Overview

Dataset statistics

Number of variables7
Number of observations84
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.8 KiB
Average record size in memory58.6 B

Variable types

Categorical3
Text3
Numeric1

Dataset

Description대전광역시 유성구 관내에 있는 자전거 도로 현황에 대한 데이터로 노선명, 기점, 종점, 총연장 등의 데이터를 제공합니다.
Author대전광역시 유성구
URLhttps://www.data.go.kr/data/15005468/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
데이터기준일자 has constant value ""Constant

Reproduction

Analysis started2023-12-12 04:58:31.298003
Analysis finished2023-12-12 04:58:32.355740
Duration1.06 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size804.0 B
대전광역시
84 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대전광역시 84
100.0%

Length

2023-12-12T13:58:32.422160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:58:32.514100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대전광역시 84
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size804.0 B
유성구
84 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유성구 84
100.0%

Length

2023-12-12T13:58:32.614260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:58:32.705264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유성구 84
100.0%

노선명
Text

Distinct83
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size804.0 B
2023-12-12T13:58:32.947769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length4.7857143
Min length3

Characters and Unicode

Total characters402
Distinct characters65
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique82 ?
Unique (%)97.6%

Sample

1st row대정북로
2nd row대학로1
3rd row대학로2
4th row대덕대로1
5th row대덕대로2
ValueCountFrequency (%)
대정북로 2
 
2.4%
엑스포로539번길 1
 
1.2%
엑스포로1 1
 
1.2%
노은서로 1
 
1.2%
노은동로4 1
 
1.2%
노은동로3 1
 
1.2%
노은동로2 1
 
1.2%
노은동로1 1
 
1.2%
지족로 1
 
1.2%
반석서로3 1
 
1.2%
Other values (73) 73
86.9%
2023-12-12T13:58:33.389783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 77
19.2%
대 28
 
7.0%
1 20
 
5.0%
2 19
 
4.7%
학 14
 
3.5%
성 13
 
3.2%
유 13
 
3.2%
노 12
 
3.0%
하 11
 
2.7%
3 10
 
2.5%
Other values (55) 185
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 328
81.6%
Decimal Number 70
 
17.4%
Uppercase Letter 4
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 77
23.5%
대 28
 
8.5%
학 14
 
4.3%
성 13
 
4.0%
유 13
 
4.0%
노 12
 
3.7%
하 11
 
3.4%
동 10
 
3.0%
은 10
 
3.0%
천 8
 
2.4%
Other values (44) 132
40.2%
Decimal Number
ValueCountFrequency (%)
1 20
28.6%
2 19
27.1%
3 10
14.3%
4 6
 
8.6%
9 4
 
5.7%
6 4
 
5.7%
5 3
 
4.3%
8 2
 
2.9%
7 1
 
1.4%
0 1
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
L 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 328
81.6%
Common 70
 
17.4%
Latin 4
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 77
23.5%
대 28
 
8.5%
학 14
 
4.3%
성 13
 
4.0%
유 13
 
4.0%
노 12
 
3.7%
하 11
 
3.4%
동 10
 
3.0%
은 10
 
3.0%
천 8
 
2.4%
Other values (44) 132
40.2%
Common
ValueCountFrequency (%)
1 20
28.6%
2 19
27.1%
3 10
14.3%
4 6
 
8.6%
9 4
 
5.7%
6 4
 
5.7%
5 3
 
4.3%
8 2
 
2.9%
7 1
 
1.4%
0 1
 
1.4%
Latin
ValueCountFrequency (%)
L 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 328
81.6%
ASCII 74
 
18.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 77
23.5%
대 28
 
8.5%
학 14
 
4.3%
성 13
 
4.0%
유 13
 
4.0%
노 12
 
3.7%
하 11
 
3.4%
동 10
 
3.0%
은 10
 
3.0%
천 8
 
2.4%
Other values (44) 132
40.2%
ASCII
ValueCountFrequency (%)
1 20
27.0%
2 19
25.7%
3 10
13.5%
4 6
 
8.1%
9 4
 
5.4%
6 4
 
5.4%
L 4
 
5.4%
5 3
 
4.1%
8 2
 
2.7%
7 1
 
1.4%

기점
Text

Distinct74
Distinct (%)88.1%
Missing0
Missing (%)0.0%
Memory size804.0 B
2023-12-12T13:58:33.666333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length15.369048
Min length7

Characters and Unicode

Total characters1291
Distinct characters154
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)77.4%

Sample

1st row대정동 507-21(한우물네거리)
2nd row가정동 52-4(과학공원네거리)
3rd row궁동258-3(충대정문오거리)
4th row봉산동 839(신구교네거리)
5th row관평동 1344(미래로네거리)
ValueCountFrequency (%)
반석동 8
 
4.8%
관평동 7
 
4.2%
전민동 6
 
3.6%
구암동 6
 
3.6%
노은동 6
 
3.6%
학하동 5
 
3.0%
대정동 4
 
2.4%
지족동 3
 
1.8%
507-21(한우물네거리 3
 
1.8%
계산동 3
 
1.8%
Other values (95) 117
69.6%
2023-12-12T13:58:34.116946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 87
 
6.7%
84
 
6.5%
) 77
 
6.0%
( 77
 
6.0%
- 57
 
4.4%
2 53
 
4.1%
6 45
 
3.5%
1 44
 
3.4%
리 40
 
3.1%
거 38
 
2.9%
Other values (144) 689
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 654
50.7%
Decimal Number 326
25.3%
Space Separator 84
 
6.5%
Close Punctuation 77
 
6.0%
Open Punctuation 77
 
6.0%
Dash Punctuation 57
 
4.4%
Lowercase Letter 10
 
0.8%
Uppercase Letter 5
 
0.4%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 87
 
13.3%
리 40
 
6.1%
거 38
 
5.8%
네 25
 
3.8%
구 21
 
3.2%
대 19
 
2.9%
지 15
 
2.3%
교 15
 
2.3%
반 13
 
2.0%
석 13
 
2.0%
Other values (118) 368
56.3%
Decimal Number
ValueCountFrequency (%)
2 53
16.3%
6 45
13.8%
1 44
13.5%
5 37
11.3%
4 33
10.1%
3 29
8.9%
7 29
8.9%
8 28
8.6%
0 16
 
4.9%
9 12
 
3.7%
Lowercase Letter
ValueCountFrequency (%)
k 2
20.0%
s 2
20.0%
o 1
10.0%
p 1
10.0%
f 1
10.0%
n 1
10.0%
e 1
10.0%
g 1
10.0%
Uppercase Letter
ValueCountFrequency (%)
K 2
40.0%
T 2
40.0%
G 1
20.0%
Space Separator
ValueCountFrequency (%)
84
100.0%
Close Punctuation
ValueCountFrequency (%)
) 77
100.0%
Open Punctuation
ValueCountFrequency (%)
( 77
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 57
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 654
50.7%
Common 622
48.2%
Latin 15
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 87
 
13.3%
리 40
 
6.1%
거 38
 
5.8%
네 25
 
3.8%
구 21
 
3.2%
대 19
 
2.9%
지 15
 
2.3%
교 15
 
2.3%
반 13
 
2.0%
석 13
 
2.0%
Other values (118) 368
56.3%
Common
ValueCountFrequency (%)
84
13.5%
) 77
12.4%
( 77
12.4%
- 57
9.2%
2 53
8.5%
6 45
7.2%
1 44
7.1%
5 37
5.9%
4 33
 
5.3%
3 29
 
4.7%
Other values (5) 86
13.8%
Latin
ValueCountFrequency (%)
k 2
13.3%
s 2
13.3%
K 2
13.3%
T 2
13.3%
o 1
6.7%
p 1
6.7%
f 1
6.7%
n 1
6.7%
e 1
6.7%
g 1
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 654
50.7%
ASCII 637
49.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 87
 
13.3%
리 40
 
6.1%
거 38
 
5.8%
네 25
 
3.8%
구 21
 
3.2%
대 19
 
2.9%
지 15
 
2.3%
교 15
 
2.3%
반 13
 
2.0%
석 13
 
2.0%
Other values (118) 368
56.3%
ASCII
ValueCountFrequency (%)
84
13.2%
) 77
12.1%
( 77
12.1%
- 57
8.9%
2 53
8.3%
6 45
7.1%
1 44
6.9%
5 37
 
5.8%
4 33
 
5.2%
3 29
 
4.6%
Other values (16) 101
15.9%

종점
Text

Distinct78
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size804.0 B
2023-12-12T13:58:34.389772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length15.142857
Min length7

Characters and Unicode

Total characters1272
Distinct characters164
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)85.7%

Sample

1st row대정동 302-4(유통단지네거리)
2nd row궁동 258-3(충대정문오거리)
3rd row봉명동 536-11(노블레스타워)
4th row관평동 1344(미래로네거리)
5th row화암동 98-6(화암네거리)
ValueCountFrequency (%)
학하동 9
 
5.3%
노은동 6
 
3.6%
관평동 6
 
3.6%
반석동 5
 
3.0%
구암동 5
 
3.0%
지족동 4
 
2.4%
전민동 4
 
2.4%
장대동 4
 
2.4%
대정동 4
 
2.4%
문지동 4
 
2.4%
Other values (98) 118
69.8%
2023-12-12T13:58:34.818685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 85
 
6.7%
85
 
6.7%
( 74
 
5.8%
) 73
 
5.7%
- 61
 
4.8%
1 58
 
4.6%
6 47
 
3.7%
2 41
 
3.2%
3 35
 
2.8%
리 33
 
2.6%
Other values (154) 680
53.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 653
51.3%
Decimal Number 322
25.3%
Space Separator 85
 
6.7%
Open Punctuation 74
 
5.8%
Close Punctuation 73
 
5.7%
Dash Punctuation 61
 
4.8%
Uppercase Letter 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 85
 
13.0%
리 33
 
5.1%
거 30
 
4.6%
지 25
 
3.8%
네 20
 
3.1%
대 19
 
2.9%
하 14
 
2.1%
학 13
 
2.0%
구 12
 
1.8%
단 12
 
1.8%
Other values (136) 390
59.7%
Decimal Number
ValueCountFrequency (%)
1 58
18.0%
6 47
14.6%
2 41
12.7%
3 35
10.9%
4 31
9.6%
7 30
9.3%
8 27
8.4%
5 22
 
6.8%
0 16
 
5.0%
9 15
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
T 1
25.0%
K 1
25.0%
C 1
25.0%
I 1
25.0%
Space Separator
ValueCountFrequency (%)
85
100.0%
Open Punctuation
ValueCountFrequency (%)
( 74
100.0%
Close Punctuation
ValueCountFrequency (%)
) 73
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 653
51.3%
Common 615
48.3%
Latin 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 85
 
13.0%
리 33
 
5.1%
거 30
 
4.6%
지 25
 
3.8%
네 20
 
3.1%
대 19
 
2.9%
하 14
 
2.1%
학 13
 
2.0%
구 12
 
1.8%
단 12
 
1.8%
Other values (136) 390
59.7%
Common
ValueCountFrequency (%)
85
13.8%
( 74
12.0%
) 73
11.9%
- 61
9.9%
1 58
9.4%
6 47
7.6%
2 41
6.7%
3 35
5.7%
4 31
 
5.0%
7 30
 
4.9%
Other values (4) 80
13.0%
Latin
ValueCountFrequency (%)
T 1
25.0%
K 1
25.0%
C 1
25.0%
I 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 653
51.3%
ASCII 619
48.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 85
 
13.0%
리 33
 
5.1%
거 30
 
4.6%
지 25
 
3.8%
네 20
 
3.1%
대 19
 
2.9%
하 14
 
2.1%
학 13
 
2.0%
구 12
 
1.8%
단 12
 
1.8%
Other values (136) 390
59.7%
ASCII
ValueCountFrequency (%)
85
13.7%
( 74
12.0%
) 73
11.8%
- 61
9.9%
1 58
9.4%
6 47
7.6%
2 41
6.6%
3 35
5.7%
4 31
 
5.0%
7 30
 
4.8%
Other values (8) 84
13.6%

총연장(km)
Real number (ℝ)

Distinct41
Distinct (%)48.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3141667
Minimum0.1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2023-12-12T13:58:34.974322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.4
Q11
median1.4
Q33.225
95-th percentile6.17
Maximum8
Range7.9
Interquartile range (IQR)2.225

Descriptive statistics

Standard deviation1.9389093
Coefficient of variation (CV)0.8378434
Kurtosis0.59369592
Mean2.3141667
Median Absolute Deviation (MAD)0.7
Skewness1.247729
Sum194.39
Variance3.7593692
MonotonicityNot monotonic
2023-12-12T13:58:35.172425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
1.2 11
 
13.1%
1.4 9
 
10.7%
1.0 5
 
6.0%
0.8 4
 
4.8%
0.4 3
 
3.6%
2.0 3
 
3.6%
1.3 3
 
3.6%
0.6 3
 
3.6%
3.0 3
 
3.6%
6.0 2
 
2.4%
Other values (31) 38
45.2%
ValueCountFrequency (%)
0.1 1
 
1.2%
0.12 1
 
1.2%
0.2 1
 
1.2%
0.4 3
3.6%
0.5 1
 
1.2%
0.6 3
3.6%
0.7 2
 
2.4%
0.8 4
4.8%
0.9 2
 
2.4%
1.0 5
6.0%
ValueCountFrequency (%)
8.0 1
1.2%
7.4 1
1.2%
7.2 1
1.2%
6.4 1
1.2%
6.2 1
1.2%
6.0 2
2.4%
5.9 1
1.2%
5.6 2
2.4%
5.4 1
1.2%
5.2 1
1.2%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size804.0 B
2021-07-31
84 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-07-31
2nd row2021-07-31
3rd row2021-07-31
4th row2021-07-31
5th row2021-07-31

Common Values

ValueCountFrequency (%)
2021-07-31 84
100.0%

Length

2023-12-12T13:58:35.365107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:58:35.502302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-07-31 84
100.0%

Interactions

2023-12-12T13:58:32.102930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:58:35.577382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선명기점종점총연장(km)
노선명1.0001.0000.9951.000
기점1.0001.0000.9830.724
종점0.9950.9831.0000.774
총연장(km)1.0000.7240.7741.000

Missing values

2023-12-12T13:58:32.212094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:58:32.310332image/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

시도명시군구명노선명기점종점총연장(km)데이터기준일자
0대전광역시유성구대정북로대정동 507-21(한우물네거리)대정동 302-4(유통단지네거리)0.82021-07-31
1대전광역시유성구대학로1가정동 52-4(과학공원네거리)궁동 258-3(충대정문오거리)3.62021-07-31
2대전광역시유성구대학로2궁동258-3(충대정문오거리)봉명동 536-11(노블레스타워)1.02021-07-31
3대전광역시유성구대덕대로1봉산동 839(신구교네거리)관평동 1344(미래로네거리)1.22021-07-31
4대전광역시유성구대덕대로2관평동 1344(미래로네거리)화암동 98-6(화암네거리)5.22021-07-31
5대전광역시유성구대덕대로3화암동 98-6(화암네거리)도룡동 381-41(도룡삼거리)4.62021-07-31
6대전광역시유성구대덕대로4도룡동 381-41(도룡삼거리)가정동 52-4(과학공원네거리)3.02021-07-31
7대전광역시유성구과학로구성동 432-2(구성삼거리)신성동 459(승적골삼거리)4.82021-07-31
8대전광역시유성구가정로신성동 302(KT&G중앙연구원)도룡동 394-3(연구단지네거리)6.42021-07-31
9대전광역시유성구가정북로장동 361-1(충렬삼거리)장동 84-19(다름고개삼거리)3.42021-07-31
시도명시군구명노선명기점종점총연장(km)데이터기준일자
74대전광역시유성구학하복용로2학하동 746-6(학무정네거리)학하동 762-71.02021-07-31
75대전광역시유성구관평천관평동 672(동화울교)용산동 513(관평교)3.22021-07-31
76대전광역시유성구반석천반석동 520(노은4지구)장대동 376-8(장현교)6.22021-07-31
77대전광역시유성구화산천계산동 720(화산제5교)학하동 767(학하2교)3.42021-07-31
78대전광역시유성구진잠천용계동 185-3(화산천 합류점)원신흥동 487(용반교)5.42021-07-31
79대전광역시유성구유성천구암동 648-2(유성천교)어은동 109(어은교)5.62021-07-31
80대전광역시유성구탄동천1자운동 36-7(자운대4거리)신성동 8-72.02021-07-31
81대전광역시유성구탄동천2구성동 32-1(구성교)구성동 32-1(매봉교)1.42021-07-31
82대전광역시유성구문지로문지동 679문지동 661-50.82021-07-31
83대전광역시유성구엑스포로4문지동 679문지동 632-71.32021-07-31