Overview

Dataset statistics

Number of variables11
Number of observations505
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory45.5 KiB
Average record size in memory92.3 B

Variable types

Text5
Categorical2
Numeric4

Dataset

Description인천시내 화재,지진, 폭발, 호우, 태풍, 기타 천재지변으로 인한 재난 발생시 임시로 대피할수 있는 임시주거시설 목록입니다.
Author인천광역시
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15103330&srcSe=7661IVAWM27C61E190

Alerts

수용가능면적(제곱미터) is highly overall correlated with 수용가능인원(명)High correlation
수용가능인원(명) is highly overall correlated with 수용가능면적(제곱미터)High correlation
시설구분 is highly overall correlated with 내진설계High correlation
내진설계 is highly overall correlated with 시설구분High correlation

Reproduction

Analysis started2024-01-28 08:50:57.660701
Analysis finished2024-01-28 08:50:59.676220
Duration2.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역 명
Text

Distinct158
Distinct (%)31.3%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2024-01-28T17:50:59.838552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length14.09703
Min length11

Characters and Unicode

Total characters7119
Distinct characters156
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

Unique73 ?
Unique (%)14.5%

Sample

1st row인천광역시 중구 항동7가
2nd row인천광역시 중구 항동7가
3rd row인천광역시 중구 신생동
4th row인천광역시 중구 관동1가
5th row인천광역시 중구 답동
ValueCountFrequency (%)
인천광역시 505
30.2%
옹진군 93
 
5.6%
서구 82
 
4.9%
강화군 64
 
3.8%
미추홀구 49
 
2.9%
부평구 47
 
2.8%
연수구 46
 
2.8%
남동구 42
 
2.5%
계양구 40
 
2.4%
백령면 30
 
1.8%
Other values (177) 674
40.3%
2024-01-28T17:51:00.188072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1167
16.4%
천 511
 
7.2%
시 508
 
7.1%
인 505
 
7.1%
광 505
 
7.1%
역 505
 
7.1%
동 420
 
5.9%
구 357
 
5.0%
군 157
 
2.2%
리 157
 
2.2%
Other values (146) 2327
32.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5941
83.5%
Space Separator 1167
 
16.4%
Decimal Number 11
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 511
 
8.6%
시 508
 
8.6%
인 505
 
8.5%
광 505
 
8.5%
역 505
 
8.5%
동 420
 
7.1%
구 357
 
6.0%
군 157
 
2.6%
리 157
 
2.6%
면 147
 
2.5%
Other values (141) 2169
36.5%
Decimal Number
ValueCountFrequency (%)
3 4
36.4%
2 3
27.3%
1 2
18.2%
7 2
18.2%
Space Separator
ValueCountFrequency (%)
1167
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5941
83.5%
Common 1178
 
16.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 511
 
8.6%
시 508
 
8.6%
인 505
 
8.5%
광 505
 
8.5%
역 505
 
8.5%
동 420
 
7.1%
구 357
 
6.0%
군 157
 
2.6%
리 157
 
2.6%
면 147
 
2.5%
Other values (141) 2169
36.5%
Common
ValueCountFrequency (%)
1167
99.1%
3 4
 
0.3%
2 3
 
0.3%
1 2
 
0.2%
7 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5941
83.5%
ASCII 1178
 
16.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1167
99.1%
3 4
 
0.3%
2 3
 
0.3%
1 2
 
0.2%
7 2
 
0.2%
Hangul
ValueCountFrequency (%)
천 511
 
8.6%
시 508
 
8.6%
인 505
 
8.5%
광 505
 
8.5%
역 505
 
8.5%
동 420
 
7.1%
구 357
 
6.0%
군 157
 
2.6%
리 157
 
2.6%
면 147
 
2.5%
Other values (141) 2169
36.5%

시설구분
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
학교
287 
경로당
75 
기타시설
44 
마을회관
41 
관공서
33 
Other values (3)
 
25

Length

Max length56
Median length2
Mean length3.5425743
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
학교 287
56.8%
경로당 75
 
14.9%
기타시설 44
 
8.7%
마을회관 41
 
8.1%
관공서 33
 
6.5%
교회 11
 
2.2%
공공시설(국·공립도서관, 공립병원, 시·도민회관, 구민회관 주민체육시설, 노인병원, 어린이도서관 등) 9
 
1.8%
연수,숙박 5
 
1.0%

Length

2024-01-28T17:51:00.333756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T17:51:00.440973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
학교 287
50.5%
경로당 75
 
13.2%
기타시설 44
 
7.7%
마을회관 41
 
7.2%
관공서 33
 
5.8%
교회 11
 
1.9%
공공시설(국·공립도서관 9
 
1.6%
공립병원 9
 
1.6%
시·도민회관 9
 
1.6%
구민회관 9
 
1.6%
Other values (5) 41
 
7.2%

시설명
Text

Distinct500
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2024-01-28T17:51:00.708586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length7.249505
Min length4

Characters and Unicode

Total characters3661
Distinct characters244
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique495 ?
Unique (%)98.0%

Sample

1st row연안동 행정복지센터
2nd row연안초등학교
3rd row신포동 행정복지센터
4th row중구제1청
5th row송도중학교
ValueCountFrequency (%)
대피호 37
 
5.6%
강당 31
 
4.7%
마을회관 17
 
2.6%
행정복지센터 15
 
2.3%
본관 9
 
1.4%
체육관 7
 
1.1%
교실 6
 
0.9%
주민센터 4
 
0.6%
다목적회관 4
 
0.6%
경로당 4
 
0.6%
Other values (517) 532
79.9%
2024-01-28T17:51:01.087614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 316
 
8.6%
학 306
 
8.4%
등 213
 
5.8%
초 179
 
4.9%
161
 
4.4%
당 105
 
2.9%
관 82
 
2.2%
경 74
 
2.0%
중 74
 
2.0%
로 70
 
1.9%
Other values (234) 2081
56.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3360
91.8%
Space Separator 161
 
4.4%
Decimal Number 122
 
3.3%
Close Punctuation 6
 
0.2%
Open Punctuation 6
 
0.2%
Other Punctuation 3
 
0.1%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 316
 
9.4%
학 306
 
9.1%
등 213
 
6.3%
초 179
 
5.3%
당 105
 
3.1%
관 82
 
2.4%
경 74
 
2.2%
중 74
 
2.2%
로 70
 
2.1%
동 69
 
2.1%
Other values (216) 1872
55.7%
Decimal Number
ValueCountFrequency (%)
1 36
29.5%
2 34
27.9%
3 15
12.3%
4 11
 
9.0%
5 9
 
7.4%
7 5
 
4.1%
6 5
 
4.1%
8 3
 
2.5%
9 3
 
2.5%
0 1
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
T 1
33.3%
M 1
33.3%
I 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
161
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3360
91.8%
Common 298
 
8.1%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 316
 
9.4%
학 306
 
9.1%
등 213
 
6.3%
초 179
 
5.3%
당 105
 
3.1%
관 82
 
2.4%
경 74
 
2.2%
중 74
 
2.2%
로 70
 
2.1%
동 69
 
2.1%
Other values (216) 1872
55.7%
Common
ValueCountFrequency (%)
161
54.0%
1 36
 
12.1%
2 34
 
11.4%
3 15
 
5.0%
4 11
 
3.7%
5 9
 
3.0%
) 6
 
2.0%
( 6
 
2.0%
7 5
 
1.7%
6 5
 
1.7%
Other values (5) 10
 
3.4%
Latin
ValueCountFrequency (%)
T 1
33.3%
M 1
33.3%
I 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3360
91.8%
ASCII 301
 
8.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 316
 
9.4%
학 306
 
9.1%
등 213
 
6.3%
초 179
 
5.3%
당 105
 
3.1%
관 82
 
2.4%
경 74
 
2.2%
중 74
 
2.2%
로 70
 
2.1%
동 69
 
2.1%
Other values (216) 1872
55.7%
ASCII
ValueCountFrequency (%)
161
53.5%
1 36
 
12.0%
2 34
 
11.3%
3 15
 
5.0%
4 11
 
3.7%
5 9
 
3.0%
) 6
 
2.0%
( 6
 
2.0%
7 5
 
1.7%
6 5
 
1.7%
Other values (8) 13
 
4.3%

상세시설명
Text

Distinct158
Distinct (%)31.3%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2024-01-28T17:51:01.262902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length5.0079208
Min length2

Characters and Unicode

Total characters2529
Distinct characters153
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

Unique126 ?
Unique (%)25.0%

Sample

1st row회의실
2nd row체육관
3rd row회의실
4th row상황실 및 회의실
5th row급식소
ValueCountFrequency (%)
강당 119
18.8%
본관 47
 
7.4%
경로당 40
 
6.3%
대피시설 37
 
5.9%
체육관 33
 
5.2%
2층 27
 
4.3%
강당(교사시설 25
 
4.0%
마을회관 22
 
3.5%
5층 15
 
2.4%
3층 12
 
1.9%
Other values (144) 255
40.3%
2024-01-28T17:51:01.557922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
당 236
 
9.3%
강 196
 
7.8%
관 155
 
6.1%
127
 
5.0%
교 121
 
4.8%
사 95
 
3.8%
층 91
 
3.6%
시 85
 
3.4%
설 84
 
3.3%
) 80
 
3.2%
Other values (143) 1259
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2082
82.3%
Decimal Number 136
 
5.4%
Space Separator 127
 
5.0%
Close Punctuation 80
 
3.2%
Open Punctuation 79
 
3.1%
Other Punctuation 21
 
0.8%
Math Symbol 3
 
0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
당 236
 
11.3%
강 196
 
9.4%
관 155
 
7.4%
교 121
 
5.8%
사 95
 
4.6%
층 91
 
4.4%
시 85
 
4.1%
설 84
 
4.0%
동 67
 
3.2%
회 64
 
3.1%
Other values (130) 888
42.7%
Decimal Number
ValueCountFrequency (%)
2 65
47.8%
1 23
 
16.9%
3 18
 
13.2%
5 16
 
11.8%
4 13
 
9.6%
8 1
 
0.7%
Other Punctuation
ValueCountFrequency (%)
, 11
52.4%
/ 10
47.6%
Space Separator
ValueCountFrequency (%)
127
100.0%
Close Punctuation
ValueCountFrequency (%)
) 80
100.0%
Open Punctuation
ValueCountFrequency (%)
( 79
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2082
82.3%
Common 446
 
17.6%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
당 236
 
11.3%
강 196
 
9.4%
관 155
 
7.4%
교 121
 
5.8%
사 95
 
4.6%
층 91
 
4.4%
시 85
 
4.1%
설 84
 
4.0%
동 67
 
3.2%
회 64
 
3.1%
Other values (130) 888
42.7%
Common
ValueCountFrequency (%)
127
28.5%
) 80
17.9%
( 79
17.7%
2 65
14.6%
1 23
 
5.2%
3 18
 
4.0%
5 16
 
3.6%
4 13
 
2.9%
, 11
 
2.5%
/ 10
 
2.2%
Other values (2) 4
 
0.9%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2082
82.3%
ASCII 447
 
17.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
당 236
 
11.3%
강 196
 
9.4%
관 155
 
7.4%
교 121
 
5.8%
사 95
 
4.6%
층 91
 
4.4%
시 85
 
4.1%
설 84
 
4.0%
동 67
 
3.2%
회 64
 
3.1%
Other values (130) 888
42.7%
ASCII
ValueCountFrequency (%)
127
28.4%
) 80
17.9%
( 79
17.7%
2 65
14.5%
1 23
 
5.1%
3 18
 
4.0%
5 16
 
3.6%
4 13
 
2.9%
, 11
 
2.5%
/ 10
 
2.2%
Other values (3) 5
 
1.1%

상세주소
Text

Distinct496
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2024-01-28T17:51:02.042070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length34
Mean length24.247525
Min length19

Characters and Unicode

Total characters12245
Distinct characters255
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

Unique489 ?
Unique (%)96.8%

Sample

1st row인천광역시 중구 축항대로86번길 44(항동7가)
2nd row인천광역시 중구 연안부두로33번길 53(항동7가)
3rd row인천광역시 중구 제물량로 168(신생동)
4th row인천광역시 중구 신포로27번길 80(관동1가)
5th row인천광역시 중구 제물량로 123(답동)
ValueCountFrequency (%)
인천광역시 505
22.8%
옹진군 93
 
4.2%
서구 82
 
3.7%
강화군 64
 
2.9%
미추홀구 49
 
2.2%
부평구 47
 
2.1%
연수구 46
 
2.1%
남동구 42
 
1.9%
계양구 40
 
1.8%
백령면 30
 
1.4%
Other values (910) 1217
54.9%
2024-01-28T17:51:02.363709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1710
 
14.0%
인 529
 
4.3%
시 514
 
4.2%
천 513
 
4.2%
역 507
 
4.1%
광 506
 
4.1%
로 476
 
3.9%
동 443
 
3.6%
구 361
 
2.9%
( 359
 
2.9%
Other values (245) 6327
51.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7851
64.1%
Decimal Number 1875
 
15.3%
Space Separator 1710
 
14.0%
Open Punctuation 359
 
2.9%
Close Punctuation 359
 
2.9%
Dash Punctuation 88
 
0.7%
Other Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 529
 
6.7%
시 514
 
6.5%
천 513
 
6.5%
역 507
 
6.5%
광 506
 
6.4%
로 476
 
6.1%
동 443
 
5.6%
구 361
 
4.6%
길 277
 
3.5%
번 228
 
2.9%
Other values (230) 3497
44.5%
Decimal Number
ValueCountFrequency (%)
1 357
19.0%
2 249
13.3%
3 229
12.2%
4 196
10.5%
5 180
9.6%
6 150
8.0%
0 137
 
7.3%
8 136
 
7.3%
7 135
 
7.2%
9 106
 
5.7%
Space Separator
ValueCountFrequency (%)
1710
100.0%
Open Punctuation
ValueCountFrequency (%)
( 359
100.0%
Close Punctuation
ValueCountFrequency (%)
) 359
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 88
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7851
64.1%
Common 4394
35.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 529
 
6.7%
시 514
 
6.5%
천 513
 
6.5%
역 507
 
6.5%
광 506
 
6.4%
로 476
 
6.1%
동 443
 
5.6%
구 361
 
4.6%
길 277
 
3.5%
번 228
 
2.9%
Other values (230) 3497
44.5%
Common
ValueCountFrequency (%)
1710
38.9%
( 359
 
8.2%
) 359
 
8.2%
1 357
 
8.1%
2 249
 
5.7%
3 229
 
5.2%
4 196
 
4.5%
5 180
 
4.1%
6 150
 
3.4%
0 137
 
3.1%
Other values (5) 468
 
10.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7851
64.1%
ASCII 4394
35.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1710
38.9%
( 359
 
8.2%
) 359
 
8.2%
1 357
 
8.1%
2 249
 
5.7%
3 229
 
5.2%
4 196
 
4.5%
5 180
 
4.1%
6 150
 
3.4%
0 137
 
3.1%
Other values (5) 468
 
10.7%
Hangul
ValueCountFrequency (%)
인 529
 
6.7%
시 514
 
6.5%
천 513
 
6.5%
역 507
 
6.5%
광 506
 
6.4%
로 476
 
6.1%
동 443
 
5.6%
구 361
 
4.6%
길 277
 
3.5%
번 228
 
2.9%
Other values (230) 3497
44.5%

위도
Real number (ℝ)

Distinct501
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.535013
Minimum37.025813
Maximum37.975742
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2024-01-28T17:51:02.522204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.025813
5-th percentile37.256452
Q137.451202
median37.502913
Q337.592573
95-th percentile37.935803
Maximum37.975742
Range0.94992914
Interquartile range (IQR)0.14137091

Descriptive statistics

Standard deviation0.16137038
Coefficient of variation (CV)0.0042991962
Kurtosis1.3086409
Mean37.535013
Median Absolute Deviation (MAD)0.05689185
Skewness0.83074695
Sum18955.181
Variance0.026040401
MonotonicityNot monotonic
2024-01-28T17:51:02.654072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.45388729 2
 
0.4%
37.49748665 2
 
0.4%
37.25144601 2
 
0.4%
37.25428345 2
 
0.4%
37.45493467 1
 
0.2%
37.61634365 1
 
0.2%
37.61390574 1
 
0.2%
37.59039921 1
 
0.2%
37.59703707 1
 
0.2%
37.59672361 1
 
0.2%
Other values (491) 491
97.2%
ValueCountFrequency (%)
37.02581301 1
0.2%
37.16775172 1
0.2%
37.17242538 1
0.2%
37.176417 1
0.2%
37.18166176 1
0.2%
37.21363543 1
0.2%
37.2232812 1
0.2%
37.22338568 1
0.2%
37.22762494 1
0.2%
37.22897812 1
0.2%
ValueCountFrequency (%)
37.97574215 1
0.2%
37.97561329 1
0.2%
37.97519138 1
0.2%
37.97473007 1
0.2%
37.97441141 1
0.2%
37.97316388 1
0.2%
37.97280722 1
0.2%
37.97273875 1
0.2%
37.97117335 1
0.2%
37.97045855 1
0.2%

경도
Real number (ℝ)

Distinct501
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.44674
Minimum124.62096
Maximum126.77993
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2024-01-28T17:51:02.787218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum124.62096
5-th percentile124.71781
Q1126.46777
median126.65848
Q3126.69907
95-th percentile126.73836
Maximum126.77993
Range2.1589716
Interquartile range (IQR)0.2313027

Descriptive statistics

Standard deviation0.53631038
Coefficient of variation (CV)0.0042413935
Kurtosis5.9268409
Mean126.44674
Median Absolute Deviation (MAD)0.05861
Skewness-2.67356
Sum63855.603
Variance0.28762883
MonotonicityNot monotonic
2024-01-28T17:51:02.904763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.6315701 2
 
0.4%
126.4842725 2
 
0.4%
126.1163432 2
 
0.4%
126.3074136 2
 
0.4%
126.6012232 1
 
0.2%
126.6947225 1
 
0.2%
126.6893271 1
 
0.2%
126.6985466 1
 
0.2%
126.7049997 1
 
0.2%
126.7035208 1
 
0.2%
Other values (491) 491
97.2%
ValueCountFrequency (%)
124.6209628 1
0.2%
124.6475203 1
0.2%
124.653772 1
0.2%
124.6557153 1
0.2%
124.6561197 1
0.2%
124.6564147 1
0.2%
124.665684 1
0.2%
124.6657639 1
0.2%
124.6664446 1
0.2%
124.6716016 1
0.2%
ValueCountFrequency (%)
126.7799344 1
0.2%
126.7597234 1
0.2%
126.7526344 1
0.2%
126.751848 1
0.2%
126.7502867 1
0.2%
126.7496558 1
0.2%
126.7495838 1
0.2%
126.7479607 1
0.2%
126.7471112 1
0.2%
126.7458701 1
0.2%

수용가능면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct401
Distinct (%)79.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1005.4704
Minimum23
Maximum31295
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2024-01-28T17:51:03.008382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23
5-th percentile74.52
Q1189
median511
Q3844
95-th percentile3168.8
Maximum31295
Range31272
Interquartile range (IQR)655

Descriptive statistics

Standard deviation2583.538
Coefficient of variation (CV)2.5694819
Kurtosis79.506038
Mean1005.4704
Median Absolute Deviation (MAD)327.04
Skewness8.1901391
Sum507762.55
Variance6674668.4
MonotonicityNot monotonic
2024-01-28T17:51:03.134627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
486.0 6
 
1.2%
132.0 6
 
1.2%
166.0 5
 
1.0%
170.0 5
 
1.0%
165.0 4
 
0.8%
66.0 4
 
0.8%
232.0 4
 
0.8%
662.0 4
 
0.8%
405.0 3
 
0.6%
98.0 3
 
0.6%
Other values (391) 461
91.3%
ValueCountFrequency (%)
23.0 1
 
0.2%
29.25 1
 
0.2%
37.8 1
 
0.2%
40.8 1
 
0.2%
45.36 1
 
0.2%
46.0 1
 
0.2%
47.6 1
 
0.2%
51.84 3
0.6%
52.0 1
 
0.2%
57.0 1
 
0.2%
ValueCountFrequency (%)
31295.0 1
0.2%
29096.0 1
0.2%
22252.0 1
0.2%
18718.0 1
0.2%
15579.9 1
0.2%
10742.0 1
0.2%
7541.0 1
0.2%
7385.0 1
0.2%
7320.0 1
0.2%
6914.0 1
0.2%

수용가능인원(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct313
Distinct (%)62.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean349.91881
Minimum6
Maximum12036
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2024-01-28T17:51:03.260937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile26
Q168
median180
Q3300
95-th percentile951.2
Maximum12036
Range12030
Interquartile range (IQR)232

Descriptive statistics

Standard deviation934.62362
Coefficient of variation (CV)2.6709728
Kurtosis97.383446
Mean349.91881
Median Absolute Deviation (MAD)114
Skewness9.075788
Sum176709
Variance873521.3
MonotonicityNot monotonic
2024-01-28T17:51:03.390622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
63 11
 
2.2%
50 7
 
1.4%
186 6
 
1.2%
100 6
 
1.2%
65 6
 
1.2%
53 5
 
1.0%
38 5
 
1.0%
37 5
 
1.0%
128 5
 
1.0%
26 5
 
1.0%
Other values (303) 444
87.9%
ValueCountFrequency (%)
6 1
 
0.2%
10 1
 
0.2%
11 1
 
0.2%
13 1
 
0.2%
14 1
 
0.2%
15 1
 
0.2%
17 1
 
0.2%
18 3
0.6%
19 3
0.6%
20 1
 
0.2%
ValueCountFrequency (%)
12036 1
0.2%
11190 1
0.2%
8558 1
0.2%
5199 1
0.2%
4721 1
0.2%
3255 1
0.2%
3177 1
0.2%
2815 1
0.2%
2285 1
0.2%
2237 1
0.2%

담당부서
Text

Distinct138
Distinct (%)27.3%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2024-01-28T17:51:03.560582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length30
Mean length20.407921
Min length5

Characters and Unicode

Total characters10306
Distinct characters127
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

Unique113 ?
Unique (%)22.4%

Sample

1st row인천광역시 중구 도시재생국 안전관리과
2nd row인천광역시 중구 도시재생국 안전관리과
3rd row인천광역시 중구 도시재생국 안전관리과
4th row인천광역시 중구 도시재생국 안전관리과
5th row인천광역시 중구 도시재생국 안전관리과
ValueCountFrequency (%)
인천광역시 407
23.0%
안전총괄과 134
 
7.6%
인천광역시교육청 95
 
5.4%
옹진군 93
 
5.3%
환경안전국 82
 
4.6%
서구 82
 
4.6%
안전관리과 82
 
4.6%
행정복지국 58
 
3.3%
재난안전과 54
 
3.1%
미추홀구 49
 
2.8%
Other values (143) 633
35.8%
2024-01-28T17:51:03.845884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1264
 
12.3%
천 639
 
6.2%
인 638
 
6.2%
시 620
 
6.0%
광 589
 
5.7%
역 584
 
5.7%
전 541
 
5.2%
안 540
 
5.2%
과 315
 
3.1%
교 279
 
2.7%
Other values (117) 4297
41.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9039
87.7%
Space Separator 1264
 
12.3%
Decimal Number 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 639
 
7.1%
인 638
 
7.1%
시 620
 
6.9%
광 589
 
6.5%
역 584
 
6.5%
전 541
 
6.0%
안 540
 
6.0%
과 315
 
3.5%
교 279
 
3.1%
국 276
 
3.1%
Other values (114) 4018
44.5%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
1 1
33.3%
Space Separator
ValueCountFrequency (%)
1264
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9039
87.7%
Common 1267
 
12.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 639
 
7.1%
인 638
 
7.1%
시 620
 
6.9%
광 589
 
6.5%
역 584
 
6.5%
전 541
 
6.0%
안 540
 
6.0%
과 315
 
3.5%
교 279
 
3.1%
국 276
 
3.1%
Other values (114) 4018
44.5%
Common
ValueCountFrequency (%)
1264
99.8%
2 2
 
0.2%
1 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9039
87.7%
ASCII 1267
 
12.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1264
99.8%
2 2
 
0.2%
1 1
 
0.1%
Hangul
ValueCountFrequency (%)
천 639
 
7.1%
인 638
 
7.1%
시 620
 
6.9%
광 589
 
6.5%
역 584
 
6.5%
전 541
 
6.0%
안 540
 
6.0%
과 315
 
3.5%
교 279
 
3.1%
국 276
 
3.1%
Other values (114) 4018
44.5%

내진설계
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
적용
260 
미적용
245 

Length

Max length3
Median length2
Mean length2.4851485
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row적용
2nd row적용
3rd row미적용
4th row적용
5th row미적용

Common Values

ValueCountFrequency (%)
적용 260
51.5%
미적용 245
48.5%

Length

2024-01-28T17:51:03.953570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T17:51:04.045822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
적용 260
51.5%
미적용 245
48.5%

Interactions

2024-01-28T17:50:59.157809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:50:58.283847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:50:58.573027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:50:58.847634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:50:59.237920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:50:58.360350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:50:58.640613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:50:58.923156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:50:59.309241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:50:58.424093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:50:58.703753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:50:58.991571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:50:59.389452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:50:58.494442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:50:58.782094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:50:59.073619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T17:51:04.113354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설구분위도경도수용가능면적(제곱미터)수용가능인원(명)내진설계
시설구분1.0000.6240.6760.2980.1140.739
위도0.6241.0000.8160.0000.0000.478
경도0.6760.8161.0000.0000.0000.631
수용가능면적(제곱미터)0.2980.0000.0001.0000.9630.097
수용가능인원(명)0.1140.0000.0000.9631.0000.000
내진설계0.7390.4780.6310.0970.0001.000
2024-01-28T17:51:04.214615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
내진설계시설구분
내진설계1.0000.564
시설구분0.5641.000
2024-01-28T17:51:04.291992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도수용가능면적(제곱미터)수용가능인원(명)시설구분내진설계
위도1.000-0.302-0.107-0.1120.3580.365
경도-0.3021.0000.3800.3430.4590.458
수용가능면적(제곱미터)-0.1070.3801.0000.9780.1030.072
수용가능인원(명)-0.1120.3430.9781.0000.0610.000
시설구분0.3580.4590.1030.0611.0000.564
내진설계0.3650.4580.0720.0000.5641.000

Missing values

2024-01-28T17:50:59.499978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T17:50:59.626648image/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

지역 명시설구분시설명상세시설명상세주소위도경도수용가능면적(제곱미터)수용가능인원(명)담당부서내진설계
0인천광역시 중구 항동7가관공서연안동 행정복지센터회의실인천광역시 중구 축항대로86번길 44(항동7가)37.454935126.601223538.050인천광역시 중구 도시재생국 안전관리과적용
1인천광역시 중구 항동7가학교연안초등학교체육관인천광역시 중구 연안부두로33번길 53(항동7가)37.453502126.607971672.0204인천광역시 중구 도시재생국 안전관리과적용
2인천광역시 중구 신생동관공서신포동 행정복지센터회의실인천광역시 중구 제물량로 168(신생동)37.470382126.624992208.063인천광역시 중구 도시재생국 안전관리과미적용
3인천광역시 중구 관동1가관공서중구제1청상황실 및 회의실인천광역시 중구 신포로27번길 80(관동1가)37.473528126.621748422.0127인천광역시 중구 도시재생국 안전관리과적용
4인천광역시 중구 답동학교송도중학교급식소인천광역시 중구 제물량로 123(답동)37.468552126.6292491080.0327인천광역시 중구 도시재생국 안전관리과미적용
5인천광역시 중구 답동학교신흥초등학교체육관인천광역시 중구 제물량로 134(답동)37.470258126.6283642545.0771인천광역시 중구 도시재생국 안전관리과미적용
6인천광역시 중구 송학동2가학교인성여중학교강당인천광역시 중구 홍예문로 39(송학동2가)37.473778126.624543325.098인천광역시 중구 도시재생국 안전관리과미적용
7인천광역시 중구 신흥동2가관공서신흥동 행정복지센터회의실인천광역시 중구 서해대로464번길 1-2 (신흥동2가)37.46741126.63584799.029인천광역시 중구 도시재생국 안전관리과미적용
8인천광역시 중구 신흥동3가학교신광초등학교급식소인천광역시 중구 인중로63번길 9(신흥동3가)37.463908126.635856726.0220인천광역시 중구 도시재생국 안전관리과적용
9인천광역시 중구 신흥동3가학교신선초등학교본관인천광역시 중구 축항대로291번길 33(신흥동3가)37.451202126.627798132.040인천광역시 중구 도시재생국 안전관리과미적용
지역 명시설구분시설명상세시설명상세주소위도경도수용가능면적(제곱미터)수용가능인원(명)담당부서내진설계
495인천광역시 옹진군 자월면 이작리마을회관이작1리마을회관마을회관인천광역시 옹진군 자월면 대이작로70번길 3-837.176417126.253383171.6766인천광역시 옹진군 행정복지국 재난안전과미적용
496인천광역시 옹진군 자월면 자월리마을회관자월1리 다목적회관마을회관인천광역시 옹진군 자월면 자월서로186번길 2637.254601126.304548183.9670인천광역시 옹진군 행정복지국 재난안전과미적용
497인천광역시 옹진군 자월면 자월리마을회관자월리 복지회관마을회관인천광역시 옹진군 자월면 자월서로 164(자월면사무소)37.254283126.307414528.0203인천광역시 옹진군 행정복지국 재난안전과미적용
498인천광역시 옹진군 연평면 연평리기타시설1호 대피호대피시설인천광역시 옹진군 연평면 연평로137번길 77-1137.662854125.703354666.0256인천광역시 옹진군 행정안전과적용
499인천광역시 옹진군 연평면 연평리기타시설2호 대피호대피시설인천광역시 옹진군 연평면 연평로165번길 8-137.661871125.705843277.0106인천광역시 옹진군 행정안전과적용
500인천광역시 옹진군 연평면 연평리기타시설3호 대피호대피시설인천광역시 옹진군 연평면 연평중앙로6번길 437.663219125.70721170.065인천광역시 옹진군 행정안전과적용
501인천광역시 옹진군 연평면 연평리기타시설5호 대피호대피시설인천광역시 옹진군 연평면 연평로 314-737.674267125.71501996.9237인천광역시 옹진군 행정안전과적용
502인천광역시 옹진군 연평면 연평리기타시설6호 대피호대피시설인천광역시 옹진군 연평면 소연평로19번길 2837.610226125.711899232.089인천광역시 옹진군 행정안전과적용
503인천광역시 옹진군 연평면 연평리기타시설7호 대피호대피시설인천광역시 옹진군 연평면 연평중앙로24번길 3(연평면사무소)37.664949125.705045337.0129인천광역시 옹진군 행정복지국 재난안전과적용
504인천광역시 옹진군 연평면 연평리기타시설연평4호 대피호대피시설인천광역시 옹진군 연평면 연평로 19637.663117125.708286170.065인천광역시 옹진군 행정안전과적용