Overview

Dataset statistics

Number of variables28
Number of observations4830
Missing cells3734
Missing cells (%)2.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 MiB
Average record size in memory239.0 B

Variable types

Text8
Categorical9
Numeric10
DateTime1

Dataset

Description공공데이터 제공 표준데이터 속성정보는 [공공데이터 제공 표준] 을 참고하시기 바랍니다. 각 기관에서 등록한 표준데이터를 취합하여 제공하기 때문에 갱신주기는 개별 파일마다 다릅니다. 일괄 제공정보는 한국도로공사를 확인 바랍니다. http://data.ex.co.kr/dataset/datasetList/list?pn=0&keyWord=%EA%B0%80%EB%B3%80%EC%A0%84%EA%B4%91%ED%91%9C%EC%A7%80%ED%8C%90
Author국토교통부, 지방자치단체
URLhttps://www.data.go.kr/data/15034544/standard.do

Alerts

출력방향코드 is highly imbalanced (67.3%)Imbalance
발광패널유형코드 is highly imbalanced (94.9%)Imbalance
도로노선번호 has 735 (15.2%) missing valuesMissing
영상표시면가로길이 has 486 (10.1%) missing valuesMissing
영상표시면세로길이 has 486 (10.1%) missing valuesMissing
전광판함체가로길이 has 659 (13.6%) missing valuesMissing
전광판함체세로길이 has 662 (13.7%) missing valuesMissing
전광판높이 has 666 (13.8%) missing valuesMissing

Reproduction

Analysis started2024-05-11 10:17:02.528309
Analysis finished2024-05-11 10:17:05.439247
Duration2.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

가변전광표지판명
Text

Distinct4306
Distinct (%)89.9%
Missing40
Missing (%)0.8%
Memory size37.9 KiB
2024-05-11T10:17:06.021157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length21
Mean length8.8561587
Min length2

Characters and Unicode

Total characters42421
Distinct characters564
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

Unique3904 ?
Unique (%)81.5%

Sample

1st row상양혈(하행)
2nd row손양IC(상행)
3rd row포월리(하행)
4th row조산삼거리(상행)
5th row쌍천교(하행)
ValueCountFrequency (%)
앞 126
 
1.7%
전 90
 
1.2%
서울방향 57
 
0.8%
국도21 45
 
0.6%
국도 41
 
0.6%
전북 41
 
0.6%
아산시 41
 
0.6%
국도32 36
 
0.5%
후 36
 
0.5%
공주시 35
 
0.5%
Other values (4718) 6746
92.5%
2024-05-11T10:17:07.292442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2515
 
5.9%
( 1886
 
4.4%
) 1885
 
4.4%
C 1246
 
2.9%
리 1056
 
2.5%
교 924
 
2.2%
I 867
 
2.0%
산 771
 
1.8%
도 649
 
1.5%
1 616
 
1.5%
Other values (554) 30006
70.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28513
67.2%
Uppercase Letter 3319
 
7.8%
Decimal Number 2780
 
6.6%
Space Separator 2515
 
5.9%
Open Punctuation 2280
 
5.4%
Close Punctuation 2279
 
5.4%
Dash Punctuation 475
 
1.1%
Other Punctuation 79
 
0.2%
Lowercase Letter 77
 
0.2%
Connector Punctuation 57
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 1056
 
3.7%
교 924
 
3.2%
산 771
 
2.7%
도 649
 
2.3%
주 584
 
2.0%
천 564
 
2.0%
차 548
 
1.9%
로 540
 
1.9%
동 537
 
1.9%
전 526
 
1.8%
Other values (504) 21814
76.5%
Uppercase Letter
ValueCountFrequency (%)
C 1246
37.5%
I 867
26.1%
J 227
 
6.8%
S 203
 
6.1%
T 195
 
5.9%
V 140
 
4.2%
M 138
 
4.2%
L 123
 
3.7%
G 68
 
2.0%
A 36
 
1.1%
Other values (9) 76
 
2.3%
Decimal Number
ValueCountFrequency (%)
1 616
22.2%
3 420
15.1%
2 416
15.0%
0 354
12.7%
4 257
9.2%
5 201
 
7.2%
7 149
 
5.4%
9 129
 
4.6%
6 129
 
4.6%
8 109
 
3.9%
Lowercase Letter
ValueCountFrequency (%)
m 17
22.1%
s 14
18.2%
u 14
18.2%
k 12
15.6%
p 11
14.3%
c 5
 
6.5%
t 2
 
2.6%
e 1
 
1.3%
i 1
 
1.3%
Other Punctuation
ValueCountFrequency (%)
. 71
89.9%
/ 7
 
8.9%
, 1
 
1.3%
Open Punctuation
ValueCountFrequency (%)
( 1886
82.7%
[ 394
 
17.3%
Close Punctuation
ValueCountFrequency (%)
) 1885
82.7%
] 394
 
17.3%
Math Symbol
ValueCountFrequency (%)
+ 41
87.2%
~ 6
 
12.8%
Space Separator
ValueCountFrequency (%)
2515
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 475
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 57
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28513
67.2%
Common 10512
 
24.8%
Latin 3396
 
8.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 1056
 
3.7%
교 924
 
3.2%
산 771
 
2.7%
도 649
 
2.3%
주 584
 
2.0%
천 564
 
2.0%
차 548
 
1.9%
로 540
 
1.9%
동 537
 
1.9%
전 526
 
1.8%
Other values (504) 21814
76.5%
Latin
ValueCountFrequency (%)
C 1246
36.7%
I 867
25.5%
J 227
 
6.7%
S 203
 
6.0%
T 195
 
5.7%
V 140
 
4.1%
M 138
 
4.1%
L 123
 
3.6%
G 68
 
2.0%
A 36
 
1.1%
Other values (18) 153
 
4.5%
Common
ValueCountFrequency (%)
2515
23.9%
( 1886
17.9%
) 1885
17.9%
1 616
 
5.9%
- 475
 
4.5%
3 420
 
4.0%
2 416
 
4.0%
] 394
 
3.7%
[ 394
 
3.7%
0 354
 
3.4%
Other values (12) 1157
11.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28513
67.2%
ASCII 13908
32.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2515
18.1%
( 1886
13.6%
) 1885
13.6%
C 1246
 
9.0%
I 867
 
6.2%
1 616
 
4.4%
- 475
 
3.4%
3 420
 
3.0%
2 416
 
3.0%
] 394
 
2.8%
Other values (40) 3188
22.9%
Hangul
ValueCountFrequency (%)
리 1056
 
3.7%
교 924
 
3.2%
산 771
 
2.7%
도 649
 
2.3%
주 584
 
2.0%
천 564
 
2.0%
차 548
 
1.9%
로 540
 
1.9%
동 537
 
1.9%
전 526
 
1.8%
Other values (504) 21814
76.5%

시도명
Categorical

Distinct19
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
경기도
1352 
강원특별자치도
522 
충청남도
396 
전라남도
384 
경상북도
357 
Other values (14)
1819 

Length

Max length7
Median length5
Mean length4.4418219
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 1352
28.0%
강원특별자치도 522
 
10.8%
충청남도 396
 
8.2%
전라남도 384
 
8.0%
경상북도 357
 
7.4%
전북특별자치도 340
 
7.0%
경상남도 306
 
6.3%
충청북도 295
 
6.1%
부산광역시 168
 
3.5%
인천광역시 145
 
3.0%
Other values (9) 565
11.7%

Length

2024-05-11T10:17:07.891561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 1352
28.0%
강원특별자치도 522
 
10.8%
충청남도 396
 
8.2%
전라남도 384
 
8.0%
경상북도 357
 
7.4%
전북특별자치도 340
 
7.0%
경상남도 306
 
6.3%
충청북도 295
 
6.1%
부산광역시 168
 
3.5%
인천광역시 145
 
3.0%
Other values (9) 565
11.7%

시군구명
Text

Distinct232
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
2024-05-11T10:17:08.838427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.2171843
Min length2

Characters and Unicode

Total characters15539
Distinct characters136
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

Unique13 ?
Unique (%)0.3%

Sample

1st row양양군
2nd row양양군
3rd row양양군
4th row양양군
5th row양양군
ValueCountFrequency (%)
강릉시 145
 
2.9%
화성시 99
 
2.0%
파주시 93
 
1.8%
김해시 81
 
1.6%
고양시 77
 
1.5%
충주시 72
 
1.4%
포천시 72
 
1.4%
성남시 71
 
1.4%
평택시 67
 
1.3%
남양주시 65
 
1.3%
Other values (223) 4193
83.3%
2024-05-11T10:17:10.348848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 2921
18.8%
군 1500
 
9.7%
주 879
 
5.7%
구 875
 
5.6%
천 544
 
3.5%
성 499
 
3.2%
산 416
 
2.7%
양 402
 
2.6%
안 294
 
1.9%
남 280
 
1.8%
Other values (126) 6929
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15334
98.7%
Space Separator 205
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 2921
19.0%
군 1500
 
9.8%
주 879
 
5.7%
구 875
 
5.7%
천 544
 
3.5%
성 499
 
3.3%
산 416
 
2.7%
양 402
 
2.6%
안 294
 
1.9%
남 280
 
1.8%
Other values (125) 6724
43.9%
Space Separator
ValueCountFrequency (%)
205
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15334
98.7%
Common 205
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 2921
19.0%
군 1500
 
9.8%
주 879
 
5.7%
구 875
 
5.7%
천 544
 
3.5%
성 499
 
3.3%
산 416
 
2.7%
양 402
 
2.6%
안 294
 
1.9%
남 280
 
1.8%
Other values (125) 6724
43.9%
Common
ValueCountFrequency (%)
205
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15334
98.7%
ASCII 205
 
1.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 2921
19.0%
군 1500
 
9.8%
주 879
 
5.7%
구 875
 
5.7%
천 544
 
3.5%
성 499
 
3.3%
산 416
 
2.7%
양 402
 
2.6%
안 294
 
1.9%
남 280
 
1.8%
Other values (125) 6724
43.9%
ASCII
ValueCountFrequency (%)
205
100.0%

시군구코드
Real number (ℝ)

Distinct267
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41779.692
Minimum11215
Maximum53500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size42.6 KiB
2024-05-11T10:17:10.986675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11215
5-th percentile26710
Q141370
median42760
Q346130
95-th percentile48850
Maximum53500
Range42285
Interquartile range (IQR)4760

Descriptive statistics

Standard deviation7088.6425
Coefficient of variation (CV)0.16966718
Kurtosis5.244507
Mean41779.692
Median Absolute Deviation (MAD)1628
Skewness-2.0770188
Sum2.0179591 × 108
Variance50248852
MonotonicityNot monotonic
2024-05-11T10:17:11.805289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
43110 300
 
6.2%
43130 110
 
2.3%
41590 99
 
2.0%
41480 93
 
1.9%
42150 90
 
1.9%
41650 72
 
1.5%
48250 70
 
1.4%
41220 67
 
1.4%
42110 67
 
1.4%
50110 67
 
1.4%
Other values (257) 3795
78.6%
ValueCountFrequency (%)
11215 63
1.3%
11260 1
 
< 0.1%
11350 2
 
< 0.1%
11380 1
 
< 0.1%
11545 1
 
< 0.1%
11650 9
 
0.2%
11680 2
 
< 0.1%
11710 2
 
< 0.1%
11740 4
 
0.1%
16110 9
 
0.2%
ValueCountFrequency (%)
53500 13
0.3%
53400 1
 
< 0.1%
52730 1
 
< 0.1%
52720 1
 
< 0.1%
52710 2
 
< 0.1%
52130 21
0.4%
52113 17
0.4%
52111 6
 
0.1%
52100 1
 
< 0.1%
51900 1
 
< 0.1%

도로종류
Categorical

Distinct9
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
일반국도
1919 
고속국도
1670 
시도
593 
지방도
361 
기타
 
81
Other values (4)
206 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반국도 1919
39.7%
고속국도 1670
34.6%
시도 593
 
12.3%
지방도 361
 
7.5%
기타 81
 
1.7%
구도 80
 
1.7%
특별시도 78
 
1.6%
국가지원지방도 30
 
0.6%
군도 18
 
0.4%

Length

2024-05-11T10:17:12.359009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:17:12.711074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반국도 1919
39.7%
고속국도 1670
34.6%
시도 593
 
12.3%
지방도 361
 
7.5%
기타 81
 
1.7%
구도 80
 
1.7%
특별시도 78
 
1.6%
국가지원지방도 30
 
0.6%
군도 18
 
0.4%

도로노선명
Text

Distinct936
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
2024-05-11T10:17:13.454339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length5.0728778
Min length2

Characters and Unicode

Total characters24502
Distinct characters341
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique390 ?
Unique (%)8.1%

Sample

1st row동해대로
2nd row동해대로
3rd row동해대로
4th row동해대로
5th row동해대로
ValueCountFrequency (%)
경부고속도로 202
 
4.2%
서해안고속도로 102
 
2.1%
당진영덕고속도로 96
 
2.0%
중부내륙고속도로 81
 
1.7%
남해고속도로 80
 
1.6%
중앙고속도로 75
 
1.5%
동해대로 70
 
1.4%
서울양양고속도로 68
 
1.4%
경강로 66
 
1.4%
호남고속도로 57
 
1.2%
Other values (926) 3953
81.5%
2024-05-11T10:17:14.586776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 4241
 
17.3%
도 1975
 
8.1%
고 1555
 
6.3%
속 1499
 
6.1%
대 902
 
3.7%
부 535
 
2.2%
해 446
 
1.8%
경 442
 
1.8%
국 440
 
1.8%
서 409
 
1.7%
Other values (331) 12058
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23288
95.0%
Decimal Number 894
 
3.6%
Open Punctuation 114
 
0.5%
Close Punctuation 114
 
0.5%
Math Symbol 50
 
0.2%
Space Separator 22
 
0.1%
Dash Punctuation 18
 
0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 4241
 
18.2%
도 1975
 
8.5%
고 1555
 
6.7%
속 1499
 
6.4%
대 902
 
3.9%
부 535
 
2.3%
해 446
 
1.9%
경 442
 
1.9%
국 440
 
1.9%
서 409
 
1.8%
Other values (314) 10844
46.6%
Decimal Number
ValueCountFrequency (%)
2 257
28.7%
1 224
25.1%
3 141
15.8%
7 99
 
11.1%
9 43
 
4.8%
0 31
 
3.5%
5 30
 
3.4%
4 30
 
3.4%
6 22
 
2.5%
8 17
 
1.9%
Space Separator
ValueCountFrequency (%)
21
95.5%
　 1
 
4.5%
Open Punctuation
ValueCountFrequency (%)
( 114
100.0%
Close Punctuation
ValueCountFrequency (%)
) 114
100.0%
Math Symbol
ValueCountFrequency (%)
~ 50
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23288
95.0%
Common 1214
 
5.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 4241
 
18.2%
도 1975
 
8.5%
고 1555
 
6.7%
속 1499
 
6.4%
대 902
 
3.9%
부 535
 
2.3%
해 446
 
1.9%
경 442
 
1.9%
국 440
 
1.9%
서 409
 
1.8%
Other values (314) 10844
46.6%
Common
ValueCountFrequency (%)
2 257
21.2%
1 224
18.5%
3 141
11.6%
( 114
9.4%
) 114
9.4%
7 99
 
8.2%
~ 50
 
4.1%
9 43
 
3.5%
0 31
 
2.6%
5 30
 
2.5%
Other values (7) 111
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23288
95.0%
ASCII 1213
 
5.0%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 4241
 
18.2%
도 1975
 
8.5%
고 1555
 
6.7%
속 1499
 
6.4%
대 902
 
3.9%
부 535
 
2.3%
해 446
 
1.9%
경 442
 
1.9%
국 440
 
1.9%
서 409
 
1.8%
Other values (314) 10844
46.6%
ASCII
ValueCountFrequency (%)
2 257
21.2%
1 224
18.5%
3 141
11.6%
( 114
9.4%
) 114
9.4%
7 99
 
8.2%
~ 50
 
4.1%
9 43
 
3.5%
0 31
 
2.6%
5 30
 
2.5%
Other values (6) 110
9.1%
None
ValueCountFrequency (%)
　 1
100.0%

도로노선번호
Text

MISSING 

Distinct283
Distinct (%)6.9%
Missing735
Missing (%)15.2%
Memory size37.9 KiB
2024-05-11T10:17:15.488522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length3
Mean length3.0070818
Min length1

Characters and Unicode

Total characters12314
Distinct characters35
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103 ?
Unique (%)2.5%

Sample

1st row7번
2nd row7번
3rd row7번
4th row7번
5th row7번
ValueCountFrequency (%)
1번 266
 
6.5%
30번 131
 
3.2%
45번 121
 
2.9%
10번 106
 
2.6%
17번 103
 
2.5%
35번 99
 
2.4%
7번 96
 
2.3%
43번 87
 
2.1%
5번 84
 
2.0%
21번 82
 
2.0%
Other values (278) 2932
71.4%
2024-05-11T10:17:16.991634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
번 3745
30.4%
1 1568
12.7%
5 1187
 
9.6%
3 1182
 
9.6%
0 1068
 
8.7%
2 943
 
7.7%
4 717
 
5.8%
7 685
 
5.6%
6 523
 
4.2%
9 268
 
2.2%
Other values (25) 428
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8383
68.1%
Other Letter 3909
31.7%
Space Separator 13
 
0.1%
Dash Punctuation 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
번 3745
95.8%
호 97
 
2.5%
선 27
 
0.7%
동 7
 
0.2%
천 3
 
0.1%
광 3
 
0.1%
로 3
 
0.1%
배 3
 
0.1%
곧 3
 
0.1%
왕 2
 
0.1%
Other values (12) 16
 
0.4%
Decimal Number
ValueCountFrequency (%)
1 1568
18.7%
5 1187
14.2%
3 1182
14.1%
0 1068
12.7%
2 943
11.2%
4 717
8.6%
7 685
8.2%
6 523
 
6.2%
9 268
 
3.2%
8 242
 
2.9%
Space Separator
ValueCountFrequency (%)
12
92.3%
　 1
 
7.7%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8405
68.3%
Hangul 3909
31.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
번 3745
95.8%
호 97
 
2.5%
선 27
 
0.7%
동 7
 
0.2%
천 3
 
0.1%
광 3
 
0.1%
로 3
 
0.1%
배 3
 
0.1%
곧 3
 
0.1%
왕 2
 
0.1%
Other values (12) 16
 
0.4%
Common
ValueCountFrequency (%)
1 1568
18.7%
5 1187
14.1%
3 1182
14.1%
0 1068
12.7%
2 943
11.2%
4 717
8.5%
7 685
8.1%
6 523
 
6.2%
9 268
 
3.2%
8 242
 
2.9%
Other values (3) 22
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8404
68.2%
Hangul 3909
31.7%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
번 3745
95.8%
호 97
 
2.5%
선 27
 
0.7%
동 7
 
0.2%
천 3
 
0.1%
광 3
 
0.1%
로 3
 
0.1%
배 3
 
0.1%
곧 3
 
0.1%
왕 2
 
0.1%
Other values (12) 16
 
0.4%
ASCII
ValueCountFrequency (%)
1 1568
18.7%
5 1187
14.1%
3 1182
14.1%
0 1068
12.7%
2 943
11.2%
4 717
8.5%
7 685
8.2%
6 523
 
6.2%
9 268
 
3.2%
8 242
 
2.9%
Other values (2) 21
 
0.2%
None
ValueCountFrequency (%)
　 1
100.0%

도로노선방향
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
1
1941 
2
1731 
<NA>
1027 
3
 
131

Length

Max length4
Median length1
Mean length1.6378882
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row2
4th row1
5th row2

Common Values

ValueCountFrequency (%)
1 1941
40.2%
2 1731
35.8%
<NA> 1027
21.3%
3 131
 
2.7%

Length

2024-05-11T10:17:17.568673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:17:17.991535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1941
40.2%
2 1731
35.8%
na 1027
21.3%
3 131
 
2.7%

위도
Real number (ℝ)

Distinct4627
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.567378
Minimum32.927291
Maximum39.397248
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size42.6 KiB
2024-05-11T10:17:18.412361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32.927291
5-th percentile34.831185
Q135.750159
median36.844997
Q337.459973
95-th percentile37.862883
Maximum39.397248
Range6.469957
Interquartile range (IQR)1.7098138

Descriptive statistics

Standard deviation1.0680701
Coefficient of variation (CV)0.029208278
Kurtosis-0.41638687
Mean36.567378
Median Absolute Deviation (MAD)0.797378
Skewness-0.59411994
Sum176620.43
Variance1.1407738
MonotonicityNot monotonic
2024-05-11T10:17:18.974728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.355845 5
 
0.1%
37.54119693 4
 
0.1%
37.461651 3
 
0.1%
37.606284 3
 
0.1%
37.512075 3
 
0.1%
37.673333 3
 
0.1%
37.473503 3
 
0.1%
37.523788 3
 
0.1%
37.560467 3
 
0.1%
35.874619 2
 
< 0.1%
Other values (4617) 4798
99.3%
ValueCountFrequency (%)
32.927291 1
< 0.1%
33.233386 1
< 0.1%
33.24574634 1
< 0.1%
33.246831 1
< 0.1%
33.25023855 1
< 0.1%
33.2502888 1
< 0.1%
33.254555 1
< 0.1%
33.25685289 1
< 0.1%
33.26364482 1
< 0.1%
33.26489341 1
< 0.1%
ValueCountFrequency (%)
39.397248 1
< 0.1%
39.294801 1
< 0.1%
38.502823 1
< 0.1%
38.450639 1
< 0.1%
38.450094 1
< 0.1%
38.415273 1
< 0.1%
38.414826 1
< 0.1%
38.377075 1
< 0.1%
38.371289 1
< 0.1%
38.358913 1
< 0.1%

경도
Real number (ℝ)

Distinct4602
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.59443
Minimum125.93643
Maximum129.90417
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size42.6 KiB
2024-05-11T10:17:19.556188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum125.93643
5-th percentile126.59916
Q1126.9438
median127.30773
Q3128.28482
95-th percentile129.11117
Maximum129.90417
Range3.96774
Interquartile range (IQR)1.3410197

Descriptive statistics

Standard deviation0.82896197
Coefficient of variation (CV)0.0064968507
Kurtosis-0.86420785
Mean127.59443
Median Absolute Deviation (MAD)0.511628
Skewness0.63068261
Sum616281.11
Variance0.68717796
MonotonicityNot monotonic
2024-05-11T10:17:20.174874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.103333 7
 
0.1%
127.103611 6
 
0.1%
126.86353 5
 
0.1%
127.0677801 4
 
0.1%
128.8993611 4
 
0.1%
126.836666 3
 
0.1%
129.090998 3
 
0.1%
129.100555 3
 
0.1%
128.872222 3
 
0.1%
127.153333 3
 
0.1%
Other values (4592) 4789
99.2%
ValueCountFrequency (%)
125.936427 1
< 0.1%
125.939867 1
< 0.1%
126.205446 1
< 0.1%
126.21207 1
< 0.1%
126.260238 1
< 0.1%
126.262925 1
< 0.1%
126.265373 1
< 0.1%
126.273024 1
< 0.1%
126.2747519 1
< 0.1%
126.281918 1
< 0.1%
ValueCountFrequency (%)
129.904167 1
< 0.1%
129.880001 1
< 0.1%
129.864722 1
< 0.1%
129.831389 1
< 0.1%
129.473381 1
< 0.1%
129.437122 1
< 0.1%
129.429987 1
< 0.1%
129.423995 1
< 0.1%
129.423595 1
< 0.1%
129.411535 1
< 0.1%

영상표시면가로길이
Real number (ℝ)

MISSING 

Distinct122
Distinct (%)2.8%
Missing486
Missing (%)10.1%
Infinite0
Infinite (%)0.0%
Mean6052.087
Minimum6.2
Maximum38400
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size42.6 KiB
2024-05-11T10:17:20.812693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.2
5-th percentile1320
Q14800
median6000
Q37200
95-th percentile9000
Maximum38400
Range38393.8
Interquartile range (IQR)2400

Descriptive statistics

Standard deviation2977.9947
Coefficient of variation (CV)0.49206078
Kurtosis16.052904
Mean6052.087
Median Absolute Deviation (MAD)1200
Skewness2.4594727
Sum26290266
Variance8868452.2
MonotonicityNot monotonic
2024-05-11T10:17:21.364713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6000.0 1735
35.9%
9000.0 527
 
10.9%
7800.0 296
 
6.1%
3600.0 248
 
5.1%
4800.0 238
 
4.9%
6600.0 177
 
3.7%
2400.0 129
 
2.7%
1200.0 90
 
1.9%
2240.0 63
 
1.3%
7200.0 55
 
1.1%
Other values (112) 786
16.3%
(Missing) 486
 
10.1%
ValueCountFrequency (%)
6.2 1
 
< 0.1%
8.6 1
 
< 0.1%
61.0 7
0.1%
256.0 12
0.2%
288.0 2
 
< 0.1%
300.0 7
0.1%
384.0 3
 
0.1%
400.0 2
 
< 0.1%
420.0 1
 
< 0.1%
550.0 1
 
< 0.1%
ValueCountFrequency (%)
38400.0 1
 
< 0.1%
32000.0 3
 
0.1%
28800.0 1
 
< 0.1%
24020.0 2
 
< 0.1%
24000.0 14
0.3%
23000.0 1
 
< 0.1%
21600.0 25
0.5%
19200.0 2
 
< 0.1%
18880.0 1
 
< 0.1%
16000.0 3
 
0.1%

영상표시면세로길이
Real number (ℝ)

MISSING 

Distinct100
Distinct (%)2.3%
Missing486
Missing (%)10.1%
Infinite0
Infinite (%)0.0%
Mean1598.6266
Minimum4.2
Maximum25600
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size42.6 KiB
2024-05-11T10:17:21.958833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.2
5-th percentile600
Q11200
median1200
Q31800
95-th percentile3600
Maximum25600
Range25595.8
Interquartile range (IQR)600

Descriptive statistics

Standard deviation1088.1726
Coefficient of variation (CV)0.68069214
Kurtosis62.962243
Mean1598.6266
Median Absolute Deviation (MAD)400
Skewness4.7789277
Sum6944434
Variance1184119.5
MonotonicityNot monotonic
2024-05-11T10:17:22.568664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1200.0 2029
42.0%
1800.0 856
17.7%
600.0 336
 
7.0%
2400.0 223
 
4.6%
4200.0 82
 
1.7%
960.0 70
 
1.4%
320.0 63
 
1.3%
3000.0 58
 
1.2%
5400.0 49
 
1.0%
120.0 41
 
0.8%
Other values (90) 537
 
11.1%
(Missing) 486
 
10.1%
ValueCountFrequency (%)
4.2 1
 
< 0.1%
4.8 1
 
< 0.1%
120.0 41
0.8%
121.0 7
 
0.1%
128.0 12
 
0.2%
200.0 2
 
< 0.1%
224.0 2
 
< 0.1%
240.0 5
 
0.1%
288.0 3
 
0.1%
300.0 1
 
< 0.1%
ValueCountFrequency (%)
25600.0 1
 
< 0.1%
9600.0 3
 
0.1%
9040.0 1
 
< 0.1%
9000.0 6
0.1%
7040.0 1
 
< 0.1%
6600.0 3
 
0.1%
6450.0 9
0.2%
6400.0 5
0.1%
6300.0 1
 
< 0.1%
6000.0 1
 
< 0.1%

전광판함체가로길이
Real number (ℝ)

MISSING 

Distinct156
Distinct (%)3.7%
Missing659
Missing (%)13.6%
Infinite0
Infinite (%)0.0%
Mean6468.5684
Minimum0
Maximum43800
Zeros3
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size42.6 KiB
2024-05-11T10:17:23.157138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1400
Q15200
median6400
Q37800
95-th percentile9450
Maximum43800
Range43800
Interquartile range (IQR)2600

Descriptive statistics

Standard deviation3426.5711
Coefficient of variation (CV)0.52972634
Kurtosis23.589305
Mean6468.5684
Median Absolute Deviation (MAD)1300
Skewness3.1939947
Sum26980399
Variance11741390
MonotonicityNot monotonic
2024-05-11T10:17:23.818219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6400 1424
29.5%
9400 428
 
8.9%
4000 265
 
5.5%
8300 190
 
3.9%
7000 184
 
3.8%
6600 161
 
3.3%
1400 119
 
2.5%
5200 103
 
2.1%
5000 78
 
1.6%
642 77
 
1.6%
Other values (146) 1142
23.6%
(Missing) 659
13.6%
ValueCountFrequency (%)
0 3
 
0.1%
42 3
 
0.1%
60 30
0.6%
64 7
 
0.1%
78 3
 
0.1%
390 12
 
0.2%
400 4
 
0.1%
500 2
 
< 0.1%
550 1
 
< 0.1%
610 13
0.3%
ValueCountFrequency (%)
43800 2
< 0.1%
40000 1
 
< 0.1%
34000 2
< 0.1%
33000 4
0.1%
30620 1
 
< 0.1%
30600 4
0.1%
30500 1
 
< 0.1%
30000 1
 
< 0.1%
29800 1
 
< 0.1%
26400 4
0.1%

전광판함체세로길이
Real number (ℝ)

MISSING 

Distinct117
Distinct (%)2.8%
Missing662
Missing (%)13.7%
Infinite0
Infinite (%)0.0%
Mean1971.6231
Minimum0
Maximum28000
Zeros3
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size42.6 KiB
2024-05-11T10:17:24.545958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile850
Q11600
median1600
Q32300
95-th percentile4000
Maximum28000
Range28000
Interquartile range (IQR)700

Descriptive statistics

Standard deviation1067.3386
Coefficient of variation (CV)0.54135021
Kurtosis92.555291
Mean1971.6231
Median Absolute Deviation (MAD)400
Skewness5.513645
Sum8217725
Variance1139211.6
MonotonicityNot monotonic
2024-05-11T10:17:25.211192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1600 1855
38.4%
2300 492
 
10.2%
2200 305
 
6.3%
800 105
 
2.2%
900 100
 
2.1%
4600 82
 
1.7%
2600 81
 
1.7%
1000 81
 
1.7%
1700 60
 
1.2%
1200 59
 
1.2%
Other values (107) 948
19.6%
(Missing) 662
 
13.7%
ValueCountFrequency (%)
0 3
 
0.1%
16 10
0.2%
36 3
 
0.1%
90 19
0.4%
110 11
0.2%
120 2
 
< 0.1%
200 2
 
< 0.1%
390 12
0.2%
450 1
 
< 0.1%
500 1
 
< 0.1%
ValueCountFrequency (%)
28000 1
 
< 0.1%
9600 3
0.1%
9040 2
 
< 0.1%
9000 7
0.1%
8300 1
 
< 0.1%
6800 4
0.1%
6400 5
0.1%
6300 1
 
< 0.1%
6141 1
 
< 0.1%
6000 4
0.1%

전광판높이
Real number (ℝ)

MISSING 

Distinct147
Distinct (%)3.5%
Missing666
Missing (%)13.8%
Infinite0
Infinite (%)0.0%
Mean6674.7613
Minimum0
Maximum25000
Zeros3
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size42.6 KiB
2024-05-11T10:17:25.807034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3315
Q16500
median6600
Q37400
95-th percentile9000
Maximum25000
Range25000
Interquartile range (IQR)900

Descriptive statistics

Standard deviation1571.3224
Coefficient of variation (CV)0.23541253
Kurtosis10.069048
Mean6674.7613
Median Absolute Deviation (MAD)400
Skewness-0.91494204
Sum27793706
Variance2469054.2
MonotonicityNot monotonic
2024-05-11T10:17:26.641591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6500 1027
21.3%
6700 346
 
7.2%
7000 288
 
6.0%
7400 227
 
4.7%
8000 163
 
3.4%
7600 109
 
2.3%
6600 101
 
2.1%
7875 90
 
1.9%
6200 83
 
1.7%
6300 80
 
1.7%
Other values (137) 1650
34.2%
(Missing) 666
13.8%
ValueCountFrequency (%)
0 3
 
0.1%
2 4
 
0.1%
8 12
0.2%
9 7
0.1%
11 3
 
0.1%
95 3
 
0.1%
300 7
0.1%
350 2
 
< 0.1%
400 2
 
< 0.1%
500 1
 
< 0.1%
ValueCountFrequency (%)
25000 1
 
< 0.1%
16100 1
 
< 0.1%
16080 1
 
< 0.1%
12060 1
 
< 0.1%
12000 6
0.1%
11800 1
 
< 0.1%
11570 2
 
< 0.1%
11500 5
0.1%
11300 4
0.1%
11050 1
 
< 0.1%

설치유형코드
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
2
1891 
3
1782 
1
1140 
4
 
17

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 1891
39.2%
3 1782
36.9%
1 1140
23.6%
4 17
 
0.4%

Length

2024-05-11T10:17:27.556217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:17:28.138394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1891
39.2%
3 1782
36.9%
1 1140
23.6%
4 17
 
0.4%

출력방향코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
2
4541 
1
 
289

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 4541
94.0%
1 289
 
6.0%

Length

2024-05-11T10:17:28.757032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:17:29.233358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 4541
94.0%
1 289
 
6.0%

발광패널유형코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
1
4802 
2
 
28

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 4802
99.4%
2 28
 
0.6%

Length

2024-05-11T10:17:29.736986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:17:30.155735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 4802
99.4%
2 28
 
0.6%

표출색상
Categorical

Distinct35
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
빨간색+노란색+녹색
1638 
적색+황색+녹색+청색+청녹색+보라색+백색
735 
<NA>
549 
모든 색상
453 
빨간색+노란색+녹색+흑색+흰색+청색+분홍색+하늘색
306 
Other values (30)
1149 

Length

Max length61
Median length27
Mean length13.978261
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row빨간색+노란색+녹색+청색+청녹색+보라색+백색
2nd row빨간색+노란색+녹색
3rd row빨간색+노란색+녹색
4th row빨간색+노란색+녹색
5th row빨간색+노란색+녹색

Common Values

ValueCountFrequency (%)
빨간색+노란색+녹색 1638
33.9%
적색+황색+녹색+청색+청녹색+보라색+백색 735
15.2%
<NA> 549
 
11.4%
모든 색상 453
 
9.4%
빨간색+노란색+녹색+흑색+흰색+청색+분홍색+하늘색 306
 
6.3%
빨간색+노란색+녹색+청색+청녹색+보라색+백색 275
 
5.7%
총천연색 222
 
4.6%
흑색+고동색+녹색+라임색+올리브색+남색+보라색+회색+은색+적색+황색+청색+분홍색+하늘색+흰색+청록색+커스텀가능 155
 
3.2%
full color 87
 
1.8%
빨간색+노란색+녹색+흑색 60
 
1.2%
Other values (25) 350
 
7.2%

Length

2024-05-11T10:17:30.697560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
빨간색+노란색+녹색 1638
30.4%
적색+황색+녹색+청색+청녹색+보라색+백색 735
13.6%
na 549
 
10.2%
모든 453
 
8.4%
색상 453
 
8.4%
빨간색+노란색+녹색+흑색+흰색+청색+분홍색+하늘색 306
 
5.7%
빨간색+노란색+녹색+청색+청녹색+보라색+백색 275
 
5.1%
총천연색 222
 
4.1%
흑색+고동색+녹색+라임색+올리브색+남색+보라색+회색+은색+적색+황색+청색+분홍색+하늘색+흰색+청록색+커스텀가능 155
 
2.9%
color 102
 
1.9%
Other values (26) 505
 
9.4%

표시유형코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
2
3890 
1
940 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 3890
80.5%
1 940
 
19.5%

Length

2024-05-11T10:17:31.327250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:17:31.605431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 3890
80.5%
1 940
 
19.5%

출력크기
Text

Distinct171
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
2024-05-11T10:17:32.194228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length5
Mean length5.0409938
Min length4

Characters and Unicode

Total characters24348
Distinct characters36
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)1.1%

Sample

1st row2단10열
2nd row2단10열
3rd row2단10열
4th row2단10열
5th row2단10열
ValueCountFrequency (%)
2단10열 1745
32.3%
3단15열 574
 
10.6%
3단13열 355
 
6.6%
2단 304
 
5.6%
2단6열 289
 
5.3%
10열 262
 
4.8%
1단10열 129
 
2.4%
1단8열 121
 
2.2%
2단12열 100
 
1.9%
4단2열 81
 
1.5%
Other values (156) 1445
26.7%
2024-05-11T10:17:33.445311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
열 4815
19.8%
단 4804
19.7%
1 4526
18.6%
2 3129
12.9%
0 2557
10.5%
3 1609
 
6.6%
5 741
 
3.0%
575
 
2.4%
6 524
 
2.2%
4 375
 
1.5%
Other values (26) 693
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14055
57.7%
Other Letter 9660
39.7%
Space Separator 576
 
2.4%
Other Punctuation 31
 
0.1%
Close Punctuation 8
 
< 0.1%
Open Punctuation 8
 
< 0.1%
Lowercase Letter 6
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
열 4815
49.8%
단 4804
49.7%
듈 8
 
0.1%
모 8
 
0.1%
딘 4
 
< 0.1%
색 3
 
< 0.1%
불 3
 
< 0.1%
가 3
 
< 0.1%
악 3
 
< 0.1%
파 3
 
< 0.1%
Other values (5) 6
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 4526
32.2%
2 3129
22.3%
0 2557
18.2%
3 1609
 
11.4%
5 741
 
5.3%
6 524
 
3.7%
4 375
 
2.7%
8 360
 
2.6%
7 140
 
1.0%
9 94
 
0.7%
Lowercase Letter
ValueCountFrequency (%)
l 2
33.3%
x 2
33.3%
f 1
16.7%
u 1
16.7%
Space Separator
ValueCountFrequency (%)
575
99.8%
　 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
* 16
51.6%
. 15
48.4%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Math Symbol
ValueCountFrequency (%)
+ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14682
60.3%
Hangul 9660
39.7%
Latin 6
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4526
30.8%
2 3129
21.3%
0 2557
17.4%
3 1609
 
11.0%
5 741
 
5.0%
575
 
3.9%
6 524
 
3.6%
4 375
 
2.6%
8 360
 
2.5%
7 140
 
1.0%
Other values (7) 146
 
1.0%
Hangul
ValueCountFrequency (%)
열 4815
49.8%
단 4804
49.7%
듈 8
 
0.1%
모 8
 
0.1%
딘 4
 
< 0.1%
색 3
 
< 0.1%
불 3
 
< 0.1%
가 3
 
< 0.1%
악 3
 
< 0.1%
파 3
 
< 0.1%
Other values (5) 6
 
0.1%
Latin
ValueCountFrequency (%)
l 2
33.3%
x 2
33.3%
f 1
16.7%
u 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14687
60.3%
Hangul 9660
39.7%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
열 4815
49.8%
단 4804
49.7%
듈 8
 
0.1%
모 8
 
0.1%
딘 4
 
< 0.1%
색 3
 
< 0.1%
불 3
 
< 0.1%
가 3
 
< 0.1%
악 3
 
< 0.1%
파 3
 
< 0.1%
Other values (5) 6
 
0.1%
ASCII
ValueCountFrequency (%)
1 4526
30.8%
2 3129
21.3%
0 2557
17.4%
3 1609
 
11.0%
5 741
 
5.0%
575
 
3.9%
6 524
 
3.6%
4 375
 
2.6%
8 360
 
2.5%
7 140
 
1.0%
Other values (10) 151
 
1.0%
None
ValueCountFrequency (%)
　 1
100.0%

제공정보종류
Categorical

Distinct18
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
01+02+03+04
2246 
01+02+03
960 
01+02
642 
1
270 
03+04
 
148
Other values (13)
564 

Length

Max length11
Median length8
Mean length8.0751553
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row01+02+03+04
2nd row01+02+03+04
3rd row01+02+03+04
4th row01+02+03+04
5th row01+02+03+04

Common Values

ValueCountFrequency (%)
01+02+03+04 2246
46.5%
01+02+03 960
19.9%
01+02 642
 
13.3%
1 270
 
5.6%
03+04 148
 
3.1%
02+04 101
 
2.1%
3 99
 
2.0%
01+04 83
 
1.7%
01+02+04 75
 
1.6%
02+03+04 58
 
1.2%
Other values (8) 148
 
3.1%

Length

2024-05-11T10:17:33.975234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
01+02+03+04 2246
46.5%
01+02+03 960
19.9%
01+02 642
 
13.3%
1 270
 
5.6%
03+04 148
 
3.1%
02+04 101
 
2.1%
3 99
 
2.0%
01+04 83
 
1.7%
01+02+04 75
 
1.6%
02+03+04 58
 
1.2%
Other values (8) 148
 
3.1%

설치연도
Real number (ℝ)

Distinct21
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2016.8099
Minimum2002
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size42.6 KiB
2024-05-11T10:17:34.402958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2002
5-th percentile2009
Q12014
median2018
Q32021
95-th percentile2022
Maximum2023
Range21
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.3482566
Coefficient of variation (CV)0.0021560071
Kurtosis-0.38348096
Mean2016.8099
Median Absolute Deviation (MAD)3
Skewness-0.65765139
Sum9741192
Variance18.907335
MonotonicityNot monotonic
2024-05-11T10:17:34.891271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
2021 621
12.9%
2022 563
11.7%
2020 521
10.8%
2017 389
8.1%
2018 373
 
7.7%
2016 369
 
7.6%
2011 288
 
6.0%
2019 279
 
5.8%
2015 260
 
5.4%
2014 234
 
4.8%
Other values (11) 933
19.3%
ValueCountFrequency (%)
2002 18
 
0.4%
2003 3
 
0.1%
2005 7
 
0.1%
2006 26
 
0.5%
2007 61
 
1.3%
2008 36
 
0.7%
2009 179
3.7%
2010 161
3.3%
2011 288
6.0%
2012 189
3.9%
ValueCountFrequency (%)
2023 74
 
1.5%
2022 563
11.7%
2021 621
12.9%
2020 521
10.8%
2019 279
5.8%
2018 373
7.7%
2017 389
8.1%
2016 369
7.6%
2015 260
5.4%
2014 234
 
4.8%

관리기관명
Text

Distinct119
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
2024-05-11T10:17:35.530551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length10.202277
Min length3

Characters and Unicode

Total characters49277
Distinct characters123
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)0.3%

Sample

1st row원주지방국토관리청
2nd row원주지방국토관리청
3rd row원주지방국토관리청
4th row원주지방국토관리청
5th row원주지방국토관리청
ValueCountFrequency (%)
한국도로공사 1421
18.6%
경기도 500
 
6.5%
대전지방국토관리청 394
 
5.2%
서울지방국토관리청 366
 
4.8%
익산지방국토관리청 341
 
4.5%
원주지방국토관리청 326
 
4.3%
수도권본부 230
 
3.0%
부산경남본부 220
 
2.9%
부산지방국토관리청 212
 
2.8%
광주전남본부 201
 
2.6%
Other values (125) 3429
44.9%
2024-05-11T10:17:36.900664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 3158
 
6.4%
국 3060
 
6.2%
2810
 
5.7%
청 2778
 
5.6%
부 1992
 
4.0%
로 1705
 
3.5%
지 1703
 
3.5%
리 1675
 
3.4%
관 1657
 
3.4%
방 1639
 
3.3%
Other values (113) 27100
55.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 46160
93.7%
Space Separator 2810
 
5.7%
Other Symbol 297
 
0.6%
Decimal Number 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 3158
 
6.8%
국 3060
 
6.6%
청 2778
 
6.0%
부 1992
 
4.3%
로 1705
 
3.7%
지 1703
 
3.7%
리 1675
 
3.6%
관 1657
 
3.6%
방 1639
 
3.6%
토 1639
 
3.6%
Other values (110) 25154
54.5%
Space Separator
ValueCountFrequency (%)
2810
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 297
100.0%
Decimal Number
ValueCountFrequency (%)
2 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 46457
94.3%
Common 2820
 
5.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 3158
 
6.8%
국 3060
 
6.6%
청 2778
 
6.0%
부 1992
 
4.3%
로 1705
 
3.7%
지 1703
 
3.7%
리 1675
 
3.6%
관 1657
 
3.6%
방 1639
 
3.5%
토 1639
 
3.5%
Other values (111) 25451
54.8%
Common
ValueCountFrequency (%)
2810
99.6%
2 10
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 46160
93.7%
ASCII 2820
 
5.7%
None 297
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 3158
 
6.8%
국 3060
 
6.6%
청 2778
 
6.0%
부 1992
 
4.3%
로 1705
 
3.7%
지 1703
 
3.7%
리 1675
 
3.6%
관 1657
 
3.6%
방 1639
 
3.6%
토 1639
 
3.6%
Other values (110) 25154
54.5%
ASCII
ValueCountFrequency (%)
2810
99.6%
2 10
 
0.4%
None
ValueCountFrequency (%)
㈜ 297
100.0%

관리기관전화번호
Text

Distinct170
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
2024-05-11T10:17:38.003890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.85528
Min length9

Characters and Unicode

Total characters57261
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

Unique22 ?
Unique (%)0.5%

Sample

1st row033-733-1333
2nd row033-733-1333
3rd row033-733-1333
4th row033-733-1333
5th row033-733-1333
ValueCountFrequency (%)
042-337-0114 394
 
8.2%
02-753-0945 366
 
7.6%
063-837-1184 341
 
7.1%
033-733-1333 326
 
6.7%
055-711-6000 229
 
4.7%
051-660-1183 212
 
4.4%
033-660-2018 110
 
2.3%
061-883-6153 106
 
2.2%
02-2084-1500 94
 
1.9%
051-600-0255 91
 
1.9%
Other values (160) 2561
53.0%
2024-05-11T10:17:39.349557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9795
17.1%
- 9512
16.6%
3 7939
13.9%
1 6298
11.0%
6 4411
7.7%
5 4070
7.1%
4 3904
 
6.8%
7 3623
 
6.3%
2 3362
 
5.9%
8 3151
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 47749
83.4%
Dash Punctuation 9512
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9795
20.5%
3 7939
16.6%
1 6298
13.2%
6 4411
9.2%
5 4070
8.5%
4 3904
 
8.2%
7 3623
 
7.6%
2 3362
 
7.0%
8 3151
 
6.6%
9 1196
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 9512
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 57261
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9795
17.1%
- 9512
16.6%
3 7939
13.9%
1 6298
11.0%
6 4411
7.7%
5 4070
7.1%
4 3904
 
6.8%
7 3623
 
6.3%
2 3362
 
5.9%
8 3151
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57261
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9795
17.1%
- 9512
16.6%
3 7939
13.9%
1 6298
11.0%
6 4411
7.7%
5 4070
7.1%
4 3904
 
6.8%
7 3623
 
6.3%
2 3362
 
5.9%
8 3151
 
5.5%

데이터기준일자
Date

Distinct73
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
Minimum2021-10-27 00:00:00
Maximum2024-04-24 00:00:00
2024-05-11T10:17:39.836496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:17:40.345115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

제공기관코드
Real number (ℝ)

Distinct87
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2570908.3
Minimum1613000
Maximum6520000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size42.6 KiB
2024-05-11T10:17:41.065536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1613000
5-th percentile1613000
Q11613000
median1613000
Q33930000
95-th percentile6265500
Maximum6520000
Range4907000
Interquartile range (IQR)2317000

Descriptive statistics

Standard deviation1556209.9
Coefficient of variation (CV)0.6053152
Kurtosis0.19872878
Mean2570908.3
Median Absolute Deviation (MAD)0
Skewness1.2862714
Sum1.2417487 × 1010
Variance2.4217892 × 1012
MonotonicityNot monotonic
2024-05-11T10:17:41.748695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1613000 3362
69.6%
6260000 91
 
1.9%
4060000 76
 
1.6%
6270000 69
 
1.4%
6500000 68
 
1.4%
3040000 63
 
1.3%
3780000 62
 
1.3%
6280000 59
 
1.2%
3940000 57
 
1.2%
4200000 55
 
1.1%
Other values (77) 868
 
18.0%
ValueCountFrequency (%)
1613000 3362
69.6%
3040000 63
 
1.3%
3310000 3
 
0.1%
3360000 8
 
0.2%
3500000 1
 
< 0.1%
3520000 3
 
0.1%
3550000 3
 
0.1%
3730000 14
 
0.3%
3740000 42
 
0.9%
3780000 62
 
1.3%
ValueCountFrequency (%)
6520000 8
 
0.2%
6500000 68
1.4%
6410000 36
 
0.7%
6300000 2
 
< 0.1%
6280000 59
1.2%
6270000 69
1.4%
6260000 91
1.9%
5700000 3
 
0.1%
5690000 28
 
0.6%
5670000 22
 
0.5%

제공기관명
Text

Distinct87
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
2024-05-11T10:17:42.433710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length5
Mean length5.7178054
Min length3

Characters and Unicode

Total characters27617
Distinct characters80
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

Unique17 ?
Unique (%)0.4%

Sample

1st row국토교통부
2nd row국토교통부
3rd row국토교통부
4th row국토교통부
5th row국토교통부
ValueCountFrequency (%)
국토교통부 3362
56.6%
경기도 562
 
9.5%
강릉시 110
 
1.9%
부산광역시 102
 
1.7%
경상남도 77
 
1.3%
강원도 77
 
1.3%
파주시 76
 
1.3%
제주특별자치도 76
 
1.3%
강원특별자치도 75
 
1.3%
대구광역시 69
 
1.2%
Other values (77) 1359
22.9%
2024-05-11T10:17:43.901536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
부 3495
12.7%
국 3362
12.2%
통 3362
12.2%
토 3362
12.2%
교 3362
12.2%
시 1361
 
4.9%
도 1133
 
4.1%
1115
 
4.0%
경 674
 
2.4%
기 562
 
2.0%
Other values (70) 5829
21.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26502
96.0%
Space Separator 1115
 
4.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 3495
13.2%
국 3362
12.7%
통 3362
12.7%
토 3362
12.7%
교 3362
12.7%
시 1361
 
5.1%
도 1133
 
4.3%
경 674
 
2.5%
기 562
 
2.1%
광 344
 
1.3%
Other values (69) 5485
20.7%
Space Separator
ValueCountFrequency (%)
1115
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26502
96.0%
Common 1115
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 3495
13.2%
국 3362
12.7%
통 3362
12.7%
토 3362
12.7%
교 3362
12.7%
시 1361
 
5.1%
도 1133
 
4.3%
경 674
 
2.5%
기 562
 
2.1%
광 344
 
1.3%
Other values (69) 5485
20.7%
Common
ValueCountFrequency (%)
1115
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26502
96.0%
ASCII 1115
 
4.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
부 3495
13.2%
국 3362
12.7%
통 3362
12.7%
토 3362
12.7%
교 3362
12.7%
시 1361
 
5.1%
도 1133
 
4.3%
경 674
 
2.5%
기 562
 
2.1%
광 344
 
1.3%
Other values (69) 5485
20.7%
ASCII
ValueCountFrequency (%)
1115
100.0%

Sample

가변전광표지판명시도명시군구명시군구코드도로종류도로노선명도로노선번호도로노선방향위도경도영상표시면가로길이영상표시면세로길이전광판함체가로길이전광판함체세로길이전광판높이설치유형코드출력방향코드발광패널유형코드표출색상표시유형코드출력크기제공정보종류설치연도관리기관명관리기관전화번호데이터기준일자제공기관코드제공기관명
0상양혈(하행)강원특별자치도양양군42830일반국도동해대로7번237.043991128.6630016000.01200.0640016006500321빨간색+노란색+녹색+청색+청녹색+보라색+백색22단10열01+02+03+042019원주지방국토관리청033-733-13332024-01-181613000국토교통부
1손양IC(상행)강원특별자치도양양군42830일반국도동해대로7번138.059924128.6437986000.01200.0640016006500321빨간색+노란색+녹색22단10열01+02+03+042014원주지방국토관리청033-733-13332024-01-181613000국토교통부
2포월리(하행)강원특별자치도양양군42830일반국도동해대로7번238.105874128.6334146000.01200.0640016006500321빨간색+노란색+녹색22단10열01+02+03+042014원주지방국토관리청033-733-13332024-01-181613000국토교통부
3조산삼거리(상행)강원특별자치도양양군42830일반국도동해대로7번138.108615128.6341976000.01200.0640016006500321빨간색+노란색+녹색22단10열01+02+03+042014원주지방국토관리청033-733-13332024-01-181613000국토교통부
4쌍천교(하행)강원특별자치도양양군42830일반국도동해대로7번238.158994128.6086316000.01200.0640016006500321빨간색+노란색+녹색22단10열01+02+03+042014원주지방국토관리청033-733-13332024-01-181613000국토교통부
5초곡리1강원특별자치도삼척시42230일반국도동해대로7번237.304232129.2890236000.01200.0640016006500321빨간색+노란색+녹색22단10열01+02+03+042016원주지방국토관리청033-733-13332024-01-181613000국토교통부
6궁촌리_강릉강원특별자치도삼척시42230일반국도동해대로7번137.324948129.2628376000.01200.0640016006500321빨간색+노란색+녹색22단10열01+02+03+042016원주지방국토관리청033-733-13332024-01-181613000국토교통부
7대구동_강릉강원특별자치도동해시42170일반국도동해대로7번137.473503129.1325266000.01200.0640016006500321빨간색+노란색+녹색22단10열01+02+03+042016원주지방국토관리청033-733-13332024-01-181613000국토교통부
8천곡동_삼척강원특별자치도동해시42170일반국도동해대로7번237.523788129.1028556000.01200.0640016006500321빨간색+노란색+녹색22단10열01+02+03+042016원주지방국토관리청033-733-13332024-01-181613000국토교통부
9효가동_강릉강원특별자치도동해시42170일반국도동해대로7번137.501779129.1107226000.01200.0640016006500321빨간색+노란색+녹색22단10열01+02+03+042016원주지방국토관리청033-733-13332024-01-181613000국토교통부
가변전광표지판명시도명시군구명시군구코드도로종류도로노선명도로노선번호도로노선방향위도경도영상표시면가로길이영상표시면세로길이전광판함체가로길이전광판함체세로길이전광판높이설치유형코드출력방향코드발광패널유형코드표출색상표시유형코드출력크기제공정보종류설치연도관리기관명관리기관전화번호데이터기준일자제공기관코드제공기관명
4820자산터널(신항방면)전라남도여수시46130시도오동도로<NA>334.740791127.7542561600.06450.060909000121<NA>14단 19열32022전라남도 여수시청061-659-41372023-10-314810000전라남도 여수시
4821죽림사거리(덕양방면)전라남도여수시46130시도화양로<NA>334.758837127.6288771600.06450.060905500121<NA>12단 10열32018전라남도 여수시청061-659-41372023-10-314810000전라남도 여수시
4822버스터미널(이마트 앞)전라남도여수시46130시도좌수영로<NA>334.758424127.7138051600.06450.060905500121<NA>12단 10열32018전라남도 여수시청061-659-41372023-10-314810000전라남도 여수시
4823한재사거리(시내방면)전라남도여수시46130시도좌수영로<NA>334.744447127.7283563500.04500.060905500121<NA>112단 16열32018전라남도 여수시청061-659-41372023-10-314810000전라남도 여수시
4824미평주공후문(만성리방면)전라남도여수시46130시도만성로<NA>334.771245127.7084151600.06400.060905500121<NA>12단 10열32018전라남도 여수시청061-659-41372023-10-314810000전라남도 여수시
4825거북선대교입구(대교삼거리)전라남도여수시46130시도돌산로<NA>334.726303127.7456733300.06400.060905500121<NA>112단 22열32017전라남도 여수시청061-659-41372023-10-314810000전라남도 여수시
4826무지개아파트건너(팔각정방면)전라남도여수시46130시도남산로<NA>334.733788127.7312341600.06400.060905500121<NA>12단 10열32017전라남도 여수시청061-659-41372023-10-314810000전라남도 여수시
4827봉산초교 아래(에스오일앞)전라남도여수시46130시도신월로<NA>334.734809127.7256961600.06400.060905500121<NA>12단 10열32017전라남도 여수시청061-659-41372023-10-314810000전라남도 여수시
4828구석기사거리 전광판경기도연천군41800일반국도전곡역로5<NA>38.022563127.067295120.03840.0<NA><NA><NA>111<NA>212단16열01+02+032020경기도 연천군청031-839-20762023-11-074140000경기도 연천군
4829연천군청 정문 전광판경기도연천군41800군도연천로5<NA>38.096518127.0741622400.0600.0<NA><NA><NA>111<NA>24단10열01+02+032012경기도 연천군청031-839-20762023-11-074140000경기도 연천군