Overview

Dataset statistics

Number of variables8
Number of observations938
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory59.7 KiB
Average record size in memory65.1 B

Variable types

Numeric1
Text3
Categorical4

Dataset

Description국토교통부_시설물안전법 대상 전국 지하차도 현황에 대한 자료(설치주소,지하차도명)로 오송지하차도 사건을 계기로 전국의 지하차도 현황을 파악할 필요가 있습니다.관리주체 및 사업주체 등이 시설물통합정보관리시스템을 통해 입력한 정보를 바탕으로 작성했습니다.
Author국토교통부
URLhttps://www.data.go.kr/data/15124755/fileData.do

Alerts

시설물구분 has constant value ""Constant
시설물종류 has constant value ""Constant
순번(No) is highly overall correlated with 종별High correlation
종별 is highly overall correlated with 순번(No)High correlation
관리주체구분 is highly imbalanced (78.0%)Imbalance
순번(No) has unique valuesUnique

Reproduction

Analysis started2024-03-14 08:46:33.110138
Analysis finished2024-03-14 08:46:34.439012
Duration1.33 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번(No)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct938
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean469.5
Minimum1
Maximum938
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.4 KiB
2024-03-14T17:46:34.615839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile47.85
Q1235.25
median469.5
Q3703.75
95-th percentile891.15
Maximum938
Range937
Interquartile range (IQR)468.5

Descriptive statistics

Standard deviation270.92158
Coefficient of variation (CV)0.57704276
Kurtosis-1.2
Mean469.5
Median Absolute Deviation (MAD)234.5
Skewness0
Sum440391
Variance73398.5
MonotonicityStrictly increasing
2024-03-14T17:46:35.050725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
631 1
 
0.1%
619 1
 
0.1%
620 1
 
0.1%
621 1
 
0.1%
622 1
 
0.1%
623 1
 
0.1%
624 1
 
0.1%
625 1
 
0.1%
626 1
 
0.1%
Other values (928) 928
98.9%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
938 1
0.1%
937 1
0.1%
936 1
0.1%
935 1
0.1%
934 1
0.1%
933 1
0.1%
932 1
0.1%
931 1
0.1%
930 1
0.1%
929 1
0.1%

시설물명
Text

Distinct914
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
2024-03-14T17:46:36.028317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length7.5063966
Min length4

Characters and Unicode

Total characters7041
Distinct characters384
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

Unique893 ?
Unique (%)95.2%

Sample

1st row원당지하차도
2nd row남태령지하차도
3rd row복합물류지하차도(군포)
4th row운양지하차도
5th row장기지하차도1
ValueCountFrequency (%)
지하차도 99
 
8.6%
지하보도 28
 
2.4%
앞 19
 
1.6%
통로box 7
 
0.6%
굴다리 4
 
0.3%
언더패스 4
 
0.3%
통로박스 3
 
0.3%
지하보차도 3
 
0.3%
중앙지하차도 3
 
0.3%
세교지하차도 3
 
0.3%
Other values (944) 980
85.0%
2024-03-14T17:46:37.239891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
하 934
 
13.3%
도 933
 
13.3%
지 926
 
13.2%
차 792
 
11.2%
215
 
3.1%
보 119
 
1.7%
) 82
 
1.2%
( 82
 
1.2%
교 75
 
1.1%
동 70
 
1.0%
Other values (374) 2813
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6448
91.6%
Space Separator 215
 
3.1%
Decimal Number 107
 
1.5%
Uppercase Letter 89
 
1.3%
Close Punctuation 82
 
1.2%
Open Punctuation 82
 
1.2%
Other Punctuation 10
 
0.1%
Dash Punctuation 7
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
하 934
 
14.5%
도 933
 
14.5%
지 926
 
14.4%
차 792
 
12.3%
보 119
 
1.8%
교 75
 
1.2%
동 70
 
1.1%
산 57
 
0.9%
로 54
 
0.8%
천 52
 
0.8%
Other values (344) 2436
37.8%
Uppercase Letter
ValueCountFrequency (%)
C 17
19.1%
I 15
16.9%
B 15
16.9%
X 10
11.2%
O 10
11.2%
R 6
 
6.7%
T 4
 
4.5%
A 4
 
4.5%
P 3
 
3.4%
M 3
 
3.4%
Other values (2) 2
 
2.2%
Decimal Number
ValueCountFrequency (%)
2 42
39.3%
1 36
33.6%
3 12
 
11.2%
4 7
 
6.5%
5 4
 
3.7%
6 4
 
3.7%
8 1
 
0.9%
7 1
 
0.9%
Other Punctuation
ValueCountFrequency (%)
# 5
50.0%
: 2
 
20.0%
, 1
 
10.0%
· 1
 
10.0%
. 1
 
10.0%
Space Separator
ValueCountFrequency (%)
215
100.0%
Close Punctuation
ValueCountFrequency (%)
) 82
100.0%
Open Punctuation
ValueCountFrequency (%)
( 82
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6448
91.6%
Common 504
 
7.2%
Latin 89
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
하 934
 
14.5%
도 933
 
14.5%
지 926
 
14.4%
차 792
 
12.3%
보 119
 
1.8%
교 75
 
1.2%
동 70
 
1.1%
산 57
 
0.9%
로 54
 
0.8%
천 52
 
0.8%
Other values (344) 2436
37.8%
Common
ValueCountFrequency (%)
215
42.7%
) 82
 
16.3%
( 82
 
16.3%
2 42
 
8.3%
1 36
 
7.1%
3 12
 
2.4%
4 7
 
1.4%
- 7
 
1.4%
# 5
 
1.0%
5 4
 
0.8%
Other values (8) 12
 
2.4%
Latin
ValueCountFrequency (%)
C 17
19.1%
I 15
16.9%
B 15
16.9%
X 10
11.2%
O 10
11.2%
R 6
 
6.7%
T 4
 
4.5%
A 4
 
4.5%
P 3
 
3.4%
M 3
 
3.4%
Other values (2) 2
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6448
91.6%
ASCII 592
 
8.4%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
하 934
 
14.5%
도 933
 
14.5%
지 926
 
14.4%
차 792
 
12.3%
보 119
 
1.8%
교 75
 
1.2%
동 70
 
1.1%
산 57
 
0.9%
로 54
 
0.8%
천 52
 
0.8%
Other values (344) 2436
37.8%
ASCII
ValueCountFrequency (%)
215
36.3%
) 82
 
13.9%
( 82
 
13.9%
2 42
 
7.1%
1 36
 
6.1%
C 17
 
2.9%
I 15
 
2.5%
B 15
 
2.5%
3 12
 
2.0%
X 10
 
1.7%
Other values (19) 66
 
11.1%
None
ValueCountFrequency (%)
· 1
100.0%

시설물구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
터널
938 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
터널 938
100.0%

Length

2024-03-14T17:46:37.644306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:46:37.930668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
터널 938
100.0%

시설물종류
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
지하차도
938 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지하차도 938
100.0%

Length

2024-03-14T17:46:38.225893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:46:38.512675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지하차도 938
100.0%

종별
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
2종
462 
3종
415 
1종
61 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1종
2nd row1종
3rd row1종
4th row1종
5th row1종

Common Values

ValueCountFrequency (%)
2종 462
49.3%
3종 415
44.2%
1종 61
 
6.5%

Length

2024-03-14T17:46:38.812212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:46:39.113526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2종 462
49.3%
3종 415
44.2%
1종 61
 
6.5%

관리주체구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
공공
905 
민간
 
33

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공 905
96.5%
민간 33
 
3.5%

Length

2024-03-14T17:46:39.442120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:46:39.729445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공 905
96.5%
민간 33
 
3.5%

항목명
Text

Distinct713
Distinct (%)76.0%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
2024-03-14T17:46:40.589283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length32
Mean length31.913646
Min length1

Characters and Unicode

Total characters29935
Distinct characters90
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

Unique590 ?
Unique (%)62.9%

Sample

1st row형식 : 박스형 / 연장 : 960.0 m, 차로수 : 4
2nd row형식 : 박스형 / 연장 : 920.0 m, 차로수 : 4
3rd row형식 : BOX+ARCH / 연장 : 840.0 m, 차로수 : 4
4th row형식 : 박스형 / 연장 : 2,722.0 m, 차로수 : 6
5th row형식 : 박스형 / 연장 : 999.0 m, 차로수 : 4
ValueCountFrequency (%)
3746
36.3%
형식 936
 
9.1%
연장 936
 
9.1%
m 936
 
9.1%
차로수 936
 
9.1%
박스형 571
 
5.5%
4 414
 
4.0%
미등록 253
 
2.5%
2 230
 
2.2%
6 115
 
1.1%
Other values (491) 1253
 
12.1%
2024-03-14T17:46:41.927674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9390
31.4%
: 2808
 
9.4%
형 1567
 
5.2%
0 1279
 
4.3%
, 973
 
3.3%
. 945
 
3.2%
차 941
 
3.1%
로 939
 
3.1%
/ 937
 
3.1%
식 936
 
3.1%
Other values (80) 9220
30.8%

Most occurring categories

ValueCountFrequency (%)
Space Separator 9390
31.4%
Other Letter 9290
31.0%
Other Punctuation 5663
18.9%
Decimal Number 4365
14.6%
Lowercase Letter 978
 
3.3%
Uppercase Letter 212
 
0.7%
Dash Punctuation 24
 
0.1%
Math Symbol 9
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
형 1567
16.9%
차 941
10.1%
로 939
10.1%
식 936
10.1%
수 936
10.1%
장 936
10.1%
연 936
10.1%
스 575
 
6.2%
박 575
 
6.2%
미 253
 
2.7%
Other values (36) 696
7.5%
Uppercase Letter
ValueCountFrequency (%)
B 33
15.6%
O 28
13.2%
X 28
13.2%
T 22
10.4%
R 17
8.0%
C 17
8.0%
U 16
7.5%
Y 14
6.6%
P 14
6.6%
E 14
6.6%
Other values (4) 9
 
4.2%
Lowercase Letter
ValueCountFrequency (%)
m 936
95.7%
e 9
 
0.9%
y 9
 
0.9%
p 9
 
0.9%
x 6
 
0.6%
o 4
 
0.4%
t 1
 
0.1%
b 1
 
0.1%
h 1
 
0.1%
r 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
0 1279
29.3%
4 677
15.5%
2 545
12.5%
1 527
12.1%
6 313
 
7.2%
5 296
 
6.8%
3 284
 
6.5%
8 190
 
4.4%
7 128
 
2.9%
9 126
 
2.9%
Other Punctuation
ValueCountFrequency (%)
: 2808
49.6%
, 973
 
17.2%
. 945
 
16.7%
/ 937
 
16.5%
Space Separator
ValueCountFrequency (%)
9390
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Math Symbol
ValueCountFrequency (%)
+ 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19455
65.0%
Hangul 9290
31.0%
Latin 1190
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
형 1567
16.9%
차 941
10.1%
로 939
10.1%
식 936
10.1%
수 936
10.1%
장 936
10.1%
연 936
10.1%
스 575
 
6.2%
박 575
 
6.2%
미 253
 
2.7%
Other values (36) 696
7.5%
Latin
ValueCountFrequency (%)
m 936
78.7%
B 33
 
2.8%
O 28
 
2.4%
X 28
 
2.4%
T 22
 
1.8%
R 17
 
1.4%
C 17
 
1.4%
U 16
 
1.3%
Y 14
 
1.2%
P 14
 
1.2%
Other values (15) 65
 
5.5%
Common
ValueCountFrequency (%)
9390
48.3%
: 2808
 
14.4%
0 1279
 
6.6%
, 973
 
5.0%
. 945
 
4.9%
/ 937
 
4.8%
4 677
 
3.5%
2 545
 
2.8%
1 527
 
2.7%
6 313
 
1.6%
Other values (9) 1061
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20645
69.0%
Hangul 9290
31.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9390
45.5%
: 2808
 
13.6%
0 1279
 
6.2%
, 973
 
4.7%
. 945
 
4.6%
/ 937
 
4.5%
m 936
 
4.5%
4 677
 
3.3%
2 545
 
2.6%
1 527
 
2.6%
Other values (34) 1628
 
7.9%
Hangul
ValueCountFrequency (%)
형 1567
16.9%
차 941
10.1%
로 939
10.1%
식 936
10.1%
수 936
10.1%
장 936
10.1%
연 936
10.1%
스 575
 
6.2%
박 575
 
6.2%
미 253
 
2.7%
Other values (36) 696
7.5%

위치
Text

Distinct143
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
2024-03-14T17:46:43.427503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.9690832
Min length7

Characters and Unicode

Total characters7475
Distinct characters109
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

Unique35 ?
Unique (%)3.7%

Sample

1st row경기도 고양시
2nd row경기도 과천시
3rd row경기도 군포시
4th row경기도 김포시
5th row경기도 김포시
ValueCountFrequency (%)
경기도 369
 
19.9%
서울특별시 197
 
10.6%
성남시 61
 
3.3%
부산광역시 49
 
2.6%
수원시 46
 
2.5%
화성시 45
 
2.4%
인천광역시 38
 
2.0%
대구광역시 36
 
1.9%
경상남도 34
 
1.8%
북구 33
 
1.8%
Other values (131) 947
51.1%
2024-03-14T17:46:45.183655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
917
 
12.3%
시 912
 
12.2%
도 521
 
7.0%
구 448
 
6.0%
경 424
 
5.7%
기 370
 
4.9%
광 269
 
3.6%
서 265
 
3.5%
울 224
 
3.0%
별 223
 
3.0%
Other values (99) 2902
38.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6558
87.7%
Space Separator 917
 
12.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 912
 
13.9%
도 521
 
7.9%
구 448
 
6.8%
경 424
 
6.5%
기 370
 
5.6%
광 269
 
4.1%
서 265
 
4.0%
울 224
 
3.4%
별 223
 
3.4%
특 223
 
3.4%
Other values (98) 2679
40.9%
Space Separator
ValueCountFrequency (%)
917
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6558
87.7%
Common 917
 
12.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 912
 
13.9%
도 521
 
7.9%
구 448
 
6.8%
경 424
 
6.5%
기 370
 
5.6%
광 269
 
4.1%
서 265
 
4.0%
울 224
 
3.4%
별 223
 
3.4%
특 223
 
3.4%
Other values (98) 2679
40.9%
Common
ValueCountFrequency (%)
917
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6558
87.7%
ASCII 917
 
12.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
917
100.0%
Hangul
ValueCountFrequency (%)
시 912
 
13.9%
도 521
 
7.9%
구 448
 
6.8%
경 424
 
6.5%
기 370
 
5.6%
광 269
 
4.1%
서 265
 
4.0%
울 224
 
3.4%
별 223
 
3.4%
특 223
 
3.4%
Other values (98) 2679
40.9%

Interactions

2024-03-14T17:46:33.743071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T17:46:45.441967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번(No)종별관리주체구분
순번(No)1.0000.9070.205
종별0.9071.0000.087
관리주체구분0.2050.0871.000
2024-03-14T17:46:45.682734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종별관리주체구분
종별1.0000.143
관리주체구분0.1431.000
2024-03-14T17:46:45.846598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번(No)종별관리주체구분
순번(No)1.0000.8610.157
종별0.8611.0000.143
관리주체구분0.1570.1431.000

Missing values

2024-03-14T17:46:34.096657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T17:46:34.348069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

순번(No)시설물명시설물구분시설물종류종별관리주체구분항목명위치
01원당지하차도터널지하차도1종공공형식 : 박스형 / 연장 : 960.0 m, 차로수 : 4경기도 고양시
12남태령지하차도터널지하차도1종공공형식 : 박스형 / 연장 : 920.0 m, 차로수 : 4경기도 과천시
23복합물류지하차도(군포)터널지하차도1종공공형식 : BOX+ARCH / 연장 : 840.0 m, 차로수 : 4경기도 군포시
34운양지하차도터널지하차도1종공공형식 : 박스형 / 연장 : 2,722.0 m, 차로수 : 6경기도 김포시
45장기지하차도1터널지하차도1종공공형식 : 박스형 / 연장 : 999.0 m, 차로수 : 4경기도 김포시
56장기지하차도2터널지하차도1종공공형식 : 박스형 / 연장 : 1,220.0 m, 차로수 : 4경기도 김포시
67송내지하차도터널지하차도1종공공형식 : 미등록 / 연장 : 715.0 m, 차로수 : 6경기도 부천시
78광장지하차도터널지하차도1종공공형식 : 박스형 / 연장 : 1,842.1 m, 차로수 : 6경기도 성남시
89백현지하차도터널지하차도1종공공형식 : 박스형 / 연장 : 898.0 m, 차로수 : 4경기도 성남시
910화랑지하차도터널지하차도1종공공형식 : 박스형 / 연장 : 1,435.0 m, 차로수 : 6경기도 성남시
순번(No)시설물명시설물구분시설물종류종별관리주체구분항목명위치
928929마송지하도(복)터널지하차도3종공공형식 : 박스형 / 연장 : 40.0 m, 차로수 : 2충청북도 음성군
929930마송지하차도터널지하차도3종공공형식 : 박스형 / 연장 : 29.0 m, 차로수 : 2충청북도 음성군
930931상노리지하도(복)터널지하차도3종공공형식 : 박스형 / 연장 : 23.6 m, 차로수 : 2충청북도 음성군
931932영천지하차도터널지하차도3종공공형식 : 박스형 / 연장 : 80.2 m, 차로수 : 4충청북도 제천시
932933궁평지하차도터널지하차도3종공공형식 : 미등록 / 연장 : 80.0 m, 차로수 : 6충청북도 청주시
933934매봉지하차도(하행)터널지하차도3종공공형식 : 미등록 / 연장 : 96.0 m, 차로수 : 2충청북도 청주시
934935묵방지하차도터널지하차도3종공공형식 : 박스형 / 연장 : 45.0 m, 차로수 : 1충청북도 청주시
935936오송지하도(복)터널지하차도3종공공형식 : 박스형 / 연장 : 28.0 m, 차로수 : 2충청북도 청주시
936937오창지하차도터널지하차도3종공공형식 : 박스형 / 연장 : 97.0 m, 차로수 : 4충청북도 청주시
937938달천지하차도터널지하차도3종공공형식 : 박스형 / 연장 : 34.0 m, 차로수 : 1충청북도 충주시