Overview

Dataset statistics

Number of variables11
Number of observations387
Missing cells786
Missing cells (%)18.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory36.0 KiB
Average record size in memory95.3 B

Variable types

Numeric4
Text3
Categorical3
Unsupported1

Dataset

Description부천시 관내 자전거 도로 데이터로 노선명, 자전거도로 시점 , 자전거도로 종점, 자전거도로종류, 총연장 길이, 분리형 자전거도로 길이 등의 정보를 제공합니다.
Author경기도 부천시
URLhttps://www.data.go.kr/data/3080234/fileData.do

Alerts

자전거전용차로(km) is highly overall correlated with 연번 and 2 other fieldsHigh correlation
자전거전용도로(km) is highly overall correlated with 연번 and 2 other fieldsHigh correlation
자전거도로종류 is highly overall correlated with 분리형 자전거도로(km) and 3 other fieldsHigh correlation
연번 is highly overall correlated with 자전거전용도로(km) and 1 other fieldsHigh correlation
총연장길이(km) is highly overall correlated with 분리형 자전거도로(km) and 3 other fieldsHigh correlation
분리형 자전거도로(km) is highly overall correlated with 총연장길이(km) and 1 other fieldsHigh correlation
비분리형 자전거 도로(km) is highly overall correlated with 총연장길이(km) and 1 other fieldsHigh correlation
자전거도로종류 is highly imbalanced (95.4%)Imbalance
자전거전용도로(km) is highly imbalanced (96.7%)Imbalance
자전거전용차로(km) is highly imbalanced (95.5%)Imbalance
분리형 자전거도로(km) has 61 (15.8%) missing valuesMissing
비분리형 자전거 도로(km) has 333 (86.0%) missing valuesMissing
Unnamed: 10 has 387 (100.0%) missing valuesMissing
Unnamed: 10 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 13:42:44.513700
Analysis finished2023-12-12 13:42:47.672898
Duration3.16 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION 

Distinct386
Distinct (%)100.0%
Missing1
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean193.5
Minimum1
Maximum386
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-12T22:42:47.766440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile20.25
Q197.25
median193.5
Q3289.75
95-th percentile366.75
Maximum386
Range385
Interquartile range (IQR)192.5

Descriptive statistics

Standard deviation111.57285
Coefficient of variation (CV)0.57660386
Kurtosis-1.2
Mean193.5
Median Absolute Deviation (MAD)96.5
Skewness0
Sum74691
Variance12448.5
MonotonicityStrictly increasing
2023-12-12T22:42:47.957501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
291 1
 
0.3%
265 1
 
0.3%
264 1
 
0.3%
263 1
 
0.3%
262 1
 
0.3%
261 1
 
0.3%
260 1
 
0.3%
259 1
 
0.3%
258 1
 
0.3%
Other values (376) 376
97.2%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
386 1
0.3%
385 1
0.3%
384 1
0.3%
383 1
0.3%
382 1
0.3%
381 1
0.3%
380 1
0.3%
379 1
0.3%
378 1
0.3%
377 1
0.3%

노선명
Text

Distinct375
Distinct (%)97.2%
Missing1
Missing (%)0.3%
Memory size3.2 KiB
2023-12-12T22:42:48.262431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length5
Mean length6.0207254
Min length3

Characters and Unicode

Total characters2324
Distinct characters96
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

Unique368 ?
Unique (%)95.3%

Sample

1st row상이로1R
2nd row상이로2R
3rd row상이로3R
4th row부일로3R
5th row부일로5R
ValueCountFrequency (%)
상동 10
 
2.3%
옥길동 10
 
2.3%
중동 7
 
1.6%
434 4
 
0.9%
484 4
 
0.9%
1261 2
 
0.5%
계남로 2
 
0.5%
446-2 2
 
0.5%
고강동 2
 
0.5%
1255 2
 
0.5%
Other values (379) 381
89.4%
2023-12-12T22:42:48.651364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 331
 
14.2%
1 165
 
7.1%
R 156
 
6.7%
L 150
 
6.5%
길 111
 
4.8%
2 95
 
4.1%
동 74
 
3.2%
4 72
 
3.1%
3 68
 
2.9%
5 64
 
2.8%
Other values (86) 1038
44.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1288
55.4%
Decimal Number 639
27.5%
Uppercase Letter 328
 
14.1%
Space Separator 40
 
1.7%
Dash Punctuation 21
 
0.9%
Open Punctuation 4
 
0.2%
Close Punctuation 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 331
25.7%
길 111
 
8.6%
동 74
 
5.7%
대 47
 
3.6%
옥 46
 
3.6%
상 41
 
3.2%
양 36
 
2.8%
지 36
 
2.8%
주 34
 
2.6%
흥 33
 
2.6%
Other values (69) 499
38.7%
Decimal Number
ValueCountFrequency (%)
1 165
25.8%
2 95
14.9%
4 72
11.3%
3 68
10.6%
5 64
 
10.0%
6 61
 
9.5%
8 35
 
5.5%
7 34
 
5.3%
0 23
 
3.6%
9 22
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
R 156
47.6%
L 150
45.7%
C 22
 
6.7%
Space Separator
ValueCountFrequency (%)
40
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1288
55.4%
Common 708
30.5%
Latin 328
 
14.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 331
25.7%
길 111
 
8.6%
동 74
 
5.7%
대 47
 
3.6%
옥 46
 
3.6%
상 41
 
3.2%
양 36
 
2.8%
지 36
 
2.8%
주 34
 
2.6%
흥 33
 
2.6%
Other values (69) 499
38.7%
Common
ValueCountFrequency (%)
1 165
23.3%
2 95
13.4%
4 72
10.2%
3 68
9.6%
5 64
 
9.0%
6 61
 
8.6%
40
 
5.6%
8 35
 
4.9%
7 34
 
4.8%
0 23
 
3.2%
Other values (4) 51
 
7.2%
Latin
ValueCountFrequency (%)
R 156
47.6%
L 150
45.7%
C 22
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1288
55.4%
ASCII 1036
44.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 331
25.7%
길 111
 
8.6%
동 74
 
5.7%
대 47
 
3.6%
옥 46
 
3.6%
상 41
 
3.2%
양 36
 
2.8%
지 36
 
2.8%
주 34
 
2.6%
흥 33
 
2.6%
Other values (69) 499
38.7%
ASCII
ValueCountFrequency (%)
1 165
15.9%
R 156
15.1%
L 150
14.5%
2 95
9.2%
4 72
6.9%
3 68
6.6%
5 64
 
6.2%
6 61
 
5.9%
40
 
3.9%
8 35
 
3.4%
Other values (7) 130
12.5%

기점
Text

Distinct212
Distinct (%)54.9%
Missing1
Missing (%)0.3%
Memory size3.2 KiB
2023-12-12T22:42:48.886882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length12
Mean length6.1658031
Min length3

Characters and Unicode

Total characters2380
Distinct characters232
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

Unique134 ?
Unique (%)34.7%

Sample

1st row부일삼거리
2nd row구지사거리
3rd row전원사거리
4th row솔안공원입구사거리
5th row중동사거리
ValueCountFrequency (%)
옥길동 15
 
3.7%
제일풍경채 10
 
2.5%
옥길브리즈힐 10
 
2.5%
계남고가사거리 8
 
2.0%
퀸즈파크옥길 8
 
2.0%
한신휴플러스 7
 
1.7%
옥길lh1단지 6
 
1.5%
까치울사거리 5
 
1.2%
옥길동시계교차로 5
 
1.2%
옥길로 5
 
1.2%
Other values (213) 322
80.3%
2023-12-12T22:42:49.232666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 188
 
7.9%
거 170
 
7.1%
사 155
 
6.5%
길 77
 
3.2%
교 75
 
3.2%
동 73
 
3.1%
옥 65
 
2.7%
로 53
 
2.2%
중 38
 
1.6%
천 36
 
1.5%
Other values (222) 1450
60.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2215
93.1%
Decimal Number 105
 
4.4%
Uppercase Letter 35
 
1.5%
Space Separator 15
 
0.6%
Dash Punctuation 4
 
0.2%
Open Punctuation 3
 
0.1%
Close Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 188
 
8.5%
거 170
 
7.7%
사 155
 
7.0%
길 77
 
3.5%
교 75
 
3.4%
동 73
 
3.3%
옥 65
 
2.9%
로 53
 
2.4%
중 38
 
1.7%
천 36
 
1.6%
Other values (198) 1285
58.0%
Decimal Number
ValueCountFrequency (%)
1 27
25.7%
2 21
20.0%
6 12
11.4%
3 12
11.4%
5 12
11.4%
0 6
 
5.7%
9 6
 
5.7%
4 5
 
4.8%
8 2
 
1.9%
7 2
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
H 9
25.7%
L 9
25.7%
I 5
14.3%
C 4
11.4%
K 2
 
5.7%
S 2
 
5.7%
D 1
 
2.9%
G 1
 
2.9%
E 1
 
2.9%
B 1
 
2.9%
Space Separator
ValueCountFrequency (%)
15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2215
93.1%
Common 130
 
5.5%
Latin 35
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 188
 
8.5%
거 170
 
7.7%
사 155
 
7.0%
길 77
 
3.5%
교 75
 
3.4%
동 73
 
3.3%
옥 65
 
2.9%
로 53
 
2.4%
중 38
 
1.7%
천 36
 
1.6%
Other values (198) 1285
58.0%
Common
ValueCountFrequency (%)
1 27
20.8%
2 21
16.2%
15
11.5%
6 12
9.2%
3 12
9.2%
5 12
9.2%
0 6
 
4.6%
9 6
 
4.6%
4 5
 
3.8%
- 4
 
3.1%
Other values (4) 10
 
7.7%
Latin
ValueCountFrequency (%)
H 9
25.7%
L 9
25.7%
I 5
14.3%
C 4
11.4%
K 2
 
5.7%
S 2
 
5.7%
D 1
 
2.9%
G 1
 
2.9%
E 1
 
2.9%
B 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2215
93.1%
ASCII 165
 
6.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 188
 
8.5%
거 170
 
7.7%
사 155
 
7.0%
길 77
 
3.5%
교 75
 
3.4%
동 73
 
3.3%
옥 65
 
2.9%
로 53
 
2.4%
중 38
 
1.7%
천 36
 
1.6%
Other values (198) 1285
58.0%
ASCII
ValueCountFrequency (%)
1 27
16.4%
2 21
12.7%
15
9.1%
6 12
 
7.3%
3 12
 
7.3%
5 12
 
7.3%
H 9
 
5.5%
L 9
 
5.5%
0 6
 
3.6%
9 6
 
3.6%
Other values (14) 36
21.8%

종점
Text

Distinct211
Distinct (%)54.7%
Missing1
Missing (%)0.3%
Memory size3.2 KiB
2023-12-12T22:42:49.469405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length6.2253886
Min length3

Characters and Unicode

Total characters2403
Distinct characters246
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

Unique132 ?
Unique (%)34.2%

Sample

1st row구지사거리
2nd row전원사거리
3rd row흥천삼거리
4th row솔안공원입구사거리
5th row산우물사거리
ValueCountFrequency (%)
옥길동 15
 
3.7%
제일풍경채 10
 
2.5%
계남고가사거리 9
 
2.2%
퀸즈파크옥길 9
 
2.2%
옥길브리즈힐 8
 
2.0%
옥길lh1단지 7
 
1.7%
까치울사거리 6
 
1.5%
한신휴플러스 6
 
1.5%
옥길로 5
 
1.2%
중원고사거리 4
 
1.0%
Other values (215) 325
80.4%
2023-12-12T22:42:49.862028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 187
 
7.8%
거 171
 
7.1%
사 155
 
6.5%
길 83
 
3.5%
교 67
 
2.8%
옥 63
 
2.6%
동 62
 
2.6%
로 60
 
2.5%
중 40
 
1.7%
삼 39
 
1.6%
Other values (236) 1476
61.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2236
93.1%
Decimal Number 105
 
4.4%
Uppercase Letter 37
 
1.5%
Space Separator 18
 
0.7%
Dash Punctuation 3
 
0.1%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 187
 
8.4%
거 171
 
7.6%
사 155
 
6.9%
길 83
 
3.7%
교 67
 
3.0%
옥 63
 
2.8%
동 62
 
2.8%
로 60
 
2.7%
중 40
 
1.8%
삼 39
 
1.7%
Other values (214) 1309
58.5%
Decimal Number
ValueCountFrequency (%)
1 26
24.8%
2 24
22.9%
8 10
 
9.5%
4 9
 
8.6%
5 9
 
8.6%
3 8
 
7.6%
6 6
 
5.7%
0 5
 
4.8%
7 4
 
3.8%
9 4
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
L 11
29.7%
H 10
27.0%
I 5
13.5%
C 4
 
10.8%
S 2
 
5.4%
K 2
 
5.4%
G 2
 
5.4%
B 1
 
2.7%
Space Separator
ValueCountFrequency (%)
18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2236
93.1%
Common 130
 
5.4%
Latin 37
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 187
 
8.4%
거 171
 
7.6%
사 155
 
6.9%
길 83
 
3.7%
교 67
 
3.0%
옥 63
 
2.8%
동 62
 
2.8%
로 60
 
2.7%
중 40
 
1.8%
삼 39
 
1.7%
Other values (214) 1309
58.5%
Common
ValueCountFrequency (%)
1 26
20.0%
2 24
18.5%
18
13.8%
8 10
 
7.7%
4 9
 
6.9%
5 9
 
6.9%
3 8
 
6.2%
6 6
 
4.6%
0 5
 
3.8%
7 4
 
3.1%
Other values (4) 11
8.5%
Latin
ValueCountFrequency (%)
L 11
29.7%
H 10
27.0%
I 5
13.5%
C 4
 
10.8%
S 2
 
5.4%
K 2
 
5.4%
G 2
 
5.4%
B 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2236
93.1%
ASCII 167
 
6.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 187
 
8.4%
거 171
 
7.6%
사 155
 
6.9%
길 83
 
3.7%
교 67
 
3.0%
옥 63
 
2.8%
동 62
 
2.8%
로 60
 
2.7%
중 40
 
1.8%
삼 39
 
1.7%
Other values (214) 1309
58.5%
ASCII
ValueCountFrequency (%)
1 26
15.6%
2 24
14.4%
18
10.8%
L 11
 
6.6%
H 10
 
6.0%
8 10
 
6.0%
4 9
 
5.4%
5 9
 
5.4%
3 8
 
4.8%
6 6
 
3.6%
Other values (12) 36
21.6%

자전거도로종류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
겸용도로
384 
전용도로
 
2
<NA>
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
겸용도로 384
99.2%
전용도로 2
 
0.5%
<NA> 1
 
0.3%

Length

2023-12-12T22:42:49.984125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:42:50.083010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
겸용도로 384
99.2%
전용도로 2
 
0.5%
na 1
 
0.3%

총연장길이(km)
Real number (ℝ)

HIGH CORRELATION 

Distinct76
Distinct (%)19.7%
Missing1
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean0.27129534
Minimum0.01
Maximum1.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-12T22:42:50.201481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.01
Q10.08
median0.245
Q30.39
95-th percentile0.7
Maximum1.72
Range1.71
Interquartile range (IQR)0.31

Descriptive statistics

Standard deviation0.2372349
Coefficient of variation (CV)0.87445254
Kurtosis4.7015406
Mean0.27129534
Median Absolute Deviation (MAD)0.155
Skewness1.5985523
Sum104.72
Variance0.056280396
MonotonicityNot monotonic
2023-12-12T22:42:50.352818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.02 37
 
9.6%
0.01 32
 
8.3%
0.25 12
 
3.1%
0.28 11
 
2.8%
0.27 10
 
2.6%
0.12 10
 
2.6%
0.18 10
 
2.6%
0.36 9
 
2.3%
0.19 8
 
2.1%
0.35 8
 
2.1%
Other values (66) 239
61.8%
ValueCountFrequency (%)
0.01 32
8.3%
0.02 37
9.6%
0.03 7
 
1.8%
0.04 5
 
1.3%
0.05 2
 
0.5%
0.06 6
 
1.6%
0.07 6
 
1.6%
0.08 4
 
1.0%
0.1 6
 
1.6%
0.11 6
 
1.6%
ValueCountFrequency (%)
1.72 1
 
0.3%
1.23 1
 
0.3%
1.2 1
 
0.3%
1.16 1
 
0.3%
1.0 2
0.5%
0.9 2
0.5%
0.85 3
0.8%
0.84 2
0.5%
0.82 1
 
0.3%
0.8 1
 
0.3%

분리형 자전거도로(km)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct68
Distinct (%)20.9%
Missing61
Missing (%)15.8%
Infinite0
Infinite (%)0.0%
Mean0.25104294
Minimum0.01
Maximum1.23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-12T22:42:50.534665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.01
Q10.06
median0.23
Q30.36
95-th percentile0.66
Maximum1.23
Range1.22
Interquartile range (IQR)0.3

Descriptive statistics

Standard deviation0.21665744
Coefficient of variation (CV)0.8630294
Kurtosis2.4296841
Mean0.25104294
Median Absolute Deviation (MAD)0.15
Skewness1.2582012
Sum81.84
Variance0.046940447
MonotonicityNot monotonic
2023-12-12T22:42:50.714406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.02 36
 
9.3%
0.01 32
 
8.3%
0.25 11
 
2.8%
0.28 10
 
2.6%
0.27 9
 
2.3%
0.36 9
 
2.3%
0.16 8
 
2.1%
0.03 7
 
1.8%
0.18 7
 
1.8%
0.31 7
 
1.8%
Other values (58) 190
49.1%
(Missing) 61
 
15.8%
ValueCountFrequency (%)
0.01 32
8.3%
0.02 36
9.3%
0.03 7
 
1.8%
0.04 4
 
1.0%
0.06 4
 
1.0%
0.07 6
 
1.6%
0.08 3
 
0.8%
0.1 6
 
1.6%
0.11 5
 
1.3%
0.12 6
 
1.6%
ValueCountFrequency (%)
1.23 1
0.3%
1.2 1
0.3%
1.0 2
0.5%
0.9 1
0.3%
0.85 1
0.3%
0.84 1
0.3%
0.82 1
0.3%
0.8 1
0.3%
0.78 1
0.3%
0.75 1
0.3%

비분리형 자전거 도로(km)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct40
Distinct (%)74.1%
Missing333
Missing (%)86.0%
Infinite0
Infinite (%)0.0%
Mean0.38222222
Minimum0.02
Maximum1.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-12T22:42:50.918821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.02
5-th percentile0.05
Q10.18
median0.325
Q30.48
95-th percentile0.8675
Maximum1.72
Range1.7
Interquartile range (IQR)0.3

Descriptive statistics

Standard deviation0.31323429
Coefficient of variation (CV)0.81950833
Kurtosis5.4100973
Mean0.38222222
Median Absolute Deviation (MAD)0.155
Skewness1.8900857
Sum20.64
Variance0.098115723
MonotonicityNot monotonic
2023-12-12T22:42:51.081677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
0.48 3
 
0.8%
0.12 3
 
0.8%
0.18 3
 
0.8%
0.41 2
 
0.5%
0.4 2
 
0.5%
0.22 2
 
0.5%
0.24 2
 
0.5%
0.19 2
 
0.5%
0.39 2
 
0.5%
0.05 2
 
0.5%
Other values (30) 31
 
8.0%
(Missing) 333
86.0%
ValueCountFrequency (%)
0.02 1
 
0.3%
0.04 1
 
0.3%
0.05 2
0.5%
0.06 2
0.5%
0.08 1
 
0.3%
0.11 1
 
0.3%
0.12 3
0.8%
0.14 1
 
0.3%
0.18 3
0.8%
0.19 2
0.5%
ValueCountFrequency (%)
1.72 1
0.3%
1.16 1
0.3%
0.9 1
0.3%
0.85 1
0.3%
0.84 1
0.3%
0.79 1
0.3%
0.71 1
0.3%
0.7 1
0.3%
0.65 1
0.3%
0.62 1
0.3%

자전거전용도로(km)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
385 
0.22
 
1
0.25
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique2 ?
Unique (%)0.5%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 385
99.5%
0.22 1
 
0.3%
0.25 1
 
0.3%

Length

2023-12-12T22:42:51.235057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:42:51.354439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 385
99.5%
0.22 1
 
0.3%
0.25 1
 
0.3%

자전거전용차로(km)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
383 
0.12
 
1
0.5
 
1
0.3
 
1
0.85
 
1

Length

Max length4
Median length4
Mean length3.994832
Min length3

Unique

Unique4 ?
Unique (%)1.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 383
99.0%
0.12 1
 
0.3%
0.5 1
 
0.3%
0.3 1
 
0.3%
0.85 1
 
0.3%

Length

2023-12-12T22:42:51.467824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:42:51.581689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 383
99.0%
0.12 1
 
0.3%
0.5 1
 
0.3%
0.3 1
 
0.3%
0.85 1
 
0.3%

Unnamed: 10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing387
Missing (%)100.0%
Memory size3.5 KiB

Interactions

2023-12-12T22:42:46.425499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:42:45.136916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:42:45.556072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:42:45.946702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:42:46.878871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:42:45.246567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:42:45.671992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:42:46.072772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:42:46.992925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:42:45.362225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:42:45.766825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:42:46.200580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:42:47.087163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:42:45.457700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:42:45.853086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:42:46.319885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:42:51.670846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번자전거도로종류총연장길이(km)분리형 자전거도로(km)비분리형 자전거 도로(km)자전거전용도로(km)자전거전용차로(km)
연번1.0000.0000.4120.5920.2530.0001.000
자전거도로종류0.0001.0000.000NaNNaNNaNNaN
총연장길이(km)0.4120.0001.0000.9421.000NaN1.000
분리형 자전거도로(km)0.592NaN0.9421.000NaNNaNNaN
비분리형 자전거 도로(km)0.253NaN1.000NaN1.000NaNNaN
자전거전용도로(km)0.000NaNNaNNaNNaN1.000NaN
자전거전용차로(km)1.000NaN1.000NaNNaNNaN1.000
2023-12-12T22:42:51.789214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자전거전용차로(km)자전거전용도로(km)자전거도로종류
자전거전용차로(km)1.000NaN1.000
자전거전용도로(km)NaN1.0001.000
자전거도로종류1.0001.0001.000
2023-12-12T22:42:51.888893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번총연장길이(km)분리형 자전거도로(km)비분리형 자전거 도로(km)자전거도로종류자전거전용도로(km)자전거전용차로(km)
연번1.0000.3970.4090.1820.0001.0001.000
총연장길이(km)0.3971.0001.0001.0000.0001.0001.000
분리형 자전거도로(km)0.4091.0001.000NaN1.0000.0000.000
비분리형 자전거 도로(km)0.1821.000NaN1.0001.0000.0000.000
자전거도로종류0.0000.0001.0001.0001.0001.0001.000
자전거전용도로(km)1.0001.0000.0000.0001.0001.0000.000
자전거전용차로(km)1.0001.0000.0000.0001.0000.0001.000

Missing values

2023-12-12T22:42:47.229846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:42:47.402216image/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.
2023-12-12T22:42:47.555911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번노선명기점종점자전거도로종류총연장길이(km)분리형 자전거도로(km)비분리형 자전거 도로(km)자전거전용도로(km)자전거전용차로(km)Unnamed: 10
01상이로1R부일삼거리구지사거리겸용도로0.270.27<NA><NA><NA><NA>
12상이로2R구지사거리전원사거리겸용도로0.250.25<NA><NA><NA><NA>
23상이로3R전원사거리흥천삼거리겸용도로0.310.31<NA><NA><NA><NA>
34부일로3R솔안공원입구사거리솔안공원입구사거리겸용도로0.020.02<NA><NA><NA><NA>
45부일로5R중동사거리산우물사거리겸용도로0.630.63<NA><NA><NA><NA>
56부일로6R산우물사거리전화국사거리겸용도로0.310.31<NA><NA><NA><NA>
67부일로1L부일삼거리서촌사거리겸용도로0.280.28<NA><NA><NA><NA>
78부일로3L솔안공원입구사거리솔안공원입구사거리겸용도로0.020.02<NA><NA><NA><NA>
89부일로6L중동사거리산우물사거리겸용도로0.60.6<NA><NA><NA><NA>
910부일로1C솔안공원입구사거리솔안공원입구사거리겸용도로0.020.02<NA><NA><NA><NA>
연번노선명기점종점자전거도로종류총연장길이(km)분리형 자전거도로(km)비분리형 자전거 도로(km)자전거전용도로(km)자전거전용차로(km)Unnamed: 10
377378중동로280번길 61중흥공원중동로 280번길 61겸용도로0.310.31<NA><NA><NA><NA>
378379도약로 112도약로 112계남로 115겸용도로0.280.28<NA><NA><NA><NA>
379380계남로 165계남로 165중동로 279번길 50겸용도로0.290.29<NA><NA><NA><NA>
380381석천로216석천로216(상가)중동로 301겸용도로0.490.49<NA><NA><NA><NA>
381382상동로 117번길 48서해그랑블1차 2323동 옆상동로 117번길 48겸용도로0.190.19<NA><NA><NA><NA>
382383계남로 106-1계남로 106-1부광초교 정문겸용도로0.220.22<NA><NA><NA><NA>
383384상동 546상동 546(2046동 옆)행복한어린이공원겸용도로0.280.28<NA><NA><NA><NA>
384385상일초교버스 정류장상일초교버스 정류장(ID 11033)풍림아이원 2729동 옆겸용도로0.370.37<NA><NA><NA><NA>
385386대장1교삼정교대장1교겸용도로0.840.84<NA><NA><NA><NA>
386<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>