용 유형수용인원대피시설 면적방송시설급수시설자가발전기내진설계비상용품함
연번1.0000.9440.9980.3760.3480.2780.2660.4810.8030.5350.4320.894
시군구0.9441.0001.0000.8670.4600.0640.0250.6840.9500.6110.4950.893
읍면동0.9981.0001.0000.9460.7390.3360.2650.8460.9780.8820.7370.956
지정 운영 여부0.3760.8670.9461.0000.1200.5080.3490.1460.0150.0000.0120.055
평시활용 유형0.3480.4600.7390.1201.0000.0000.0000.3220.0590.3880.4370.201
수용인원0.2780.0640.3360.5080.0001.0000.8320.0000.0000.0000.1300.000
대피시설 면적0.2660.0250.2650.3490.0000.8321.0000.0000.0000.1040.1320.380
방송시설0.4810.6840.8460.1460.3220.0000.0001.0000.1150.2590.2480.181
급수시설0.8030.9500.9780.0150.0590.0000.0000.1151.0000.5250.0000.432
자가발전기0.5350.6110.8820.0000.3880.0000.1040.2590.5251.0000.4910.124
내진설계0.4320.4950.7370.0120.4370.1300.1320.2480.0000.4911.0000.106
비상용품함0.8940.8930.9560.0550.2010.0000.3800.1810.4320.1240.1061.000
2024-03-15T01:59:40.440661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
평시활용 유형시군구지정 운영 여부자가발전기급수시설내진설계방송시설비상용품함
평시활용 유형1.0000.1920.0690.3690.0550.4160.1970.111
시군구0.1921.0000.7280.4790.8140.3860.4860.712
지정 운영 여부0.0690.7281.0000.0000.0250.0200.0440.041
자가발전기0.3690.4790.0001.0000.3520.3270.4210.151
급수시설0.0550.8140.0250.3521.0000.0000.1890.524
내진설계0.4160.3860.0200.3270.0001.0000.4040.129
방송시설0.1970.4860.0440.4210.1890.4041.0000.137
비상용품함0.1110.7120.0410.1510.5240.1290.1371.000
2024-03-15T01:59:40.680528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번수용인원대피시설 면적시군구지정 운영 여부평시활용 유형방송시설급수시설자가발전기내진설계비상용품함
연번1.000-0.165-0.1690.7610.2420.1560.3280.6330.4090.3300.577
수용인원-0.1651.0000.9660.0290.2420.0000.0000.0000.0000.0930.000
대피시설 면적-0.1690.9661.0000.0060.2360.0000.0000.0000.0780.0980.244
시군구0.7610.0290.0061.0000.7280.1920.4860.8140.4790.3860.712
지정 운영 여부0.2420.2420.2360.7281.0000.0690.0440.0250.0000.0200.041
평시활용 유형0.1560.0000.0000.1920.0691.0000.1970.0550.3690.4160.111
방송시설0.3280.0000.0000.4860.0440.1971.0000.1890.4210.4040.137
급수시설0.6330.0000.0000.8140.0250.0550.1891.0000.3520.0000.524
자가발전기0.4090.0000.0780.4790.0000.3690.4210.3521.0000.3270.151
내진설계0.3300.0930.0980.3860.0200.4160.4040.0000.3271.0000.129
비상용품함0.5770.0000.2440.7120.0410.1110.1370.5240.1510.1291.000

Missing values

2024-03-15T01:59:21.144770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T01:59:21.551497image/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

연번시군구읍면동지정 운영 여부대피시설명평시활용 유형도로명 주소지번주소수용인원대피시설 면적건축연도지정연도방송시설급수시설자가발전기내진설계비상용품함
01전주시 완산구중앙동지정운영다가기타전주시 완산구 전주천동로 224전주시 완산구 다가동3가 185157112961980-01-011980-01-01라디오여부부3
12전주시 완산구중앙동지정운영하나금융투자상가시설전주시 완산구 팔달로 229전주시 완산구 고사동 2-1151512501984-01-012010-01-01방송시설여여부2
23전주시 완산구중앙동지정운영성원오피스텔주거시설전주시 완산구 풍남문4길 25-26전주시 완산구 중앙동4가 31-18189815661994-01-012010-01-01방송시설여여여2
34전주시 완산구중앙동지정운영앤씨웨이브상가시설전주시 완산구 전주객사5길 35전주시 완산구 고사동 96-1690957002000-01-012010-01-01방송시설여여여2
45전주시 완산구중앙동지정운영전주태평SK뷰아파트아파트 지하공간전주시 완산구 태평2길 22전주시 완산구 태평동 291606150002009-01-012010-01-01방송시설여여여2
56전주시 완산구풍남동지정운영한벽문화관편의시설전주시 완산구 전주천동로 20전주시 완산구 교동 7-1283623402003-02-072003-02-07방송시설여여여3
67전주시 완산구풍남동지정운영르윈호텔상가시설전주시 완산구 기린대로 85전주시 완산구 풍남동3가 26-5564546572010-01-012010-01-01방송시설여여여1
78전주시 완산구풍남동지정운영한국전통문화전당편의시설전주시 완산구 현무1길 20전주시 완산구 경원동3가 14-2862771172012-06-042019-05-15방송시설여여여3
89전주시 완산구노송동지정운영풍남초등학교교육시설전주시 완산구 견훤왕궁로 1전주시 완산구 남노송동 507번지 1호10188401988-10-201988-10-20라디오여여부3
910전주시 완산구노송동지정운영기린봉아파트아파트 지하주차장전주시 완산구 견훤로 100전주시 완산구 중노송동 26번지 1호221918311993-03-301993-03-30방송시설여여여0
연번시군구읍면동지정 운영 여부대피시설명평시활용 유형도로명 주소지번주소수용인원대피시설 면적건축연도지정연도방송시설급수시설자가발전기내진설계비상용품함
572573부안군부안읍지정운영대림아파트아파트 지하공간부안군 낭주길 5부안군 부안읍 선은리 258-112029921997-08-292005-01-28방송시설부부여1
573574부안군부안읍지정운영동원아파트아파트 지하공간부안군 학동길 11-6부안군 부안읍 봉덕리 8149708001990-01-012005-01-28라디오부여여1
574575부안군부안읍지정운영상원아파트아파트 지하공간부안군 상원길 19부안군 부안읍 동중리 1069387741993-11-192005-01-28라디오부부여1
575576부안군부안읍지정운영하이안아파트아파트 지하주차장부안군 오리정로 172부안군 부안읍 봉덕리 910315226002005-10-212006-07-12방송시설부여여1
576577부안군부안읍지정운영부안군청관공서부안군 당산로 91부안군 부안읍 동중리 222-1460638002010-12-022010-11-29방송시설부여여1
577578부안군부안읍지정운영현대아파트아파트 지하주차장부안군 봉신길 19부안군 부안읍 봉덕리 626-4233219241995-01-011995-01-02방송시설부여여1
578579부안군부안읍지정운영미소가애(주공4차)아파트 지하주차장부안군 석정로 262부안군 부안읍 봉덕리 912727360002015-02-012017-10-19방송시설여여여1
579580부안군변산면지정운영송림아파트아파트 지하주차장부안군 지서로 80부안군 변산면 지서리 408606150002000-10-012011-03-09방송시설부여여1
580581부안군변산면지정운영대명리조트상가시설부안군 변산해변로 51부안군 변산면 격포리 259-63121210002008-07-112011-03-09방송시설부여여1
581582부안군변산면지정운영양우아파트아파트 지하주차장부안군 격포윗길 20부안군 변산면 격포리 272-21242420001994-02-042011-03-10방송시설부부여1