Overview

Dataset statistics

Number of variables8
Number of observations50
Missing cells47
Missing cells (%)11.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory67.6 B

Variable types

Categorical3
Text3
Numeric1
DateTime1

Dataset

Description제주특별자치도 제주시에서 관리하는 등산로 폐쇄구간지정 관련 현황 데이터를 제공합니다. 항목 : 관리기관,산명(권역명),위치,등산로 노선번호,등산로 구산,개방여부
URLhttps://www.data.go.kr/data/15056268/fileData.do

Alerts

관리기관 has constant value ""Constant
등산로 구간 has constant value ""Constant
데이터기준일자 has constant value ""Constant
개방여부 is highly imbalanced (75.8%)Imbalance
비고 has 47 (94.0%) missing valuesMissing
등산로 노선번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:45:53.880447
Analysis finished2023-12-12 14:45:54.480821
Duration0.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리기관
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
제주시
50 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제주시 50
100.0%

Length

2023-12-12T23:45:54.561313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:45:54.655656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주시 50
100.0%

산명(권역명)
Text

Distinct48
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2023-12-12T23:45:54.878584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length4.08
Min length3

Characters and Unicode

Total characters204
Distinct characters86
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)92.0%

Sample

1st row느지리오름
2nd row정물오름
3rd row갯거리오름
4th row정월악
5th row다래오름
ValueCountFrequency (%)
민오름 2
 
4.0%
국유림일대 2
 
4.0%
방애오름 1
 
2.0%
느지리오름 1
 
2.0%
돔배오름 1
 
2.0%
다랑쉬오름 1
 
2.0%
아끈다랑쉬 1
 
2.0%
지미봉 1
 
2.0%
손자봉 1
 
2.0%
용눈이오름 1
 
2.0%
Other values (38) 38
76.0%
2023-12-12T23:45:55.577999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
름 33
 
16.2%
오 33
 
16.2%
봉 8
 
3.9%
이 6
 
2.9%
거 6
 
2.9%
지 5
 
2.5%
미 5
 
2.5%
문 4
 
2.0%
리 4
 
2.0%
다 3
 
1.5%
Other values (76) 97
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 202
99.0%
Math Symbol 2
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
름 33
 
16.3%
오 33
 
16.3%
봉 8
 
4.0%
이 6
 
3.0%
거 6
 
3.0%
지 5
 
2.5%
미 5
 
2.5%
문 4
 
2.0%
리 4
 
2.0%
다 3
 
1.5%
Other values (75) 95
47.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 202
99.0%
Common 2
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
름 33
 
16.3%
오 33
 
16.3%
봉 8
 
4.0%
이 6
 
3.0%
거 6
 
3.0%
지 5
 
2.5%
미 5
 
2.5%
문 4
 
2.0%
리 4
 
2.0%
다 3
 
1.5%
Other values (75) 95
47.0%
Common
ValueCountFrequency (%)
+ 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 202
99.0%
ASCII 2
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
름 33
 
16.3%
오 33
 
16.3%
봉 8
 
4.0%
이 6
 
3.0%
거 6
 
3.0%
지 5
 
2.5%
미 5
 
2.5%
문 4
 
2.0%
리 4
 
2.0%
다 3
 
1.5%
Other values (75) 95
47.0%
ASCII
ValueCountFrequency (%)
+ 2
100.0%

위치
Text

Distinct27
Distinct (%)54.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2023-12-12T23:45:55.808418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length6.76
Min length2

Characters and Unicode

Total characters338
Distinct characters55
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)40.0%

Sample

1st row한림읍 상명리
2nd row한림읍 금악리
3rd row한림읍 명월리
4th row한림읍 금능리
5th row애월읍 어음리
ValueCountFrequency (%)
구좌읍 18
18.6%
애월읍 11
11.3%
조천읍 10
10.3%
송당리 8
 
8.2%
교래리 7
 
7.2%
종달리 5
 
5.2%
한림읍 4
 
4.1%
봉성리 4
 
4.1%
한경면 4
 
4.1%
어음리 2
 
2.1%
Other values (22) 24
24.7%
2023-12-12T23:45:56.161276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
47
13.9%
리 47
13.9%
읍 43
 
12.7%
구 18
 
5.3%
좌 18
 
5.3%
월 12
 
3.6%
천 11
 
3.3%
애 11
 
3.3%
조 10
 
3.0%
한 9
 
2.7%
Other values (45) 112
33.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 291
86.1%
Space Separator 47
 
13.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 47
16.2%
읍 43
14.8%
구 18
 
6.2%
좌 18
 
6.2%
월 12
 
4.1%
천 11
 
3.8%
애 11
 
3.8%
조 10
 
3.4%
한 9
 
3.1%
당 8
 
2.7%
Other values (44) 104
35.7%
Space Separator
ValueCountFrequency (%)
47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 291
86.1%
Common 47
 
13.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 47
16.2%
읍 43
14.8%
구 18
 
6.2%
좌 18
 
6.2%
월 12
 
4.1%
천 11
 
3.8%
애 11
 
3.8%
조 10
 
3.4%
한 9
 
3.1%
당 8
 
2.7%
Other values (44) 104
35.7%
Common
ValueCountFrequency (%)
47
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 291
86.1%
ASCII 47
 
13.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
47
100.0%
Hangul
ValueCountFrequency (%)
리 47
16.2%
읍 43
14.8%
구 18
 
6.2%
좌 18
 
6.2%
월 12
 
4.1%
천 11
 
3.8%
애 11
 
3.8%
조 10
 
3.4%
한 9
 
3.1%
당 8
 
2.7%
Other values (44) 104
35.7%

등산로 노선번호
Real number (ℝ)

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.5
Minimum1
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-12T23:45:56.306089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.45
Q113.25
median25.5
Q337.75
95-th percentile47.55
Maximum50
Range49
Interquartile range (IQR)24.5

Descriptive statistics

Standard deviation14.57738
Coefficient of variation (CV)0.57166195
Kurtosis-1.2
Mean25.5
Median Absolute Deviation (MAD)12.5
Skewness0
Sum1275
Variance212.5
MonotonicityStrictly increasing
2023-12-12T23:45:56.455102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
2.0%
39 1
 
2.0%
29 1
 
2.0%
30 1
 
2.0%
31 1
 
2.0%
32 1
 
2.0%
33 1
 
2.0%
34 1
 
2.0%
35 1
 
2.0%
36 1
 
2.0%
Other values (40) 40
80.0%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
10 1
2.0%
ValueCountFrequency (%)
50 1
2.0%
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%
45 1
2.0%
44 1
2.0%
43 1
2.0%
42 1
2.0%
41 1
2.0%

등산로 구간
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
입구-정상
50 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row입구-정상
2nd row입구-정상
3rd row입구-정상
4th row입구-정상
5th row입구-정상

Common Values

ValueCountFrequency (%)
입구-정상 50
100.0%

Length

2023-12-12T23:45:56.583503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:45:56.675928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
입구-정상 50
100.0%

개방여부
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
개방
48 
폐쇄
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개방 48
96.0%
폐쇄 2
 
4.0%

Length

2023-12-12T23:45:56.758406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:45:56.847265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개방 48
96.0%
폐쇄 2
 
4.0%

비고
Text

MISSING 

Distinct2
Distinct (%)66.7%
Missing47
Missing (%)94.0%
Memory size532.0 B
2023-12-12T23:45:56.969954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.3333333
Min length2

Characters and Unicode

Total characters10
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st row임도
2nd row휴식년제
3rd row휴식년제
ValueCountFrequency (%)
휴식년제 2
66.7%
임도 1
33.3%
2023-12-12T23:45:57.258026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
휴 2
20.0%
식 2
20.0%
년 2
20.0%
제 2
20.0%
임 1
10.0%
도 1
10.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
휴 2
20.0%
식 2
20.0%
년 2
20.0%
제 2
20.0%
임 1
10.0%
도 1
10.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
휴 2
20.0%
식 2
20.0%
년 2
20.0%
제 2
20.0%
임 1
10.0%
도 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
휴 2
20.0%
식 2
20.0%
년 2
20.0%
제 2
20.0%
임 1
10.0%
도 1
10.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
Minimum2023-04-04 00:00:00
Maximum2023-04-04 00:00:00
2023-12-12T23:45:57.370651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:45:57.459875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T23:45:54.166992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:45:57.524863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
산명(권역명)위치등산로 노선번호개방여부비고
산명(권역명)1.0000.9820.8611.0001.000
위치0.9821.0000.9250.0000.000
등산로 노선번호0.8610.9251.0000.0001.000
개방여부1.0000.0000.0001.0000.000
비고1.0000.0001.0000.0001.000
2023-12-12T23:45:57.608540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등산로 노선번호개방여부
등산로 노선번호1.0000.000
개방여부0.0001.000

Missing values

2023-12-12T23:45:54.268303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:45:54.424743image/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

관리기관산명(권역명)위치등산로 노선번호등산로 구간개방여부비고데이터기준일자
0제주시느지리오름한림읍 상명리1입구-정상개방<NA>2023-04-04
1제주시정물오름한림읍 금악리2입구-정상개방<NA>2023-04-04
2제주시갯거리오름한림읍 명월리3입구-정상개방<NA>2023-04-04
3제주시정월악한림읍 금능리4입구-정상개방<NA>2023-04-04
4제주시다래오름애월읍 어음리5입구-정상개방<NA>2023-04-04
5제주시괴오름애월읍 봉성리6입구-정상개방<NA>2023-04-04
6제주시새별오름애월읍 봉성리7입구-정상개방<NA>2023-04-04
7제주시이달봉애월읍 봉성리8입구-정상개방<NA>2023-04-04
8제주시국유림일대애월읍 봉성리9입구-정상개방임도2023-04-04
9제주시파군봉애월읍 하귀리10입구-정상개방<NA>2023-04-04
관리기관산명(권역명)위치등산로 노선번호등산로 구간개방여부비고데이터기준일자
40제주시알밤오름조천읍 교래리41입구-정상개방<NA>2023-04-04
41제주시샘이악조천읍 대흘리42입구-정상개방<NA>2023-04-04
42제주시꾀꼬리오름조천읍 대흘리43입구-정상개방<NA>2023-04-04
43제주시저지오름한경면 저지리44입구-정상개방<NA>2023-04-04
44제주시가마오름한경면 청수리45입구-정상개방<NA>2023-04-04
45제주시판포오름한경면 판포리46입구-정상개방<NA>2023-04-04
46제주시당산봉한경면 고산리47입구-정상개방<NA>2023-04-04
47제주시거문오름연동48입구-정상개방<NA>2023-04-04
48제주시열안지오름오라동49입구-정상개방<NA>2023-04-04
49제주시삼의오름아라동50입구-정상개방<NA>2023-04-04