Overview

Dataset statistics

Number of variables10
Number of observations43
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory87.1 B

Variable types

Text2
Categorical3
Numeric4
DateTime1

Dataset

Description대구광역시 북구_민방위급수시설_20190812
Author대구광역시 북구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15006274&dataSetDetailId=150062741e5bb7769ccae_201909251550&provdMethod=FILE

Alerts

데이터기준일자 has constant value ""Constant
급수능력(Ton) is highly overall correlated with 일일사용가능인원 and 1 other fieldsHigh correlation
일일사용가능인원 is highly overall correlated with 급수능력(Ton) and 2 other fieldsHigh correlation
용도 is highly overall correlated with 급수능력(Ton) and 1 other fieldsHigh correlation
개방유무 is highly overall correlated with 일일사용가능인원 and 1 other fieldsHigh correlation
시설종류 is highly overall correlated with 개방유무High correlation
개방유무 is highly imbalanced (55.4%)Imbalance
시설명 has unique valuesUnique

Reproduction

Analysis started2024-04-21 23:59:24.933158
Analysis finished2024-04-21 23:59:26.801900
Duration1.87 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
2024-04-22T08:59:26.957006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length6.7674419
Min length3

Characters and Unicode

Total characters291
Distinct characters109
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

Unique43 ?
Unique (%)100.0%

Sample

1st row시민운동장
2nd row북구청
3rd row대구체육관
4th row대현아파트
5th row연경동
ValueCountFrequency (%)
시민운동장 1
 
2.1%
우영펠리스(2 1
 
2.1%
칠곡보석헬스장(1 1
 
2.1%
대현탕 1
 
2.1%
유니버시아드 1
 
2.1%
레포츠센터 1
 
2.1%
서변온천(1 1
 
2.1%
서변온천(2 1
 
2.1%
대백아파트 1
 
2.1%
송림스포츠프라자 1
 
2.1%
Other values (37) 37
78.7%
2024-04-22T08:59:27.268573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 11
 
3.8%
) 11
 
3.8%
대 11
 
3.8%
우 9
 
3.1%
북 8
 
2.7%
사 7
 
2.4%
동 7
 
2.4%
스 7
 
2.4%
경 6
 
2.1%
나 6
 
2.1%
Other values (99) 208
71.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 254
87.3%
Open Punctuation 11
 
3.8%
Close Punctuation 11
 
3.8%
Decimal Number 11
 
3.8%
Space Separator 4
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 11
 
4.3%
우 9
 
3.5%
북 8
 
3.1%
사 7
 
2.8%
동 7
 
2.8%
스 7
 
2.8%
경 6
 
2.4%
나 6
 
2.4%
시 6
 
2.4%
원 5
 
2.0%
Other values (93) 182
71.7%
Decimal Number
ValueCountFrequency (%)
2 5
45.5%
1 5
45.5%
3 1
 
9.1%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 254
87.3%
Common 37
 
12.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 11
 
4.3%
우 9
 
3.5%
북 8
 
3.1%
사 7
 
2.8%
동 7
 
2.8%
스 7
 
2.8%
경 6
 
2.4%
나 6
 
2.4%
시 6
 
2.4%
원 5
 
2.0%
Other values (93) 182
71.7%
Common
ValueCountFrequency (%)
( 11
29.7%
) 11
29.7%
2 5
13.5%
1 5
13.5%
4
 
10.8%
3 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 254
87.3%
ASCII 37
 
12.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 11
29.7%
) 11
29.7%
2 5
13.5%
1 5
13.5%
4
 
10.8%
3 1
 
2.7%
Hangul
ValueCountFrequency (%)
대 11
 
4.3%
우 9
 
3.5%
북 8
 
3.1%
사 7
 
2.8%
동 7
 
2.8%
스 7
 
2.8%
경 6
 
2.4%
나 6
 
2.4%
시 6
 
2.4%
원 5
 
2.0%
Other values (93) 182
71.7%

용도
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size476.0 B
생활
32 
음용
11 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row생활
2nd row생활
3rd row음용
4th row음용
5th row음용

Common Values

ValueCountFrequency (%)
생활 32
74.4%
음용 11
 
25.6%

Length

2024-04-22T08:59:27.382153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T08:59:27.470544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생활 32
74.4%
음용 11
 
25.6%

개방유무
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size476.0 B
미개방
39 
개방
4 

Length

Max length3
Median length3
Mean length2.9069767
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row미개방
2nd row미개방
3rd row개방
4th row미개방
5th row개방

Common Values

ValueCountFrequency (%)
미개방 39
90.7%
개방 4
 
9.3%

Length

2024-04-22T08:59:27.562999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T08:59:27.651696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미개방 39
90.7%
개방 4
 
9.3%

시설종류
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
공공용
30 
정부지원
9 
지자체
4 

Length

Max length4
Median length3
Mean length3.2093023
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공용 30
69.8%
정부지원 9
 
20.9%
지자체 4
 
9.3%

Length

2024-04-22T08:59:27.752659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T08:59:27.848524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공용 30
69.8%
정부지원 9
 
20.9%
지자체 4
 
9.3%

도로명주소
Text

Distinct38
Distinct (%)88.4%
Missing0
Missing (%)0.0%
Memory size476.0 B
2024-04-22T08:59:28.070359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length26
Mean length23.116279
Min length16

Characters and Unicode

Total characters994
Distinct characters67
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

Unique34 ?
Unique (%)79.1%

Sample

1st row대구광역시 북구 고성로 191 (고성동3가)
2nd row대구광역시 북구 옥산로 65 (침산동)
3rd row대구광역시 북구 대구체육관로 39 (산격동)
4th row대구광역시 북구 대현로19길 15 (대현동)
5th row대구광역시 북구 도덕길 176-1 (연경동)
ValueCountFrequency (%)
대구광역시 43
20.3%
북구 43
20.3%
칠곡중앙대로 6
 
2.8%
산격동 5
 
2.4%
구암동 5
 
2.4%
태전동 5
 
2.4%
학정로 4
 
1.9%
복현동 4
 
1.9%
읍내동 4
 
1.9%
411 3
 
1.4%
Other values (73) 90
42.5%
2024-04-22T08:59:28.399902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
179
18.0%
구 95
 
9.6%
대 61
 
6.1%
동 51
 
5.1%
북 44
 
4.4%
시 43
 
4.3%
역 43
 
4.3%
광 43
 
4.3%
) 41
 
4.1%
( 41
 
4.1%
Other values (57) 353
35.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 596
60.0%
Space Separator 179
 
18.0%
Decimal Number 131
 
13.2%
Close Punctuation 41
 
4.1%
Open Punctuation 41
 
4.1%
Dash Punctuation 6
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 95
15.9%
대 61
 
10.2%
동 51
 
8.6%
북 44
 
7.4%
시 43
 
7.2%
역 43
 
7.2%
광 43
 
7.2%
로 38
 
6.4%
현 11
 
1.8%
길 10
 
1.7%
Other values (43) 157
26.3%
Decimal Number
ValueCountFrequency (%)
1 36
27.5%
9 15
11.5%
2 13
 
9.9%
4 13
 
9.9%
6 11
 
8.4%
3 10
 
7.6%
5 9
 
6.9%
7 8
 
6.1%
0 8
 
6.1%
8 8
 
6.1%
Space Separator
ValueCountFrequency (%)
179
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 596
60.0%
Common 398
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 95
15.9%
대 61
 
10.2%
동 51
 
8.6%
북 44
 
7.4%
시 43
 
7.2%
역 43
 
7.2%
광 43
 
7.2%
로 38
 
6.4%
현 11
 
1.8%
길 10
 
1.7%
Other values (43) 157
26.3%
Common
ValueCountFrequency (%)
179
45.0%
) 41
 
10.3%
( 41
 
10.3%
1 36
 
9.0%
9 15
 
3.8%
2 13
 
3.3%
4 13
 
3.3%
6 11
 
2.8%
3 10
 
2.5%
5 9
 
2.3%
Other values (4) 30
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 596
60.0%
ASCII 398
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
179
45.0%
) 41
 
10.3%
( 41
 
10.3%
1 36
 
9.0%
9 15
 
3.8%
2 13
 
3.3%
4 13
 
3.3%
6 11
 
2.8%
3 10
 
2.5%
5 9
 
2.3%
Other values (4) 30
 
7.5%
Hangul
ValueCountFrequency (%)
구 95
15.9%
대 61
 
10.2%
동 51
 
8.6%
북 44
 
7.4%
시 43
 
7.2%
역 43
 
7.2%
광 43
 
7.2%
로 38
 
6.4%
현 11
 
1.8%
길 10
 
1.7%
Other values (43) 157
26.3%

급수능력(Ton)
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)55.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean272.7907
Minimum40
Maximum700
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2024-04-22T08:59:28.776928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40
5-th percentile90.2
Q1150
median250
Q3360
95-th percentile538
Maximum700
Range660
Interquartile range (IQR)210

Descriptive statistics

Standard deviation156.13251
Coefficient of variation (CV)0.57235276
Kurtosis-0.057318881
Mean272.7907
Median Absolute Deviation (MAD)100
Skewness0.71624643
Sum11730
Variance24377.36
MonotonicityNot monotonic
2024-04-22T08:59:28.901879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
150 5
 
11.6%
300 4
 
9.3%
210 3
 
7.0%
100 3
 
7.0%
500 3
 
7.0%
200 3
 
7.0%
250 2
 
4.7%
320 2
 
4.7%
370 2
 
4.7%
400 2
 
4.7%
Other values (14) 14
32.6%
ValueCountFrequency (%)
40 1
 
2.3%
80 1
 
2.3%
90 1
 
2.3%
92 1
 
2.3%
98 1
 
2.3%
100 3
7.0%
136 1
 
2.3%
150 5
11.6%
200 3
7.0%
206 1
 
2.3%
ValueCountFrequency (%)
700 1
 
2.3%
550 1
 
2.3%
540 1
 
2.3%
520 1
 
2.3%
500 3
7.0%
400 2
4.7%
370 2
4.7%
350 1
 
2.3%
340 1
 
2.3%
328 1
 
2.3%

일일사용가능인원
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)62.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21707
Minimum2500
Maximum77778
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2024-04-22T08:59:29.017623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2500
5-th percentile5637.5
Q19375
median15625
Q333333
95-th percentile44444
Maximum77778
Range75278
Interquartile range (IQR)23958

Descriptive statistics

Standard deviation15997.091
Coefficient of variation (CV)0.73695538
Kurtosis2.1721957
Mean21707
Median Absolute Deviation (MAD)9375
Skewness1.2986139
Sum933401
Variance2.5590691 × 108
MonotonicityNot monotonic
2024-04-22T08:59:29.133523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
9375 5
 
11.6%
33333 4
 
9.3%
13125 3
 
7.0%
6250 3
 
7.0%
15625 2
 
4.7%
20000 2
 
4.7%
12500 2
 
4.7%
31250 2
 
4.7%
44444 2
 
4.7%
6125 1
 
2.3%
Other values (17) 17
39.5%
ValueCountFrequency (%)
2500 1
 
2.3%
5000 1
 
2.3%
5625 1
 
2.3%
5750 1
 
2.3%
6125 1
 
2.3%
6250 3
7.0%
8500 1
 
2.3%
9375 5
11.6%
12500 2
 
4.7%
12875 1
 
2.3%
ValueCountFrequency (%)
77778 1
 
2.3%
55556 1
 
2.3%
44444 2
4.7%
41111 1
 
2.3%
38889 1
 
2.3%
34375 1
 
2.3%
33750 1
 
2.3%
33333 4
9.3%
32500 1
 
2.3%
31250 2
4.7%

위도
Real number (ℝ)

Distinct37
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.919302
Minimum35.879559
Maximum35.963547
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2024-04-22T08:59:29.284344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.879559
5-th percentile35.8839
Q135.896348
median35.928031
Q335.938045
95-th percentile35.956131
Maximum35.963547
Range0.083988
Interquartile range (IQR)0.041697

Descriptive statistics

Standard deviation0.02432222
Coefficient of variation (CV)0.00067713509
Kurtosis-1.3250798
Mean35.919302
Median Absolute Deviation (MAD)0.019073
Skewness-0.10900325
Sum1544.53
Variance0.00059157038
MonotonicityNot monotonic
2024-04-22T08:59:29.431234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
35.932515 3
 
7.0%
35.947104 2
 
4.7%
35.943908 2
 
4.7%
35.941797 2
 
4.7%
35.921366 2
 
4.7%
35.932194 1
 
2.3%
35.899772 1
 
2.3%
35.899828 1
 
2.3%
35.884232 1
 
2.3%
35.879559 1
 
2.3%
Other values (27) 27
62.8%
ValueCountFrequency (%)
35.879559 1
2.3%
35.882279 1
2.3%
35.883863 1
2.3%
35.884232 1
2.3%
35.885382 1
2.3%
35.887446 1
2.3%
35.890701 1
2.3%
35.892594 1
2.3%
35.893844 1
2.3%
35.896027 1
2.3%
ValueCountFrequency (%)
35.963547 1
2.3%
35.9576 1
2.3%
35.957134 1
2.3%
35.947104 2
4.7%
35.943908 2
4.7%
35.94217 1
2.3%
35.941797 2
4.7%
35.938262 1
2.3%
35.937827 1
2.3%
35.936252 1
2.3%

경도
Real number (ℝ)

Distinct37
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.57657
Minimum128.51725
Maximum128.62124
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2024-04-22T08:59:29.545433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.51725
5-th percentile128.54172
Q1128.55379
median128.56379
Q3128.60225
95-th percentile128.61619
Maximum128.62124
Range0.103997
Interquartile range (IQR)0.048464

Descriptive statistics

Standard deviation0.027954997
Coefficient of variation (CV)0.00021741906
Kurtosis-1.2860877
Mean128.57657
Median Absolute Deviation (MAD)0.021044
Skewness0.072338836
Sum5528.7926
Variance0.00078148188
MonotonicityNot monotonic
2024-04-22T08:59:29.659045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
128.547979 3
 
7.0%
128.558277 2
 
4.7%
128.563331 2
 
4.7%
128.563792 2
 
4.7%
128.598807 2
 
4.7%
128.541227 1
 
2.3%
128.616291 1
 
2.3%
128.621243 1
 
2.3%
128.609569 1
 
2.3%
128.605037 1
 
2.3%
Other values (27) 27
62.8%
ValueCountFrequency (%)
128.517246 1
 
2.3%
128.540992 1
 
2.3%
128.541227 1
 
2.3%
128.546143 1
 
2.3%
128.546619 1
 
2.3%
128.547979 3
7.0%
128.548946 1
 
2.3%
128.551392 1
 
2.3%
128.553003 1
 
2.3%
128.554568 1
 
2.3%
ValueCountFrequency (%)
128.621243 1
2.3%
128.617186 1
2.3%
128.616291 1
2.3%
128.615268 1
2.3%
128.614802 1
2.3%
128.614075 1
2.3%
128.609642 1
2.3%
128.609569 1
2.3%
128.6095 1
2.3%
128.605037 1
2.3%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
Minimum2019-08-12 00:00:00
Maximum2019-08-12 00:00:00
2024-04-22T08:59:29.752276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T08:59:29.826799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-22T08:59:26.266186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T08:59:25.280651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T08:59:25.584945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T08:59:25.921595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T08:59:26.346780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T08:59:25.352116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T08:59:25.669716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T08:59:26.016943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T08:59:26.439595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T08:59:25.435395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T08:59:25.755154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T08:59:26.098446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T08:59:26.507699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T08:59:25.507900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T08:59:25.835077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T08:59:26.175467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-22T08:59:29.891916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명용도개방유무시설종류도로명주소급수능력(Ton)일일사용가능인원위도경도
시설명1.0001.0001.0001.0001.0001.0001.0001.0001.000
용도1.0001.0000.6290.1931.0000.5930.9560.5590.000
개방유무1.0000.6291.0000.3771.0000.3920.7220.0000.000
시설종류1.0000.1930.3771.0001.0000.7890.5300.2950.268
도로명주소1.0001.0001.0001.0001.0000.0000.4451.0001.000
급수능력(Ton)1.0000.5930.3920.7890.0001.0000.9110.5790.000
일일사용가능인원1.0000.9560.7220.5300.4450.9111.0000.5970.000
위도1.0000.5590.0000.2951.0000.5790.5971.0000.762
경도1.0000.0000.0000.2681.0000.0000.0000.7621.000
2024-04-22T08:59:29.992631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
개방유무용도시설종류
개방유무1.0000.4330.590
용도0.4331.0000.311
시설종류0.5900.3111.000
2024-04-22T08:59:30.073308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
급수능력(Ton)일일사용가능인원위도경도용도개방유무시설종류
급수능력(Ton)1.0000.9300.179-0.1150.5410.3510.452
일일사용가능인원0.9301.0000.183-0.1330.7550.5120.388
위도0.1790.1831.000-0.4820.3810.0000.152
경도-0.115-0.133-0.4821.0000.0580.3760.210
용도0.5410.7550.3810.0581.0000.4330.311
개방유무0.3510.5120.0000.3760.4331.0000.590
시설종류0.4520.3880.1520.2100.3110.5901.000

Missing values

2024-04-22T08:59:26.613690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-22T08:59:26.742849image/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

시설명용도개방유무시설종류도로명주소급수능력(Ton)일일사용가능인원위도경도데이터기준일자
0시민운동장생활미개방정부지원대구광역시 북구 고성로 191 (고성동3가)5003125035.882279128.587262019-08-12
1북구청생활미개방정부지원대구광역시 북구 옥산로 65 (침산동)5403375035.885382128.5830632019-08-12
2대구체육관음용개방정부지원대구광역시 북구 대구체육관로 39 (산격동)4004444435.893844128.6033732019-08-12
3대현아파트음용미개방정부지원대구광역시 북구 대현로19길 15 (대현동)2002222235.883863128.60952019-08-12
4연경동음용개방정부지원대구광역시 북구 도덕길 176-1 (연경동)5005555635.957134128.6140752019-08-12
5매천동생활미개방정부지원대구광역시 북구 매천로동17길 49-9 (매천동)5003125035.908995128.5409922019-08-12
6관음공원음용개방정부지원대구광역시 북구 칠곡중앙대로91길 21 (관음동)3003333335.936252128.5466192019-08-12
7금호공원음용개방정부지원대구광역시 북구 한강로 96(금호동)3003333335.896616128.5172462019-08-12
8칠곡시장생활미개방정부지원대구광역시 북구 칠곡중앙대로 518-9 (읍내동)5203250035.94217128.5513922019-08-12
9침산공원생활미개방지자체대구광역시 북구 침산1동 118898612535.896027128.5848362019-08-12
시설명용도개방유무시설종류도로명주소급수능력(Ton)일일사용가능인원위도경도데이터기준일자
33칠곡보석헬스장(1)생활미개방공공용대구광역시 북구 학정로 416 (구암동)3702312535.941797128.5637922019-08-12
34칠곡보석헬스장(2)생활미개방공공용대구광역시 북구 학정로 416 (구암동)2101312535.941797128.5637922019-08-12
35태백사우나생활미개방공공용대구광역시 북구 팔거천동로 80-1 (구암동)3202000035.931427128.5552852019-08-12
36칠곡시티월드사우나생활미개방공공용대구광역시 북구 대천로 31 (읍내동)2101312535.937827128.5530032019-08-12
37동아아울렛강북점음용미개방공공용대구광역시 북구 칠곡중앙대로 416 (읍내동)3003333335.933033128.5489462019-08-12
38대천목욕탕생활미개방공공용대구광역시 북구 팔거천서로 157-16 (읍내동)2501562535.938262128.5545682019-08-12
39그린파크사우나(1)생활미개방공공용대구광역시 북구 학정로 439 (동천동)5503437535.943908128.5633312019-08-12
40그린파크사우나(2)생활미개방공공용대구광역시 북구 학정로 439 (동천동)3202000035.943908128.5633312019-08-12
41강북웰빙랜드(1)음용미개방공공용대구광역시 북구 구리로 29 (학정동)4004444435.947104128.5582772019-08-12
42강북웰빙랜드(2)음용미개방공공용대구광역시 북구 구리로 29 (학정동)3003333335.947104128.5582772019-08-12