Overview

Dataset statistics

Number of variables12
Number of observations179
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.3 KiB
Average record size in memory98.7 B

Variable types

Categorical6
Text3
Numeric2
DateTime1

Dataset

Description경상남도 양산시 체육 종목별 시설 현황에 대한 데이터로 명칭, 위치, 규모, 규격, 면수, 설치년도 등의 항목을 제공합니다.
Author경상남도 양산시
URLhttps://www.data.go.kr/data/15074122/fileData.do

Alerts

출처 has constant value ""Constant
데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
시설명 is highly overall correlated with 규격High correlation
규격 is highly overall correlated with 시설명High correlation
부서 is highly overall correlated with 경도High correlation
면수 관수 is highly imbalanced (54.1%)Imbalance

Reproduction

Analysis started2023-12-12 05:46:54.400767
Analysis finished2023-12-12 05:46:55.819636
Duration1.42 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)11.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
게이트볼장
24 
족구장
23 
축구장
20 
배드민턴장
17 
농구장
16 
Other values (15)
79 

Length

Max length8
Median length3
Mean length3.8994413
Min length3

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st rowX게임장
2nd rowX게임장
3rd row게이트볼장
4th row게이트볼장
5th row게이트볼장

Common Values

ValueCountFrequency (%)
게이트볼장 24
13.4%
족구장 23
12.8%
축구장 20
11.2%
배드민턴장 17
9.5%
농구장 16
8.9%
테니스장 15
8.4%
풋살장 11
 
6.1%
야구장 8
 
4.5%
다목적구장 7
 
3.9%
수영장 7
 
3.9%
Other values (10) 31
17.3%

Length

2023-12-12T14:46:55.890046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
게이트볼장 24
13.4%
족구장 23
12.8%
축구장 20
11.2%
배드민턴장 17
9.5%
농구장 16
8.9%
테니스장 15
8.4%
풋살장 11
 
6.1%
야구장 8
 
4.5%
다목적구장 7
 
3.9%
수영장 7
 
3.9%
Other values (10) 31
17.3%

명칭
Text

Distinct127
Distinct (%)70.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T14:46:56.147706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length7.7430168
Min length3

Characters and Unicode

Total characters1386
Distinct characters169
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

Unique102 ?
Unique (%)57.0%

Sample

1st row금산근린공원
2nd row성산어린이공원
3rd row양산종합운동장
4th row동면상동체육공원
5th row선리게이트볼장
ValueCountFrequency (%)
완충녹지 8
 
3.6%
웅상체육공원 6
 
2.7%
황산공원 6
 
2.7%
근린공원 6
 
2.7%
상북문화의집 5
 
2.2%
가산수변공원 5
 
2.2%
양산종합운동장 5
 
2.2%
하북체육공원 4
 
1.8%
수질정화공원 4
 
1.8%
동면상동체육공원 4
 
1.8%
Other values (124) 170
76.2%
2023-12-12T14:46:56.541075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
공 95
 
6.9%
원 95
 
6.9%
59
 
4.3%
장 57
 
4.1%
산 53
 
3.8%
체 36
 
2.6%
육 36
 
2.6%
린 35
 
2.5%
상 30
 
2.2%
이 28
 
2.0%
Other values (159) 862
62.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1249
90.1%
Space Separator 59
 
4.3%
Decimal Number 43
 
3.1%
Close Punctuation 17
 
1.2%
Open Punctuation 17
 
1.2%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 95
 
7.6%
원 95
 
7.6%
장 57
 
4.6%
산 53
 
4.2%
체 36
 
2.9%
육 36
 
2.9%
린 35
 
2.8%
상 30
 
2.4%
이 28
 
2.2%
어 28
 
2.2%
Other values (148) 756
60.5%
Decimal Number
ValueCountFrequency (%)
2 12
27.9%
1 10
23.3%
3 6
14.0%
4 5
11.6%
0 4
 
9.3%
6 4
 
9.3%
7 2
 
4.7%
Space Separator
ValueCountFrequency (%)
59
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1249
90.1%
Common 136
 
9.8%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 95
 
7.6%
원 95
 
7.6%
장 57
 
4.6%
산 53
 
4.2%
체 36
 
2.9%
육 36
 
2.9%
린 35
 
2.8%
상 30
 
2.4%
이 28
 
2.2%
어 28
 
2.2%
Other values (148) 756
60.5%
Common
ValueCountFrequency (%)
59
43.4%
) 17
 
12.5%
( 17
 
12.5%
2 12
 
8.8%
1 10
 
7.4%
3 6
 
4.4%
4 5
 
3.7%
0 4
 
2.9%
6 4
 
2.9%
7 2
 
1.5%
Latin
ValueCountFrequency (%)
e 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1249
90.1%
ASCII 137
 
9.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
공 95
 
7.6%
원 95
 
7.6%
장 57
 
4.6%
산 53
 
4.2%
체 36
 
2.9%
육 36
 
2.9%
린 35
 
2.8%
상 30
 
2.4%
이 28
 
2.2%
어 28
 
2.2%
Other values (148) 756
60.5%
ASCII
ValueCountFrequency (%)
59
43.1%
) 17
 
12.4%
( 17
 
12.4%
2 12
 
8.8%
1 10
 
7.3%
3 6
 
4.4%
4 5
 
3.6%
0 4
 
2.9%
6 4
 
2.9%
7 2
 
1.5%

위치
Text

Distinct129
Distinct (%)72.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T14:46:56.874981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length26
Mean length21.189944
Min length16

Characters and Unicode

Total characters3793
Distinct characters104
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

Unique95 ?
Unique (%)53.1%

Sample

1st row경상남도 양산시 동면 금산리 1460-2
2nd row경상남도 양산시 물금읍 범어리 2712-10
3rd row경상남도 양산시 양산대로 849
4th row경상남도 양산시 동면 여락리 301-1
5th row경상남도 양산시 원동면 선리 1489
ValueCountFrequency (%)
양산시 179
21.1%
경상남도 178
21.0%
물금읍 41
 
4.8%
동면 35
 
4.1%
범어리 17
 
2.0%
상북면 14
 
1.7%
하북면 13
 
1.5%
물금리 12
 
1.4%
강변로 12
 
1.4%
남부동 10
 
1.2%
Other values (168) 336
39.7%
2023-12-12T14:46:57.540923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
793
20.9%
산 238
 
6.3%
상 193
 
5.1%
남 190
 
5.0%
양 190
 
5.0%
시 179
 
4.7%
경 178
 
4.7%
도 178
 
4.7%
1 125
 
3.3%
동 97
 
2.6%
Other values (94) 1432
37.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2210
58.3%
Space Separator 793
 
20.9%
Decimal Number 656
 
17.3%
Dash Punctuation 85
 
2.2%
Open Punctuation 24
 
0.6%
Close Punctuation 24
 
0.6%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 238
 
10.8%
상 193
 
8.7%
남 190
 
8.6%
양 190
 
8.6%
시 179
 
8.1%
경 178
 
8.1%
도 178
 
8.1%
동 97
 
4.4%
리 74
 
3.3%
면 66
 
3.0%
Other values (79) 627
28.4%
Decimal Number
ValueCountFrequency (%)
1 125
19.1%
2 87
13.3%
8 78
11.9%
5 64
9.8%
4 56
8.5%
3 54
8.2%
6 52
7.9%
0 50
 
7.6%
9 47
 
7.2%
7 43
 
6.6%
Space Separator
ValueCountFrequency (%)
793
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 85
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2210
58.3%
Common 1582
41.7%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 238
 
10.8%
상 193
 
8.7%
남 190
 
8.6%
양 190
 
8.6%
시 179
 
8.1%
경 178
 
8.1%
도 178
 
8.1%
동 97
 
4.4%
리 74
 
3.3%
면 66
 
3.0%
Other values (79) 627
28.4%
Common
ValueCountFrequency (%)
793
50.1%
1 125
 
7.9%
2 87
 
5.5%
- 85
 
5.4%
8 78
 
4.9%
5 64
 
4.0%
4 56
 
3.5%
3 54
 
3.4%
6 52
 
3.3%
0 50
 
3.2%
Other values (4) 138
 
8.7%
Latin
ValueCountFrequency (%)
e 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2210
58.3%
ASCII 1583
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
793
50.1%
1 125
 
7.9%
2 87
 
5.5%
- 85
 
5.4%
8 78
 
4.9%
5 64
 
4.0%
4 56
 
3.5%
3 54
 
3.4%
6 52
 
3.3%
0 50
 
3.2%
Other values (5) 139
 
8.8%
Hangul
ValueCountFrequency (%)
산 238
 
10.8%
상 193
 
8.7%
남 190
 
8.6%
양 190
 
8.6%
시 179
 
8.1%
경 178
 
8.1%
도 178
 
8.1%
동 97
 
4.4%
리 74
 
3.3%
면 66
 
3.0%
Other values (79) 627
28.4%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct155
Distinct (%)86.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.356877
Minimum35.284846
Maximum35.503619
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T14:46:57.659994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.284846
5-th percentile35.297786
Q135.320311
median35.336395
Q335.390507
95-th percentile35.481
Maximum35.503619
Range0.218773
Interquartile range (IQR)0.07019663

Descriptive statistics

Standard deviation0.052437102
Coefficient of variation (CV)0.0014830807
Kurtosis0.29003322
Mean35.356877
Median Absolute Deviation (MAD)0.02979
Skewness1.0108586
Sum6328.8809
Variance0.0027496496
MonotonicityNot monotonic
2023-12-12T14:46:57.777470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.376171 6
 
3.4%
35.32648559 3
 
1.7%
35.32031055 3
 
1.7%
35.32422137 2
 
1.1%
35.329746 2
 
1.1%
35.39563488 2
 
1.1%
35.29680951 2
 
1.1%
35.303349 2
 
1.1%
35.321473 2
 
1.1%
35.344732 2
 
1.1%
Other values (145) 153
85.5%
ValueCountFrequency (%)
35.284846 1
0.6%
35.28593216 1
0.6%
35.28762823 2
1.1%
35.29545989 1
0.6%
35.29549491 1
0.6%
35.29680951 2
1.1%
35.29724 1
0.6%
35.29784658 1
0.6%
35.301567 1
0.6%
35.3015867 1
0.6%
ValueCountFrequency (%)
35.503619 1
0.6%
35.498414 1
0.6%
35.494105 1
0.6%
35.486792 1
0.6%
35.484407 1
0.6%
35.48383686 1
0.6%
35.48110522 1
0.6%
35.48106154 1
0.6%
35.481 2
1.1%
35.480915 1
0.6%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct154
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.05063
Minimum128.90117
Maximum129.19226
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T14:46:57.932930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.90117
5-th percentile128.99052
Q1129.01706
median129.02897
Q3129.07873
95-th percentile129.16348
Maximum129.19226
Range0.2910833
Interquartile range (IQR)0.06166835

Descriptive statistics

Standard deviation0.056997299
Coefficient of variation (CV)0.00044166617
Kurtosis0.10716069
Mean129.05063
Median Absolute Deviation (MAD)0.028394
Skewness0.83452152
Sum23100.063
Variance0.0032486921
MonotonicityNot monotonic
2023-12-12T14:46:58.064603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.143655 6
 
3.4%
128.9952242 3
 
1.7%
129.0122958 3
 
1.7%
129.1556596 2
 
1.1%
129.022182 2
 
1.1%
129.032186 2
 
1.1%
128.995226 2
 
1.1%
129.021589 2
 
1.1%
129.032216 2
 
1.1%
129.1559808 2
 
1.1%
Other values (144) 153
85.5%
ValueCountFrequency (%)
128.9011737 1
0.6%
128.917874 1
0.6%
128.960049 1
0.6%
128.9846542 1
0.6%
128.985207 1
0.6%
128.987244 2
1.1%
128.9880582 1
0.6%
128.989517 1
0.6%
128.9906352 2
1.1%
128.99095 1
0.6%
ValueCountFrequency (%)
129.192257 1
0.6%
129.179608 2
1.1%
129.179598 1
0.6%
129.174812 1
0.6%
129.174719 1
0.6%
129.174538 1
0.6%
129.1665527 1
0.6%
129.166519 1
0.6%
129.163147 1
0.6%
129.160816 1
0.6%

규모
Text

Distinct105
Distinct (%)58.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T14:46:58.456862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length7.9162011
Min length2

Characters and Unicode

Total characters1417
Distinct characters28
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)46.4%

Sample

1st row830제곱미터
2nd row720제곱미터
3rd row17.6m×2.6m
4th row6.5m×20m
5th row418제곱미터
ValueCountFrequency (%)
23.77 15
 
7.2%
m×10.97m 15
 
7.2%
미상 13
 
6.2%
15m×6.5m 10
 
4.8%
105m×68m 7
 
3.4%
15m×26m 6
 
2.9%
센터110m 6
 
2.9%
좌우95m 5
 
2.4%
42m×25m 4
 
1.9%
100m×64m 4
 
1.9%
Other values (100) 123
59.1%
2023-12-12T14:46:58.976426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
m 232
16.4%
1 131
 
9.2%
0 118
 
8.3%
× 108
 
7.6%
5 94
 
6.6%
2 93
 
6.6%
. 76
 
5.4%
7 70
 
4.9%
6 64
 
4.5%
3 62
 
4.4%
Other values (18) 369
26.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 741
52.3%
Lowercase Letter 232
 
16.4%
Other Letter 211
 
14.9%
Math Symbol 108
 
7.6%
Other Punctuation 88
 
6.2%
Space Separator 30
 
2.1%
Uppercase Letter 7
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
미 49
23.2%
터 42
19.9%
곱 36
17.1%
제 36
17.1%
상 13
 
6.2%
레 8
 
3.8%
인 8
 
3.8%
우 6
 
2.8%
센 6
 
2.8%
좌 6
 
2.8%
Decimal Number
ValueCountFrequency (%)
1 131
17.7%
0 118
15.9%
5 94
12.7%
2 93
12.6%
7 70
9.4%
6 64
8.6%
3 62
8.4%
4 51
 
6.9%
8 31
 
4.2%
9 27
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 76
86.4%
, 12
 
13.6%
Uppercase Letter
ValueCountFrequency (%)
M 6
85.7%
A 1
 
14.3%
Lowercase Letter
ValueCountFrequency (%)
m 232
100.0%
Math Symbol
ValueCountFrequency (%)
× 108
100.0%
Space Separator
ValueCountFrequency (%)
30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 967
68.2%
Latin 239
 
16.9%
Hangul 211
 
14.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 131
13.5%
0 118
12.2%
× 108
11.2%
5 94
9.7%
2 93
9.6%
. 76
7.9%
7 70
7.2%
6 64
6.6%
3 62
6.4%
4 51
 
5.3%
Other values (4) 100
10.3%
Hangul
ValueCountFrequency (%)
미 49
23.2%
터 42
19.9%
곱 36
17.1%
제 36
17.1%
상 13
 
6.2%
레 8
 
3.8%
인 8
 
3.8%
우 6
 
2.8%
센 6
 
2.8%
좌 6
 
2.8%
Latin
ValueCountFrequency (%)
m 232
97.1%
M 6
 
2.5%
A 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1098
77.5%
Hangul 211
 
14.9%
None 108
 
7.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
m 232
21.1%
1 131
11.9%
0 118
10.7%
5 94
8.6%
2 93
8.5%
. 76
 
6.9%
7 70
 
6.4%
6 64
 
5.8%
3 62
 
5.6%
4 51
 
4.6%
Other values (6) 107
9.7%
None
ValueCountFrequency (%)
× 108
100.0%
Hangul
ValueCountFrequency (%)
미 49
23.2%
터 42
19.9%
곱 36
17.1%
제 36
17.1%
상 13
 
6.2%
레 8
 
3.8%
인 8
 
3.8%
우 6
 
2.8%
센 6
 
2.8%
좌 6
 
2.8%

규격
Categorical

HIGH CORRELATION 

Distinct26
Distinct (%)14.5%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
인조잔디
46 
우레탄
29 
미상
29 
클레이코트
17 
마사토
11 
Other values (21)
47 

Length

Max length11
Median length9
Mean length3.4916201
Min length2

Unique

Unique12 ?
Unique (%)6.7%

Sample

1st row미상
2nd row미상
3rd row클레이코트, 인조잔디
4th row클레이코트
5th row인조잔디

Common Values

ValueCountFrequency (%)
인조잔디 46
25.7%
우레탄 29
16.2%
미상 29
16.2%
클레이코트 17
 
9.5%
마사토 11
 
6.1%
천연잔디 7
 
3.9%
아크릴 6
 
3.4%
클레이 6
 
3.4%
마룻바닥 4
 
2.2%
유아풀 3
 
1.7%
Other values (16) 21
11.7%

Length

2023-12-12T14:46:59.131900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
인조잔디 48
26.4%
우레탄 30
16.5%
미상 29
15.9%
클레이코트 18
 
9.9%
마사토 12
 
6.6%
천연잔디 7
 
3.8%
아크릴 7
 
3.8%
클레이 6
 
3.3%
마룻바닥 4
 
2.2%
유아풀 3
 
1.6%
Other values (13) 18
 
9.9%

면수 관수
Categorical

IMBALANCE 

Distinct9
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
1
123 
2
33 
4
 
12
3
 
6
3관
 
1
Other values (4)
 
4

Length

Max length2
Median length1
Mean length1.0111732
Min length1

Unique

Unique5 ?
Unique (%)2.8%

Sample

1st row1
2nd row1
3rd row2
4th row2
5th row1

Common Values

ValueCountFrequency (%)
1 123
68.7%
2 33
 
18.4%
4 12
 
6.7%
3 6
 
3.4%
3관 1
 
0.6%
4관 1
 
0.6%
8 1
 
0.6%
6 1
 
0.6%
5 1
 
0.6%

Length

2023-12-12T14:46:59.326060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:46:59.466184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 123
68.7%
2 33
 
18.4%
4 12
 
6.7%
3 6
 
3.4%
3관 1
 
0.6%
4관 1
 
0.6%
8 1
 
0.6%
6 1
 
0.6%
5 1
 
0.6%

설치
Categorical

Distinct28
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2016
22 
2009
18 
미상
17 
2010
17 
2007
13 
Other values (23)
92 

Length

Max length13
Median length4
Mean length3.8547486
Min length2

Unique

Unique7 ?
Unique (%)3.9%

Sample

1st row2009
2nd row2009
3rd row2017
4th row2016
5th row2015

Common Values

ValueCountFrequency (%)
2016 22
12.3%
2009 18
 
10.1%
미상 17
 
9.5%
2010 17
 
9.5%
2007 13
 
7.3%
2015 11
 
6.1%
2017 10
 
5.6%
2006 9
 
5.0%
2012 8
 
4.5%
2013 8
 
4.5%
Other values (18) 46
25.7%

Length

2023-12-12T14:46:59.671933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2016 22
12.1%
2009 18
 
9.9%
미상 17
 
9.3%
2010 17
 
9.3%
2007 13
 
7.1%
2015 11
 
6.0%
2017 10
 
5.5%
2006 10
 
5.5%
2012 8
 
4.4%
2013 8
 
4.4%
Other values (19) 48
26.4%

부서
Categorical

HIGH CORRELATION 

Distinct26
Distinct (%)14.5%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
공원
28 
공단
17 
시설관리공단
16 
웅상
14 
동면
12 
Other values (21)
92 

Length

Max length8
Median length2
Mean length2.8882682
Min length2

Unique

Unique4 ?
Unique (%)2.2%

Sample

1st row공원과
2nd row공원과
3rd row공단
4th row동면
5th row원동

Common Values

ValueCountFrequency (%)
공원 28
15.6%
공단 17
 
9.5%
시설관리공단 16
 
8.9%
웅상 14
 
7.8%
동면 12
 
6.7%
체육 12
 
6.7%
하북 10
 
5.6%
물금 10
 
5.6%
상북 8
 
4.5%
건설 8
 
4.5%
Other values (16) 44
24.6%

Length

2023-12-12T14:46:59.857355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
공원 28
14.5%
공단 24
12.4%
시설관리공단 16
 
8.3%
웅상 14
 
7.3%
동면 12
 
6.2%
체육 12
 
6.2%
하북 10
 
5.2%
물금 10
 
5.2%
건설 8
 
4.1%
상북 8
 
4.1%
Other values (17) 51
26.4%

출처
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
기본현황
179 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기본현황 179
100.0%

Length

2023-12-12T14:47:00.042650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:47:00.182451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기본현황 179
100.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum2021-08-04 00:00:00
Maximum2021-08-04 00:00:00
2023-12-12T14:47:00.302541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:47:00.426182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T14:46:55.291378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:46:55.120855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:46:55.388540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:46:55.195658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:47:00.505259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명위도경도규격면수 관수설치부서
시설명1.0000.0000.0000.9380.6830.4110.856
위도0.0001.0000.7810.0000.0000.7440.855
경도0.0000.7811.0000.0000.3270.6230.853
규격0.9380.0000.0001.0000.4170.7680.775
면수 관수0.6830.0000.3270.4171.0000.0000.000
설치0.4110.7440.6230.7680.0001.0000.599
부서0.8560.8550.8530.7750.0000.5991.000
2023-12-12T14:47:00.657638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
규격설치부서면수 관수시설명
규격1.0000.2830.2330.1590.583
설치0.2831.0000.1780.0000.113
부서0.2330.1781.0000.0000.409
면수 관수0.1590.0000.0001.0000.339
시설명0.5830.1130.4090.3391.000
2023-12-12T14:47:00.789051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도시설명규격면수 관수설치부서
위도1.0000.6960.0000.0000.0000.3560.498
경도0.6961.0000.0000.0000.1670.2800.523
시설명0.0000.0001.0000.5830.3390.1130.409
규격0.0000.0000.5831.0000.1590.2830.233
면수 관수0.0000.1670.3390.1591.0000.0000.000
설치0.3560.2800.1130.2830.0001.0000.178
부서0.4980.5230.4090.2330.0000.1781.000

Missing values

2023-12-12T14:46:55.529900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:46:55.749623image/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

시설명명칭위치위도경도규모규격면수 관수설치부서출처데이터기준일자
0X게임장금산근린공원경상남도 양산시 동면 금산리 1460-235.308989129.025688830제곱미터미상12009공원과기본현황2021-08-04
1X게임장성산어린이공원경상남도 양산시 물금읍 범어리 2712-1035.3298129.016981720제곱미터미상12009공원과기본현황2021-08-04
2게이트볼장양산종합운동장경상남도 양산시 양산대로 84935.344215129.03088317.6m×2.6m클레이코트, 인조잔디22017공단기본현황2021-08-04
3게이트볼장동면상동체육공원경상남도 양산시 동면 여락리 301-135.306543129.0899596.5m×20m클레이코트22016동면기본현황2021-08-04
4게이트볼장선리게이트볼장경상남도 양산시 원동면 선리 148935.486792128.985207418제곱미터인조잔디12015원동기본현황2021-08-04
5게이트볼장원리게이트볼장경상남도 양산시 원동면 원리 857-1435.367231128.917874437제곱미터인조잔디1미상원동기본현황2021-08-04
6게이트볼장범서게이트볼장경상남도 양산시 원동면 서룡리 38735.34336128.960049381제곱미터인조잔디1미상원동기본현황2021-08-04
7게이트볼장상북문화의집경상남도 양산시 상북면 삼계동길 2735.418524129.06667미상미상1미상상북기본현황2021-08-04
8게이트볼장삼감게이트볼장경상남도 양산시 하북면 삼감리 470-335.451475129.071347409제곱미터미상12007하북기본현황2021-08-04
9게이트볼장어곡주민공원경상남도 양산시 어곡동 2012-1535.378202129.025742460제곱미터클레이코트12008체육기본현황2021-08-04
시설명명칭위치위도경도규모규격면수 관수설치부서출처데이터기준일자
169축구장물금체육공원(1구장)경상남도 양산시 물금읍 백호로 2335.32525129.000578100m×64m인조잔디12015물금읍기본현황2021-08-04
170축구장물금체육공원(2구장)경상남도 양산시 물금읍 백호로 2335.32525129.000578100m×64m인조잔디12015물금읍기본현황2021-08-04
171축구장동면상동체육공원경상남도 양산시 동면 여락리 29935.3063129.090559105m×68m인조잔디12016동면기본현황2021-08-04
172축구장어곡산업단지근린공원경상남도 양산시 어곡공단3길 5035.379989129.01652180m×60m인조잔디12017체육지원기본현황2021-08-04
173축구장가산수변공원경상남도 양산시 동면 호포로 73-135.285932129.012327100m×64m천연잔디12012건설하천기본현황2021-08-04
174축구장가야진사공원경상남도 양산시 원동면 용당리 49035.369235128.901174100m×64m클레이코트12015건설하천기본현황2021-08-04
175축구장삼성체육공원경상남도 양산시 호계동 66535.368018129.069274103m×66m클레이코트12015체육지원기본현황2021-08-04
176축구장황산공원경상남도 양산시 물금읍 물금리 162-135.302043128.990959105m×68m클레이코트22016건설하천기본현황2021-08-04
177축구장양산천 남부둔치경상남도 양산시 양산시 중부동 498-135.335477129.02321511000천연잔디22017공단기본현황2021-08-04
178축구장천성산스포츠파크경상남도 양산시 상북면 석계리 산23-135.420852129.069886100m×68m인조잔디12020상북면기본현황2021-08-04