Overview

Dataset statistics

Number of variables11
Number of observations1128
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory102.6 KiB
Average record size in memory93.1 B

Variable types

Numeric4
Categorical5
Text1
Boolean1

Dataset

Description이 파일데이터는 서울특별시 동작구에 위치한 과속방지턱에 대한 위치, 시설명, 설치종류, 폭, 높이, 연장, 면적 등의 정보를 포함하고 있습니다.
Author서울특별시 동작구
URLhttps://www.data.go.kr/data/15043012/fileData.do

Alerts

시설명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연장 is highly overall correlated with 면적 and 1 other fieldsHigh correlation
면적 is highly overall correlated with 연장 and 1 other fieldsHigh correlation
보차도구분(YN) is highly overall correlated with 연장 and 1 other fieldsHigh correlation
시군구 is highly imbalanced (99.0%)Imbalance
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-13 12:40:34.760439
Analysis finished2024-04-13 12:40:42.813861
Duration8.05 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct1128
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean564.5
Minimum1
Maximum1128
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.0 KiB
2024-04-13T21:40:43.028701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile57.35
Q1282.75
median564.5
Q3846.25
95-th percentile1071.65
Maximum1128
Range1127
Interquartile range (IQR)563.5

Descriptive statistics

Standard deviation325.76986
Coefficient of variation (CV)0.57709452
Kurtosis-1.2
Mean564.5
Median Absolute Deviation (MAD)282
Skewness0
Sum636756
Variance106126
MonotonicityStrictly increasing
2024-04-13T21:40:43.613466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
751 1
 
0.1%
757 1
 
0.1%
756 1
 
0.1%
755 1
 
0.1%
754 1
 
0.1%
753 1
 
0.1%
752 1
 
0.1%
750 1
 
0.1%
759 1
 
0.1%
Other values (1118) 1118
99.1%
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 (%)
1128 1
0.1%
1127 1
0.1%
1126 1
0.1%
1125 1
0.1%
1124 1
0.1%
1123 1
0.1%
1122 1
0.1%
1121 1
0.1%
1120 1
0.1%
1119 1
0.1%

시군구
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.9 KiB
동작구
1127 
동자구
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
동작구 1127
99.9%
동자구 1
 
0.1%

Length

2024-04-13T21:40:44.014270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T21:40:44.326292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동작구 1127
99.9%
동자구 1
 
0.1%

시설명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.9 KiB
과속방지턱
1128 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
과속방지턱 1128
100.0%

Length

2024-04-13T21:40:44.641870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T21:40:44.932660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
과속방지턱 1128
100.0%

위치
Text

Distinct1077
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size8.9 KiB
2024-04-13T21:40:45.850851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length28
Mean length11.14805
Min length5

Characters and Unicode

Total characters12575
Distinct characters231
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1031 ?
Unique (%)91.4%

Sample

1st row강남초등6길 2
2nd row강남초등길 12
3rd row강남초등길 12
4th row강남초등길 14
5th row강남초등길 22
ValueCountFrequency (%)
앞 90
 
3.5%
상도로 25
 
1.0%
등용로 23
 
0.9%
만양로 22
 
0.8%
10 22
 
0.8%
13 21
 
0.8%
18 21
 
0.8%
7 21
 
0.8%
매봉로 20
 
0.8%
16 20
 
0.8%
Other values (687) 2313
89.0%
2024-04-13T21:40:47.314710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1470
 
11.7%
로 998
 
7.9%
길 957
 
7.6%
1 891
 
7.1%
2 758
 
6.0%
3 446
 
3.5%
6 367
 
2.9%
4 365
 
2.9%
0 346
 
2.8%
5 336
 
2.7%
Other values (221) 5641
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6337
50.4%
Decimal Number 4168
33.1%
Space Separator 1470
 
11.7%
Close Punctuation 190
 
1.5%
Open Punctuation 190
 
1.5%
Dash Punctuation 95
 
0.8%
Other Punctuation 84
 
0.7%
Uppercase Letter 31
 
0.2%
Lowercase Letter 10
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 998
 
15.7%
길 957
 
15.1%
대 309
 
4.9%
사 272
 
4.3%
동 235
 
3.7%
당 223
 
3.5%
도 211
 
3.3%
상 208
 
3.3%
방 181
 
2.9%
여 107
 
1.7%
Other values (194) 2636
41.6%
Decimal Number
ValueCountFrequency (%)
1 891
21.4%
2 758
18.2%
3 446
10.7%
6 367
8.8%
4 365
8.8%
0 346
 
8.3%
5 336
 
8.1%
7 263
 
6.3%
9 214
 
5.1%
8 182
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
I 8
25.8%
G 8
25.8%
L 8
25.8%
Y 3
 
9.7%
C 2
 
6.5%
N 1
 
3.2%
K 1
 
3.2%
Lowercase Letter
ValueCountFrequency (%)
a 3
30.0%
b 3
30.0%
e 2
20.0%
c 1
 
10.0%
d 1
 
10.0%
Space Separator
ValueCountFrequency (%)
1470
100.0%
Close Punctuation
ValueCountFrequency (%)
) 190
100.0%
Open Punctuation
ValueCountFrequency (%)
( 190
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 95
100.0%
Other Punctuation
ValueCountFrequency (%)
@ 84
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6337
50.4%
Common 6197
49.3%
Latin 41
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 998
 
15.7%
길 957
 
15.1%
대 309
 
4.9%
사 272
 
4.3%
동 235
 
3.7%
당 223
 
3.5%
도 211
 
3.3%
상 208
 
3.3%
방 181
 
2.9%
여 107
 
1.7%
Other values (194) 2636
41.6%
Common
ValueCountFrequency (%)
1470
23.7%
1 891
14.4%
2 758
12.2%
3 446
 
7.2%
6 367
 
5.9%
4 365
 
5.9%
0 346
 
5.6%
5 336
 
5.4%
7 263
 
4.2%
9 214
 
3.5%
Other values (5) 741
12.0%
Latin
ValueCountFrequency (%)
I 8
19.5%
G 8
19.5%
L 8
19.5%
a 3
 
7.3%
b 3
 
7.3%
Y 3
 
7.3%
e 2
 
4.9%
C 2
 
4.9%
c 1
 
2.4%
N 1
 
2.4%
Other values (2) 2
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6337
50.4%
ASCII 6238
49.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1470
23.6%
1 891
14.3%
2 758
12.2%
3 446
 
7.1%
6 367
 
5.9%
4 365
 
5.9%
0 346
 
5.5%
5 336
 
5.4%
7 263
 
4.2%
9 214
 
3.4%
Other values (17) 782
12.5%
Hangul
ValueCountFrequency (%)
로 998
 
15.7%
길 957
 
15.1%
대 309
 
4.9%
사 272
 
4.3%
동 235
 
3.7%
당 223
 
3.5%
도 211
 
3.3%
상 208
 
3.3%
방 181
 
2.9%
여 107
 
1.7%
Other values (194) 2636
41.6%

보차도구분(YN)
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
False
655 
True
473 
ValueCountFrequency (%)
False 655
58.1%
True 473
41.9%
2024-04-13T21:40:47.658222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

설치종류
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.9 KiB
원호형
986 
가상형
142 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row원호형
2nd row가상형
3rd row가상형
4th row원호형
5th row원호형

Common Values

ValueCountFrequency (%)
원호형 986
87.4%
가상형 142
 
12.6%

Length

2024-04-13T21:40:47.978972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T21:40:48.283784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
원호형 986
87.4%
가상형 142
 
12.6%

폭
Real number (ℝ)

Distinct23
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6425532
Minimum1.8
Maximum9.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.0 KiB
2024-04-13T21:40:48.582720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.8
5-th percentile3.6
Q13.6
median3.6
Q33.6
95-th percentile3.6
Maximum9.2
Range7.4
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.44147997
Coefficient of variation (CV)0.12120069
Kurtosis92.212735
Mean3.6425532
Median Absolute Deviation (MAD)0
Skewness8.8983073
Sum4108.8
Variance0.19490457
MonotonicityNot monotonic
2024-04-13T21:40:48.973964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
3.6 1057
93.7%
3.8 21
 
1.9%
3.4 15
 
1.3%
4.0 5
 
0.4%
7.0 3
 
0.3%
8.0 3
 
0.3%
3.2 3
 
0.3%
2.0 2
 
0.2%
3.9 2
 
0.2%
3.0 2
 
0.2%
Other values (13) 15
 
1.3%
ValueCountFrequency (%)
1.8 1
 
0.1%
2.0 2
 
0.2%
2.6 1
 
0.1%
2.7 1
 
0.1%
3.0 2
 
0.2%
3.2 3
 
0.3%
3.4 15
 
1.3%
3.6 1057
93.7%
3.8 21
 
1.9%
3.9 2
 
0.2%
ValueCountFrequency (%)
9.2 1
 
0.1%
9.0 1
 
0.1%
8.5 1
 
0.1%
8.0 3
0.3%
7.2 1
 
0.1%
7.0 3
0.3%
6.0 2
0.2%
5.0 1
 
0.1%
4.8 1
 
0.1%
4.7 1
 
0.1%

높이
Categorical

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size8.9 KiB
0.1
846 
<NA>
142 
0.08
111 
0.12
 
29

Length

Max length4
Median length3
Mean length3.25
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.08
2nd row<NA>
3rd row<NA>
4th row0.1
5th row0.1

Common Values

ValueCountFrequency (%)
0.1 846
75.0%
<NA> 142
 
12.6%
0.08 111
 
9.8%
0.12 29
 
2.6%

Length

2024-04-13T21:40:49.381569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T21:40:49.666598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.1 846
75.0%
na 142
 
12.6%
0.08 111
 
9.8%
0.12 29
 
2.6%

연장
Real number (ℝ)

HIGH CORRELATION 

Distinct105
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.7696543
Minimum0.7
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.0 KiB
2024-04-13T21:40:49.881243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.7
5-th percentile3
Q14.2
median5.25
Q36.8
95-th percentile9.6
Maximum21
Range20.3
Interquartile range (IQR)2.6

Descriptive statistics

Standard deviation2.2792378
Coefficient of variation (CV)0.39503888
Kurtosis5.2003185
Mean5.7696543
Median Absolute Deviation (MAD)1.25
Skewness1.7404355
Sum6508.17
Variance5.1949247
MonotonicityNot monotonic
2024-04-13T21:40:50.148471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.0 60
 
5.3%
4.0 59
 
5.2%
6.0 50
 
4.4%
4.5 41
 
3.6%
8.0 37
 
3.3%
4.6 31
 
2.7%
7.0 31
 
2.7%
6.5 30
 
2.7%
4.7 29
 
2.6%
4.8 28
 
2.5%
Other values (95) 732
64.9%
ValueCountFrequency (%)
0.7 1
 
0.1%
1.7 1
 
0.1%
2.2 1
 
0.1%
2.47 1
 
0.1%
2.5 5
 
0.4%
2.6 5
 
0.4%
2.7 9
0.8%
2.8 8
 
0.7%
2.9 6
 
0.5%
3.0 21
1.9%
ValueCountFrequency (%)
21.0 1
0.1%
19.0 1
0.1%
16.0 1
0.1%
15.9 2
0.2%
15.7 1
0.1%
15.5 2
0.2%
14.9 1
0.1%
13.9 1
0.1%
13.7 2
0.2%
13.6 1
0.1%

면적
Real number (ℝ)

HIGH CORRELATION 

Distinct169
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.935594
Minimum2.52
Maximum75.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.0 KiB
2024-04-13T21:40:50.413914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.52
5-th percentile10.8
Q115.12
median19.08
Q324.48
95-th percentile35.154
Maximum75.6
Range73.08
Interquartile range (IQR)9.36

Descriptive statistics

Standard deviation8.2639954
Coefficient of variation (CV)0.39473422
Kurtosis4.8376566
Mean20.935594
Median Absolute Deviation (MAD)4.68
Skewness1.6632857
Sum23615.35
Variance68.293619
MonotonicityNot monotonic
2024-04-13T21:40:50.671683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14.4 60
 
5.3%
18.0 58
 
5.1%
21.6 52
 
4.6%
16.2 39
 
3.5%
28.8 37
 
3.3%
25.2 31
 
2.7%
23.4 29
 
2.6%
16.92 28
 
2.5%
17.28 25
 
2.2%
28.08 23
 
2.0%
Other values (159) 746
66.1%
ValueCountFrequency (%)
2.52 1
 
0.1%
6.12 1
 
0.1%
6.4 1
 
0.1%
7.92 1
 
0.1%
8.37 1
 
0.1%
8.89 1
 
0.1%
9.0 6
0.5%
9.36 5
0.4%
9.6 1
 
0.1%
9.7 1
 
0.1%
ValueCountFrequency (%)
75.6 1
0.1%
68.4 1
0.1%
57.6 1
0.1%
57.24 2
0.2%
56.52 1
0.1%
55.8 2
0.2%
53.64 1
0.1%
50.04 1
0.1%
49.32 1
0.1%
48.96 1
0.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.9 KiB
2024-04-05
1128 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-04-05
2nd row2024-04-05
3rd row2024-04-05
4th row2024-04-05
5th row2024-04-05

Common Values

ValueCountFrequency (%)
2024-04-05 1128
100.0%

Length

2024-04-13T21:40:50.913496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T21:40:51.072436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-04-05 1128
100.0%

Interactions

2024-04-13T21:40:40.894455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:37.627840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:38.703602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:39.791703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:41.155043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:37.889447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:38.962181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:40.056697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:41.429894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:38.156711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:39.238221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:40.335468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:41.710687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:38.434275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:39.518532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:40.618622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-13T21:40:51.181114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군구보차도구분(YN)설치종류폭높이연장면적
연번1.0000.0000.3550.0980.2110.1930.2650.256
시군구0.0001.0000.0000.0000.0000.0000.0000.000
보차도구분(YN)0.3550.0001.0000.0360.0870.0200.5080.521
설치종류0.0980.0000.0361.0000.2100.0000.1810.184
폭0.2110.0000.0870.2101.0000.0760.0000.350
높이0.1930.0000.0200.0000.0761.0000.1860.170
연장0.2650.0000.5080.1810.0000.1861.0001.000
면적0.2560.0000.5210.1840.3500.1701.0001.000
2024-04-13T21:40:51.375866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구보차도구분(YN)설치종류높이
시군구1.0000.0000.0000.000
보차도구분(YN)0.0001.0000.0230.033
설치종류0.0000.0231.0000.000
높이0.0000.0330.0001.000
2024-04-13T21:40:51.543068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번폭연장면적시군구보차도구분(YN)설치종류높이
연번1.0000.1580.0280.0760.0000.2720.0750.116
폭0.1581.000-0.0480.1160.0000.0860.2090.047
연장0.028-0.0481.0000.9660.0000.5080.1800.082
면적0.0760.1160.9661.0000.0000.5210.1830.075
시군구0.0000.0000.0000.0001.0000.0000.0000.000
보차도구분(YN)0.2720.0860.5080.5210.0001.0000.0230.033
설치종류0.0750.2090.1800.1830.0000.0231.0000.000
높이0.1160.0470.0820.0750.0000.0330.0001.000

Missing values

2024-04-13T21:40:42.090701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-13T21:40:42.603743image/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

연번시군구시설명위치보차도구분(YN)설치종류폭높이연장면적데이터기준일자
01동작구과속방지턱강남초등6길 2Y원호형3.60.084.716.922024-04-05
12동작구과속방지턱강남초등길 12Y가상형3.6<NA>4.716.922024-04-05
23동작구과속방지턱강남초등길 12N가상형3.6<NA>4.014.42024-04-05
34동작구과속방지턱강남초등길 14N원호형3.60.14.616.562024-04-05
45동작구과속방지턱강남초등길 22Y원호형3.60.15.519.82024-04-05
56동작구과속방지턱강남초등길 3Y원호형3.60.14.716.922024-04-05
67동작구과속방지턱강남초등길 5Y원호형3.60.14.716.922024-04-05
78동작구과속방지턱국사봉10길 52N원호형3.60.14.014.42024-04-05
89동작구과속방지턱국사봉1길 108N원호형3.60.16.021.62024-04-05
910동작구과속방지턱국사봉1길 11N원호형3.60.16.523.42024-04-05
연번시군구시설명위치보차도구분(YN)설치종류폭높이연장면적데이터기준일자
11181119동작구과속방지턱흑석로13길7N원호형9.00.14.641.42024-04-05
11191120동작구과속방지턱동작대로29길118Y원호형8.00.13.628.82024-04-05
11201121동작구과속방지턱사당로16길15Y원호형6.00.13.621.62024-04-05
11211122동작구과속방지턱성대로37길2Y원호형6.00.13.621.62024-04-05
11221123동작구과속방지턱대방동1길(서울공고 앞)Y원호형7.20.13.625.922024-04-05
11231124동작구과속방지턱신대방1길 42N원호형4.70.13.616.922024-04-05
11241125동작구과속방지턱동작대로39가길N원호형4.50.13.616.22024-04-05
11251126동작구과속방지턱여의대방로10길Y원호형4.80.13.617.282024-04-05
11261127동작구과속방지턱만양로 84Y원호형9.20.13.633.122024-04-05
11271128동작구과속방지턱노량진로17길N원호형8.50.13.630.62024-04-05