Overview

Dataset statistics

Number of variables21
Number of observations231
Missing cells924
Missing cells (%)19.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory39.6 KiB
Average record size in memory175.6 B

Variable types

Text5
Categorical8
Numeric4
Unsupported3
Boolean1

Dataset

Description공공데이터 제공 표준데이터 속성정보(허용값, 표현형식/단위 등)는 [공공데이터 제공 표준] 전문을 참고하시기 바랍니다.(공공데이터포털>정보공유>자료실) 졸음쉼터 일괄 제공정보는 한국도로공사를 확인 바랍니다. 링크 : http://data.ex.co.kr/dataset/datasetList/list?pn=0&keyWord=%EC%A1%B8%EC%9D%8C%EC%89%BC%ED%84%B0
Author한국도로공사
URLhttps://www.data.go.kr/data/15028203/standard.do

Alerts

도로종류 has constant value ""Constant
데이터기준일자 has constant value ""Constant
제공기관코드 has constant value ""Constant
제공기관명 has constant value ""Constant
화장실유무 is highly imbalanced (92.8%)Imbalance
소재지도로명주소 has 229 (99.1%) missing valuesMissing
총연장 has 231 (100.0%) missing valuesMissing
방범용CCTV수 has 231 (100.0%) missing valuesMissing
기타편의시설 has 231 (100.0%) missing valuesMissing
총연장 is an unsupported type, check if it needs cleaning or further analysisUnsupported
방범용CCTV수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기타편의시설 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-15 00:21:17.811644
Analysis finished2024-03-15 00:21:18.444120
Duration0.63 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

졸음쉼터명
Text

Distinct154
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-03-15T09:21:19.737581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.1774892
Min length2

Characters and Unicode

Total characters503
Distinct characters136
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

Unique77 ?
Unique (%)33.3%

Sample

1st row일죽
2nd row대소
3rd row진천
4th row농다리
5th row오창
ValueCountFrequency (%)
일죽 2
 
0.9%
안평 2
 
0.9%
진례 2
 
0.9%
김해 2
 
0.9%
일광 2
 
0.9%
죽령 2
 
0.9%
남상 2
 
0.9%
명곡 2
 
0.9%
강진 2
 
0.9%
칠곡 2
 
0.9%
Other values (144) 211
91.3%
2024-03-15T09:21:21.705983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 24
 
4.8%
주 16
 
3.2%
서 15
 
3.0%
천 15
 
3.0%
대 14
 
2.8%
성 14
 
2.8%
양 14
 
2.8%
금 11
 
2.2%
진 11
 
2.2%
남 10
 
2.0%
Other values (126) 359
71.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 503
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 24
 
4.8%
주 16
 
3.2%
서 15
 
3.0%
천 15
 
3.0%
대 14
 
2.8%
성 14
 
2.8%
양 14
 
2.8%
금 11
 
2.2%
진 11
 
2.2%
남 10
 
2.0%
Other values (126) 359
71.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 503
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 24
 
4.8%
주 16
 
3.2%
서 15
 
3.0%
천 15
 
3.0%
대 14
 
2.8%
성 14
 
2.8%
양 14
 
2.8%
금 11
 
2.2%
진 11
 
2.2%
남 10
 
2.0%
Other values (126) 359
71.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 503
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 24
 
4.8%
주 16
 
3.2%
서 15
 
3.0%
천 15
 
3.0%
대 14
 
2.8%
성 14
 
2.8%
양 14
 
2.8%
금 11
 
2.2%
진 11
 
2.2%
남 10
 
2.0%
Other values (126) 359
71.4%

시도명
Categorical

Distinct14
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
경기도
38 
경상북도
37 
경상남도
29 
충청북도
24 
전북특별자치도
21 
Other values (9)
82 

Length

Max length7
Median length4
Mean length4.4848485
Min length3

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row경기도
2nd row충청북도
3rd row충청북도
4th row충청북도
5th row충청북도

Common Values

ValueCountFrequency (%)
경기도 38
16.5%
경상북도 37
16.0%
경상남도 29
12.6%
충청북도 24
10.4%
전북특별자치도 21
9.1%
강원특별자치도 21
9.1%
충청남도 20
8.7%
전라남도 19
8.2%
대전광역시 6
 
2.6%
대구광역시 6
 
2.6%
Other values (4) 10
 
4.3%

Length

2024-03-15T09:21:21.984028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 38
16.5%
경상북도 37
16.0%
경상남도 29
12.6%
충청북도 24
10.4%
전북특별자치도 21
9.1%
강원특별자치도 21
9.1%
충청남도 20
8.7%
전라남도 19
8.2%
대전광역시 6
 
2.6%
대구광역시 6
 
2.6%
Other values (4) 10
 
4.3%

시군구명
Text

Distinct90
Distinct (%)39.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-03-15T09:21:23.156151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.961039
Min length2

Characters and Unicode

Total characters684
Distinct characters79
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

Unique20 ?
Unique (%)8.7%

Sample

1st row안성시
2nd row음성군
3rd row진천군
4th row진천군
5th row청주시
ValueCountFrequency (%)
광주시 6
 
2.6%
여주시 6
 
2.6%
김천시 6
 
2.6%
정읍시 5
 
2.2%
구미시 5
 
2.2%
충주시 5
 
2.2%
북구 5
 
2.2%
장성군 4
 
1.7%
보령시 4
 
1.7%
횡성군 4
 
1.7%
Other values (80) 181
78.4%
2024-03-15T09:21:24.703423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 127
18.6%
군 92
 
13.5%
주 45
 
6.6%
천 36
 
5.3%
성 28
 
4.1%
구 20
 
2.9%
양 20
 
2.9%
산 16
 
2.3%
김 14
 
2.0%
진 13
 
1.9%
Other values (69) 273
39.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 684
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 127
18.6%
군 92
 
13.5%
주 45
 
6.6%
천 36
 
5.3%
성 28
 
4.1%
구 20
 
2.9%
양 20
 
2.9%
산 16
 
2.3%
김 14
 
2.0%
진 13
 
1.9%
Other values (69) 273
39.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 684
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 127
18.6%
군 92
 
13.5%
주 45
 
6.6%
천 36
 
5.3%
성 28
 
4.1%
구 20
 
2.9%
양 20
 
2.9%
산 16
 
2.3%
김 14
 
2.0%
진 13
 
1.9%
Other values (69) 273
39.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 684
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 127
18.6%
군 92
 
13.5%
주 45
 
6.6%
천 36
 
5.3%
성 28
 
4.1%
구 20
 
2.9%
양 20
 
2.9%
산 16
 
2.3%
김 14
 
2.0%
진 13
 
1.9%
Other values (69) 273
39.9%

도로종류
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
고속국도
231 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
고속국도 231
100.0%

Length

2024-03-15T09:21:25.119718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T09:21:25.460517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고속국도 231
100.0%

도로노선명
Categorical

Distinct28
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
경부선
30 
서해안선
22 
호남선
18 
중부내륙선
17 
통영대전선
16 
Other values (23)
128 

Length

Max length9
Median length8
Mean length4.1341991
Min length3

Unique

Unique3 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
경부선 30
13.0%
서해안선 22
 
9.5%
호남선 18
 
7.8%
중부내륙선 17
 
7.4%
통영대전선 16
 
6.9%
영동선 16
 
6.9%
중앙선 15
 
6.5%
중부선 13
 
5.6%
남해선 12
 
5.2%
청주영덕선 10
 
4.3%
Other values (18) 62
26.8%

Length

2024-03-15T09:21:25.794355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경부선 30
13.0%
서해안선 22
 
9.5%
호남선 18
 
7.8%
중부내륙선 17
 
7.4%
통영대전선 16
 
6.9%
영동선 16
 
6.9%
중앙선 15
 
6.5%
중부선 13
 
5.6%
남해선 12
 
5.2%
청주영덕선 10
 
4.3%
Other values (18) 62
26.8%

도로노선번호
Real number (ℝ)

Distinct24
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.619048
Minimum1
Maximum700
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-03-15T09:21:26.127731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q115
median35
Q350
95-th percentile251
Maximum700
Range699
Interquartile range (IQR)35

Descriptive statistics

Standard deviation113.25851
Coefficient of variation (CV)1.8997034
Kurtosis20.312501
Mean59.619048
Median Absolute Deviation (MAD)20
Skewness4.3485831
Sum13772
Variance12827.489
MonotonicityNot monotonic
2024-03-15T09:21:26.523971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 30
13.0%
35 29
12.6%
15 22
9.5%
25 18
 
7.8%
45 17
 
7.4%
50 16
 
6.9%
55 15
 
6.5%
10 15
 
6.5%
30 11
 
4.8%
40 7
 
3.0%
Other values (14) 51
22.1%
ValueCountFrequency (%)
1 30
13.0%
10 15
6.5%
12 6
 
2.6%
15 22
9.5%
16 2
 
0.9%
20 5
 
2.2%
25 18
7.8%
30 11
 
4.8%
35 29
12.6%
37 2
 
0.9%
ValueCountFrequency (%)
700 4
1.7%
600 2
 
0.9%
300 1
 
0.4%
253 4
1.7%
251 6
2.6%
151 2
 
0.9%
102 2
 
0.9%
100 7
3.0%
65 3
1.3%
60 5
2.2%

도로노선방향
Text

Distinct52
Distinct (%)22.5%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-03-15T09:21:27.424491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length11.099567
Min length10

Characters and Unicode

Total characters2564
Distinct characters64
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

Unique16 ?
Unique (%)6.9%

Sample

1st row통영기점 + 하남종점
2nd row통영기점 + 하남종점
3rd row통영기점 + 하남종점
4th row하남기점 + 통영종점
5th row하남기점 + 통영종점
ValueCountFrequency (%)
231
33.3%
부산기점 29
 
4.2%
서울종점 29
 
4.2%
서울기점 28
 
4.0%
부산종점 28
 
4.0%
순천기점 19
 
2.7%
통영기점 16
 
2.3%
하남종점 16
 
2.3%
하남기점 15
 
2.2%
통영종점 15
 
2.2%
Other values (76) 267
38.5%
2024-03-15T09:21:28.896792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 462
18.0%
462
18.0%
기 233
 
9.1%
+ 231
 
9.0%
종 231
 
9.0%
천 91
 
3.5%
산 78
 
3.0%
서 64
 
2.5%
울 59
 
2.3%
부 57
 
2.2%
Other values (54) 596
23.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1871
73.0%
Space Separator 462
 
18.0%
Math Symbol 231
 
9.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 462
24.7%
기 233
12.5%
종 231
12.3%
천 91
 
4.9%
산 78
 
4.2%
서 64
 
3.4%
울 59
 
3.2%
부 57
 
3.0%
영 44
 
2.4%
순 33
 
1.8%
Other values (52) 519
27.7%
Space Separator
ValueCountFrequency (%)
462
100.0%
Math Symbol
ValueCountFrequency (%)
+ 231
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1871
73.0%
Common 693
 
27.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 462
24.7%
기 233
12.5%
종 231
12.3%
천 91
 
4.9%
산 78
 
4.2%
서 64
 
3.4%
울 59
 
3.2%
부 57
 
3.0%
영 44
 
2.4%
순 33
 
1.8%
Other values (52) 519
27.7%
Common
ValueCountFrequency (%)
462
66.7%
+ 231
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1871
73.0%
ASCII 693
 
27.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 462
24.7%
기 233
12.5%
종 231
12.3%
천 91
 
4.9%
산 78
 
4.2%
서 64
 
3.4%
울 59
 
3.2%
부 57
 
3.0%
영 44
 
2.4%
순 33
 
1.8%
Other values (52) 519
27.7%
ASCII
ValueCountFrequency (%)
462
66.7%
+ 231
33.3%

소재지도로명주소
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing229
Missing (%)99.1%
Memory size1.9 KiB
2024-03-15T09:21:29.497443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19.5
Mean length19.5
Min length17

Characters and Unicode

Total characters39
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row경기도 시흥시 군자로335번길 36-29
2nd row경기도 의왕시 안양판교로 476
ValueCountFrequency (%)
경기도 2
25.0%
시흥시 1
12.5%
군자로335번길 1
12.5%
36-29 1
12.5%
의왕시 1
12.5%
안양판교로 1
12.5%
476 1
12.5%
2024-03-15T09:21:30.495427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
 
15.4%
시 3
 
7.7%
3 3
 
7.7%
경 2
 
5.1%
도 2
 
5.1%
로 2
 
5.1%
기 2
 
5.1%
6 2
 
5.1%
9 1
 
2.6%
4 1
 
2.6%
Other values (15) 15
38.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22
56.4%
Decimal Number 10
25.6%
Space Separator 6
 
15.4%
Dash Punctuation 1
 
2.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 3
13.6%
경 2
 
9.1%
도 2
 
9.1%
로 2
 
9.1%
기 2
 
9.1%
교 1
 
4.5%
판 1
 
4.5%
양 1
 
4.5%
안 1
 
4.5%
왕 1
 
4.5%
Other values (6) 6
27.3%
Decimal Number
ValueCountFrequency (%)
3 3
30.0%
6 2
20.0%
9 1
 
10.0%
4 1
 
10.0%
2 1
 
10.0%
5 1
 
10.0%
7 1
 
10.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22
56.4%
Common 17
43.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 3
13.6%
경 2
 
9.1%
도 2
 
9.1%
로 2
 
9.1%
기 2
 
9.1%
교 1
 
4.5%
판 1
 
4.5%
양 1
 
4.5%
안 1
 
4.5%
왕 1
 
4.5%
Other values (6) 6
27.3%
Common
ValueCountFrequency (%)
6
35.3%
3 3
17.6%
6 2
 
11.8%
9 1
 
5.9%
4 1
 
5.9%
2 1
 
5.9%
- 1
 
5.9%
5 1
 
5.9%
7 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22
56.4%
ASCII 17
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
35.3%
3 3
17.6%
6 2
 
11.8%
9 1
 
5.9%
4 1
 
5.9%
2 1
 
5.9%
- 1
 
5.9%
5 1
 
5.9%
7 1
 
5.9%
Hangul
ValueCountFrequency (%)
시 3
13.6%
경 2
 
9.1%
도 2
 
9.1%
로 2
 
9.1%
기 2
 
9.1%
교 1
 
4.5%
판 1
 
4.5%
양 1
 
4.5%
안 1
 
4.5%
왕 1
 
4.5%
Other values (6) 6
27.3%

소재지지번주소
Text

Distinct212
Distinct (%)92.6%
Missing2
Missing (%)0.9%
Memory size1.9 KiB
2024-03-15T09:21:32.070955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24
Mean length21.554585
Min length14

Characters and Unicode

Total characters4936
Distinct characters207
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique195 ?
Unique (%)85.2%

Sample

1st row경기도 안성시 일죽면 월정리 755
2nd row충청북도 음성군 대소면 오류리 208-7
3rd row충청북도 진천군 초평면 중석리 1215
4th row충청북도 진천군 문백면 구곡리 87
5th row충청북도 청주시 청원구 오창읍 주성리 15-6
ValueCountFrequency (%)
경상북도 37
 
3.3%
경기도 35
 
3.1%
경상남도 29
 
2.6%
충청북도 25
 
2.2%
전북특별자치도 21
 
1.9%
강원특별자치도 21
 
1.9%
충청남도 20
 
1.8%
전라남도 19
 
1.7%
대전광역시 6
 
0.5%
여주시 6
 
0.5%
Other values (590) 895
80.3%
2024-03-15T09:21:33.792873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
885
 
17.9%
도 214
 
4.3%
리 188
 
3.8%
- 172
 
3.5%
1 167
 
3.4%
면 147
 
3.0%
시 146
 
3.0%
산 115
 
2.3%
2 112
 
2.3%
경 110
 
2.2%
Other values (197) 2680
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3063
62.1%
Space Separator 885
 
17.9%
Decimal Number 816
 
16.5%
Dash Punctuation 172
 
3.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 214
 
7.0%
리 188
 
6.1%
면 147
 
4.8%
시 146
 
4.8%
산 115
 
3.8%
경 110
 
3.6%
북 101
 
3.3%
군 95
 
3.1%
남 90
 
2.9%
상 85
 
2.8%
Other values (185) 1772
57.9%
Decimal Number
ValueCountFrequency (%)
1 167
20.5%
2 112
13.7%
3 90
11.0%
5 83
10.2%
4 79
9.7%
6 72
8.8%
8 64
 
7.8%
9 56
 
6.9%
7 52
 
6.4%
0 41
 
5.0%
Space Separator
ValueCountFrequency (%)
885
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 172
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3063
62.1%
Common 1873
37.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 214
 
7.0%
리 188
 
6.1%
면 147
 
4.8%
시 146
 
4.8%
산 115
 
3.8%
경 110
 
3.6%
북 101
 
3.3%
군 95
 
3.1%
남 90
 
2.9%
상 85
 
2.8%
Other values (185) 1772
57.9%
Common
ValueCountFrequency (%)
885
47.3%
- 172
 
9.2%
1 167
 
8.9%
2 112
 
6.0%
3 90
 
4.8%
5 83
 
4.4%
4 79
 
4.2%
6 72
 
3.8%
8 64
 
3.4%
9 56
 
3.0%
Other values (2) 93
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3063
62.1%
ASCII 1873
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
885
47.3%
- 172
 
9.2%
1 167
 
8.9%
2 112
 
6.0%
3 90
 
4.8%
5 83
 
4.4%
4 79
 
4.2%
6 72
 
3.8%
8 64
 
3.4%
9 56
 
3.0%
Other values (2) 93
 
5.0%
Hangul
ValueCountFrequency (%)
도 214
 
7.0%
리 188
 
6.1%
면 147
 
4.8%
시 146
 
4.8%
산 115
 
3.8%
경 110
 
3.6%
북 101
 
3.3%
군 95
 
3.1%
남 90
 
2.9%
상 85
 
2.8%
Other values (185) 1772
57.9%

위도
Real number (ℝ)

Distinct215
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.313152
Minimum34.686562
Maximum38.119539
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-03-15T09:21:34.146886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.686562
5-th percentile35.054552
Q135.604802
median36.210985
Q337.073985
95-th percentile37.628114
Maximum38.119539
Range3.4329774
Interquartile range (IQR)1.4691827

Descriptive statistics

Standard deviation0.85000757
Coefficient of variation (CV)0.023407705
Kurtosis-1.0788567
Mean36.313152
Median Absolute Deviation (MAD)0.74116493
Skewness0.12592914
Sum8388.3382
Variance0.72251287
MonotonicityNot monotonic
2024-03-15T09:21:34.412627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.08423849 2
 
0.9%
36.90075043 2
 
0.9%
34.98175411 2
 
0.9%
34.98462117 2
 
0.9%
35.05593487 2
 
0.9%
35.24883378 2
 
0.9%
35.29233912 2
 
0.9%
35.22085404 2
 
0.9%
36.06879574 2
 
0.9%
35.26331546 2
 
0.9%
Other values (205) 211
91.3%
ValueCountFrequency (%)
34.68656192 1
0.4%
34.694235 1
0.4%
34.823812 1
0.4%
34.94576778 1
0.4%
34.95257541 1
0.4%
34.98175411 2
0.9%
34.98462117 2
0.9%
34.99606303 1
0.4%
35.05317013 2
0.9%
35.05593487 2
0.9%
ValueCountFrequency (%)
38.11953935 1
0.4%
38.1184743 1
0.4%
37.99956719 1
0.4%
37.99622926 1
0.4%
37.84347461 1
0.4%
37.84093096 1
0.4%
37.75810138 1
0.4%
37.72400902 1
0.4%
37.71175324 1
0.4%
37.6751734 1
0.4%

경도
Real number (ℝ)

Distinct215
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.73292
Minimum126.50382
Maximum129.21077
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-03-15T09:21:34.786860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.50382
5-th percentile126.67016
Q1127.11096
median127.70365
Q3128.30676
95-th percentile129.021
Maximum129.21077
Range2.7069497
Interquartile range (IQR)1.1958076

Descriptive statistics

Standard deviation0.73360986
Coefficient of variation (CV)0.0057433108
Kurtosis-1.0039264
Mean127.73292
Median Absolute Deviation (MAD)0.6024793
Skewness0.20009272
Sum29506.305
Variance0.53818342
MonotonicityNot monotonic
2024-03-15T09:21:35.160648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.4570094 2
 
0.9%
126.7184687 2
 
0.9%
128.3735157 2
 
0.9%
127.5891467 2
 
0.9%
127.2773555 2
 
0.9%
126.9283468 2
 
0.9%
129.2061941 2
 
0.9%
128.8702906 2
 
0.9%
126.747055 2
 
0.9%
128.6120097 2
 
0.9%
Other values (205) 211
91.3%
ValueCountFrequency (%)
126.5038207 1
0.4%
126.504596 1
0.4%
126.5189718 1
0.4%
126.5531285 1
0.4%
126.5583118 1
0.4%
126.5791253 1
0.4%
126.5872371 1
0.4%
126.5884265 1
0.4%
126.588515 1
0.4%
126.5929585 1
0.4%
ValueCountFrequency (%)
129.2107704 1
0.4%
129.2061941 2
0.9%
129.194721 1
0.4%
129.1747296 1
0.4%
129.1676029 1
0.4%
129.1675288 1
0.4%
129.140183 1
0.4%
129.118872 1
0.4%
129.107133 1
0.4%
129.0428034 1
0.4%

총연장
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing231
Missing (%)100.0%
Memory size2.2 KiB

주차면수
Real number (ℝ)

Distinct40
Distinct (%)17.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.142857
Minimum4
Maximum94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-03-15T09:21:35.543583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile6
Q18
median12
Q316
95-th percentile34.5
Maximum94
Range90
Interquartile range (IQR)8

Descriptive statistics

Standard deviation12.628864
Coefficient of variation (CV)0.83398157
Kurtosis17.055333
Mean15.142857
Median Absolute Deviation (MAD)4
Skewness3.644047
Sum3498
Variance159.4882
MonotonicityNot monotonic
2024-03-15T09:21:35.819630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
7 32
13.9%
6 20
 
8.7%
16 17
 
7.4%
8 17
 
7.4%
11 16
 
6.9%
14 16
 
6.9%
15 13
 
5.6%
10 12
 
5.2%
13 11
 
4.8%
9 9
 
3.9%
Other values (30) 68
29.4%
ValueCountFrequency (%)
4 1
 
0.4%
5 3
 
1.3%
6 20
8.7%
7 32
13.9%
8 17
7.4%
9 9
 
3.9%
10 12
 
5.2%
11 16
6.9%
12 7
 
3.0%
13 11
 
4.8%
ValueCountFrequency (%)
94 1
0.4%
89 1
0.4%
82 1
0.4%
81 1
0.4%
54 1
0.4%
48 1
0.4%
45 1
0.4%
44 1
0.4%
43 1
0.4%
38 1
0.4%

화장실유무
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size359.0 B
True
229 
False
 
2
ValueCountFrequency (%)
True 229
99.1%
False 2
 
0.9%
2024-03-15T09:21:36.004614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

방범용CCTV수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing231
Missing (%)100.0%
Memory size2.2 KiB

기타편의시설
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing231
Missing (%)100.0%
Memory size2.2 KiB

관리기관명
Categorical

Distinct8
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
한국도로공사 대구경상북도본부
39 
한국도로공사 부산경상남도본부
35 
한국도로공사 전북특별자치도본부
30 
한국도로공사 충청북도본부
28 
한국도로공사 강원본부
28 
Other values (3)
71 

Length

Max length18
Median length16
Mean length14.376623
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row한국도로공사 충청북도본부
2nd row한국도로공사 충청북도본부
3rd row한국도로공사 충청북도본부
4th row한국도로공사 충청북도본부
5th row한국도로공사 충청북도본부

Common Values

ValueCountFrequency (%)
한국도로공사 대구경상북도본부 39
16.9%
한국도로공사 부산경상남도본부 35
15.2%
한국도로공사 전북특별자치도본부 30
13.0%
한국도로공사 충청북도본부 28
12.1%
한국도로공사 강원본부 28
12.1%
한국도로공사 수도권본부 25
10.8%
한국도로공사 대전충청남도본부 23
10.0%
한국도로공사 광주광역시전라남도본부 23
10.0%

Length

2024-03-15T09:21:36.212446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T09:21:36.520881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한국도로공사 231
50.0%
대구경상북도본부 39
 
8.4%
부산경상남도본부 35
 
7.6%
전북특별자치도본부 30
 
6.5%
충청북도본부 28
 
6.1%
강원본부 28
 
6.1%
수도권본부 25
 
5.4%
대전충청남도본부 23
 
5.0%
광주광역시전라남도본부 23
 
5.0%

관리기관전화번호
Categorical

Distinct8
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
053-714-6000
39 
055-711-6000
35 
063-714-6000
30 
043-721-6000
28 
033-811-6000
28 
Other values (3)
71 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row043-721-6000
2nd row043-721-6000
3rd row043-721-6000
4th row043-721-6000
5th row043-721-6000

Common Values

ValueCountFrequency (%)
053-714-6000 39
16.9%
055-711-6000 35
15.2%
063-714-6000 30
13.0%
043-721-6000 28
12.1%
033-811-6000 28
12.1%
02-2219-6000 25
10.8%
042-722-6000 23
10.0%
061-883-6000 23
10.0%

Length

2024-03-15T09:21:36.875131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T09:21:37.079115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
053-714-6000 39
16.9%
055-711-6000 35
15.2%
063-714-6000 30
13.0%
043-721-6000 28
12.1%
033-811-6000 28
12.1%
02-2219-6000 25
10.8%
042-722-6000 23
10.0%
061-883-6000 23
10.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-01-19
231 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-01-19
2nd row2024-01-19
3rd row2024-01-19
4th row2024-01-19
5th row2024-01-19

Common Values

ValueCountFrequency (%)
2024-01-19 231
100.0%

Length

2024-03-15T09:21:37.327722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T09:21:37.481385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-01-19 231
100.0%

제공기관코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
B500004
231 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowB500004
2nd rowB500004
3rd rowB500004
4th rowB500004
5th rowB500004

Common Values

ValueCountFrequency (%)
B500004 231
100.0%

Length

2024-03-15T09:21:37.781874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T09:21:38.021657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
b500004 231
100.0%

제공기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
한국도로공사
231 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
한국도로공사 231
100.0%

Length

2024-03-15T09:21:38.181062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T09:21:38.560857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한국도로공사 231
100.0%

Sample

졸음쉼터명시도명시군구명도로종류도로노선명도로노선번호도로노선방향소재지도로명주소소재지지번주소위도경도총연장주차면수화장실유무방범용CCTV수기타편의시설관리기관명관리기관전화번호데이터기준일자제공기관코드제공기관명
0일죽경기도안성시고속국도중부선35통영기점 + 하남종점<NA>경기도 안성시 일죽면 월정리 75537.084238127.457009<NA>22Y<NA><NA>한국도로공사 충청북도본부043-721-60002024-01-19B500004한국도로공사
1대소충청북도음성군고속국도중부선35통영기점 + 하남종점<NA>충청북도 음성군 대소면 오류리 208-736.977074127.469281<NA>17Y<NA><NA>한국도로공사 충청북도본부043-721-60002024-01-19B500004한국도로공사
2진천충청북도진천군고속국도중부선35통영기점 + 하남종점<NA>충청북도 진천군 초평면 중석리 121536.853611127.486878<NA>19Y<NA><NA>한국도로공사 충청북도본부043-721-60002024-01-19B500004한국도로공사
3농다리충청북도진천군고속국도중부선35하남기점 + 통영종점<NA>충청북도 진천군 문백면 구곡리 8736.834656127.494039<NA>37Y<NA><NA>한국도로공사 충청북도본부043-721-60002024-01-19B500004한국도로공사
4오창충청북도청주시고속국도중부선35하남기점 + 통영종점<NA>충청북도 청주시 청원구 오창읍 주성리 15-636.7352127.456313<NA>13Y<NA><NA>한국도로공사 충청북도본부043-721-60002024-01-19B500004한국도로공사
5오창충청북도청주시고속국도중부선35통영기점 + 하남종점<NA>충청북도 청주시 청원구 오창읍 괴정리 46-136.734646127.456615<NA>14Y<NA><NA>한국도로공사 충청북도본부043-721-60002024-01-19B500004한국도로공사
6봉양충청북도제천시고속국도중앙선55부산기점 + 춘천종점<NA>충청북도 제천시 봉양읍 명암리 642-237.178504128.128943<NA>7Y<NA><NA>한국도로공사 충청북도본부043-721-60002024-01-19B500004한국도로공사
7가남경기도여주시고속국도중부내륙선45양평기점 + 창원종점<NA>경기도 여주시 가남읍 삼승리 143-137.169074127.626537<NA>16Y<NA><NA>한국도로공사 충청북도본부043-721-60002024-01-19B500004한국도로공사
8앙성충청북도충주시고속국도중부내륙선45창원기점 + 양평종점<NA>충청북도 충주시 앙성면 지당리 731-1737.099407127.715727<NA>15Y<NA><NA>한국도로공사 충청북도본부043-721-60002024-01-19B500004한국도로공사
9노은충청북도충주시고속국도중부내륙선45양평기점 + 창원종점<NA>충청북도 충주시 노은면 신효리 67937.039839127.770346<NA>8Y<NA><NA>한국도로공사 충청북도본부043-721-60002024-01-19B500004한국도로공사
졸음쉼터명시도명시군구명도로종류도로노선명도로노선번호도로노선방향소재지도로명주소소재지지번주소위도경도총연장주차면수화장실유무방범용CCTV수기타편의시설관리기관명관리기관전화번호데이터기준일자제공기관코드제공기관명
221도척경기도광주시고속국도중부선35통영기점 + 하남종점<NA>경기도 광주시 도척면 진우리 482-137.323327127.338784<NA>12Y<NA><NA>한국도로공사 수도권본부02-2219-60002024-01-19B500004한국도로공사
222상번천경기도광주시고속국도제2중부선37하남기점 + 통영종점<NA>경기도 광주시 남한산성면 상번천리 315-237.448652127.273677<NA>34Y<NA><NA>한국도로공사 수도권본부02-2219-60002024-01-19B500004한국도로공사
223상번천경기도광주시고속국도제2중부선37통영기점 + 하남종점<NA>경기도 광주시 남한산성면 상번천리 24537.447871127.275447<NA>7Y<NA><NA>한국도로공사 수도권본부02-2219-60002024-01-19B500004한국도로공사
224청계경기도의왕시고속국도서울외곽선100판교기점 + 일산종점경기도 의왕시 안양판교로 476<NA>37.39327127.02231<NA>19Y<NA><NA>한국도로공사 수도권본부02-2219-60002024-01-19B500004한국도로공사
225성남경기도성남시고속국도서울외곽선100퇴계원기점 + 구리종점<NA>경기도 성남시 수정구 수진동 3937.441191127.134719<NA>81Y<NA><NA>한국도로공사 수도권본부02-2219-60002024-01-19B500004한국도로공사
226구리남양주경기도구리시고속국도서울외곽선100판교기점 + 일산종점<NA>경기도 구리시 토평동 8637.589703127.155902<NA>89Y<NA><NA>한국도로공사 수도권본부02-2219-60002024-01-19B500004한국도로공사
227생태습지경기도여주시고속국도영동선50인천기점 + 강릉종점<NA>경기도 여주시 가남읍 안금리 9237.235266127.603842<NA>14Y<NA><NA>한국도로공사 강원본부033-811-60002024-01-19B500004한국도로공사
228적금경기도여주시고속국도영동선50강릉기점 + 인천종점<NA>경기도 여주시 강천면 적금리 26937.252854127.703654<NA>14Y<NA><NA>한국도로공사 강원본부033-811-60002024-01-19B500004한국도로공사
229적금경기도여주시고속국도영동선50인천기점 + 강릉종점<NA>경기도 여주시 강천면 적금리 588-237.258857127.7153<NA>14Y<NA><NA>한국도로공사 강원본부033-811-60002024-01-19B500004한국도로공사
230소초강원특별자치도원주시고속국도영동선50강릉기점 + 인천종점<NA>강원특별자치도 원주시 소초면 평장리 산125-437.420264128.00195<NA>24Y<NA><NA>한국도로공사 강원본부033-811-60002024-01-19B500004한국도로공사