Overview

Dataset statistics

Number of variables11
Number of observations36
Missing cells26
Missing cells (%)6.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory94.7 B

Variable types

Text3
DateTime1
Numeric3
Categorical3
Boolean1

Dataset

Description수성구 관내 재해예방 및 환경관리에 도움을 줄 수 있는 빗물이용시설 현황에 대한 데이터로 시설명, 위치, 설치연월, 설치 비 등에 대한 데이터를 제공합니다.
Author대구광역시 수성구
URLhttps://www.data.go.kr/data/3075312/fileData.do

Alerts

설치비(백만원) is highly overall correlated with 집수면적(세제곱미터) and 3 other fieldsHigh correlation
집수면적(세제곱미터) is highly overall correlated with 설치비(백만원) and 3 other fieldsHigh correlation
저류조 용량(세제곱미터) is highly overall correlated with 설치비(백만원) and 3 other fieldsHigh correlation
여과 등 처리시설 유무 is highly overall correlated with 설치비(백만원) and 3 other fieldsHigh correlation
빗물활용 용도 is highly overall correlated with 여과 등 처리시설 유무High correlation
법적시설여부(대상_미대상) is highly overall correlated with 설치비(백만원) and 2 other fieldsHigh correlation
집수면 is highly imbalanced (81.7%)Imbalance
연간 사용량(세제곱미터_년) has 26 (72.2%) missing valuesMissing
위치(주소) has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:32:19.611011
Analysis finished2023-12-12 09:32:21.544745
Duration1.93 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

Distinct33
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-12T18:32:21.715605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length7.4166667
Min length2

Characters and Unicode

Total characters267
Distinct characters125
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)88.9%

Sample

1st row대구육상진흥센터
2nd row대구미술관
3rd row들안길초등학교
4th row노변중학교
5th row교보생명빌딩
ValueCountFrequency (%)
주택 4
 
9.8%
대구스포츠단훈련센터 1
 
2.4%
하늘빛유치원 1
 
2.4%
시지코오롱하늘채 1
 
2.4%
스카이뷰 1
 
2.4%
삼도더펜트하우스수성 1
 
2.4%
사회복지법인전원어린이집 1
 
2.4%
미소드림빌라 1
 
2.4%
사회복지법인해달별어린이집 1
 
2.4%
대구시장애인체육센터 1
 
2.4%
Other values (28) 28
68.3%
2023-12-12T18:32:22.071255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 13
 
4.9%
어 11
 
4.1%
린 8
 
3.0%
집 8
 
3.0%
구 7
 
2.6%
원 7
 
2.6%
수 6
 
2.2%
유 5
 
1.9%
치 5
 
1.9%
대 5
 
1.9%
Other values (115) 192
71.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 259
97.0%
Space Separator 5
 
1.9%
Close Punctuation 1
 
0.4%
Open Punctuation 1
 
0.4%
Other Symbol 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 13
 
5.0%
어 11
 
4.2%
린 8
 
3.1%
집 8
 
3.1%
구 7
 
2.7%
원 7
 
2.7%
수 6
 
2.3%
유 5
 
1.9%
치 5
 
1.9%
대 5
 
1.9%
Other values (111) 184
71.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 260
97.4%
Common 7
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 13
 
5.0%
어 11
 
4.2%
린 8
 
3.1%
집 8
 
3.1%
구 7
 
2.7%
원 7
 
2.7%
수 6
 
2.3%
유 5
 
1.9%
치 5
 
1.9%
대 5
 
1.9%
Other values (112) 185
71.2%
Common
ValueCountFrequency (%)
5
71.4%
) 1
 
14.3%
( 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 259
97.0%
ASCII 7
 
2.6%
None 1
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 13
 
5.0%
어 11
 
4.2%
린 8
 
3.1%
집 8
 
3.1%
구 7
 
2.7%
원 7
 
2.7%
수 6
 
2.3%
유 5
 
1.9%
치 5
 
1.9%
대 5
 
1.9%
Other values (111) 184
71.0%
ASCII
ValueCountFrequency (%)
5
71.4%
) 1
 
14.3%
( 1
 
14.3%
None
ValueCountFrequency (%)
㈜ 1
100.0%

위치(주소)
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-12T18:32:22.338607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length33
Mean length24.305556
Min length16

Characters and Unicode

Total characters875
Distinct characters87
Distinct categories6 ?
Distinct scripts2 ?
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 row대구광역시 수성구 미술관로 88(삼덕동)
2nd row대구광역시 수성구 미술관로 40(삼덕동)
3rd row대구광역시 수성구 들안로 16길 58(두산동)
4th row대구광역시 수성구 시지로 66(노변동)
5th row대구광역시 수성구 달구벌대로 2330(수성동2가)
ValueCountFrequency (%)
대구광역시 37
22.4%
수성구 35
21.2%
달구벌대로 4
 
2.4%
범어동 3
 
1.8%
유니버시아드로42길 3
 
1.8%
대흥동 3
 
1.8%
미술관로 2
 
1.2%
21 2
 
1.2%
125 1
 
0.6%
유니버시아드로68길 1
 
0.6%
Other values (74) 74
44.8%
2023-12-12T18:32:22.737590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
133
 
15.2%
구 80
 
9.1%
대 48
 
5.5%
시 43
 
4.9%
광 38
 
4.3%
역 38
 
4.3%
수 37
 
4.2%
성 36
 
4.1%
로 33
 
3.8%
1 30
 
3.4%
Other values (77) 359
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 550
62.9%
Decimal Number 141
 
16.1%
Space Separator 133
 
15.2%
Open Punctuation 21
 
2.4%
Close Punctuation 21
 
2.4%
Dash Punctuation 9
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 80
14.5%
대 48
 
8.7%
시 43
 
7.8%
광 38
 
6.9%
역 38
 
6.9%
수 37
 
6.7%
성 36
 
6.5%
로 33
 
6.0%
동 27
 
4.9%
길 22
 
4.0%
Other values (63) 148
26.9%
Decimal Number
ValueCountFrequency (%)
1 30
21.3%
2 26
18.4%
3 19
13.5%
6 18
12.8%
4 16
11.3%
5 12
 
8.5%
0 6
 
4.3%
8 6
 
4.3%
7 5
 
3.5%
9 3
 
2.1%
Space Separator
ValueCountFrequency (%)
133
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 550
62.9%
Common 325
37.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 80
14.5%
대 48
 
8.7%
시 43
 
7.8%
광 38
 
6.9%
역 38
 
6.9%
수 37
 
6.7%
성 36
 
6.5%
로 33
 
6.0%
동 27
 
4.9%
길 22
 
4.0%
Other values (63) 148
26.9%
Common
ValueCountFrequency (%)
133
40.9%
1 30
 
9.2%
2 26
 
8.0%
( 21
 
6.5%
) 21
 
6.5%
3 19
 
5.8%
6 18
 
5.5%
4 16
 
4.9%
5 12
 
3.7%
- 9
 
2.8%
Other values (4) 20
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 550
62.9%
ASCII 325
37.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
133
40.9%
1 30
 
9.2%
2 26
 
8.0%
( 21
 
6.5%
) 21
 
6.5%
3 19
 
5.8%
6 18
 
5.5%
4 16
 
4.9%
5 12
 
3.7%
- 9
 
2.8%
Other values (4) 20
 
6.2%
Hangul
ValueCountFrequency (%)
구 80
14.5%
대 48
 
8.7%
시 43
 
7.8%
광 38
 
6.9%
역 38
 
6.9%
수 37
 
6.7%
성 36
 
6.5%
로 33
 
6.0%
동 27
 
4.9%
길 22
 
4.0%
Other values (63) 148
26.9%

설치년월
Date

Distinct28
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
Minimum2010-03-19 00:00:00
Maximum2023-04-27 00:00:00
2023-12-12T18:32:22.878162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:32:23.000195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)

설치비(백만원)
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.065
Minimum1.74
Maximum319
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T18:32:23.112757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.74
5-th percentile2.775
Q13.3
median3.465
Q352.25
95-th percentile115.25
Maximum319
Range317.26
Interquartile range (IQR)48.95

Descriptive statistics

Standard deviation62.399834
Coefficient of variation (CV)1.8317873
Kurtosis12.72436
Mean34.065
Median Absolute Deviation (MAD)0.535
Skewness3.2801912
Sum1226.34
Variance3893.7393
MonotonicityNot monotonic
2023-12-12T18:32:23.228656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
3.3 10
27.8%
4.0 3
 
8.3%
3.0 2
 
5.6%
319.0 1
 
2.8%
66.0 1
 
2.8%
185.0 1
 
2.8%
3.46 1
 
2.8%
3.47 1
 
2.8%
3.36 1
 
2.8%
38.0 1
 
2.8%
Other values (14) 14
38.9%
ValueCountFrequency (%)
1.74 1
 
2.8%
2.7 1
 
2.8%
2.8 1
 
2.8%
3.0 2
 
5.6%
3.3 10
27.8%
3.36 1
 
2.8%
3.41 1
 
2.8%
3.46 1
 
2.8%
3.47 1
 
2.8%
4.0 3
 
8.3%
ValueCountFrequency (%)
319.0 1
2.8%
185.0 1
2.8%
92.0 1
2.8%
80.0 1
2.8%
72.0 1
2.8%
68.0 1
2.8%
66.0 1
2.8%
54.0 1
2.8%
53.0 1
2.8%
52.0 1
2.8%

집수면
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
지붕면
35 
기타
 
1

Length

Max length3
Median length3
Mean length2.9722222
Min length2

Unique

Unique1 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
지붕면 35
97.2%
기타 1
 
2.8%

Length

2023-12-12T18:32:23.396316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:32:23.511033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지붕면 35
97.2%
기타 1
 
2.8%

집수면적(세제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct34
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1315.4593
Minimum1.42
Maximum13049.14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T18:32:23.637372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.42
5-th percentile1.75
Q15.38
median25.4
Q31712.5375
95-th percentile5566.455
Maximum13049.14
Range13047.72
Interquartile range (IQR)1707.1575

Descriptive statistics

Standard deviation2690.2168
Coefficient of variation (CV)2.045078
Kurtosis10.768256
Mean1315.4593
Median Absolute Deviation (MAD)23.5925
Skewness3.0758786
Sum47356.535
Variance7237266.6
MonotonicityNot monotonic
2023-12-12T18:32:23.790997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
6.0 3
 
8.3%
3504.0 1
 
2.8%
30.8 1
 
2.8%
1143.88 1
 
2.8%
1661.05 1
 
2.8%
1867.0 1
 
2.8%
1.42 1
 
2.8%
1.6 1
 
2.8%
1.8 1
 
2.8%
2.46 1
 
2.8%
Other values (24) 24
66.7%
ValueCountFrequency (%)
1.42 1
2.8%
1.6 1
2.8%
1.8 1
2.8%
1.815 1
2.8%
2.46 1
2.8%
3.0 1
2.8%
3.9 1
2.8%
5.13 1
2.8%
5.2 1
2.8%
5.44 1
2.8%
ValueCountFrequency (%)
13049.14 1
2.8%
8384.82 1
2.8%
4627.0 1
2.8%
3504.0 1
2.8%
2946.0 1
2.8%
2902.0 1
2.8%
2890.71 1
2.8%
2726.0 1
2.8%
1867.0 1
2.8%
1661.05 1
2.8%

여과 등 처리시설 유무
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
여과시설
24 
스크린
4 
약품시설
 
2
초기우수배재
 
1
자동여과
 
1
Other values (4)
4 

Length

Max length16
Median length4
Mean length4.9166667
Min length3

Unique

Unique6 ?
Unique (%)16.7%

Sample

1st row초기우수배재
2nd row자동여과
3rd row스크린
4th row스크린
5th row스크린

Common Values

ValueCountFrequency (%)
여과시설 24
66.7%
스크린 4
 
11.1%
약품시설 2
 
5.6%
초기우수배재 1
 
2.8%
자동여과 1
 
2.8%
초기우수배제, 여과, 살균 1
 
2.8%
스크린, 여과시설 1
 
2.8%
초기우수배제, 여과시설 1
 
2.8%
초기우수배제 및 물리적처리방법 1
 
2.8%

Length

2023-12-12T18:32:23.976792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:32:24.168455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여과시설 26
61.9%
스크린 5
 
11.9%
초기우수배제 3
 
7.1%
약품시설 2
 
4.8%
초기우수배재 1
 
2.4%
자동여과 1
 
2.4%
여과 1
 
2.4%
살균 1
 
2.4%
및 1
 
2.4%
물리적처리방법 1
 
2.4%

저류조 용량(세제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)47.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean99.509444
Minimum1
Maximum715
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T18:32:24.325845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1.5
Q375
95-th percentile664.25
Maximum715
Range714
Interquartile range (IQR)74

Descriptive statistics

Standard deviation202.40755
Coefficient of variation (CV)2.0340537
Kurtosis4.244357
Mean99.509444
Median Absolute Deviation (MAD)0.5
Skewness2.3005971
Sum3582.34
Variance40968.817
MonotonicityNot monotonic
2023-12-12T18:32:24.591381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
1.0 15
41.7%
1.5 6
 
16.7%
451.0 1
 
2.8%
715.0 1
 
2.8%
144.54 1
 
2.8%
660.0 1
 
2.8%
106.3 1
 
2.8%
90.0 1
 
2.8%
70.0 1
 
2.8%
677.0 1
 
2.8%
Other values (7) 7
19.4%
ValueCountFrequency (%)
1.0 15
41.7%
1.5 6
 
16.7%
2.0 1
 
2.8%
2.5 1
 
2.8%
30.0 1
 
2.8%
40.0 1
 
2.8%
60.0 1
 
2.8%
70.0 1
 
2.8%
90.0 1
 
2.8%
106.3 1
 
2.8%
ValueCountFrequency (%)
715.0 1
2.8%
677.0 1
2.8%
660.0 1
2.8%
451.0 1
2.8%
270.0 1
2.8%
240.0 1
2.8%
144.54 1
2.8%
106.3 1
2.8%
90.0 1
2.8%
70.0 1
2.8%

연간 사용량(세제곱미터_년)
Text

MISSING 

Distinct9
Distinct (%)90.0%
Missing26
Missing (%)72.2%
Memory size420.0 B
2023-12-12T18:32:24.770779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.2
Min length1

Characters and Unicode

Total characters22
Distinct characters8
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

Unique8 ?
Unique (%)80.0%

Sample

1st row210
2nd row42
3rd row30
4th row100
5th row35
ValueCountFrequency (%)
30 2
22.2%
210 1
11.1%
42 1
11.1%
100 1
11.1%
35 1
11.1%
115 1
11.1%
3 1
11.1%
1.2 1
11.1%
2023-12-12T18:32:25.155187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5
22.7%
1 5
22.7%
3 4
18.2%
2 3
13.6%
5 2
 
9.1%
4 1
 
4.5%
. 1
 
4.5%
1
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20
90.9%
Other Punctuation 1
 
4.5%
Space Separator 1
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5
25.0%
1 5
25.0%
3 4
20.0%
2 3
15.0%
5 2
 
10.0%
4 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5
22.7%
1 5
22.7%
3 4
18.2%
2 3
13.6%
5 2
 
9.1%
4 1
 
4.5%
. 1
 
4.5%
1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5
22.7%
1 5
22.7%
3 4
18.2%
2 3
13.6%
5 2
 
9.1%
4 1
 
4.5%
. 1
 
4.5%
1
 
4.5%

빗물활용 용도
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size420.0 B
조경용수
24 
조경용
8 
농업용수
3 
조경 및 청소
 
1

Length

Max length7
Median length4
Mean length3.8611111
Min length3

Unique

Unique1 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
조경용수 24
66.7%
조경용 8
 
22.2%
농업용수 3
 
8.3%
조경 및 청소 1
 
2.8%

Length

2023-12-12T18:32:25.373258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:32:25.549444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
조경용수 24
63.2%
조경용 8
 
21.1%
농업용수 3
 
7.9%
조경 1
 
2.6%
및 1
 
2.6%
청소 1
 
2.6%

법적시설여부(대상_미대상)
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size168.0 B
False
31 
True
5 
ValueCountFrequency (%)
False 31
86.1%
True 5
 
13.9%
2023-12-12T18:32:25.696015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2023-12-12T18:32:20.717930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:32:20.102788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:32:20.431197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:32:20.807938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:32:20.197402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:32:20.533448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:32:20.893335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:32:20.320824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:32:20.619596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:32:25.798075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명위치(주소)설치년월설치비(백만원)집수면집수면적(세제곱미터)여과 등 처리시설 유무저류조 용량(세제곱미터)연간 사용량(세제곱미터_년)빗물활용 용도법적시설여부(대상_미대상)
시설명1.0001.0000.9441.0001.0001.0001.0001.0001.0001.0001.000
위치(주소)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
설치년월0.9441.0001.0000.9631.0000.9640.9700.9650.9430.7921.000
설치비(백만원)1.0001.0000.9631.0000.0000.8220.8890.6490.4080.0970.503
집수면1.0001.0001.0000.0001.0000.0000.0000.000NaN0.2030.000
집수면적(세제곱미터)1.0001.0000.9640.8220.0001.0000.8700.9410.0000.2320.904
여과 등 처리시설 유무1.0001.0000.9700.8890.0000.8701.0000.8580.8190.7890.068
저류조 용량(세제곱미터)1.0001.0000.9650.6490.0000.9410.8581.0000.7000.0000.920
연간 사용량(세제곱미터_년)1.0001.0000.9430.408NaN0.0000.8190.7001.0000.0001.000
빗물활용 용도1.0001.0000.7920.0970.2030.2320.7890.0000.0001.0000.000
법적시설여부(대상_미대상)1.0001.0001.0000.5030.0000.9040.0680.9201.0000.0001.000
2023-12-12T18:32:25.966037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
여과 등 처리시설 유무법적시설여부(대상_미대상)집수면빗물활용 용도
여과 등 처리시설 유무1.0000.0000.0000.590
법적시설여부(대상_미대상)0.0001.0000.0000.000
집수면0.0000.0001.0000.121
빗물활용 용도0.5900.0000.1211.000
2023-12-12T18:32:26.121749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치비(백만원)집수면적(세제곱미터)저류조 용량(세제곱미터)집수면여과 등 처리시설 유무빗물활용 용도법적시설여부(대상_미대상)
설치비(백만원)1.0000.7170.8310.0000.7190.0510.581
집수면적(세제곱미터)0.7171.0000.7340.0000.6190.1310.679
저류조 용량(세제곱미터)0.8310.7341.0000.0000.5990.0000.702
집수면0.0000.0000.0001.0000.0000.1210.000
여과 등 처리시설 유무0.7190.6190.5990.0001.0000.5900.000
빗물활용 용도0.0510.1310.0000.1210.5901.0000.000
법적시설여부(대상_미대상)0.5810.6790.7020.0000.0000.0001.000

Missing values

2023-12-12T18:32:21.023369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:32:21.476096image/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

시설명위치(주소)설치년월설치비(백만원)집수면집수면적(세제곱미터)여과 등 처리시설 유무저류조 용량(세제곱미터)연간 사용량(세제곱미터_년)빗물활용 용도법적시설여부(대상_미대상)
0대구육상진흥센터대구광역시 수성구 미술관로 88(삼덕동)2013-05-23319.0지붕면3504.0초기우수배재677.0210조경용Y
1대구미술관대구광역시 수성구 미술관로 40(삼덕동)2010-03-1953.0지붕면2902.0자동여과240.042조경용N
2들안길초등학교대구광역시 수성구 들안로 16길 58(두산동)2010-08-0850.0지붕면2726.0스크린30.030조경용N
3노변중학교대구광역시 수성구 시지로 66(노변동)2012-02-0180.0지붕면2946.0스크린60.0100조경용N
4교보생명빌딩대구광역시 수성구 달구벌대로 2330(수성동2가)2015-09-1192.0지붕면676.8스크린40.035조경용N
5삼성라이온즈파크대구광역시 수성구 야구전설로 1 (연호동)2016-01-2568.0지붕면4627.0초기우수배제, 여과, 살균270.0115조경용N
6비컨영어마을학원대구광역시 수성구 범어로 133 (범어동)2016-07-294.0지붕면6.21스크린, 여과시설2.0<NA>조경용N
7단비유치원대구광역시 수성구 신매로 512016-08-183.0기타1.815여과시설1.0<NA>조경용N
8이남희헤어대구광역시 수성구 동대구로8길 212016-07-292.8지붕면73.91스크린1.0<NA>조경 및 청소N
9수정유치원대구광역시 수성구 달구벌대로 650길 212017-06-285.4지붕면11.0여과시설2.53조경용수N
시설명위치(주소)설치년월설치비(백만원)집수면집수면적(세제곱미터)여과 등 처리시설 유무저류조 용량(세제곱미터)연간 사용량(세제곱미터_년)빗물활용 용도법적시설여부(대상_미대상)
26사회복지법인해달별어린이집대구광역시 수성구 용학로46길 22 (지산동)2020-07-213.3지붕면1.6여과시설1.5<NA>조경용수N
27사회복지법인전원어린이집대구광역시 수성구 유니버시아드로68길 16 전원어린이집 (욱수동)2020-07-203.3지붕면1.8여과시설1.5<NA>조경용수N
28주택대구광역시 수성구 상화로4길 34-3 (상동)2020-07-213.41지붕면2.46여과시설1.0<NA>조경용수N
29주택대구광역시 수성구 청솔로 42-21 (황금동)2020-07-261.74지붕면5.2여과시설1.0<NA>조경용수N
30삼도더펜트하우스수성대구광역시 수성구 파동로26길 26(파동)2020-11-1752.0지붕면13049.14여과시설660.0<NA>조경용수Y
31시지코오롱하늘채 스카이뷰대구광역시 수성구 고산로 101(신매동)2022-02-0438.0지붕면2890.71초기우수배제, 여과시설144.54<NA>조경용수N
32하늘빛유치원대구광역시 수성구 지범로40길 11(범물동)2022-06-103.36지붕면5.13여과시설1.0<NA>조경용수N
33수성구청직장어린이집대구광역시 수성구 달구벌대로495길 26-13(범어동)2022-06-073.47지붕면6.4여과시설1.0<NA>조경용수N
34국공립키즈하버드어린이집대구광역시 수성구 세진로3길 41-4(범어동)2022-06-023.46지붕면5.44여과시설1.0<NA>조경용수N
35더샵 수성라크에르대구광역시 지산로3길 33(지산동)2023-04-27185.0지붕면8384.82초기우수배제 및 물리적처리방법715.030조경용수N