Overview

Dataset statistics

Number of variables7
Number of observations82
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.8 KiB
Average record size in memory59.6 B

Variable types

Categorical3
Text2
Numeric2

Dataset

Description인천광역시 서구 이재민 임시주거시설 지정 현황에 대한 데이터로 시설구분, 시설명, 상세주소, 내진설계 등의 정보가 포함되어 있습니다.
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15090837&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
수용가능면적(제곱미터) is highly overall correlated with 수용가능인원(명) and 2 other fieldsHigh correlation
수용가능인원(명) is highly overall correlated with 수용가능면적(제곱미터) and 2 other fieldsHigh correlation
시설구분 is highly overall correlated with 수용가능면적(제곱미터) and 2 other fieldsHigh correlation
내진설계 is highly overall correlated with 수용가능면적(제곱미터) and 2 other fieldsHigh correlation
시설명 has unique valuesUnique
상세주소 has unique valuesUnique

Reproduction

Analysis started2024-03-18 04:49:47.738692
Analysis finished2024-03-18 04:49:48.566743
Duration0.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size788.0 B
학교
55 
경로당
26 
연수,숙박
 
1

Length

Max length5
Median length2
Mean length2.3536585
Min length2

Unique

Unique1 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
학교 55
67.1%
경로당 26
31.7%
연수,숙박 1
 
1.2%

Length

2024-03-18T13:49:48.636214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:49:48.723525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
학교 55
67.1%
경로당 26
31.7%
연수,숙박 1
 
1.2%

시설명
Text

UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size788.0 B
2024-03-18T13:49:48.920146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length6.0853659
Min length5

Characters and Unicode

Total characters499
Distinct characters83
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

Unique82 ?
Unique (%)100.0%

Sample

1st row간재울중학교
2nd row간재울초등학교
3rd row검암초등학교
4th row경서초등학교
5th row백석고등학교
ValueCountFrequency (%)
간재울중학교 1
 
1.2%
완정초등학교 1
 
1.2%
연희동분회경로당 1
 
1.2%
고현경로당 1
 
1.2%
시천경로당 1
 
1.2%
공촌경로당 1
 
1.2%
검암경로당 1
 
1.2%
인재개발원 1
 
1.2%
왕길초등학교 1
 
1.2%
단봉초등학교 1
 
1.2%
Other values (74) 74
88.1%
2024-03-18T13:49:49.243358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 55
 
11.0%
교 55
 
11.0%
등 39
 
7.8%
초 33
 
6.6%
당 27
 
5.4%
경 25
 
5.0%
로 24
 
4.8%
중 16
 
3.2%
가 14
 
2.8%
동 13
 
2.6%
Other values (73) 198
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 488
97.8%
Decimal Number 9
 
1.8%
Space Separator 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 55
 
11.3%
교 55
 
11.3%
등 39
 
8.0%
초 33
 
6.8%
당 27
 
5.5%
경 25
 
5.1%
로 24
 
4.9%
중 16
 
3.3%
가 14
 
2.9%
동 13
 
2.7%
Other values (68) 187
38.3%
Decimal Number
ValueCountFrequency (%)
1 3
33.3%
3 3
33.3%
2 2
22.2%
4 1
 
11.1%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 488
97.8%
Common 11
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 55
 
11.3%
교 55
 
11.3%
등 39
 
8.0%
초 33
 
6.8%
당 27
 
5.5%
경 25
 
5.1%
로 24
 
4.9%
중 16
 
3.3%
가 14
 
2.9%
동 13
 
2.7%
Other values (68) 187
38.3%
Common
ValueCountFrequency (%)
1 3
27.3%
3 3
27.3%
2
18.2%
2 2
18.2%
4 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 488
97.8%
ASCII 11
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 55
 
11.3%
교 55
 
11.3%
등 39
 
8.0%
초 33
 
6.8%
당 27
 
5.5%
경 25
 
5.1%
로 24
 
4.9%
중 16
 
3.3%
가 14
 
2.9%
동 13
 
2.7%
Other values (68) 187
38.3%
ASCII
ValueCountFrequency (%)
1 3
27.3%
3 3
27.3%
2
18.2%
2 2
18.2%
4 1
 
9.1%

상세주소
Text

UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size788.0 B
2024-03-18T13:49:49.474299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length30
Mean length24.963415
Min length21

Characters and Unicode

Total characters2047
Distinct characters112
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

Unique82 ?
Unique (%)100.0%

Sample

1st row인천광역시 서구 승학로512번길 34 (검암동)
2nd row인천광역시 서구 승학로 433 (검암동)
3rd row인천광역시 서구 승학로599번길 45 (검암동)
4th row인천광역시 서구 경서로31번길 31 (경서동)
5th row인천광역시 서구 서곶로 701 (백석동)
ValueCountFrequency (%)
인천광역시 82
19.9%
서구 82
19.9%
석남동 14
 
3.4%
청라동 12
 
2.9%
가좌동 11
 
2.7%
마전동 6
 
1.5%
검암동 6
 
1.5%
신현동 5
 
1.2%
23 4
 
1.0%
22 3
 
0.7%
Other values (143) 187
45.4%
2024-03-18T13:49:49.790686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
330
 
16.1%
서 91
 
4.4%
로 85
 
4.2%
천 83
 
4.1%
시 83
 
4.1%
인 82
 
4.0%
동 82
 
4.0%
( 82
 
4.0%
) 82
 
4.0%
구 82
 
4.0%
Other values (102) 965
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1220
59.6%
Space Separator 330
 
16.1%
Decimal Number 318
 
15.5%
Open Punctuation 82
 
4.0%
Close Punctuation 82
 
4.0%
Dash Punctuation 13
 
0.6%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 91
 
7.5%
로 85
 
7.0%
천 83
 
6.8%
시 83
 
6.8%
인 82
 
6.7%
동 82
 
6.7%
구 82
 
6.7%
광 82
 
6.7%
역 82
 
6.7%
길 52
 
4.3%
Other values (87) 416
34.1%
Decimal Number
ValueCountFrequency (%)
1 71
22.3%
2 46
14.5%
3 40
12.6%
4 32
10.1%
0 30
9.4%
5 23
 
7.2%
8 21
 
6.6%
6 19
 
6.0%
7 19
 
6.0%
9 17
 
5.3%
Space Separator
ValueCountFrequency (%)
330
100.0%
Open Punctuation
ValueCountFrequency (%)
( 82
100.0%
Close Punctuation
ValueCountFrequency (%)
) 82
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1220
59.6%
Common 827
40.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 91
 
7.5%
로 85
 
7.0%
천 83
 
6.8%
시 83
 
6.8%
인 82
 
6.7%
동 82
 
6.7%
구 82
 
6.7%
광 82
 
6.7%
역 82
 
6.7%
길 52
 
4.3%
Other values (87) 416
34.1%
Common
ValueCountFrequency (%)
330
39.9%
( 82
 
9.9%
) 82
 
9.9%
1 71
 
8.6%
2 46
 
5.6%
3 40
 
4.8%
4 32
 
3.9%
0 30
 
3.6%
5 23
 
2.8%
8 21
 
2.5%
Other values (5) 70
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1220
59.6%
ASCII 827
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
330
39.9%
( 82
 
9.9%
) 82
 
9.9%
1 71
 
8.6%
2 46
 
5.6%
3 40
 
4.8%
4 32
 
3.9%
0 30
 
3.6%
5 23
 
2.8%
8 21
 
2.5%
Other values (5) 70
 
8.5%
Hangul
ValueCountFrequency (%)
서 91
 
7.5%
로 85
 
7.0%
천 83
 
6.8%
시 83
 
6.8%
인 82
 
6.7%
동 82
 
6.7%
구 82
 
6.7%
광 82
 
6.7%
역 82
 
6.7%
길 52
 
4.3%
Other values (87) 416
34.1%

내진설계
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
적용
43 
미적용
39 

Length

Max length3
Median length2
Mean length2.4756098
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
적용 43
52.4%
미적용 39
47.6%

Length

2024-03-18T13:49:49.904420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:49:50.269138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
적용 43
52.4%
미적용 39
47.6%

수용가능면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct73
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean543.29268
Minimum58
Maximum3039
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-03-18T13:49:50.378075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum58
5-th percentile69.3
Q1150
median500
Q3801.75
95-th percentile1069.6
Maximum3039
Range2981
Interquartile range (IQR)651.75

Descriptive statistics

Standard deviation438.08423
Coefficient of variation (CV)0.80635032
Kurtosis11.763664
Mean543.29268
Median Absolute Deviation (MAD)338.5
Skewness2.3613883
Sum44550
Variance191917.79
MonotonicityNot monotonic
2024-03-18T13:49:50.491907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
486 6
 
7.3%
844 2
 
2.4%
91 2
 
2.4%
150 2
 
2.4%
494 2
 
2.4%
68 1
 
1.2%
156 1
 
1.2%
1336 1
 
1.2%
405 1
 
1.2%
823 1
 
1.2%
Other values (63) 63
76.8%
ValueCountFrequency (%)
58 1
1.2%
66 1
1.2%
67 1
1.2%
68 1
1.2%
69 1
1.2%
75 1
1.2%
79 1
1.2%
88 1
1.2%
90 1
1.2%
91 2
2.4%
ValueCountFrequency (%)
3039 1
1.2%
1447 1
1.2%
1336 1
1.2%
1108 1
1.2%
1074 1
1.2%
986 1
1.2%
949 1
1.2%
914 1
1.2%
911 1
1.2%
909 1
1.2%

수용가능인원(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct70
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean208.45122
Minimum22
Maximum1168
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-03-18T13:49:50.605785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile26.1
Q157
median192
Q3308
95-th percentile411.3
Maximum1168
Range1146
Interquartile range (IQR)251

Descriptive statistics

Standard deviation168.46608
Coefficient of variation (CV)0.80817985
Kurtosis11.753324
Mean208.45122
Median Absolute Deviation (MAD)130
Skewness2.3605191
Sum17093
Variance28380.819
MonotonicityNot monotonic
2024-03-18T13:49:50.721273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
186 6
 
7.3%
190 2
 
2.4%
26 2
 
2.4%
25 2
 
2.4%
324 2
 
2.4%
35 2
 
2.4%
341 2
 
2.4%
57 2
 
2.4%
221 1
 
1.2%
68 1
 
1.2%
Other values (60) 60
73.2%
ValueCountFrequency (%)
22 1
1.2%
25 2
2.4%
26 2
2.4%
28 1
1.2%
30 1
1.2%
33 1
1.2%
34 1
1.2%
35 2
2.4%
37 1
1.2%
38 1
1.2%
ValueCountFrequency (%)
1168 1
1.2%
556 1
1.2%
513 1
1.2%
426 1
1.2%
413 1
1.2%
379 1
1.2%
365 1
1.2%
351 1
1.2%
350 1
1.2%
349 1
1.2%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
2022-08-01
82 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-08-01
2nd row2022-08-01
3rd row2022-08-01
4th row2022-08-01
5th row2022-08-01

Common Values

ValueCountFrequency (%)
2022-08-01 82
100.0%

Length

2024-03-18T13:49:50.827031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:49:50.906623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-08-01 82
100.0%

Interactions

2024-03-18T13:49:48.184644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:49:48.010916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:49:48.282524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:49:48.106446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T13:49:50.960989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설구분시설명상세주소내진설계수용가능면적(제곱미터)수용가능인원(명)
시설구분1.0001.0001.0000.3930.9990.999
시설명1.0001.0001.0001.0001.0001.000
상세주소1.0001.0001.0001.0001.0001.000
내진설계0.3931.0001.0001.0000.8240.824
수용가능면적(제곱미터)0.9991.0001.0000.8241.0001.000
수용가능인원(명)0.9991.0001.0000.8241.0001.000
2024-03-18T13:49:51.043224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
내진설계시설구분
내진설계1.0000.616
시설구분0.6161.000
2024-03-18T13:49:51.109210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수용가능면적(제곱미터)수용가능인원(명)시설구분내진설계
수용가능면적(제곱미터)1.0001.0000.9400.612
수용가능인원(명)1.0001.0000.9400.612
시설구분0.9400.9401.0000.616
내진설계0.6120.6120.6161.000

Missing values

2024-03-18T13:49:48.394853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T13:49:48.519166image/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

시설구분시설명상세주소내진설계수용가능면적(제곱미터)수용가능인원(명)데이터기준일자
0학교간재울중학교인천광역시 서구 승학로512번길 34 (검암동)적용4941902022-08-01
1학교간재울초등학교인천광역시 서구 승학로 433 (검암동)적용4861862022-08-01
2학교검암초등학교인천광역시 서구 승학로599번길 45 (검암동)미적용4861862022-08-01
3학교경서초등학교인천광역시 서구 경서로31번길 31 (경서동)적용6302422022-08-01
4학교백석고등학교인천광역시 서구 서곶로 701 (백석동)미적용6732582022-08-01
5학교은지초등학교인천광역시 서구 승학로572번길 22 (검암동)적용5181992022-08-01
6학교공촌초등학교인천광역시 서구 심곡로188번길 21 (공촌동)적용7002692022-08-01
7학교서곶중학교인천광역시 서구 대평로56번길 22 (연희동)미적용8443242022-08-01
8학교서곶초등학교인천광역시 서구 대평로56번길 9 (연희동)적용7562902022-08-01
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