Overview

Dataset statistics

Number of variables8
Number of observations35
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory69.8 B

Variable types

Numeric2
Text3
Categorical2
DateTime1

Dataset

Description충청북도 제천시의 등산로현황 공공데이터입니다.연번, 산명, 시군구, 등산로, 노선, 거리, 데이터기준일로 구성되어 있습니다.
Author충청북도 제천시
URLhttps://www.data.go.kr/data/15123925/fileData.do

Alerts

시군구 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연번 has unique valuesUnique
산명 has unique valuesUnique
등산로 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:46:47.250924
Analysis finished2023-12-12 06:46:48.318396
Duration1.07 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18
Minimum1
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-12T15:46:48.398178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.7
Q19.5
median18
Q326.5
95-th percentile33.3
Maximum35
Range34
Interquartile range (IQR)17

Descriptive statistics

Standard deviation10.246951
Coefficient of variation (CV)0.56927504
Kurtosis-1.2
Mean18
Median Absolute Deviation (MAD)9
Skewness0
Sum630
Variance105
MonotonicityStrictly increasing
2023-12-12T15:46:48.563338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
1 1
 
2.9%
2 1
 
2.9%
21 1
 
2.9%
22 1
 
2.9%
23 1
 
2.9%
24 1
 
2.9%
25 1
 
2.9%
26 1
 
2.9%
27 1
 
2.9%
28 1
 
2.9%
Other values (25) 25
71.4%
ValueCountFrequency (%)
1 1
2.9%
2 1
2.9%
3 1
2.9%
4 1
2.9%
5 1
2.9%
6 1
2.9%
7 1
2.9%
8 1
2.9%
9 1
2.9%
10 1
2.9%
ValueCountFrequency (%)
35 1
2.9%
34 1
2.9%
33 1
2.9%
32 1
2.9%
31 1
2.9%
30 1
2.9%
29 1
2.9%
28 1
2.9%
27 1
2.9%
26 1
2.9%

산명
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-12T15:46:48.815580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.4857143
Min length2

Characters and Unicode

Total characters122
Distinct characters61
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

Unique35 ?
Unique (%)100.0%

Sample

1st row용두산
2nd row감악산
3rd row송학산
4th row무등 왕박산
5th row까치봉 백곡산
ValueCountFrequency (%)
뒷산 2
 
5.0%
용두산 1
 
2.5%
구학산 1
 
2.5%
마폐봉 1
 
2.5%
백운산 1
 
2.5%
십자봉 1
 
2.5%
삼봉산 1
 
2.5%
봉황산 1
 
2.5%
미르봉 1
 
2.5%
영봉 1
 
2.5%
Other values (29) 29
72.5%
2023-12-12T15:46:49.556199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 25
20.5%
봉 14
 
11.5%
5
 
4.1%
동 4
 
3.3%
성 3
 
2.5%
등 3
 
2.5%
당 2
 
1.6%
치 2
 
1.6%
두 2
 
1.6%
하 2
 
1.6%
Other values (51) 60
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 117
95.9%
Space Separator 5
 
4.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 25
21.4%
봉 14
 
12.0%
동 4
 
3.4%
성 3
 
2.6%
등 3
 
2.6%
당 2
 
1.7%
치 2
 
1.7%
두 2
 
1.7%
하 2
 
1.7%
재 2
 
1.7%
Other values (50) 58
49.6%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 117
95.9%
Common 5
 
4.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 25
21.4%
봉 14
 
12.0%
동 4
 
3.4%
성 3
 
2.6%
등 3
 
2.6%
당 2
 
1.7%
치 2
 
1.7%
두 2
 
1.7%
하 2
 
1.7%
재 2
 
1.7%
Other values (50) 58
49.6%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 117
95.9%
ASCII 5
 
4.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 25
21.4%
봉 14
 
12.0%
동 4
 
3.4%
성 3
 
2.6%
등 3
 
2.6%
당 2
 
1.7%
치 2
 
1.7%
두 2
 
1.7%
하 2
 
1.7%
재 2
 
1.7%
Other values (50) 58
49.6%
ASCII
ValueCountFrequency (%)
5
100.0%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
제천시
35 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제천시 35
100.0%

Length

2023-12-12T15:46:49.726814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:46:49.852162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제천시 35
100.0%

읍면동
Categorical

Distinct14
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
백운면
7 
한수면
6 
금성면
4 
청풍면
3 
제천시
2 
Other values (9)
13 

Length

Max length4
Median length3
Mean length3.2
Min length3

Unique

Unique5 ?
Unique (%)14.3%

Sample

1st row제천시
2nd row봉양읍
3rd row송학면
4th row송학면
5th row제천시

Common Values

ValueCountFrequency (%)
백운면 7
20.0%
한수면 6
17.1%
금성면 4
11.4%
청풍면 3
8.6%
제천시 2
 
5.7%
송학면 2
 
5.7%
청풍면 2
 
5.7%
봉양읍 2
 
5.7%
모산동 2
 
5.7%
봉양읍 1
 
2.9%
Other values (4) 4
11.4%

Length

2023-12-12T15:46:49.985395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
백운면 7
20.0%
한수면 6
17.1%
금성면 5
14.3%
청풍면 5
14.3%
봉양읍 3
8.6%
제천시 2
 
5.7%
송학면 2
 
5.7%
모산동 2
 
5.7%
용두동 1
 
2.9%
신백동 1
 
2.9%

등산로
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-12T15:46:50.210690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length7
Mean length7.4857143
Min length6

Characters and Unicode

Total characters262
Distinct characters62
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

Unique35 ?
Unique (%)100.0%

Sample

1st row용두산 등산로
2nd row감악산 등산로
3rd row송학산 등산로
4th row무등 왕박산 등산로
5th row까치봉 백곡산 등산로
ValueCountFrequency (%)
등산로 35
46.7%
뒷산 2
 
2.7%
용두산 1
 
1.3%
영봉 1
 
1.3%
만수봉 1
 
1.3%
마폐봉 1
 
1.3%
백운산 1
 
1.3%
십자봉 1
 
1.3%
삼봉산 1
 
1.3%
봉황산 1
 
1.3%
Other values (30) 30
40.0%
2023-12-12T15:46:50.584686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 60
22.9%
40
15.3%
등 38
14.5%
로 35
13.4%
봉 14
 
5.3%
동 4
 
1.5%
성 3
 
1.1%
마 2
 
0.8%
치 2
 
0.8%
두 2
 
0.8%
Other values (52) 62
23.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 222
84.7%
Space Separator 40
 
15.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 60
27.0%
등 38
17.1%
로 35
15.8%
봉 14
 
6.3%
동 4
 
1.8%
성 3
 
1.4%
마 2
 
0.9%
치 2
 
0.9%
두 2
 
0.9%
하 2
 
0.9%
Other values (51) 60
27.0%
Space Separator
ValueCountFrequency (%)
40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 222
84.7%
Common 40
 
15.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 60
27.0%
등 38
17.1%
로 35
15.8%
봉 14
 
6.3%
동 4
 
1.8%
성 3
 
1.4%
마 2
 
0.9%
치 2
 
0.9%
두 2
 
0.9%
하 2
 
0.9%
Other values (51) 60
27.0%
Common
ValueCountFrequency (%)
40
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 222
84.7%
ASCII 40
 
15.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 60
27.0%
등 38
17.1%
로 35
15.8%
봉 14
 
6.3%
동 4
 
1.8%
성 3
 
1.4%
마 2
 
0.9%
치 2
 
0.9%
두 2
 
0.9%
하 2
 
0.9%
Other values (51) 60
27.0%
ASCII
ValueCountFrequency (%)
40
100.0%

노선
Text

Distinct34
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-12T15:46:50.806149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length8.0285714
Min length5

Characters and Unicode

Total characters281
Distinct characters105
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)94.3%

Sample

1st row수련원~용담사
2nd row용두산~감악산
3rd row포전리~입석
4th row서문리~송학통불사
5th row의림지~명암저수지
ValueCountFrequency (%)
무암사~무암사 2
 
5.7%
상선암~내궁기마을 1
 
2.9%
모산동~모산동 1
 
2.9%
솔밭공원~수프리모골드빈 1
 
2.9%
제천동중학교~제천동중학교 1
 
2.9%
동명초등학교~현진에버빌 1
 
2.9%
미륵리~하늘재 1
 
2.9%
창도리~운학리,차도리 1
 
2.9%
하늘재,만수교~만수봉 1
 
2.9%
연곡리~대류 1
 
2.9%
Other values (24) 24
68.6%
2023-12-12T15:46:51.202020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
~ 36
 
12.8%
리 21
 
7.5%
학 9
 
3.2%
사 8
 
2.8%
동 8
 
2.8%
산 7
 
2.5%
전 7
 
2.5%
지 7
 
2.5%
암 6
 
2.1%
교 6
 
2.1%
Other values (95) 166
59.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 242
86.1%
Math Symbol 36
 
12.8%
Other Punctuation 3
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 21
 
8.7%
학 9
 
3.7%
사 8
 
3.3%
동 8
 
3.3%
산 7
 
2.9%
전 7
 
2.9%
지 7
 
2.9%
암 6
 
2.5%
교 6
 
2.5%
수 6
 
2.5%
Other values (93) 157
64.9%
Math Symbol
ValueCountFrequency (%)
~ 36
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 242
86.1%
Common 39
 
13.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 21
 
8.7%
학 9
 
3.7%
사 8
 
3.3%
동 8
 
3.3%
산 7
 
2.9%
전 7
 
2.9%
지 7
 
2.9%
암 6
 
2.5%
교 6
 
2.5%
수 6
 
2.5%
Other values (93) 157
64.9%
Common
ValueCountFrequency (%)
~ 36
92.3%
, 3
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 242
86.1%
ASCII 39
 
13.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
~ 36
92.3%
, 3
 
7.7%
Hangul
ValueCountFrequency (%)
리 21
 
8.7%
학 9
 
3.7%
사 8
 
3.3%
동 8
 
3.3%
산 7
 
2.9%
전 7
 
2.9%
지 7
 
2.9%
암 6
 
2.5%
교 6
 
2.5%
수 6
 
2.5%
Other values (93) 157
64.9%

거리
Real number (ℝ)

Distinct16
Distinct (%)45.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.9885714
Minimum1.9
Maximum14.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-12T15:46:51.336156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9
5-th percentile1.97
Q15
median7
Q38.5
95-th percentile12.15
Maximum14.4
Range12.5
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation3.2996231
Coefficient of variation (CV)0.47214558
Kurtosis-0.43187155
Mean6.9885714
Median Absolute Deviation (MAD)2
Skewness0.28443
Sum244.6
Variance10.887513
MonotonicityNot monotonic
2023-12-12T15:46:51.463790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
8.0 6
17.1%
6.0 4
11.4%
7.0 4
11.4%
5.0 3
8.6%
12.0 3
8.6%
4.0 2
 
5.7%
1.9 2
 
5.7%
9.0 2
 
5.7%
2.0 2
 
5.7%
2.3 1
 
2.9%
Other values (6) 6
17.1%
ValueCountFrequency (%)
1.9 2
 
5.7%
2.0 2
 
5.7%
2.3 1
 
2.9%
3.5 1
 
2.9%
4.0 2
 
5.7%
5.0 3
8.6%
6.0 4
11.4%
6.1 1
 
2.9%
7.0 4
11.4%
8.0 6
17.1%
ValueCountFrequency (%)
14.4 1
 
2.9%
12.5 1
 
2.9%
12.0 3
8.6%
11.0 1
 
2.9%
10.0 1
 
2.9%
9.0 2
 
5.7%
8.0 6
17.1%
7.0 4
11.4%
6.1 1
 
2.9%
6.0 4
11.4%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
Minimum2023-09-25 00:00:00
Maximum2023-09-25 00:00:00
2023-12-12T15:46:51.583906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:51.668947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T15:46:47.855810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:47.627290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:47.972254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:47.740034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:46:51.746389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번산명읍면동등산로노선거리
연번1.0001.0000.8351.0001.0000.520
산명1.0001.0001.0001.0001.0001.000
읍면동0.8351.0001.0001.0001.0000.741
등산로1.0001.0001.0001.0001.0001.000
노선1.0001.0001.0001.0001.0001.000
거리0.5201.0000.7411.0001.0001.000
2023-12-12T15:46:51.860845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번거리읍면동
연번1.000-0.2640.473
거리-0.2641.0000.362
읍면동0.4730.3621.000

Missing values

2023-12-12T15:46:48.106320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:46:48.249449image/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

연번산명시군구읍면동등산로노선거리데이터기준일자
01용두산제천시제천시용두산 등산로수련원~용담사4.02023-09-25
12감악산제천시봉양읍감악산 등산로용두산~감악산10.02023-09-25
23송학산제천시송학면송학산 등산로포전리~입석6.02023-09-25
34무등 왕박산제천시송학면무등 왕박산 등산로서문리~송학통불사5.02023-09-25
45까치봉 백곡산제천시제천시까치봉 백곡산 등산로의림지~명암저수지8.02023-09-25
56마당재산제천시금성면마당재산 등산로포전~포전6.02023-09-25
67당두산제천시금성면당두산 등산로중전~중전5.02023-09-25
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