Overview

Dataset statistics

Number of variables9
Number of observations68
Missing cells40
Missing cells (%)6.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.0 KiB
Average record size in memory75.9 B

Variable types

Text4
Numeric2
Categorical3

Dataset

Description경상남도 양산시 관광자원 현황에 대한 데이터로 관광지, 소재지, 위도, 경도, 전화번호, 유형, 비고 등의 항목을 제공합니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15074034

Alerts

출처 has constant value ""Constant
데이터기준일자 has constant value ""Constant
위도 has 4 (5.9%) missing valuesMissing
경도 has 4 (5.9%) missing valuesMissing
전화번호 has 27 (39.7%) missing valuesMissing
비고 has 5 (7.4%) missing valuesMissing

Reproduction

Analysis started2023-12-11 01:03:25.578216
Analysis finished2023-12-11 01:03:27.270715
Duration1.69 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관광지
Text

Distinct67
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
2023-12-11T10:03:27.492709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length5.6911765
Min length3

Characters and Unicode

Total characters387
Distinct characters146
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

Unique66 ?
Unique (%)97.1%

Sample

1st row천성산
2nd row내원사 계곡
3rd row홍룡폭포
4th row배내골
5th row천태산
ValueCountFrequency (%)
천태산 2
 
2.8%
내원사 2
 
2.8%
오봉산 2
 
2.8%
배내골사과축제 1
 
1.4%
수질정화공원 1
 
1.4%
법기수원지 1
 
1.4%
워터파크 1
 
1.4%
양산천구름다리 1
 
1.4%
영대교 1
 
1.4%
전국문학인꽃축제 1
 
1.4%
Other values (59) 59
81.9%
2023-12-11T10:03:27.900371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 23
 
5.9%
원 17
 
4.4%
리 12
 
3.1%
양 12
 
3.1%
축 11
 
2.8%
사 11
 
2.8%
제 10
 
2.6%
트 8
 
2.1%
화 7
 
1.8%
내 7
 
1.8%
Other values (136) 269
69.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 380
98.2%
Space Separator 4
 
1.0%
Other Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%
Open Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 23
 
6.1%
원 17
 
4.5%
리 12
 
3.2%
양 12
 
3.2%
축 11
 
2.9%
사 11
 
2.9%
제 10
 
2.6%
트 8
 
2.1%
화 7
 
1.8%
내 7
 
1.8%
Other values (132) 262
68.9%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 380
98.2%
Common 7
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 23
 
6.1%
원 17
 
4.5%
리 12
 
3.2%
양 12
 
3.2%
축 11
 
2.9%
사 11
 
2.9%
제 10
 
2.6%
트 8
 
2.1%
화 7
 
1.8%
내 7
 
1.8%
Other values (132) 262
68.9%
Common
ValueCountFrequency (%)
4
57.1%
& 1
 
14.3%
) 1
 
14.3%
( 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 380
98.2%
ASCII 7
 
1.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 23
 
6.1%
원 17
 
4.5%
리 12
 
3.2%
양 12
 
3.2%
축 11
 
2.9%
사 11
 
2.9%
제 10
 
2.6%
트 8
 
2.1%
화 7
 
1.8%
내 7
 
1.8%
Other values (132) 262
68.9%
ASCII
ValueCountFrequency (%)
4
57.1%
& 1
 
14.3%
) 1
 
14.3%
( 1
 
14.3%

소재지
Text

Distinct58
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Memory size676.0 B
2023-12-11T10:03:28.219297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length18.676471
Min length12

Characters and Unicode

Total characters1270
Distinct characters112
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)76.5%

Sample

1st row경상남도 양산시 주진일원 상북 하북
2nd row경상남도 양산시 하북면 용연리
3rd row경상남도 양산시 상북면 홍룡로 372
4th row경상남도 양산시 원동면 대리ㆍ선리
5th row경상남도 양산시 원동면 용당리
ValueCountFrequency (%)
경상남도 68
22.4%
양산시 68
22.4%
원동면 18
 
5.9%
하북면 13
 
4.3%
일원 10
 
3.3%
상북면 7
 
2.3%
물금읍 4
 
1.3%
동면 3
 
1.0%
용당리 3
 
1.0%
홍룡로 2
 
0.7%
Other values (95) 107
35.3%
2023-12-11T10:03:28.650017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
235
18.5%
산 79
 
6.2%
상 78
 
6.1%
도 74
 
5.8%
양 70
 
5.5%
남 69
 
5.4%
시 68
 
5.4%
경 68
 
5.4%
면 41
 
3.2%
동 39
 
3.1%
Other values (102) 449
35.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 875
68.9%
Space Separator 235
 
18.5%
Decimal Number 137
 
10.8%
Dash Punctuation 10
 
0.8%
Open Punctuation 6
 
0.5%
Close Punctuation 6
 
0.5%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 79
 
9.0%
상 78
 
8.9%
도 74
 
8.5%
양 70
 
8.0%
남 69
 
7.9%
시 68
 
7.8%
경 68
 
7.8%
면 41
 
4.7%
동 39
 
4.5%
원 35
 
4.0%
Other values (87) 254
29.0%
Decimal Number
ValueCountFrequency (%)
2 27
19.7%
1 26
19.0%
7 17
12.4%
6 15
10.9%
8 14
10.2%
0 12
8.8%
3 8
 
5.8%
4 8
 
5.8%
9 7
 
5.1%
5 3
 
2.2%
Space Separator
ValueCountFrequency (%)
235
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 875
68.9%
Common 395
31.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 79
 
9.0%
상 78
 
8.9%
도 74
 
8.5%
양 70
 
8.0%
남 69
 
7.9%
시 68
 
7.8%
경 68
 
7.8%
면 41
 
4.7%
동 39
 
4.5%
원 35
 
4.0%
Other values (87) 254
29.0%
Common
ValueCountFrequency (%)
235
59.5%
2 27
 
6.8%
1 26
 
6.6%
7 17
 
4.3%
6 15
 
3.8%
8 14
 
3.5%
0 12
 
3.0%
- 10
 
2.5%
3 8
 
2.0%
4 8
 
2.0%
Other values (5) 23
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 874
68.8%
ASCII 395
31.1%
Compat Jamo 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
235
59.5%
2 27
 
6.8%
1 26
 
6.6%
7 17
 
4.3%
6 15
 
3.8%
8 14
 
3.5%
0 12
 
3.0%
- 10
 
2.5%
3 8
 
2.0%
4 8
 
2.0%
Other values (5) 23
 
5.8%
Hangul
ValueCountFrequency (%)
산 79
 
9.0%
상 78
 
8.9%
도 74
 
8.5%
양 70
 
8.0%
남 69
 
7.9%
시 68
 
7.8%
경 68
 
7.8%
면 41
 
4.7%
동 39
 
4.5%
원 35
 
4.0%
Other values (86) 253
28.9%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

위도
Real number (ℝ)

MISSING 

Distinct63
Distinct (%)98.4%
Missing4
Missing (%)5.9%
Infinite0
Infinite (%)0.0%
Mean35.405577
Minimum35.298598
Maximum35.538427
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2023-12-11T10:03:28.797538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.298598
5-th percentile35.317034
Q135.355551
median35.398335
Q335.45638
95-th percentile35.501986
Maximum35.538427
Range0.239829
Interquartile range (IQR)0.100829

Descriptive statistics

Standard deviation0.062193198
Coefficient of variation (CV)0.0017565933
Kurtosis-0.95171911
Mean35.405577
Median Absolute Deviation (MAD)0.0521165
Skewness0.21853893
Sum2265.9569
Variance0.0038679939
MonotonicityNot monotonic
2023-12-11T10:03:28.988562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.397856 2
 
2.9%
35.478515 1
 
1.5%
35.298598 1
 
1.5%
35.307287 1
 
1.5%
35.351349 1
 
1.5%
35.325311 1
 
1.5%
35.345579 1
 
1.5%
35.344112 1
 
1.5%
35.32595 1
 
1.5%
35.4878801 1
 
1.5%
Other values (53) 53
77.9%
(Missing) 4
 
5.9%
ValueCountFrequency (%)
35.298598 1
1.5%
35.303116 1
1.5%
35.307287 1
1.5%
35.317012 1
1.5%
35.317161 1
1.5%
35.322273 1
1.5%
35.325311 1
1.5%
35.32595 1
1.5%
35.330832 1
1.5%
35.340957 1
1.5%
ValueCountFrequency (%)
35.538427 1
1.5%
35.51699 1
1.5%
35.504542 1
1.5%
35.502549 1
1.5%
35.498795 1
1.5%
35.49236 1
1.5%
35.488375 1
1.5%
35.487908 1
1.5%
35.4878801 1
1.5%
35.487868 1
1.5%

경도
Real number (ℝ)

MISSING 

Distinct63
Distinct (%)98.4%
Missing4
Missing (%)5.9%
Infinite0
Infinite (%)0.0%
Mean129.04573
Minimum128.90237
Maximum129.21165
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2023-12-11T10:03:29.159511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.90237
5-th percentile128.91152
Q1128.99657
median129.04945
Q3129.08624
95-th percentile129.17113
Maximum129.21165
Range0.30928
Interquartile range (IQR)0.089673

Descriptive statistics

Standard deviation0.069741207
Coefficient of variation (CV)0.00054043795
Kurtosis0.14892819
Mean129.04573
Median Absolute Deviation (MAD)0.040884
Skewness0.06284573
Sum8258.9265
Variance0.004863836
MonotonicityNot monotonic
2023-12-11T10:03:29.331509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.907418 2
 
2.9%
129.058195 1
 
1.5%
128.991785 1
 
1.5%
129.022838 1
 
1.5%
129.104156 1
 
1.5%
129.00099 1
 
1.5%
129.030246 1
 
1.5%
129.029053 1
 
1.5%
129.024039 1
 
1.5%
129.064921 1
 
1.5%
Other values (53) 53
77.9%
(Missing) 4
 
5.9%
ValueCountFrequency (%)
128.902365 1
1.5%
128.906593 1
1.5%
128.907418 2
2.9%
128.934782 1
1.5%
128.950867 1
1.5%
128.954596 1
1.5%
128.966002 1
1.5%
128.97362 1
1.5%
128.975977 1
1.5%
128.976905 1
1.5%
ValueCountFrequency (%)
129.211645 1
1.5%
129.210404 1
1.5%
129.184503 1
1.5%
129.17603 1
1.5%
129.143333 1
1.5%
129.13116 1
1.5%
129.129949 1
1.5%
129.121514 1
1.5%
129.112164 1
1.5%
129.104156 1
1.5%

전화번호
Text

MISSING 

Distinct36
Distinct (%)87.8%
Missing27
Missing (%)39.7%
Memory size676.0 B
2023-12-11T10:03:29.565135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.04878
Min length12

Characters and Unicode

Total characters494
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

Unique31 ?
Unique (%)75.6%

Sample

1st row055-392-2114
2nd row055-380-4826
3rd row055-375-4177
4th row055-384-4101
5th row055-379-8670
ValueCountFrequency (%)
055-392-2547 3
 
7.3%
055-375-4177 2
 
4.9%
055-382-7182 2
 
4.9%
055-392-2114 2
 
4.9%
055-384-4101 2
 
4.9%
055-370-1300 1
 
2.4%
055-379-9000 1
 
2.4%
055-371-3500 1
 
2.4%
055-388-1315 1
 
2.4%
055-367-9026 1
 
2.4%
Other values (25) 25
61.0%
2023-12-11T10:03:29.889002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 100
20.2%
- 82
16.6%
0 77
15.6%
3 54
10.9%
1 30
 
6.1%
8 30
 
6.1%
2 29
 
5.9%
7 28
 
5.7%
4 24
 
4.9%
9 24
 
4.9%
Other values (2) 16
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 410
83.0%
Dash Punctuation 82
 
16.6%
Space Separator 2
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 100
24.4%
0 77
18.8%
3 54
13.2%
1 30
 
7.3%
8 30
 
7.3%
2 29
 
7.1%
7 28
 
6.8%
4 24
 
5.9%
9 24
 
5.9%
6 14
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 82
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 494
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 100
20.2%
- 82
16.6%
0 77
15.6%
3 54
10.9%
1 30
 
6.1%
8 30
 
6.1%
2 29
 
5.9%
7 28
 
5.7%
4 24
 
4.9%
9 24
 
4.9%
Other values (2) 16
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 494
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 100
20.2%
- 82
16.6%
0 77
15.6%
3 54
10.9%
1 30
 
6.1%
8 30
 
6.1%
2 29
 
5.9%
7 28
 
5.7%
4 24
 
4.9%
9 24
 
4.9%
Other values (2) 16
 
3.2%

유형
Categorical

Distinct23
Distinct (%)33.8%
Missing0
Missing (%)0.0%
Memory size676.0 B
사찰
9 
관광축제
8 
명산
7 
유적지
7 
골프장
6 
Other values (18)
31 

Length

Max length7
Median length5
Mean length2.8823529
Min length2

Unique

Unique12 ?
Unique (%)17.6%

Sample

1st row명산
2nd row명승
3rd row명승
4th row명승
5th row명산

Common Values

ValueCountFrequency (%)
사찰 9
13.2%
관광축제 8
11.8%
명산 7
10.3%
유적지 7
10.3%
골프장 6
8.8%
명승 5
 
7.4%
공원 4
 
5.9%
폭포 4
 
5.9%
문화축제 2
 
2.9%
교량 2
 
2.9%
Other values (13) 14
20.6%

Length

2023-12-11T10:03:30.050862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
사찰 9
13.2%
관광축제 8
11.8%
명산 7
10.3%
유적지 7
10.3%
골프장 6
8.8%
명승 5
 
7.4%
공원 4
 
5.9%
폭포 4
 
5.9%
문화축제 2
 
2.9%
교량 2
 
2.9%
Other values (13) 14
20.6%

비고
Text

MISSING 

Distinct42
Distinct (%)66.7%
Missing5
Missing (%)7.4%
Memory size676.0 B
2023-12-11T10:03:30.345602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length9
Mean length5.6190476
Min length2

Characters and Unicode

Total characters354
Distinct characters137
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)49.2%

Sample

1st row양산팔경
2nd row양산팔경
3rd row양산팔경
4th row양산팔경
5th row양산팔경
ValueCountFrequency (%)
양산팔경 8
 
8.7%
多 5
 
5.4%
등산코스 5
 
5.4%
27홀 3
 
3.3%
창건 3
 
3.3%
음악분수 2
 
2.2%
11월 2
 
2.2%
5월 2
 
2.2%
등 2
 
2.2%
3월 2
 
2.2%
Other values (53) 58
63.0%
2023-12-11T10:03:30.780232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
45
 
12.7%
산 13
 
3.7%
월 10
 
2.8%
물 8
 
2.3%
1 8
 
2.3%
양 8
 
2.3%
팔 8
 
2.3%
경 8
 
2.3%
등 7
 
2.0%
시 6
 
1.7%
Other values (127) 233
65.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 267
75.4%
Space Separator 45
 
12.7%
Decimal Number 32
 
9.0%
Open Punctuation 4
 
1.1%
Close Punctuation 4
 
1.1%
Other Punctuation 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 13
 
4.9%
월 10
 
3.7%
물 8
 
3.0%
양 8
 
3.0%
팔 8
 
3.0%
경 8
 
3.0%
등 7
 
2.6%
시 6
 
2.2%
홀 6
 
2.2%
스 5
 
1.9%
Other values (113) 188
70.4%
Decimal Number
ValueCountFrequency (%)
1 8
25.0%
2 5
15.6%
3 4
12.5%
5 4
12.5%
7 4
12.5%
9 2
 
6.2%
0 2
 
6.2%
8 2
 
6.2%
6 1
 
3.1%
Other Punctuation
ValueCountFrequency (%)
· 1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
45
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 262
74.0%
Common 87
 
24.6%
Han 5
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 13
 
5.0%
월 10
 
3.8%
물 8
 
3.1%
양 8
 
3.1%
팔 8
 
3.1%
경 8
 
3.1%
등 7
 
2.7%
시 6
 
2.3%
홀 6
 
2.3%
스 5
 
1.9%
Other values (112) 183
69.8%
Common
ValueCountFrequency (%)
45
51.7%
1 8
 
9.2%
2 5
 
5.7%
( 4
 
4.6%
) 4
 
4.6%
3 4
 
4.6%
5 4
 
4.6%
7 4
 
4.6%
9 2
 
2.3%
0 2
 
2.3%
Other values (4) 5
 
5.7%
Han
ValueCountFrequency (%)
多 5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 262
74.0%
ASCII 86
 
24.3%
CJK 5
 
1.4%
None 1
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
45
52.3%
1 8
 
9.3%
2 5
 
5.8%
( 4
 
4.7%
) 4
 
4.7%
3 4
 
4.7%
5 4
 
4.7%
7 4
 
4.7%
9 2
 
2.3%
0 2
 
2.3%
Other values (3) 4
 
4.7%
Hangul
ValueCountFrequency (%)
산 13
 
5.0%
월 10
 
3.8%
물 8
 
3.1%
양 8
 
3.1%
팔 8
 
3.1%
경 8
 
3.1%
등 7
 
2.7%
시 6
 
2.3%
홀 6
 
2.3%
스 5
 
1.9%
Other values (112) 183
69.8%
CJK
ValueCountFrequency (%)
多 5
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

출처
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
기본현황
68 

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 68
100.0%

Length

2023-12-11T10:03:30.911829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T10:03:31.026024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기본현황 68
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
2020-11-30
68 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-11-30
2nd row2020-11-30
3rd row2020-11-30
4th row2020-11-30
5th row2020-11-30

Common Values

ValueCountFrequency (%)
2020-11-30 68
100.0%

Length

2023-12-11T10:03:31.154526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T10:03:31.288608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-11-30 68
100.0%

Interactions

2023-12-11T10:03:26.285568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:03:26.051877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:03:26.394281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:03:26.157484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T10:03:31.353254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관광지소재지위도경도전화번호유형비고
관광지1.0001.0001.0001.0001.0001.0000.999
소재지1.0001.0000.9780.9970.9900.9670.973
위도1.0000.9781.0000.7330.9960.5720.793
경도1.0000.9970.7331.0000.9940.0000.000
전화번호1.0000.9900.9960.9941.0000.9810.948
유형1.0000.9670.5720.0000.9811.0000.996
비고0.9990.9730.7930.0000.9480.9961.000
2023-12-11T10:03:31.457007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도유형
위도1.0000.2680.205
경도0.2681.0000.000
유형0.2050.0001.000

Missing values

2023-12-11T10:03:26.540236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T10:03:27.010266image/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.
2023-12-11T10:03:27.179177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

관광지소재지위도경도전화번호유형비고출처데이터기준일자
0천성산경상남도 양산시 주진일원 상북 하북35.420247129.112164055-392-2114명산양산팔경기본현황2020-11-30
1내원사 계곡경상남도 양산시 하북면 용연리35.436245129.098399055-380-4826명승양산팔경기본현황2020-11-30
2홍룡폭포경상남도 양산시 상북면 홍룡로 37235.396997129.087746055-375-4177명승양산팔경기본현황2020-11-30
3배내골경상남도 양산시 원동면 대리ㆍ선리35.454165128.966002<NA>명승양산팔경기본현황2020-11-30
4천태산경상남도 양산시 원동면 용당리35.397856128.907418055-384-4101명산양산팔경기본현황2020-11-30
5오봉산 임경대경상남도 양산시 원동면 화제리35.322273128.976905<NA>명승양산팔경기본현황2020-11-30
6대운산자연휴양림경상남도 양산시 탑골길 208-124(용당동)35.417143129.210404055-379-8670명승양산팔경기본현황2020-11-30
7통도사경상남도 양산시 하북면 통도사로 10835.487908129.064235055-382-7182사찰양산팔경기본현황2020-11-30
8용화사경상남도 양산시 물금읍 원동로 199-13335.317012128.975977055-384-5111사찰보물(석조여래좌상)기본현황2020-11-30
9내원사경상남도 양산시 하북면 내원로 20735.436223129.098409055-374-6466사찰원효대사 창건기본현황2020-11-30
관광지소재지위도경도전화번호유형비고출처데이터기준일자
58원동자연휴양림경상남도 양산시 원동면 늘밭로 6935.398814128.934782055-382-5839휴양림피 서 지기본현황2020-11-30
59해운청소년수련원경상남도 양산시 하북면 삼수온천길2735.463026129.071611055-384-0061청소년수련시설수련시설기본현황2020-11-30
60통도환타지아 (아쿠아환타지아)경상남도 양산시 하북면 통도7길 6835.498795129.086218055-379-7000유원지유희시설기본현황2020-11-30
61양산에덴밸리리조트 &스키장경상남도 양산시 원동면 어실로 120635.429066128.984487055-379-8000유원지및스키장객실255개 슬로프7 리프트3기본현황2020-11-30
62통도파인이스트컨트리클럽경상남도 양산시 하북면 신평남부로7835.485596129.100716055-370-1300골프장36홀기본현황2020-11-30
63동부산컨트리클럽경상남도 양산시 매곡외산로 28235.359571129.184503055-388-1315골프장27홀기본현황2020-11-30
64에이원컨트리클럽경상남도 양산시 덕명로 19035.378228129.17603055-371-3500골프장27홀기본현황2020-11-30
65에덴밸리컨트리클럽경상남도 양산시 원동면 어실로 120635.427526128.994213055-379-9000골프장18홀기본현황2020-11-30
66양산컨트리클럽경상남도 양산시 상북면 충렬로 68735.402294129.040821055-379-0000골프장27홀기본현황2020-11-30
67양산동원로얄컨트리클럽경상남도 양산시 어곡동 산 28335.400363129.016974055-389-7000골프장18홀기본현황2020-11-30