Overview

Dataset statistics

Number of variables8
Number of observations153
Missing cells139
Missing cells (%)11.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.0 KiB
Average record size in memory66.9 B

Variable types

Numeric2
Text4
Categorical2

Dataset

Description해당 데이터는 인천광역시 남동구의 자전거도로현황에 관련된 자료로서, 인천광역시 남동구 자전거도로현황의 노선번호, 노선명, 자전거 도로의 종류, 기점, 종점, 주요경유지, 총길이(㎞), 데이터기준일자의 정보를 확인할 수 있다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15067448&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
주요경유지 has 139 (90.8%) missing valuesMissing
노선번호 has unique valuesUnique

Reproduction

Analysis started2024-01-28 09:18:54.165890
Analysis finished2024-01-28 09:18:54.998362
Duration0.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

노선번호
Real number (ℝ)

UNIQUE 

Distinct153
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77
Minimum1
Maximum153
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-01-28T18:18:55.053616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.6
Q139
median77
Q3115
95-th percentile145.4
Maximum153
Range152
Interquartile range (IQR)76

Descriptive statistics

Standard deviation44.311398
Coefficient of variation (CV)0.5754727
Kurtosis-1.2
Mean77
Median Absolute Deviation (MAD)38
Skewness0
Sum11781
Variance1963.5
MonotonicityStrictly increasing
2024-01-28T18:18:55.177495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
106 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
101 1
 
0.7%
102 1
 
0.7%
103 1
 
0.7%
104 1
 
0.7%
105 1
 
0.7%
107 1
 
0.7%
Other values (143) 143
93.5%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
153 1
0.7%
152 1
0.7%
151 1
0.7%
150 1
0.7%
149 1
0.7%
148 1
0.7%
147 1
0.7%
146 1
0.7%
145 1
0.7%
144 1
0.7%

노선명
Text

Distinct152
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-28T18:18:55.428700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length19
Mean length7.8823529
Min length3

Characters and Unicode

Total characters1206
Distinct characters78
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

Unique151 ?
Unique (%)98.7%

Sample

1st row소래역남로 1R
2nd row소래역남로 1L
3rd row아암대로1
4th row아암대로2
5th row아암대로1437번길 1R
ValueCountFrequency (%)
1r 23
 
8.3%
1l 20
 
7.2%
2r 14
 
5.1%
2l 11
 
4.0%
l 10
 
3.6%
인주대로 9
 
3.2%
매소홀로 9
 
3.2%
r 8
 
2.9%
백범로 7
 
2.5%
청능대로 6
 
2.2%
Other values (97) 160
57.8%
2024-01-28T18:18:55.774028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 134
 
11.1%
124
 
10.3%
1 92
 
7.6%
R 89
 
7.4%
L 73
 
6.1%
2 54
 
4.5%
3 50
 
4.1%
대 47
 
3.9%
남 34
 
2.8%
- 33
 
2.7%
Other values (68) 476
39.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 576
47.8%
Decimal Number 281
23.3%
Uppercase Letter 162
 
13.4%
Space Separator 124
 
10.3%
Dash Punctuation 33
 
2.7%
Open Punctuation 15
 
1.2%
Close Punctuation 15
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 134
23.3%
대 47
 
8.2%
남 34
 
5.9%
중 25
 
4.3%
동 18
 
3.1%
인 17
 
3.0%
소 17
 
3.0%
창 15
 
2.6%
서 15
 
2.6%
고 14
 
2.4%
Other values (52) 240
41.7%
Decimal Number
ValueCountFrequency (%)
1 92
32.7%
2 54
19.2%
3 50
17.8%
6 21
 
7.5%
4 16
 
5.7%
0 16
 
5.7%
7 14
 
5.0%
5 12
 
4.3%
8 4
 
1.4%
9 2
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
R 89
54.9%
L 73
45.1%
Space Separator
ValueCountFrequency (%)
124
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 576
47.8%
Common 468
38.8%
Latin 162
 
13.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 134
23.3%
대 47
 
8.2%
남 34
 
5.9%
중 25
 
4.3%
동 18
 
3.1%
인 17
 
3.0%
소 17
 
3.0%
창 15
 
2.6%
서 15
 
2.6%
고 14
 
2.4%
Other values (52) 240
41.7%
Common
ValueCountFrequency (%)
124
26.5%
1 92
19.7%
2 54
11.5%
3 50
10.7%
- 33
 
7.1%
6 21
 
4.5%
4 16
 
3.4%
0 16
 
3.4%
( 15
 
3.2%
) 15
 
3.2%
Other values (4) 32
 
6.8%
Latin
ValueCountFrequency (%)
R 89
54.9%
L 73
45.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 630
52.2%
Hangul 576
47.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 134
23.3%
대 47
 
8.2%
남 34
 
5.9%
중 25
 
4.3%
동 18
 
3.1%
인 17
 
3.0%
소 17
 
3.0%
창 15
 
2.6%
서 15
 
2.6%
고 14
 
2.4%
Other values (52) 240
41.7%
ASCII
ValueCountFrequency (%)
124
19.7%
1 92
14.6%
R 89
14.1%
L 73
11.6%
2 54
8.6%
3 50
7.9%
- 33
 
5.2%
6 21
 
3.3%
4 16
 
2.5%
0 16
 
2.5%
Other values (6) 62
9.8%

자전거 도로의 종류
Categorical

Distinct3
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
겸용도로(분리형)
118 
전용도로
20 
겸용도로(비분리형)
15 

Length

Max length10
Median length9
Mean length8.4444444
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row겸용도로(분리형)
2nd row겸용도로(분리형)
3rd row전용도로
4th row겸용도로(비분리형)
5th row전용도로

Common Values

ValueCountFrequency (%)
겸용도로(분리형) 118
77.1%
전용도로 20
 
13.1%
겸용도로(비분리형) 15
 
9.8%

Length

2024-01-28T18:18:55.887861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:18:55.980961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
겸용도로(분리형 118
77.1%
전용도로 20
 
13.1%
겸용도로(비분리형 15
 
9.8%

기점
Text

Distinct105
Distinct (%)68.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-28T18:18:56.240881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length6.869281
Min length3

Characters and Unicode

Total characters1051
Distinct characters119
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique69 ?
Unique (%)45.1%

Sample

1st row아암대로
2nd row아암대로
3rd row아암대로 1437번길
4th row아암2교
5th row아암대로
ValueCountFrequency (%)
인주대로 7
 
3.4%
아암대로 6
 
2.9%
앵고개로 5
 
2.4%
청능대로 4
 
1.9%
길병원사거리 4
 
1.9%
백범로 4
 
1.9%
중(보)1-313 4
 
1.9%
남동구 4
 
1.9%
논현동 3
 
1.5%
남동대로 3
 
1.5%
Other values (119) 162
78.6%
2024-01-28T18:18:56.627975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 82
 
7.8%
1 60
 
5.7%
57
 
5.4%
대 42
 
4.0%
동 39
 
3.7%
- 35
 
3.3%
3 33
 
3.1%
2 30
 
2.9%
0 29
 
2.8%
6 27
 
2.6%
Other values (109) 617
58.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 634
60.3%
Decimal Number 282
26.8%
Space Separator 57
 
5.4%
Dash Punctuation 35
 
3.3%
Close Punctuation 20
 
1.9%
Open Punctuation 20
 
1.9%
Math Symbol 2
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 82
 
12.9%
대 42
 
6.6%
동 39
 
6.2%
남 26
 
4.1%
중 21
 
3.3%
리 20
 
3.2%
거 18
 
2.8%
사 17
 
2.7%
구 16
 
2.5%
길 14
 
2.2%
Other values (93) 339
53.5%
Decimal Number
ValueCountFrequency (%)
1 60
21.3%
3 33
11.7%
2 30
10.6%
0 29
10.3%
6 27
9.6%
4 27
9.6%
7 24
 
8.5%
5 22
 
7.8%
8 21
 
7.4%
9 9
 
3.2%
Space Separator
ValueCountFrequency (%)
57
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Other Punctuation
ValueCountFrequency (%)
@ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 634
60.3%
Common 417
39.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 82
 
12.9%
대 42
 
6.6%
동 39
 
6.2%
남 26
 
4.1%
중 21
 
3.3%
리 20
 
3.2%
거 18
 
2.8%
사 17
 
2.7%
구 16
 
2.5%
길 14
 
2.2%
Other values (93) 339
53.5%
Common
ValueCountFrequency (%)
1 60
14.4%
57
13.7%
- 35
8.4%
3 33
7.9%
2 30
7.2%
0 29
 
7.0%
6 27
 
6.5%
4 27
 
6.5%
7 24
 
5.8%
5 22
 
5.3%
Other values (6) 73
17.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 634
60.3%
ASCII 417
39.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 82
 
12.9%
대 42
 
6.6%
동 39
 
6.2%
남 26
 
4.1%
중 21
 
3.3%
리 20
 
3.2%
거 18
 
2.8%
사 17
 
2.7%
구 16
 
2.5%
길 14
 
2.2%
Other values (93) 339
53.5%
ASCII
ValueCountFrequency (%)
1 60
14.4%
57
13.7%
- 35
8.4%
3 33
7.9%
2 30
7.2%
0 29
 
7.0%
6 27
 
6.5%
4 27
 
6.5%
7 24
 
5.8%
5 22
 
5.3%
Other values (6) 73
17.5%

종점
Text

Distinct93
Distinct (%)60.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-28T18:18:56.899675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length6.4901961
Min length3

Characters and Unicode

Total characters993
Distinct characters119
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

Unique59 ?
Unique (%)38.6%

Sample

1st row앵고개로
2nd row앵고개로
3rd row아암2교
4th row에코중앙로
5th row에코중앙로
ValueCountFrequency (%)
대2-76 8
 
4.1%
청능대로 6
 
3.1%
인주대로 6
 
3.1%
소래로 6
 
3.1%
앵고개로 4
 
2.0%
아암대로 4
 
2.0%
올림픽공원사거리 4
 
2.0%
대3-105 4
 
2.0%
백범로 4
 
2.0%
전재울사거리 3
 
1.5%
Other values (105) 147
75.0%
2024-01-28T18:18:57.262555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 76
 
7.7%
1 50
 
5.0%
44
 
4.4%
대 43
 
4.3%
- 34
 
3.4%
6 34
 
3.4%
0 30
 
3.0%
2 30
 
3.0%
동 29
 
2.9%
3 29
 
2.9%
Other values (109) 594
59.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 625
62.9%
Decimal Number 262
26.4%
Space Separator 44
 
4.4%
Dash Punctuation 34
 
3.4%
Open Punctuation 12
 
1.2%
Close Punctuation 12
 
1.2%
Uppercase Letter 4
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 76
 
12.2%
대 43
 
6.9%
동 29
 
4.6%
리 24
 
3.8%
거 22
 
3.5%
사 19
 
3.0%
중 18
 
2.9%
구 18
 
2.9%
남 18
 
2.9%
소 16
 
2.6%
Other values (93) 342
54.7%
Decimal Number
ValueCountFrequency (%)
1 50
19.1%
6 34
13.0%
0 30
11.5%
2 30
11.5%
3 29
11.1%
4 26
9.9%
7 24
9.2%
8 17
 
6.5%
5 17
 
6.5%
9 5
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
B 2
50.0%
L 2
50.0%
Space Separator
ValueCountFrequency (%)
44
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 625
62.9%
Common 364
36.7%
Latin 4
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 76
 
12.2%
대 43
 
6.9%
동 29
 
4.6%
리 24
 
3.8%
거 22
 
3.5%
사 19
 
3.0%
중 18
 
2.9%
구 18
 
2.9%
남 18
 
2.9%
소 16
 
2.6%
Other values (93) 342
54.7%
Common
ValueCountFrequency (%)
1 50
13.7%
44
12.1%
- 34
9.3%
6 34
9.3%
0 30
8.2%
2 30
8.2%
3 29
8.0%
4 26
7.1%
7 24
6.6%
8 17
 
4.7%
Other values (4) 46
12.6%
Latin
ValueCountFrequency (%)
B 2
50.0%
L 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 625
62.9%
ASCII 368
37.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 76
 
12.2%
대 43
 
6.9%
동 29
 
4.6%
리 24
 
3.8%
거 22
 
3.5%
사 19
 
3.0%
중 18
 
2.9%
구 18
 
2.9%
남 18
 
2.9%
소 16
 
2.6%
Other values (93) 342
54.7%
ASCII
ValueCountFrequency (%)
1 50
13.6%
44
12.0%
- 34
9.2%
6 34
9.2%
0 30
8.2%
2 30
8.2%
3 29
7.9%
4 26
7.1%
7 24
6.5%
8 17
 
4.6%
Other values (6) 50
13.6%

주요경유지
Text

MISSING 

Distinct12
Distinct (%)85.7%
Missing139
Missing (%)90.8%
Memory size1.3 KiB
2024-01-28T18:18:57.420335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length7.2142857
Min length4

Characters and Unicode

Total characters101
Distinct characters51
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

Unique10 ?
Unique (%)71.4%

Sample

1st row에코메트로3차더타워
2nd row에코메트로5단지아파트
3rd row사리울초등학교
4th row에코메트로9단지 아파트
5th row스퀘이어
ValueCountFrequency (%)
사리골사거리 2
13.3%
인천논현역 2
13.3%
에코메트로3차더타워 1
 
6.7%
에코메트로5단지아파트 1
 
6.7%
사리울초등학교 1
 
6.7%
에코메트로9단지 1
 
6.7%
아파트 1
 
6.7%
스퀘이어 1
 
6.7%
남동대교 1
 
6.7%
소래포구어시장 1
 
6.7%
Other values (3) 3
20.0%
2024-01-28T18:18:57.662982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
트 6
 
5.9%
사 5
 
5.0%
리 5
 
5.0%
코 3
 
3.0%
지 3
 
3.0%
단 3
 
3.0%
교 3
 
3.0%
로 3
 
3.0%
파 3
 
3.0%
메 3
 
3.0%
Other values (41) 64
63.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 95
94.1%
Decimal Number 5
 
5.0%
Space Separator 1
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
트 6
 
6.3%
사 5
 
5.3%
리 5
 
5.3%
코 3
 
3.2%
지 3
 
3.2%
단 3
 
3.2%
교 3
 
3.2%
로 3
 
3.2%
파 3
 
3.2%
메 3
 
3.2%
Other values (35) 58
61.1%
Decimal Number
ValueCountFrequency (%)
3 1
20.0%
1 1
20.0%
5 1
20.0%
9 1
20.0%
0 1
20.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 95
94.1%
Common 6
 
5.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
트 6
 
6.3%
사 5
 
5.3%
리 5
 
5.3%
코 3
 
3.2%
지 3
 
3.2%
단 3
 
3.2%
교 3
 
3.2%
로 3
 
3.2%
파 3
 
3.2%
메 3
 
3.2%
Other values (35) 58
61.1%
Common
ValueCountFrequency (%)
3 1
16.7%
1 1
16.7%
5 1
16.7%
1
16.7%
9 1
16.7%
0 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 95
94.1%
ASCII 6
 
5.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
트 6
 
6.3%
사 5
 
5.3%
리 5
 
5.3%
코 3
 
3.2%
지 3
 
3.2%
단 3
 
3.2%
교 3
 
3.2%
로 3
 
3.2%
파 3
 
3.2%
메 3
 
3.2%
Other values (35) 58
61.1%
ASCII
ValueCountFrequency (%)
3 1
16.7%
1 1
16.7%
5 1
16.7%
1
16.7%
9 1
16.7%
0 1
16.7%

총길이(킬로미터)
Real number (ℝ)

Distinct80
Distinct (%)52.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.88189542
Minimum0.04
Maximum4.98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-01-28T18:18:57.769162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.04
5-th percentile0.116
Q10.27
median0.55
Q31.2
95-th percentile2.582
Maximum4.98
Range4.94
Interquartile range (IQR)0.93

Descriptive statistics

Standard deviation0.8435278
Coefficient of variation (CV)0.95649413
Kurtosis3.1997694
Mean0.88189542
Median Absolute Deviation (MAD)0.33
Skewness1.6590071
Sum134.93
Variance0.71153915
MonotonicityNot monotonic
2024-01-28T18:18:57.883126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.26 7
 
4.6%
0.25 5
 
3.3%
0.2 5
 
3.3%
1.2 4
 
2.6%
0.1 4
 
2.6%
0.55 4
 
2.6%
0.5 4
 
2.6%
0.52 3
 
2.0%
0.27 3
 
2.0%
2.2 3
 
2.0%
Other values (70) 111
72.5%
ValueCountFrequency (%)
0.04 1
 
0.7%
0.1 4
2.6%
0.11 3
2.0%
0.12 2
 
1.3%
0.13 2
 
1.3%
0.16 2
 
1.3%
0.17 1
 
0.7%
0.19 2
 
1.3%
0.2 5
3.3%
0.22 3
2.0%
ValueCountFrequency (%)
4.98 1
0.7%
3.2 1
0.7%
3.12 1
0.7%
2.82 1
0.7%
2.7 2
1.3%
2.63 2
1.3%
2.55 2
1.3%
2.4 2
1.3%
2.33 1
0.7%
2.3 2
1.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-08-07
153 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-07
2nd row2023-08-07
3rd row2023-08-07
4th row2023-08-07
5th row2023-08-07

Common Values

ValueCountFrequency (%)
2023-08-07 153
100.0%

Length

2024-01-28T18:18:57.997997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:18:58.081283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-07 153
100.0%

Interactions

2024-01-28T18:18:54.689219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:18:54.505415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:18:54.758863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:18:54.598804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T18:18:58.126598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호자전거 도로의 종류종점주요경유지총길이(킬로미터)
노선번호1.0000.5100.9781.0000.381
자전거 도로의 종류0.5101.0000.7871.0000.103
종점0.9780.7871.0001.0000.826
주요경유지1.0001.0001.0001.0001.000
총길이(킬로미터)0.3810.1030.8261.0001.000
2024-01-28T18:18:58.212330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호총길이(킬로미터)자전거 도로의 종류
노선번호1.000-0.2200.347
총길이(킬로미터)-0.2201.0000.062
자전거 도로의 종류0.3470.0621.000

Missing values

2024-01-28T18:18:54.843175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T18:18:54.955922image/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

노선번호노선명자전거 도로의 종류기점종점주요경유지총길이(킬로미터)데이터기준일자
01소래역남로 1R겸용도로(분리형)아암대로앵고개로에코메트로3차더타워0.52023-08-07
12소래역남로 1L겸용도로(분리형)아암대로앵고개로에코메트로5단지아파트0.52023-08-07
23아암대로1전용도로아암대로 1437번길아암2교<NA>1.512023-08-07
34아암대로2겸용도로(비분리형)아암2교에코중앙로<NA>1.02023-08-07
45아암대로1437번길 1R전용도로아암대로에코중앙로사리울초등학교0.342023-08-07
56아암대로1437번길 1L전용도로아암대로에코중앙로에코메트로9단지 아파트0.342023-08-07
67청능대로 남동대교 1R겸용도로(분리형)스퀘어어1청능대로스퀘이어0.192023-08-07
78청능대로 남동대교 1L겸용도로(분리형)스퀘어어1청능대로남동대교0.192023-08-07
89청능대로 1R전용도로남동대교청능대로 484번길 4사리골사거리2.552023-08-07
910청능대로 1R전용도로남동대교청능대로 484번길 4사리골사거리2.552023-08-07
노선번호노선명자전거 도로의 종류기점종점주요경유지총길이(킬로미터)데이터기준일자
143144중2-604 R겸용도로(분리형)중(보)1-315대2-76<NA>0.42023-08-07
144145중2-604 L겸용도로(비분리형)중(보)1-315대2-76<NA>0.42023-08-07
145146중2-605 R겸용도로(분리형)중(집)2-604공동주택 13BL<NA>0.12023-08-07
146147중2-605 L겸용도로(비분리형)중(집)2-604공동주택 13BL<NA>0.12023-08-07
147148중3-369 L겸용도로(분리형)중(집)2-602서창2지구 서측 지구계<NA>0.112023-08-07
148149중3-369 R겸용도로(비분리형)중(집)2-602서창2지구 서측 지구계<NA>0.112023-08-07
149150중3-371 R겸용도로(분리형)대3-106대3-106<NA>0.22023-08-07
150151중3-371 L겸용도로(비분리형)대3-106대3-106<NA>0.22023-08-07
151152중3-372 R겸용도로(분리형)대3-107대3-107<NA>0.22023-08-07
152153중3-372 L겸용도로(비분리형)대3-107대3-107<NA>0.22023-08-07