Overview

Dataset statistics

Number of variables21
Number of observations10000
Missing cells47785
Missing cells (%)22.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 MiB
Average record size in memory183.0 B

Variable types

Text10
Categorical2
Numeric7
Boolean1
DateTime1

Dataset

Description공공데이터 제공 표준데이터 속성정보(허용값, 표현형식/단위 등)는 [공공데이터 제공 표준] 전문을 참고하시기 바랍니다.(공공데이터포털>정보공유>자료실)
Author지방자치단체
URLhttps://www.data.go.kr/data/15100063/standard.do

Alerts

자전거도로종류 is highly imbalanced (62.0%)Imbalance
노선번호 has 8042 (80.4%) missing valuesMissing
도로구간-기점(위도) has 4554 (45.5%) missing valuesMissing
도로구간-기점(경도) has 4554 (45.5%) missing valuesMissing
도로구간-종점(위도) has 4559 (45.6%) missing valuesMissing
도로구간-종점(경도) has 4559 (45.6%) missing valuesMissing
주요경유지 has 8693 (86.9%) missing valuesMissing
일반도로너비(m) has 9538 (95.4%) missing valuesMissing
자전거도로고시유무 has 2294 (22.9%) missing valuesMissing
관리기관전화번호 has 992 (9.9%) missing valuesMissing

Reproduction

Analysis started2024-05-11 10:09:17.864395
Analysis finished2024-05-11 10:09:22.462020
Duration4.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

노선명
Text

Distinct8979
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T10:09:23.091576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length25
Mean length7.2187
Min length2

Characters and Unicode

Total characters72187
Distinct characters488
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8332 ?
Unique (%)83.3%

Sample

1st row산호대로1R-45
2nd row국토종주자전거길1-400
3rd row강동로2-6
4th row불정로376번길
5th row형곡로1R-31
ValueCountFrequency (%)
r 112
 
1.0%
l 106
 
1.0%
1l 53
 
0.5%
1r 48
 
0.4%
2r 33
 
0.3%
2 32
 
0.3%
2l 29
 
0.3%
흥덕2로 29
 
0.3%
1 26
 
0.2%
경기대로 24
 
0.2%
Other values (8884) 10638
95.6%
2024-05-11T10:09:24.535066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 8522
 
11.8%
1 5743
 
8.0%
- 4570
 
6.3%
2 3237
 
4.5%
R 2963
 
4.1%
L 2901
 
4.0%
3 2152
 
3.0%
길 2038
 
2.8%
대 1647
 
2.3%
4 1506
 
2.1%
Other values (478) 36908
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 41833
58.0%
Decimal Number 17523
24.3%
Uppercase Letter 5979
 
8.3%
Dash Punctuation 4570
 
6.3%
Space Separator 1130
 
1.6%
Open Punctuation 523
 
0.7%
Close Punctuation 523
 
0.7%
Math Symbol 53
 
0.1%
Other Punctuation 27
 
< 0.1%
Connector Punctuation 23
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 8522
 
20.4%
길 2038
 
4.9%
대 1647
 
3.9%
동 1358
 
3.2%
산 1277
 
3.1%
단 773
 
1.8%
공 668
 
1.6%
전 596
 
1.4%
번 586
 
1.4%
자 557
 
1.3%
Other values (441) 23811
56.9%
Uppercase Letter
ValueCountFrequency (%)
R 2963
49.6%
L 2901
48.5%
B 46
 
0.8%
C 16
 
0.3%
G 15
 
0.3%
I 14
 
0.2%
X 10
 
0.2%
A 6
 
0.1%
D 5
 
0.1%
S 2
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 5743
32.8%
2 3237
18.5%
3 2152
 
12.3%
4 1506
 
8.6%
5 1161
 
6.6%
6 1087
 
6.2%
7 806
 
4.6%
8 638
 
3.6%
0 626
 
3.6%
9 567
 
3.2%
Other Punctuation
ValueCountFrequency (%)
, 22
81.5%
. 2
 
7.4%
/ 1
 
3.7%
? 1
 
3.7%
@ 1
 
3.7%
Math Symbol
ValueCountFrequency (%)
~ 28
52.8%
> 16
30.2%
+ 9
 
17.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
33.3%
m 1
33.3%
l 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 4570
100.0%
Space Separator
ValueCountFrequency (%)
1130
100.0%
Open Punctuation
ValueCountFrequency (%)
( 523
100.0%
Close Punctuation
ValueCountFrequency (%)
) 523
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 41833
58.0%
Common 24372
33.8%
Latin 5982
 
8.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 8522
 
20.4%
길 2038
 
4.9%
대 1647
 
3.9%
동 1358
 
3.2%
산 1277
 
3.1%
단 773
 
1.8%
공 668
 
1.6%
전 596
 
1.4%
번 586
 
1.4%
자 557
 
1.3%
Other values (441) 23811
56.9%
Common
ValueCountFrequency (%)
1 5743
23.6%
- 4570
18.8%
2 3237
13.3%
3 2152
 
8.8%
4 1506
 
6.2%
5 1161
 
4.8%
1130
 
4.6%
6 1087
 
4.5%
7 806
 
3.3%
8 638
 
2.6%
Other values (13) 2342
9.6%
Latin
ValueCountFrequency (%)
R 2963
49.5%
L 2901
48.5%
B 46
 
0.8%
C 16
 
0.3%
G 15
 
0.3%
I 14
 
0.2%
X 10
 
0.2%
A 6
 
0.1%
D 5
 
0.1%
S 2
 
< 0.1%
Other values (4) 4
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 41833
58.0%
ASCII 30354
42.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 8522
 
20.4%
길 2038
 
4.9%
대 1647
 
3.9%
동 1358
 
3.2%
산 1277
 
3.1%
단 773
 
1.8%
공 668
 
1.6%
전 596
 
1.4%
번 586
 
1.4%
자 557
 
1.3%
Other values (441) 23811
56.9%
ASCII
ValueCountFrequency (%)
1 5743
18.9%
- 4570
15.1%
2 3237
10.7%
R 2963
9.8%
L 2901
9.6%
3 2152
 
7.1%
4 1506
 
5.0%
5 1161
 
3.8%
1130
 
3.7%
6 1087
 
3.6%
Other values (27) 3904
12.9%

노선번호
Text

MISSING 

Distinct1224
Distinct (%)62.5%
Missing8042
Missing (%)80.4%
Memory size156.2 KiB
2024-05-11T10:09:25.649578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length27
Mean length4.5086823
Min length1

Characters and Unicode

Total characters8828
Distinct characters134
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique946 ?
Unique (%)48.3%

Sample

1st row171
2nd row시의국도7호
3rd row214
4th row723
5th row728
ValueCountFrequency (%)
중로 49
 
2.3%
대로 42
 
2.0%
2 17
 
0.8%
5 13
 
0.6%
7 12
 
0.6%
대로3-21 12
 
0.6%
1 12
 
0.6%
24 11
 
0.5%
3 11
 
0.5%
13 11
 
0.5%
Other values (1251) 1945
91.1%
2024-05-11T10:09:27.142809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1151
13.0%
- 820
 
9.3%
2 806
 
9.1%
3 738
 
8.4%
로 557
 
6.3%
4 438
 
5.0%
대 382
 
4.3%
5 360
 
4.1%
6 359
 
4.1%
중 354
 
4.0%
Other values (124) 2863
32.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5068
57.4%
Other Letter 2474
28.0%
Dash Punctuation 820
 
9.3%
Space Separator 177
 
2.0%
Open Punctuation 114
 
1.3%
Close Punctuation 113
 
1.3%
Math Symbol 49
 
0.6%
Other Punctuation 7
 
0.1%
Uppercase Letter 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 557
22.5%
대 382
15.4%
중 354
14.3%
도 133
 
5.4%
호 109
 
4.4%
류 107
 
4.3%
선 93
 
3.8%
광 51
 
2.1%
구 38
 
1.5%
군 38
 
1.5%
Other values (104) 612
24.7%
Decimal Number
ValueCountFrequency (%)
1 1151
22.7%
2 806
15.9%
3 738
14.6%
4 438
 
8.6%
5 360
 
7.1%
6 359
 
7.1%
7 353
 
7.0%
8 316
 
6.2%
0 274
 
5.4%
9 273
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
A 3
50.0%
L 2
33.3%
R 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
, 4
57.1%
. 3
42.9%
Dash Punctuation
ValueCountFrequency (%)
- 820
100.0%
Space Separator
ValueCountFrequency (%)
177
100.0%
Open Punctuation
ValueCountFrequency (%)
( 114
100.0%
Close Punctuation
ValueCountFrequency (%)
) 113
100.0%
Math Symbol
ValueCountFrequency (%)
+ 49
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6348
71.9%
Hangul 2474
 
28.0%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 557
22.5%
대 382
15.4%
중 354
14.3%
도 133
 
5.4%
호 109
 
4.4%
류 107
 
4.3%
선 93
 
3.8%
광 51
 
2.1%
구 38
 
1.5%
군 38
 
1.5%
Other values (104) 612
24.7%
Common
ValueCountFrequency (%)
1 1151
18.1%
- 820
12.9%
2 806
12.7%
3 738
11.6%
4 438
 
6.9%
5 360
 
5.7%
6 359
 
5.7%
7 353
 
5.6%
8 316
 
5.0%
0 274
 
4.3%
Other values (7) 733
11.5%
Latin
ValueCountFrequency (%)
A 3
50.0%
L 2
33.3%
R 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6354
72.0%
Hangul 2473
 
28.0%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1151
18.1%
- 820
12.9%
2 806
12.7%
3 738
11.6%
4 438
 
6.9%
5 360
 
5.7%
6 359
 
5.6%
7 353
 
5.6%
8 316
 
5.0%
0 274
 
4.3%
Other values (10) 739
11.6%
Hangul
ValueCountFrequency (%)
로 557
22.5%
대 382
15.4%
중 354
14.3%
도 133
 
5.4%
호 109
 
4.4%
류 107
 
4.3%
선 93
 
3.8%
광 51
 
2.1%
구 38
 
1.5%
군 38
 
1.5%
Other values (103) 611
24.7%
Compat Jamo
ValueCountFrequency (%)
ㄹ 1
100.0%

시도명
Categorical

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경상북도
4401 
경기도
2491 
광주광역시
 
380
경상남도
 
370
울산광역시
 
359
Other values (14)
1999 

Length

Max length7
Median length4
Mean length3.9684
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경상북도
2nd row경상북도
3rd row경상북도
4th row경기도
5th row경상북도

Common Values

ValueCountFrequency (%)
경상북도 4401
44.0%
경기도 2491
24.9%
광주광역시 380
 
3.8%
경상남도 370
 
3.7%
울산광역시 359
 
3.6%
전라북도 267
 
2.7%
대전광역시 249
 
2.5%
인천광역시 216
 
2.2%
강원도 202
 
2.0%
강원특별자치도 201
 
2.0%
Other values (9) 864
 
8.6%

Length

2024-05-11T10:09:27.767105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경상북도 4401
44.0%
경기도 2491
24.9%
광주광역시 380
 
3.8%
경상남도 370
 
3.7%
울산광역시 359
 
3.6%
전라북도 267
 
2.7%
대전광역시 249
 
2.5%
인천광역시 216
 
2.2%
강원도 205
 
2.1%
강원특별자치도 201
 
2.0%
Other values (8) 861
 
8.6%

시군구명
Text

Distinct116
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T10:09:28.405858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9389
Min length2

Characters and Unicode

Total characters29389
Distinct characters92
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row구미시
2nd row구미시
3rd row구미시
4th row성남시
5th row구미시
ValueCountFrequency (%)
구미시 3997
40.0%
용인시 482
 
4.8%
평택시 322
 
3.2%
수원시 317
 
3.2%
북구 285
 
2.9%
화성시 212
 
2.1%
단원구 211
 
2.1%
서구 199
 
2.0%
부천시 195
 
1.9%
군산시 169
 
1.7%
Other values (106) 3611
36.1%
2024-05-11T10:09:29.736869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 7735
26.3%
구 5826
19.8%
미 4015
13.7%
원 727
 
2.5%
군 680
 
2.3%
주 673
 
2.3%
천 662
 
2.3%
성 532
 
1.8%
용 496
 
1.7%
인 493
 
1.7%
Other values (82) 7550
25.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29389
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 7735
26.3%
구 5826
19.8%
미 4015
13.7%
원 727
 
2.5%
군 680
 
2.3%
주 673
 
2.3%
천 662
 
2.3%
성 532
 
1.8%
용 496
 
1.7%
인 493
 
1.7%
Other values (82) 7550
25.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29389
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 7735
26.3%
구 5826
19.8%
미 4015
13.7%
원 727
 
2.5%
군 680
 
2.3%
주 673
 
2.3%
천 662
 
2.3%
성 532
 
1.8%
용 496
 
1.7%
인 493
 
1.7%
Other values (82) 7550
25.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29389
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 7735
26.3%
구 5826
19.8%
미 4015
13.7%
원 727
 
2.5%
군 680
 
2.3%
주 673
 
2.3%
천 662
 
2.3%
성 532
 
1.8%
용 496
 
1.7%
인 493
 
1.7%
Other values (82) 7550
25.7%

도로구간-기점
Text

Distinct5480
Distinct (%)54.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T10:09:30.629754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length35
Mean length18.6001
Min length2

Characters and Unicode

Total characters186001
Distinct characters507
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4734 ?
Unique (%)47.3%

Sample

1st row경상북도 구미시 공단동 343
2nd row경상북도 구미시 공단동 360-1
3rd row경상북도 구미시 산동읍 인덕리 100
4th row경기도 성남시 분당구 서현동 353-2
5th row경상북도 구미시 형곡동 104-19
ValueCountFrequency (%)
경상북도 4401
 
10.6%
구미시 3997
 
9.6%
경기도 2023
 
4.9%
공단동 724
 
1.7%
용인시 481
 
1.2%
산동읍 401
 
1.0%
광주광역시 380
 
0.9%
경상남도 356
 
0.9%
울산광역시 322
 
0.8%
평택시 320
 
0.8%
Other values (6986) 28117
67.7%
2024-05-11T10:09:32.327786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31634
 
17.0%
시 9014
 
4.8%
동 8479
 
4.6%
도 8124
 
4.4%
구 7161
 
3.8%
경 7040
 
3.8%
1 7036
 
3.8%
- 6080
 
3.3%
북 5236
 
2.8%
상 5041
 
2.7%
Other values (497) 91156
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 110181
59.2%
Decimal Number 37032
 
19.9%
Space Separator 31634
 
17.0%
Dash Punctuation 6080
 
3.3%
Close Punctuation 485
 
0.3%
Open Punctuation 483
 
0.3%
Uppercase Letter 59
 
< 0.1%
Other Punctuation 39
 
< 0.1%
Lowercase Letter 7
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 9014
 
8.2%
동 8479
 
7.7%
도 8124
 
7.4%
구 7161
 
6.5%
경 7040
 
6.4%
북 5236
 
4.8%
상 5041
 
4.6%
미 4198
 
3.8%
리 2485
 
2.3%
기 2358
 
2.1%
Other values (454) 51045
46.3%
Uppercase Letter
ValueCountFrequency (%)
A 11
18.6%
I 7
11.9%
C 7
11.9%
L 6
10.2%
S 6
10.2%
Y 4
 
6.8%
D 3
 
5.1%
K 3
 
5.1%
H 2
 
3.4%
G 2
 
3.4%
Other values (6) 8
13.6%
Decimal Number
ValueCountFrequency (%)
1 7036
19.0%
2 4550
12.3%
3 4121
11.1%
4 3731
10.1%
6 3488
9.4%
5 3150
8.5%
8 2863
7.7%
7 2851
7.7%
0 2785
 
7.5%
9 2457
 
6.6%
Lowercase Letter
ValueCountFrequency (%)
u 1
14.3%
f 1
14.3%
n 1
14.3%
o 1
14.3%
p 1
14.3%
e 1
14.3%
k 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 35
89.7%
＠ 1
 
2.6%
@ 1
 
2.6%
. 1
 
2.6%
? 1
 
2.6%
Space Separator
ValueCountFrequency (%)
31634
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6080
100.0%
Close Punctuation
ValueCountFrequency (%)
) 485
100.0%
Open Punctuation
ValueCountFrequency (%)
( 483
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 110179
59.2%
Common 75754
40.7%
Latin 66
 
< 0.1%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 9014
 
8.2%
동 8479
 
7.7%
도 8124
 
7.4%
구 7161
 
6.5%
경 7040
 
6.4%
북 5236
 
4.8%
상 5041
 
4.6%
미 4198
 
3.8%
리 2485
 
2.3%
기 2358
 
2.1%
Other values (453) 51043
46.3%
Latin
ValueCountFrequency (%)
A 11
16.7%
I 7
10.6%
C 7
10.6%
L 6
 
9.1%
S 6
 
9.1%
Y 4
 
6.1%
D 3
 
4.5%
K 3
 
4.5%
H 2
 
3.0%
G 2
 
3.0%
Other values (13) 15
22.7%
Common
ValueCountFrequency (%)
31634
41.8%
1 7036
 
9.3%
- 6080
 
8.0%
2 4550
 
6.0%
3 4121
 
5.4%
4 3731
 
4.9%
6 3488
 
4.6%
5 3150
 
4.2%
8 2863
 
3.8%
7 2851
 
3.8%
Other values (10) 6250
 
8.3%
Han
ValueCountFrequency (%)
家 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 110179
59.2%
ASCII 75819
40.8%
CJK 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31634
41.7%
1 7036
 
9.3%
- 6080
 
8.0%
2 4550
 
6.0%
3 4121
 
5.4%
4 3731
 
4.9%
6 3488
 
4.6%
5 3150
 
4.2%
8 2863
 
3.8%
7 2851
 
3.8%
Other values (32) 6315
 
8.3%
Hangul
ValueCountFrequency (%)
시 9014
 
8.2%
동 8479
 
7.7%
도 8124
 
7.4%
구 7161
 
6.5%
경 7040
 
6.4%
북 5236
 
4.8%
상 5041
 
4.6%
미 4198
 
3.8%
리 2485
 
2.3%
기 2358
 
2.1%
Other values (453) 51043
46.3%
CJK
ValueCountFrequency (%)
家 2
100.0%
None
ValueCountFrequency (%)
＠ 1
100.0%

도로구간-종점
Text

Distinct5521
Distinct (%)55.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T10:09:33.235385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length36
Mean length18.8173
Min length3

Characters and Unicode

Total characters188173
Distinct characters490
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4783 ?
Unique (%)47.8%

Sample

1st row경상북도 구미시 거의동 620-1
2nd row경상북도 상주시 낙동면 낙동리 1067-2
3rd row경상북도 구미시 산동읍 인덕리 372-4
4th row경기도 성남시 분당구 서현동 312-3
5th row경상북도 구미시 형곡동 229-3
ValueCountFrequency (%)
경상북도 4401
 
10.5%
구미시 3669
 
8.8%
경기도 2022
 
4.8%
용인시 480
 
1.1%
공단동 441
 
1.1%
광주광역시 380
 
0.9%
경상남도 365
 
0.9%
산동읍 357
 
0.9%
상주시 342
 
0.8%
평택시 322
 
0.8%
Other values (7003) 29105
69.5%
2024-05-11T10:09:35.220021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31988
 
17.0%
시 9061
 
4.8%
동 8756
 
4.7%
도 8141
 
4.3%
1 7315
 
3.9%
경 7045
 
3.7%
구 6804
 
3.6%
- 6081
 
3.2%
상 5443
 
2.9%
북 5235
 
2.8%
Other values (480) 92304
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 111576
59.3%
Decimal Number 37428
 
19.9%
Space Separator 31988
 
17.0%
Dash Punctuation 6081
 
3.2%
Open Punctuation 492
 
0.3%
Close Punctuation 490
 
0.3%
Uppercase Letter 73
 
< 0.1%
Other Punctuation 33
 
< 0.1%
Math Symbol 11
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 9061
 
8.1%
동 8756
 
7.8%
도 8141
 
7.3%
경 7045
 
6.3%
구 6804
 
6.1%
상 5443
 
4.9%
북 5235
 
4.7%
미 3922
 
3.5%
리 2823
 
2.5%
기 2338
 
2.1%
Other values (447) 52008
46.6%
Uppercase Letter
ValueCountFrequency (%)
C 15
20.5%
I 12
16.4%
A 10
13.7%
L 7
9.6%
Y 7
9.6%
G 6
 
8.2%
S 6
 
8.2%
H 2
 
2.7%
D 2
 
2.7%
T 2
 
2.7%
Other values (4) 4
 
5.5%
Decimal Number
ValueCountFrequency (%)
1 7315
19.5%
2 4647
12.4%
4 3915
10.5%
3 3740
10.0%
6 3366
9.0%
7 3095
8.3%
5 3084
8.2%
0 2976
8.0%
8 2667
 
7.1%
9 2623
 
7.0%
Other Punctuation
ValueCountFrequency (%)
, 32
97.0%
＠ 1
 
3.0%
Math Symbol
ValueCountFrequency (%)
> 9
81.8%
~ 2
 
18.2%
Space Separator
ValueCountFrequency (%)
31988
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6081
100.0%
Open Punctuation
ValueCountFrequency (%)
( 492
100.0%
Close Punctuation
ValueCountFrequency (%)
) 490
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 111577
59.3%
Common 76523
40.7%
Latin 73
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 9061
 
8.1%
동 8756
 
7.8%
도 8141
 
7.3%
경 7045
 
6.3%
구 6804
 
6.1%
상 5443
 
4.9%
북 5235
 
4.7%
미 3922
 
3.5%
리 2823
 
2.5%
기 2338
 
2.1%
Other values (448) 52009
46.6%
Common
ValueCountFrequency (%)
31988
41.8%
1 7315
 
9.6%
- 6081
 
7.9%
2 4647
 
6.1%
4 3915
 
5.1%
3 3740
 
4.9%
6 3366
 
4.4%
7 3095
 
4.0%
5 3084
 
4.0%
0 2976
 
3.9%
Other values (8) 6316
 
8.3%
Latin
ValueCountFrequency (%)
C 15
20.5%
I 12
16.4%
A 10
13.7%
L 7
9.6%
Y 7
9.6%
G 6
 
8.2%
S 6
 
8.2%
H 2
 
2.7%
D 2
 
2.7%
T 2
 
2.7%
Other values (4) 4
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 111576
59.3%
ASCII 76595
40.7%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31988
41.8%
1 7315
 
9.6%
- 6081
 
7.9%
2 4647
 
6.1%
4 3915
 
5.1%
3 3740
 
4.9%
6 3366
 
4.4%
7 3095
 
4.0%
5 3084
 
4.0%
0 2976
 
3.9%
Other values (21) 6388
 
8.3%
Hangul
ValueCountFrequency (%)
시 9061
 
8.1%
동 8756
 
7.8%
도 8141
 
7.3%
경 7045
 
6.3%
구 6804
 
6.1%
상 5443
 
4.9%
북 5235
 
4.7%
미 3922
 
3.5%
리 2823
 
2.5%
기 2338
 
2.1%
Other values (447) 52008
46.6%
None
ValueCountFrequency (%)
＠ 1
50.0%
㈜ 1
50.0%

도로구간-기점(위도)
Real number (ℝ)

MISSING 

Distinct1656
Distinct (%)30.4%
Missing4554
Missing (%)45.5%
Infinite0
Infinite (%)0.0%
Mean36.168819
Minimum26.705984
Maximum38.133104
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T10:09:35.871731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26.705984
5-th percentile35.664924
Q136.107534
median36.126883
Q336.160432
95-th percentile37.402887
Maximum38.133104
Range11.42712
Interquartile range (IQR)0.0528975

Descriptive statistics

Standard deviation0.83212619
Coefficient of variation (CV)0.023006729
Kurtosis89.80158
Mean36.168819
Median Absolute Deviation (MAD)0.024842
Skewness-7.9001676
Sum196975.39
Variance0.692434
MonotonicityNot monotonic
2024-05-11T10:09:36.411367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.124247 319
 
3.2%
36.123178 85
 
0.9%
36.134193 80
 
0.8%
36.168904 59
 
0.6%
36.132047 50
 
0.5%
36.127103 49
 
0.5%
36.203078 48
 
0.5%
36.135494 43
 
0.4%
36.110803 40
 
0.4%
36.122521 39
 
0.4%
Other values (1646) 4634
46.3%
(Missing) 4554
45.5%
ValueCountFrequency (%)
26.705984 30
0.3%
34.314888 1
 
< 0.1%
34.392403 1
 
< 0.1%
34.570291 1
 
< 0.1%
34.5801125 1
 
< 0.1%
34.60253833 1
 
< 0.1%
34.603502 1
 
< 0.1%
34.61346443 1
 
< 0.1%
34.733512 1
 
< 0.1%
34.743898 1
 
< 0.1%
ValueCountFrequency (%)
38.1331038 1
< 0.1%
38.0405235 1
< 0.1%
37.97069086 1
< 0.1%
37.84018 1
< 0.1%
37.830433 1
< 0.1%
37.82275 1
< 0.1%
37.816892 1
< 0.1%
37.813168 1
< 0.1%
37.747246 1
< 0.1%
37.616294 1
< 0.1%

도로구간-기점(경도)
Real number (ℝ)

MISSING 

Distinct1652
Distinct (%)30.3%
Missing4554
Missing (%)45.5%
Infinite0
Infinite (%)0.0%
Mean128.26164
Minimum126.09767
Maximum137.45617
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T10:09:37.025183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.09767
5-th percentile126.91657
Q1128.31344
median128.36271
Q3128.41693
95-th percentile129.10362
Maximum137.45617
Range11.358498
Interquartile range (IQR)0.103496

Descriptive statistics

Standard deviation0.87933491
Coefficient of variation (CV)0.0068557903
Kurtosis63.719224
Mean128.26164
Median Absolute Deviation (MAD)0.05324
Skewness5.9225069
Sum698512.89
Variance0.77322988
MonotonicityNot monotonic
2024-05-11T10:09:37.476220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.387037 319
 
3.2%
128.416935 88
 
0.9%
128.362804 85
 
0.9%
128.433515 59
 
0.6%
128.493565 50
 
0.5%
128.360989 49
 
0.5%
128.390282 48
 
0.5%
128.428899 43
 
0.4%
128.365041 40
 
0.4%
128.385843 39
 
0.4%
Other values (1642) 4626
46.3%
(Missing) 4554
45.5%
ValueCountFrequency (%)
126.0976749 1
< 0.1%
126.386333 1
< 0.1%
126.389492 1
< 0.1%
126.453085 1
< 0.1%
126.456554 2
< 0.1%
126.461264 1
< 0.1%
126.467028 1
< 0.1%
126.473013 2
< 0.1%
126.475084 1
< 0.1%
126.475621 1
< 0.1%
ValueCountFrequency (%)
137.456173 30
0.3%
129.518424 1
 
< 0.1%
129.5163733 1
 
< 0.1%
129.5162829 1
 
< 0.1%
129.510239 1
 
< 0.1%
129.5097318 2
 
< 0.1%
129.5094717 1
 
< 0.1%
129.5083469 1
 
< 0.1%
129.5073058 1
 
< 0.1%
129.4996566 1
 
< 0.1%

도로구간-종점(위도)
Real number (ℝ)

MISSING 

Distinct1647
Distinct (%)30.3%
Missing4559
Missing (%)45.6%
Infinite0
Infinite (%)0.0%
Mean36.180693
Minimum26.705916
Maximum38.213228
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T10:09:38.010467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26.705916
5-th percentile35.667147
Q136.102095
median36.133567
Q336.237729
95-th percentile37.403035
Maximum38.213228
Range11.507312
Interquartile range (IQR)0.135634

Descriptive statistics

Standard deviation0.83369868
Coefficient of variation (CV)0.02304264
Kurtosis89.643669
Mean36.180693
Median Absolute Deviation (MAD)0.041016
Skewness-7.9031845
Sum196859.15
Variance0.69505349
MonotonicityNot monotonic
2024-05-11T10:09:38.627277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.356719 319
 
3.2%
36.087093 85
 
0.9%
36.130201 80
 
0.8%
36.196719 59
 
0.6%
36.163141 50
 
0.5%
36.122832 49
 
0.5%
36.230878 48
 
0.5%
36.136501 43
 
0.4%
36.110911 40
 
0.4%
36.137132 39
 
0.4%
Other values (1637) 4629
46.3%
(Missing) 4559
45.6%
ValueCountFrequency (%)
26.705916 30
0.3%
34.316041 1
 
< 0.1%
34.388767 1
 
< 0.1%
34.5668991 1
 
< 0.1%
34.5840931 1
 
< 0.1%
34.60253833 1
 
< 0.1%
34.603502 1
 
< 0.1%
34.61346443 1
 
< 0.1%
34.743188 2
 
< 0.1%
34.747093 1
 
< 0.1%
ValueCountFrequency (%)
38.2132277 1
< 0.1%
38.10419114 1
< 0.1%
38.1025384 1
< 0.1%
37.882028 1
< 0.1%
37.846882 1
< 0.1%
37.826499 1
< 0.1%
37.806948 1
< 0.1%
37.806836 1
< 0.1%
37.773506 1
< 0.1%
37.617958 1
< 0.1%

도로구간-종점(경도)
Real number (ℝ)

MISSING 

Distinct1642
Distinct (%)30.2%
Missing4559
Missing (%)45.6%
Infinite0
Infinite (%)0.0%
Mean128.25988
Minimum126.08164
Maximum137.45618
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T10:09:39.071650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.08164
5-th percentile126.91867
Q1128.29607
median128.35578
Q3128.41706
95-th percentile129.10727
Maximum137.45618
Range11.37454
Interquartile range (IQR)0.120986

Descriptive statistics

Standard deviation0.87912762
Coefficient of variation (CV)0.0068542681
Kurtosis63.890642
Mean128.25988
Median Absolute Deviation (MAD)0.061273
Skewness5.9415252
Sum697862.02
Variance0.77286537
MonotonicityNot monotonic
2024-05-11T10:09:39.665253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.292997 319
 
3.2%
128.361212 85
 
0.9%
128.456701 80
 
0.8%
128.392164 59
 
0.6%
128.463088 50
 
0.5%
128.385558 49
 
0.5%
128.355784 48
 
0.5%
128.448001 43
 
0.4%
128.385206 40
 
0.4%
128.412278 39
 
0.4%
Other values (1632) 4629
46.3%
(Missing) 4559
45.6%
ValueCountFrequency (%)
126.0816353 1
< 0.1%
126.372587 1
< 0.1%
126.41887 1
< 0.1%
126.443495 1
< 0.1%
126.453085 1
< 0.1%
126.457981 1
< 0.1%
126.461264 2
< 0.1%
126.465908 1
< 0.1%
126.473089 2
< 0.1%
126.483615 1
< 0.1%
ValueCountFrequency (%)
137.456175 30
0.3%
129.879487 1
 
< 0.1%
129.518424 1
 
< 0.1%
129.5163733 1
 
< 0.1%
129.510239 2
 
< 0.1%
129.5097318 1
 
< 0.1%
129.5094717 1
 
< 0.1%
129.5083469 1
 
< 0.1%
129.5073058 2
 
< 0.1%
129.4996566 1
 
< 0.1%

주요경유지
Text

MISSING 

Distinct1044
Distinct (%)79.9%
Missing8693
Missing (%)86.9%
Memory size156.2 KiB
2024-05-11T10:09:40.244220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length16
Mean length6.9808722
Min length1

Characters and Unicode

Total characters9124
Distinct characters452
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique881 ?
Unique (%)67.4%

Sample

1st row신은초등학교 삼거리
2nd row운남동 1781
3rd row신정이펜하우스2단지
4th row삼척IC
5th row모래내행복센터
ValueCountFrequency (%)
47
 
3.1%
운남동 16
 
1.0%
수원제3일반산업단지 11
 
0.7%
삼호읍 10
 
0.7%
운서동 10
 
0.7%
용장리 10
 
0.7%
내남면 10
 
0.7%
중산동 9
 
0.6%
정류장 8
 
0.5%
동남리 7
 
0.5%
Other values (1142) 1391
91.0%
2024-05-11T10:09:41.591003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 309
 
3.4%
원 267
 
2.9%
동 236
 
2.6%
리 234
 
2.6%
222
 
2.4%
지 188
 
2.1%
학 156
 
1.7%
거 142
 
1.6%
- 141
 
1.5%
1 134
 
1.5%
Other values (442) 7095
77.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7822
85.7%
Decimal Number 666
 
7.3%
Space Separator 222
 
2.4%
Dash Punctuation 141
 
1.5%
Uppercase Letter 123
 
1.3%
Math Symbol 70
 
0.8%
Close Punctuation 35
 
0.4%
Open Punctuation 35
 
0.4%
Other Punctuation 6
 
0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 309
 
4.0%
원 267
 
3.4%
동 236
 
3.0%
리 234
 
3.0%
지 188
 
2.4%
학 156
 
2.0%
거 142
 
1.8%
수 133
 
1.7%
트 125
 
1.6%
대 122
 
1.6%
Other values (404) 5910
75.6%
Uppercase Letter
ValueCountFrequency (%)
K 19
15.4%
C 17
13.8%
S 14
11.4%
L 12
9.8%
T 12
9.8%
H 10
8.1%
I 9
7.3%
G 7
 
5.7%
B 7
 
5.7%
A 4
 
3.3%
Other values (9) 12
9.8%
Decimal Number
ValueCountFrequency (%)
1 134
20.1%
3 114
17.1%
2 82
12.3%
7 59
8.9%
6 58
8.7%
8 49
 
7.4%
4 46
 
6.9%
5 42
 
6.3%
0 42
 
6.3%
9 40
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 3
50.0%
& 2
33.3%
@ 1
 
16.7%
Space Separator
ValueCountFrequency (%)
222
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 141
100.0%
Math Symbol
ValueCountFrequency (%)
+ 70
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7822
85.7%
Common 1175
 
12.9%
Latin 127
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 309
 
4.0%
원 267
 
3.4%
동 236
 
3.0%
리 234
 
3.0%
지 188
 
2.4%
학 156
 
2.0%
거 142
 
1.8%
수 133
 
1.7%
트 125
 
1.6%
대 122
 
1.6%
Other values (404) 5910
75.6%
Latin
ValueCountFrequency (%)
K 19
15.0%
C 17
13.4%
S 14
11.0%
L 12
9.4%
T 12
9.4%
H 10
7.9%
I 9
7.1%
G 7
 
5.5%
B 7
 
5.5%
e 4
 
3.1%
Other values (10) 16
12.6%
Common
ValueCountFrequency (%)
222
18.9%
- 141
12.0%
1 134
11.4%
3 114
9.7%
2 82
 
7.0%
+ 70
 
6.0%
7 59
 
5.0%
6 58
 
4.9%
8 49
 
4.2%
4 46
 
3.9%
Other values (8) 200
17.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7822
85.7%
ASCII 1302
 
14.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 309
 
4.0%
원 267
 
3.4%
동 236
 
3.0%
리 234
 
3.0%
지 188
 
2.4%
학 156
 
2.0%
거 142
 
1.8%
수 133
 
1.7%
트 125
 
1.6%
대 122
 
1.6%
Other values (404) 5910
75.6%
ASCII
ValueCountFrequency (%)
222
17.1%
- 141
10.8%
1 134
10.3%
3 114
 
8.8%
2 82
 
6.3%
+ 70
 
5.4%
7 59
 
4.5%
6 58
 
4.5%
8 49
 
3.8%
4 46
 
3.5%
Other values (28) 327
25.1%

총길이(km)
Real number (ℝ)

Distinct648
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8663231
Minimum0.01
Maximum58
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T10:09:42.036532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.05
Q10.05
median0.24
Q30.92
95-th percentile3.5
Maximum58
Range57.99
Interquartile range (IQR)0.87

Descriptive statistics

Standard deviation2.0347319
Coefficient of variation (CV)2.3486986
Kurtosis195.89706
Mean0.8663231
Median Absolute Deviation (MAD)0.19
Skewness10.266416
Sum8663.231
Variance4.1401337
MonotonicityNot monotonic
2024-05-11T10:09:42.496640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.05 3858
38.6%
0.3 122
 
1.2%
0.2 119
 
1.2%
1.2 115
 
1.1%
0.5 113
 
1.1%
0.4 110
 
1.1%
0.6 91
 
0.9%
0.8 88
 
0.9%
1.0 82
 
0.8%
0.7 72
 
0.7%
Other values (638) 5230
52.3%
ValueCountFrequency (%)
0.01 67
 
0.7%
0.02 51
 
0.5%
0.03 55
 
0.5%
0.04 50
 
0.5%
0.05 3858
38.6%
0.06 31
 
0.3%
0.062 1
 
< 0.1%
0.067 1
 
< 0.1%
0.069 1
 
< 0.1%
0.07 28
 
0.3%
ValueCountFrequency (%)
58.0 1
< 0.1%
57.2 1
< 0.1%
43.5 1
< 0.1%
40.46 1
< 0.1%
37.9 1
< 0.1%
36.0 1
< 0.1%
30.0 1
< 0.1%
28.0 1
< 0.1%
25.89 1
< 0.1%
24.5 1
< 0.1%

일반도로너비(m)
Real number (ℝ)

MISSING 

Distinct35
Distinct (%)7.6%
Missing9538
Missing (%)95.4%
Infinite0
Infinite (%)0.0%
Mean13.876623
Minimum0
Maximum55
Zeros42
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T10:09:42.882313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median8
Q325
95-th percentile35
Maximum55
Range55
Interquartile range (IQR)22

Descriptive statistics

Standard deviation12.065437
Coefficient of variation (CV)0.86947931
Kurtosis-0.8284404
Mean13.876623
Median Absolute Deviation (MAD)7
Skewness0.61227202
Sum6411
Variance145.57477
MonotonicityNot monotonic
2024-05-11T10:09:43.264425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
3 73
 
0.7%
30 50
 
0.5%
0 42
 
0.4%
25 41
 
0.4%
4 32
 
0.3%
5 28
 
0.3%
6 27
 
0.3%
20 25
 
0.2%
35 20
 
0.2%
15 19
 
0.2%
Other values (25) 105
 
1.1%
(Missing) 9538
95.4%
ValueCountFrequency (%)
0 42
0.4%
2 11
 
0.1%
3 73
0.7%
4 32
0.3%
5 28
 
0.3%
6 27
 
0.3%
7 12
 
0.1%
8 15
 
0.1%
10 3
 
< 0.1%
12 7
 
0.1%
ValueCountFrequency (%)
55 1
 
< 0.1%
50 1
 
< 0.1%
45 1
 
< 0.1%
40 7
 
0.1%
36 1
 
< 0.1%
35 20
 
0.2%
34 1
 
< 0.1%
32 1
 
< 0.1%
31 1
 
< 0.1%
30 50
0.5%

자전거도로너비(m)
Text

Distinct122
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T10:09:43.722143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length2.1141
Min length1

Characters and Unicode

Total characters21141
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)0.5%

Sample

1st row4
2nd row4
3rd row2
4th row1.5
5th row3
ValueCountFrequency (%)
2 1815
18.1%
1.5 1665
16.7%
3 1340
13.4%
2.5 1103
11.0%
4 877
8.8%
3.5 406
 
4.1%
1.2 342
 
3.4%
5 245
 
2.5%
1.8 227
 
2.3%
2.2 151
 
1.5%
Other values (112) 1829
18.3%
2024-05-11T10:09:44.611309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 5504
26.0%
2 4146
19.6%
5 3772
17.8%
1 3297
15.6%
3 2100
 
9.9%
4 1287
 
6.1%
8 319
 
1.5%
7 262
 
1.2%
6 213
 
1.0%
0 139
 
0.7%
Other values (2) 102
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15631
73.9%
Other Punctuation 5504
 
26.0%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 4146
26.5%
5 3772
24.1%
1 3297
21.1%
3 2100
13.4%
4 1287
 
8.2%
8 319
 
2.0%
7 262
 
1.7%
6 213
 
1.4%
0 139
 
0.9%
9 96
 
0.6%
Other Punctuation
ValueCountFrequency (%)
. 5504
100.0%
Math Symbol
ValueCountFrequency (%)
+ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21141
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 5504
26.0%
2 4146
19.6%
5 3772
17.8%
1 3297
15.6%
3 2100
 
9.9%
4 1287
 
6.1%
8 319
 
1.5%
7 262
 
1.2%
6 213
 
1.0%
0 139
 
0.7%
Other values (2) 102
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21141
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 5504
26.0%
2 4146
19.6%
5 3772
17.8%
1 3297
15.6%
3 2100
 
9.9%
4 1287
 
6.1%
8 319
 
1.5%
7 262
 
1.2%
6 213
 
1.0%
0 139
 
0.7%
Other values (2) 102
 
0.5%

자전거도로종류
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
자전거보행자겸용도로
7773 
<NA>
1496 
자전거전용도로
 
473
자전거전용차로
 
129
자전거우선도로
 
124
Other values (2)
 
5

Length

Max length18
Median length10
Mean length8.8886
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
자전거보행자겸용도로 7773
77.7%
<NA> 1496
 
15.0%
자전거전용도로 473
 
4.7%
자전거전용차로 129
 
1.3%
자전거우선도로 124
 
1.2%
자전거전용도로+자전거보행자겸용도로 4
 
< 0.1%
자전거보행자겸용도로+자전거전용도로 1
 
< 0.1%

Length

2024-05-11T10:09:45.054345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:09:45.405425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자전거보행자겸용도로 7773
77.7%
na 1496
 
15.0%
자전거전용도로 473
 
4.7%
자전거전용차로 129
 
1.3%
자전거우선도로 124
 
1.2%
자전거전용도로+자전거보행자겸용도로 4
 
< 0.1%
자전거보행자겸용도로+자전거전용도로 1
 
< 0.1%

자전거도로고시유무
Boolean

MISSING 

Distinct2
Distinct (%)< 0.1%
Missing2294
Missing (%)22.9%
Memory size97.7 KiB
False
4588 
True
3118 
(Missing)
2294 
ValueCountFrequency (%)
False 4588
45.9%
True 3118
31.2%
(Missing) 2294
22.9%
2024-05-11T10:09:45.729215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

관리기관명
Text

Distinct148
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T10:09:46.330719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length9
Mean length9.3606
Min length3

Characters and Unicode

Total characters93606
Distinct characters120
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

Unique11 ?
Unique (%)0.1%

Sample

1st row경상북도 구미시청
2nd row경상북도 구미시청
3rd row경상북도 구미시청
4th row경기도 성남시청
5th row경상북도 구미시청
ValueCountFrequency (%)
경상북도 4401
21.1%
구미시청 3997
19.2%
경기도 2476
 
11.9%
용인시청 469
 
2.3%
광주광역시 380
 
1.8%
경상남도 370
 
1.8%
안산시 326
 
1.6%
철도교통과 326
 
1.6%
평택시청 322
 
1.5%
수원시청 317
 
1.5%
Other values (149) 7430
35.7%
2024-05-11T10:09:47.331586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10814
11.6%
시 9639
 
10.3%
도 9119
 
9.7%
청 9073
 
9.7%
경 7441
 
7.9%
구 5261
 
5.6%
북 5090
 
5.4%
상 4799
 
5.1%
미 4025
 
4.3%
기 2476
 
2.6%
Other values (110) 25869
27.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 82792
88.4%
Space Separator 10814
 
11.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 9639
11.6%
도 9119
 
11.0%
청 9073
 
11.0%
경 7441
 
9.0%
구 5261
 
6.4%
북 5090
 
6.1%
상 4799
 
5.8%
미 4025
 
4.9%
기 2476
 
3.0%
광 1879
 
2.3%
Other values (109) 23990
29.0%
Space Separator
ValueCountFrequency (%)
10814
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 82792
88.4%
Common 10814
 
11.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 9639
11.6%
도 9119
 
11.0%
청 9073
 
11.0%
경 7441
 
9.0%
구 5261
 
6.4%
북 5090
 
6.1%
상 4799
 
5.8%
미 4025
 
4.9%
기 2476
 
3.0%
광 1879
 
2.3%
Other values (109) 23990
29.0%
Common
ValueCountFrequency (%)
10814
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 82792
88.4%
ASCII 10814
 
11.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10814
100.0%
Hangul
ValueCountFrequency (%)
시 9639
11.6%
도 9119
 
11.0%
청 9073
 
11.0%
경 7441
 
9.0%
구 5261
 
6.4%
북 5090
 
6.1%
상 4799
 
5.8%
미 4025
 
4.9%
기 2476
 
3.0%
광 1879
 
2.3%
Other values (109) 23990
29.0%

관리기관전화번호
Text

MISSING 

Distinct179
Distinct (%)2.0%
Missing992
Missing (%)9.9%
Memory size156.2 KiB
2024-05-11T10:09:48.051491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.97036
Min length7

Characters and Unicode

Total characters107829
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

Unique45 ?
Unique (%)0.5%

Sample

1st row054-480-5485
2nd row054-480-5485
3rd row054-480-5485
4th row031-729-3302
5th row054-480-5485
ValueCountFrequency (%)
054-480-5485 3694
41.0%
031-324-2437 459
 
5.1%
031-481-2293 326
 
3.6%
031-8024-4742 322
 
3.6%
031-228-3435 317
 
3.5%
031-5189-3671 212
 
2.4%
032-625-9092 195
 
2.2%
063-454-3593 169
 
1.9%
042-120 157
 
1.7%
033-250-4271 130
 
1.4%
Other values (169) 3027
33.6%
2024-05-11T10:09:49.401968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 17859
16.6%
4 17353
16.1%
5 16401
15.2%
0 16054
14.9%
8 10527
9.8%
3 8628
8.0%
2 7266
6.7%
1 4266
 
4.0%
6 3599
 
3.3%
7 3495
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 89970
83.4%
Dash Punctuation 17859
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 17353
19.3%
5 16401
18.2%
0 16054
17.8%
8 10527
11.7%
3 8628
9.6%
2 7266
8.1%
1 4266
 
4.7%
6 3599
 
4.0%
7 3495
 
3.9%
9 2381
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 17859
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 107829
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 17859
16.6%
4 17353
16.1%
5 16401
15.2%
0 16054
14.9%
8 10527
9.8%
3 8628
8.0%
2 7266
6.7%
1 4266
 
4.0%
6 3599
 
3.3%
7 3495
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 107829
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 17859
16.6%
4 17353
16.1%
5 16401
15.2%
0 16054
14.9%
8 10527
9.8%
3 8628
8.0%
2 7266
6.7%
1 4266
 
4.0%
6 3599
 
3.3%
7 3495
 
3.2%

데이터기준일자
Date

Distinct88
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-05-26 00:00:00
Maximum2024-04-01 00:00:00
2024-05-11T10:09:49.937640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:09:50.408252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

제공기관코드
Real number (ℝ)

Distinct138
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4728847.8
Minimum3020000
Maximum6520000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T10:09:50.983670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3020000
5-th percentile3530000
Q14050000
median5080000
Q35080000
95-th percentile6300000
Maximum6520000
Range3500000
Interquartile range (IQR)1030000

Descriptive statistics

Standard deviation761358.28
Coefficient of variation (CV)0.16100292
Kurtosis-0.42194645
Mean4728847.8
Median Absolute Deviation (MAD)409000
Skewness0.03081514
Sum4.7288478 × 1010
Variance5.7966643 × 1011
MonotonicityNot monotonic
2024-05-11T10:09:51.618704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5080000 3997
40.0%
4050000 482
 
4.8%
3930000 326
 
3.3%
6310000 322
 
3.2%
3910000 322
 
3.2%
3740000 317
 
3.2%
5530000 212
 
2.1%
3860000 195
 
1.9%
6290000 183
 
1.8%
6300000 157
 
1.6%
Other values (128) 3487
34.9%
ValueCountFrequency (%)
3020000 14
 
0.1%
3030000 15
 
0.1%
3060000 9
 
0.1%
3070000 13
 
0.1%
3100000 11
 
0.1%
3140000 35
0.4%
3150000 43
0.4%
3160000 16
 
0.2%
3210000 24
0.2%
3280000 1
 
< 0.1%
ValueCountFrequency (%)
6520000 50
 
0.5%
6310000 322
3.2%
6300000 157
1.6%
6290000 183
1.8%
6260000 1
 
< 0.1%
5700000 12
 
0.1%
5680000 23
 
0.2%
5670000 95
 
0.9%
5600000 13
 
0.1%
5540000 26
 
0.3%

제공기관명
Text

Distinct138
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T10:09:52.400498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length7.7425
Min length5

Characters and Unicode

Total characters77425
Distinct characters98
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

Unique9 ?
Unique (%)0.1%

Sample

1st row경상북도 구미시
2nd row경상북도 구미시
3rd row경상북도 구미시
4th row경기도 성남시
5th row경상북도 구미시
ValueCountFrequency (%)
경상북도 4403
22.8%
구미시 3997
20.7%
경기도 2491
12.9%
용인시 482
 
2.5%
광주광역시 380
 
2.0%
경상남도 370
 
1.9%
울산광역시 359
 
1.9%
안산시 326
 
1.7%
평택시 322
 
1.7%
수원시 317
 
1.6%
Other values (121) 5890
30.5%
2024-05-11T10:09:53.751405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 9623
12.4%
9337
12.1%
도 8454
10.9%
경 7458
 
9.6%
구 5009
 
6.5%
북 4994
 
6.5%
상 4801
 
6.2%
미 4015
 
5.2%
기 2491
 
3.2%
광 1828
 
2.4%
Other values (88) 19415
25.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68088
87.9%
Space Separator 9337
 
12.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 9623
14.1%
도 8454
12.4%
경 7458
11.0%
구 5009
 
7.4%
북 4994
 
7.3%
상 4801
 
7.1%
미 4015
 
5.9%
기 2491
 
3.7%
광 1828
 
2.7%
역 1382
 
2.0%
Other values (87) 18033
26.5%
Space Separator
ValueCountFrequency (%)
9337
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68088
87.9%
Common 9337
 
12.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 9623
14.1%
도 8454
12.4%
경 7458
11.0%
구 5009
 
7.4%
북 4994
 
7.3%
상 4801
 
7.1%
미 4015
 
5.9%
기 2491
 
3.7%
광 1828
 
2.7%
역 1382
 
2.0%
Other values (87) 18033
26.5%
Common
ValueCountFrequency (%)
9337
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68088
87.9%
ASCII 9337
 
12.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 9623
14.1%
도 8454
12.4%
경 7458
11.0%
구 5009
 
7.4%
북 4994
 
7.3%
상 4801
 
7.1%
미 4015
 
5.9%
기 2491
 
3.7%
광 1828
 
2.7%
역 1382
 
2.0%
Other values (87) 18033
26.5%
ASCII
ValueCountFrequency (%)
9337
100.0%

Sample

노선명노선번호시도명시군구명도로구간-기점도로구간-종점도로구간-기점(위도)도로구간-기점(경도)도로구간-종점(위도)도로구간-종점(경도)주요경유지총길이(km)일반도로너비(m)자전거도로너비(m)자전거도로종류자전거도로고시유무관리기관명관리기관전화번호데이터기준일자제공기관코드제공기관명
13576산호대로1R-45<NA>경상북도구미시경상북도 구미시 공단동 343경상북도 구미시 거의동 620-136.122744128.38573636.136895128.412455<NA>0.05<NA>4자전거보행자겸용도로N경상북도 구미시청054-480-54852023-11-275080000경상북도 구미시
19894국토종주자전거길1-400<NA>경상북도구미시경상북도 구미시 공단동 360-1경상북도 상주시 낙동면 낙동리 1067-236.124247128.38703736.356719128.292997<NA>0.05<NA>4자전거보행자겸용도로N경상북도 구미시청054-480-54852023-11-275080000경상북도 구미시
19164강동로2-6<NA>경상북도구미시경상북도 구미시 산동읍 인덕리 100경상북도 구미시 산동읍 인덕리 372-436.163141128.46308836.163681128.459462<NA>0.05<NA>2자전거보행자겸용도로N경상북도 구미시청054-480-54852023-11-275080000경상북도 구미시
3890불정로376번길<NA>경기도성남시경기도 성남시 분당구 서현동 353-2경기도 성남시 분당구 서현동 312-3<NA><NA><NA><NA><NA>0.42<NA>1.5자전거보행자겸용도로<NA>경기도 성남시청031-729-33022023-08-243780000경기도 성남시
16637형곡로1R-31<NA>경상북도구미시경상북도 구미시 형곡동 104-19경상북도 구미시 형곡동 229-336.116304128.33891636.108091128.339707<NA>0.05<NA>3자전거보행자겸용도로N경상북도 구미시청054-480-54852023-11-275080000경상북도 구미시
8163봉오대로3L<NA>경기도부천시경기도 부천시 오정구 오정동739-8번지경기도 부천시 오정구 오정동734번지<NA><NA><NA><NA><NA>0.43<NA>3.5자전거보행자겸용도로Y경기도 부천시 건설정책과032-625-90922024-01-183860000경기도 부천시
8281소사동로6R<NA>경기도부천시경기도 부천시 소사구 괴안동251-2번지경기도 부천시 소사구 괴안동251-5번지<NA><NA><NA><NA><NA>0.32<NA>3자전거보행자겸용도로Y경기도 부천시 건설정책과032-625-90922024-01-183860000경기도 부천시
16790형곡동로3L-3<NA>경상북도구미시경상북도 구미시 형곡동 385경상북도 구미시 형곡동 38536.106636128.33614636.102335128.336168<NA>0.05<NA>3자전거보행자겸용도로N경상북도 구미시청054-480-54852023-11-275080000경상북도 구미시
2389원당로2R<NA>경상북도영주시경상북도 영주시 휴천3동 642-3경상북도 영주시 영주2동 584<NA><NA><NA><NA><NA>0.46<NA>2.7자전거보행자겸용도로Y경상북도 영주시청054-639-39132023-07-165090000경상북도 영주시
13109옥계2공단로1R-12<NA>경상북도구미시경상북도 구미시 산동읍 성수리 220경상북도 구미시 산동읍 성수리 산22-1336.165951128.41541536.160546128.415915<NA>0.05<NA>3.5자전거보행자겸용도로N경상북도 구미시청054-480-54852023-11-275080000경상북도 구미시
노선명노선번호시도명시군구명도로구간-기점도로구간-종점도로구간-기점(위도)도로구간-기점(경도)도로구간-종점(위도)도로구간-종점(경도)주요경유지총길이(km)일반도로너비(m)자전거도로너비(m)자전거도로종류자전거도로고시유무관리기관명관리기관전화번호데이터기준일자제공기관코드제공기관명
6094월드컵대로<NA>대전광역시유성구대전광역시 유성구 봉명동 560-15대전광역시 유성구 구암동 629-536.348851127.33990436.348817127.326793인삼골네거리+유성고등학교2.02<NA>1.5자전거전용도로Y대전광역시042-1202023-01-056300000대전광역시
2481산막공단북9길대로 3-26경상남도양산시경상남도 양산시 산막동 558-9경상남도 양산시 호계동 112235.375088129.05636835.364524129.065263DTR3.22<NA>1.7자전거보행자겸용도로<NA>경상남도 양산시 도로관리과055-392-27552022-06-145380000경상남도 양산시
1664휴암로(1)시도27경기도파주시경기도 파주시 내포리 1416-4경기도 파주시 내포리 970-2<NA><NA><NA><NA>-1.4<NA>1.5자전거보행자겸용도로Y경기도 파주시청031-940-46662023-07-124060000경기도 파주시
923야은로R7-19<NA>경상북도구미시경상북도 구미시 지산동 657-13경상북도 구미시 신평동 474-236.129309128.34646836.122793128.364329<NA>0.05<NA>5자전거보행자겸용도로N경상북도 구미시청054-480-54852023-11-275080000경상북도 구미시
7214와동로2L<NA>경기도단원구와동 721-4 (와공인중개사)와동 723-5 (삼성빌라사거리)<NA><NA><NA><NA><NA>0.15<NA>1.2자전거보행자겸용도로Y경기도 안산시 철도교통과031-481-22932023-06-123930000경기도 안산시
19567국토종주자전거길1-73<NA>경상북도구미시경상북도 구미시 공단동 360-1경상북도 상주시 낙동면 낙동리 1067-236.124247128.38703736.356719128.292997<NA>0.05<NA>4자전거보행자겸용도로N경상북도 구미시청054-480-54852023-11-275080000경상북도 구미시
11135삼산로82번길L<NA>울산광역시남구울산광역시 남구 달동 1399-14울산광역시 남구 달동 1406-17<NA><NA><NA><NA><NA>0.14<NA>1.5<NA><NA>울산광역시 남구청<NA>2023-07-036310000울산광역시
11196등대로R<NA>울산광역시동구울산광역시 동구 일산동 980울산광역시 동구 화정동 671-1<NA><NA><NA><NA><NA>0.65<NA>1.6<NA><NA>울산광역시청 종합건설본부<NA>2023-07-036310000울산광역시
11473처용산업로L<NA>울산광역시울주군울산광역시 울주군 처용리 650울산광역시 울주군 처용리 630<NA><NA><NA><NA><NA>1.29<NA>1.5<NA><NA>울산광역시청 종합건설본부<NA>2023-07-036310000울산광역시
7005해안로2R<NA>경기도단원구초지동 794-1 (일반폐기물 매립지)사동 1512-7 (사리사거리)<NA><NA><NA><NA><NA>1.81<NA>2자전거보행자겸용도로Y경기도 안산시 철도교통과031-481-22932023-06-123930000경기도 안산시