Overview

Dataset statistics

Number of variables7
Number of observations49
Missing cells3
Missing cells (%)0.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory60.7 B

Variable types

Numeric2
Text3
Categorical2

Dataset

Description석면안전관리법 제21조, 같은 법 시행령 제29조에 따른 대구광역시 서구 관내 건축물석면조사 대상 건축물(관공서, 다중이용시설 등)자료로 건축물명,주소,연면적 정보를 포함하고 있습니다.
URLhttps://www.data.go.kr/data/3068390/fileData.do

Alerts

연번 is highly overall correlated with 구분 and 1 other fieldsHigh correlation
구분 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
석면조사 기한 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
전화번호 has 3 (6.1%) missing valuesMissing
연번 has unique valuesUnique
연면적(제곱미터) has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:57:58.921701
Analysis finished2023-12-12 12:57:59.964829
Duration1.04 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25
Minimum1
Maximum49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T21:58:00.076771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.4
Q113
median25
Q337
95-th percentile46.6
Maximum49
Range48
Interquartile range (IQR)24

Descriptive statistics

Standard deviation14.28869
Coefficient of variation (CV)0.57154761
Kurtosis-1.2
Mean25
Median Absolute Deviation (MAD)12
Skewness0
Sum1225
Variance204.16667
MonotonicityStrictly increasing
2023-12-12T21:58:00.291153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
1 1
 
2.0%
38 1
 
2.0%
28 1
 
2.0%
29 1
 
2.0%
30 1
 
2.0%
31 1
 
2.0%
32 1
 
2.0%
33 1
 
2.0%
34 1
 
2.0%
35 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
10 1
2.0%
ValueCountFrequency (%)
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%
45 1
2.0%
44 1
2.0%
43 1
2.0%
42 1
2.0%
41 1
2.0%
40 1
2.0%

건축물명
Text

Distinct34
Distinct (%)69.4%
Missing0
Missing (%)0.0%
Memory size524.0 B
2023-12-12T21:58:00.523350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length10.346939
Min length5

Characters and Unicode

Total characters507
Distinct characters117
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)59.2%

Sample

1st row서대구우체국
2nd row비산1동 주민센터
3rd row평리3동 주민센터
4th row비산5동 주민센터
5th row서대구근로자복지회관
ValueCountFrequency (%)
대구공공시설관리공단 11
 
16.7%
달서천사업소 7
 
10.6%
한국섬유개발연구원 5
 
7.6%
북부사업소 4
 
6.1%
주민센터 3
 
4.5%
평상새마을금고 2
 
3.0%
ibk기업은행 2
 
3.0%
신애보육원 1
 
1.5%
예린어린이집 1
 
1.5%
가람어린이집 1
 
1.5%
Other values (29) 29
43.9%
2023-12-12T21:58:00.893280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
공 35
 
6.9%
구 23
 
4.5%
19
 
3.7%
대 18
 
3.6%
관 14
 
2.8%
업 14
 
2.8%
소 13
 
2.6%
서 13
 
2.6%
사 13
 
2.6%
시 13
 
2.6%
Other values (107) 332
65.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 467
92.1%
Space Separator 19
 
3.7%
Decimal Number 11
 
2.2%
Uppercase Letter 6
 
1.2%
Close Punctuation 2
 
0.4%
Open Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 35
 
7.5%
구 23
 
4.9%
대 18
 
3.9%
관 14
 
3.0%
업 14
 
3.0%
소 13
 
2.8%
서 13
 
2.8%
사 13
 
2.8%
시 13
 
2.8%
단 12
 
2.6%
Other values (95) 299
64.0%
Decimal Number
ValueCountFrequency (%)
1 3
27.3%
0 2
18.2%
3 2
18.2%
5 2
18.2%
4 1
 
9.1%
7 1
 
9.1%
Uppercase Letter
ValueCountFrequency (%)
K 2
33.3%
B 2
33.3%
I 2
33.3%
Space Separator
ValueCountFrequency (%)
19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 467
92.1%
Common 34
 
6.7%
Latin 6
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 35
 
7.5%
구 23
 
4.9%
대 18
 
3.9%
관 14
 
3.0%
업 14
 
3.0%
소 13
 
2.8%
서 13
 
2.8%
사 13
 
2.8%
시 13
 
2.8%
단 12
 
2.6%
Other values (95) 299
64.0%
Common
ValueCountFrequency (%)
19
55.9%
1 3
 
8.8%
0 2
 
5.9%
3 2
 
5.9%
5 2
 
5.9%
) 2
 
5.9%
( 2
 
5.9%
4 1
 
2.9%
7 1
 
2.9%
Latin
ValueCountFrequency (%)
K 2
33.3%
B 2
33.3%
I 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 467
92.1%
ASCII 40
 
7.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
공 35
 
7.5%
구 23
 
4.9%
대 18
 
3.9%
관 14
 
3.0%
업 14
 
3.0%
소 13
 
2.8%
서 13
 
2.8%
사 13
 
2.8%
시 13
 
2.8%
단 12
 
2.6%
Other values (95) 299
64.0%
ASCII
ValueCountFrequency (%)
19
47.5%
1 3
 
7.5%
0 2
 
5.0%
3 2
 
5.0%
5 2
 
5.0%
) 2
 
5.0%
K 2
 
5.0%
( 2
 
5.0%
B 2
 
5.0%
I 2
 
5.0%
Other values (2) 2
 
5.0%

전화번호
Text

MISSING 

Distinct32
Distinct (%)69.6%
Missing3
Missing (%)6.1%
Memory size524.0 B
2023-12-12T21:58:01.095527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.065217
Min length12

Characters and Unicode

Total characters555
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)60.9%

Sample

1st row053-560-5308
2nd row053-663-2225
3rd row053-663-2225
4th row053-663-2225
5th row053-562-5552
ValueCountFrequency (%)
053-605-8304 7
 
15.2%
053-560-6786 5
 
10.9%
053-605-8270 4
 
8.7%
053-663-2225 3
 
6.5%
053-552-3495 2
 
4.3%
053-573-0071 1
 
2.2%
053-320-4424 1
 
2.2%
053-558-3425 1
 
2.2%
053-353-8310 1
 
2.2%
053-567-0521 1
 
2.2%
Other values (20) 20
43.5%
2023-12-12T21:58:01.449315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 110
19.8%
0 100
18.0%
- 92
16.6%
3 80
14.4%
6 48
8.6%
2 33
 
5.9%
8 26
 
4.7%
4 20
 
3.6%
7 20
 
3.6%
1 14
 
2.5%
Other values (2) 12
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 460
82.9%
Dash Punctuation 92
 
16.6%
Space Separator 3
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 110
23.9%
0 100
21.7%
3 80
17.4%
6 48
10.4%
2 33
 
7.2%
8 26
 
5.7%
4 20
 
4.3%
7 20
 
4.3%
1 14
 
3.0%
9 9
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 92
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 555
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 110
19.8%
0 100
18.0%
- 92
16.6%
3 80
14.4%
6 48
8.6%
2 33
 
5.9%
8 26
 
4.7%
4 20
 
3.6%
7 20
 
3.6%
1 14
 
2.5%
Other values (2) 12
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 555
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 110
19.8%
0 100
18.0%
- 92
16.6%
3 80
14.4%
6 48
8.6%
2 33
 
5.9%
8 26
 
4.7%
4 20
 
3.6%
7 20
 
3.6%
1 14
 
2.5%
Other values (2) 12
 
2.2%

건축물 주소
Text

Distinct36
Distinct (%)73.5%
Missing0
Missing (%)0.0%
Memory size524.0 B
2023-12-12T21:58:01.707650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length26
Mean length23.387755
Min length15

Characters and Unicode

Total characters1146
Distinct characters53
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

Unique33 ?
Unique (%)67.3%

Sample

1st row대구광역시 서구 서대구로 97 (평리동)
2nd row대구광역시 서구 북비산로65길 18 (비산동)
3rd row대구광역시 서구 문화로 261 (평리동)
4th row대구광역시 서구 달서천로65길 (비산동)
5th row대구광역시 서구 국채보상로 124 (중리동)
ValueCountFrequency (%)
서구 49
20.2%
대구광역시 47
19.3%
비산동 21
 
8.6%
평리동 9
 
3.7%
내당동 8
 
3.3%
염색공단로 7
 
2.9%
130 7
 
2.9%
국채보상로 6
 
2.5%
중리동 6
 
2.5%
달서천로 6
 
2.5%
Other values (54) 77
31.7%
2023-12-12T21:58:02.149975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
194
16.9%
구 107
 
9.3%
서 68
 
5.9%
대 61
 
5.3%
동 49
 
4.3%
시 47
 
4.1%
역 47
 
4.1%
광 47
 
4.1%
로 47
 
4.1%
) 47
 
4.1%
Other values (43) 432
37.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 697
60.8%
Space Separator 194
 
16.9%
Decimal Number 153
 
13.4%
Close Punctuation 47
 
4.1%
Open Punctuation 47
 
4.1%
Dash Punctuation 7
 
0.6%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 107
15.4%
서 68
 
9.8%
대 61
 
8.8%
동 49
 
7.0%
시 47
 
6.7%
역 47
 
6.7%
광 47
 
6.7%
로 47
 
6.7%
산 27
 
3.9%
비 26
 
3.7%
Other values (28) 171
24.5%
Decimal Number
ValueCountFrequency (%)
1 36
23.5%
3 31
20.3%
6 18
11.8%
2 16
10.5%
5 13
 
8.5%
0 11
 
7.2%
7 11
 
7.2%
8 8
 
5.2%
9 5
 
3.3%
4 4
 
2.6%
Space Separator
ValueCountFrequency (%)
194
100.0%
Close Punctuation
ValueCountFrequency (%)
) 47
100.0%
Open Punctuation
ValueCountFrequency (%)
( 47
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 697
60.8%
Common 449
39.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 107
15.4%
서 68
 
9.8%
대 61
 
8.8%
동 49
 
7.0%
시 47
 
6.7%
역 47
 
6.7%
광 47
 
6.7%
로 47
 
6.7%
산 27
 
3.9%
비 26
 
3.7%
Other values (28) 171
24.5%
Common
ValueCountFrequency (%)
194
43.2%
) 47
 
10.5%
( 47
 
10.5%
1 36
 
8.0%
3 31
 
6.9%
6 18
 
4.0%
2 16
 
3.6%
5 13
 
2.9%
0 11
 
2.4%
7 11
 
2.4%
Other values (5) 25
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 697
60.8%
ASCII 449
39.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
194
43.2%
) 47
 
10.5%
( 47
 
10.5%
1 36
 
8.0%
3 31
 
6.9%
6 18
 
4.0%
2 16
 
3.6%
5 13
 
2.9%
0 11
 
2.4%
7 11
 
2.4%
Other values (5) 25
 
5.6%
Hangul
ValueCountFrequency (%)
구 107
15.4%
서 68
 
9.8%
대 61
 
8.8%
동 49
 
7.0%
시 47
 
6.7%
역 47
 
6.7%
광 47
 
6.7%
로 47
 
6.7%
산 27
 
3.9%
비 26
 
3.7%
Other values (28) 171
24.5%

구분
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)18.4%
Missing0
Missing (%)0.0%
Memory size524.0 B
지방공사.공단
13 
공공기관
12 
특수법인
7 
행정기관
6 
어린이집
5 
Other values (4)
6 

Length

Max length13
Median length4
Mean length5.6734694
Min length4

Unique

Unique3 ?
Unique (%)6.1%

Sample

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

Common Values

ValueCountFrequency (%)
지방공사.공단 13
26.5%
공공기관 12
24.5%
특수법인 7
14.3%
행정기관 6
12.2%
어린이집 5
 
10.2%
다중이용시설(의료기관) 3
 
6.1%
다중이용시설(지하도상가) 1
 
2.0%
다중이용시설(대규모점포) 1
 
2.0%
어린이시설 1
 
2.0%

Length

2023-12-12T21:58:02.329412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:58:02.453774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방공사.공단 13
26.5%
공공기관 12
24.5%
특수법인 7
14.3%
행정기관 6
12.2%
어린이집 5
 
10.2%
다중이용시설(의료기관 3
 
6.1%
다중이용시설(지하도상가 1
 
2.0%
다중이용시설(대규모점포 1
 
2.0%
어린이시설 1
 
2.0%

연면적(제곱미터)
Real number (ℝ)

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2572.3265
Minimum103
Maximum8916
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T21:58:02.623649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum103
5-th percentile152.8
Q1838
median2354
Q33265
95-th percentile6389.8
Maximum8916
Range8813
Interquartile range (IQR)2427

Descriptive statistics

Standard deviation2107.9011
Coefficient of variation (CV)0.81945316
Kurtosis1.6867743
Mean2572.3265
Median Absolute Deviation (MAD)1491
Skewness1.2816218
Sum126044
Variance4443247
MonotonicityNot monotonic
2023-12-12T21:58:02.775746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
3265 1
 
2.0%
8916 1
 
2.0%
2626 1
 
2.0%
4826 1
 
2.0%
1433 1
 
2.0%
659 1
 
2.0%
1890 1
 
2.0%
863 1
 
2.0%
838 1
 
2.0%
509 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
103 1
2.0%
143 1
2.0%
148 1
2.0%
160 1
2.0%
479 1
2.0%
508 1
2.0%
509 1
2.0%
659 1
2.0%
742 1
2.0%
752 1
2.0%
ValueCountFrequency (%)
8916 1
2.0%
8869 1
2.0%
6395 1
2.0%
6382 1
2.0%
5479 1
2.0%
5081 1
2.0%
4860 1
2.0%
4826 1
2.0%
4137 1
2.0%
4122 1
2.0%

석면조사 기한
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size524.0 B
1차
39 
2차
5 
<NA>
5 

Length

Max length4
Median length2
Mean length2.2040816
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1차
2nd row1차
3rd row1차
4th row1차
5th row1차

Common Values

ValueCountFrequency (%)
1차 39
79.6%
2차 5
 
10.2%
<NA> 5
 
10.2%

Length

2023-12-12T21:58:02.942004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:58:03.075206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1차 39
79.6%
2차 5
 
10.2%
na 5
 
10.2%

Interactions

2023-12-12T21:57:59.503779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:57:59.279523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:57:59.599667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:57:59.420455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:58:03.450616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번건축물명전화번호건축물 주소구분연면적(제곱미터)석면조사 기한
연번1.0000.9640.9580.9560.8390.1780.578
건축물명0.9641.0000.9991.0001.0000.0001.000
전화번호0.9580.9991.0000.9981.0000.0001.000
건축물 주소0.9561.0000.9981.0001.0000.0001.000
구분0.8391.0001.0001.0001.0000.7760.869
연면적(제곱미터)0.1780.0000.0000.0000.7761.0000.231
석면조사 기한0.5781.0001.0001.0000.8690.2311.000
2023-12-12T21:58:03.577664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분석면조사 기한
구분1.0000.824
석면조사 기한0.8241.000
2023-12-12T21:58:03.665024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번연면적(제곱미터)구분석면조사 기한
연번1.000-0.2220.5760.528
연면적(제곱미터)-0.2221.0000.3470.201
구분0.5760.3471.0000.824
석면조사 기한0.5280.2010.8241.000

Missing values

2023-12-12T21:57:59.730709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:57:59.890605image/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

연번건축물명전화번호건축물 주소구분연면적(제곱미터)석면조사 기한
01서대구우체국053-560-5308대구광역시 서구 서대구로 97 (평리동)행정기관32651차
12비산1동 주민센터053-663-2225대구광역시 서구 북비산로65길 18 (비산동)행정기관9551차
23평리3동 주민센터053-663-2225대구광역시 서구 문화로 261 (평리동)행정기관7421차
34비산5동 주민센터053-663-2225대구광역시 서구 달서천로65길 (비산동)행정기관7911차
45서대구근로자복지회관053-562-5552대구광역시 서구 국채보상로 124 (중리동)공공기관39451차
56교통안전공단053-565-5000대구광역시 서구 문화로 27 (이현동)공공기관17471차
67내당변전소053-210-3784대구 서구 비산동 315-3공공기관28971차
78대구경북지역본부 자재센타053-350-2212대구 서구 이현동 243-3공공기관34761차
89대구광역시서부교육지원청053-233-0109대구광역시 서구 서대구로3길 5 (내당동)행정기관25151차
910한국전력공사053-550-2216대구광역시 서구 달서로 85 (비산동)공공기관63821차
연번건축물명전화번호건축물 주소구분연면적(제곱미터)석면조사 기한
3940웰니스1004병원053-570-1004대구광역시 서구 달구벌대로 1889 (내당동)다중이용시설(의료기관)41372차
4041열린요양병원053-562-2500대구광역시 서구 북비산로 239 (평리동)다중이용시설(의료기관)28202차
4142신애보육원053-567-0521대구광역시 서구 북비산로33길 9-2 (평리동)어린이시설11091차
4243서구제일종합사회복지관053-353-8310대구광역시 서구 옥산로6길 9 (원대동3가)공공기관41221차
4344내당어린이집053-558-3425대구광역시 서구 달서로5길 11-10, (내당동)어린이집4792차
4445서부소방서053-320-4424대구광역시 서구 달서천로 186 (평리동)행정기관3244<NA>
4546가람어린이집053-563-9983대구광역시 서구 국채보상로75길 41 (비산동)어린이집103<NA>
4647예린어린이집053-567-6868대구광역시 서구 달서로36길 12 (비산동)어린이집148<NA>
4748나래어린이집053-354-4977대구광역시 서구 달서천로 386-1 (원대동1가)어린이집160<NA>
4849앙팡예능어린이집053-554-6533대구광역시 서구 북비산로72길 5 (비산동)어린이집143<NA>