Overview

Dataset statistics

Number of variables7
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory62.6 B

Variable types

Numeric3
Categorical2
Text2

Dataset

Description대구광역시 서구 비상대피시설 현황 데이터 입니다. 시설명, 시설 도로명 주소, 연면적, 수용인원, 시설등급 등의 데이터를 포함하고 있습니다.
Author대구광역시 서구
URLhttps://www.data.go.kr/data/15092933/fileData.do

Alerts

연번 is highly overall correlated with 동명High correlation
연면적(제곱미터) is highly overall correlated with 수용인원High correlation
수용인원 is highly overall correlated with 연면적(제곱미터)High correlation
동명 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
시설명 has unique valuesUnique

Reproduction

Analysis started2024-04-20 22:58:34.846241
Analysis finished2024-04-20 22:58:38.155274
Duration3.31 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.5
Minimum1
Maximum36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size452.0 B
2024-04-21T07:58:38.343379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.75
Q19.75
median18.5
Q327.25
95-th percentile34.25
Maximum36
Range35
Interquartile range (IQR)17.5

Descriptive statistics

Standard deviation10.535654
Coefficient of variation (CV)0.5694948
Kurtosis-1.2
Mean18.5
Median Absolute Deviation (MAD)9
Skewness0
Sum666
Variance111
MonotonicityStrictly increasing
2024-04-21T07:58:38.757816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
1 1
 
2.8%
20 1
 
2.8%
22 1
 
2.8%
23 1
 
2.8%
24 1
 
2.8%
25 1
 
2.8%
26 1
 
2.8%
27 1
 
2.8%
28 1
 
2.8%
29 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
1 1
2.8%
2 1
2.8%
3 1
2.8%
4 1
2.8%
5 1
2.8%
6 1
2.8%
7 1
2.8%
8 1
2.8%
9 1
2.8%
10 1
2.8%
ValueCountFrequency (%)
36 1
2.8%
35 1
2.8%
34 1
2.8%
33 1
2.8%
32 1
2.8%
31 1
2.8%
30 1
2.8%
29 1
2.8%
28 1
2.8%
27 1
2.8%

동명
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)47.2%
Missing0
Missing (%)0.0%
Memory size416.0 B
평리3동
6 
내당1동
5 
비산4동
3 
평리5동
3 
원대동
3 
Other values (12)
16 

Length

Max length6
Median length4
Mean length4.0833333
Min length3

Unique

Unique8 ?
Unique (%)22.2%

Sample

1st row내당1동
2nd row내당1동
3rd row내당1동
4th row내당1동
5th row내당1동

Common Values

ValueCountFrequency (%)
평리3동 6
16.7%
내당1동 5
13.9%
비산4동 3
8.3%
평리5동 3
8.3%
원대동 3
8.3%
평리4동 2
 
5.6%
상중이동 2
 
5.6%
내당2.3동 2
 
5.6%
비산5동 2
 
5.6%
비산2.3동 1
 
2.8%
Other values (7) 7
19.4%

Length

2024-04-21T07:58:39.192164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
평리3동 6
16.7%
내당1동 5
13.9%
비산4동 3
8.3%
평리5동 3
8.3%
원대동 3
8.3%
내당2.3동 2
 
5.6%
비산5동 2
 
5.6%
상중이동 2
 
5.6%
평리4동 2
 
5.6%
비산2.3동 1
 
2.8%
Other values (7) 7
19.4%

시설명
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size416.0 B
2024-04-21T07:58:39.982652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length22
Mean length16.25
Min length9

Characters and Unicode

Total characters585
Distinct characters143
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

Unique36 ?
Unique (%)100.0%

Sample

1st row내당역 대합실 지하1층
2nd rowe편한세상두류역 지하주차장 1~3층
3rd row홍실2차 아파트 지하주차장 1층
4th row황제맨션2 지하주차장 1층
5th row황제맨션1 지하주차장 1층
ValueCountFrequency (%)
지하주차장 18
 
16.1%
1층 14
 
12.5%
지하1층 13
 
11.6%
1,2층 4
 
3.6%
지하 4
 
3.6%
1~2층 3
 
2.7%
아파트 3
 
2.7%
서대구역 2
 
1.8%
서구청 2
 
1.8%
주차장 2
 
1.8%
Other values (47) 47
42.0%
2024-04-21T07:58:41.265758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
76
 
13.0%
지 43
 
7.4%
1 39
 
6.7%
층 37
 
6.3%
하 37
 
6.3%
차 23
 
3.9%
주 23
 
3.9%
장 22
 
3.8%
구 13
 
2.2%
서 12
 
2.1%
Other values (133) 260
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 436
74.5%
Space Separator 76
 
13.0%
Decimal Number 54
 
9.2%
Other Punctuation 7
 
1.2%
Uppercase Letter 7
 
1.2%
Math Symbol 4
 
0.7%
Lowercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 43
 
9.9%
층 37
 
8.5%
하 37
 
8.5%
차 23
 
5.3%
주 23
 
5.3%
장 22
 
5.0%
구 13
 
3.0%
서 12
 
2.8%
대 10
 
2.3%
리 8
 
1.8%
Other values (118) 208
47.7%
Uppercase Letter
ValueCountFrequency (%)
K 2
28.6%
T 1
14.3%
X 1
14.3%
I 1
14.3%
B 1
14.3%
M 1
14.3%
Decimal Number
ValueCountFrequency (%)
1 39
72.2%
2 11
 
20.4%
0 2
 
3.7%
4 1
 
1.9%
3 1
 
1.9%
Space Separator
ValueCountFrequency (%)
76
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 436
74.5%
Common 141
 
24.1%
Latin 8
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 43
 
9.9%
층 37
 
8.5%
하 37
 
8.5%
차 23
 
5.3%
주 23
 
5.3%
장 22
 
5.0%
구 13
 
3.0%
서 12
 
2.8%
대 10
 
2.3%
리 8
 
1.8%
Other values (118) 208
47.7%
Common
ValueCountFrequency (%)
76
53.9%
1 39
27.7%
2 11
 
7.8%
, 7
 
5.0%
~ 4
 
2.8%
0 2
 
1.4%
4 1
 
0.7%
3 1
 
0.7%
Latin
ValueCountFrequency (%)
K 2
25.0%
T 1
12.5%
X 1
12.5%
I 1
12.5%
B 1
12.5%
M 1
12.5%
e 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 436
74.5%
ASCII 149
 
25.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
76
51.0%
1 39
26.2%
2 11
 
7.4%
, 7
 
4.7%
~ 4
 
2.7%
K 2
 
1.3%
0 2
 
1.3%
T 1
 
0.7%
X 1
 
0.7%
I 1
 
0.7%
Other values (5) 5
 
3.4%
Hangul
ValueCountFrequency (%)
지 43
 
9.9%
층 37
 
8.5%
하 37
 
8.5%
차 23
 
5.3%
주 23
 
5.3%
장 22
 
5.0%
구 13
 
3.0%
서 12
 
2.8%
대 10
 
2.3%
리 8
 
1.8%
Other values (118) 208
47.7%

도로명주소
Text

Distinct33
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size416.0 B
2024-04-21T07:58:42.070920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length32
Mean length28.25
Min length20

Characters and Unicode

Total characters1017
Distinct characters114
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

Unique31 ?
Unique (%)86.1%

Sample

1st row대구광역시 서구 달구벌대로 지하 1827(내당동)
2nd row대구광역시 서구 달구벌대로361길 41 (내당동, e편한세상두류역)
3rd row대구광역시 서구 통학로39(내당동,보성2차홍실타운)
4th row대구광역시 서구 통학로 46(내당동,황제맨션)
5th row대구광역시 서구 통학로 46(내당동,황제맨션)
ValueCountFrequency (%)
서구 36
21.6%
대구광역시 33
19.8%
국채보상로 6
 
3.6%
달구벌대로 4
 
2.4%
257(평리동 3
 
1.8%
서구청 3
 
1.8%
대구 3
 
1.8%
서대구로 3
 
1.8%
고성로 2
 
1.2%
달서로 2
 
1.2%
Other values (68) 72
43.1%
2024-04-21T07:58:43.348165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
135
 
13.3%
구 91
 
8.9%
대 57
 
5.6%
서 55
 
5.4%
( 36
 
3.5%
역 36
 
3.5%
) 36
 
3.5%
로 36
 
3.5%
동 36
 
3.5%
광 33
 
3.2%
Other values (104) 466
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 667
65.6%
Space Separator 135
 
13.3%
Decimal Number 118
 
11.6%
Open Punctuation 36
 
3.5%
Close Punctuation 36
 
3.5%
Other Punctuation 24
 
2.4%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 91
 
13.6%
대 57
 
8.5%
서 55
 
8.2%
역 36
 
5.4%
로 36
 
5.4%
동 36
 
5.4%
광 33
 
4.9%
시 33
 
4.9%
리 22
 
3.3%
평 18
 
2.7%
Other values (89) 250
37.5%
Decimal Number
ValueCountFrequency (%)
3 18
15.3%
1 18
15.3%
2 15
12.7%
7 13
11.0%
4 13
11.0%
5 10
8.5%
6 10
8.5%
9 8
6.8%
8 7
 
5.9%
0 6
 
5.1%
Space Separator
ValueCountFrequency (%)
135
100.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%
Other Punctuation
ValueCountFrequency (%)
, 24
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 667
65.6%
Common 349
34.3%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 91
 
13.6%
대 57
 
8.5%
서 55
 
8.2%
역 36
 
5.4%
로 36
 
5.4%
동 36
 
5.4%
광 33
 
4.9%
시 33
 
4.9%
리 22
 
3.3%
평 18
 
2.7%
Other values (89) 250
37.5%
Common
ValueCountFrequency (%)
135
38.7%
( 36
 
10.3%
) 36
 
10.3%
, 24
 
6.9%
3 18
 
5.2%
1 18
 
5.2%
2 15
 
4.3%
7 13
 
3.7%
4 13
 
3.7%
5 10
 
2.9%
Other values (4) 31
 
8.9%
Latin
ValueCountFrequency (%)
e 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 667
65.6%
ASCII 350
34.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
135
38.6%
( 36
 
10.3%
) 36
 
10.3%
, 24
 
6.9%
3 18
 
5.1%
1 18
 
5.1%
2 15
 
4.3%
7 13
 
3.7%
4 13
 
3.7%
5 10
 
2.9%
Other values (5) 32
 
9.1%
Hangul
ValueCountFrequency (%)
구 91
 
13.6%
대 57
 
8.5%
서 55
 
8.2%
역 36
 
5.4%
로 36
 
5.4%
동 36
 
5.4%
광 33
 
4.9%
시 33
 
4.9%
리 22
 
3.3%
평 18
 
2.7%
Other values (89) 250
37.5%

연면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14582.278
Minimum198
Maximum87148
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size452.0 B
2024-04-21T07:58:43.578635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum198
5-th percentile265.75
Q1587.25
median1595.5
Q310837.25
95-th percentile67408.75
Maximum87148
Range86950
Interquartile range (IQR)10250

Descriptive statistics

Standard deviation24788.869
Coefficient of variation (CV)1.6999312
Kurtosis1.7871554
Mean14582.278
Median Absolute Deviation (MAD)1294
Skewness1.7414333
Sum524962
Variance6.1448803 × 108
MonotonicityNot monotonic
2024-04-21T07:58:43.796141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
1418 2
 
5.6%
6760 1
 
2.8%
65053 1
 
2.8%
198 1
 
2.8%
498 1
 
2.8%
457 1
 
2.8%
13616 1
 
2.8%
87148 1
 
2.8%
33375 1
 
2.8%
2873 1
 
2.8%
Other values (25) 25
69.4%
ValueCountFrequency (%)
198 1
2.8%
208 1
2.8%
285 1
2.8%
336 1
2.8%
354 1
2.8%
409 1
2.8%
457 1
2.8%
498 1
2.8%
564 1
2.8%
595 1
2.8%
ValueCountFrequency (%)
87148 1
2.8%
74476 1
2.8%
65053 1
2.8%
63000 1
2.8%
46404 1
2.8%
46193 1
2.8%
44677 1
2.8%
33375 1
2.8%
13616 1
2.8%
9911 1
2.8%

수용인원
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17674.972
Minimum240
Maximum105633
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size452.0 B
2024-04-21T07:58:44.013165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum240
5-th percentile321.75
Q1711.5
median1933.5
Q313135.75
95-th percentile81707.25
Maximum105633
Range105393
Interquartile range (IQR)12424.25

Descriptive statistics

Standard deviation30047.049
Coefficient of variation (CV)1.6999772
Kurtosis1.7871335
Mean17674.972
Median Absolute Deviation (MAD)1568.5
Skewness1.7414296
Sum636299
Variance9.0282517 × 108
MonotonicityNot monotonic
2024-04-21T07:58:44.240186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
1718 2
 
5.6%
8193 1
 
2.8%
78852 1
 
2.8%
240 1
 
2.8%
603 1
 
2.8%
553 1
 
2.8%
16504 1
 
2.8%
105633 1
 
2.8%
40454 1
 
2.8%
3482 1
 
2.8%
Other values (25) 25
69.4%
ValueCountFrequency (%)
240 1
2.8%
252 1
2.8%
345 1
2.8%
407 1
2.8%
429 1
2.8%
495 1
2.8%
553 1
2.8%
603 1
2.8%
683 1
2.8%
721 1
2.8%
ValueCountFrequency (%)
105633 1
2.8%
90273 1
2.8%
78852 1
2.8%
76363 1
2.8%
56247 1
2.8%
55991 1
2.8%
54153 1
2.8%
40454 1
2.8%
16504 1
2.8%
12013 1
2.8%

비고
Categorical

Distinct3
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size416.0 B
민간
25 
공공기관
6 
지자체
5 

Length

Max length4
Median length2
Mean length2.4722222
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공공기관
2nd row민간
3rd row민간
4th row민간
5th row민간

Common Values

ValueCountFrequency (%)
민간 25
69.4%
공공기관 6
 
16.7%
지자체 5
 
13.9%

Length

2024-04-21T07:58:44.474429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T07:58:44.669234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민간 25
69.4%
공공기관 6
 
16.7%
지자체 5
 
13.9%

Interactions

2024-04-21T07:58:36.815551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T07:58:35.373347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T07:58:36.103964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T07:58:37.064908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T07:58:35.624379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T07:58:36.354194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T07:58:37.298528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T07:58:35.862306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T07:58:36.579614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T07:58:44.798797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번동명시설명도로명주소연면적(제곱미터)수용인원비고
연번1.0000.9221.0000.8830.4790.4790.568
동명0.9221.0001.0001.0000.3170.3170.669
시설명1.0001.0001.0001.0001.0001.0001.000
도로명주소0.8831.0001.0001.0001.0001.0001.000
연면적(제곱미터)0.4790.3171.0001.0001.0001.0000.000
수용인원0.4790.3171.0001.0001.0001.0000.000
비고0.5680.6691.0001.0000.0000.0001.000
2024-04-21T07:58:44.975807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비고동명
비고1.0000.343
동명0.3431.000
2024-04-21T07:58:45.115592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번연면적(제곱미터)수용인원동명비고
연번1.0000.3160.3160.6170.490
연면적(제곱미터)0.3161.0001.0000.1230.000
수용인원0.3161.0001.0000.1230.000
동명0.6170.1230.1231.0000.343
비고0.4900.0000.0000.3431.000

Missing values

2024-04-21T07:58:37.631855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T07:58:38.012871image/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

연번동명시설명도로명주소연면적(제곱미터)수용인원비고
01내당1동내당역 대합실 지하1층대구광역시 서구 달구벌대로 지하 1827(내당동)67608193공공기관
12내당1동e편한세상두류역 지하주차장 1~3층대구광역시 서구 달구벌대로361길 41 (내당동, e편한세상두류역)4467754153민간
23내당1동홍실2차 아파트 지하주차장 1층대구광역시 서구 통학로39(내당동,보성2차홍실타운)16321978민간
34내당1동황제맨션2 지하주차장 1층대구광역시 서구 통학로 46(내당동,황제맨션)14181718민간
45내당1동황제맨션1 지하주차장 1층대구광역시 서구 통학로 46(내당동,황제맨션)14181718민간
56내당2.3동열린큰병원 지하주차장 1층대구광역시 서구 달구벌대로 1877(내당동,열린큰병원)564683민간
67내당2.3동웰니스1004 병원 지하주차장 1층대구광역시 서구 달구벌대로 1889(내당동)15841920민간
78내당4동M플라자 지하주차장 1,2층대구광역시 서구 달구벌대로 1691(내당동)31483815민간
89비산1동비봉초등학교 지하주차장 1층대구광역시 서구 달서로45길 30, 비봉초등학교(비산동)409495공공기관
910비산2.3동인동촌건강나눔센터 지하1층 주차장대구광역시 서구 북비산로75길6(비산동)354429지자체
연번동명시설명도로명주소연면적(제곱미터)수용인원비고
2627평리4동평리푸르지오 지하주차장 1~2층대구 서구 국채보상로50길 20(평리동, 평리푸르지오)87148105633민간
2728평리5동서대구역 서한이다음더퍼스트 지하주차장 1,2층대구 서구 국채보상로37길 38(평리동, 서대구역서한이다음더퍼스트)3337540454민간
2829평리5동서대구역 화성파크드림 지하주차장1,2층대구광역시 서구 서대구로29길 30 (평리동, 서대구역화성파크드림)6505378852민간
2930평리5동한국폴리텍대학 대구캠퍼스 산학협력관 지하1층대구광역시 서구 국채보상로43길 15(평리동, 한국폴리텍대학 대구캠퍼스)28733482공공기관
3031평리6동서대구역KTX영무예다음 지하주차장 1,2층대구광역시 서구 당산로 446 (평리동, 서대구영무예다음)6300076363민간
3132상중이동대구의료원 본관 지하1층, 라파엘웰빙센터 지하1층대구광역시 서구 평리로 157(중리동, 대구의료원)991112013공공기관
3233상중이동중리롯데캐슬 지하주차장 1~2층대구광역시 서구 국채보상로34길 12(중리동, 중리롯데캐슬)4640456247민간
3334원대동서대구센트럴자이 지하주차장 1,2층대구광역시 서구 고성로 33 (원대동3가, 서대구센트럴자이)7447690273민간
3435원대동서구제일종합사회복지관 지하1층대구광역시 서구 옥산로6길 9(원대동3가)12741544민간
3536원대동원대금류타운 아파트 지하주차장 1층대구광역시 서구 원대로13길 2(원대동2가, 원대금류타운)30083646민간