Overview

Dataset statistics

Number of variables7
Number of observations30
Missing cells29
Missing cells (%)13.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory62.4 B

Variable types

Categorical2
Text3
Numeric2

Dataset

Description대전광역시 유성구 관내에 있는 지진옥외대피장소 지정현황으로 시도명, 시군구명, 행정동, 시설명, 소재지도로명주소, 수용인원, 면적 등의 데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15119297/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
수용인원 is highly overall correlated with 면적(m2)High correlation
면적(m2) is highly overall correlated with 수용인원High correlation
시군구명 has 29 (96.7%) missing valuesMissing
시설명 has unique valuesUnique
소재지도로명주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:25:28.368646
Analysis finished2023-12-12 06:25:29.079813
Duration0.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
대전광역시
30 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대전광역시 30
100.0%

Length

2023-12-12T15:25:29.127303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:25:29.200236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대전광역시 30
100.0%

시군구명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing29
Missing (%)96.7%
Memory size372.0 B
2023-12-12T15:25:29.267782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row유성구
ValueCountFrequency (%)
유성구 1
100.0%
2023-12-12T15:25:29.457296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
유 1
33.3%
성 1
33.3%
구 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
유 1
33.3%
성 1
33.3%
구 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
유 1
33.3%
성 1
33.3%
구 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
유 1
33.3%
성 1
33.3%
구 1
33.3%

행정동
Categorical

Distinct11
Distinct (%)36.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
진잠동
5 
원신흥동
3 
온천2동
3 
노은1동
3 
노은3동
3 
Other values (6)
13 

Length

Max length4
Median length4
Mean length3.5333333
Min length3

Unique

Unique1 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
진잠동 5
16.7%
원신흥동 3
10.0%
온천2동 3
10.0%
노은1동 3
10.0%
노은3동 3
10.0%
노은2동 3
10.0%
구즉동 3
10.0%
신성동 2
 
6.7%
전민동 2
 
6.7%
관평동 2
 
6.7%

Length

2023-12-12T15:25:29.582936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
진잠동 5
16.7%
원신흥동 3
10.0%
온천2동 3
10.0%
노은1동 3
10.0%
노은3동 3
10.0%
노은2동 3
10.0%
구즉동 3
10.0%
신성동 2
 
6.7%
전민동 2
 
6.7%
관평동 2
 
6.7%

시설명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-12T15:25:29.837292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0666667
Min length6

Characters and Unicode

Total characters182
Distinct characters52
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row남선초등학교
2nd row진잠초등학교
3rd row대정초등학교
4th row학하초등학교
5th row계산초등학교
ValueCountFrequency (%)
남선초등학교 1
 
3.3%
진잠초등학교 1
 
3.3%
관평초등학교 1
 
3.3%
송강초등학교 1
 
3.3%
두리초등학교 1
 
3.3%
구즉초등학교 1
 
3.3%
문지초등학교 1
 
3.3%
전민초등학교 1
 
3.3%
대덕초등학교 1
 
3.3%
금성초등학교 1
 
3.3%
Other values (20) 20
66.7%
2023-12-12T15:25:30.252312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 31
17.0%
초 30
16.5%
등 30
16.5%
교 30
16.5%
지 3
 
1.6%
송 3
 
1.6%
대 3
 
1.6%
덕 2
 
1.1%
정 2
 
1.1%
하 2
 
1.1%
Other values (42) 46
25.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 182
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 31
17.0%
초 30
16.5%
등 30
16.5%
교 30
16.5%
지 3
 
1.6%
송 3
 
1.6%
대 3
 
1.6%
덕 2
 
1.1%
정 2
 
1.1%
하 2
 
1.1%
Other values (42) 46
25.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 182
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 31
17.0%
초 30
16.5%
등 30
16.5%
교 30
16.5%
지 3
 
1.6%
송 3
 
1.6%
대 3
 
1.6%
덕 2
 
1.1%
정 2
 
1.1%
하 2
 
1.1%
Other values (42) 46
25.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 182
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 31
17.0%
초 30
16.5%
등 30
16.5%
교 30
16.5%
지 3
 
1.6%
송 3
 
1.6%
대 3
 
1.6%
덕 2
 
1.1%
정 2
 
1.1%
하 2
 
1.1%
Other values (42) 46
25.3%

소재지도로명주소
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-12T15:25:30.532160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length19.166667
Min length16

Characters and Unicode

Total characters575
Distinct characters65
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row대전광역시 유성구 계백로93번길277-99
2nd row대전광역시 유성구 진잠로 59번길 53
3rd row대전광역시 유성구 대정로 28번길 55
4th row대전광역시 유성구 진잠옛로 165
5th row대전광역시 유성구 학사서로 74
ValueCountFrequency (%)
대전광역시 30
25.2%
유성구 30
25.2%
반석동로 2
 
1.7%
165 2
 
1.7%
37 2
 
1.7%
62 2
 
1.7%
102 1
 
0.8%
노은로410번길 1
 
0.8%
123-14 1
 
0.8%
송림로19번길 1
 
0.8%
Other values (47) 47
39.5%
2023-12-12T15:25:30.992974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
89
15.5%
대 35
 
6.1%
전 32
 
5.6%
성 31
 
5.4%
구 31
 
5.4%
광 30
 
5.2%
역 30
 
5.2%
시 30
 
5.2%
유 30
 
5.2%
로 29
 
5.0%
Other values (55) 208
36.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 376
65.4%
Decimal Number 106
 
18.4%
Space Separator 89
 
15.5%
Dash Punctuation 2
 
0.3%
Other Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 35
9.3%
전 32
 
8.5%
성 31
 
8.2%
구 31
 
8.2%
광 30
 
8.0%
역 30
 
8.0%
시 30
 
8.0%
유 30
 
8.0%
로 29
 
7.7%
길 15
 
4.0%
Other values (42) 83
22.1%
Decimal Number
ValueCountFrequency (%)
1 17
16.0%
2 17
16.0%
5 13
12.3%
3 13
12.3%
6 13
12.3%
4 10
9.4%
9 8
7.5%
7 7
6.6%
0 5
 
4.7%
8 3
 
2.8%
Space Separator
ValueCountFrequency (%)
89
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
? 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 376
65.4%
Common 199
34.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 35
9.3%
전 32
 
8.5%
성 31
 
8.2%
구 31
 
8.2%
광 30
 
8.0%
역 30
 
8.0%
시 30
 
8.0%
유 30
 
8.0%
로 29
 
7.7%
길 15
 
4.0%
Other values (42) 83
22.1%
Common
ValueCountFrequency (%)
89
44.7%
1 17
 
8.5%
2 17
 
8.5%
5 13
 
6.5%
3 13
 
6.5%
6 13
 
6.5%
4 10
 
5.0%
9 8
 
4.0%
7 7
 
3.5%
0 5
 
2.5%
Other values (3) 7
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 376
65.4%
ASCII 199
34.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
89
44.7%
1 17
 
8.5%
2 17
 
8.5%
5 13
 
6.5%
3 13
 
6.5%
6 13
 
6.5%
4 10
 
5.0%
9 8
 
4.0%
7 7
 
3.5%
0 5
 
2.5%
Other values (3) 7
 
3.5%
Hangul
ValueCountFrequency (%)
대 35
9.3%
전 32
 
8.5%
성 31
 
8.2%
구 31
 
8.2%
광 30
 
8.0%
역 30
 
8.0%
시 30
 
8.0%
유 30
 
8.0%
로 29
 
7.7%
길 15
 
4.0%
Other values (42) 83
22.1%

수용인원
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3788.3667
Minimum2381
Maximum7065
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T15:25:31.160748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2381
5-th percentile2532.5
Q13138.25
median3359.5
Q34308.75
95-th percentile6262.9
Maximum7065
Range4684
Interquartile range (IQR)1170.5

Descriptive statistics

Standard deviation1156.9855
Coefficient of variation (CV)0.30540482
Kurtosis2.4433381
Mean3788.3667
Median Absolute Deviation (MAD)633.5
Skewness1.4969991
Sum113651
Variance1338615.3
MonotonicityNot monotonic
2023-12-12T15:25:31.321581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
3294 2
 
6.7%
2653 1
 
3.3%
3023 1
 
3.3%
3138 1
 
3.3%
2615 1
 
3.3%
4678 1
 
3.3%
3980 1
 
3.3%
3139 1
 
3.3%
2969 1
 
3.3%
7000 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
2381 1
3.3%
2465 1
3.3%
2615 1
3.3%
2635 1
3.3%
2653 1
3.3%
2969 1
3.3%
3023 1
3.3%
3138 1
3.3%
3139 1
3.3%
3144 1
3.3%
ValueCountFrequency (%)
7065 1
3.3%
7000 1
3.3%
5362 1
3.3%
4710 1
3.3%
4678 1
3.3%
4616 1
3.3%
4589 1
3.3%
4402 1
3.3%
4029 1
3.3%
3997 1
3.3%

면적(m2)
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3125.7667
Minimum1965
Maximum5829
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T15:25:31.481870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1965
5-th percentile2089.8
Q12589.25
median2772
Q33555
95-th percentile5167.05
Maximum5829
Range3864
Interquartile range (IQR)965.75

Descriptive statistics

Standard deviation954.47013
Coefficient of variation (CV)0.30535553
Kurtosis2.4429605
Mean3125.7667
Median Absolute Deviation (MAD)522.5
Skewness1.4969517
Sum93773
Variance911013.22
MonotonicityNot monotonic
2023-12-12T15:25:31.652088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
2718 2
 
6.7%
2189 1
 
3.3%
2494 1
 
3.3%
2589 1
 
3.3%
2158 1
 
3.3%
3860 1
 
3.3%
3284 1
 
3.3%
2590 1
 
3.3%
2450 1
 
3.3%
5775 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
1965 1
3.3%
2034 1
3.3%
2158 1
3.3%
2174 1
3.3%
2189 1
3.3%
2450 1
3.3%
2494 1
3.3%
2589 1
3.3%
2590 1
3.3%
2594 1
3.3%
ValueCountFrequency (%)
5829 1
3.3%
5775 1
3.3%
4424 1
3.3%
3886 1
3.3%
3860 1
3.3%
3809 1
3.3%
3786 1
3.3%
3632 1
3.3%
3324 1
3.3%
3298 1
3.3%

Interactions

2023-12-12T15:25:28.746010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:28.604795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:28.812479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:28.672269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:25:31.778028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동시설명소재지도로명주소수용인원면적(m2)
행정동1.0001.0001.0000.0000.000
시설명1.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.000
수용인원0.0001.0001.0001.0001.000
면적(m2)0.0001.0001.0001.0001.000
2023-12-12T15:25:32.238875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수용인원면적(m2)행정동
수용인원1.0001.0000.000
면적(m2)1.0001.0000.000
행정동0.0000.0001.000

Missing values

2023-12-12T15:25:28.932294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:25:29.042780image/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

시도명시군구명행정동시설명소재지도로명주소수용인원면적(m2)
0대전광역시유성구진잠동남선초등학교대전광역시 유성구 계백로93번길277-9926532189
1대전광역시<NA>진잠동진잠초등학교대전광역시 유성구 진잠로 59번길 5330232494
2대전광역시<NA>진잠동대정초등학교대전광역시 유성구 대정로 28번길 5537393085
3대전광역시<NA>진잠동학하초등학교대전광역시 유성구 진잠옛로 16544023632
4대전광역시<NA>진잠동계산초등학교대전광역시 유성구 학사서로 7423811965
5대전광역시<NA>원신흥동원신흥초등학교대전광역시 유성구 원신흥로55번길 3733582771
6대전광역시<NA>원신흥동흥도초등학교대전광역시 유성구 원신흥남로?2032152653
7대전광역시<NA>원신흥동봉명초등학교대전광역시 유성구 계룡로132번길 6235552933
8대전광역시<NA>온천1동덕송초등학교대전광역시 유성구 현충원로 26524652034
9대전광역시<NA>온천2동유성초등학교대전광역시 유성구 장대로71번길 1253624424
시도명시군구명행정동시설명소재지도로명주소수용인원면적(m2)
20대전광역시<NA>노은3동외삼초등학교대전광역시 유성구 반석동로 6331442594
21대전광역시<NA>신성동금성초등학교대전광역시 유성구 신성로72번길 570005775
22대전광역시<NA>신성동대덕초등학교대전광역시 유성구 대덕대로556번길 10229692450
23대전광역시<NA>전민동전민초등학교대전광역시 유성구 엑스포로466번길 4232942718
24대전광역시<NA>전민동문지초등학교대전광역시 유성구 전민로 4131392590
25대전광역시<NA>구즉동구즉초등학교대전광역시 유성구 구룡달전로 3432942718
26대전광역시<NA>구즉동두리초등학교대전광역시 유성구 와룡로 3739803284
27대전광역시<NA>구즉동송강초등학교대전광역시 유성구 송강로42번길 646783860
28대전광역시<NA>관평동관평초등학교대전광역시 유성구 테크노4로 13226152158
29대전광역시<NA>관평동용산초등학교대전광역시 유성구 배울2로 10131382589