Overview

Dataset statistics

Number of variables31
Number of observations576
Missing cells551
Missing cells (%)3.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory146.4 KiB
Average record size in memory260.2 B

Variable types

Categorical13
Text4
Numeric11
DateTime1
Boolean2

Dataset

Description도로 터널 정보 현황(제공표준)
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=L5VTWKI18DRL6JEGJNU825903239&infSeq=1

Alerts

데이터기준일자 has constant value ""Constant
터널보수보강내역 is highly imbalanced (90.2%)Imbalance
최종안전점검유형 is highly imbalanced (72.0%)Imbalance
중계기종류명 is highly imbalanced (89.4%)Imbalance
터널관리시스템적용여부 is highly imbalanced (82.6%)Imbalance
터널보수보강비용 has 551 (95.7%) missing valuesMissing
터널시작점위도 has 16 (2.8%) zerosZeros
터널시작점경도 has 16 (2.8%) zerosZeros
터널종료점위도 has 17 (3.0%) zerosZeros
터널종료점경도 has 17 (3.0%) zerosZeros
터널총폭 has 11 (1.9%) zerosZeros
터널높이 has 37 (6.4%) zerosZeros
터널보도폭 has 431 (74.8%) zerosZeros

Reproduction

Analysis started2024-05-10 21:20:23.315082
Analysis finished2024-05-10 21:20:24.616882
Duration1.3 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

Distinct43
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
화성시
51 
남양주시
45 
성남시 분당구
 
28
광명시
 
23
의정부시
 
21
Other values (38)
408 

Length

Max length8
Median length3
Mean length4.6006944
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가평군
2nd row여주시
3rd row여주시
4th row양평군
5th row이천시

Common Values

ValueCountFrequency (%)
화성시 51
 
8.9%
남양주시 45
 
7.8%
성남시 분당구 28
 
4.9%
광명시 23
 
4.0%
의정부시 21
 
3.6%
안성시 21
 
3.6%
성남시 수정구 20
 
3.5%
수원시 영통구 20
 
3.5%
용인시 기흥구 19
 
3.3%
가평군 19
 
3.3%
Other values (33) 309
53.6%

Length

2024-05-10T21:20:24.853647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
성남시 61
 
7.8%
수원시 52
 
6.6%
화성시 51
 
6.5%
남양주시 45
 
5.7%
용인시 40
 
5.1%
고양시 28
 
3.6%
분당구 28
 
3.6%
광명시 23
 
2.9%
의정부시 21
 
2.7%
안성시 21
 
2.7%
Other values (38) 417
53.0%

터널명
Text

Distinct567
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2024-05-10T21:20:25.369790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length7.515625
Min length4

Characters and Unicode

Total characters4329
Distinct characters274
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique559 ?
Unique (%)97.0%

Sample

1st row대성터널
2nd row여주터널(상)
3rd row부평터널(상)
4th row용문터널(상)
5th row오천터널(상)
ValueCountFrequency (%)
지하차도 28
 
4.5%
통로box 6
 
1.0%
세교지하차도 3
 
0.5%
통로박스 3
 
0.5%
금곡지하차도 2
 
0.3%
효원지하차도 2
 
0.3%
법원지하차도 2
 
0.3%
봉담지하차도 2
 
0.3%
제2지하차도 2
 
0.3%
능곡지하차도 2
 
0.3%
Other values (573) 576
91.7%
2024-05-10T21:20:26.379473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
하 389
 
9.0%
지 330
 
7.6%
도 327
 
7.6%
차 323
 
7.5%
) 259
 
6.0%
( 259
 
6.0%
터 247
 
5.7%
널 244
 
5.6%
상 62
 
1.4%
산 55
 
1.3%
Other values (264) 1834
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3583
82.8%
Close Punctuation 259
 
6.0%
Open Punctuation 259
 
6.0%
Decimal Number 109
 
2.5%
Uppercase Letter 58
 
1.3%
Space Separator 52
 
1.2%
Other Punctuation 7
 
0.2%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
하 389
 
10.9%
지 330
 
9.2%
도 327
 
9.1%
차 323
 
9.0%
터 247
 
6.9%
널 244
 
6.8%
상 62
 
1.7%
산 55
 
1.5%
천 50
 
1.4%
양 48
 
1.3%
Other values (240) 1508
42.1%
Uppercase Letter
ValueCountFrequency (%)
C 11
19.0%
I 10
17.2%
B 9
15.5%
O 9
15.5%
X 8
13.8%
P 3
 
5.2%
A 3
 
5.2%
R 2
 
3.4%
M 2
 
3.4%
L 1
 
1.7%
Decimal Number
ValueCountFrequency (%)
2 39
35.8%
1 38
34.9%
3 15
 
13.8%
4 6
 
5.5%
0 5
 
4.6%
5 4
 
3.7%
6 1
 
0.9%
7 1
 
0.9%
Other Punctuation
ValueCountFrequency (%)
# 5
71.4%
, 2
 
28.6%
Close Punctuation
ValueCountFrequency (%)
) 259
100.0%
Open Punctuation
ValueCountFrequency (%)
( 259
100.0%
Space Separator
ValueCountFrequency (%)
52
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3583
82.8%
Common 688
 
15.9%
Latin 58
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
하 389
 
10.9%
지 330
 
9.2%
도 327
 
9.1%
차 323
 
9.0%
터 247
 
6.9%
널 244
 
6.8%
상 62
 
1.7%
산 55
 
1.5%
천 50
 
1.4%
양 48
 
1.3%
Other values (240) 1508
42.1%
Common
ValueCountFrequency (%)
) 259
37.6%
( 259
37.6%
52
 
7.6%
2 39
 
5.7%
1 38
 
5.5%
3 15
 
2.2%
4 6
 
0.9%
0 5
 
0.7%
# 5
 
0.7%
5 4
 
0.6%
Other values (4) 6
 
0.9%
Latin
ValueCountFrequency (%)
C 11
19.0%
I 10
17.2%
B 9
15.5%
O 9
15.5%
X 8
13.8%
P 3
 
5.2%
A 3
 
5.2%
R 2
 
3.4%
M 2
 
3.4%
L 1
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3583
82.8%
ASCII 746
 
17.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
하 389
 
10.9%
지 330
 
9.2%
도 327
 
9.1%
차 323
 
9.0%
터 247
 
6.9%
널 244
 
6.8%
상 62
 
1.7%
산 55
 
1.5%
천 50
 
1.4%
양 48
 
1.3%
Other values (240) 1508
42.1%
ASCII
ValueCountFrequency (%)
) 259
34.7%
( 259
34.7%
52
 
7.0%
2 39
 
5.2%
1 38
 
5.1%
3 15
 
2.0%
C 11
 
1.5%
I 10
 
1.3%
B 9
 
1.2%
O 9
 
1.2%
Other values (14) 45
 
6.0%

터널종류명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
지하차도
336 
도로터널
240 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지하차도 336
58.3%
도로터널 240
41.7%

Length

2024-05-10T21:20:26.797335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:20:27.102280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지하차도 336
58.3%
도로터널 240
41.7%

시설물종별등급구분명
Categorical

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2
317 
1
140 
3
86 
99
33 

Length

Max length2
Median length1
Mean length1.0572917
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 317
55.0%
1 140
24.3%
3 86
 
14.9%
99 33
 
5.7%

Length

2024-05-10T21:20:27.461351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:20:27.788702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 317
55.0%
1 140
24.3%
3 86
 
14.9%
99 33
 
5.7%

도로종류명
Categorical

Distinct7
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
시도
247 
고속국도
154 
일반국도
96 
지방도
36 
국가지원지방도
32 
Other values (2)
 
11

Length

Max length7
Median length4
Mean length3.2083333
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
시도 247
42.9%
고속국도 154
26.7%
일반국도 96
 
16.7%
지방도 36
 
6.2%
국가지원지방도 32
 
5.6%
기타 9
 
1.6%
군도 2
 
0.3%

Length

2024-05-10T21:20:28.272398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:20:28.761290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시도 247
42.9%
고속국도 154
26.7%
일반국도 96
 
16.7%
지방도 36
 
6.2%
국가지원지방도 32
 
5.6%
기타 9
 
1.6%
군도 2
 
0.3%

도로노선번호정보
Categorical

Distinct48
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
-
258 
100
 
25
60
 
22
171
 
21
45
 
18
Other values (43)
232 

Length

Max length3
Median length1
Mean length1.6458333
Min length1

Unique

Unique11 ?
Unique (%)1.9%

Sample

1st row98
2nd row42
3rd row42
4th row6
5th row42

Common Values

ValueCountFrequency (%)
- 258
44.8%
100 25
 
4.3%
60 22
 
3.8%
171 21
 
3.6%
45 18
 
3.1%
50 16
 
2.8%
43 15
 
2.6%
37 14
 
2.4%
29 14
 
2.4%
3 13
 
2.3%
Other values (38) 160
27.8%

Length

2024-05-10T21:20:29.202499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
258
44.8%
100 25
 
4.3%
60 22
 
3.8%
171 21
 
3.6%
45 18
 
3.1%
50 16
 
2.8%
43 15
 
2.6%
37 14
 
2.4%
29 14
 
2.4%
3 13
 
2.3%
Other values (38) 160
27.8%

도로노선명
Text

Distinct54
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2024-05-10T21:20:29.640441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.4861111
Min length2

Characters and Unicode

Total characters3160
Distinct characters58
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 (%)1.9%

Sample

1st row국가지원지방도98호선
2nd row일반국도42호선
3rd row일반국도42호선
4th row일반국도6호선
5th row일반국도42호선
ValueCountFrequency (%)
시도 247
42.9%
서울외곽순환고속국도 25
 
4.3%
서울양양고속국도 22
 
3.8%
용인서울고속국도 21
 
3.6%
영동고속국도 16
 
2.8%
일반국도43호선 15
 
2.6%
세종포천고속국도 14
 
2.4%
중부내륙고속국도 14
 
2.4%
일반국도3호선 13
 
2.3%
일반국도6호선 12
 
2.1%
Other values (44) 177
30.7%
2024-05-10T21:20:30.317603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 586
18.5%
국 282
 
8.9%
시 254
 
8.0%
선 164
 
5.2%
호 164
 
5.2%
고 154
 
4.9%
속 154
 
4.9%
지 100
 
3.2%
3 98
 
3.1%
일 96
 
3.0%
Other values (48) 1108
35.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2817
89.1%
Decimal Number 343
 
10.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 586
20.8%
국 282
 
10.0%
시 254
 
9.0%
선 164
 
5.8%
호 164
 
5.8%
고 154
 
5.5%
속 154
 
5.5%
지 100
 
3.5%
일 96
 
3.4%
반 96
 
3.4%
Other values (38) 767
27.2%
Decimal Number
ValueCountFrequency (%)
3 98
28.6%
4 40
11.7%
2 36
 
10.5%
7 31
 
9.0%
9 30
 
8.7%
6 27
 
7.9%
8 24
 
7.0%
5 24
 
7.0%
1 21
 
6.1%
0 12
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2817
89.1%
Common 343
 
10.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 586
20.8%
국 282
 
10.0%
시 254
 
9.0%
선 164
 
5.8%
호 164
 
5.8%
고 154
 
5.5%
속 154
 
5.5%
지 100
 
3.5%
일 96
 
3.4%
반 96
 
3.4%
Other values (38) 767
27.2%
Common
ValueCountFrequency (%)
3 98
28.6%
4 40
11.7%
2 36
 
10.5%
7 31
 
9.0%
9 30
 
8.7%
6 27
 
7.9%
8 24
 
7.0%
5 24
 
7.0%
1 21
 
6.1%
0 12
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2817
89.1%
ASCII 343
 
10.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 586
20.8%
국 282
 
10.0%
시 254
 
9.0%
선 164
 
5.8%
호 164
 
5.8%
고 154
 
5.5%
속 154
 
5.5%
지 100
 
3.5%
일 96
 
3.4%
반 96
 
3.4%
Other values (38) 767
27.2%
ASCII
ValueCountFrequency (%)
3 98
28.6%
4 40
11.7%
2 36
 
10.5%
7 31
 
9.0%
9 30
 
8.7%
6 27
 
7.9%
8 24
 
7.0%
5 24
 
7.0%
1 21
 
6.1%
0 12
 
3.5%

도로노선방향구분명
Categorical

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
양방향
312 
상행
144 
하행
120 

Length

Max length3
Median length3
Mean length2.5416667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row양방향
2nd row상행
3rd row상행
4th row상행
5th row상행

Common Values

ValueCountFrequency (%)
양방향 312
54.2%
상행 144
25.0%
하행 120
 
20.8%

Length

2024-05-10T21:20:30.752627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:20:31.006833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양방향 312
54.2%
상행 144
25.0%
하행 120
 
20.8%

차로수
Real number (ℝ)

Distinct10
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2708333
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-05-10T21:20:31.485777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q12
median3
Q34
95-th percentile6
Maximum10
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4636167
Coefficient of variation (CV)0.44747518
Kurtosis0.82955489
Mean3.2708333
Median Absolute Deviation (MAD)1
Skewness0.86931079
Sum1884
Variance2.1421739
MonotonicityNot monotonic
2024-05-10T21:20:31.839849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2 221
38.4%
4 202
35.1%
3 59
 
10.2%
6 58
 
10.1%
1 24
 
4.2%
8 4
 
0.7%
5 4
 
0.7%
7 2
 
0.3%
10 1
 
0.2%
9 1
 
0.2%
ValueCountFrequency (%)
1 24
 
4.2%
2 221
38.4%
3 59
 
10.2%
4 202
35.1%
5 4
 
0.7%
6 58
 
10.1%
7 2
 
0.3%
8 4
 
0.7%
9 1
 
0.2%
10 1
 
0.2%
ValueCountFrequency (%)
10 1
 
0.2%
9 1
 
0.2%
8 4
 
0.7%
7 2
 
0.3%
6 58
 
10.1%
5 4
 
0.7%
4 202
35.1%
3 59
 
10.2%
2 221
38.4%
1 24
 
4.2%

소재지명
Text

Distinct310
Distinct (%)53.8%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2024-05-10T21:20:32.418610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length13.751736
Min length10

Characters and Unicode

Total characters7921
Distinct characters201
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

Unique155 ?
Unique (%)26.9%

Sample

1st row경기도 가평군 청평면 대성리
2nd row경기도 여주시 강천면 간매리
3rd row경기도 여주시 강천면 부평리
4th row경기도 양평군 용문면 삼성리
5th row경기도 이천시 마장면 회억리
ValueCountFrequency (%)
경기도 576
27.4%
성남시 61
 
2.9%
수원시 52
 
2.5%
화성시 51
 
2.4%
남양주시 45
 
2.1%
용인시 40
 
1.9%
고양시 28
 
1.3%
분당구 28
 
1.3%
광명시 23
 
1.1%
기흥구 23
 
1.1%
Other values (385) 1173
55.9%
2024-05-10T21:20:33.371388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1524
19.2%
기 600
 
7.6%
도 589
 
7.4%
경 576
 
7.3%
시 561
 
7.1%
동 451
 
5.7%
구 225
 
2.8%
리 162
 
2.0%
양 158
 
2.0%
성 154
 
1.9%
Other values (191) 2921
36.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6397
80.8%
Space Separator 1524
 
19.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 600
 
9.4%
도 589
 
9.2%
경 576
 
9.0%
시 561
 
8.8%
동 451
 
7.1%
구 225
 
3.5%
리 162
 
2.5%
양 158
 
2.5%
성 154
 
2.4%
남 138
 
2.2%
Other values (190) 2783
43.5%
Space Separator
ValueCountFrequency (%)
1524
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6397
80.8%
Common 1524
 
19.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 600
 
9.4%
도 589
 
9.2%
경 576
 
9.0%
시 561
 
8.8%
동 451
 
7.1%
구 225
 
3.5%
리 162
 
2.5%
양 158
 
2.5%
성 154
 
2.4%
남 138
 
2.2%
Other values (190) 2783
43.5%
Common
ValueCountFrequency (%)
1524
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6397
80.8%
ASCII 1524
 
19.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1524
100.0%
Hangul
ValueCountFrequency (%)
기 600
 
9.4%
도 589
 
9.2%
경 576
 
9.0%
시 561
 
8.8%
동 451
 
7.1%
구 225
 
3.5%
리 162
 
2.5%
양 158
 
2.5%
성 154
 
2.4%
남 138
 
2.2%
Other values (190) 2783
43.5%

터널시작점위도
Real number (ℝ)

ZEROS 

Distinct520
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.386661
Minimum0
Maximum38.043983
Zeros16
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-05-10T21:20:33.780787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile36.998064
Q137.275014
median37.397846
Q337.612423
95-th percentile37.750618
Maximum38.043983
Range38.043983
Interquartile range (IQR)0.3374095

Descriptive statistics

Standard deviation6.1593719
Coefficient of variation (CV)0.16927555
Kurtosis31.231068
Mean36.386661
Median Absolute Deviation (MAD)0.141546
Skewness-5.7514911
Sum20958.717
Variance37.937862
MonotonicityNot monotonic
2024-05-10T21:20:34.200958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 16
 
2.8%
37.397846 4
 
0.7%
37.411851 4
 
0.7%
37.275065 4
 
0.7%
37.517231 3
 
0.5%
37.334684 3
 
0.5%
37.313408 3
 
0.5%
37.242834 3
 
0.5%
37.704917 2
 
0.3%
37.457715 2
 
0.3%
Other values (510) 532
92.4%
ValueCountFrequency (%)
0.0 16
2.8%
36.963228 2
 
0.3%
36.975075 2
 
0.3%
36.97687 2
 
0.3%
36.981493 1
 
0.2%
36.981799 2
 
0.3%
36.986117 1
 
0.2%
36.992765 1
 
0.2%
36.997607 1
 
0.2%
36.997696 1
 
0.2%
ValueCountFrequency (%)
38.043983 1
0.2%
38.041073 1
0.2%
38.03039 1
0.2%
38.022334 1
0.2%
37.998317 1
0.2%
37.955643 1
0.2%
37.946027 1
0.2%
37.87598 1
0.2%
37.869174 1
0.2%
37.862403 1
0.2%

터널시작점경도
Real number (ℝ)

ZEROS 

Distinct520
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean123.54729
Minimum0
Maximum127.75558
Zeros16
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-05-10T21:20:34.635816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile126.72594
Q1126.92834
median127.06415
Q3127.16147
95-th percentile127.49105
Maximum127.75558
Range127.75558
Interquartile range (IQR)0.23313575

Descriptive statistics

Standard deviation20.902424
Coefficient of variation (CV)0.16918562
Kurtosis31.303746
Mean123.54729
Median Absolute Deviation (MAD)0.1162085
Skewness-5.7612154
Sum71163.237
Variance436.91134
MonotonicityNot monotonic
2024-05-10T21:20:35.088721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 16
 
2.8%
127.519849 4
 
0.7%
127.506053 4
 
0.7%
127.177851 4
 
0.7%
127.023694 3
 
0.5%
127.279057 3
 
0.5%
127.18073 3
 
0.5%
126.87904 3
 
0.5%
127.167944 2
 
0.3%
126.957413 2
 
0.3%
Other values (510) 532
92.4%
ValueCountFrequency (%)
0.0 16
2.8%
126.602222 1
 
0.2%
126.669503 1
 
0.2%
126.669593 1
 
0.2%
126.676611 1
 
0.2%
126.679642 1
 
0.2%
126.69218 1
 
0.2%
126.702031 1
 
0.2%
126.708065 1
 
0.2%
126.710577 1
 
0.2%
ValueCountFrequency (%)
127.755581 1
0.2%
127.752309 1
0.2%
127.73588 2
0.3%
127.732527 1
0.2%
127.73165 1
0.2%
127.723183 1
0.2%
127.677096 1
0.2%
127.574294 1
0.2%
127.56836 1
0.2%
127.56469 1
0.2%

터널종료점위도
Real number (ℝ)

ZEROS 

Distinct519
Distinct (%)90.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.321307
Minimum0
Maximum38.043597
Zeros17
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-05-10T21:20:35.462378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile36.997078
Q137.27472
median37.397525
Q337.612291
95-th percentile37.749835
Maximum38.043597
Range38.043597
Interquartile range (IQR)0.33757175

Descriptive statistics

Standard deviation6.3429613
Coefficient of variation (CV)0.17463472
Kurtosis29.106501
Mean36.321307
Median Absolute Deviation (MAD)0.141526
Skewness-5.5648475
Sum20921.073
Variance40.233158
MonotonicityNot monotonic
2024-05-10T21:20:36.001795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 17
 
3.0%
37.397846 4
 
0.7%
37.411851 4
 
0.7%
37.275065 4
 
0.7%
37.334684 3
 
0.5%
37.242834 3
 
0.5%
37.517231 3
 
0.5%
37.313408 3
 
0.5%
37.024151 2
 
0.3%
37.379185 2
 
0.3%
Other values (509) 531
92.2%
ValueCountFrequency (%)
0.0 17
3.0%
36.963228 2
 
0.3%
36.975075 2
 
0.3%
36.97687 2
 
0.3%
36.981799 2
 
0.3%
36.982063 1
 
0.2%
36.989665 1
 
0.2%
36.994586 1
 
0.2%
36.99635 1
 
0.2%
36.99732 1
 
0.2%
ValueCountFrequency (%)
38.043597 1
0.2%
38.041063 1
0.2%
38.030188 1
0.2%
38.022239 1
0.2%
38.004613 1
0.2%
37.955806 1
0.2%
37.945863 1
0.2%
37.87615 1
0.2%
37.868984 1
0.2%
37.866004 1
0.2%

터널종료점경도
Real number (ℝ)

ZEROS 

Distinct520
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean123.32721
Minimum0
Maximum127.75553
Zeros17
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-05-10T21:20:36.484041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile126.72585
Q1126.93032
median127.06473
Q3127.16142
95-th percentile127.49055
Maximum127.75553
Range127.75553
Interquartile range (IQR)0.23110125

Descriptive statistics

Standard deviation21.526514
Coefficient of variation (CV)0.17454797
Kurtosis29.170214
Mean123.32721
Median Absolute Deviation (MAD)0.1156915
Skewness-5.5736769
Sum71036.471
Variance463.3908
MonotonicityNot monotonic
2024-05-10T21:20:37.003334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 17
 
3.0%
127.519849 4
 
0.7%
127.506053 4
 
0.7%
127.177851 4
 
0.7%
127.023694 3
 
0.5%
127.279057 3
 
0.5%
127.18073 3
 
0.5%
126.87904 3
 
0.5%
127.252815 2
 
0.3%
126.957413 2
 
0.3%
Other values (510) 531
92.2%
ValueCountFrequency (%)
0.0 17
3.0%
126.603541 1
 
0.2%
126.675271 1
 
0.2%
126.679752 1
 
0.2%
126.680877 1
 
0.2%
126.686924 1
 
0.2%
126.687059 1
 
0.2%
126.693542 1
 
0.2%
126.706485 1
 
0.2%
126.708678 1
 
0.2%
ValueCountFrequency (%)
127.755529 1
0.2%
127.751995 1
0.2%
127.73588 2
0.3%
127.734228 1
0.2%
127.732674 1
0.2%
127.723158 1
0.2%
127.679993 1
0.2%
127.569985 1
0.2%
127.56977 1
0.2%
127.568299 1
0.2%

터널총길이
Real number (ℝ)

Distinct374
Distinct (%)64.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean499.94462
Minimum10
Maximum3997
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-05-10T21:20:37.465707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile37.525
Q1140
median339
Q3621.75
95-th percentile1671.25
Maximum3997
Range3987
Interquartile range (IQR)481.75

Descriptive statistics

Standard deviation567.60798
Coefficient of variation (CV)1.1353417
Kurtosis9.3958774
Mean499.94462
Median Absolute Deviation (MAD)212.6
Skewness2.6394014
Sum287968.1
Variance322178.81
MonotonicityNot monotonic
2024-05-10T21:20:38.027323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
160.0 11
 
1.9%
495.0 9
 
1.6%
140.0 9
 
1.6%
180.0 8
 
1.4%
120.0 8
 
1.4%
40.0 7
 
1.2%
100.0 7
 
1.2%
80.0 7
 
1.2%
380.0 6
 
1.0%
240.0 5
 
0.9%
Other values (364) 499
86.6%
ValueCountFrequency (%)
10.0 1
 
0.2%
11.0 2
 
0.3%
13.0 1
 
0.2%
20.0 2
 
0.3%
21.0 1
 
0.2%
25.0 3
0.5%
26.5 1
 
0.2%
27.0 1
 
0.2%
30.0 5
0.9%
31.0 2
 
0.3%
ValueCountFrequency (%)
3997.0 1
0.2%
3993.0 1
0.2%
3605.0 1
0.2%
3483.5 1
0.2%
3125.0 1
0.2%
2950.0 1
0.2%
2722.0 1
0.2%
2355.0 1
0.2%
2340.0 2
0.3%
2300.0 1
0.2%

터널총폭
Real number (ℝ)

ZEROS 

Distinct165
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.081424
Minimum0
Maximum305
Zeros11
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-05-10T21:20:38.750109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.875
Q110
median13.6
Q318.5
95-th percentile28.9
Maximum305
Range305
Interquartile range (IQR)8.5

Descriptive statistics

Standard deviation17.390964
Coefficient of variation (CV)1.0814319
Kurtosis194.76113
Mean16.081424
Median Absolute Deviation (MAD)4.05
Skewness12.66733
Sum9262.9
Variance302.44562
MonotonicityNot monotonic
2024-05-10T21:20:39.183812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.0 36
 
6.2%
7.0 21
 
3.6%
18.0 17
 
3.0%
17.6 16
 
2.8%
16.0 14
 
2.4%
19.0 13
 
2.3%
13.0 12
 
2.1%
13.6 11
 
1.9%
10.5 11
 
1.9%
0.0 11
 
1.9%
Other values (155) 414
71.9%
ValueCountFrequency (%)
0.0 11
1.9%
2.0 2
 
0.3%
3.5 4
 
0.7%
4.0 4
 
0.7%
4.5 3
 
0.5%
4.8 1
 
0.2%
5.0 1
 
0.2%
5.1 1
 
0.2%
5.3 1
 
0.2%
5.5 1
 
0.2%
ValueCountFrequency (%)
305.0 1
0.2%
256.0 1
0.2%
60.0 1
0.2%
58.0 1
0.2%
53.1 1
0.2%
43.7 1
0.2%
40.0 1
0.2%
39.0 1
0.2%
37.0 1
0.2%
36.0 1
0.2%

터널높이
Real number (ℝ)

ZEROS 

Distinct61
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.7904514
Minimum0
Maximum14.9
Zeros37
Zeros (%)6.4%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-05-10T21:20:39.621754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14.7
median5.7
Q37.3
95-th percentile8.7
Maximum14.9
Range14.9
Interquartile range (IQR)2.6

Descriptive statistics

Standard deviation2.1225733
Coefficient of variation (CV)0.36656439
Kurtosis1.8784759
Mean5.7904514
Median Absolute Deviation (MAD)1.2
Skewness-0.81227205
Sum3335.3
Variance4.5053174
MonotonicityNot monotonic
2024-05-10T21:20:40.082648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.0 66
 
11.5%
4.5 63
 
10.9%
7.3 40
 
6.9%
0.0 37
 
6.4%
6.7 33
 
5.7%
7.0 27
 
4.7%
6.6 23
 
4.0%
4.7 18
 
3.1%
8.0 18
 
3.1%
6.5 16
 
2.8%
Other values (51) 235
40.8%
ValueCountFrequency (%)
0.0 37
6.4%
2.5 1
 
0.2%
3.0 2
 
0.3%
3.2 1
 
0.2%
3.3 2
 
0.3%
3.8 2
 
0.3%
4.0 9
 
1.6%
4.1 1
 
0.2%
4.2 5
 
0.9%
4.3 4
 
0.7%
ValueCountFrequency (%)
14.9 1
 
0.2%
11.0 1
 
0.2%
10.0 4
 
0.7%
9.9 1
 
0.2%
9.4 1
 
0.2%
9.3 1
 
0.2%
9.2 1
 
0.2%
9.1 10
1.7%
9.0 6
1.0%
8.8 1
 
0.2%

터널보도폭
Real number (ℝ)

ZEROS 

Distinct61
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9251736
Minimum0
Maximum53.1
Zeros431
Zeros (%)74.8%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-05-10T21:20:40.508427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.425
95-th percentile14.625
Maximum53.1
Range53.1
Interquartile range (IQR)0.425

Descriptive statistics

Standard deviation5.3406017
Coefficient of variation (CV)2.7740883
Kurtosis22.902959
Mean1.9251736
Median Absolute Deviation (MAD)0
Skewness4.1566992
Sum1108.9
Variance28.522026
MonotonicityNot monotonic
2024-05-10T21:20:40.923650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 431
74.8%
1.0 18
 
3.1%
1.5 15
 
2.6%
2.0 11
 
1.9%
3.0 8
 
1.4%
7.6 5
 
0.9%
4.0 5
 
0.9%
6.5 4
 
0.7%
16.5 3
 
0.5%
18.0 3
 
0.5%
Other values (51) 73
 
12.7%
ValueCountFrequency (%)
0.0 431
74.8%
0.4 1
 
0.2%
0.5 1
 
0.2%
0.8 1
 
0.2%
0.9 2
 
0.3%
1.0 18
 
3.1%
1.3 1
 
0.2%
1.5 15
 
2.6%
1.7 1
 
0.2%
1.8 3
 
0.5%
ValueCountFrequency (%)
53.1 1
 
0.2%
36.0 1
 
0.2%
31.8 1
 
0.2%
25.0 3
0.5%
24.0 2
0.3%
23.0 1
 
0.2%
22.0 1
 
0.2%
20.5 1
 
0.2%
20.0 1
 
0.2%
19.0 2
0.3%

안전등급
Categorical

Distinct5
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
B
286 
A
270 
C
 
11
b
 
6
<NA>
 
3

Length

Max length4
Median length1
Mean length1.015625
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowA
2nd rowA
3rd rowA
4th rowB
5th rowA

Common Values

ValueCountFrequency (%)
B 286
49.7%
A 270
46.9%
C 11
 
1.9%
b 6
 
1.0%
<NA> 3
 
0.5%

Length

2024-05-10T21:20:41.359725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:20:41.705969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
b 292
50.7%
a 270
46.9%
c 11
 
1.9%
na 3
 
0.5%

터널보수보강내역
Categorical

IMBALANCE 

Distinct26
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
-
551 
터널 보차도 보차도 분리부 설치 H=4.0 x W=2.0/보차도 분리부 출입문 설치
 
1
포장면, BOX부 아스콘재포장 A=675㎡, 표면보수 A=613㎡, 균열보수 L=83m, 유도배수관교체 L=14m
 
1
박스구간 상부슬래브, 벽체 등 주입보수 등
 
1
포장면, BOX, 옹벽 아스콘 재포장 A=623㎡, 초속경 LMC 포장 A=874㎡, 표면보수 A=,326㎡, 선홈통 설치 L=14m 등, 포장면 소파보수 A=144.8㎡, 배수공 59m 등
 
1
Other values (21)
 
21

Length

Max length242
Median length1
Mean length3.4618056
Min length1

Unique

Unique25 ?
Unique (%)4.3%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-

Common Values

ValueCountFrequency (%)
- 551
95.7%
터널 보차도 보차도 분리부 설치 H=4.0 x W=2.0/보차도 분리부 출입문 설치 1
 
0.2%
포장면, BOX부 아스콘재포장 A=675㎡, 표면보수 A=613㎡, 균열보수 L=83m, 유도배수관교체 L=14m 1
 
0.2%
박스구간 상부슬래브, 벽체 등 주입보수 등 1
 
0.2%
포장면, BOX, 옹벽 아스콘 재포장 A=623㎡, 초속경 LMC 포장 A=874㎡, 표면보수 A=,326㎡, 선홈통 설치 L=14m 등, 포장면 소파보수 A=144.8㎡, 배수공 59m 등 1
 
0.2%
포장면, BOX 아스콘 재포장 A=6,491㎡, 표면보수 A=405㎡ 1
 
0.2%
BOX, 옹벽 타일보수 425EA, 선홈통 제작 설치 L=28m 등, 포장면 소파보수 A=103.8㎡, 배수공 68m 등 1
 
0.2%
S1 ~ S146 라이닝-표면처리 320.84m2, 주입보수 118m, 단면보수 0.54m2, /배수로청소 2일, /공동구- 주입보수 20m, 단면보수 7.2m2, 덮개재설치 1498개, 그레이팅재설치 52개/고소작업차 11일 1
 
0.2%
S1 ~ S141 라이닝-표면처리 229.46m2, 주입보수 150.5m, 단면보수 1.57m2, /배수로청소 2일, /공동구- 주입보수 1.2m, 단면보수 8.37m2, 덮개재설치 540개, 그레이팅재설치 53개, 방청처리 0.9m2, 표면처리 500m2/고소작업차 18일 1
 
0.2%
S1 ~ S214 라이닝-표면처리 287.42m2, 주입보수 151.4m, 단면보수 0.42m2, /배수로청소 4일, /공동구-덮개재설치 1442개, 그레이팅재설치 186개, 타일보수 1.17m2/고소작업차 12일 1
 
0.2%
Other values (16) 16
 
2.8%

Length

2024-05-10T21:20:42.123032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
555
67.3%
라이닝 15
 
1.8%
등 13
 
1.6%
주입보수 8
 
1.0%
균열보수 7
 
0.8%
단면보수 7
 
0.8%
및 7
 
0.8%
공동구 6
 
0.7%
설치 5
 
0.6%
포장면 5
 
0.6%
Other values (144) 197
 
23.9%

터널보수보강비용
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)92.0%
Missing551
Missing (%)95.7%
Infinite0
Infinite (%)0.0%
Mean185815.48
Minimum640
Maximum943894
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-05-10T21:20:42.483110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum640
5-th percentile7261.4
Q121000
median47848
Q3349755
95-th percentile669384.6
Maximum943894
Range943254
Interquartile range (IQR)328755

Descriptive statistics

Standard deviation250275.8
Coefficient of variation (CV)1.346905
Kurtosis2.5274299
Mean185815.48
Median Absolute Deviation (MAD)40848
Skewness1.7222443
Sum4645387
Variance6.2637978 × 1010
MonotonicityNot monotonic
2024-05-10T21:20:42.838076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
46000 2
 
0.3%
21000 2
 
0.3%
110875 1
 
0.2%
943894 1
 
0.2%
9000 1
 
0.2%
34000 1
 
0.2%
43000 1
 
0.2%
84180 1
 
0.2%
8307 1
 
0.2%
474518 1
 
0.2%
Other values (13) 13
 
2.3%
(Missing) 551
95.7%
ValueCountFrequency (%)
640 1
0.2%
7000 1
0.2%
8307 1
0.2%
9000 1
0.2%
9486 1
0.2%
21000 2
0.3%
34000 1
0.2%
37718 1
0.2%
43000 1
0.2%
46000 2
0.3%
ValueCountFrequency (%)
943894 1
0.2%
706667 1
0.2%
520255 1
0.2%
474518 1
0.2%
378055 1
0.2%
351655 1
0.2%
349755 1
0.2%
204534 1
0.2%
110875 1
0.2%
100000 1
0.2%

최종안전점검일자
Date

Distinct92
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
Minimum2019-12-31 00:00:00
Maximum2023-12-31 00:00:00
2024-05-10T21:20:43.221627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:20:43.600176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

최종안전점검유형
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
정기점검
548 
정밀점검
 
28

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정기점검 548
95.1%
정밀점검 28
 
4.9%

Length

2024-05-10T21:20:43.920534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:20:44.195411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기점검 548
95.1%
정밀점검 28
 
4.9%

내진성능확보여부
Boolean

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size708.0 B
False
504 
True
72 
ValueCountFrequency (%)
False 504
87.5%
True 72
 
12.5%
2024-05-10T21:20:44.391565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

내진설계적용여부명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
미적용
504 
적용
72 

Length

Max length3
Median length3
Mean length2.875
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미적용 504
87.5%
적용 72
 
12.5%

Length

2024-05-10T21:20:44.726632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:20:44.980567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미적용 504
87.5%
적용 72
 
12.5%

중계기종류명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
-
568 
라디오+DMB+셀룰러
 
8

Length

Max length11
Median length1
Mean length1.1388889
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-

Common Values

ValueCountFrequency (%)
- 568
98.6%
라디오+DMB+셀룰러 8
 
1.4%

Length

2024-05-10T21:20:45.274101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:20:45.568833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
568
98.6%
라디오+dmb+셀룰러 8
 
1.4%

터널관리시스템적용여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size708.0 B
False
561 
True
 
15
ValueCountFrequency (%)
False 561
97.4%
True 15
 
2.6%
2024-05-10T21:20:45.771592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

터널준공년도
Real number (ℝ)

Distinct44
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2005.6892
Minimum1970
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-05-10T21:20:46.342371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1970
5-th percentile1991
Q11999
median2008
Q32012
95-th percentile2017
Maximum2022
Range52
Interquartile range (IQR)13

Descriptive statistics

Standard deviation8.6204381
Coefficient of variation (CV)0.0042979929
Kurtosis0.56609975
Mean2005.6892
Median Absolute Deviation (MAD)5
Skewness-0.78874299
Sum1155277
Variance74.311954
MonotonicityNot monotonic
2024-05-10T21:20:46.749572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
2009 66
 
11.5%
2012 37
 
6.4%
2006 35
 
6.1%
2005 34
 
5.9%
2011 31
 
5.4%
2017 30
 
5.2%
2008 30
 
5.2%
1998 22
 
3.8%
1993 19
 
3.3%
1996 19
 
3.3%
Other values (34) 253
43.9%
ValueCountFrequency (%)
1970 1
0.2%
1975 1
0.2%
1977 1
0.2%
1978 2
0.3%
1980 1
0.2%
1981 1
0.2%
1982 1
0.2%
1983 1
0.2%
1984 2
0.3%
1985 1
0.2%
ValueCountFrequency (%)
2022 1
 
0.2%
2021 3
 
0.5%
2020 2
 
0.3%
2019 8
 
1.4%
2018 9
 
1.6%
2017 30
5.2%
2016 15
2.6%
2015 16
2.8%
2014 15
2.6%
2013 18
3.1%

관리기관명
Text

Distinct63
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2024-05-10T21:20:47.168233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length8.484375
Min length6

Characters and Unicode

Total characters4887
Distinct characters82
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)1.4%

Sample

1st row경기 북부도로과
2nd row서울청 수원사무소
3rd row서울청 수원사무소
4th row서울청 의정부사무소
5th row서울청 수원사무소
ValueCountFrequency (%)
경기 345
29.9%
한국도로공사 78
 
6.8%
본사 76
 
6.6%
서울청 69
 
6.0%
의정부사무소 47
 
4.1%
성남시 45
 
3.9%
화성시 37
 
3.2%
고양시 24
 
2.1%
수원사무소 22
 
1.9%
서울춘천고속도로㈜ 22
 
1.9%
Other values (59) 387
33.6%
2024-05-10T21:20:48.083089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
576
 
11.8%
경 392
 
8.0%
기 385
 
7.9%
시 336
 
6.9%
사 309
 
6.3%
도 181
 
3.7%
로 176
 
3.6%
서 122
 
2.5%
울 120
 
2.5%
고 102
 
2.1%
Other values (72) 2188
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4211
86.2%
Space Separator 576
 
11.8%
Other Symbol 84
 
1.7%
Uppercase Letter 12
 
0.2%
Decimal Number 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 392
 
9.3%
기 385
 
9.1%
시 336
 
8.0%
사 309
 
7.3%
도 181
 
4.3%
로 176
 
4.2%
서 122
 
2.9%
울 120
 
2.8%
고 102
 
2.4%
부 100
 
2.4%
Other values (66) 1988
47.2%
Uppercase Letter
ValueCountFrequency (%)
H 6
50.0%
L 6
50.0%
Decimal Number
ValueCountFrequency (%)
3 2
50.0%
2 2
50.0%
Space Separator
ValueCountFrequency (%)
576
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 84
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4295
87.9%
Common 580
 
11.9%
Latin 12
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 392
 
9.1%
기 385
 
9.0%
시 336
 
7.8%
사 309
 
7.2%
도 181
 
4.2%
로 176
 
4.1%
서 122
 
2.8%
울 120
 
2.8%
고 102
 
2.4%
부 100
 
2.3%
Other values (67) 2072
48.2%
Common
ValueCountFrequency (%)
576
99.3%
3 2
 
0.3%
2 2
 
0.3%
Latin
ValueCountFrequency (%)
H 6
50.0%
L 6
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4211
86.2%
ASCII 592
 
12.1%
None 84
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
576
97.3%
H 6
 
1.0%
L 6
 
1.0%
3 2
 
0.3%
2 2
 
0.3%
Hangul
ValueCountFrequency (%)
경 392
 
9.3%
기 385
 
9.1%
시 336
 
8.0%
사 309
 
7.3%
도 181
 
4.3%
로 176
 
4.2%
서 122
 
2.9%
울 120
 
2.8%
고 102
 
2.4%
부 100
 
2.4%
Other values (66) 1988
47.2%
None
ValueCountFrequency (%)
㈜ 84
100.0%

관리기관전화번호
Categorical

Distinct42
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
000-0000-0000
152 
031-820-1761
47 
031-729-4935
45 
031-5189-2466
37 
031-8075-2863
 
24
Other values (37)
271 

Length

Max length13
Median length12
Mean length12.387153
Min length9

Unique

Unique5 ?
Unique (%)0.9%

Sample

1st row031-8008-8322
2nd row031-218-1777
3rd row031-218-1777
4th row031-820-1761
5th row031-218-1777

Common Values

ValueCountFrequency (%)
000-0000-0000 152
26.4%
031-820-1761 47
 
8.2%
031-729-4935 45
 
7.8%
031-5189-2466 37
 
6.4%
031-8075-2863 24
 
4.2%
031-218-1777 22
 
3.8%
02-2680-2934 20
 
3.5%
031-324-6406 19
 
3.3%
031-228-6445 17
 
3.0%
1877-1925 14
 
2.4%
Other values (32) 179
31.1%

Length

2024-05-10T21:20:48.600454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
000-0000-0000 152
26.4%
031-820-1761 47
 
8.2%
031-729-4935 45
 
7.8%
031-5189-2466 37
 
6.4%
031-8075-2863 24
 
4.2%
031-218-1777 22
 
3.8%
02-2680-2934 20
 
3.5%
031-324-6406 19
 
3.3%
031-228-6445 17
 
3.0%
1877-1925 14
 
2.4%
Other values (32) 179
31.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
0000-12-31
576 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0000-12-31
2nd row0000-12-31
3rd row0000-12-31
4th row0000-12-31
5th row0000-12-31

Common Values

ValueCountFrequency (%)
0000-12-31 576
100.0%

Length

2024-05-10T21:20:49.100074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:20:49.403147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0000-12-31 576
100.0%

Sample

시군명터널명터널종류명시설물종별등급구분명도로종류명도로노선번호정보도로노선명도로노선방향구분명차로수소재지명터널시작점위도터널시작점경도터널종료점위도터널종료점경도터널총길이터널총폭터널높이터널보도폭안전등급터널보수보강내역터널보수보강비용최종안전점검일자최종안전점검유형내진성능확보여부내진설계적용여부명중계기종류명터널관리시스템적용여부터널준공년도관리기관명관리기관전화번호데이터기준일자
0가평군대성터널도로터널2국가지원지방도98국가지원지방도98호선양방향2경기도 가평군 청평면 대성리37.695891127.37727437.694885127.371885500.09.77.00.0A-<NA>2023-12-07정기점검N미적용-N2005경기 북부도로과031-8008-83220000-12-31
1여주시여주터널(상)도로터널2일반국도42일반국도42호선상행2경기도 여주시 강천면 간매리37.272237127.72318337.272507127.732674750.010.06.70.0A-<NA>2023-11-30정기점검N미적용-N1999서울청 수원사무소031-218-17770000-12-31
2여주시부평터널(상)도로터널2일반국도42일반국도42호선상행2경기도 여주시 강천면 부평리37.27486127.75230937.278011127.755529478.010.08.00.0A-<NA>2023-11-30정기점검N미적용-N1999서울청 수원사무소031-218-17770000-12-31
3양평군용문터널(상)도로터널2일반국도6일반국도6호선상행2경기도 양평군 용문면 삼성리37.483754127.5646937.48402127.568299345.09.86.62.8B-<NA>2023-12-31정기점검N미적용-N1999서울청 의정부사무소031-820-17610000-12-31
4이천시오천터널(상)도로터널2일반국도42일반국도42호선상행2경기도 이천시 마장면 회억리37.254554127.3669937.254584127.371899457.010.06.71.0A-<NA>2023-11-30정기점검N미적용-N2004서울청 수원사무소031-218-17770000-12-31
5안성시만세터널(상)도로터널1일반국도45일반국도45호선상행2경기도 안성시 원곡면 칠곡리37.056592127.16637637.066943127.1765421461.08.07.01.0A-<NA>2023-11-30정기점검Y적용-N2005서울청 수원사무소031-218-17770000-12-31
6안성시양성터널(상)도로터널2일반국도45일반국도45호선상행2경기도 안성시 양성면 동항리37.06839127.1811737.069679127.186706481.08.07.71.0A-<NA>2023-11-30정기점검Y적용-N2005서울청 수원사무소031-218-17770000-12-31
7남양주시마석터널(상)도로터널1일반국도46일반국도46호선상행2경기도 남양주시 호평동37.654456127.26316237.648738127.2761871320.08.67.00.0B-<NA>2023-12-31정기점검Y적용-N2005서울청 의정부사무소031-820-17610000-12-31
8남양주시모란터널(상)도로터널1일반국도46일반국도46호선상행2경기도 남양주시 화도읍 창현리37.64157127.31090337.646619127.3281191610.08.67.00.0B-<NA>2023-12-31정기점검N미적용-N2005서울청 의정부사무소031-820-17610000-12-31
9포천시일동터널(상)도로터널1일반국도37일반국도37호선상행2경기도 포천시 일동면 길명리37.946027127.27532537.955806127.2637161477.010.57.01.5B-<NA>2023-12-31정기점검N미적용-N2006서울청 의정부사무소031-820-17610000-12-31
시군명터널명터널종류명시설물종별등급구분명도로종류명도로노선번호정보도로노선명도로노선방향구분명차로수소재지명터널시작점위도터널시작점경도터널종료점위도터널종료점경도터널총길이터널총폭터널높이터널보도폭안전등급터널보수보강내역터널보수보강비용최종안전점검일자최종안전점검유형내진성능확보여부내진설계적용여부명중계기종류명터널관리시스템적용여부터널준공년도관리기관명관리기관전화번호데이터기준일자
566시흥시능곡지하차도지하차도99시도-시도양방향4경기도 시흥시 능곡동37.374818126.81222837.375615126.81184270.024.04.54.0B-<NA>2023-12-31정기점검N미적용-N2008경기 시흥시031-310-24380000-12-31
567과천시옥탑지하차도지하차도2기타-기타양방향7경기도 과천시 갈현동37.407497126.98664737.406889126.98571106.033.09.94.0A-<NA>2023-12-20정기점검N미적용-N2017국토교통부 LH공사000-0000-00000000-12-31
568화성시장지교차로지하차도지하차도2국가지원지방도23국가지원지방도23호선양방향4경기도 화성시 장지동37.15429127.11870437.152375127.123328160.018.05.00.0A-<NA>2023-06-30정기점검N미적용-N2017경기 화성시031-5189-24660000-12-31
569의정부시경민지하차도B지하차도2시도-시도양방향4경기도 의정부시 가능동37.744054127.0251837.744867127.025705150.016.84.80.0A-<NA>2023-11-15정기점검N미적용-N2005경기 의정부시031-828-86320000-12-31
570구리시구리터널(포천)도로터널1고속국도29세종포천고속국도상행3경기도 구리시 교문동37.578722127.12965237.604821127.11513605.014.914.91.0A-<NA>2023-11-30정기점검Y적용라디오+DMB+셀룰러Y2017서울북부고속도로㈜ 본사1877-19250000-12-31
571의정부시축석령터널(포천)도로터널1고속국도29세종포천고속국도상행3경기도 의정부시 자일동37.771619127.11994337.776023127.121495.014.97.81.0A-<NA>2023-11-30정기점검Y적용라디오+DMB+셀룰러Y2017서울북부고속도로㈜ 본사1877-19250000-12-31
572구리시구리터널(구리)도로터널1고속국도29세종포천고속국도하행3경기도 구리시 교문동37.588664127.11488837.588439127.1150123483.514.97.81.0A-<NA>2023-11-30정기점검Y적용라디오+DMB+셀룰러Y2017서울북부고속도로㈜ 본사1877-19250000-12-31
573포천시축석령터널(구리)도로터널1고속국도29세종포천고속국도하행3경기도 포천시 소흘읍 이동교리37.776285127.12056937.771953127.119518495.014.97.81.0A-<NA>2023-11-30정기점검Y적용라디오+DMB+셀룰러Y2017서울북부고속도로㈜ 본사1877-19250000-12-31
574포천시석문령터널(양주)도로터널1고속국도29세종포천고속국도상행2경기도 포천시 소흘읍 송우리37.826626127.12927237.832157127.1121521675.018.47.10.0A-<NA>2023-11-30정기점검Y적용라디오+DMB+셀룰러Y2017서울북부고속도로㈜ 본사1877-19250000-12-31
575양주시석문령터널(서울)도로터널1고속국도29세종포천고속국도하행2경기도 양주시 율정동37.831887127.11176537.826347127.1292041670.018.47.10.0A-<NA>2023-11-30정기점검Y적용라디오+DMB+셀룰러Y2017서울북부고속도로㈜ 본사1877-19250000-12-31