Overview

Dataset statistics

Number of variables10
Number of observations26
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory90.1 B

Variable types

Numeric5
Text2
Categorical2
DateTime1

Dataset

Description충청남도 공주시 야외휴게쉼터 현황에 대한 데이터로 컬럼은 쉼터명칭, 지번주소, 위도, 경도, 휴게시설, 시설면적, 이용가능인원, 데이터기준일 이 포함되어 있음
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=35&beforeMenuCd=DOM_000000201001001000&publicdatapk=15117601

Alerts

데이터기준일 has constant value ""Constant
연번 is highly overall correlated with 관리부서High correlation
시설면적 is highly overall correlated with 이용가능인원 and 1 other fieldsHigh correlation
이용가능인원 is highly overall correlated with 시설면적 and 1 other fieldsHigh correlation
휴게시설 is highly overall correlated with 시설면적 and 2 other fieldsHigh correlation
관리부서 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연번 has unique valuesUnique
쉼터명칭 has unique valuesUnique
지번주소 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2024-01-09 22:59:14.109553
Analysis finished2024-01-09 22:59:16.907563
Duration2.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.5
Minimum1
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2024-01-10T07:59:16.962980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.25
Q17.25
median13.5
Q319.75
95-th percentile24.75
Maximum26
Range25
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation7.6485293
Coefficient of variation (CV)0.56655772
Kurtosis-1.2
Mean13.5
Median Absolute Deviation (MAD)6.5
Skewness0
Sum351
Variance58.5
MonotonicityStrictly increasing
2024-01-10T07:59:17.069103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 1
 
3.8%
15 1
 
3.8%
26 1
 
3.8%
25 1
 
3.8%
24 1
 
3.8%
23 1
 
3.8%
22 1
 
3.8%
21 1
 
3.8%
20 1
 
3.8%
19 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
1 1
3.8%
2 1
3.8%
3 1
3.8%
4 1
3.8%
5 1
3.8%
6 1
3.8%
7 1
3.8%
8 1
3.8%
9 1
3.8%
10 1
3.8%
ValueCountFrequency (%)
26 1
3.8%
25 1
3.8%
24 1
3.8%
23 1
3.8%
22 1
3.8%
21 1
3.8%
20 1
3.8%
19 1
3.8%
18 1
3.8%
17 1
3.8%

쉼터명칭
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2024-01-10T07:59:17.248820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length6.7307692
Min length3

Characters and Unicode

Total characters175
Distinct characters76
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

Unique26 ?
Unique (%)100.0%

Sample

1st row신관어울림공원
2nd row풀 향기 숲공원
3rd row돝음별 공원
4th row숲속놀이터
5th row관골2공원
ValueCountFrequency (%)
공원 5
 
13.5%
스마트쉼터 4
 
10.8%
신관어울림공원 1
 
2.7%
산성문화공원(냉난방쉼터 1
 
2.7%
공산성 1
 
2.7%
무령왕릉 1
 
2.7%
한옥마을 1
 
2.7%
미르섬 1
 
2.7%
정안천생태공원 1
 
2.7%
공공녹지 1
 
2.7%
Other values (20) 20
54.1%
2024-01-10T07:59:17.531180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
공 25
 
14.3%
원 20
 
11.4%
11
 
6.3%
터 6
 
3.4%
쉼 5
 
2.9%
마 5
 
2.9%
미 4
 
2.3%
트 4
 
2.3%
스 4
 
2.3%
지 4
 
2.3%
Other values (66) 87
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 157
89.7%
Space Separator 11
 
6.3%
Decimal Number 4
 
2.3%
Uppercase Letter 1
 
0.6%
Open Punctuation 1
 
0.6%
Close Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 25
 
15.9%
원 20
 
12.7%
터 6
 
3.8%
쉼 5
 
3.2%
마 5
 
3.2%
미 4
 
2.5%
트 4
 
2.5%
스 4
 
2.5%
지 4
 
2.5%
골 3
 
1.9%
Other values (60) 77
49.0%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
2 2
50.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 157
89.7%
Common 17
 
9.7%
Latin 1
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 25
 
15.9%
원 20
 
12.7%
터 6
 
3.8%
쉼 5
 
3.2%
마 5
 
3.2%
미 4
 
2.5%
트 4
 
2.5%
스 4
 
2.5%
지 4
 
2.5%
골 3
 
1.9%
Other values (60) 77
49.0%
Common
ValueCountFrequency (%)
11
64.7%
1 2
 
11.8%
2 2
 
11.8%
( 1
 
5.9%
) 1
 
5.9%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 157
89.7%
ASCII 18
 
10.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
공 25
 
15.9%
원 20
 
12.7%
터 6
 
3.8%
쉼 5
 
3.2%
마 5
 
3.2%
미 4
 
2.5%
트 4
 
2.5%
스 4
 
2.5%
지 4
 
2.5%
골 3
 
1.9%
Other values (60) 77
49.0%
ASCII
ValueCountFrequency (%)
11
61.1%
1 2
 
11.1%
2 2
 
11.1%
A 1
 
5.6%
( 1
 
5.6%
) 1
 
5.6%

지번주소
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2024-01-10T07:59:17.701046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16.5
Mean length13.730769
Min length10

Characters and Unicode

Total characters357
Distinct characters47
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st row공주시 신관동 366-6 일원
2nd row공주시 금흥동 667 일원
3rd row공주시 월송동 672 일원
4th row공주시 월송동 621 일원
5th row공주시 신관동 665
ValueCountFrequency (%)
공주시 26
29.5%
신관동 8
 
9.1%
일원 6
 
6.8%
금흥동 3
 
3.4%
금성동 3
 
3.4%
정안면 2
 
2.3%
월송동 2
 
2.3%
웅진동 2
 
2.3%
499-15 1
 
1.1%
465 1
 
1.1%
Other values (34) 34
38.6%
2024-01-10T07:59:17.982117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
62
17.4%
공 26
 
7.3%
시 26
 
7.3%
주 26
 
7.3%
1 25
 
7.0%
동 22
 
6.2%
- 17
 
4.8%
6 16
 
4.5%
5 13
 
3.6%
2 12
 
3.4%
Other values (37) 112
31.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 180
50.4%
Decimal Number 98
27.5%
Space Separator 62
 
17.4%
Dash Punctuation 17
 
4.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 26
14.4%
시 26
14.4%
주 26
14.4%
동 22
12.2%
관 8
 
4.4%
신 8
 
4.4%
금 7
 
3.9%
원 6
 
3.3%
일 6
 
3.3%
리 4
 
2.2%
Other values (25) 41
22.8%
Decimal Number
ValueCountFrequency (%)
1 25
25.5%
6 16
16.3%
5 13
13.3%
2 12
12.2%
9 9
 
9.2%
4 8
 
8.2%
8 5
 
5.1%
0 4
 
4.1%
3 3
 
3.1%
7 3
 
3.1%
Space Separator
ValueCountFrequency (%)
62
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 180
50.4%
Common 177
49.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 26
14.4%
시 26
14.4%
주 26
14.4%
동 22
12.2%
관 8
 
4.4%
신 8
 
4.4%
금 7
 
3.9%
원 6
 
3.3%
일 6
 
3.3%
리 4
 
2.2%
Other values (25) 41
22.8%
Common
ValueCountFrequency (%)
62
35.0%
1 25
14.1%
- 17
 
9.6%
6 16
 
9.0%
5 13
 
7.3%
2 12
 
6.8%
9 9
 
5.1%
4 8
 
4.5%
8 5
 
2.8%
0 4
 
2.3%
Other values (2) 6
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 180
50.4%
ASCII 177
49.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
62
35.0%
1 25
14.1%
- 17
 
9.6%
6 16
 
9.0%
5 13
 
7.3%
2 12
 
6.8%
9 9
 
5.1%
4 8
 
4.5%
8 5
 
2.8%
0 4
 
2.3%
Other values (2) 6
 
3.4%
Hangul
ValueCountFrequency (%)
공 26
14.4%
시 26
14.4%
주 26
14.4%
동 22
12.2%
관 8
 
4.4%
신 8
 
4.4%
금 7
 
3.9%
원 6
 
3.3%
일 6
 
3.3%
리 4
 
2.2%
Other values (25) 41
22.8%

위도
Real number (ℝ)

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.13542
Minimum127.1043
Maximum127.2564
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2024-01-10T07:59:18.099610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.1043
5-th percentile127.10894
Q1127.1226
median127.13213
Q3127.13632
95-th percentile127.15417
Maximum127.2564
Range0.1521
Interquartile range (IQR)0.0137275

Descriptive statistics

Standard deviation0.027724065
Coefficient of variation (CV)0.00021806721
Kurtosis15.251678
Mean127.13542
Median Absolute Deviation (MAD)0.008875
Skewness3.4810859
Sum3305.5208
Variance0.00076862378
MonotonicityNot monotonic
2024-01-10T07:59:18.209531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
127.1315 1
 
3.8%
127.11961 1
 
3.8%
127.13275 1
 
3.8%
127.12361 1
 
3.8%
127.11298 1
 
3.8%
127.10759 1
 
3.8%
127.12744 1
 
3.8%
127.13454 1
 
3.8%
127.13604 1
 
3.8%
127.1225 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
127.1043 1
3.8%
127.10759 1
3.8%
127.11298 1
3.8%
127.11961 1
3.8%
127.1223 1
3.8%
127.12241 1
3.8%
127.1225 1
3.8%
127.12289 1
3.8%
127.12361 1
3.8%
127.12744 1
3.8%
ValueCountFrequency (%)
127.2564 1
3.8%
127.15439 1
3.8%
127.15351 1
3.8%
127.15312 1
3.8%
127.14514 1
3.8%
127.13886 1
3.8%
127.13642 1
3.8%
127.13604 1
3.8%
127.13571 1
3.8%
127.13454 1
3.8%

경도
Real number (ℝ)

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.477927
Minimum36.387348
Maximum36.62069
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2024-01-10T07:59:18.321997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.387348
5-th percentile36.445325
Q136.464786
median36.472202
Q336.476519
95-th percentile36.574097
Maximum36.62069
Range0.233342
Interquartile range (IQR)0.01173325

Descriptive statistics

Standard deviation0.043667619
Coefficient of variation (CV)0.0011970971
Kurtosis6.6691845
Mean36.477927
Median Absolute Deviation (MAD)0.006715
Skewness2.0730389
Sum948.42609
Variance0.0019068609
MonotonicityNot monotonic
2024-01-10T07:59:18.439792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
36.473845 1
 
3.8%
36.441523 1
 
3.8%
36.458199 1
 
3.8%
36.465499 1
 
3.8%
36.462437 1
 
3.8%
36.464677 1
 
3.8%
36.470208 1
 
3.8%
36.491396 1
 
3.8%
36.476786 1
 
3.8%
36.601664 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
36.387348 1
3.8%
36.441523 1
3.8%
36.456732 1
3.8%
36.458199 1
3.8%
36.462437 1
3.8%
36.46304 1
3.8%
36.464677 1
3.8%
36.465113 1
3.8%
36.465499 1
3.8%
36.467693 1
3.8%
ValueCountFrequency (%)
36.62069 1
3.8%
36.601664 1
3.8%
36.491396 1
3.8%
36.488866 1
3.8%
36.478929 1
3.8%
36.47864 1
3.8%
36.476786 1
3.8%
36.475719 1
3.8%
36.475201 1
3.8%
36.473845 1
3.8%

휴게시설
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)34.6%
Missing0
Missing (%)0.0%
Memory size340.0 B
파고라 2개소
6 
정자 2개소
6 
정자 1개소
4 
쉘터 1개소
4 
파고라 1개소
2 
Other values (4)
4 

Length

Max length15
Median length6
Mean length6.7307692
Min length6

Unique

Unique4 ?
Unique (%)15.4%

Sample

1st row정자 1개소, 파고라 1개소
2nd row파고라 2개소
3rd row정자 2개소
4th row정자 2개소
5th row정자 2개소

Common Values

ValueCountFrequency (%)
파고라 2개소 6
23.1%
정자 2개소 6
23.1%
정자 1개소 4
15.4%
쉘터 1개소 4
15.4%
파고라 1개소 2
 
7.7%
정자 1개소, 파고라 1개소 1
 
3.8%
파고라 3개소 1
 
3.8%
정자 6개소 1
 
3.8%
정자 10개소 1
 
3.8%

Length

2024-01-10T07:59:18.541403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:59:18.638657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정자 13
24.1%
2개소 12
22.2%
1개소 12
22.2%
파고라 10
18.5%
쉘터 4
 
7.4%
3개소 1
 
1.9%
6개소 1
 
1.9%
10개소 1
 
1.9%

시설면적
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)42.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.846154
Minimum8
Maximum192.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2024-01-10T07:59:18.744579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile9.75
Q116.5
median32
Q335
95-th percentile104.625
Maximum192.5
Range184.5
Interquartile range (IQR)18.5

Descriptive statistics

Standard deviation38.831886
Coefficient of variation (CV)0.97454541
Kurtosis9.627199
Mean39.846154
Median Absolute Deviation (MAD)15
Skewness2.8852895
Sum1036
Variance1507.9154
MonotonicityNot monotonic
2024-01-10T07:59:18.839944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
32.0 10
38.5%
16.0 3
 
11.5%
48.0 2
 
7.7%
8.0 2
 
7.7%
72.0 2
 
7.7%
15.0 2
 
7.7%
36.0 1
 
3.8%
115.5 1
 
3.8%
192.5 1
 
3.8%
18.0 1
 
3.8%
ValueCountFrequency (%)
8.0 2
 
7.7%
15.0 2
 
7.7%
16.0 3
 
11.5%
18.0 1
 
3.8%
20.0 1
 
3.8%
32.0 10
38.5%
36.0 1
 
3.8%
48.0 2
 
7.7%
72.0 2
 
7.7%
115.5 1
 
3.8%
ValueCountFrequency (%)
192.5 1
 
3.8%
115.5 1
 
3.8%
72.0 2
 
7.7%
48.0 2
 
7.7%
36.0 1
 
3.8%
32.0 10
38.5%
20.0 1
 
3.8%
18.0 1
 
3.8%
16.0 3
 
11.5%
15.0 2
 
7.7%

이용가능인원
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)38.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.846154
Minimum6
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2024-01-10T07:59:18.938999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile6
Q112
median15
Q318
95-th percentile75
Maximum150
Range144
Interquartile range (IQR)6

Descriptive statistics

Standard deviation30.445614
Coefficient of variation (CV)1.3326363
Kurtosis13.3107
Mean22.846154
Median Absolute Deviation (MAD)3
Skewness3.5747288
Sum594
Variance926.93538
MonotonicityNot monotonic
2024-01-10T07:59:19.033231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
15 7
26.9%
18 5
19.2%
6 3
11.5%
12 3
11.5%
8 2
 
7.7%
30 2
 
7.7%
9 1
 
3.8%
90 1
 
3.8%
150 1
 
3.8%
20 1
 
3.8%
ValueCountFrequency (%)
6 3
11.5%
8 2
 
7.7%
9 1
 
3.8%
12 3
11.5%
15 7
26.9%
18 5
19.2%
20 1
 
3.8%
30 2
 
7.7%
90 1
 
3.8%
150 1
 
3.8%
ValueCountFrequency (%)
150 1
 
3.8%
90 1
 
3.8%
30 2
 
7.7%
20 1
 
3.8%
18 5
19.2%
15 7
26.9%
12 3
11.5%
9 1
 
3.8%
8 2
 
7.7%
6 3
11.5%

관리부서
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size340.0 B
산림공원과
22 
도시정책과
4 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
산림공원과 22
84.6%
도시정책과 4
 
15.4%

Length

2024-01-10T07:59:19.144920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:59:19.224514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
산림공원과 22
84.6%
도시정책과 4
 
15.4%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
Minimum2023-08-01 00:00:00
Maximum2023-08-01 00:00:00
2024-01-10T07:59:19.293582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:59:19.373606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-10T07:59:16.310055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:59:14.460932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:59:14.856419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:59:15.261472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:59:15.902846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:59:16.385411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:59:14.527887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:59:14.932673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:59:15.589404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:59:15.984394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:59:16.469859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:59:14.612049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:59:15.020819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:59:15.668995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:59:16.074976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:59:16.544588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:59:14.679811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:59:15.094000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:59:15.736858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:59:16.146962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:59:16.625504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:59:14.767418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:59:15.181405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:59:15.813129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:59:16.230588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:59:19.439487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번쉼터명칭지번주소위도경도휴게시설시설면적이용가능인원관리부서
연번1.0001.0001.0000.0000.8330.5710.4980.0000.964
쉼터명칭1.0001.0001.0001.0001.0001.0001.0001.0001.000
지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
위도0.0001.0001.0001.0000.8180.0000.0000.0000.337
경도0.8331.0001.0000.8181.0000.5830.1940.1850.000
휴게시설0.5711.0001.0000.0000.5831.0000.9480.8911.000
시설면적0.4981.0001.0000.0000.1940.9481.0001.0000.595
이용가능인원0.0001.0001.0000.0000.1850.8911.0001.0000.000
관리부서0.9641.0001.0000.3370.0001.0000.5950.0001.000
2024-01-10T07:59:19.548474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리부서휴게시설
관리부서1.0000.842
휴게시설0.8421.000
2024-01-10T07:59:19.651580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도시설면적이용가능인원휴게시설관리부서
연번1.000-0.463-0.246-0.1420.0960.2350.716
위도-0.4631.0000.2510.0440.0570.0000.377
경도-0.2460.2511.000-0.006-0.1640.3280.000
시설면적-0.1420.044-0.0061.0000.6640.7400.387
이용가능인원0.0960.057-0.1640.6641.0000.7050.000
휴게시설0.2350.0000.3280.7400.7051.0000.842
관리부서0.7160.3770.0000.3870.0000.8421.000

Missing values

2024-01-10T07:59:16.734183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:59:16.857750image/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

연번쉼터명칭지번주소위도경도휴게시설시설면적이용가능인원관리부서데이터기준일
01신관어울림공원공주시 신관동 366-6 일원127.131536.473845정자 1개소, 파고라 1개소48.015산림공원과2023-08-01
12풀 향기 숲공원공주시 금흥동 667 일원127.1531236.478929파고라 2개소8.08산림공원과2023-08-01
23돝음별 공원공주시 월송동 672 일원127.1535136.472728정자 2개소32.018산림공원과2023-08-01
34숲속놀이터공주시 월송동 621 일원127.1543936.475719정자 2개소32.018산림공원과2023-08-01
45관골2공원공주시 신관동 665127.1357136.475201정자 2개소32.018산림공원과2023-08-01
56관골1공원공주시 신관동 589-5127.1301336.471873정자 1개소16.09산림공원과2023-08-01
67번영1공원공주시 신관동 602-14127.1343936.470994정자 2개소32.018산림공원과2023-08-01
78현대A공원공주시 신관동 610-8127.1364236.467693파고라 1개소16.06산림공원과2023-08-01
89신금2공원공주시 신관동 21127.1451436.472531정자 2개소72.030산림공원과2023-08-01
910백미고을공원공주시 금성동 182-1127.122336.465113파고라 2개소32.012산림공원과2023-08-01
연번쉼터명칭지번주소위도경도휴게시설시설면적이용가능인원관리부서데이터기준일
1617월미농공단지 공원공주시 월미동 465127.104336.488866파고라 2개소32.012산림공원과2023-08-01
1718원전말길 공원공주시 반포면 온천리 169-1 일원127.256436.387348정자 1개소32.015산림공원과2023-08-01
1819보물농공단지 공원공주시 정안면 보물리 521-1127.122536.601664파고라 1개소16.06산림공원과2023-08-01
1920공공녹지공주시 금흥동 499-15 일원127.1360436.476786파고라 2개소8.08산림공원과2023-08-01
2021정안천생태공원공주시 의당면 청룡리 918127.1345436.491396정자 6개소115.590산림공원과2023-08-01
2122미르섬공주시 신관동 553127.1274436.470208정자 10개소192.5150산림공원과2023-08-01
2223한옥마을 스마트쉼터공주시 웅진동 325-11127.1075936.464677쉘터 1개소15.015도시정책과2023-08-01
2324무령왕릉 스마트쉼터공주시 웅진동 57-1127.1129836.462437쉘터 1개소15.015도시정책과2023-08-01
2425공산성 스마트쉼터공주시 금성동 16-5127.1236136.465499쉘터 1개소18.020도시정책과2023-08-01
2526은개길 스마트쉼터공주시 옥룡동 421-4127.1327536.458199쉘터 1개소20.015도시정책과2023-08-01