Overview

Dataset statistics

Number of variables9
Number of observations68
Missing cells31
Missing cells (%)5.1%
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 양산시
URLhttps://www.data.go.kr/data/15074034/fileData.do

Alerts

출처 has constant value ""Constant
데이터기준일자 has constant value ""Constant
전화번호 has 26 (38.2%) missing valuesMissing
비고 has 5 (7.4%) missing valuesMissing

Reproduction

Analysis started2023-12-12 18:35:09.740762
Analysis finished2023-12-12 18:35:10.951875
Duration1.21 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
2023-12-13T03:35:11.138865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length5.6617647
Min length3

Characters and Unicode

Total characters385
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
 
2.9%
내원사 2
 
2.9%
오봉산 2
 
2.9%
수질정화공원 1
 
1.4%
법기수원지 1
 
1.4%
워터파크 1
 
1.4%
양산천구름다리 1
 
1.4%
영대교 1
 
1.4%
전국문학인꽃축제 1
 
1.4%
양산타워 1
 
1.4%
Other values (57) 57
81.4%
2023-12-13T03:35:11.549145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 23
 
6.0%
원 17
 
4.4%
리 12
 
3.1%
양 12
 
3.1%
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 (136) 267
69.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 380
98.7%
Space Separator 2
 
0.5%
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 (%)
2
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
98.7%
Common 5
 
1.3%

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 (%)
2
40.0%
& 1
20.0%
) 1
20.0%
( 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 380
98.7%
ASCII 5
 
1.3%

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 (%)
2
40.0%
& 1
20.0%
) 1
20.0%
( 1
20.0%

소재지
Text

Distinct58
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Memory size676.0 B
2023-12-13T03:35:11.916890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length18.661765
Min length12

Characters and Unicode

Total characters1269
Distinct characters113
Distinct categories8 ?
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 (%)
양산시 68
22.4%
경상남도 67
22.1%
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 (97) 108
35.6%
2023-12-13T03:35:12.438936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
235
18.5%
산 79
 
6.2%
상 77
 
6.1%
도 73
 
5.8%
양 70
 
5.5%
남 69
 
5.4%
경 68
 
5.4%
시 68
 
5.4%
면 41
 
3.2%
동 39
 
3.1%
Other values (103) 450
35.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 873
68.8%
Space Separator 235
 
18.5%
Decimal Number 136
 
10.7%
Dash Punctuation 10
 
0.8%
Close Punctuation 6
 
0.5%
Open Punctuation 6
 
0.5%
Other Punctuation 2
 
0.2%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 79
 
9.0%
상 77
 
8.8%
도 73
 
8.4%
양 70
 
8.0%
남 69
 
7.9%
경 68
 
7.8%
시 68
 
7.8%
면 41
 
4.7%
동 39
 
4.5%
원 35
 
4.0%
Other values (87) 254
29.1%
Decimal Number
ValueCountFrequency (%)
2 28
20.6%
1 26
19.1%
7 16
11.8%
8 14
10.3%
6 14
10.3%
0 12
8.8%
3 8
 
5.9%
4 7
 
5.1%
9 7
 
5.1%
5 4
 
2.9%
Space Separator
ValueCountFrequency (%)
235
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 873
68.8%
Common 396
31.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 79
 
9.0%
상 77
 
8.8%
도 73
 
8.4%
양 70
 
8.0%
남 69
 
7.9%
경 68
 
7.8%
시 68
 
7.8%
면 41
 
4.7%
동 39
 
4.5%
원 35
 
4.0%
Other values (87) 254
29.1%
Common
ValueCountFrequency (%)
235
59.3%
2 28
 
7.1%
1 26
 
6.6%
7 16
 
4.0%
8 14
 
3.5%
6 14
 
3.5%
0 12
 
3.0%
- 10
 
2.5%
3 8
 
2.0%
4 7
 
1.8%
Other values (6) 26
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 872
68.7%
ASCII 396
31.2%
Compat Jamo 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
235
59.3%
2 28
 
7.1%
1 26
 
6.6%
7 16
 
4.0%
8 14
 
3.5%
6 14
 
3.5%
0 12
 
3.0%
- 10
 
2.5%
3 8
 
2.0%
4 7
 
1.8%
Other values (6) 26
 
6.6%
Hangul
ValueCountFrequency (%)
산 79
 
9.1%
상 77
 
8.8%
도 73
 
8.4%
양 70
 
8.0%
남 69
 
7.9%
경 68
 
7.8%
시 68
 
7.8%
면 41
 
4.7%
동 39
 
4.5%
원 35
 
4.0%
Other values (86) 253
29.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

위도
Real number (ℝ)

Distinct67
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.40782
Minimum35.298598
Maximum35.538427
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2023-12-13T03:35:12.654734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.298598
5-th percentile35.317064
Q135.358025
median35.399589
Q335.464495
95-th percentile35.501235
Maximum35.538427
Range0.239829
Interquartile range (IQR)0.10647

Descriptive statistics

Standard deviation0.061982791
Coefficient of variation (CV)0.0017505396
Kurtosis-0.99464522
Mean35.40782
Median Absolute Deviation (MAD)0.0521165
Skewness0.16349518
Sum2407.7317
Variance0.0038418664
MonotonicityNot monotonic
2023-12-13T03:35:12.847095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.397856 2
 
2.9%
35.420247 1
 
1.5%
35.317161 1
 
1.5%
35.380131 1
 
1.5%
35.377515 1
 
1.5%
35.421254 1
 
1.5%
35.487023 1
 
1.5%
35.344194 1
 
1.5%
35.479909 1
 
1.5%
35.4878801 1
 
1.5%
Other values (57) 57
83.8%
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)

Distinct67
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.04059
Minimum128.90237
Maximum129.21165
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2023-12-13T03:35:13.077322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.90237
5-th percentile128.91221
Q1128.98614
median129.04417
Q3129.08509
95-th percentile129.16459
Maximum129.21165
Range0.30928
Interquartile range (IQR)0.0989515

Descriptive statistics

Standard deviation0.071060435
Coefficient of variation (CV)0.00055068281
Kurtosis-0.025622227
Mean129.04059
Median Absolute Deviation (MAD)0.0477785
Skewness0.12886094
Sum8774.7601
Variance0.0050495854
MonotonicityNot monotonic
2023-12-13T03:35:13.277142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.907418 2
 
2.9%
129.112164 1
 
1.5%
128.97362 1
 
1.5%
128.921117 1
 
1.5%
129.143333 1
 
1.5%
128.940917 1
 
1.5%
128.986172 1
 
1.5%
129.030908 1
 
1.5%
129.076884 1
 
1.5%
129.064921 1
 
1.5%
Other values (57) 57
83.8%
ValueCountFrequency (%)
128.902365 1
1.5%
128.906593 1
1.5%
128.907418 2
2.9%
128.921117 1
1.5%
128.934782 1
1.5%
128.940917 1
1.5%
128.950867 1
1.5%
128.954596 1
1.5%
128.966002 1
1.5%
128.97362 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 

Distinct37
Distinct (%)88.1%
Missing26
Missing (%)38.2%
Memory size676.0 B
2023-12-13T03:35:13.581591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.047619
Min length12

Characters and Unicode

Total characters506
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

Unique32 ?
Unique (%)76.2%

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
 
7.1%
055-375-4177 2
 
4.8%
055-382-7182 2
 
4.8%
055-392-2114 2
 
4.8%
055-384-4101 2
 
4.8%
055-379-8000 1
 
2.4%
055-367-9026 1
 
2.4%
055-379-9000 1
 
2.4%
055-371-3500 1
 
2.4%
055-388-1315 1
 
2.4%
Other values (26) 26
61.9%
2023-12-13T03:35:14.024640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 103
20.4%
- 84
16.6%
0 78
15.4%
3 55
10.9%
1 33
 
6.5%
8 30
 
5.9%
7 29
 
5.7%
2 29
 
5.7%
4 25
 
4.9%
9 24
 
4.7%
Other values (2) 16
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 420
83.0%
Dash Punctuation 84
 
16.6%
Space Separator 2
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 103
24.5%
0 78
18.6%
3 55
13.1%
1 33
 
7.9%
8 30
 
7.1%
7 29
 
6.9%
2 29
 
6.9%
4 25
 
6.0%
9 24
 
5.7%
6 14
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 506
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 103
20.4%
- 84
16.6%
0 78
15.4%
3 55
10.9%
1 33
 
6.5%
8 30
 
5.9%
7 29
 
5.7%
2 29
 
5.7%
4 25
 
4.9%
9 24
 
4.7%
Other values (2) 16
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 506
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 103
20.4%
- 84
16.6%
0 78
15.4%
3 55
10.9%
1 33
 
6.5%
8 30
 
5.9%
7 29
 
5.7%
2 29
 
5.7%
4 25
 
4.9%
9 24
 
4.7%
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

2023-12-13T03:35:14.214571image/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
2023-12-13T03:35:14.510572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length10
Mean length5.3492063
Min length2

Characters and Unicode

Total characters337
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
 
9.1%
多 5
 
5.7%
등산코스 5
 
5.7%
27홀 3
 
3.4%
창건 3
 
3.4%
음악분수 2
 
2.3%
11월 2
 
2.3%
5월 2
 
2.3%
등 2
 
2.3%
3월 2
 
2.3%
Other values (49) 54
61.4%
2023-12-13T03:35:15.008895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25
 
7.4%
산 13
 
3.9%
월 10
 
3.0%
물 8
 
2.4%
양 8
 
2.4%
1 8
 
2.4%
경 8
 
2.4%
팔 8
 
2.4%
등 7
 
2.1%
시 6
 
1.8%
Other values (127) 236
70.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 267
79.2%
Decimal Number 32
 
9.5%
Space Separator 25
 
7.4%
Other Punctuation 5
 
1.5%
Open Punctuation 4
 
1.2%
Close Punctuation 4
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 13
 
4.9%
월 10
 
3.7%
물 8
 
3.0%
양 8
 
3.0%
경 8
 
3.0%
팔 8
 
3.0%
등 7
 
2.6%
시 6
 
2.2%
홀 6
 
2.2%
창 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%
8 2
 
6.2%
9 2
 
6.2%
0 2
 
6.2%
6 1
 
3.1%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
· 1
 
20.0%
Space Separator
ValueCountFrequency (%)
25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 262
77.7%
Common 70
 
20.8%
Han 5
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 13
 
5.0%
월 10
 
3.8%
물 8
 
3.1%
양 8
 
3.1%
경 8
 
3.1%
팔 8
 
3.1%
등 7
 
2.7%
시 6
 
2.3%
홀 6
 
2.3%
창 5
 
1.9%
Other values (112) 183
69.8%
Common
ValueCountFrequency (%)
25
35.7%
1 8
 
11.4%
2 5
 
7.1%
( 4
 
5.7%
, 4
 
5.7%
) 4
 
5.7%
3 4
 
5.7%
5 4
 
5.7%
7 4
 
5.7%
8 2
 
2.9%
Other values (4) 6
 
8.6%
Han
ValueCountFrequency (%)
多 5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 262
77.7%
ASCII 69
 
20.5%
CJK 5
 
1.5%
None 1
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25
36.2%
1 8
 
11.6%
2 5
 
7.2%
( 4
 
5.8%
, 4
 
5.8%
) 4
 
5.8%
3 4
 
5.8%
5 4
 
5.8%
7 4
 
5.8%
8 2
 
2.9%
Other values (3) 5
 
7.2%
Hangul
ValueCountFrequency (%)
산 13
 
5.0%
월 10
 
3.8%
물 8
 
3.1%
양 8
 
3.1%
경 8
 
3.1%
팔 8
 
3.1%
등 7
 
2.7%
시 6
 
2.3%
홀 6
 
2.3%
창 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

2023-12-13T03:35:15.175888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:35:15.613158image/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
2021-08-05
68 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-08-05
2nd row2021-08-05
3rd row2021-08-05
4th row2021-08-05
5th row2021-08-05

Common Values

ValueCountFrequency (%)
2021-08-05 68
100.0%

Length

2023-12-13T03:35:15.749930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:35:15.865139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-08-05 68
100.0%

Interactions

2023-12-13T03:35:10.444369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:10.263579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:10.536461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:10.355102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:35:15.934875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관광지소재지위도경도전화번호유형비고
관광지1.0001.0001.0001.0001.0001.0000.999
소재지1.0001.0000.9640.9670.9900.9670.973
위도1.0000.9641.0000.7130.9670.6210.798
경도1.0000.9670.7131.0000.9570.0000.000
전화번호1.0000.9900.9670.9571.0000.9800.944
유형1.0000.9670.6210.0000.9801.0000.996
비고0.9990.9730.7980.0000.9440.9961.000
2023-12-13T03:35:16.084578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도유형
위도1.0000.2100.239
경도0.2101.0000.000
유형0.2390.0001.000

Missing values

2023-12-13T03:35:10.667010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:35:10.805673image/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.
2023-12-13T03:35:10.905008image/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, 하북35.420247129.112164055-392-2114명산양산팔경기본현황2021-08-05
1내원사 계곡경상남도 양산시 하북면 용연리35.436245129.098399055-380-4826명승양산팔경기본현황2021-08-05
2홍룡폭포경상남도 양산시 상북면 홍룡로 37235.396997129.087746055-375-4177명승양산팔경기본현황2021-08-05
3배내골경상남도 양산시 원동면 대리ㆍ선리35.454165128.966002<NA>명승양산팔경기본현황2021-08-05
4천태산경상남도 양산시 원동면 용당리35.397856128.907418055-384-4101명산양산팔경기본현황2021-08-05
5오봉산 임경대경상남도 양산시 원동면 화제리35.322273128.976905<NA>명승양산팔경기본현황2021-08-05
6대운산자연휴양림경상남도 양산시 탑골길 208-124(용당동)35.417143129.210404055-379-8670명승양산팔경기본현황2021-08-05
7통도사경상남도 양산시 하북면 통도사로 10835.487908129.064235055-382-7182사찰양산팔경기본현황2021-08-05
8용화사경상남도 양산시 물금읍 원동로 199-13335.317012128.975977055-384-5111사찰보물(석조여래좌상)기본현황2021-08-05
9내원사경상남도 양산시 하북면 내원로 20735.436223129.098409055-374-6466사찰원효대사 창건기본현황2021-08-05
관광지소재지위도경도전화번호유형비고출처데이터기준일자
58원동자연휴양림경상남도 양산시 원동면 늘밭로 6935.398814128.934782055-382-5839휴양림피서지기본현황2021-08-05
59해운청소년수련원경상남도 양산시 하북면 삼수온천길2735.463026129.071611055-384-0061청소년수련시설수련시설기본현황2021-08-05
60통도환타지아(아쿠아환타지아)경상남도 양산시 하북면 통도7길 6835.498795129.086218055-379-7000유원지유희시설기본현황2021-08-05
61양산에덴밸리리조트&스키장경상남도 양산시 원동면 어실로 120635.429066128.984487055-379-8000유원지및스키장객실255개, 슬로프7, 리프트3기본현황2021-08-05
62통도파인이스트컨트리클럽경상남도 양산시 하북면 신평남부로7835.485596129.100716055-370-1300골프장36홀기본현황2021-08-05
63동부산컨트리클럽경상남도 양산시 매곡외산로 28235.359571129.184503055-388-1315골프장27홀기본현황2021-08-05
64에이원컨트리클럽경상남도 양산시 덕명로 19035.378228129.17603055-371-3500골프장27홀기본현황2021-08-05
65에덴밸리컨트리클럽경상남도 양산시 원동면 어실로 120635.427526128.994213055-379-9000골프장18홀기본현황2021-08-05
66양산컨트리클럽경상남도 양산시 상북면 충렬로 68735.402294129.040821055-379-0000골프장27홀기본현황2021-08-05
67양산동원로얄컨트리클럽경상남도 양산시 어곡동 산 28335.400363129.016974055-389-7000골프장18홀기본현황2021-08-05