Overview

Dataset statistics

Number of variables19
Number of observations1617
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory251.2 KiB
Average record size in memory159.1 B

Variable types

Categorical10
Numeric5
Text4

Dataset

Description경기도 화성시_과속방지턱에 대한 데이터로 지형지물부호, 관리번호, 행정읍면동, 도엽번호, 관리기관, 설치일자, 폭원, 연장, 대장초기화, 방지턱높이, 일교통량, 수급자, 도색상태, 표지판설치유무, 비고, 도로구간번호, 공사번호, 납품업체, 로딩일자 등의 항목을 제공합니다.
Author경기도 화성시
URLhttps://www.data.go.kr/data/15093478/fileData.do

Alerts

대장초기화여부 has constant value ""Constant
일교통량 has constant value ""Constant
수급자 is highly overall correlated with 관리기관High correlation
도색상태 is highly overall correlated with 지형지물부호 and 1 other fieldsHigh correlation
관리기관 is highly overall correlated with 도로구간번호 and 4 other fieldsHigh correlation
행정읍면동 is highly overall correlated with 관리기관High correlation
공사번호 is highly overall correlated with 관리기관High correlation
표지판설치유무 is highly overall correlated with 지형지물부호 and 1 other fieldsHigh correlation
지형지물부호 is highly overall correlated with 관리기관 and 2 other fieldsHigh correlation
관리번호 is highly overall correlated with 폭원 and 2 other fieldsHigh correlation
폭원 is highly overall correlated with 관리번호High correlation
도로구간번호 is highly overall correlated with 관리번호 and 2 other fieldsHigh correlation
납품업체 is highly overall correlated with 관리번호 and 1 other fieldsHigh correlation
지형지물부호 is highly imbalanced (98.6%)Imbalance
관리기관 is highly imbalanced (77.2%)Imbalance
수급자 is highly imbalanced (92.6%)Imbalance
도색상태 is highly imbalanced (57.6%)Imbalance
공사번호 is highly imbalanced (99.3%)Imbalance
납품업체 is highly imbalanced (59.6%)Imbalance
폭원 has 33 (2.0%) zerosZeros
연장 has 33 (2.0%) zerosZeros
방지턱높이 has 338 (20.9%) zerosZeros

Reproduction

Analysis started2023-12-12 20:51:13.032693
Analysis finished2023-12-12 20:51:17.711632
Duration4.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지형지물부호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.8 KiB
과속방지턱
1615 
횡단보도
 
2

Length

Max length5
Median length5
Mean length4.9987631
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
과속방지턱 1615
99.9%
횡단보도 2
 
0.1%

Length

2023-12-13T05:51:17.789988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:51:17.896227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
과속방지턱 1615
99.9%
횡단보도 2
 
0.1%

관리번호
Real number (ℝ)

HIGH CORRELATION 

Distinct1614
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.02022 × 1013
Minimum100002
Maximum8.9991907 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.3 KiB
2023-12-13T05:51:18.016068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100002
5-th percentile100085.8
Q1402031
median2.116214 × 1011
Q31.2161911 × 1013
95-th percentile8.9991901 × 1013
Maximum8.9991907 × 1013
Range8.9991907 × 1013
Interquartile range (IQR)1.2161911 × 1013

Descriptive statistics

Standard deviation3.5333159 × 1013
Coefficient of variation (CV)1.7489758
Kurtosis-0.041951672
Mean2.02022 × 1013
Median Absolute Deviation (MAD)2.116213 × 1011
Skewness1.360938
Sum3.2666958 × 1016
Variance1.2484321 × 1027
MonotonicityNot monotonic
2023-12-13T05:51:18.227784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12161904010002 2
 
0.1%
12161904010001 2
 
0.1%
12161904010003 2
 
0.1%
402024 1
 
0.1%
500097 1
 
0.1%
215302905003 1
 
0.1%
215302905028 1
 
0.1%
215302905027 1
 
0.1%
206307080014 1
 
0.1%
206307290013 1
 
0.1%
Other values (1604) 1604
99.2%
ValueCountFrequency (%)
100002 1
0.1%
100003 1
0.1%
100004 1
0.1%
100005 1
0.1%
100006 1
0.1%
100007 1
0.1%
100008 1
0.1%
100009 1
0.1%
100010 1
0.1%
100011 1
0.1%
ValueCountFrequency (%)
89991907270001 1
0.1%
89991907240071 1
0.1%
89991907240070 1
0.1%
89991907240069 1
0.1%
89991907240068 1
0.1%
89991907240067 1
0.1%
89991907240066 1
0.1%
89991907240065 1
0.1%
89991907240064 1
0.1%
89991907240063 1
0.1%

행정읍면동
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size12.8 KiB
<NA>
335 
향남읍
177 
봉담읍
162 
남양읍
106 
반월동
 
71
Other values (20)
766 

Length

Max length4
Median length3
Mean length3.3636364
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row병점2동
2nd row봉담읍
3rd row정남면
4th row기배동
5th row정남면

Common Values

ValueCountFrequency (%)
<NA> 335
20.7%
향남읍 177
 
10.9%
봉담읍 162
 
10.0%
남양읍 106
 
6.6%
반월동 71
 
4.4%
기배동 70
 
4.3%
정남면 63
 
3.9%
진안동 63
 
3.9%
송산면 57
 
3.5%
동탄5동 55
 
3.4%
Other values (15) 458
28.3%

Length

2023-12-13T05:51:18.397631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 335
20.7%
향남읍 177
 
10.9%
봉담읍 162
 
10.0%
남양읍 106
 
6.6%
반월동 71
 
4.4%
기배동 70
 
4.3%
정남면 63
 
3.9%
진안동 63
 
3.9%
송산면 57
 
3.5%
동탄5동 55
 
3.4%
Other values (15) 458
28.3%

도엽번호
Text

Distinct739
Distinct (%)45.7%
Missing0
Missing (%)0.0%
Memory size12.8 KiB
2023-12-13T05:51:18.723211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters16170
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique350 ?
Unique (%)21.6%

Sample

1st row377130179B
2nd row376160523C
3rd row377130693C
4th row376160545B
5th row376161067B
ValueCountFrequency (%)
376161901a 13
 
0.8%
377130708d 12
 
0.7%
376161725d 11
 
0.7%
376160706d 10
 
0.6%
376161431d 10
 
0.6%
377130232d 10
 
0.6%
376161464a 10
 
0.6%
376150577a 9
 
0.6%
376160557a 9
 
0.6%
377130780d 9
 
0.6%
Other values (729) 1514
93.6%
2023-12-13T05:51:19.166329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 2819
17.4%
3 2744
17.0%
1 2451
15.2%
6 2164
13.4%
0 1537
9.5%
5 739
 
4.6%
2 682
 
4.2%
8 559
 
3.5%
4 502
 
3.1%
D 444
 
2.7%
Other values (4) 1529
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14553
90.0%
Uppercase Letter 1617
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 2819
19.4%
3 2744
18.9%
1 2451
16.8%
6 2164
14.9%
0 1537
10.6%
5 739
 
5.1%
2 682
 
4.7%
8 559
 
3.8%
4 502
 
3.4%
9 356
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
D 444
27.5%
C 433
26.8%
A 396
24.5%
B 344
21.3%

Most occurring scripts

ValueCountFrequency (%)
Common 14553
90.0%
Latin 1617
 
10.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 2819
19.4%
3 2744
18.9%
1 2451
16.8%
6 2164
14.9%
0 1537
10.6%
5 739
 
5.1%
2 682
 
4.7%
8 559
 
3.8%
4 502
 
3.4%
9 356
 
2.4%
Latin
ValueCountFrequency (%)
D 444
27.5%
C 433
26.8%
A 396
24.5%
B 344
21.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16170
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 2819
17.4%
3 2744
17.0%
1 2451
15.2%
6 2164
13.4%
0 1537
9.5%
5 739
 
4.6%
2 682
 
4.2%
8 559
 
3.5%
4 502
 
3.1%
D 444
 
2.7%
Other values (4) 1529
9.5%

관리기관
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size12.8 KiB
<NA>
1508 
도로과
 
108
화성시
 
1

Length

Max length4
Median length4
Mean length3.9325912
Min length3

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1508
93.3%
도로과 108
 
6.7%
화성시 1
 
0.1%

Length

2023-12-13T05:51:19.325710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:51:19.428782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1508
93.3%
도로과 108
 
6.7%
화성시 1
 
0.1%

설치일자
Text

Distinct57
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size12.8 KiB
2023-12-13T05:51:19.613324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.3432282
Min length1

Characters and Unicode

Total characters15108
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)0.4%

Sample

1st row2006-06-20
2nd row2012-06-01
3rd row1900-01-01
4th row1900-01-01
5th row1900-01-01
ValueCountFrequency (%)
1900-01-01 521
34.8%
2016-01-01 249
16.6%
2014-01-01 76
 
5.1%
2017-01-01 70
 
4.7%
2006-05-01 67
 
4.5%
2010-01-01 41
 
2.7%
2006-06-20 39
 
2.6%
2011-06-01 38
 
2.5%
2020-01-01 36
 
2.4%
2017-12-01 28
 
1.9%
Other values (46) 334
22.3%
2023-12-13T05:51:19.941079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5087
33.7%
1 3985
26.4%
- 2998
19.8%
2 1184
 
7.8%
9 611
 
4.0%
6 524
 
3.5%
7 187
 
1.2%
4 146
 
1.0%
118
 
0.8%
5 110
 
0.7%
Other values (2) 158
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11992
79.4%
Dash Punctuation 2998
 
19.8%
Space Separator 118
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5087
42.4%
1 3985
33.2%
2 1184
 
9.9%
9 611
 
5.1%
6 524
 
4.4%
7 187
 
1.6%
4 146
 
1.2%
5 110
 
0.9%
3 108
 
0.9%
8 50
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 2998
100.0%
Space Separator
ValueCountFrequency (%)
118
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15108
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5087
33.7%
1 3985
26.4%
- 2998
19.8%
2 1184
 
7.8%
9 611
 
4.0%
6 524
 
3.5%
7 187
 
1.2%
4 146
 
1.0%
118
 
0.8%
5 110
 
0.7%
Other values (2) 158
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15108
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5087
33.7%
1 3985
26.4%
- 2998
19.8%
2 1184
 
7.8%
9 611
 
4.0%
6 524
 
3.5%
7 187
 
1.2%
4 146
 
1.0%
118
 
0.8%
5 110
 
0.7%
Other values (2) 158
 
1.0%

폭원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct523
Distinct (%)32.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.1298887
Minimum0
Maximum46.12
Zeros33
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size14.3 KiB
2023-12-13T05:51:20.121134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.3
Q13.5
median5.65
Q38.21
95-th percentile13.468
Maximum46.12
Range46.12
Interquartile range (IQR)4.71

Descriptive statistics

Standard deviation4.1775824
Coefficient of variation (CV)0.68151032
Kurtosis8.7817758
Mean6.1298887
Median Absolute Deviation (MAD)2.33
Skewness2.0326758
Sum9912.03
Variance17.452195
MonotonicityNot monotonic
2023-12-13T05:51:20.282037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.5 90
 
5.6%
3.0 83
 
5.1%
4.0 68
 
4.2%
3.6 52
 
3.2%
3.7 41
 
2.5%
0.0 33
 
2.0%
2.0 25
 
1.5%
3.8 25
 
1.5%
6.0 25
 
1.5%
10.0 24
 
1.5%
Other values (513) 1151
71.2%
ValueCountFrequency (%)
0.0 33
2.0%
0.5 3
 
0.2%
0.6 5
 
0.3%
0.7 1
 
0.1%
0.8 11
 
0.7%
0.9 5
 
0.3%
1.0 7
 
0.4%
1.1 4
 
0.2%
1.2 6
 
0.4%
1.3 12
 
0.7%
ValueCountFrequency (%)
46.12 1
 
0.1%
30.0 1
 
0.1%
26.19 1
 
0.1%
25.0 8
0.5%
24.0 1
 
0.1%
23.0 5
0.3%
21.98 1
 
0.1%
21.71 1
 
0.1%
21.0 1
 
0.1%
20.96 2
 
0.1%

연장
Real number (ℝ)

ZEROS 

Distinct360
Distinct (%)22.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.2019542
Minimum0
Maximum39.93
Zeros33
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size14.3 KiB
2023-12-13T05:51:20.433821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.9
Q13.6
median4.6
Q37.66
95-th percentile16
Maximum39.93
Range39.93
Interquartile range (IQR)4.06

Descriptive statistics

Standard deviation4.4509849
Coefficient of variation (CV)0.71767458
Kurtosis9.1776022
Mean6.2019542
Median Absolute Deviation (MAD)1.3
Skewness2.5731727
Sum10028.56
Variance19.811266
MonotonicityNot monotonic
2023-12-13T05:51:20.579384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.6 126
 
7.8%
6.0 63
 
3.9%
3.61 41
 
2.5%
10.0 39
 
2.4%
3.5 36
 
2.2%
3.58 34
 
2.1%
3.62 34
 
2.1%
0.0 33
 
2.0%
6.5 31
 
1.9%
4.0 29
 
1.8%
Other values (350) 1151
71.2%
ValueCountFrequency (%)
0.0 33
2.0%
0.7 1
 
0.1%
0.8 1
 
0.1%
0.9 1
 
0.1%
1.0 1
 
0.1%
1.2 1
 
0.1%
1.5 1
 
0.1%
1.6 1
 
0.1%
1.8 1
 
0.1%
1.94 1
 
0.1%
ValueCountFrequency (%)
39.93 1
0.1%
37.19 1
0.1%
31.45 1
0.1%
31.09 1
0.1%
30.84 1
0.1%
30.2 1
0.1%
28.26 1
0.1%
28.0 1
0.1%
27.52 1
0.1%
25.0 2
0.1%

대장초기화여부
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.8 KiB
1
1617 

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 1617
100.0%

Length

2023-12-13T05:51:20.736435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:51:20.823238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1617
100.0%

방지턱높이
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.10628324
Minimum0
Maximum1.5
Zeros338
Zeros (%)20.9%
Negative0
Negative (%)0.0%
Memory size14.3 KiB
2023-12-13T05:51:20.905055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.08
median0.1
Q30.15
95-th percentile0.18
Maximum1.5
Range1.5
Interquartile range (IQR)0.07

Descriptive statistics

Standard deviation0.12290412
Coefficient of variation (CV)1.1563829
Kurtosis40.382123
Mean0.10628324
Median Absolute Deviation (MAD)0.02
Skewness5.4387711
Sum171.86
Variance0.015105422
MonotonicityNot monotonic
2023-12-13T05:51:21.007529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0.1 689
42.6%
0.0 338
20.9%
0.15 282
17.4%
0.08 166
 
10.3%
0.18 65
 
4.0%
0.2 38
 
2.4%
0.8 25
 
1.5%
1.0 4
 
0.2%
0.25 4
 
0.2%
0.01 3
 
0.2%
Other values (2) 3
 
0.2%
ValueCountFrequency (%)
0.0 338
20.9%
0.01 3
 
0.2%
0.05 1
 
0.1%
0.08 166
 
10.3%
0.1 689
42.6%
0.15 282
17.4%
0.18 65
 
4.0%
0.2 38
 
2.4%
0.25 4
 
0.2%
0.8 25
 
1.5%
ValueCountFrequency (%)
1.5 2
 
0.1%
1.0 4
 
0.2%
0.8 25
 
1.5%
0.25 4
 
0.2%
0.2 38
 
2.4%
0.18 65
 
4.0%
0.15 282
17.4%
0.1 689
42.6%
0.08 166
 
10.3%
0.05 1
 
0.1%

일교통량
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.8 KiB
0
1617 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1617
100.0%

Length

2023-12-13T05:51:21.118913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:51:21.211383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1617
100.0%

수급자
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct10
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size12.8 KiB
1573 
사설
 
21
일반
 
7
석우초교
 
6
송리초교
 
3
Other values (5)
 
7

Length

Max length4
Median length1
Mean length1.0463822
Min length1

Unique

Unique3 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
1573
97.3%
사설 21
 
1.3%
일반 7
 
0.4%
석우초교 6
 
0.4%
송리초교 3
 
0.2%
학동초교 2
 
0.1%
능리초교 2
 
0.1%
화성시 1
 
0.1%
솔빛초교 1
 
0.1%
반석초교 1
 
0.1%

Length

2023-12-13T05:51:21.315850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:51:21.458082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사설 21
47.7%
일반 7
 
15.9%
석우초교 6
 
13.6%
송리초교 3
 
6.8%
학동초교 2
 
4.5%
능리초교 2
 
4.5%
화성시 1
 
2.3%
솔빛초교 1
 
2.3%
반석초교 1
 
2.3%

도색상태
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size12.8 KiB
양호
1323 
도색무
212 
불량
 
80
미분류
 
2

Length

Max length3
Median length2
Mean length2.1323438
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row양호
2nd row양호
3rd row양호
4th row도색무
5th row양호

Common Values

ValueCountFrequency (%)
양호 1323
81.8%
도색무 212
 
13.1%
불량 80
 
4.9%
미분류 2
 
0.1%

Length

2023-12-13T05:51:21.589794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:51:21.691831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양호 1323
81.8%
도색무 212
 
13.1%
불량 80
 
4.9%
미분류 2
 
0.1%

표지판설치유무
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size12.8 KiB
미설치
989 
설치
626 
미분류
 
2

Length

Max length3
Median length3
Mean length2.6128633
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row설치
2nd row설치
3rd row설치
4th row미설치
5th row미설치

Common Values

ValueCountFrequency (%)
미설치 989
61.2%
설치 626
38.7%
미분류 2
 
0.1%

Length

2023-12-13T05:51:21.818368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:51:21.929094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미설치 989
61.2%
설치 626
38.7%
미분류 2
 
0.1%

비고
Text

Distinct251
Distinct (%)15.5%
Missing0
Missing (%)0.0%
Memory size12.8 KiB
2023-12-13T05:51:22.139699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length1
Mean length11.732839
Min length1

Characters and Unicode

Total characters18972
Distinct characters177
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

Unique194 ?
Unique (%)12.0%

Sample

1st row
2nd row봉담읍 수영리 교차로 개선사업 GIS DB구축
3rd row31103001
4th row
5th row
ValueCountFrequency (%)
gis 348
 
10.8%
db 223
 
6.9%
구축용역 159
 
4.9%
db구축용역 127
 
3.9%
구축 121
 
3.8%
동탄(2)택지개발사업 118
 
3.7%
부지공사(1단계)gis 118
 
3.7%
및 117
 
3.6%
도로 113
 
3.5%
지하시설물 99
 
3.1%
Other values (338) 1679
52.1%
2023-12-13T05:51:22.504798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3335
 
17.6%
0 604
 
3.2%
사 575
 
3.0%
구 562
 
3.0%
축 508
 
2.7%
I 504
 
2.7%
S 500
 
2.6%
G 500
 
2.6%
1 490
 
2.6%
2 472
 
2.5%
Other values (167) 10922
57.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9880
52.1%
Space Separator 3335
 
17.6%
Uppercase Letter 2301
 
12.1%
Decimal Number 2285
 
12.0%
Close Punctuation 417
 
2.2%
Open Punctuation 417
 
2.2%
Other Punctuation 196
 
1.0%
Dash Punctuation 100
 
0.5%
Lowercase Letter 26
 
0.1%
Connector Punctuation 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 575
 
5.8%
구 562
 
5.7%
축 508
 
5.1%
도 447
 
4.5%
지 431
 
4.4%
역 401
 
4.1%
용 400
 
4.0%
공 384
 
3.9%
로 351
 
3.6%
설 290
 
2.9%
Other values (140) 5531
56.0%
Decimal Number
ValueCountFrequency (%)
0 604
26.4%
1 490
21.4%
2 472
20.7%
3 276
12.1%
7 90
 
3.9%
5 85
 
3.7%
8 83
 
3.6%
6 67
 
2.9%
9 65
 
2.8%
4 53
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
I 504
21.9%
S 500
21.7%
G 500
21.7%
B 396
17.2%
D 396
17.2%
C 4
 
0.2%
H 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 138
70.4%
. 39
 
19.9%
, 19
 
9.7%
Space Separator
ValueCountFrequency (%)
3335
100.0%
Close Punctuation
ValueCountFrequency (%)
) 417
100.0%
Open Punctuation
ValueCountFrequency (%)
( 417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 100
100.0%
Lowercase Letter
ValueCountFrequency (%)
x 26
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9880
52.1%
Common 6765
35.7%
Latin 2327
 
12.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 575
 
5.8%
구 562
 
5.7%
축 508
 
5.1%
도 447
 
4.5%
지 431
 
4.4%
역 401
 
4.1%
용 400
 
4.0%
공 384
 
3.9%
로 351
 
3.6%
설 290
 
2.9%
Other values (140) 5531
56.0%
Common
ValueCountFrequency (%)
3335
49.3%
0 604
 
8.9%
1 490
 
7.2%
2 472
 
7.0%
) 417
 
6.2%
( 417
 
6.2%
3 276
 
4.1%
/ 138
 
2.0%
- 100
 
1.5%
7 90
 
1.3%
Other values (9) 426
 
6.3%
Latin
ValueCountFrequency (%)
I 504
21.7%
S 500
21.5%
G 500
21.5%
B 396
17.0%
D 396
17.0%
x 26
 
1.1%
C 4
 
0.2%
H 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9880
52.1%
ASCII 9092
47.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3335
36.7%
0 604
 
6.6%
I 504
 
5.5%
S 500
 
5.5%
G 500
 
5.5%
1 490
 
5.4%
2 472
 
5.2%
) 417
 
4.6%
( 417
 
4.6%
B 396
 
4.4%
Other values (17) 1457
16.0%
Hangul
ValueCountFrequency (%)
사 575
 
5.8%
구 562
 
5.7%
축 508
 
5.1%
도 447
 
4.5%
지 431
 
4.4%
역 401
 
4.1%
용 400
 
4.0%
공 384
 
3.9%
로 351
 
3.6%
설 290
 
2.9%
Other values (140) 5531
56.0%

도로구간번호
Real number (ℝ)

HIGH CORRELATION 

Distinct1144
Distinct (%)70.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0183937 × 1013
Minimum6.1300058 × 108
Maximum8.9991907 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.3 KiB
2023-12-13T05:51:22.690776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.1300058 × 108
5-th percentile6.1481028 × 108
Q12.707931 × 109
median9.020419 × 109
Q31.2161911 × 1013
95-th percentile8.9991901 × 1013
Maximum8.9991907 × 1013
Range8.9991294 × 1013
Interquartile range (IQR)1.2159203 × 1013

Descriptive statistics

Standard deviation3.5481178 × 1013
Coefficient of variation (CV)1.7578919
Kurtosis-0.073963826
Mean2.0183937 × 1013
Median Absolute Deviation (MAD)8.4074184 × 109
Skewness1.348908
Sum3.2637425 × 1016
Variance1.258914 × 1027
MonotonicityNot monotonic
2023-12-13T05:51:22.841753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21162129001 20
 
1.2%
12161512310002 15
 
0.9%
89991901300261 8
 
0.5%
89991907240028 7
 
0.4%
2705419001 7
 
0.4%
89991907240010 7
 
0.4%
89991901300154 6
 
0.4%
89991901300224 6
 
0.4%
9002931005 6
 
0.4%
89991907240017 6
 
0.4%
Other values (1134) 1529
94.6%
ValueCountFrequency (%)
613000575 1
0.1%
613000579 1
0.1%
613000581 1
0.1%
613000582 1
0.1%
613000587 1
0.1%
613000596 1
0.1%
613000598 1
0.1%
613000628 1
0.1%
613900620 1
0.1%
613900625 1
0.1%
ValueCountFrequency (%)
89991907240159 1
 
0.1%
89991907240158 1
 
0.1%
89991907240155 1
 
0.1%
89991907240154 4
0.2%
89991907240153 1
 
0.1%
89991907240152 1
 
0.1%
89991907240150 1
 
0.1%
89991907240149 2
0.1%
89991907240142 1
 
0.1%
89991907240125 1
 
0.1%

공사번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.8 KiB
1616 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1616
99.9%
1 1
 
0.1%

Length

2023-12-13T05:51:22.970172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:51:23.068654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1
100.0%

납품업체
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct15
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size12.8 KiB
1219 
새한항업
 
101
㈜한양지에스티
 
70
㈜진성이엔씨
 
68
(주)지아이에스21
 
30
Other values (10)
129 

Length

Max length10
Median length1
Mean length2.3382808
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1219
75.4%
새한항업 101
 
6.2%
㈜한양지에스티 70
 
4.3%
㈜진성이엔씨 68
 
4.2%
(주)지아이에스21 30
 
1.9%
(주)진성이엔씨 27
 
1.7%
㈜선진이엔씨 26
 
1.6%
(주)성원공간정보 22
 
1.4%
(주)한라지리정보 19
 
1.2%
㈜대광지오텍 10
 
0.6%
Other values (5) 25
 
1.5%

Length

2023-12-13T05:51:23.177705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
새한항업 101
25.4%
㈜한양지에스티 70
17.6%
㈜진성이엔씨 68
17.1%
주)지아이에스21 30
 
7.5%
주)진성이엔씨 27
 
6.8%
㈜선진이엔씨 26
 
6.5%
주)성원공간정보 22
 
5.5%
주)한라지리정보 19
 
4.8%
㈜대광지오텍 10
 
2.5%
주)선진이엔씨 7
 
1.8%
Other values (4) 18
 
4.5%

로딩일자
Text

Distinct52
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size12.8 KiB
2023-12-13T05:51:23.369736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length1
Mean length4.0612245
Min length1

Characters and Unicode

Total characters6567
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)0.7%

Sample

1st row
2nd row
3rd row
4th row
5th row
ValueCountFrequency (%)
2019-12-04 118
21.5%
2020-05-20 77
14.0%
2019-01-05 75
13.6%
2021-03-23 30
 
5.5%
2019-04-05 26
 
4.7%
2021-04-16 19
 
3.5%
2018-04-12 15
 
2.7%
2018-09-17 15
 
2.7%
2020-03-13 13
 
2.4%
2017-12-20 12
 
2.2%
Other values (41) 150
27.3%
2023-12-13T05:51:23.696066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1461
22.2%
- 1100
16.8%
2 1087
16.6%
1067
16.2%
1 810
12.3%
9 268
 
4.1%
5 210
 
3.2%
4 204
 
3.1%
8 149
 
2.3%
3 115
 
1.8%
Other values (2) 96
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4400
67.0%
Dash Punctuation 1100
 
16.8%
Space Separator 1067
 
16.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1461
33.2%
2 1087
24.7%
1 810
18.4%
9 268
 
6.1%
5 210
 
4.8%
4 204
 
4.6%
8 149
 
3.4%
3 115
 
2.6%
7 61
 
1.4%
6 35
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 1100
100.0%
Space Separator
ValueCountFrequency (%)
1067
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6567
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1461
22.2%
- 1100
16.8%
2 1087
16.6%
1067
16.2%
1 810
12.3%
9 268
 
4.1%
5 210
 
3.2%
4 204
 
3.1%
8 149
 
2.3%
3 115
 
1.8%
Other values (2) 96
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6567
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1461
22.2%
- 1100
16.8%
2 1087
16.6%
1067
16.2%
1 810
12.3%
9 268
 
4.1%
5 210
 
3.2%
4 204
 
3.1%
8 149
 
2.3%
3 115
 
1.8%
Other values (2) 96
 
1.5%

Interactions

2023-12-13T05:51:16.405763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:14.418772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:14.951683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:15.394315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:15.874059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:16.495543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:14.516496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:15.031202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:15.475688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:15.985000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:16.596795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:14.605837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:15.119961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:15.553248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:16.089143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:16.712884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:14.707132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:15.213261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:15.656426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:16.200076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:17.139110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:14.832396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:15.305270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:15.778874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:16.300254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:51:23.811472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지형지물부호관리번호행정읍면동관리기관설치일자폭원연장방지턱높이수급자도색상태표지판설치유무도로구간번호공사번호납품업체로딩일자
지형지물부호1.0000.0000.217NaN0.0000.0000.0000.0000.0001.0001.0000.3300.0000.2850.686
관리번호0.0001.0000.7350.1090.9640.3910.3400.2730.0000.1510.4221.0000.0000.9920.979
행정읍면동0.2170.7351.0001.0000.9540.5200.4980.6920.6400.5920.5330.7380.0760.8060.871
관리기관NaN0.1091.0001.0001.0000.0000.1290.000NaN0.0000.0001.000NaN0.1271.000
설치일자0.0000.9640.9541.0001.0000.7510.5990.7090.6460.5170.5250.9611.0000.9790.992
폭원0.0000.3910.5200.0000.7511.0000.6040.3100.4740.3270.1430.3890.0000.4140.540
연장0.0000.3400.4980.1290.5990.6041.0000.3550.3380.2250.2740.3390.0000.2900.315
방지턱높이0.0000.2730.6920.0000.7090.3100.3551.0000.0000.1710.1110.2760.0000.4480.489
수급자0.0000.0000.640NaN0.6460.4740.3380.0001.0000.0000.1330.0000.0000.0000.000
도색상태1.0000.1510.5920.0000.5170.3270.2250.1710.0001.0000.7050.2560.0000.4040.652
표지판설치유무1.0000.4220.5330.0000.5250.1430.2740.1110.1330.7051.0000.5310.0000.5070.708
도로구간번호0.3301.0000.7381.0000.9610.3890.3390.2760.0000.2560.5311.0000.0000.9910.980
공사번호0.0000.0000.076NaN1.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.000
납품업체0.2850.9920.8060.1270.9790.4140.2900.4480.0000.4040.5070.9910.0001.0000.996
로딩일자0.6860.9790.8711.0000.9920.5400.3150.4890.0000.6520.7080.9800.0000.9961.000
2023-12-13T05:51:24.314999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수급자도색상태관리기관행정읍면동공사번호납품업체표지판설치유무지형지물부호
수급자1.0000.0001.0000.2810.0000.0000.0790.000
도색상태0.0001.0000.0000.3160.0000.2390.7430.999
관리기관1.0000.0001.0000.9621.0000.0870.0001.000
행정읍면동0.2810.3160.9621.0000.0590.3670.2900.170
공사번호0.0000.0001.0000.0591.0000.0000.0000.000
납품업체0.0000.2390.0870.3670.0001.0000.2680.259
표지판설치유무0.0790.7430.0000.2900.0000.2681.0001.000
지형지물부호0.0000.9991.0000.1700.0000.2591.0001.000
2023-12-13T05:51:24.443432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호폭원연장방지턱높이도로구간번호지형지물부호행정읍면동관리기관수급자도색상태표지판설치유무공사번호납품업체
관리번호1.0000.601-0.0970.1680.7210.0000.4610.1300.0000.0970.1920.0000.936
폭원0.6011.0000.1250.2190.3140.0000.2510.0000.2490.1510.0910.0000.191
연장-0.0970.1251.0000.352-0.2450.0000.2120.2110.1600.1450.1250.0000.122
방지턱높이0.1680.2190.3521.000-0.0110.0000.4190.0000.0000.2380.1370.0000.152
도로구간번호0.7210.314-0.245-0.0111.0000.2370.4640.9810.0000.1670.2570.0000.934
지형지물부호0.0000.0000.0000.0000.2371.0000.1701.0000.0000.9991.0000.0000.259
행정읍면동0.4610.2510.2120.4190.4640.1701.0000.9620.2810.3160.2900.0590.367
관리기관0.1300.0000.2110.0000.9811.0000.9621.0001.0000.0000.0001.0000.087
수급자0.0000.2490.1600.0000.0000.0000.2811.0001.0000.0000.0790.0000.000
도색상태0.0970.1510.1450.2380.1670.9990.3160.0000.0001.0000.7430.0000.239
표지판설치유무0.1920.0910.1250.1370.2571.0000.2900.0000.0790.7431.0000.0000.268
공사번호0.0000.0000.0000.0000.0000.0000.0591.0000.0000.0000.0001.0000.000
납품업체0.9360.1910.1220.1520.9340.2590.3670.0870.0000.2390.2680.0001.000

Missing values

2023-12-13T05:51:17.292633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:51:17.602484image/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

지형지물부호관리번호행정읍면동도엽번호관리기관설치일자폭원연장대장초기화여부방지턱높이일교통량수급자도색상태표지판설치유무비고도로구간번호공사번호납품업체로딩일자
0과속방지턱402024병점2동377130179B<NA>2006-06-203.66.610.10양호설치9004544085
1과속방지턱211605230004봉담읍376160523C<NA>2012-06-013.23.610.00양호설치봉담읍 수영리 교차로 개선사업 GIS DB구축21160523027
2과속방지턱500164정남면377130693C<NA>1900-01-013.76.510.00양호설치311030013220631107
3과속방지턱100031기배동376160545B<NA>1900-01-013.63.610.10도색무미설치9008021002
4과속방지턱100239정남면376161067B<NA>1900-01-013.04.510.10양호미설치9006511002
5과속방지턱411009동탄3동377130262C<NA>2006-05-013.79.610.10양호미설치무/양호2700619003
6과속방지턱100005봉담읍376160511D<NA>1900-01-011.34.410.00양호미설치3110121013
7과속방지턱888614810067향남읍376161481A<NA>2016-01-016.393.610.10양호설치614810266
8과속방지턱200035양감면376161939B<NA>1900-01-013.85.610.00양호미설치1104312003
9과속방지턱100254봉담읍376160974D<NA>1900-01-012.65.210.10불량미설치9002911004
지형지물부호관리번호행정읍면동도엽번호관리기관설치일자폭원연장대장초기화여부방지턱높이일교통량수급자도색상태표지판설치유무비고도로구간번호공사번호납품업체로딩일자
1607과속방지턱82112004010005<NA>376122279D<NA>2020-01-0110.83.510.10양호설치82112004010401(주)지아이에스212021-03-23
1608과속방지턱82112004010006<NA>376122257D<NA>2020-01-016.79.110.150양호설치82112004010367(주)지아이에스212021-03-23
1609과속방지턱82112004010007<NA>376122256D<NA>2020-01-016.13.610.00양호미설치82112004010355(주)지아이에스212021-03-23
1610과속방지턱82112004010008<NA>376122247D<NA>2020-01-016.79.210.150양호설치82112004010382(주)지아이에스212021-03-23
1611과속방지턱82112004010009<NA>376122245D<NA>2020-01-0110.08.610.150양호미설치82112004010299(주)지아이에스212021-03-23
1612과속방지턱82112004010010<NA>376122245D<NA>2020-01-0110.08.610.150양호미설치82112004010301(주)지아이에스212021-03-23
1613과속방지턱82112004010011<NA>376122244D<NA>2020-01-0110.08.110.150양호미설치82112004010290(주)지아이에스212021-03-23
1614과속방지턱82112004010012<NA>376122244D<NA>2020-01-0110.08.210.150양호미설치82112004010293(주)지아이에스212021-03-23
1615과속방지턱82112004010013<NA>376122222D<NA>2020-01-016.03.610.00양호미설치82112004010270(주)지아이에스212021-03-23
1616과속방지턱82112004010014<NA>376122222D<NA>2020-01-0110.03.610.00양호미설치82112004010272(주)지아이에스212021-03-23