Overview

Dataset statistics

Number of variables22
Number of observations274
Missing cells767
Missing cells (%)12.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory51.2 KiB
Average record size in memory191.5 B

Variable types

Numeric14
Text4
Boolean1
Categorical2
DateTime1

Dataset

Description전주시 관내 자전거 도로에 대한 정보입니다.항목 : 일련번호, 노선명, 기점, 기점경도, 기점위도, 중기점, 중기점경도, 중기점위도, 종점, 종점경도, 종점위도, 도로연계성, 자전거도로종류, 연장(km), 전용도로폭원, 자전거도로폭원(분리형), 보도폭원(분리형), 유효폭원측정1(비분리형), 도로폭원(비분리형), 유효폭원측정2(비분리형), 보행량(점)제공부서 : 자전거정책과
Author전북특별자치도 전주시
URLhttps://www.data.go.kr/data/3079829/fileData.do

Alerts

도로연계성 has constant value ""Constant
데이터기준일자 has constant value ""Constant
자전거도로 종류 is highly imbalanced (76.7%)Imbalance
기점 has 45 (16.4%) missing valuesMissing
기점 경도 has 91 (33.2%) missing valuesMissing
기점 위도 has 91 (33.2%) missing valuesMissing
중기점 has 45 (16.4%) missing valuesMissing
중기점 경도 has 91 (33.2%) missing valuesMissing
중기점 위도 has 91 (33.2%) missing valuesMissing
종점 has 45 (16.4%) missing valuesMissing
종점 경도 has 91 (33.2%) missing valuesMissing
종점 위도 has 91 (33.2%) missing valuesMissing
도로연계성 has 86 (31.4%) missing valuesMissing
일련번호 has unique valuesUnique
전용도로 폭원 has 268 (97.8%) zerosZeros
자전거도로 폭원(분리형) has 173 (63.1%) zerosZeros
보도 폭원(분리형) has 173 (63.1%) zerosZeros
유효폭원측정1(비분리형) has 173 (63.1%) zerosZeros
도로폭원(비분리형) has 104 (38.0%) zerosZeros
유효폭원측정2(비분리형) has 104 (38.0%) zerosZeros

Reproduction

Analysis started2024-03-14 23:46:28.202328
Analysis finished2024-03-14 23:46:28.992269
Duration0.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호
Real number (ℝ)

UNIQUE 

Distinct274
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean137.5
Minimum1
Maximum274
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-15T08:46:29.120148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14.65
Q169.25
median137.5
Q3205.75
95-th percentile260.35
Maximum274
Range273
Interquartile range (IQR)136.5

Descriptive statistics

Standard deviation79.241193
Coefficient of variation (CV)0.57629959
Kurtosis-1.2
Mean137.5
Median Absolute Deviation (MAD)68.5
Skewness0
Sum37675
Variance6279.1667
MonotonicityStrictly increasing
2024-03-15T08:46:29.452135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
182 1
 
0.4%
188 1
 
0.4%
187 1
 
0.4%
186 1
 
0.4%
185 1
 
0.4%
184 1
 
0.4%
183 1
 
0.4%
181 1
 
0.4%
207 1
 
0.4%
Other values (264) 264
96.4%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
274 1
0.4%
273 1
0.4%
272 1
0.4%
271 1
0.4%
270 1
0.4%
269 1
0.4%
268 1
0.4%
267 1
0.4%
266 1
0.4%
265 1
0.4%

노선명
Text

Distinct272
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-03-15T08:46:30.415282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.5583942
Min length4

Characters and Unicode

Total characters1523
Distinct characters152
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique270 ?
Unique (%)98.5%

Sample

1st row가련산로L
2nd row가련산로R
3rd row가리내로L
4th row가리내로R
5th row거마평로L
ValueCountFrequency (%)
에코시티-1r 2
 
0.7%
에코시티-1l 2
 
0.7%
팔과정로r 1
 
0.4%
태진로r 1
 
0.4%
틀못2길l 1
 
0.4%
틀못2길r 1
 
0.4%
평화로r 1
 
0.4%
틀못4길l 1
 
0.4%
팔과정로l 1
 
0.4%
팔달로l 1
 
0.4%
Other values (262) 262
95.6%
2024-03-15T08:46:31.889295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 199
 
13.1%
R 139
 
9.1%
L 134
 
8.8%
1 63
 
4.1%
- 58
 
3.8%
시 48
 
3.2%
에 46
 
3.0%
코 46
 
3.0%
티 46
 
3.0%
2 43
 
2.8%
Other values (142) 701
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 981
64.4%
Uppercase Letter 287
 
18.8%
Decimal Number 146
 
9.6%
Dash Punctuation 58
 
3.8%
Letter Number 50
 
3.3%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 199
 
20.3%
시 48
 
4.9%
에 46
 
4.7%
코 46
 
4.7%
티 46
 
4.7%
천 25
 
2.5%
산 18
 
1.8%
기 17
 
1.7%
성 16
 
1.6%
대 16
 
1.6%
Other values (116) 504
51.4%
Letter Number
ValueCountFrequency (%)
Ⅱ 28
56.0%
Ⅰ 4
 
8.0%
Ⅶ 4
 
8.0%
Ⅸ 2
 
4.0%
Ⅵ 2
 
4.0%
Ⅲ 2
 
4.0%
Ⅷ 2
 
4.0%
Ⅴ 2
 
4.0%
Ⅳ 2
 
4.0%
Ⅹ 2
 
4.0%
Decimal Number
ValueCountFrequency (%)
1 63
43.2%
2 43
29.5%
3 16
 
11.0%
4 8
 
5.5%
5 6
 
4.1%
6 4
 
2.7%
9 2
 
1.4%
8 2
 
1.4%
7 2
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
R 139
48.4%
L 134
46.7%
I 8
 
2.8%
V 4
 
1.4%
X 2
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%
Lowercase Letter
ValueCountFrequency (%)
l 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 981
64.4%
Latin 338
 
22.2%
Common 204
 
13.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 199
 
20.3%
시 48
 
4.9%
에 46
 
4.7%
코 46
 
4.7%
티 46
 
4.7%
천 25
 
2.5%
산 18
 
1.8%
기 17
 
1.7%
성 16
 
1.6%
대 16
 
1.6%
Other values (116) 504
51.4%
Latin
ValueCountFrequency (%)
R 139
41.1%
L 134
39.6%
Ⅱ 28
 
8.3%
I 8
 
2.4%
Ⅰ 4
 
1.2%
Ⅶ 4
 
1.2%
V 4
 
1.2%
Ⅸ 2
 
0.6%
Ⅵ 2
 
0.6%
Ⅲ 2
 
0.6%
Other values (6) 11
 
3.3%
Common
ValueCountFrequency (%)
1 63
30.9%
- 58
28.4%
2 43
21.1%
3 16
 
7.8%
4 8
 
3.9%
5 6
 
2.9%
6 4
 
2.0%
9 2
 
1.0%
8 2
 
1.0%
7 2
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 981
64.4%
ASCII 492
32.3%
Number Forms 50
 
3.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 199
 
20.3%
시 48
 
4.9%
에 46
 
4.7%
코 46
 
4.7%
티 46
 
4.7%
천 25
 
2.5%
산 18
 
1.8%
기 17
 
1.7%
성 16
 
1.6%
대 16
 
1.6%
Other values (116) 504
51.4%
ASCII
ValueCountFrequency (%)
R 139
28.3%
L 134
27.2%
1 63
12.8%
- 58
11.8%
2 43
 
8.7%
3 16
 
3.3%
I 8
 
1.6%
4 8
 
1.6%
5 6
 
1.2%
6 4
 
0.8%
Other values (6) 13
 
2.6%
Number Forms
ValueCountFrequency (%)
Ⅱ 28
56.0%
Ⅰ 4
 
8.0%
Ⅶ 4
 
8.0%
Ⅸ 2
 
4.0%
Ⅵ 2
 
4.0%
Ⅲ 2
 
4.0%
Ⅷ 2
 
4.0%
Ⅴ 2
 
4.0%
Ⅳ 2
 
4.0%
Ⅹ 2
 
4.0%

기점
Text

MISSING 

Distinct122
Distinct (%)53.3%
Missing45
Missing (%)16.4%
Memory size2.3 KiB
2024-03-15T08:46:32.686823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length22
Mean length12.860262
Min length3

Characters and Unicode

Total characters2945
Distinct characters175
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)8.7%

Sample

1st row덕진동695-6(가련교)
2nd row덕진동695-6(가련교)
3rd row덕진동2가693-5(가련교)
4th row덕진동2가693-5(가련교)
5th row삼천동1가767-1
ValueCountFrequency (%)
앞 20
 
5.8%
송천동2가 10
 
2.9%
장동 8
 
2.3%
만성동 7
 
2.0%
사거리 6
 
1.7%
중동 5
 
1.4%
117-9 4
 
1.2%
771 4
 
1.2%
삼거리 4
 
1.2%
옆 4
 
1.2%
Other values (148) 275
79.3%
2024-03-15T08:46:33.664930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 242
 
8.2%
동 216
 
7.3%
- 167
 
5.7%
가 140
 
4.8%
2 138
 
4.7%
120
 
4.1%
3 101
 
3.4%
) 92
 
3.1%
( 92
 
3.1%
4 82
 
2.8%
Other values (165) 1555
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1472
50.0%
Decimal Number 990
33.6%
Dash Punctuation 167
 
5.7%
Space Separator 120
 
4.1%
Close Punctuation 92
 
3.1%
Open Punctuation 92
 
3.1%
Uppercase Letter 10
 
0.3%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 216
 
14.7%
가 140
 
9.5%
천 44
 
3.0%
교 41
 
2.8%
송 38
 
2.6%
자 36
 
2.4%
효 32
 
2.2%
리 32
 
2.2%
진 28
 
1.9%
거 27
 
1.8%
Other values (145) 838
56.9%
Decimal Number
ValueCountFrequency (%)
1 242
24.4%
2 138
13.9%
3 101
10.2%
4 82
 
8.3%
7 80
 
8.1%
6 77
 
7.8%
5 75
 
7.6%
0 70
 
7.1%
8 68
 
6.9%
9 57
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
H 2
20.0%
L 2
20.0%
G 2
20.0%
N 2
20.0%
E 2
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 167
100.0%
Space Separator
ValueCountFrequency (%)
120
100.0%
Close Punctuation
ValueCountFrequency (%)
) 92
100.0%
Open Punctuation
ValueCountFrequency (%)
( 92
100.0%
Other Punctuation
ValueCountFrequency (%)
@ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1472
50.0%
Common 1463
49.7%
Latin 10
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 216
 
14.7%
가 140
 
9.5%
천 44
 
3.0%
교 41
 
2.8%
송 38
 
2.6%
자 36
 
2.4%
효 32
 
2.2%
리 32
 
2.2%
진 28
 
1.9%
거 27
 
1.8%
Other values (145) 838
56.9%
Common
ValueCountFrequency (%)
1 242
16.5%
- 167
11.4%
2 138
9.4%
120
8.2%
3 101
 
6.9%
) 92
 
6.3%
( 92
 
6.3%
4 82
 
5.6%
7 80
 
5.5%
6 77
 
5.3%
Other values (5) 272
18.6%
Latin
ValueCountFrequency (%)
H 2
20.0%
L 2
20.0%
G 2
20.0%
N 2
20.0%
E 2
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1473
50.0%
Hangul 1472
50.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 242
16.4%
- 167
11.3%
2 138
9.4%
120
8.1%
3 101
 
6.9%
) 92
 
6.2%
( 92
 
6.2%
4 82
 
5.6%
7 80
 
5.4%
6 77
 
5.2%
Other values (10) 282
19.1%
Hangul
ValueCountFrequency (%)
동 216
 
14.7%
가 140
 
9.5%
천 44
 
3.0%
교 41
 
2.8%
송 38
 
2.6%
자 36
 
2.4%
효 32
 
2.2%
리 32
 
2.2%
진 28
 
1.9%
거 27
 
1.8%
Other values (145) 838
56.9%

기점 경도
Real number (ℝ)

MISSING 

Distinct98
Distinct (%)53.6%
Missing91
Missing (%)33.2%
Infinite0
Infinite (%)0.0%
Mean127.11821
Minimum127.00762
Maximum127.19859
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-15T08:46:34.090925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.00762
5-th percentile127.06686
Q1127.09811
median127.11764
Q3127.13617
95-th percentile127.1643
Maximum127.19859
Range0.1909725
Interquartile range (IQR)0.0380606

Descriptive statistics

Standard deviation0.02924235
Coefficient of variation (CV)0.0002300406
Kurtosis0.47155606
Mean127.11821
Median Absolute Deviation (MAD)0.0187631
Skewness-0.24141268
Sum23262.633
Variance0.00085511505
MonotonicityNot monotonic
2024-03-15T08:46:34.449759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0668594 3
 
1.1%
127.110316 2
 
0.7%
127.1134682 2
 
0.7%
127.1135762 2
 
0.7%
127.1227375 2
 
0.7%
127.0981053 2
 
0.7%
127.0864599 2
 
0.7%
127.1015392 2
 
0.7%
127.1076426 2
 
0.7%
127.1232625 2
 
0.7%
Other values (88) 162
59.1%
(Missing) 91
33.2%
ValueCountFrequency (%)
127.007622 1
 
0.4%
127.0581333 2
0.7%
127.058602 1
 
0.4%
127.058631 2
0.7%
127.0653102 2
0.7%
127.0668594 3
1.1%
127.0706028 2
0.7%
127.07321 2
0.7%
127.0800136 2
0.7%
127.0816414 2
0.7%
ValueCountFrequency (%)
127.1985945 1
0.4%
127.1763285 2
0.7%
127.1699265 2
0.7%
127.1661228 2
0.7%
127.1658603 2
0.7%
127.1643014 2
0.7%
127.1638854 1
0.4%
127.1614462 2
0.7%
127.1614188 2
0.7%
127.1607394 2
0.7%

기점 위도
Real number (ℝ)

MISSING 

Distinct98
Distinct (%)53.6%
Missing91
Missing (%)33.2%
Infinite0
Infinite (%)0.0%
Mean35.827527
Minimum35.753022
Maximum35.875284
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-15T08:46:34.725090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.753022
5-th percentile35.792382
Q135.811557
median35.825787
Q335.847925
95-th percentile35.865114
Maximum35.875284
Range0.1222618
Interquartile range (IQR)0.0363679

Descriptive statistics

Standard deviation0.023939428
Coefficient of variation (CV)0.00066818533
Kurtosis-0.2113639
Mean35.827527
Median Absolute Deviation (MAD)0.0187609
Skewness-0.26241885
Sum6556.4374
Variance0.0005730962
MonotonicityNot monotonic
2024-03-15T08:46:35.109953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.8566441 3
 
1.1%
35.7985498 2
 
0.7%
35.8256621 2
 
0.7%
35.7931672 2
 
0.7%
35.825275 2
 
0.7%
35.8248357 2
 
0.7%
35.8217068 2
 
0.7%
35.8026496 2
 
0.7%
35.8142012 2
 
0.7%
35.8059 2
 
0.7%
Other values (88) 162
59.1%
(Missing) 91
33.2%
ValueCountFrequency (%)
35.7530224 1
0.4%
35.7536364 1
0.4%
35.7790361 1
0.4%
35.7825186 2
0.7%
35.7852016 2
0.7%
35.7853908 2
0.7%
35.7923816 2
0.7%
35.7931672 2
0.7%
35.7931821 2
0.7%
35.7959244 2
0.7%
ValueCountFrequency (%)
35.8752842 1
0.4%
35.8701332 1
0.4%
35.8696198 2
0.7%
35.8687758 2
0.7%
35.8659353 2
0.7%
35.865245 2
0.7%
35.8639353 2
0.7%
35.8599388 2
0.7%
35.8596312 2
0.7%
35.8595322 2
0.7%

중기점
Text

MISSING 

Distinct124
Distinct (%)54.1%
Missing45
Missing (%)16.4%
Memory size2.3 KiB
2024-03-15T08:46:36.426826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length10.384279
Min length5

Characters and Unicode

Total characters2378
Distinct characters91
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)12.2%

Sample

1st row덕진동2가 245-34
2nd row덕진동2가 245-8
3rd row덕진동2가 646-34
4th row덕진동2가 646-34
5th row삼천2동 592
ValueCountFrequency (%)
송천동2가 17
 
3.6%
효자동3가 16
 
3.4%
효자동2가 14
 
3.0%
덕진동1가 13
 
2.7%
장동 11
 
2.3%
만성동 10
 
2.1%
중동 9
 
1.9%
송천동1가 8
 
1.7%
서신동 8
 
1.7%
덕진동2가 8
 
1.7%
Other values (182) 360
75.9%
2024-03-15T08:46:37.993950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
245
 
10.3%
동 220
 
9.3%
1 220
 
9.3%
2 207
 
8.7%
- 176
 
7.4%
3 129
 
5.4%
가 116
 
4.9%
4 82
 
3.4%
6 81
 
3.4%
5 80
 
3.4%
Other values (81) 822
34.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1047
44.0%
Other Letter 906
38.1%
Space Separator 245
 
10.3%
Dash Punctuation 176
 
7.4%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 220
24.3%
가 116
 
12.8%
천 39
 
4.3%
송 37
 
4.1%
자 36
 
4.0%
효 34
 
3.8%
산 33
 
3.6%
서 27
 
3.0%
진 23
 
2.5%
덕 22
 
2.4%
Other values (67) 319
35.2%
Decimal Number
ValueCountFrequency (%)
1 220
21.0%
2 207
19.8%
3 129
12.3%
4 82
 
7.8%
6 81
 
7.7%
5 80
 
7.6%
9 69
 
6.6%
7 64
 
6.1%
8 59
 
5.6%
0 56
 
5.3%
Space Separator
ValueCountFrequency (%)
245
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 176
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1472
61.9%
Hangul 906
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 220
24.3%
가 116
 
12.8%
천 39
 
4.3%
송 37
 
4.1%
자 36
 
4.0%
효 34
 
3.8%
산 33
 
3.6%
서 27
 
3.0%
진 23
 
2.5%
덕 22
 
2.4%
Other values (67) 319
35.2%
Common
ValueCountFrequency (%)
245
16.6%
1 220
14.9%
2 207
14.1%
- 176
12.0%
3 129
8.8%
4 82
 
5.6%
6 81
 
5.5%
5 80
 
5.4%
9 69
 
4.7%
7 64
 
4.3%
Other values (4) 119
8.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1472
61.9%
Hangul 906
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
245
16.6%
1 220
14.9%
2 207
14.1%
- 176
12.0%
3 129
8.8%
4 82
 
5.6%
6 81
 
5.5%
5 80
 
5.4%
9 69
 
4.7%
7 64
 
4.3%
Other values (4) 119
8.1%
Hangul
ValueCountFrequency (%)
동 220
24.3%
가 116
 
12.8%
천 39
 
4.3%
송 37
 
4.1%
자 36
 
4.0%
효 34
 
3.8%
산 33
 
3.6%
서 27
 
3.0%
진 23
 
2.5%
덕 22
 
2.4%
Other values (67) 319
35.2%

중기점 경도
Real number (ℝ)

MISSING 

Distinct99
Distinct (%)54.1%
Missing91
Missing (%)33.2%
Infinite0
Infinite (%)0.0%
Mean127.11968
Minimum127.03866
Maximum127.18917
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-15T08:46:38.476177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.03866
5-th percentile127.07139
Q1127.09999
median127.12036
Q3127.13754
95-th percentile127.16365
Maximum127.18917
Range0.150509
Interquartile range (IQR)0.0375492

Descriptive statistics

Standard deviation0.027933491
Coefficient of variation (CV)0.00021974168
Kurtosis-0.29610777
Mean127.11968
Median Absolute Deviation (MAD)0.019664
Skewness-0.12363884
Sum23262.901
Variance0.00078027993
MonotonicityNot monotonic
2024-03-15T08:46:38.745922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1169403 4
 
1.5%
127.092215 4
 
1.5%
127.1474145 4
 
1.5%
127.1220688 2
 
0.7%
127.1260539 2
 
0.7%
127.1123716 2
 
0.7%
127.0984783 2
 
0.7%
127.1018092 2
 
0.7%
127.096924 2
 
0.7%
127.1327908 2
 
0.7%
Other values (89) 157
57.3%
(Missing) 91
33.2%
ValueCountFrequency (%)
127.0386624 1
0.4%
127.0619317 1
0.4%
127.064464 1
0.4%
127.0664996 2
0.7%
127.0671351 2
0.7%
127.068395 2
0.7%
127.071391 2
0.7%
127.0715102 2
0.7%
127.074171 2
0.7%
127.0743319 2
0.7%
ValueCountFrequency (%)
127.1891714 1
0.4%
127.1784548 1
0.4%
127.1703623 1
0.4%
127.1697992 2
0.7%
127.1690913 2
0.7%
127.1636837 1
0.4%
127.1636641 2
0.7%
127.1634948 2
0.7%
127.163444 2
0.7%
127.162275 1
0.4%

중기점 위도
Real number (ℝ)

MISSING 

Distinct99
Distinct (%)54.1%
Missing91
Missing (%)33.2%
Infinite0
Infinite (%)0.0%
Mean35.83266
Minimum35.767757
Maximum35.888166
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-15T08:46:39.208484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.767757
5-th percentile35.798365
Q135.818211
median35.8313
Q335.851862
95-th percentile35.867924
Maximum35.888166
Range0.1204088
Interquartile range (IQR)0.03365085

Descriptive statistics

Standard deviation0.022827275
Coefficient of variation (CV)0.00063705221
Kurtosis-0.50741931
Mean35.83266
Median Absolute Deviation (MAD)0.0177793
Skewness-0.09087794
Sum6557.3767
Variance0.00052108449
MonotonicityNot monotonic
2024-03-15T08:46:39.662309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.8318558 4
 
1.5%
35.8492185 4
 
1.5%
35.8185808 4
 
1.5%
35.798365 2
 
0.7%
35.8253486 2
 
0.7%
35.8254224 2
 
0.7%
35.8259523 2
 
0.7%
35.8117277 2
 
0.7%
35.816327 2
 
0.7%
35.8079332 2
 
0.7%
Other values (89) 157
57.3%
(Missing) 91
33.2%
ValueCountFrequency (%)
35.7677572 1
0.4%
35.774965 1
0.4%
35.7894061 2
0.7%
35.7902668 2
0.7%
35.7923873 2
0.7%
35.7981417 1
0.4%
35.798365 2
0.7%
35.798427 2
0.7%
35.8001722 2
0.7%
35.8011912 2
0.7%
ValueCountFrequency (%)
35.888166 1
0.4%
35.8771726 1
0.4%
35.8735038 2
0.7%
35.8713647 2
0.7%
35.8699216 2
0.7%
35.8682145 2
0.7%
35.8653105 2
0.7%
35.8649595 2
0.7%
35.8646941 2
0.7%
35.864613 2
0.7%

종점
Text

MISSING 

Distinct133
Distinct (%)58.1%
Missing45
Missing (%)16.4%
Memory size2.3 KiB
2024-03-15T08:46:40.504640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length21
Mean length13.131004
Min length3

Characters and Unicode

Total characters3007
Distinct characters179
Distinct categories8 ?
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 (%)16.6%

Sample

1st row덕진동2가142-28(가련광장)
2nd row덕진동2가142-27(가련광장)
3rd row덕진동2가683(하가더루벤스아파트)
4th row덕진동2가683(하가더루벤스아파트)
5th row효자동3가 37-47
ValueCountFrequency (%)
앞 15
 
4.4%
송천동2가 10
 
2.9%
만성동 9
 
2.6%
장동 6
 
1.7%
사거리 5
 
1.5%
효자동3가 4
 
1.2%
중동 4
 
1.2%
삼거리 4
 
1.2%
화개네거리 3
 
0.9%
호성동2가 3
 
0.9%
Other values (163) 280
81.6%
2024-03-15T08:46:41.693329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 235
 
7.8%
동 220
 
7.3%
- 160
 
5.3%
2 145
 
4.8%
가 141
 
4.7%
116
 
3.9%
3 109
 
3.6%
) 98
 
3.3%
( 98
 
3.3%
6 95
 
3.2%
Other values (169) 1590
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1522
50.6%
Decimal Number 1001
33.3%
Dash Punctuation 160
 
5.3%
Space Separator 116
 
3.9%
Close Punctuation 98
 
3.3%
Open Punctuation 98
 
3.3%
Uppercase Letter 8
 
0.3%
Other Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 220
 
14.5%
가 141
 
9.3%
천 39
 
2.6%
송 38
 
2.5%
아 35
 
2.3%
서 34
 
2.2%
효 32
 
2.1%
진 32
 
2.1%
자 31
 
2.0%
장 29
 
1.9%
Other values (150) 891
58.5%
Decimal Number
ValueCountFrequency (%)
1 235
23.5%
2 145
14.5%
3 109
10.9%
6 95
9.5%
7 82
 
8.2%
5 76
 
7.6%
8 71
 
7.1%
0 69
 
6.9%
4 69
 
6.9%
9 50
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
S 2
25.0%
K 2
25.0%
L 2
25.0%
G 2
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 160
100.0%
Space Separator
ValueCountFrequency (%)
116
100.0%
Close Punctuation
ValueCountFrequency (%)
) 98
100.0%
Open Punctuation
ValueCountFrequency (%)
( 98
100.0%
Other Punctuation
ValueCountFrequency (%)
@ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1522
50.6%
Common 1477
49.1%
Latin 8
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 220
 
14.5%
가 141
 
9.3%
천 39
 
2.6%
송 38
 
2.5%
아 35
 
2.3%
서 34
 
2.2%
효 32
 
2.1%
진 32
 
2.1%
자 31
 
2.0%
장 29
 
1.9%
Other values (150) 891
58.5%
Common
ValueCountFrequency (%)
1 235
15.9%
- 160
10.8%
2 145
9.8%
116
7.9%
3 109
7.4%
) 98
 
6.6%
( 98
 
6.6%
6 95
 
6.4%
7 82
 
5.6%
5 76
 
5.1%
Other values (5) 263
17.8%
Latin
ValueCountFrequency (%)
S 2
25.0%
K 2
25.0%
L 2
25.0%
G 2
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1522
50.6%
ASCII 1485
49.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 235
15.8%
- 160
10.8%
2 145
9.8%
116
7.8%
3 109
7.3%
) 98
 
6.6%
( 98
 
6.6%
6 95
 
6.4%
7 82
 
5.5%
5 76
 
5.1%
Other values (9) 271
18.2%
Hangul
ValueCountFrequency (%)
동 220
 
14.5%
가 141
 
9.3%
천 39
 
2.6%
송 38
 
2.5%
아 35
 
2.3%
서 34
 
2.2%
효 32
 
2.1%
진 32
 
2.1%
자 31
 
2.0%
장 29
 
1.9%
Other values (150) 891
58.5%

종점 경도
Real number (ℝ)

MISSING 

Distinct101
Distinct (%)55.2%
Missing91
Missing (%)33.2%
Infinite0
Infinite (%)0.0%
Mean127.12069
Minimum127.06108
Maximum127.19024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-15T08:46:42.152806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.06108
5-th percentile127.06719
Q1127.10161
median127.12163
Q3127.13985
95-th percentile127.16817
Maximum127.19024
Range0.1291627
Interquartile range (IQR)0.0382399

Descriptive statistics

Standard deviation0.029629726
Coefficient of variation (CV)0.00023308343
Kurtosis-0.59561845
Mean127.12069
Median Absolute Deviation (MAD)0.0193823
Skewness-0.11359615
Sum23263.086
Variance0.00087792063
MonotonicityNot monotonic
2024-03-15T08:46:42.796892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0668594 3
 
1.1%
127.1476941 3
 
1.1%
127.1216282 2
 
0.7%
127.12139 2
 
0.7%
127.1619058 2
 
0.7%
127.1292461 2
 
0.7%
127.1227375 2
 
0.7%
127.0981053 2
 
0.7%
127.1022459 2
 
0.7%
127.096815 2
 
0.7%
Other values (91) 161
58.8%
(Missing) 91
33.2%
ValueCountFrequency (%)
127.0610775 1
 
0.4%
127.0613063 2
0.7%
127.0628579 1
 
0.4%
127.0628965 1
 
0.4%
127.0640474 2
0.7%
127.0668594 3
1.1%
127.070193 2
0.7%
127.0706028 2
0.7%
127.0712686 1
 
0.4%
127.071936 1
 
0.4%
ValueCountFrequency (%)
127.1902402 1
0.4%
127.1751692 2
0.7%
127.17407 2
0.7%
127.1711982 2
0.7%
127.1706114 2
0.7%
127.1681715 2
0.7%
127.1673537 2
0.7%
127.16475 1
0.4%
127.1638854 1
0.4%
127.1627394 2
0.7%

종점 위도
Real number (ℝ)

MISSING 

Distinct101
Distinct (%)55.2%
Missing91
Missing (%)33.2%
Infinite0
Infinite (%)0.0%
Mean35.837176
Minimum35.775631
Maximum35.899699
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-15T08:46:43.374795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.775631
5-th percentile35.798168
Q135.820616
median35.836072
Q335.856009
95-th percentile35.873812
Maximum35.899699
Range0.1240675
Interquartile range (IQR)0.03539275

Descriptive statistics

Standard deviation0.024021382
Coefficient of variation (CV)0.00067029228
Kurtosis-0.60637273
Mean35.837176
Median Absolute Deviation (MAD)0.0172181
Skewness0.021470982
Sum6558.2031
Variance0.0005770268
MonotonicityNot monotonic
2024-03-15T08:46:44.158005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.8566441 3
 
1.1%
35.8673908 3
 
1.1%
35.8695783 2
 
0.7%
35.869711 2
 
0.7%
35.8088114 2
 
0.7%
35.8265803 2
 
0.7%
35.825275 2
 
0.7%
35.8248357 2
 
0.7%
35.8248824 2
 
0.7%
35.8208504 2
 
0.7%
Other values (91) 161
58.8%
(Missing) 91
33.2%
ValueCountFrequency (%)
35.7756314 1
0.4%
35.7853908 1
0.4%
35.7937691 2
0.7%
35.7950002 2
0.7%
35.7966716 2
0.7%
35.798042 1
0.4%
35.7981682 2
0.7%
35.8026955 2
0.7%
35.8037828 2
0.7%
35.8043789 2
0.7%
ValueCountFrequency (%)
35.8996989 1
0.4%
35.8914459 1
0.4%
35.8911308 1
0.4%
35.8773261 2
0.7%
35.8746711 2
0.7%
35.8739539 2
0.7%
35.8738246 1
0.4%
35.8737012 1
0.4%
35.8735589 1
0.4%
35.869711 2
0.7%

도로연계성
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing86
Missing (%)31.4%
Memory size676.0 B
True
188 
(Missing)
86 
ValueCountFrequency (%)
True 188
68.6%
(Missing) 86
31.4%
2024-03-15T08:46:44.699847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

자전거도로 종류
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
겸용도로
254 
겸용도로(하천산책로)
 
11
전용도로
 
8
우선도로
 
1

Length

Max length11
Median length4
Mean length4.2810219
Min length4

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
겸용도로 254
92.7%
겸용도로(하천산책로) 11
 
4.0%
전용도로 8
 
2.9%
우선도로 1
 
0.4%

Length

2024-03-15T08:46:45.074151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T08:46:45.438088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
겸용도로 254
92.7%
겸용도로(하천산책로 11
 
4.0%
전용도로 8
 
2.9%
우선도로 1
 
0.4%

연장 (km)
Real number (ℝ)

Distinct88
Distinct (%)32.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6423723
Minimum0
Maximum14.1
Zeros2
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-15T08:46:45.830944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.2165
Q10.5
median1.16
Q32
95-th percentile4.2925
Maximum14.1
Range14.1
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation1.837824
Coefficient of variation (CV)1.1190057
Kurtosis16.348841
Mean1.6423723
Median Absolute Deviation (MAD)0.715
Skewness3.4116778
Sum450.01
Variance3.3775969
MonotonicityNot monotonic
2024-03-15T08:46:46.420470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.35 16
 
5.8%
1.4 10
 
3.6%
0.7 10
 
3.6%
1.5 9
 
3.3%
0.4 9
 
3.3%
0.25 8
 
2.9%
0.3 8
 
2.9%
2.1 8
 
2.9%
1.15 6
 
2.2%
0.5 6
 
2.2%
Other values (78) 184
67.2%
ValueCountFrequency (%)
0.0 2
 
0.7%
0.1 6
2.2%
0.15 2
 
0.7%
0.2 2
 
0.7%
0.21 2
 
0.7%
0.22 2
 
0.7%
0.23 2
 
0.7%
0.25 8
2.9%
0.3 8
2.9%
0.34 1
 
0.4%
ValueCountFrequency (%)
14.1 1
0.4%
13.81 1
0.4%
8.4 2
0.7%
8.25 2
0.7%
7.85 1
0.4%
7.7 1
0.4%
7.0 1
0.4%
5.75 1
0.4%
5.2 1
0.4%
4.89 1
0.4%

전용도로 폭원
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.061313869
Minimum0
Maximum3.2
Zeros268
Zeros (%)97.8%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-15T08:46:46.649320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum3.2
Range3.2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4166407
Coefficient of variation (CV)6.7952115
Kurtosis45.581638
Mean0.061313869
Median Absolute Deviation (MAD)0
Skewness6.8192236
Sum16.8
Variance0.17358948
MonotonicityNot monotonic
2024-03-15T08:46:46.833841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0.0 268
97.8%
3.2 2
 
0.7%
2.7 1
 
0.4%
3.0 1
 
0.4%
1.8 1
 
0.4%
2.9 1
 
0.4%
ValueCountFrequency (%)
0.0 268
97.8%
1.8 1
 
0.4%
2.7 1
 
0.4%
2.9 1
 
0.4%
3.0 1
 
0.4%
3.2 2
 
0.7%
ValueCountFrequency (%)
3.2 2
 
0.7%
3.0 1
 
0.4%
2.9 1
 
0.4%
2.7 1
 
0.4%
1.8 1
 
0.4%
0.0 268
97.8%

자전거도로 폭원(분리형)
Real number (ℝ)

ZEROS 

Distinct18
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.68467153
Minimum0
Maximum4.8
Zeros173
Zeros (%)63.1%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-15T08:46:47.042628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31.5
95-th percentile2.5
Maximum4.8
Range4.8
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation0.95494783
Coefficient of variation (CV)1.3947532
Kurtosis0.1019826
Mean0.68467153
Median Absolute Deviation (MAD)0
Skewness1.0146481
Sum187.6
Variance0.91192535
MonotonicityNot monotonic
2024-03-15T08:46:47.425902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.0 173
63.1%
1.5 32
 
11.7%
2.0 30
 
10.9%
2.5 8
 
2.9%
1.2 5
 
1.8%
1.3 4
 
1.5%
1.4 4
 
1.5%
3.0 4
 
1.5%
1.6 2
 
0.7%
2.6 2
 
0.7%
Other values (8) 10
 
3.6%
ValueCountFrequency (%)
0.0 173
63.1%
1.0 1
 
0.4%
1.2 5
 
1.8%
1.3 4
 
1.5%
1.4 4
 
1.5%
1.5 32
 
11.7%
1.6 2
 
0.7%
1.7 1
 
0.4%
1.8 1
 
0.4%
1.9 1
 
0.4%
ValueCountFrequency (%)
4.8 1
 
0.4%
3.0 4
 
1.5%
2.6 2
 
0.7%
2.5 8
 
2.9%
2.4 2
 
0.7%
2.2 1
 
0.4%
2.1 2
 
0.7%
2.0 30
10.9%
1.9 1
 
0.4%
1.8 1
 
0.4%

보도 폭원(분리형)
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.93069343
Minimum0
Maximum13.5
Zeros173
Zeros (%)63.1%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-15T08:46:47.811298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile2.5
Maximum13.5
Range13.5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.686388
Coefficient of variation (CV)1.8119694
Kurtosis23.710765
Mean0.93069343
Median Absolute Deviation (MAD)0
Skewness3.9374787
Sum255.01
Variance2.8439046
MonotonicityNot monotonic
2024-03-15T08:46:48.258210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0.0 173
63.1%
2.0 33
 
12.0%
2.5 24
 
8.8%
1.5 7
 
2.6%
1.0 4
 
1.5%
1.8 4
 
1.5%
2.1 3
 
1.1%
2.2 3
 
1.1%
5.0 2
 
0.7%
1.6 2
 
0.7%
Other values (14) 19
 
6.9%
ValueCountFrequency (%)
0.0 173
63.1%
1.0 4
 
1.5%
1.3 2
 
0.7%
1.4 1
 
0.4%
1.5 7
 
2.6%
1.6 2
 
0.7%
1.7 2
 
0.7%
1.8 4
 
1.5%
1.9 1
 
0.4%
2.0 33
 
12.0%
ValueCountFrequency (%)
13.5 2
 
0.7%
8.5 2
 
0.7%
5.0 2
 
0.7%
4.5 1
 
0.4%
4.2 1
 
0.4%
3.8 1
 
0.4%
3.0 1
 
0.4%
2.7 2
 
0.7%
2.6 1
 
0.4%
2.5 24
8.8%

유효폭원측정1(비분리형)
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.615365
Minimum0
Maximum15
Zeros173
Zeros (%)63.1%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-15T08:46:48.594466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33.5
95-th percentile4.805
Maximum15
Range15
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation2.4435948
Coefficient of variation (CV)1.5127199
Kurtosis5.9884668
Mean1.615365
Median Absolute Deviation (MAD)0
Skewness1.9355163
Sum442.61
Variance5.9711554
MonotonicityNot monotonic
2024-03-15T08:46:48.840404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0.0 173
63.1%
4.5 18
 
6.6%
3.5 18
 
6.6%
4.0 16
 
5.8%
3.0 10
 
3.6%
5.0 4
 
1.5%
2.8 4
 
1.5%
4.7 4
 
1.5%
3.3 3
 
1.1%
4.6 3
 
1.1%
Other values (14) 21
 
7.7%
ValueCountFrequency (%)
0.0 173
63.1%
2.5 1
 
0.4%
2.8 4
 
1.5%
2.9 2
 
0.7%
3.0 10
 
3.6%
3.2 2
 
0.7%
3.3 3
 
1.1%
3.5 18
 
6.6%
3.6 1
 
0.4%
3.9 1
 
0.4%
ValueCountFrequency (%)
15.0 2
0.7%
10.0 2
0.7%
9.0 1
 
0.4%
8.0 2
0.7%
6.5 1
 
0.4%
5.5 1
 
0.4%
5.11 1
 
0.4%
5.0 4
1.5%
4.7 4
1.5%
4.6 3
1.1%

도로폭원(비분리형)
Real number (ℝ)

ZEROS 

Distinct33
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5167883
Minimum0
Maximum5
Zeros104
Zeros (%)38.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-15T08:46:49.082846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.8
Q32.775
95-th percentile3.3
Maximum5
Range5
Interquartile range (IQR)2.775

Descriptive statistics

Standard deviation1.322831
Coefficient of variation (CV)0.87212633
Kurtosis-1.2748091
Mean1.5167883
Median Absolute Deviation (MAD)1.2
Skewness0.096304154
Sum415.6
Variance1.749882
MonotonicityNot monotonic
2024-03-15T08:46:49.535390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0.0 104
38.0%
2.0 36
 
13.1%
3.0 34
 
12.4%
1.8 10
 
3.6%
2.2 9
 
3.3%
3.2 7
 
2.6%
2.8 7
 
2.6%
1.5 6
 
2.2%
2.1 5
 
1.8%
2.4 5
 
1.8%
Other values (23) 51
18.6%
ValueCountFrequency (%)
0.0 104
38.0%
0.7 1
 
0.4%
1.0 1
 
0.4%
1.1 1
 
0.4%
1.2 4
 
1.5%
1.3 2
 
0.7%
1.4 2
 
0.7%
1.5 6
 
2.2%
1.6 4
 
1.5%
1.7 3
 
1.1%
ValueCountFrequency (%)
5.0 2
 
0.7%
4.0 3
1.1%
3.8 1
 
0.4%
3.7 2
 
0.7%
3.6 2
 
0.7%
3.5 3
1.1%
3.3 2
 
0.7%
3.25 2
 
0.7%
3.2 7
2.6%
3.1 3
1.1%

유효폭원측정2(비분리형)
Real number (ℝ)

ZEROS 

Distinct33
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5167883
Minimum0
Maximum5
Zeros104
Zeros (%)38.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-15T08:46:49.928406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.8
Q32.775
95-th percentile3.3
Maximum5
Range5
Interquartile range (IQR)2.775

Descriptive statistics

Standard deviation1.322831
Coefficient of variation (CV)0.87212633
Kurtosis-1.2748091
Mean1.5167883
Median Absolute Deviation (MAD)1.2
Skewness0.096304154
Sum415.6
Variance1.749882
MonotonicityNot monotonic
2024-03-15T08:46:50.349920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0.0 104
38.0%
2.0 36
 
13.1%
3.0 34
 
12.4%
1.8 10
 
3.6%
2.2 9
 
3.3%
3.2 7
 
2.6%
2.8 7
 
2.6%
1.5 6
 
2.2%
2.1 5
 
1.8%
2.4 5
 
1.8%
Other values (23) 51
18.6%
ValueCountFrequency (%)
0.0 104
38.0%
0.7 1
 
0.4%
1.0 1
 
0.4%
1.1 1
 
0.4%
1.2 4
 
1.5%
1.3 2
 
0.7%
1.4 2
 
0.7%
1.5 6
 
2.2%
1.6 4
 
1.5%
1.7 3
 
1.1%
ValueCountFrequency (%)
5.0 2
 
0.7%
4.0 3
1.1%
3.8 1
 
0.4%
3.7 2
 
0.7%
3.6 2
 
0.7%
3.5 3
1.1%
3.3 2
 
0.7%
3.25 2
 
0.7%
3.2 7
2.6%
3.1 3
1.1%

보행량 (점)
Categorical

Distinct5
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
3
118 
<NA>
101 
2
26 
4
21 
5
 
8

Length

Max length4
Median length1
Mean length2.1058394
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row2
4th row2
5th row3

Common Values

ValueCountFrequency (%)
3 118
43.1%
<NA> 101
36.9%
2 26
 
9.5%
4 21
 
7.7%
5 8
 
2.9%

Length

2024-03-15T08:46:50.785975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T08:46:51.134631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 118
43.1%
na 101
36.9%
2 26
 
9.5%
4 21
 
7.7%
5 8
 
2.9%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
Minimum2023-11-07 00:00:00
Maximum2023-11-07 00:00:00
2024-03-15T08:46:51.306508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:46:51.463735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Sample

일련번호노선명기점기점 경도기점 위도중기점중기점 경도중기점 위도종점종점 경도종점 위도도로연계성자전거도로 종류연장 (km)전용도로 폭원자전거도로 폭원(분리형)보도 폭원(분리형)유효폭원측정1(비분리형)도로폭원(비분리형)유효폭원측정2(비분리형)보행량 (점)데이터기준일자
01가련산로L덕진동695-6(가련교)127.11011335.840276덕진동2가 245-34127.11404935.844296덕진동2가142-28(가련광장)127.11737735.846888Y겸용도로1.10.01.32.63.90.00.032023-11-07
12가련산로R덕진동695-6(가련교)127.11011335.840276덕진동2가 245-8127.11422135.844397덕진동2가142-27(가련광장)127.11675835.84698Y겸용도로1.10.02.02.04.00.00.032023-11-07
23가리내로L덕진동2가693-5(가련교)127.10943935.840624덕진동2가 646-34127.10630735.843175덕진동2가683(하가더루벤스아파트)127.10816835.845595Y겸용도로1.050.00.00.00.01.31.322023-11-07
34가리내로R덕진동2가693-5(가련교)127.10943935.840624덕진동2가 646-34127.10630735.843175덕진동2가683(하가더루벤스아파트)127.10816835.845595Y겸용도로1.050.00.00.00.01.51.522023-11-07
45거마평로L삼천동1가767-1127.11577735.793182삼천2동 592127.11707535.800172효자동3가 37-47127.11716135.806178Y겸용도로2.30.00.00.00.03.63.632023-11-07
56거마평로R삼천동1가767-1127.11577735.793182삼천2동 592127.11707535.800172효자동3가 37-47127.11716135.806178Y겸용도로2.280.00.00.00.03.33.332023-11-07
67건산로L인후동2가261-8(고려정형외과)127.14518835.832389인후3동 448-42127.15764435.833728산정동875-6127.17119835.837211Y겸용도로2.50.00.00.00.02.02.032023-11-07
78건산로R인후동2가261-8(고려정형외과)127.14518835.832389인후3동 448-42127.15764435.833728산정동875-6127.17119835.837211Y겸용도로2.50.00.00.00.02.12.132023-11-07
89건지산로1L덕진동1가산18-10127.13300635.851476덕진동1가 산31127.13412435.852987덕진동1가 640-7(전주덕진실내배드민턴장)127.13564335.852828Y겸용도로0.350.00.00.00.02.02.032023-11-07
910건지산로1R덕진동1가산18-10127.13300635.851476덕진동1가 산31127.13412435.852987덕진동1가 640-7(전주덕진실내배드민턴장)127.13564335.852828Y겸용도로0.350.00.00.00.02.12.132023-11-07
일련번호노선명기점기점 경도기점 위도중기점중기점 경도중기점 위도종점종점 경도종점 위도도로연계성자전거도로 종류연장 (km)전용도로 폭원자전거도로 폭원(분리형)보도 폭원(분리형)유효폭원측정1(비분리형)도로폭원(비분리형)유효폭원측정2(비분리형)보행량 (점)데이터기준일자
264265에코시티Ⅹ-1L송천동2가 346-8<NA><NA>송천동2가 343<NA><NA>송천동2가 117-7<NA><NA><NA>겸용도로0.470.00.00.00.03.03.0<NA>2023-11-07
265266에코시티Ⅹ-1R<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>겸용도로0.470.00.00.00.03.03.0<NA>2023-11-07
266267에코시티-1L<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>겸용도로0.250.00.00.00.03.03.0<NA>2023-11-07
267268에코시티-1R<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>겸용도로0.250.00.00.00.03.03.0<NA>2023-11-07
268269에코시티-1L<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>겸용도로1.50.02.02.04.00.00.0<NA>2023-11-07
269270에코시티-1R<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>겸용도로1.50.02.02.04.00.00.0<NA>2023-11-07
270271에코시티VIII-1L<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>겸용도로0.250.02.02.04.00.00.0<NA>2023-11-07
271272에코시티VIII-1R<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>겸용도로0.250.02.02.04.00.00.0<NA>2023-11-07
272273에코시티XIV-1L<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>겸용도로0.220.02.02.04.00.00.0<NA>2023-11-07
273274에코시티XIV-1R<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>겸용도로0.220.02.02.04.00.00.0<NA>2023-11-07