Overview

Dataset statistics

Number of variables6
Number of observations40
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory53.3 B

Variable types

Numeric2
Text3
Categorical1

Dataset

Description인천광역시 미추홀구 자전거도로 현황에 대한 데이터로 연번, 노선명,기점,종점,자전거도로 종류, 연장 등을 제공합니다.
Author인천광역시 미추홀구
URLhttps://www.data.go.kr/data/15077687/fileData.do

Alerts

연번 is highly overall correlated with 자전거도로 종류High correlation
자전거도로 종류 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:39:49.225072
Analysis finished2023-12-12 21:39:49.949509
Duration0.72 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.5
Minimum1
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-13T06:39:50.005218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.95
Q110.75
median20.5
Q330.25
95-th percentile38.05
Maximum40
Range39
Interquartile range (IQR)19.5

Descriptive statistics

Standard deviation11.690452
Coefficient of variation (CV)0.57026595
Kurtosis-1.2
Mean20.5
Median Absolute Deviation (MAD)10
Skewness0
Sum820
Variance136.66667
MonotonicityStrictly increasing
2023-12-13T06:39:50.109942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1 1
 
2.5%
22 1
 
2.5%
24 1
 
2.5%
25 1
 
2.5%
26 1
 
2.5%
27 1
 
2.5%
28 1
 
2.5%
29 1
 
2.5%
30 1
 
2.5%
31 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
1 1
2.5%
2 1
2.5%
3 1
2.5%
4 1
2.5%
5 1
2.5%
6 1
2.5%
7 1
2.5%
8 1
2.5%
9 1
2.5%
10 1
2.5%
ValueCountFrequency (%)
40 1
2.5%
39 1
2.5%
38 1
2.5%
37 1
2.5%
36 1
2.5%
35 1
2.5%
34 1
2.5%
33 1
2.5%
32 1
2.5%
31 1
2.5%

노선명
Text

Distinct39
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-13T06:39:50.283568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length5.725
Min length4

Characters and Unicode

Total characters229
Distinct characters44
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)95.0%

Sample

1st row매소홀로1R
2nd row매소홀로2R
3rd row매소홀로1L
4th row인하로1R
5th row인하로2R
ValueCountFrequency (%)
매소홀로 3
 
7.0%
290번길r 2
 
4.7%
경원대로1l 1
 
2.3%
경원대로2l 1
 
2.3%
한나루로1r 1
 
2.3%
한나루로1l 1
 
2.3%
한나루로2l 1
 
2.3%
미추홀대로1r 1
 
2.3%
미추홀대로1l 1
 
2.3%
경원대로r 1
 
2.3%
Other values (30) 30
69.8%
2023-12-13T06:39:50.588939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 40
17.5%
R 22
 
9.6%
1 20
 
8.7%
L 17
 
7.4%
2 9
 
3.9%
홀 8
 
3.5%
대 8
 
3.5%
인 8
 
3.5%
정 7
 
3.1%
석 7
 
3.1%
Other values (34) 83
36.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 147
64.2%
Decimal Number 40
 
17.5%
Uppercase Letter 39
 
17.0%
Space Separator 3
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 40
27.2%
홀 8
 
5.4%
대 8
 
5.4%
인 8
 
5.4%
정 7
 
4.8%
석 7
 
4.8%
매 6
 
4.1%
소 6
 
4.1%
경 5
 
3.4%
길 4
 
2.7%
Other values (25) 48
32.7%
Decimal Number
ValueCountFrequency (%)
1 20
50.0%
2 9
22.5%
9 4
 
10.0%
0 3
 
7.5%
3 3
 
7.5%
4 1
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
R 22
56.4%
L 17
43.6%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 147
64.2%
Common 43
 
18.8%
Latin 39
 
17.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 40
27.2%
홀 8
 
5.4%
대 8
 
5.4%
인 8
 
5.4%
정 7
 
4.8%
석 7
 
4.8%
매 6
 
4.1%
소 6
 
4.1%
경 5
 
3.4%
길 4
 
2.7%
Other values (25) 48
32.7%
Common
ValueCountFrequency (%)
1 20
46.5%
2 9
20.9%
9 4
 
9.3%
0 3
 
7.0%
3 3
 
7.0%
3
 
7.0%
4 1
 
2.3%
Latin
ValueCountFrequency (%)
R 22
56.4%
L 17
43.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 147
64.2%
ASCII 82
35.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 40
27.2%
홀 8
 
5.4%
대 8
 
5.4%
인 8
 
5.4%
정 7
 
4.8%
석 7
 
4.8%
매 6
 
4.1%
소 6
 
4.1%
경 5
 
3.4%
길 4
 
2.7%
Other values (25) 48
32.7%
ASCII
ValueCountFrequency (%)
R 22
26.8%
1 20
24.4%
L 17
20.7%
2 9
11.0%
9 4
 
4.9%
0 3
 
3.7%
3 3
 
3.7%
3
 
3.7%
4 1
 
1.2%

기점
Text

Distinct34
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-13T06:39:50.759129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length7
Min length4

Characters and Unicode

Total characters280
Distinct characters93
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

Unique30 ?
Unique (%)75.0%

Sample

1st row두산위브아파트
2nd row문학경기장
3rd row무형문화제전수교육관
4th row인하로134번길3
5th row인하로398
ValueCountFrequency (%)
두산위브아파트 3
 
7.3%
인천축구전용경기장 3
 
7.3%
도화오거리 2
 
4.9%
독정이삼거리 2
 
4.9%
문학경기장사거리 1
 
2.4%
엑슬루타워 1
 
2.4%
103동 1
 
2.4%
경인북길1 1
 
2.4%
수봉로19-1 1
 
2.4%
종합터미널입구 1
 
2.4%
Other values (25) 25
61.0%
2023-12-13T06:39:51.043571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 12
 
4.3%
인 11
 
3.9%
3 11
 
3.9%
리 11
 
3.9%
거 10
 
3.6%
장 9
 
3.2%
경 9
 
3.2%
1 8
 
2.9%
6 7
 
2.5%
천 6
 
2.1%
Other values (83) 186
66.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 233
83.2%
Decimal Number 45
 
16.1%
Dash Punctuation 1
 
0.4%
Space Separator 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 12
 
5.2%
인 11
 
4.7%
리 11
 
4.7%
거 10
 
4.3%
장 9
 
3.9%
경 9
 
3.9%
천 6
 
2.6%
길 6
 
2.6%
파 5
 
2.1%
대 5
 
2.1%
Other values (71) 149
63.9%
Decimal Number
ValueCountFrequency (%)
3 11
24.4%
1 8
17.8%
6 7
15.6%
4 5
11.1%
9 4
 
8.9%
2 3
 
6.7%
0 2
 
4.4%
8 2
 
4.4%
5 2
 
4.4%
7 1
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 233
83.2%
Common 47
 
16.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 12
 
5.2%
인 11
 
4.7%
리 11
 
4.7%
거 10
 
4.3%
장 9
 
3.9%
경 9
 
3.9%
천 6
 
2.6%
길 6
 
2.6%
파 5
 
2.1%
대 5
 
2.1%
Other values (71) 149
63.9%
Common
ValueCountFrequency (%)
3 11
23.4%
1 8
17.0%
6 7
14.9%
4 5
10.6%
9 4
 
8.5%
2 3
 
6.4%
0 2
 
4.3%
8 2
 
4.3%
5 2
 
4.3%
- 1
 
2.1%
Other values (2) 2
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 233
83.2%
ASCII 47
 
16.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 12
 
5.2%
인 11
 
4.7%
리 11
 
4.7%
거 10
 
4.3%
장 9
 
3.9%
경 9
 
3.9%
천 6
 
2.6%
길 6
 
2.6%
파 5
 
2.1%
대 5
 
2.1%
Other values (71) 149
63.9%
ASCII
ValueCountFrequency (%)
3 11
23.4%
1 8
17.0%
6 7
14.9%
4 5
10.6%
9 4
 
8.5%
2 3
 
6.4%
0 2
 
4.3%
8 2
 
4.3%
5 2
 
4.3%
- 1
 
2.1%
Other values (2) 2
 
4.3%

종점
Text

Distinct36
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-13T06:39:51.228496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8.5
Mean length6.65
Min length4

Characters and Unicode

Total characters266
Distinct characters92
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

Unique34 ?
Unique (%)85.0%

Sample

1st row두산위브아파트
2nd row선학동28-1
3rd row관교동549-13
4th row제운사거리
5th row관교초등학교
ValueCountFrequency (%)
두산위브아파트 3
 
7.1%
인천축구전용경기장 3
 
7.1%
제2경인시점 1
 
2.4%
도화신동아파밀리에 1
 
2.4%
경인로265번길 1
 
2.4%
한나루로569 1
 
2.4%
한나루로521 1
 
2.4%
제일시장사거리 1
 
2.4%
미추홀대로662 1
 
2.4%
주승로180 1
 
2.4%
Other values (28) 28
66.7%
2023-12-13T06:39:51.504227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 14
 
5.3%
1 12
 
4.5%
리 11
 
4.1%
거 10
 
3.8%
사 9
 
3.4%
인 7
 
2.6%
2 7
 
2.6%
0 6
 
2.3%
장 6
 
2.3%
3 6
 
2.3%
Other values (82) 178
66.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 208
78.2%
Decimal Number 53
 
19.9%
Dash Punctuation 3
 
1.1%
Space Separator 2
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 14
 
6.7%
리 11
 
5.3%
거 10
 
4.8%
사 9
 
4.3%
인 7
 
3.4%
장 6
 
2.9%
경 6
 
2.9%
동 5
 
2.4%
용 5
 
2.4%
기 5
 
2.4%
Other values (70) 130
62.5%
Decimal Number
ValueCountFrequency (%)
1 12
22.6%
2 7
13.2%
0 6
11.3%
3 6
11.3%
4 5
9.4%
5 4
 
7.5%
6 4
 
7.5%
9 4
 
7.5%
7 3
 
5.7%
8 2
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 208
78.2%
Common 58
 
21.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 14
 
6.7%
리 11
 
5.3%
거 10
 
4.8%
사 9
 
4.3%
인 7
 
3.4%
장 6
 
2.9%
경 6
 
2.9%
동 5
 
2.4%
용 5
 
2.4%
기 5
 
2.4%
Other values (70) 130
62.5%
Common
ValueCountFrequency (%)
1 12
20.7%
2 7
12.1%
0 6
10.3%
3 6
10.3%
4 5
8.6%
5 4
 
6.9%
6 4
 
6.9%
9 4
 
6.9%
7 3
 
5.2%
- 3
 
5.2%
Other values (2) 4
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 208
78.2%
ASCII 58
 
21.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 14
 
6.7%
리 11
 
5.3%
거 10
 
4.8%
사 9
 
4.3%
인 7
 
3.4%
장 6
 
2.9%
경 6
 
2.9%
동 5
 
2.4%
용 5
 
2.4%
기 5
 
2.4%
Other values (70) 130
62.5%
ASCII
ValueCountFrequency (%)
1 12
20.7%
2 7
12.1%
0 6
10.3%
3 6
10.3%
4 5
8.6%
5 4
 
6.9%
6 4
 
6.9%
9 4
 
6.9%
7 3
 
5.2%
- 3
 
5.2%
Other values (2) 4
 
6.9%

자전거도로 종류
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
겸용도로
33 
전용도로
7 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전용도로
2nd row전용도로
3rd row전용도로
4th row전용도로
5th row겸용도로

Common Values

ValueCountFrequency (%)
겸용도로 33
82.5%
전용도로 7
 
17.5%

Length

2023-12-13T06:39:51.642286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:39:51.729092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
겸용도로 33
82.5%
전용도로 7
 
17.5%

연장
Real number (ℝ)

Distinct32
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3995
Minimum0.05
Maximum1.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-13T06:39:51.811078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.05
5-th percentile0.0895
Q10.2
median0.33
Q30.505
95-th percentile0.963
Maximum1.15
Range1.1
Interquartile range (IQR)0.305

Descriptive statistics

Standard deviation0.27686848
Coefficient of variation (CV)0.69303749
Kurtosis0.60659462
Mean0.3995
Median Absolute Deviation (MAD)0.15
Skewness1.1003607
Sum15.98
Variance0.076656154
MonotonicityNot monotonic
2023-12-13T06:39:51.908731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0.2 3
 
7.5%
0.46 3
 
7.5%
0.21 2
 
5.0%
0.24 2
 
5.0%
0.15 2
 
5.0%
0.41 2
 
5.0%
0.08 1
 
2.5%
0.68 1
 
2.5%
0.65 1
 
2.5%
0.96 1
 
2.5%
Other values (22) 22
55.0%
ValueCountFrequency (%)
0.05 1
 
2.5%
0.08 1
 
2.5%
0.09 1
 
2.5%
0.11 1
 
2.5%
0.15 2
5.0%
0.16 1
 
2.5%
0.17 1
 
2.5%
0.18 1
 
2.5%
0.2 3
7.5%
0.21 2
5.0%
ValueCountFrequency (%)
1.15 1
2.5%
1.02 1
2.5%
0.96 1
2.5%
0.92 1
2.5%
0.84 1
2.5%
0.68 1
2.5%
0.65 1
2.5%
0.62 1
2.5%
0.54 1
2.5%
0.52 1
2.5%

Interactions

2023-12-13T06:39:49.663511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:39:49.489560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:39:49.754567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:39:49.573845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:39:51.989451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번노선명기점종점자전거도로 종류연장
연번1.0001.0000.9200.9180.9320.638
노선명1.0001.0001.0001.0000.0001.000
기점0.9201.0001.0001.0000.7160.978
종점0.9181.0001.0001.0000.3470.981
자전거도로 종류0.9320.0000.7160.3471.0000.423
연장0.6381.0000.9780.9810.4231.000
2023-12-13T06:39:52.074867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번연장자전거도로 종류
연번1.0000.2130.692
연장0.2131.0000.377
자전거도로 종류0.6920.3771.000

Missing values

2023-12-13T06:39:49.841333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:39:49.918261image/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

연번노선명기점종점자전거도로 종류연장
01매소홀로1R두산위브아파트두산위브아파트전용도로0.15
12매소홀로2R문학경기장선학동28-1전용도로1.02
23매소홀로1L무형문화제전수교육관관교동549-13전용도로1.15
34인하로1R인하로134번길3제운사거리전용도로0.41
45인하로2R인하로398관교초등학교겸용도로0.17
56인하로1L신라아파트승학사거리겸용도로0.08
67인주대로1R독정이삼거리인주대로174겸용도로0.09
78인주대로1L독정이삼거리수봉남로1겸용도로0.05
89인주대로2L인주대로237번길2용일사거리겸용도로0.41
910장천로1R장천로14번길3숭의오거리겸용도로0.21
연번노선명기점종점자전거도로 종류연장
3031예술로L종합터미널입구터미널사거리전용도로0.5
3132수봉로R수봉로19-1수봉로7겸용도로0.16
3233석정로49번길R인천축구전용경기장인천축구전용경기장겸용도로0.15
3334샛골로R인천축구전용경기장인천축구전용경기장겸용도로0.46
3435독배로R경인북길1용현사거리겸용도로0.46
3536매소홀로 309번길R엑슬루타워 103동엑슬루타워 101동겸용도로0.24
3637아암로R경인방송제2경인시점겸용도로0.96
3738매소홀로 290번길R두산위브아파트두산위브아파트겸용도로0.2
3839매소홀로 290번길R두산위브아파트두산위브아파트전용도로0.2
3940숙골로L인천대삼거리도화동 37-20겸용도로0.65