Overview

Dataset statistics

Number of variables6
Number of observations241
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.1 KiB
Average record size in memory51.5 B

Variable types

Numeric3
Categorical2
Text1

Dataset

Description한국도로공사 고속도로 졸음쉼터 설치현황에 대한 데이터입니다. (번호, 설치년도, 노선, 이정, 방향, 명칭) 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15043710/fileData.do

Alerts

번호 is highly overall correlated with 노선High correlation
노선 is highly overall correlated with 번호 and 1 other fieldsHigh correlation
방향 is highly overall correlated with 노선High correlation
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-13 00:47:05.786137
Analysis finished2023-12-13 00:47:06.806528
Duration1.02 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct241
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean121
Minimum1
Maximum241
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-13T09:47:06.860662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13
Q161
median121
Q3181
95-th percentile229
Maximum241
Range240
Interquartile range (IQR)120

Descriptive statistics

Standard deviation69.714896
Coefficient of variation (CV)0.57615616
Kurtosis-1.2
Mean121
Median Absolute Deviation (MAD)60
Skewness0
Sum29161
Variance4860.1667
MonotonicityStrictly increasing
2023-12-13T09:47:06.961414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
182 1
 
0.4%
154 1
 
0.4%
155 1
 
0.4%
156 1
 
0.4%
157 1
 
0.4%
158 1
 
0.4%
159 1
 
0.4%
160 1
 
0.4%
161 1
 
0.4%
Other values (231) 231
95.9%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
241 1
0.4%
240 1
0.4%
239 1
0.4%
238 1
0.4%
237 1
0.4%
236 1
0.4%
235 1
0.4%
234 1
0.4%
233 1
0.4%
232 1
0.4%

설치년도
Real number (ℝ)

Distinct12
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2014.0498
Minimum2011
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-13T09:47:07.048679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2011
5-th percentile2011
Q12012
median2013
Q32015
95-th percentile2021
Maximum2022
Range11
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.8616738
Coefficient of variation (CV)0.0014208555
Kurtosis0.97757901
Mean2014.0498
Median Absolute Deviation (MAD)2
Skewness1.1951923
Sum485386
Variance8.189177
MonotonicityNot monotonic
2023-12-13T09:47:07.146362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2012 68
28.2%
2015 37
15.4%
2011 37
15.4%
2014 25
 
10.4%
2016 21
 
8.7%
2013 17
 
7.1%
2022 11
 
4.6%
2018 9
 
3.7%
2017 8
 
3.3%
2020 5
 
2.1%
Other values (2) 3
 
1.2%
ValueCountFrequency (%)
2011 37
15.4%
2012 68
28.2%
2013 17
 
7.1%
2014 25
 
10.4%
2015 37
15.4%
2016 21
 
8.7%
2017 8
 
3.3%
2018 9
 
3.7%
2019 1
 
0.4%
2020 5
 
2.1%
ValueCountFrequency (%)
2022 11
 
4.6%
2021 2
 
0.8%
2020 5
 
2.1%
2019 1
 
0.4%
2018 9
 
3.7%
2017 8
 
3.3%
2016 21
8.7%
2015 37
15.4%
2014 25
10.4%
2013 17
7.1%

노선
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)12.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
경부선
31 
서해안선
22 
호남선
18 
중부내륙선
17 
영동선
16 
Other values (25)
137 

Length

Max length12
Median length11
Mean length4.8589212
Min length3

Unique

Unique3 ?
Unique (%)1.2%

Sample

1st row수도권제1순환선
2nd row수도권제1순환선
3rd row수도권제1순환선
4th row수도권제1순환선
5th row서해안선

Common Values

ValueCountFrequency (%)
경부선 31
12.9%
서해안선 22
 
9.1%
호남선 18
 
7.5%
중부내륙선 17
 
7.1%
영동선 16
 
6.6%
통영대전선 16
 
6.6%
중앙선 15
 
6.2%
중부선 13
 
5.4%
남해선(순천부산) 12
 
5.0%
당진영덕선(청주영덕) 11
 
4.6%
Other values (20) 70
29.0%

Length

2023-12-13T09:47:07.252265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경부선 31
12.9%
서해안선 22
 
9.1%
호남선 18
 
7.5%
중부내륙선 17
 
7.1%
영동선 16
 
6.6%
통영대전선 16
 
6.6%
중앙선 15
 
6.2%
중부선 13
 
5.4%
남해선(순천부산 12
 
5.0%
당진영덕선(청주영덕 11
 
4.6%
Other values (20) 70
29.0%

이정
Real number (ℝ)

Distinct189
Distinct (%)78.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean134.01988
Minimum1.4
Maximum379.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-13T09:47:07.368684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.4
5-th percentile10.8
Q143.2
median118.9
Q3189.9
95-th percentile345.1
Maximum379.6
Range378.2
Interquartile range (IQR)146.7

Descriptive statistics

Standard deviation102.93088
Coefficient of variation (CV)0.76802695
Kurtosis-0.5115156
Mean134.01988
Median Absolute Deviation (MAD)75.7
Skewness0.68350629
Sum32298.79
Variance10594.765
MonotonicityNot monotonic
2023-12-13T09:47:07.474703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
43.2 3
 
1.2%
10.8 3
 
1.2%
109.3 2
 
0.8%
126.7 2
 
0.8%
2.0 2
 
0.8%
168.4 2
 
0.8%
214.6 2
 
0.8%
49.1 2
 
0.8%
124.6 2
 
0.8%
76.0 2
 
0.8%
Other values (179) 219
90.9%
ValueCountFrequency (%)
1.4 1
 
0.4%
2.0 2
0.8%
4.0 2
0.8%
5.1 1
 
0.4%
8.8 1
 
0.4%
9.8 1
 
0.4%
9.97 1
 
0.4%
10.5 1
 
0.4%
10.8 3
1.2%
11.2 1
 
0.4%
ValueCountFrequency (%)
379.6 2
0.8%
371.8 1
0.4%
366.8 1
0.4%
361.1 1
0.4%
355.0 1
0.4%
353.4 1
0.4%
353.3 1
0.4%
351.8 2
0.8%
350.4 1
0.4%
346.0 1
0.4%

방향
Categorical

HIGH CORRELATION 

Distinct45
Distinct (%)18.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
서울
32 
부산
28 
통영
15 
순천
15 
하남
14 
Other values (40)
137 

Length

Max length3
Median length2
Mean length2.0082988
Min length2

Unique

Unique12 ?
Unique (%)5.0%

Sample

1st row내측
2nd row외측
3rd row내측
4th row외측
5th row서울

Common Values

ValueCountFrequency (%)
서울 32
 
13.3%
부산 28
 
11.6%
통영 15
 
6.2%
순천 15
 
6.2%
하남 14
 
5.8%
목포 11
 
4.6%
천안 10
 
4.1%
강릉 9
 
3.7%
양평 8
 
3.3%
춘천 8
 
3.3%
Other values (35) 91
37.8%

Length

2023-12-13T09:47:07.578668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울 32
 
13.3%
부산 28
 
11.6%
통영 15
 
6.2%
순천 15
 
6.2%
하남 14
 
5.8%
목포 11
 
4.6%
천안 10
 
4.1%
강릉 9
 
3.7%
양평 8
 
3.3%
춘천 8
 
3.3%
Other values (35) 91
37.8%

명칭
Text

Distinct161
Distinct (%)66.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-13T09:47:07.859684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.1784232
Min length2

Characters and Unicode

Total characters525
Distinct characters140
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

Unique81 ?
Unique (%)33.6%

Sample

1st row김포
2nd row김포
3rd row시흥
4th row시흥
5th row서서울
ValueCountFrequency (%)
김포 2
 
0.8%
창원 2
 
0.8%
곤양 2
 
0.8%
주암 2
 
0.8%
태령 2
 
0.8%
장성물류 2
 
0.8%
삼기 2
 
0.8%
장성 2
 
0.8%
서천 2
 
0.8%
춘장대 2
 
0.8%
Other values (151) 221
91.7%
2023-12-13T09:47:08.237479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 25
 
4.8%
주 17
 
3.2%
천 15
 
2.9%
양 15
 
2.9%
서 15
 
2.9%
대 14
 
2.7%
성 14
 
2.7%
진 11
 
2.1%
남 11
 
2.1%
금 11
 
2.1%
Other values (130) 377
71.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 525
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 25
 
4.8%
주 17
 
3.2%
천 15
 
2.9%
양 15
 
2.9%
서 15
 
2.9%
대 14
 
2.7%
성 14
 
2.7%
진 11
 
2.1%
남 11
 
2.1%
금 11
 
2.1%
Other values (130) 377
71.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 525
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 25
 
4.8%
주 17
 
3.2%
천 15
 
2.9%
양 15
 
2.9%
서 15
 
2.9%
대 14
 
2.7%
성 14
 
2.7%
진 11
 
2.1%
남 11
 
2.1%
금 11
 
2.1%
Other values (130) 377
71.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 525
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 25
 
4.8%
주 17
 
3.2%
천 15
 
2.9%
양 15
 
2.9%
서 15
 
2.9%
대 14
 
2.7%
성 14
 
2.7%
진 11
 
2.1%
남 11
 
2.1%
금 11
 
2.1%
Other values (130) 377
71.8%

Interactions

2023-12-13T09:47:06.461378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:06.070363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:06.269850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:06.535268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:06.132792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:06.335535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:06.612577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:06.202977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:06.395552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T09:47:08.316687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호설치년도노선이정방향
번호1.0000.5830.9260.7170.825
설치년도0.5831.0000.8310.4410.755
노선0.9260.8311.0000.6360.995
이정0.7170.4410.6361.0000.000
방향0.8250.7550.9950.0001.000
2023-12-13T09:47:08.400442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
방향노선
방향1.0000.802
노선0.8021.000
2023-12-13T09:47:08.471743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호설치년도이정노선방향
번호1.000-0.045-0.3210.5770.428
설치년도-0.0451.000-0.2680.4560.351
이정-0.321-0.2681.0000.2430.000
노선0.5770.4560.2431.0000.802
방향0.4280.3510.0000.8021.000

Missing values

2023-12-13T09:47:06.701224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:47:06.776759image/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

번호설치년도노선이정방향명칭
012015수도권제1순환선76.0내측김포
122015수도권제1순환선77.0외측김포
232015수도권제1순환선95.8내측시흥
342015수도권제1순환선95.8외측시흥
452015서해안선327.5서울서서울
562015서해안선327.5목포서서울
672017영동선10.5인천군자
782013영동선30.2강릉이목
892014영동선45.1강릉용인
9102011서해안선293.4목포향남
번호설치년도노선이정방향명칭
2312322015중부내륙선36.0창원창녕
2322332012통영대전선39.8통영금곡
2332342015통영대전선39.6하남금곡
2342352015통영대전선16.0통영고성
2352362014통영대전선16.0하남고성
2362372018경부선61.8서울내남
2372382018경부선43.2부산언양
2382392012경부선37.5서울삼남
2392402015경부선13.8부산양산
2402412014경부선13.7서울양산