Overview

Dataset statistics

Number of variables13
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory107.7 B

Variable types

Text6
Categorical6
DateTime1

Dataset

Description서울특별시 광진구 자전거도로 현황(노선명, 자전거도로종류,기점,종점,주요경유지,자전거도로폭,도로재질 등)
Author서울특별시 광진구
URLhttps://www.data.go.kr/data/15062580/fileData.do

Alerts

데이터기준일 has constant value ""Constant
자전거도로종류 is highly overall correlated with 일반도로폭 and 3 other fieldsHigh correlation
일반도로폭 is highly overall correlated with 자전거도로종류 and 1 other fieldsHigh correlation
자전거도로폭 is highly overall correlated with 자전거도로종류 and 1 other fieldsHigh correlation
도로재질 is highly overall correlated with 자전거도로종류 and 1 other fieldsHigh correlation
비고 is highly overall correlated with 자전거도로종류 and 1 other fieldsHigh correlation
자전거도로종류 is highly imbalanced (55.3%)Imbalance
비고 is highly imbalanced (69.1%)Imbalance

Reproduction

Analysis started2024-03-16 04:12:25.553343
Analysis finished2024-03-16 04:12:27.938787
Duration2.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

노선명
Text

Distinct20
Distinct (%)55.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-03-16T13:12:28.210015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6.5
Mean length4.1944444
Min length3

Characters and Unicode

Total characters151
Distinct characters38
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)41.7%

Sample

1st row동일로
2nd row광나루로56길
3rd row아차산로70길
4th row능동로
5th row능동로
ValueCountFrequency (%)
아차산로 6
16.7%
천호대로 4
 
11.1%
능동로 4
 
11.1%
광나루로 4
 
11.1%
자양로 3
 
8.3%
강변역로 1
 
2.8%
동일로 1
 
2.8%
아차산로36길 1
 
2.8%
자양로13길 1
 
2.8%
자양강변길 1
 
2.8%
Other values (10) 10
27.8%
2024-03-16T13:12:28.901044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 34
22.5%
산 9
 
6.0%
아 8
 
5.3%
차 8
 
5.3%
길 7
 
4.6%
천 6
 
4.0%
동 6
 
4.0%
자 6
 
4.0%
양 6
 
4.0%
광 5
 
3.3%
Other values (28) 56
37.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 139
92.1%
Decimal Number 12
 
7.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 34
24.5%
산 9
 
6.5%
아 8
 
5.8%
차 8
 
5.8%
길 7
 
5.0%
천 6
 
4.3%
동 6
 
4.3%
자 6
 
4.3%
양 6
 
4.3%
광 5
 
3.6%
Other values (21) 44
31.7%
Decimal Number
ValueCountFrequency (%)
6 2
16.7%
5 2
16.7%
1 2
16.7%
0 2
16.7%
3 2
16.7%
7 1
8.3%
2 1
8.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 139
92.1%
Common 12
 
7.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 34
24.5%
산 9
 
6.5%
아 8
 
5.8%
차 8
 
5.8%
길 7
 
5.0%
천 6
 
4.3%
동 6
 
4.3%
자 6
 
4.3%
양 6
 
4.3%
광 5
 
3.6%
Other values (21) 44
31.7%
Common
ValueCountFrequency (%)
6 2
16.7%
5 2
16.7%
1 2
16.7%
0 2
16.7%
3 2
16.7%
7 1
8.3%
2 1
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 139
92.1%
ASCII 12
 
7.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 34
24.5%
산 9
 
6.5%
아 8
 
5.8%
차 8
 
5.8%
길 7
 
5.0%
천 6
 
4.3%
동 6
 
4.3%
자 6
 
4.3%
양 6
 
4.3%
광 5
 
3.6%
Other values (21) 44
31.7%
ASCII
ValueCountFrequency (%)
6 2
16.7%
5 2
16.7%
1 2
16.7%
0 2
16.7%
3 2
16.7%
7 1
8.3%
2 1
8.3%

자전거도로종류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size420.0 B
자전거및보행자겸용도로
30 
자전거우선도로
 
3
자전거전용도로
 
2
자전거전용차로
 
1

Length

Max length11
Median length11
Mean length10.333333
Min length7

Unique

Unique1 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
자전거및보행자겸용도로 30
83.3%
자전거우선도로 3
 
8.3%
자전거전용도로 2
 
5.6%
자전거전용차로 1
 
2.8%

Length

2024-03-16T13:12:29.134410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:12:29.360807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자전거및보행자겸용도로 30
83.3%
자전거우선도로 3
 
8.3%
자전거전용도로 2
 
5.6%
자전거전용차로 1
 
2.8%

기점
Text

Distinct29
Distinct (%)80.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-03-16T13:12:29.924320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length6.4444444
Min length3

Characters and Unicode

Total characters232
Distinct characters78
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)66.7%

Sample

1st row장평교교차로
2nd row테크노마트
3rd row광남중고교 입구교차로
4th row용곡삼거리
5th row군자역사거리
ValueCountFrequency (%)
광장사거리 4
 
9.3%
입구교차로 2
 
4.7%
군자교 2
 
4.7%
교차로 2
 
4.7%
자양사거리 2
 
4.7%
아차산역 2
 
4.7%
구의사거리 2
 
4.7%
화양사거리 2
 
4.7%
어린이대공원역 2
 
4.7%
광남중고교 1
 
2.3%
Other values (22) 22
51.2%
2024-03-16T13:12:30.420010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
거 16
 
6.9%
리 16
 
6.9%
교 14
 
6.0%
사 12
 
5.2%
로 10
 
4.3%
자 9
 
3.9%
양 8
 
3.4%
차 8
 
3.4%
역 7
 
3.0%
7
 
3.0%
Other values (68) 125
53.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 208
89.7%
Decimal Number 10
 
4.3%
Space Separator 7
 
3.0%
Close Punctuation 3
 
1.3%
Open Punctuation 3
 
1.3%
Uppercase Letter 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
거 16
 
7.7%
리 16
 
7.7%
교 14
 
6.7%
사 12
 
5.8%
로 10
 
4.8%
자 9
 
4.3%
양 8
 
3.8%
차 8
 
3.8%
역 7
 
3.4%
광 7
 
3.4%
Other values (57) 101
48.6%
Decimal Number
ValueCountFrequency (%)
3 3
30.0%
1 2
20.0%
5 1
 
10.0%
2 1
 
10.0%
6 1
 
10.0%
9 1
 
10.0%
0 1
 
10.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 208
89.7%
Common 23
 
9.9%
Latin 1
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
거 16
 
7.7%
리 16
 
7.7%
교 14
 
6.7%
사 12
 
5.8%
로 10
 
4.8%
자 9
 
4.3%
양 8
 
3.8%
차 8
 
3.8%
역 7
 
3.4%
광 7
 
3.4%
Other values (57) 101
48.6%
Common
ValueCountFrequency (%)
7
30.4%
3 3
13.0%
) 3
13.0%
( 3
13.0%
1 2
 
8.7%
5 1
 
4.3%
2 1
 
4.3%
6 1
 
4.3%
9 1
 
4.3%
0 1
 
4.3%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 208
89.7%
ASCII 24
 
10.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
거 16
 
7.7%
리 16
 
7.7%
교 14
 
6.7%
사 12
 
5.8%
로 10
 
4.8%
자 9
 
4.3%
양 8
 
3.8%
차 8
 
3.8%
역 7
 
3.4%
광 7
 
3.4%
Other values (57) 101
48.6%
ASCII
ValueCountFrequency (%)
7
29.2%
3 3
12.5%
) 3
12.5%
( 3
12.5%
1 2
 
8.3%
5 1
 
4.2%
C 1
 
4.2%
2 1
 
4.2%
6 1
 
4.2%
9 1
 
4.2%

종점
Text

Distinct32
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-03-16T13:12:30.775714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length7.1944444
Min length3

Characters and Unicode

Total characters259
Distinct characters93
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)77.8%

Sample

1st row군자교교차로
2nd row광남중고교입구교차로
3rd row광남중입구
4th row군자역사거리
5th row어린이대공원역
ValueCountFrequency (%)
군자교교차로 2
 
4.7%
광장사거리 2
 
4.7%
자양사거리 2
 
4.7%
경계 2
 
4.7%
구의사거리 2
 
4.7%
자양유수지 1
 
2.3%
잠실철교 1
 
2.3%
교차지점 1
 
2.3%
동일로 1
 
2.3%
코오롱글로벌빌딩앞 1
 
2.3%
Other values (28) 28
65.1%
2024-03-16T13:12:31.370795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 19
 
7.3%
구 12
 
4.6%
로 10
 
3.9%
리 9
 
3.5%
대 9
 
3.5%
사 8
 
3.1%
거 8
 
3.1%
자 8
 
3.1%
광 7
 
2.7%
7
 
2.7%
Other values (83) 162
62.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 243
93.8%
Space Separator 7
 
2.7%
Close Punctuation 3
 
1.2%
Open Punctuation 3
 
1.2%
Decimal Number 2
 
0.8%
Uppercase Letter 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 19
 
7.8%
구 12
 
4.9%
로 10
 
4.1%
리 9
 
3.7%
대 9
 
3.7%
사 8
 
3.3%
거 8
 
3.3%
자 8
 
3.3%
광 7
 
2.9%
역 6
 
2.5%
Other values (77) 147
60.5%
Decimal Number
ValueCountFrequency (%)
5 1
50.0%
4 1
50.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 243
93.8%
Common 15
 
5.8%
Latin 1
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 19
 
7.8%
구 12
 
4.9%
로 10
 
4.1%
리 9
 
3.7%
대 9
 
3.7%
사 8
 
3.3%
거 8
 
3.3%
자 8
 
3.3%
광 7
 
2.9%
역 6
 
2.5%
Other values (77) 147
60.5%
Common
ValueCountFrequency (%)
7
46.7%
) 3
20.0%
( 3
20.0%
5 1
 
6.7%
4 1
 
6.7%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 243
93.8%
ASCII 16
 
6.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 19
 
7.8%
구 12
 
4.9%
로 10
 
4.1%
리 9
 
3.7%
대 9
 
3.7%
사 8
 
3.3%
거 8
 
3.3%
자 8
 
3.3%
광 7
 
2.9%
역 6
 
2.5%
Other values (77) 147
60.5%
ASCII
ValueCountFrequency (%)
7
43.8%
) 3
18.8%
( 3
18.8%
C 1
 
6.2%
5 1
 
6.2%
4 1
 
6.2%

주요경유지
Text

Distinct34
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-03-16T13:12:31.775487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length5.7777778
Min length3

Characters and Unicode

Total characters208
Distinct characters98
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

Unique32 ?
Unique (%)88.9%

Sample

1st row중곡빗물펌프장
2nd row프라임아파트
3rd row한강시민공원연결로
4th row중곡역
5th row세종대학교
ValueCountFrequency (%)
아차산역 2
 
5.1%
화양삼거리 2
 
5.1%
스타시티 2
 
5.1%
광진구민체육센터 1
 
2.6%
중곡1동사거리 1
 
2.6%
자양1파출소 1
 
2.6%
중곡사거리 1
 
2.6%
성자초교 1
 
2.6%
b동 1
 
2.6%
d동 1
 
2.6%
Other values (26) 26
66.7%
2024-03-16T13:12:32.374486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 8
 
3.8%
동 8
 
3.8%
구 7
 
3.4%
교 7
 
3.4%
파 7
 
3.4%
역 7
 
3.4%
양 5
 
2.4%
중 5
 
2.4%
트 5
 
2.4%
리 5
 
2.4%
Other values (88) 144
69.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 198
95.2%
Decimal Number 5
 
2.4%
Space Separator 3
 
1.4%
Uppercase Letter 2
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 8
 
4.0%
동 8
 
4.0%
구 7
 
3.5%
교 7
 
3.5%
파 7
 
3.5%
역 7
 
3.5%
양 5
 
2.5%
중 5
 
2.5%
트 5
 
2.5%
리 5
 
2.5%
Other values (83) 134
67.7%
Decimal Number
ValueCountFrequency (%)
1 3
60.0%
2 2
40.0%
Uppercase Letter
ValueCountFrequency (%)
D 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 198
95.2%
Common 8
 
3.8%
Latin 2
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 8
 
4.0%
동 8
 
4.0%
구 7
 
3.5%
교 7
 
3.5%
파 7
 
3.5%
역 7
 
3.5%
양 5
 
2.5%
중 5
 
2.5%
트 5
 
2.5%
리 5
 
2.5%
Other values (83) 134
67.7%
Common
ValueCountFrequency (%)
1 3
37.5%
3
37.5%
2 2
25.0%
Latin
ValueCountFrequency (%)
D 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 198
95.2%
ASCII 10
 
4.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 8
 
4.0%
동 8
 
4.0%
구 7
 
3.5%
교 7
 
3.5%
파 7
 
3.5%
역 7
 
3.5%
양 5
 
2.5%
중 5
 
2.5%
트 5
 
2.5%
리 5
 
2.5%
Other values (83) 134
67.7%
ASCII
ValueCountFrequency (%)
1 3
30.0%
3
30.0%
2 2
20.0%
D 1
 
10.0%
B 1
 
10.0%

방향
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
편방
21 
양방
15 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
편방 21
58.3%
양방 15
41.7%

Length

2024-03-16T13:12:32.811595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:12:33.003324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
편방 21
58.3%
양방 15
41.7%

총연장
Text

Distinct33
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-03-16T13:12:33.271559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.5277778
Min length1

Characters and Unicode

Total characters199
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)83.3%

Sample

1st row1.5(3.0)
2nd row0.5(1.0)
3rd row0.5(1.0)
4th row1.4(2.8)
5th row1.2(2.4)
ValueCountFrequency (%)
0.5(1.0 2
 
5.6%
0.6 2
 
5.6%
0.2 2
 
5.6%
0.9(1.8 1
 
2.8%
3.1 1
 
2.8%
0.4 1
 
2.8%
0.52(1.04 1
 
2.8%
0.95(1.9 1
 
2.8%
0.91(1.82 1
 
2.8%
1.5(3.0 1
 
2.8%
Other values (23) 23
63.9%
2024-03-16T13:12:33.756075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 50
25.1%
0 30
15.1%
1 21
10.6%
( 15
 
7.5%
) 15
 
7.5%
5 13
 
6.5%
2 11
 
5.5%
8 10
 
5.0%
4 8
 
4.0%
9 8
 
4.0%
Other values (3) 18
 
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 119
59.8%
Other Punctuation 50
25.1%
Open Punctuation 15
 
7.5%
Close Punctuation 15
 
7.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 30
25.2%
1 21
17.6%
5 13
10.9%
2 11
 
9.2%
8 10
 
8.4%
4 8
 
6.7%
9 8
 
6.7%
3 7
 
5.9%
7 6
 
5.0%
6 5
 
4.2%
Other Punctuation
ValueCountFrequency (%)
. 50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 199
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 50
25.1%
0 30
15.1%
1 21
10.6%
( 15
 
7.5%
) 15
 
7.5%
5 13
 
6.5%
2 11
 
5.5%
8 10
 
5.0%
4 8
 
4.0%
9 8
 
4.0%
Other values (3) 18
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 199
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 50
25.1%
0 30
15.1%
1 21
10.6%
( 15
 
7.5%
) 15
 
7.5%
5 13
 
6.5%
2 11
 
5.5%
8 10
 
5.0%
4 8
 
4.0%
9 8
 
4.0%
Other values (3) 18
 
9.0%

일반도로폭
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size420.0 B
30
9 
25
8 
35
4 
50
4 
22
2 
Other values (7)
9 

Length

Max length5
Median length2
Mean length1.9722222
Min length1

Unique

Unique5 ?
Unique (%)13.9%

Sample

1st row30
2nd row35
3rd row20
4th row25
5th row25

Common Values

ValueCountFrequency (%)
30 9
25.0%
25 8
22.2%
35 4
11.1%
50 4
11.1%
22 2
 
5.6%
27 2
 
5.6%
9 2
 
5.6%
20 1
 
2.8%
40/22 1
 
2.8%
18 1
 
2.8%
Other values (2) 2
 
5.6%

Length

2024-03-16T13:12:34.043284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
30 9
25.0%
25 8
22.2%
35 4
11.1%
50 4
11.1%
22 2
 
5.6%
27 2
 
5.6%
9 2
 
5.6%
20 1
 
2.8%
40/22 1
 
2.8%
18 1
 
2.8%
Other values (2) 2
 
5.6%

자전거도로폭
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)36.1%
Missing0
Missing (%)0.0%
Memory size420.0 B
4
8 
3.5
8 
4.0(2.0)
5 
6
3 
2
2 
Other values (8)
10 

Length

Max length8
Median length5
Mean length3.1388889
Min length1

Unique

Unique6 ?
Unique (%)16.7%

Sample

1st row4
2nd row3.5
3rd row3.0(2.0)
4th row4.0(2.0)
5th row4.0(2.0)

Common Values

ValueCountFrequency (%)
4 8
22.2%
3.5 8
22.2%
4.0(2.0) 5
13.9%
6 3
 
8.3%
2 2
 
5.6%
1.5 2
 
5.6%
9 2
 
5.6%
3.0(2.0) 1
 
2.8%
3 1
 
2.8%
2.5 1
 
2.8%
Other values (3) 3
 
8.3%

Length

2024-03-16T13:12:34.473675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
4 8
22.2%
3.5 8
22.2%
4.0(2.0 5
13.9%
6 3
 
8.3%
2 2
 
5.6%
1.5 2
 
5.6%
9 2
 
5.6%
3.0(2.0 1
 
2.8%
3 1
 
2.8%
2.5 1
 
2.8%
Other values (3) 3
 
8.3%

설치연도
Text

Distinct18
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-03-16T13:12:34.773409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length4
Mean length4.8333333
Min length4

Characters and Unicode

Total characters174
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)33.3%

Sample

1st row1996
2nd row1996
3rd row2007
4th row1999
5th row1996/2020
ValueCountFrequency (%)
1998 7
19.4%
2007 5
13.9%
2016 4
11.1%
1997 3
 
8.3%
1999 3
 
8.3%
1996 2
 
5.6%
2021 1
 
2.8%
2015 1
 
2.8%
2022 1
 
2.8%
1997/2020 1
 
2.8%
Other values (8) 8
22.2%
2024-03-16T13:12:35.356792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 39
22.4%
0 39
22.4%
2 32
18.4%
1 27
15.5%
7 10
 
5.7%
8 9
 
5.2%
6 8
 
4.6%
/ 6
 
3.4%
5 2
 
1.1%
3 1
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 168
96.6%
Other Punctuation 6
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 39
23.2%
0 39
23.2%
2 32
19.0%
1 27
16.1%
7 10
 
6.0%
8 9
 
5.4%
6 8
 
4.8%
5 2
 
1.2%
3 1
 
0.6%
4 1
 
0.6%
Other Punctuation
ValueCountFrequency (%)
/ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 174
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 39
22.4%
0 39
22.4%
2 32
18.4%
1 27
15.5%
7 10
 
5.7%
8 9
 
5.2%
6 8
 
4.6%
/ 6
 
3.4%
5 2
 
1.1%
3 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 174
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 39
22.4%
0 39
22.4%
2 32
18.4%
1 27
15.5%
7 10
 
5.7%
8 9
 
5.2%
6 8
 
4.6%
/ 6
 
3.4%
5 2
 
1.1%
3 1
 
0.6%

도로재질
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)27.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
고압블럭
16 
투수콘/ 블럭
4 
아스콘
4 
적색투수콘
3 
점토블럭
2 
Other values (5)
7 

Length

Max length7
Median length6.5
Mean length4.6944444
Min length3

Unique

Unique3 ?
Unique (%)8.3%

Sample

1st row고압블럭
2nd row고압블럭
3rd row고압블럭
4th row투수콘/블럭
5th row투수콘/화강석

Common Values

ValueCountFrequency (%)
고압블럭 16
44.4%
투수콘/ 블럭 4
 
11.1%
아스콘 4
 
11.1%
적색투수콘 3
 
8.3%
점토블럭 2
 
5.6%
화강석/ 블럭 2
 
5.6%
초록색우레탄 2
 
5.6%
투수콘/블럭 1
 
2.8%
투수콘/화강석 1
 
2.8%
우레탄 1
 
2.8%

Length

2024-03-16T13:12:35.577159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:12:35.770360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고압블럭 16
38.1%
블럭 6
 
14.3%
투수콘 4
 
9.5%
아스콘 4
 
9.5%
적색투수콘 3
 
7.1%
점토블럭 2
 
4.8%
화강석 2
 
4.8%
초록색우레탄 2
 
4.8%
투수콘/블럭 1
 
2.4%
투수콘/화강석 1
 
2.4%

비고
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size420.0 B
표지
33 
라인
 
2
라인표지
 
1

Length

Max length4
Median length2
Mean length2.0555556
Min length2

Unique

Unique1 ?
Unique (%)2.8%

Sample

1st row표지
2nd row표지
3rd row표지
4th row표지
5th row라인표지

Common Values

ValueCountFrequency (%)
표지 33
91.7%
라인 2
 
5.6%
라인표지 1
 
2.8%

Length

2024-03-16T13:12:36.010099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:12:36.207002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
표지 33
91.7%
라인 2
 
5.6%
라인표지 1
 
2.8%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
Minimum2024-03-12 00:00:00
Maximum2024-03-12 00:00:00
2024-03-16T13:12:36.358968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:36.565317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2024-03-16T13:12:36.751940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선명자전거도로종류기점종점주요경유지방향총연장일반도로폭자전거도로폭설치연도도로재질비고
노선명1.0000.7260.9730.9671.0000.6530.8260.9780.9020.0000.5660.000
자전거도로종류0.7261.0000.8521.0001.0000.0000.7060.9260.8650.9720.8050.552
기점0.9730.8521.0000.9080.9930.7860.9280.9250.8810.0000.8631.000
종점0.9671.0000.9081.0000.9730.5260.8670.9730.9650.8410.9211.000
주요경유지1.0001.0000.9930.9731.0001.0000.9631.0000.9400.0000.9851.000
방향0.6530.0000.7860.5261.0001.0001.0000.6840.4170.3900.5220.095
총연장0.8260.7060.9280.8670.9631.0001.0000.8180.0000.0000.9671.000
일반도로폭0.9780.9260.9250.9731.0000.6840.8181.0000.8580.0000.6980.489
자전거도로폭0.9020.8650.8810.9650.9400.4170.0000.8581.0000.3260.7610.310
설치연도0.0000.9720.0000.8410.0000.3900.0000.0000.3261.0000.8301.000
도로재질0.5660.8050.8630.9210.9850.5220.9670.6980.7610.8301.0000.811
비고0.0000.5521.0001.0001.0000.0951.0000.4890.3101.0000.8111.000
2024-03-16T13:12:37.154952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비고일반도로폭자전거도로종류방향도로재질자전거도로폭
비고1.0000.1960.5490.1490.6240.117
일반도로폭0.1961.0000.5720.4460.3550.528
자전거도로종류0.5490.5721.0000.0000.5640.602
방향0.1490.4460.0001.0000.3430.307
도로재질0.6240.3550.5640.3431.0000.407
자전거도로폭0.1170.5280.6020.3070.4071.000
2024-03-16T13:12:37.354142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자전거도로종류방향일반도로폭자전거도로폭도로재질비고
자전거도로종류1.0000.0000.5720.6020.5640.549
방향0.0001.0000.4460.3070.3430.149
일반도로폭0.5720.4461.0000.5280.3550.196
자전거도로폭0.6020.3070.5281.0000.4070.117
도로재질0.5640.3430.3550.4071.0000.624
비고0.5490.1490.1960.1170.6241.000

Missing values

2024-03-16T13:12:27.452193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T13:12:27.779793image/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

노선명자전거도로종류기점종점주요경유지방향총연장일반도로폭자전거도로폭설치연도도로재질비고데이터기준일
0동일로자전거및보행자겸용도로장평교교차로군자교교차로중곡빗물펌프장양방1.5(3.0)3041996고압블럭표지2024-03-12
1광나루로56길자전거및보행자겸용도로테크노마트광남중고교입구교차로프라임아파트양방0.5(1.0)353.51996고압블럭표지2024-03-12
2아차산로70길자전거및보행자겸용도로광남중고교 입구교차로광남중입구한강시민공원연결로양방0.5(1.0)203.0(2.0)2007고압블럭표지2024-03-12
3능동로자전거및보행자겸용도로용곡삼거리군자역사거리중곡역양방1.4(2.8)254.0(2.0)1999투수콘/블럭표지2024-03-12
4능동로자전거및보행자겸용도로군자역사거리어린이대공원역세종대학교양방1.2(2.4)254.0(2.0)1996/2020투수콘/화강석라인표지2024-03-12
5능동로자전거및보행자겸용도로어린이대공원역건대입구역건국대학교병원편방0.85354.0(2.0)2005/2006점토블럭표지2024-03-12
6능동로자전거및보행자겸용도로건대입구역뚝섬유원지역신양초교편방0.95254.0(2.0)2002/2020점토블럭표지2024-03-12
7광나루로자전거및보행자겸용도로화양사거리어린이대공원역(5번출구)화양삼거리편방0.63042015투수콘/ 블럭표지2024-03-12
8광나루로자전거및보행자겸용도로화양사거리어린이대공원역(4번출구)화양삼거리편방0.573032022고압블럭표지2024-03-12
9광나루로자전거및보행자겸용도로어린이대공원역구의사거리어린이회관편방1303.51997/2020투수콘/ 블럭표지2024-03-12
노선명자전거도로종류기점종점주요경유지방향총연장일반도로폭자전거도로폭설치연도도로재질비고데이터기준일
26뚝섬로자전거및보행자겸용도로신자초교 입구교차로잠실대교북단교차로성자초교양방0.9(1.8)2241999고압블럭표지2024-03-12
27아차산로36길자전거및보행자겸용도로이마트스타시티 C동스타시티 B동편방0.27271.52007초록색우레탄표지2024-03-12
28능동로10길자전거및보행자겸용도로스타시티 C동광진문화예술회관스타시티 D동편방0.361822007초록색우레탄표지2024-03-12
29강변역로자전거및보행자겸용도로강변역(1번출구)잠실철교 입구(연결로)강변역편방0.2276.0(2.0)2007고압블럭표지2024-03-12
30중랑천자전거전용도로장평교군자교중랑천편방1.6042003/2007적색투수콘라인2024-03-12
31천호대로자전거전용도로광장사거리천호대교북단극동2차아파트편방0.2501.52018적색투수콘표지2024-03-12
32천호대로자전거전용차로군자교코오롱글로벌빌딩앞군자교입구편방0.3502.22010아스콘라인2024-03-12
33자양강변길자전거우선도로광양중학교동일로 경계뚝섬유원지역편방2.74662016아스콘표지2024-03-12
34자양로13길자전거우선도로자양로13길(자양로93)뚝섬로 교차지점자양1동주민센터양방0.55(1.1)992016아스콘표지2024-03-12
35뚝섬로52길자전거우선도로뚝섬로52길(뚝섬로630)자양유수지 체육시설경남아파트양방0.40(0.8)992016아스콘표지2024-03-12