Overview

Dataset statistics

Number of variables11
Number of observations41
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory94.2 B

Variable types

Numeric2
Categorical6
Text3

Dataset

Description군민 및 외부 관광객이 등산 중 길을 잃거나 부상을 입어서 거동이 불가한 상황에 119에 신고를 하여 정확한 위치를 알수 없을 때 고유번호를 확인하여 신속하게 현장 출동할 수 있는 조난위치표지목 현황 데이터로, 산 이름, 고유번호, 좌표 등의 정보를 제공합니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15065355

Alerts

관할표시 has constant value ""Constant
수량 has constant value ""Constant
연번 is highly overall correlated with 코스명(주소등) and 1 other fieldsHigh correlation
코스(킬로미터) is highly overall correlated with 코스명(주소등) and 1 other fieldsHigh correlation
코스명(주소등) is highly overall correlated with 연번 and 3 other fieldsHigh correlation
산 이름 is highly overall correlated with 코스(킬로미터) and 2 other fieldsHigh correlation
종류 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
설치연도(이력사항) is highly overall correlated with 산 이름 and 1 other fieldsHigh correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:27:22.933331
Analysis finished2023-12-11 00:27:23.808836
Duration0.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21
Minimum1
Maximum41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-11T09:27:23.861071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q111
median21
Q331
95-th percentile39
Maximum41
Range40
Interquartile range (IQR)20

Descriptive statistics

Standard deviation11.979149
Coefficient of variation (CV)0.57043565
Kurtosis-1.2
Mean21
Median Absolute Deviation (MAD)10
Skewness0
Sum861
Variance143.5
MonotonicityStrictly increasing
2023-12-11T09:27:23.982392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
1 1
 
2.4%
32 1
 
2.4%
24 1
 
2.4%
25 1
 
2.4%
26 1
 
2.4%
27 1
 
2.4%
28 1
 
2.4%
29 1
 
2.4%
30 1
 
2.4%
31 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
1 1
2.4%
2 1
2.4%
3 1
2.4%
4 1
2.4%
5 1
2.4%
6 1
2.4%
7 1
2.4%
8 1
2.4%
9 1
2.4%
10 1
2.4%
ValueCountFrequency (%)
41 1
2.4%
40 1
2.4%
39 1
2.4%
38 1
2.4%
37 1
2.4%
36 1
2.4%
35 1
2.4%
34 1
2.4%
33 1
2.4%
32 1
2.4%

코스명(주소등)
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)31.7%
Missing0
Missing (%)0.0%
Memory size460.0 B
부곡면 덕암산입구∼ 정상
10 
관룡사~동문
6 
자하곡~배바위
5 
산장~서문
5 
관룡사~허준세트장
4 
Other values (8)
11 

Length

Max length15
Median length13
Mean length9.2926829
Min length5

Unique

Unique5 ?
Unique (%)12.2%

Sample

1st row자하곡~배바위
2nd row자하곡~배바위
3rd row자하곡~배바위
4th row자하곡~배바위
5th row자하곡~배바위

Common Values

ValueCountFrequency (%)
부곡면 덕암산입구∼ 정상 10
24.4%
관룡사~동문 6
14.6%
자하곡~배바위 5
12.2%
산장~서문 5
12.2%
관룡사~허준세트장 4
 
9.8%
도성암~서문 2
 
4.9%
덕암산 입구~ 정상 2
 
4.9%
용선대코스(창녕읍 옥천리) 2
 
4.9%
관룡사~용선대 1
 
2.4%
제 1등산로(창녕읍 송현리) 1
 
2.4%
Other values (3) 3
 
7.3%

Length

2023-12-11T09:27:24.087159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
정상 12
16.7%
부곡면 11
15.3%
덕암산입구∼ 10
13.9%
관룡사~동문 6
8.3%
자하곡~배바위 5
6.9%
산장~서문 5
6.9%
관룡사~허준세트장 4
 
5.6%
옥천리 3
 
4.2%
용선대코스(창녕읍 2
 
2.8%
송현리 2
 
2.8%
Other values (9) 12
16.7%

산 이름
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size460.0 B
화왕산
27 
덕암산
13 
관룡산
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
화왕산 27
65.9%
덕암산 13
31.7%
관룡산 1
 
2.4%

Length

2023-12-11T09:27:24.175596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:27:24.257268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
화왕산 27
65.9%
덕암산 13
31.7%
관룡산 1
 
2.4%

고유번호
Text

Distinct39
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-11T09:27:24.420001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length6
Mean length6.3658537
Min length3

Characters and Unicode

Total characters261
Distinct characters28
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

Unique37 ?
Unique (%)90.2%

Sample

1st row창녕군1-1
2nd row창녕군1-2
3rd row창녕군1-3
4th row창녕군1-4
5th row창녕군1-5
ValueCountFrequency (%)
창녕군4-5 2
 
4.1%
창녕군2-3 2
 
4.1%
1-1(소방서 2
 
4.1%
04월 2
 
4.1%
04일 2
 
4.1%
창녕군1-2 1
 
2.0%
6-1 1
 
2.0%
창녕군6-4 1
 
2.0%
창녕군6-5 1
 
2.0%
창녕군6-6 1
 
2.0%
Other values (34) 34
69.4%
2023-12-11T09:27:24.704018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 36
13.8%
창 33
12.6%
군 33
12.6%
녕 33
12.6%
1 17
 
6.5%
4 15
 
5.7%
2 12
 
4.6%
6 12
 
4.6%
5 11
 
4.2%
0 10
 
3.8%
Other values (18) 49
18.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 123
47.1%
Decimal Number 90
34.5%
Dash Punctuation 36
 
13.8%
Space Separator 8
 
3.1%
Close Punctuation 2
 
0.8%
Open Punctuation 2
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
창 33
26.8%
군 33
26.8%
녕 33
26.8%
월 5
 
4.1%
일 5
 
4.1%
산 2
 
1.6%
서 2
 
1.6%
방 2
 
1.6%
소 2
 
1.6%
가 2
 
1.6%
Other values (4) 4
 
3.3%
Decimal Number
ValueCountFrequency (%)
1 17
18.9%
4 15
16.7%
2 12
13.3%
6 12
13.3%
5 11
12.2%
0 10
11.1%
3 10
11.1%
9 1
 
1.1%
8 1
 
1.1%
7 1
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 138
52.9%
Hangul 123
47.1%

Most frequent character per script

Common
ValueCountFrequency (%)
- 36
26.1%
1 17
12.3%
4 15
10.9%
2 12
 
8.7%
6 12
 
8.7%
5 11
 
8.0%
0 10
 
7.2%
3 10
 
7.2%
8
 
5.8%
) 2
 
1.4%
Other values (4) 5
 
3.6%
Hangul
ValueCountFrequency (%)
창 33
26.8%
군 33
26.8%
녕 33
26.8%
월 5
 
4.1%
일 5
 
4.1%
산 2
 
1.6%
서 2
 
1.6%
방 2
 
1.6%
소 2
 
1.6%
가 2
 
1.6%
Other values (4) 4
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 138
52.9%
Hangul 123
47.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 36
26.1%
1 17
12.3%
4 15
10.9%
2 12
 
8.7%
6 12
 
8.7%
5 11
 
8.0%
0 10
 
7.2%
3 10
 
7.2%
8
 
5.8%
) 2
 
1.4%
Other values (4) 5
 
3.6%
Hangul
ValueCountFrequency (%)
창 33
26.8%
군 33
26.8%
녕 33
26.8%
월 5
 
4.1%
일 5
 
4.1%
산 2
 
1.6%
서 2
 
1.6%
방 2
 
1.6%
소 2
 
1.6%
가 2
 
1.6%
Other values (4) 4
 
3.3%

좌표
Text

Distinct32
Distinct (%)78.0%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-11T09:27:24.912901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length36
Mean length33.731707
Min length31

Characters and Unicode

Total characters1383
Distinct characters22
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

Unique25 ?
Unique (%)61.0%

Sample

1st row위도 N 35°32'32.2"경도 E 128°31'10.4"
2nd row위도 N 35°32'33.0"경도 E 128°31'22.4"
3rd row위도 N 35°32'33.5" 경도 E 128°31'33.0"
4th row위도 N 35°32'38.5" 경도 E 128°31'00.7"
5th row위도 N 35°32'11.4" 경도 E 128°31'09.0"
ValueCountFrequency (%)
위도 41
15.6%
e 41
15.6%
n 41
15.6%
경도 26
 
9.9%
31′ 8
 
3.0%
35° 8
 
3.0%
32′ 8
 
3.0%
128° 8
 
3.0%
35°4491514경도 3
 
1.1%
128°5886464 3
 
1.1%
Other values (60) 76
28.9%
2023-12-11T09:27:25.220747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
222
16.1%
3 138
 
10.0%
5 97
 
7.0%
1 97
 
7.0%
2 96
 
6.9%
도 82
 
5.9%
° 82
 
5.9%
8 61
 
4.4%
4 60
 
4.3%
. 55
 
4.0%
Other values (12) 393
28.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 666
48.2%
Space Separator 222
 
16.1%
Other Punctuation 167
 
12.1%
Other Letter 164
 
11.9%
Other Symbol 82
 
5.9%
Uppercase Letter 82
 
5.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 138
20.7%
5 97
14.6%
1 97
14.6%
2 96
14.4%
8 61
9.2%
4 60
9.0%
6 36
 
5.4%
0 33
 
5.0%
9 30
 
4.5%
7 18
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 55
32.9%
' 40
24.0%
" 40
24.0%
′ 16
 
9.6%
″ 16
 
9.6%
Other Letter
ValueCountFrequency (%)
도 82
50.0%
위 41
25.0%
경 41
25.0%
Uppercase Letter
ValueCountFrequency (%)
E 41
50.0%
N 41
50.0%
Space Separator
ValueCountFrequency (%)
222
100.0%
Other Symbol
ValueCountFrequency (%)
° 82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1137
82.2%
Hangul 164
 
11.9%
Latin 82
 
5.9%

Most frequent character per script

Common
ValueCountFrequency (%)
222
19.5%
3 138
12.1%
5 97
8.5%
1 97
8.5%
2 96
8.4%
° 82
 
7.2%
8 61
 
5.4%
4 60
 
5.3%
. 55
 
4.8%
' 40
 
3.5%
Other values (7) 189
16.6%
Hangul
ValueCountFrequency (%)
도 82
50.0%
위 41
25.0%
경 41
25.0%
Latin
ValueCountFrequency (%)
E 41
50.0%
N 41
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1105
79.9%
Hangul 164
 
11.9%
None 82
 
5.9%
Punctuation 32
 
2.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
222
20.1%
3 138
12.5%
5 97
8.8%
1 97
8.8%
2 96
8.7%
8 61
 
5.5%
4 60
 
5.4%
. 55
 
5.0%
E 41
 
3.7%
N 41
 
3.7%
Other values (6) 197
17.8%
Hangul
ValueCountFrequency (%)
도 82
50.0%
위 41
25.0%
경 41
25.0%
None
ValueCountFrequency (%)
° 82
100.0%
Punctuation
ValueCountFrequency (%)
′ 16
50.0%
″ 16
50.0%

현위치
Text

Distinct36
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-11T09:27:25.406399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length6.195122
Min length2

Characters and Unicode

Total characters254
Distinct characters79
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

Unique31 ?
Unique (%)75.6%

Sample

1st row산장밑삼거리
2nd row놀이공원
3rd row전망대
4th row전망대위1.4km
5th row장군바위
ValueCountFrequency (%)
용선대 3
 
6.7%
환장고개입구 2
 
4.4%
약수터 2
 
4.4%
부근(체육시설 2
 
4.4%
장군바위 2
 
4.4%
헬기장 2
 
4.4%
암석지대 1
 
2.2%
목마산성갈림길 1
 
2.2%
200m 1
 
2.2%
전 1
 
2.2%
Other values (28) 28
62.2%
2023-12-11T09:27:25.679529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
 
5.9%
m 11
 
4.3%
삼 8
 
3.1%
장 8
 
3.1%
리 8
 
3.1%
산 7
 
2.8%
암 7
 
2.8%
거 7
 
2.8%
구 6
 
2.4%
대 6
 
2.4%
Other values (69) 171
67.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 191
75.2%
Decimal Number 28
 
11.0%
Lowercase Letter 16
 
6.3%
Close Punctuation 5
 
2.0%
Open Punctuation 5
 
2.0%
Other Punctuation 5
 
2.0%
Space Separator 4
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
삼 8
 
4.2%
장 8
 
4.2%
리 8
 
4.2%
산 7
 
3.7%
암 7
 
3.7%
거 7
 
3.7%
구 6
 
3.1%
대 6
 
3.1%
룡 6
 
3.1%
위 6
 
3.1%
Other values (55) 122
63.9%
Decimal Number
ValueCountFrequency (%)
0 15
53.6%
4 3
 
10.7%
1 3
 
10.7%
2 3
 
10.7%
6 1
 
3.6%
7 1
 
3.6%
5 1
 
3.6%
3 1
 
3.6%
Lowercase Letter
ValueCountFrequency (%)
m 11
68.8%
k 5
31.2%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Other Punctuation
ValueCountFrequency (%)
. 5
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 191
75.2%
Common 47
 
18.5%
Latin 16
 
6.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
삼 8
 
4.2%
장 8
 
4.2%
리 8
 
4.2%
산 7
 
3.7%
암 7
 
3.7%
거 7
 
3.7%
구 6
 
3.1%
대 6
 
3.1%
룡 6
 
3.1%
위 6
 
3.1%
Other values (55) 122
63.9%
Common
ValueCountFrequency (%)
0 15
31.9%
) 5
 
10.6%
( 5
 
10.6%
. 5
 
10.6%
4
 
8.5%
4 3
 
6.4%
1 3
 
6.4%
2 3
 
6.4%
6 1
 
2.1%
7 1
 
2.1%
Other values (2) 2
 
4.3%
Latin
ValueCountFrequency (%)
m 11
68.8%
k 5
31.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 191
75.2%
ASCII 63
 
24.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15
23.8%
m 11
17.5%
k 5
 
7.9%
) 5
 
7.9%
( 5
 
7.9%
. 5
 
7.9%
4
 
6.3%
4 3
 
4.8%
1 3
 
4.8%
2 3
 
4.8%
Other values (4) 4
 
6.3%
Hangul
ValueCountFrequency (%)
삼 8
 
4.2%
장 8
 
4.2%
리 8
 
4.2%
산 7
 
3.7%
암 7
 
3.7%
거 7
 
3.7%
구 6
 
3.1%
대 6
 
3.1%
룡 6
 
3.1%
위 6
 
3.1%
Other values (55) 122
63.9%

관할표시
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
창녕군
41 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
창녕군 41
100.0%

Length

2023-12-11T09:27:25.784403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:27:25.857736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
창녕군 41
100.0%

코스(킬로미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)39.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4770732
Minimum0.4
Maximum5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-11T09:27:25.927577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.4
5-th percentile1.1
Q11.9
median2.7
Q33
95-th percentile3.94
Maximum5
Range4.6
Interquartile range (IQR)1.1

Descriptive statistics

Standard deviation0.97855568
Coefficient of variation (CV)0.39504512
Kurtosis0.30539921
Mean2.4770732
Median Absolute Deviation (MAD)0.8
Skewness0.18758306
Sum101.56
Variance0.95757122
MonotonicityNot monotonic
2023-12-11T09:27:26.012105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1.9 8
19.5%
2.8 5
12.2%
2.7 5
12.2%
3.94 4
9.8%
2.4 3
 
7.3%
3.0 3
 
7.3%
1.4 2
 
4.9%
0.4 2
 
4.9%
1.5 2
 
4.9%
1.7 1
 
2.4%
Other values (6) 6
14.6%
ValueCountFrequency (%)
0.4 2
 
4.9%
1.1 1
 
2.4%
1.4 2
 
4.9%
1.5 2
 
4.9%
1.7 1
 
2.4%
1.9 8
19.5%
2.0 1
 
2.4%
2.4 3
 
7.3%
2.7 5
12.2%
2.8 5
12.2%
ValueCountFrequency (%)
5.0 1
 
2.4%
4.0 1
 
2.4%
3.94 4
9.8%
3.3 1
 
2.4%
3.2 1
 
2.4%
3.0 3
7.3%
2.8 5
12.2%
2.7 5
12.2%
2.4 3
7.3%
2.0 1
 
2.4%

수량
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
1
41 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 41
100.0%

Length

2023-12-11T09:27:26.103929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:27:26.175288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 41
100.0%

종류
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size460.0 B
조난위치표지목
30 
조난위치표시등
6 
위치표지판
 
3
CPR안내도
 
2

Length

Max length7
Median length7
Mean length6.804878
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
조난위치표지목 30
73.2%
조난위치표시등 6
 
14.6%
위치표지판 3
 
7.3%
CPR안내도 2
 
4.9%

Length

2023-12-11T09:27:26.269203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:27:26.362273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
조난위치표지목 30
73.2%
조난위치표시등 6
 
14.6%
위치표지판 3
 
7.3%
cpr안내도 2
 
4.9%

설치연도(이력사항)
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size460.0 B
2007
15 
2016
12 
2010
5 
2013
3 
2018
2 
Other values (4)
4 

Length

Max length10
Median length4
Mean length4.1463415
Min length4

Unique

Unique4 ?
Unique (%)9.8%

Sample

1st row2016
2nd row2007
3rd row2007
4th row2007
5th row2016

Common Values

ValueCountFrequency (%)
2007 15
36.6%
2016 12
29.3%
2010 5
 
12.2%
2013 3
 
7.3%
2018 2
 
4.9%
2008 1
 
2.4%
2011 1
 
2.4%
2020(2013) 1
 
2.4%
2009 1
 
2.4%

Length

2023-12-11T09:27:26.454524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:27:26.548818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2007 15
36.6%
2016 12
29.3%
2010 5
 
12.2%
2013 3
 
7.3%
2018 2
 
4.9%
2008 1
 
2.4%
2011 1
 
2.4%
2020(2013 1
 
2.4%
2009 1
 
2.4%

Interactions

2023-12-11T09:27:23.465304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:27:23.325595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:27:23.535963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:27:23.397705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:27:26.890911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번코스명(주소등)산 이름고유번호좌표현위치코스(킬로미터)종류설치연도(이력사항)
연번1.0000.8990.7040.8880.3460.7000.7780.8680.792
코스명(주소등)0.8991.0001.0001.0000.0000.9480.8920.8690.747
산 이름0.7041.0001.0001.0001.0001.0000.9210.4600.855
고유번호0.8881.0001.0001.0001.0001.0001.0000.0000.980
좌표0.3460.0001.0001.0001.0001.0000.5950.0000.000
현위치0.7000.9481.0001.0001.0001.0000.9780.0000.547
코스(킬로미터)0.7780.8920.9211.0000.5950.9781.0000.1840.875
종류0.8680.8690.4600.0000.0000.0000.1841.0000.886
설치연도(이력사항)0.7920.7470.8550.9800.0000.5470.8750.8861.000
2023-12-11T09:27:26.983081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
코스명(주소등)산 이름설치연도(이력사항)종류
코스명(주소등)1.0000.8580.4040.625
산 이름0.8581.0000.5210.448
설치연도(이력사항)0.4040.5211.0000.740
종류0.6250.4480.7401.000
2023-12-11T09:27:27.060830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번코스(킬로미터)코스명(주소등)산 이름종류설치연도(이력사항)
연번1.000-0.1010.6230.4700.7060.486
코스(킬로미터)-0.1011.0000.6200.6160.0830.463
코스명(주소등)0.6230.6201.0000.8580.6250.404
산 이름0.4700.6160.8581.0000.4480.521
종류0.7060.0830.6250.4481.0000.740
설치연도(이력사항)0.4860.4630.4040.5210.7401.000

Missing values

2023-12-11T09:27:23.619251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:27:23.764038image/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

연번코스명(주소등)산 이름고유번호좌표현위치관할표시코스(킬로미터)수량종류설치연도(이력사항)
01자하곡~배바위화왕산창녕군1-1위도 N 35°32'32.2"경도 E 128°31'10.4"산장밑삼거리창녕군2.81조난위치표지목2016
12자하곡~배바위화왕산창녕군1-2위도 N 35°32'33.0"경도 E 128°31'22.4"놀이공원창녕군2.81조난위치표지목2007
23자하곡~배바위화왕산창녕군1-3위도 N 35°32'33.5" 경도 E 128°31'33.0"전망대창녕군2.81조난위치표지목2007
34자하곡~배바위화왕산창녕군1-4위도 N 35°32'38.5" 경도 E 128°31'00.7"전망대위1.4km창녕군2.81조난위치표지목2007
45자하곡~배바위화왕산창녕군1-5위도 N 35°32'11.4" 경도 E 128°31'09.0"장군바위창녕군2.81조난위치표지목2016
56산장~서문화왕산창녕군2-1위도 N 35° 32′ 38.5″ 경도 E 128° 31′ 39.2″해삼바위창녕군2.71조난위치표지목2016
67산장~서문화왕산창녕군2-2위도 N 35° 32′ 38.9″ 경도 E 128° 31′ 49.6″탱크바위창녕군2.71조난위치표지목2007
78산장~서문화왕산창녕군2-3위도 N 35° 32′ 40.6″ 경도 E 128° 31′ 55.5″환장고개입구창녕군2.71조난위치표지목2016
89산장~서문화왕산창녕군2-4위도 N 35° 32′ 41.9″ 경도 E 128° 31′ 00.0″서문창녕군2.71조난위치표지목2007
910도성암~서문화왕산창녕군3-1위도 N 35° 32′ 43″ 경도 E 128° 31′ 31.7″명상의숲창녕군1.91조난위치표지목2007
연번코스명(주소등)산 이름고유번호좌표현위치관할표시코스(킬로미터)수량종류설치연도(이력사항)
3132관룡사~동문화왕산창녕군4-5위도 N 35°32'23.5" 경도 E 128°33'13.9"헬기장창녕군1.91위치표지판2007
3233덕암산 입구~ 정상덕암산창녕군 6-1위도 N 35°4491514경도 E 128°5886464약수터 부근(체육시설)창녕군1.41위치표지판2007
3334덕암산 입구~ 정상덕암산덕암산 1-1(소방서)위도 N 35°4491514경도 E 128°5886464약수터 부근(체육시설)창녕군1.41CPR안내도2018
3435관룡사~용선대관룡산관룡산 1-1(소방서)위도 N 35°31'55.6" 경도 E 128°33'07.3"용선대 200m 전창녕군0.41CPR안내도2018
3536제 1등산로(창녕읍 송현리)화왕산가-1위도 N 35°32'11.4" 경도 E 128°31'09.0"장군바위창녕군3.31조난위치표시등2009
3637제3등산로(창녕읍 송현리)화왕산03월 04일위도 N 35° 32′ 53.2″ 경도 E 128° 31′ 58.3″목마산성갈림길창녕군2.01조난위치표시등2010
3738용선대코스(창녕읍 옥천리)화왕산04월 02일위도 N 35°31'54.4" 경도 E 128°32'56.4"용선대창녕군1.51조난위치표시등2010
3839용선대코스(창녕읍 옥천리)화왕산04월 05일위도 N 35°32'23.5" 경도 E 128°33'13.9"헬리포트창녕군4.01조난위치표시등2010
3940청룡암코스(창녕읍 옥천리)화왕산05월 04일위도 N 35°32'20.5" 경도 E 128°33'18.5"구룡산삼거리창녕군3.01조난위치표시등2010
4041부곡면 덕암산입구덕암산06월 03일위도 N 35°4512676경도 E 128°6010187덕암산정상창녕군5.01조난위치표시등2010