Overview

Dataset statistics

Number of variables5
Number of observations52
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory44.5 B

Variable types

Numeric2
Text3

Dataset

Description전국 고속도로 노선에 대한 시종점 현황정보 제공(노선번호, 노선명, 시점, 종점, 공용중) 고속도로 노선번호, 고속도로 노선명, 시점, 종점, 공용중 표기
URLhttps://www.data.go.kr/data/15045541/fileData.do

Alerts

노선번호 is highly overall correlated with 공용중High correlation
공용중 is highly overall correlated with 노선번호High correlation
노선명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:02:18.491563
Analysis finished2023-12-12 18:02:19.540895
Duration1.05 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

노선번호
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)82.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean145.80769
Minimum1
Maximum700
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-13T03:02:19.632906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.1
Q126.5
median62.5
Q3179.25
95-th percentile522.95
Maximum700
Range699
Interquartile range (IQR)152.75

Descriptive statistics

Standard deviation174.65788
Coefficient of variation (CV)1.1978646
Kurtosis1.7409271
Mean145.80769
Median Absolute Deviation (MAD)47.5
Skewness1.5935083
Sum7582
Variance30505.374
MonotonicityIncreasing
2023-12-13T03:02:19.794871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
400 3
 
5.8%
12 2
 
3.8%
10 2
 
3.8%
65 2
 
3.8%
20 2
 
3.8%
25 2
 
3.8%
171 2
 
3.8%
35 2
 
3.8%
1 1
 
1.9%
251 1
 
1.9%
Other values (33) 33
63.5%
ValueCountFrequency (%)
1 1
1.9%
10 2
3.8%
12 2
3.8%
14 1
1.9%
15 1
1.9%
16 1
1.9%
17 1
1.9%
20 2
3.8%
25 2
3.8%
27 1
1.9%
ValueCountFrequency (%)
700 1
 
1.9%
600 1
 
1.9%
551 1
 
1.9%
500 1
 
1.9%
451 1
 
1.9%
400 3
5.8%
301 1
 
1.9%
300 1
 
1.9%
253 1
 
1.9%
251 1
 
1.9%

노선명
Text

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-12-13T03:02:20.076231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length6.9615385
Min length3

Characters and Unicode

Total characters362
Distinct characters82
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

Unique52 ?
Unique (%)100.0%

Sample

1st row경부선
2nd row남해선(영암~순천)
3rd row남해선(순천~부산)
4th row무안~광주선
5th row광주~대구선
ValueCountFrequency (%)
경부선 1
 
1.9%
동해선(삼척~속초 1
 
1.9%
수도권제1순환선 1
 
1.9%
남해제1지선 1
 
1.9%
남해제2지선 1
 
1.9%
남해제3지선(부산항신항선 1
 
1.9%
제2경인선 1
 
1.9%
경인선 1
 
1.9%
인천국제공항선 1
 
1.9%
서천공주선 1
 
1.9%
Other values (43) 43
81.1%
2023-12-13T03:02:20.573905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
선 57
 
15.7%
~ 20
 
5.5%
주 13
 
3.6%
천 12
 
3.3%
) 11
 
3.0%
( 11
 
3.0%
순 11
 
3.0%
제 11
 
3.0%
부 10
 
2.8%
산 9
 
2.5%
Other values (72) 197
54.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 310
85.6%
Math Symbol 20
 
5.5%
Close Punctuation 11
 
3.0%
Open Punctuation 11
 
3.0%
Decimal Number 9
 
2.5%
Space Separator 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
선 57
 
18.4%
주 13
 
4.2%
천 12
 
3.9%
순 11
 
3.5%
제 11
 
3.5%
부 10
 
3.2%
산 9
 
2.9%
환 8
 
2.6%
포 8
 
2.6%
해 8
 
2.6%
Other values (65) 163
52.6%
Decimal Number
ValueCountFrequency (%)
2 6
66.7%
1 2
 
22.2%
3 1
 
11.1%
Math Symbol
ValueCountFrequency (%)
~ 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 310
85.6%
Common 52
 
14.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
선 57
 
18.4%
주 13
 
4.2%
천 12
 
3.9%
순 11
 
3.5%
제 11
 
3.5%
부 10
 
3.2%
산 9
 
2.9%
환 8
 
2.6%
포 8
 
2.6%
해 8
 
2.6%
Other values (65) 163
52.6%
Common
ValueCountFrequency (%)
~ 20
38.5%
) 11
21.2%
( 11
21.2%
2 6
 
11.5%
1 2
 
3.8%
1
 
1.9%
3 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 310
85.6%
ASCII 52
 
14.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
선 57
 
18.4%
주 13
 
4.2%
천 12
 
3.9%
순 11
 
3.5%
제 11
 
3.5%
부 10
 
3.2%
산 9
 
2.9%
환 8
 
2.6%
포 8
 
2.6%
해 8
 
2.6%
Other values (65) 163
52.6%
ASCII
ValueCountFrequency (%)
~ 20
38.5%
) 11
21.2%
( 11
21.2%
2 6
 
11.5%
1 2
 
3.8%
1
 
1.9%
3 1
 
1.9%

시점
Text

Distinct49
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-12-13T03:02:21.031174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length23
Mean length20.346154
Min length15

Characters and Unicode

Total characters1058
Distinct characters130
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

Unique46 ?
Unique (%)88.5%

Sample

1st row부산광역시 금정구 구서동 61-11
2nd row전라남도 영암군 학산면 은곡리 299
3rd row전라남도 순천시 서면 동산리 329-2
4th row전라남도 무안군 망운면 피서리 28-2
5th row광주광역시 북구 문흥동 산65-3
ValueCountFrequency (%)
경기도 11
 
4.6%
경상남도 8
 
3.3%
전라남도 6
 
2.5%
인천광역시 5
 
2.1%
충청남도 5
 
2.1%
평택시 3
 
1.2%
순천시 3
 
1.2%
중구 3
 
1.2%
대구광역시 3
 
1.2%
전라북도 3
 
1.2%
Other values (173) 191
79.3%
2023-12-13T03:02:21.661726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
189
 
17.9%
- 45
 
4.3%
시 44
 
4.2%
1 43
 
4.1%
도 38
 
3.6%
동 31
 
2.9%
리 30
 
2.8%
2 29
 
2.7%
구 25
 
2.4%
산 25
 
2.4%
Other values (120) 559
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 624
59.0%
Decimal Number 200
 
18.9%
Space Separator 189
 
17.9%
Dash Punctuation 45
 
4.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 44
 
7.1%
도 38
 
6.1%
동 31
 
5.0%
리 30
 
4.8%
구 25
 
4.0%
산 25
 
4.0%
남 24
 
3.8%
면 21
 
3.4%
경 20
 
3.2%
광 19
 
3.0%
Other values (108) 347
55.6%
Decimal Number
ValueCountFrequency (%)
1 43
21.5%
2 29
14.5%
3 25
12.5%
8 21
10.5%
4 18
9.0%
5 18
9.0%
6 15
 
7.5%
7 12
 
6.0%
9 12
 
6.0%
0 7
 
3.5%
Space Separator
ValueCountFrequency (%)
189
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 624
59.0%
Common 434
41.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 44
 
7.1%
도 38
 
6.1%
동 31
 
5.0%
리 30
 
4.8%
구 25
 
4.0%
산 25
 
4.0%
남 24
 
3.8%
면 21
 
3.4%
경 20
 
3.2%
광 19
 
3.0%
Other values (108) 347
55.6%
Common
ValueCountFrequency (%)
189
43.5%
- 45
 
10.4%
1 43
 
9.9%
2 29
 
6.7%
3 25
 
5.8%
8 21
 
4.8%
4 18
 
4.1%
5 18
 
4.1%
6 15
 
3.5%
7 12
 
2.8%
Other values (2) 19
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 624
59.0%
ASCII 434
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
189
43.5%
- 45
 
10.4%
1 43
 
9.9%
2 29
 
6.7%
3 25
 
5.8%
8 21
 
4.8%
4 18
 
4.1%
5 18
 
4.1%
6 15
 
3.5%
7 12
 
2.8%
Other values (2) 19
 
4.4%
Hangul
ValueCountFrequency (%)
시 44
 
7.1%
도 38
 
6.1%
동 31
 
5.0%
리 30
 
4.8%
구 25
 
4.0%
산 25
 
4.0%
남 24
 
3.8%
면 21
 
3.4%
경 20
 
3.2%
광 19
 
3.0%
Other values (108) 347
55.6%

종점
Text

Distinct51
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-12-13T03:02:22.124438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length22
Mean length20.480769
Min length13

Characters and Unicode

Total characters1065
Distinct characters134
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

Unique50 ?
Unique (%)96.2%

Sample

1st row서울특별시 서초구 양재동 227-4
2nd row전라남도 순천시 해룡면 성산리 산 127-2
3rd row부산광역시 북구 덕천동 680-18
4th row광주광역시 광산구 운수동 233-13
5th row대구광역시 달성군 옥포면 본리리 656-2
ValueCountFrequency (%)
경기도 13
 
5.3%
강원도 5
 
2.0%
서울특별시 4
 
1.6%
전라북도 4
 
1.6%
경상북도 4
 
1.6%
부산광역시 3
 
1.2%
경상남도 3
 
1.2%
대구광역시 3
 
1.2%
동구 3
 
1.2%
북구 3
 
1.2%
Other values (184) 199
81.6%
2023-12-13T03:02:22.820869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
192
 
18.0%
- 46
 
4.3%
시 44
 
4.1%
도 37
 
3.5%
1 36
 
3.4%
2 29
 
2.7%
리 29
 
2.7%
동 29
 
2.7%
산 28
 
2.6%
구 24
 
2.3%
Other values (124) 571
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 628
59.0%
Decimal Number 199
 
18.7%
Space Separator 192
 
18.0%
Dash Punctuation 46
 
4.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 44
 
7.0%
도 37
 
5.9%
리 29
 
4.6%
동 29
 
4.6%
산 28
 
4.5%
구 24
 
3.8%
경 20
 
3.2%
면 19
 
3.0%
남 17
 
2.7%
광 16
 
2.5%
Other values (112) 365
58.1%
Decimal Number
ValueCountFrequency (%)
1 36
18.1%
2 29
14.6%
4 23
11.6%
3 23
11.6%
8 20
10.1%
5 15
7.5%
7 14
 
7.0%
0 14
 
7.0%
6 13
 
6.5%
9 12
 
6.0%
Space Separator
ValueCountFrequency (%)
192
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 628
59.0%
Common 437
41.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 44
 
7.0%
도 37
 
5.9%
리 29
 
4.6%
동 29
 
4.6%
산 28
 
4.5%
구 24
 
3.8%
경 20
 
3.2%
면 19
 
3.0%
남 17
 
2.7%
광 16
 
2.5%
Other values (112) 365
58.1%
Common
ValueCountFrequency (%)
192
43.9%
- 46
 
10.5%
1 36
 
8.2%
2 29
 
6.6%
4 23
 
5.3%
3 23
 
5.3%
8 20
 
4.6%
5 15
 
3.4%
7 14
 
3.2%
0 14
 
3.2%
Other values (2) 25
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 628
59.0%
ASCII 437
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
192
43.9%
- 46
 
10.5%
1 36
 
8.2%
2 29
 
6.6%
4 23
 
5.3%
3 23
 
5.3%
8 20
 
4.6%
5 15
 
3.4%
7 14
 
3.2%
0 14
 
3.2%
Other values (2) 25
 
5.7%
Hangul
ValueCountFrequency (%)
시 44
 
7.0%
도 37
 
5.9%
리 29
 
4.6%
동 29
 
4.6%
산 28
 
4.5%
구 24
 
3.8%
경 20
 
3.2%
면 19
 
3.0%
남 17
 
2.7%
광 16
 
2.5%
Other values (112) 365
58.1%

공용중
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95.030769
Minimum2.6
Maximum415.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-13T03:02:23.017415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.6
5-th percentile11.02
Q127.8
median55.5
Q3123.075
95-th percentile317.345
Maximum415.3
Range412.7
Interquartile range (IQR)95.275

Descriptive statistics

Standard deviation99.588431
Coefficient of variation (CV)1.0479598
Kurtosis2.2238355
Mean95.030769
Median Absolute Deviation (MAD)39.35
Skewness1.6526719
Sum4941.6
Variance9917.8555
MonotonicityNot monotonic
2023-12-13T03:02:23.229201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.5 2
 
3.8%
415.3 1
 
1.9%
54.0 1
 
1.9%
17.9 1
 
1.9%
20.3 1
 
1.9%
15.3 1
 
1.9%
70.0 1
 
1.9%
13.4 1
 
1.9%
61.4 1
 
1.9%
42.6 1
 
1.9%
Other values (41) 41
78.8%
ValueCountFrequency (%)
2.6 1
1.9%
6.0 1
1.9%
9.7 1
1.9%
12.1 1
1.9%
13.3 1
1.9%
13.4 1
1.9%
14.3 1
1.9%
15.3 1
1.9%
17.4 1
1.9%
17.9 1
1.9%
ValueCountFrequency (%)
415.3 1
1.9%
370.8 1
1.9%
336.1 1
1.9%
302.0 1
1.9%
278.9 1
1.9%
234.4 1
1.9%
215.3 1
1.9%
194.2 1
1.9%
171.5 1
1.9%
166.4 1
1.9%

Interactions

2023-12-13T03:02:19.163473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:18.933553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:19.286074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:19.049886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:02:23.365536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호노선명시점종점공용중
노선번호1.0001.0000.9340.8430.000
노선명1.0001.0001.0001.0001.000
시점0.9341.0001.0000.9890.854
종점0.8431.0000.9891.0000.832
공용중0.0001.0000.8540.8321.000
2023-12-13T03:02:23.482193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호공용중
노선번호1.000-0.516
공용중-0.5161.000

Missing values

2023-12-13T03:02:19.403723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:02:19.499390image/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

노선번호노선명시점종점공용중
01경부선부산광역시 금정구 구서동 61-11서울특별시 서초구 양재동 227-4415.3
110남해선(영암~순천)전라남도 영암군 학산면 은곡리 299전라남도 순천시 해룡면 성산리 산 127-2106.8
210남해선(순천~부산)전라남도 순천시 서면 동산리 329-2부산광역시 북구 덕천동 680-18166.4
312무안~광주선전라남도 무안군 망운면 피서리 28-2광주광역시 광산구 운수동 233-1341.4
412광주~대구선광주광역시 북구 문흥동 산65-3대구광역시 달성군 옥포면 본리리 656-2171.5
514함양울산선경상남도 함양군 지곡면 마산리 산18-2울산광역시 울주군 청량읍 삼정리 산186-445.0
615서해안선전라남도 무안군 삼향읍 맥포리 905서울특별시 금천구 독산동 871-45336.1
716울산선울산광역시 울주군 언양읍 동부리 81-2울산광역시 남구 무거동 316-214.3
817평택~파주선경기도 평택시 오성면 안화리 428-2경기도 파주시 군내면 백연리 산104-189.3
920새만금포항선(완주~장수)전라북도 완주군 상관면 의암리 산187-4전라북도 장수군 장계면 월강리 산2-2836.5
노선번호노선명시점종점공용중
42300대전남부순환선대전광역시 유성구 원내동 474-4대전광역시 동구 비룡동 12-413.3
43301상주영천선경상북도 상주시 낙동면 승곡리 66-1경상북도 영천시 북안면 임포리 43894.0
44400수도권제2순환선(화성~광주)경기도 화성시 마도면 석교리 452-10경기도 광주시 도척면 진우리 898-458.7
45400수도권제2순환선(인천~김포)인천광역시 중구 신흥동3가 58경기도 김포시 양촌읍 흥신리 44-128.9
46400수도권제2순환선(양주~포천)경기도 양주시 회암동 398-1경기도 포천시 소흘읍 무봉리 796.0
47451중부내륙선의지선대구광역시 달성군 현풍면 지리 161-2대구광역시 북구 금호동 472-330.0
48500광주외곽순환선광주광역시 광산구 송치동 181-6전라남도 장성군 남면 분향리 907-49.7
49551중앙선의지선경상남도 김해시 안동 694-1경상남도 양산시 남부동 89-217.4
50600부산외곽순환선경상남도 김해시 진영읍 우동리 354-1부산광역시 기장군 일광면 화전리 350-148.8
51700대구외곽순환선대구광역시 달서구 대천동 857-2대구광역시 동구 상매동 산10632.9