Overview

Dataset statistics

Number of variables33
Number of observations813
Missing cells2104
Missing cells (%)7.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory220.8 KiB
Average record size in memory278.2 B

Variable types

Text2
Categorical23
Numeric7
Boolean1

Dataset

Description보행자 전용 도로 현황(제공표준)
Author남양주시
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=TQMX82C749EXZS09KJ9F25885168&infSeq=1

Alerts

시도명 has constant value ""Constant
관리점검결과 has constant value ""Constant
지정일자 is highly imbalanced (92.3%)Imbalance
운영방식구분 is highly imbalanced (97.5%)Imbalance
평일운영시작시각 is highly imbalanced (95.7%)Imbalance
평일운영종료시각 is highly imbalanced (79.0%)Imbalance
주말운영시작시각 is highly imbalanced (95.0%)Imbalance
주말운영종료시각 is highly imbalanced (79.4%)Imbalance
자전거보행자겸용도로구분 is highly imbalanced (85.2%)Imbalance
보차분리여부 is highly imbalanced (54.1%)Imbalance
지정목적 is highly imbalanced (87.5%)Imbalance
관리점검일자 is highly imbalanced (54.5%)Imbalance
유지보수내용 is highly imbalanced (93.1%)Imbalance
영상정보기처리기기설치개수 is highly imbalanced (85.9%)Imbalance
횡단보도설치개수 is highly imbalanced (85.9%)Imbalance
방호울타리설치개수 is highly imbalanced (88.4%)Imbalance
속도저감시설설치개수 is highly imbalanced (78.4%)Imbalance
교통표지판설치개수 is highly imbalanced (78.4%)Imbalance
이정표설치개수 is highly imbalanced (85.6%)Imbalance
점자블럭설치개수 is highly imbalanced (87.8%)Imbalance
보차분리여부 has 534 (65.7%) missing valuesMissing
보안등설치개수 has 782 (96.2%) missing valuesMissing
차량진입억제용말뚝설치개수 has 784 (96.4%) missing valuesMissing
보안등설치개수 has 15 (1.8%) zerosZeros
차량진입억제용말뚝설치개수 has 23 (2.8%) zerosZeros

Reproduction

Analysis started2024-04-11 03:00:30.232084
Analysis finished2024-04-11 03:00:31.101547
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

보행자전용도로명
Text

Distinct764
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2024-04-11T12:00:31.311741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length31
Mean length10.084871
Min length2

Characters and Unicode

Total characters8199
Distinct characters126
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique759 ?
Unique (%)93.4%

Sample

1st row고등동 소로1
2nd row고등동 소로2
3rd row고등동 소로11
4th row고등동 소로10
5th row고등동 소로9
ValueCountFrequency (%)
소로 255
 
13.7%
비전동 71
 
3.8%
용이동 65
 
3.5%
운중동 64
 
3.4%
판교동 53
 
2.8%
없음 46
 
2.5%
구미동 45
 
2.4%
동삭동 37
 
2.0%
창곡동 34
 
1.8%
죽백동 28
 
1.5%
Other values (480) 1165
62.5%
2024-04-11T12:00:31.771764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1050
 
12.8%
로 880
 
10.7%
소 743
 
9.1%
동 685
 
8.4%
3 487
 
5.9%
- 382
 
4.7%
1 358
 
4.4%
2 302
 
3.7%
4 193
 
2.4%
6 175
 
2.1%
Other values (116) 2944
35.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4501
54.9%
Decimal Number 2148
26.2%
Space Separator 1050
 
12.8%
Dash Punctuation 382
 
4.7%
Open Punctuation 59
 
0.7%
Close Punctuation 59
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 880
19.6%
소 743
16.5%
동 685
15.2%
자 112
 
2.5%
도 89
 
2.0%
전 71
 
1.6%
비 71
 
1.6%
이 71
 
1.6%
산 71
 
1.6%
운 70
 
1.6%
Other values (102) 1638
36.4%
Decimal Number
ValueCountFrequency (%)
3 487
22.7%
1 358
16.7%
2 302
14.1%
4 193
 
9.0%
6 175
 
8.1%
5 161
 
7.5%
7 133
 
6.2%
8 121
 
5.6%
9 110
 
5.1%
0 108
 
5.0%
Space Separator
ValueCountFrequency (%)
1050
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 382
100.0%
Open Punctuation
ValueCountFrequency (%)
( 59
100.0%
Close Punctuation
ValueCountFrequency (%)
) 59
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4501
54.9%
Common 3698
45.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 880
19.6%
소 743
16.5%
동 685
15.2%
자 112
 
2.5%
도 89
 
2.0%
전 71
 
1.6%
비 71
 
1.6%
이 71
 
1.6%
산 71
 
1.6%
운 70
 
1.6%
Other values (102) 1638
36.4%
Common
ValueCountFrequency (%)
1050
28.4%
3 487
13.2%
- 382
 
10.3%
1 358
 
9.7%
2 302
 
8.2%
4 193
 
5.2%
6 175
 
4.7%
5 161
 
4.4%
7 133
 
3.6%
8 121
 
3.3%
Other values (4) 336
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4501
54.9%
ASCII 3698
45.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1050
28.4%
3 487
13.2%
- 382
 
10.3%
1 358
 
9.7%
2 302
 
8.2%
4 193
 
5.2%
6 175
 
4.7%
5 161
 
4.4%
7 133
 
3.6%
8 121
 
3.3%
Other values (4) 336
 
9.1%
Hangul
ValueCountFrequency (%)
로 880
19.6%
소 743
16.5%
동 685
15.2%
자 112
 
2.5%
도 89
 
2.0%
전 71
 
1.6%
비 71
 
1.6%
이 71
 
1.6%
산 71
 
1.6%
운 70
 
1.6%
Other values (102) 1638
36.4%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
경기도
813 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 813
100.0%

Length

2024-04-11T12:00:31.903022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-11T12:00:31.991143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 813
100.0%

시군구명
Categorical

Distinct11
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
성남시
418 
평택시
246 
오산시
59 
하남시
46 
파주시
 
17
Other values (6)
 
27

Length

Max length7
Median length3
Mean length3.0381304
Min length3

Unique

Unique3 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
성남시 418
51.4%
평택시 246
30.3%
오산시 59
 
7.3%
하남시 46
 
5.7%
파주시 17
 
2.1%
양주시 10
 
1.2%
남양주시 10
 
1.2%
수원시 팔달구 4
 
0.5%
안성시 1
 
0.1%
수원시 영통구 1
 
0.1%

Length

2024-04-11T12:00:32.112909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
성남시 418
51.1%
평택시 246
30.1%
오산시 59
 
7.2%
하남시 46
 
5.6%
파주시 17
 
2.1%
양주시 10
 
1.2%
남양주시 10
 
1.2%
수원시 5
 
0.6%
팔달구 4
 
0.5%
안성시 1
 
0.1%
Other values (2) 2
 
0.2%

법정동명
Text

Distinct80
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2024-04-11T12:00:32.295837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.2349323
Min length2

Characters and Unicode

Total characters2630
Distinct characters94
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)3.7%

Sample

1st row고등동
2nd row고등동
3rd row고등동
4th row고등동
5th row고등동
ValueCountFrequency (%)
비전동 71
 
8.5%
용이동 65
 
7.8%
운중동 64
 
7.7%
판교동 53
 
6.4%
구미동 45
 
5.4%
동삭동 37
 
4.4%
창곡동 34
 
4.1%
덕풍동 31
 
3.7%
죽백동 28
 
3.4%
삼평동 28
 
3.4%
Other values (73) 377
45.3%
2024-04-11T12:00:32.607429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 830
31.6%
전 72
 
2.7%
비 71
 
2.7%
교 71
 
2.7%
이 71
 
2.7%
정 66
 
2.5%
운 66
 
2.5%
용 65
 
2.5%
중 64
 
2.4%
백 54
 
2.1%
Other values (84) 1200
45.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2497
94.9%
Decimal Number 113
 
4.3%
Space Separator 20
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 830
33.2%
전 72
 
2.9%
비 71
 
2.8%
교 71
 
2.8%
이 71
 
2.8%
정 66
 
2.6%
운 66
 
2.6%
용 65
 
2.6%
중 64
 
2.6%
백 54
 
2.2%
Other values (80) 1067
42.7%
Decimal Number
ValueCountFrequency (%)
3 46
40.7%
1 39
34.5%
2 28
24.8%
Space Separator
ValueCountFrequency (%)
20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2497
94.9%
Common 133
 
5.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 830
33.2%
전 72
 
2.9%
비 71
 
2.8%
교 71
 
2.8%
이 71
 
2.8%
정 66
 
2.6%
운 66
 
2.6%
용 65
 
2.6%
중 64
 
2.6%
백 54
 
2.2%
Other values (80) 1067
42.7%
Common
ValueCountFrequency (%)
3 46
34.6%
1 39
29.3%
2 28
21.1%
20
15.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2497
94.9%
ASCII 133
 
5.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 830
33.2%
전 72
 
2.9%
비 71
 
2.8%
교 71
 
2.8%
이 71
 
2.8%
정 66
 
2.6%
운 66
 
2.6%
용 65
 
2.6%
중 64
 
2.6%
백 54
 
2.2%
Other values (80) 1067
42.7%
ASCII
ValueCountFrequency (%)
3 46
34.6%
1 39
29.3%
2 28
21.1%
20
15.0%

지정일자
Categorical

IMBALANCE 

Distinct8
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
792 
2006-12-13
 
10
2005-11-10
 
3
2014-04-02
 
2
2013-01-03
 
2
Other values (3)
 
4

Length

Max length10
Median length4
Mean length4.1549815
Min length4

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 792
97.4%
2006-12-13 10
 
1.2%
2005-11-10 3
 
0.4%
2014-04-02 2
 
0.2%
2013-01-03 2
 
0.2%
2003-10-06 2
 
0.2%
2005-08-04 1
 
0.1%
2013-12-31 1
 
0.1%

Length

2024-04-11T12:00:32.721629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-11T12:00:32.821649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 792
97.4%
2006-12-13 10
 
1.2%
2005-11-10 3
 
0.4%
2014-04-02 2
 
0.2%
2013-01-03 2
 
0.2%
2003-10-06 2
 
0.2%
2005-08-04 1
 
0.1%
2013-12-31 1
 
0.1%

운영방식구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
전일제
811 
주말제
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전일제 811
99.8%
주말제 2
 
0.2%

Length

2024-04-11T12:00:32.925250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-11T12:00:33.012545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전일제 811
99.8%
주말제 2
 
0.2%

평일운영시작시각
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
00:00
807 
01:00
 
5
10:00
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row00:00
2nd row00:00
3rd row00:00
4th row00:00
5th row00:00

Common Values

ValueCountFrequency (%)
00:00 807
99.3%
01:00 5
 
0.6%
10:00 1
 
0.1%

Length

2024-04-11T12:00:33.102821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-11T12:00:33.199498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00 807
99.3%
01:00 5
 
0.6%
10:00 1
 
0.1%

평일운영종료시각
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
23:59
765 
00:00
 
47
01:00
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row23:59
2nd row23:59
3rd row23:59
4th row23:59
5th row23:59

Common Values

ValueCountFrequency (%)
23:59 765
94.1%
00:00 47
 
5.8%
01:00 1
 
0.1%

Length

2024-04-11T12:00:33.314739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-11T12:00:33.418865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
23:59 765
94.1%
00:00 47
 
5.8%
01:00 1
 
0.1%

주말운영시작시각
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
00:00
806 
01:00
 
5
10:00
 
2

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row00:00
2nd row00:00
3rd row00:00
4th row00:00
5th row00:00

Common Values

ValueCountFrequency (%)
00:00 806
99.1%
01:00 5
 
0.6%
10:00 2
 
0.2%

Length

2024-04-11T12:00:33.534558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-11T12:00:33.680116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00 806
99.1%
01:00 5
 
0.6%
10:00 2
 
0.2%

주말운영종료시각
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
23:59
766 
00:00
 
46
18:00
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row23:59
2nd row23:59
3rd row23:59
4th row23:59
5th row23:59

Common Values

ValueCountFrequency (%)
23:59 766
94.2%
00:00 46
 
5.7%
18:00 1
 
0.1%

Length

2024-04-11T12:00:33.823776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-11T12:00:33.926702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
23:59 766
94.2%
00:00 46
 
5.7%
18:00 1
 
0.1%

보행자전용도로시작점위도
Real number (ℝ)

Distinct801
Distinct (%)98.6%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean37.263901
Minimum32.709611
Maximum39.98806
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-04-11T12:00:34.026212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32.709611
5-th percentile36.993636
Q137.008368
median37.352587
Q337.392702
95-th percentile37.471792
Maximum39.98806
Range7.278449
Interquartile range (IQR)0.38433425

Descriptive statistics

Standard deviation0.27551393
Coefficient of variation (CV)0.007393588
Kurtosis102.34269
Mean37.263901
Median Absolute Deviation (MAD)0.0592425
Skewness-4.3657794
Sum30258.287
Variance0.075907925
MonotonicityNot monotonic
2024-04-11T12:00:34.145134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.725402 2
 
0.2%
37.398891 2
 
0.2%
37.008454 2
 
0.2%
37.187651 2
 
0.2%
37.389936 2
 
0.2%
37.171871 2
 
0.2%
37.366178 2
 
0.2%
37.391908 2
 
0.2%
37.002914 2
 
0.2%
37.402503 2
 
0.2%
Other values (791) 792
97.4%
ValueCountFrequency (%)
32.709611 1
0.1%
36.946099 1
0.1%
36.946113 1
0.1%
36.946381 1
0.1%
36.946393 1
0.1%
36.946614 1
0.1%
36.946716 1
0.1%
36.946739 1
0.1%
36.946875 1
0.1%
36.947367 1
0.1%
ValueCountFrequency (%)
39.98806 1
0.1%
37.895635 1
0.1%
37.832141 1
0.1%
37.822291 1
0.1%
37.813291 1
0.1%
37.811631 1
0.1%
37.803181 1
0.1%
37.797621 1
0.1%
37.796401 1
0.1%
37.785281 1
0.1%

보행자전용도로시작점경도
Real number (ℝ)

Distinct800
Distinct (%)98.5%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean127.10078
Minimum126.733
Maximum127.30291
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-04-11T12:00:34.264848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.733
5-th percentile127.04824
Q1127.09256
median127.11121
Q3127.1255
95-th percentile127.14425
Maximum127.30291
Range0.569908
Interquartile range (IQR)0.0329389

Descriptive statistics

Standard deviation0.057589942
Coefficient of variation (CV)0.00045310456
Kurtosis24.195744
Mean127.10078
Median Absolute Deviation (MAD)0.0158555
Skewness-4.284675
Sum103205.83
Variance0.0033166014
MonotonicityNot monotonic
2024-04-11T12:00:34.378355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.131968 2
 
0.2%
127.126574 2
 
0.2%
127.129292 2
 
0.2%
127.113841 2
 
0.2%
127.112411 2
 
0.2%
127.078516 2
 
0.2%
127.114514 2
 
0.2%
127.044081 2
 
0.2%
127.138118 2
 
0.2%
127.072981 2
 
0.2%
Other values (790) 792
97.4%
ValueCountFrequency (%)
126.733004 1
0.1%
126.734729 1
0.1%
126.735631 1
0.1%
126.735848 1
0.1%
126.7450242 1
0.1%
126.7464189 1
0.1%
126.751738 1
0.1%
126.758032 1
0.1%
126.7599325 1
0.1%
126.7600361 1
0.1%
ValueCountFrequency (%)
127.302912 1
0.1%
127.289797 1
0.1%
127.2699801 1
0.1%
127.210474 1
0.1%
127.205693 1
0.1%
127.193267 1
0.1%
127.154594 1
0.1%
127.154174 1
0.1%
127.150111 1
0.1%
127.150097 1
0.1%

보행자전용도로종료점위도
Real number (ℝ)

Distinct804
Distinct (%)99.0%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean37.27069
Minimum36.945998
Maximum39.999225
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-04-11T12:00:34.493115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.945998
5-th percentile36.99354
Q137.008006
median37.354433
Q337.39274
95-th percentile37.472065
Maximum39.999225
Range3.053227
Interquartile range (IQR)0.38473456

Descriptive statistics

Standard deviation0.22586542
Coefficient of variation (CV)0.0060601352
Kurtosis25.130715
Mean37.27069
Median Absolute Deviation (MAD)0.0574245
Skewness2.1723092
Sum30263.8
Variance0.051015187
MonotonicityNot monotonic
2024-04-11T12:00:34.619320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.008437 2
 
0.2%
37.384668 2
 
0.2%
37.411836 2
 
0.2%
37.008433 2
 
0.2%
37.009229 2
 
0.2%
37.361681 2
 
0.2%
37.385796 2
 
0.2%
37.003411 2
 
0.2%
37.392751 1
 
0.1%
37.392327 1
 
0.1%
Other values (794) 794
97.7%
ValueCountFrequency (%)
36.945998 1
0.1%
36.946037 1
0.1%
36.946102 1
0.1%
36.946107 1
0.1%
36.946453 1
0.1%
36.946472 1
0.1%
36.946745 1
0.1%
36.946988 1
0.1%
36.947106 1
0.1%
36.953333 1
0.1%
ValueCountFrequency (%)
39.999225 1
0.1%
37.893552 1
0.1%
37.841251 1
0.1%
37.838161 1
0.1%
37.821861 1
0.1%
37.821231 1
0.1%
37.808981 1
0.1%
37.805301 1
0.1%
37.803181 1
0.1%
37.800111 1
0.1%

보행자전용도로종료점경도
Real number (ℝ)

Distinct805
Distinct (%)99.1%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean127.10034
Minimum126.73121
Maximum127.27133
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-04-11T12:00:34.738385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.73121
5-th percentile127.04876
Q1127.09243
median127.11117
Q3127.1253
95-th percentile127.14372
Maximum127.27133
Range0.5401197
Interquartile range (IQR)0.032871

Descriptive statistics

Standard deviation0.057101053
Coefficient of variation (CV)0.00044925966
Kurtosis25.924381
Mean127.10034
Median Absolute Deviation (MAD)0.01549
Skewness-4.6260434
Sum103205.47
Variance0.0032605303
MonotonicityNot monotonic
2024-04-11T12:00:34.857758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.110919 4
 
0.5%
127.111063 2
 
0.2%
127.099506 2
 
0.2%
127.114591 2
 
0.2%
127.111152 2
 
0.2%
127.063331 1
 
0.1%
127.062591 1
 
0.1%
127.063231 1
 
0.1%
127.063907 1
 
0.1%
127.063854 1
 
0.1%
Other values (795) 795
97.8%
ValueCountFrequency (%)
126.731213 1
0.1%
126.732488 1
0.1%
126.733372 1
0.1%
126.735884 1
0.1%
126.7462861 1
0.1%
126.746373 1
0.1%
126.7464849 1
0.1%
126.7596461 1
0.1%
126.759697 1
0.1%
126.7600361 1
0.1%
ValueCountFrequency (%)
127.2713327 1
0.1%
127.210997 1
0.1%
127.207591 1
0.1%
127.193275 1
0.1%
127.154127 1
0.1%
127.150949 1
0.1%
127.150496 1
0.1%
127.150204 1
0.1%
127.150015 1
0.1%
127.150006 1
0.1%

자전거보행자겸용도로구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
787 
겸용
 
16
전용
 
10

Length

Max length4
Median length4
Mean length3.9360394
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 787
96.8%
겸용 16
 
2.0%
전용 10
 
1.2%

Length

2024-04-11T12:00:34.975742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-11T12:00:35.073773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 787
96.8%
겸용 16
 
2.0%
전용 10
 
1.2%

보행자전용도로폭
Real number (ℝ)

Distinct34
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.907749
Minimum2
Maximum2030
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-04-11T12:00:35.167474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4
Q16
median6
Q310
95-th percentile15.4
Maximum2030
Range2028
Interquartile range (IQR)4

Descriptive statistics

Standard deviation133.53821
Coefficient of variation (CV)5.8293904
Kurtosis141.38768
Mean22.907749
Median Absolute Deviation (MAD)2
Skewness11.096639
Sum18624
Variance17832.454
MonotonicityNot monotonic
2024-04-11T12:00:35.281183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
6.0 383
47.1%
15.0 104
 
12.8%
10.0 92
 
11.3%
8.0 91
 
11.2%
4.0 35
 
4.3%
3.0 28
 
3.4%
20.0 21
 
2.6%
2.0 10
 
1.2%
5.0 10
 
1.2%
30.0 5
 
0.6%
Other values (24) 34
 
4.2%
ValueCountFrequency (%)
2.0 10
 
1.2%
3.0 28
3.4%
3.1 1
 
0.1%
3.2 1
 
0.1%
4.0 35
4.3%
4.2 1
 
0.1%
4.6 1
 
0.1%
4.7 1
 
0.1%
4.8 2
 
0.2%
5.0 10
 
1.2%
ValueCountFrequency (%)
2030.0 2
 
0.2%
1030.0 1
 
0.1%
1015.0 1
 
0.1%
1014.0 1
 
0.1%
816.0 1
 
0.1%
715.0 4
0.5%
710.0 1
 
0.1%
510.0 1
 
0.1%
46.0 1
 
0.1%
30.0 5
0.6%

보차분리여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.7%
Missing534
Missing (%)65.7%
Memory size1.7 KiB
False
252 
True
 
27
(Missing)
534 
ValueCountFrequency (%)
False 252
31.0%
True 27
 
3.3%
(Missing) 534
65.7%
2024-04-11T12:00:35.381967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

지정목적
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
보행환경개선
779 
안전한 보행로 확보
 
17
보행안전+편의증진
 
10
지역상권활성화+보행환경개선
 
5
보행자 안전
 
1

Length

Max length14
Median length6
Mean length6.1722017
Min length6

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
보행환경개선 779
95.8%
안전한 보행로 확보 17
 
2.1%
보행안전+편의증진 10
 
1.2%
지역상권활성화+보행환경개선 5
 
0.6%
보행자 안전 1
 
0.1%
주말여가장소제공 1
 
0.1%

Length

2024-04-11T12:00:35.671520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-11T12:00:35.769043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보행환경개선 779
91.9%
안전한 17
 
2.0%
보행로 17
 
2.0%
확보 17
 
2.0%
보행안전+편의증진 10
 
1.2%
지역상권활성화+보행환경개선 5
 
0.6%
보행자 1
 
0.1%
안전 1
 
0.1%
주말여가장소제공 1
 
0.1%

관리점검일자
Categorical

IMBALANCE 

Distinct19
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2023-10-18
418 
2023-02-28
246 
2020-06-30
59 
2021-10-20
46 
2019-06-29
 
10
Other values (14)
 
34

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique7 ?
Unique (%)0.9%

Sample

1st row2023-10-18
2nd row2023-10-18
3rd row2023-10-18
4th row2023-10-18
5th row2023-10-18

Common Values

ValueCountFrequency (%)
2023-10-18 418
51.4%
2023-02-28 246
30.3%
2020-06-30 59
 
7.3%
2021-10-20 46
 
5.7%
2019-06-29 10
 
1.2%
2021-10-13 10
 
1.2%
2022-03-27 5
 
0.6%
2020-10-05 3
 
0.4%
2020-07-06 3
 
0.4%
2020-09-22 2
 
0.2%
Other values (9) 11
 
1.4%

Length

2024-04-11T12:00:35.869478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023-10-18 418
51.4%
2023-02-28 246
30.3%
2020-06-30 59
 
7.3%
2021-10-20 46
 
5.7%
2019-06-29 10
 
1.2%
2021-10-13 10
 
1.2%
2022-03-27 5
 
0.6%
2020-10-05 3
 
0.4%
2020-07-06 3
 
0.4%
2020-11-16 2
 
0.2%
Other values (9) 11
 
1.4%

관리점검결과
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
합격
813 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
합격 813
100.0%

Length

2024-04-11T12:00:35.960639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-11T12:00:36.042280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
합격 813
100.0%

유지보수내용
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
802 
시설물 양호(미보수)
 
10
없음
 
1

Length

Max length11
Median length4
Mean length4.0836408
Min length2

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> 802
98.6%
시설물 양호(미보수) 10
 
1.2%
없음 1
 
0.1%

Length

2024-04-11T12:00:36.128371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-11T12:00:36.213638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 802
97.4%
시설물 10
 
1.2%
양호(미보수 10
 
1.2%
없음 1
 
0.1%

영상정보기처리기기설치개수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
785 
0
 
27
1
 
1

Length

Max length4
Median length4
Mean length3.896679
Min length1

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> 785
96.6%
0 27
 
3.3%
1 1
 
0.1%

Length

2024-04-11T12:00:36.314933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-11T12:00:36.402316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 785
96.6%
0 27
 
3.3%
1 1
 
0.1%

보안등설치개수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)35.5%
Missing782
Missing (%)96.2%
Infinite0
Infinite (%)0.0%
Mean6.3548387
Minimum0
Maximum52
Zeros15
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-04-11T12:00:36.482452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q38
95-th percentile31
Maximum52
Range52
Interquartile range (IQR)8

Descriptive statistics

Standard deviation12.655824
Coefficient of variation (CV)1.9915257
Kurtosis9.9138979
Mean6.3548387
Median Absolute Deviation (MAD)1
Skewness3.1672251
Sum197
Variance160.16989
MonotonicityNot monotonic
2024-04-11T12:00:36.576275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 15
 
1.8%
8 5
 
0.6%
10 2
 
0.2%
6 2
 
0.2%
51 1
 
0.1%
5 1
 
0.1%
11 1
 
0.1%
1 1
 
0.1%
3 1
 
0.1%
52 1
 
0.1%
(Missing) 782
96.2%
ValueCountFrequency (%)
0 15
1.8%
1 1
 
0.1%
2 1
 
0.1%
3 1
 
0.1%
5 1
 
0.1%
6 2
 
0.2%
8 5
 
0.6%
10 2
 
0.2%
11 1
 
0.1%
51 1
 
0.1%
ValueCountFrequency (%)
52 1
 
0.1%
51 1
 
0.1%
11 1
 
0.1%
10 2
 
0.2%
8 5
0.6%
6 2
 
0.2%
5 1
 
0.1%
3 1
 
0.1%
2 1
 
0.1%
1 1
 
0.1%

횡단보도설치개수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
785 
0
 
27
1
 
1

Length

Max length4
Median length4
Mean length3.896679
Min length1

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> 785
96.6%
0 27
 
3.3%
1 1
 
0.1%

Length

2024-04-11T12:00:36.691735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-11T12:00:36.780544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 785
96.6%
0 27
 
3.3%
1 1
 
0.1%

방호울타리설치개수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
785 
0
 
26
3
 
1
28
 
1

Length

Max length4
Median length4
Mean length3.897909
Min length1

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 785
96.6%
0 26
 
3.2%
3 1
 
0.1%
28 1
 
0.1%

Length

2024-04-11T12:00:36.876186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-11T12:00:36.966123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 785
96.6%
0 26
 
3.2%
3 1
 
0.1%
28 1
 
0.1%

차량진입억제용말뚝설치개수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)20.7%
Missing784
Missing (%)96.4%
Infinite0
Infinite (%)0.0%
Mean1.3448276
Minimum0
Maximum13
Zeros23
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-04-11T12:00:37.047214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile9.2
Maximum13
Range13
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.2871597
Coefficient of variation (CV)2.4442982
Kurtosis6.5503431
Mean1.3448276
Median Absolute Deviation (MAD)0
Skewness2.6781511
Sum39
Variance10.805419
MonotonicityNot monotonic
2024-04-11T12:00:37.143243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 23
 
2.8%
3 2
 
0.2%
10 1
 
0.1%
2 1
 
0.1%
13 1
 
0.1%
8 1
 
0.1%
(Missing) 784
96.4%
ValueCountFrequency (%)
0 23
2.8%
2 1
 
0.1%
3 2
 
0.2%
8 1
 
0.1%
10 1
 
0.1%
13 1
 
0.1%
ValueCountFrequency (%)
13 1
 
0.1%
10 1
 
0.1%
8 1
 
0.1%
3 2
 
0.2%
2 1
 
0.1%
0 23
2.8%

속도저감시설설치개수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
785 
0
 
28

Length

Max length4
Median length4
Mean length3.896679
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 785
96.6%
0 28
 
3.4%

Length

2024-04-11T12:00:37.247032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-11T12:00:37.335316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 785
96.6%
0 28
 
3.4%

교통표지판설치개수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
785 
0
 
28

Length

Max length4
Median length4
Mean length3.896679
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 785
96.6%
0 28
 
3.4%

Length

2024-04-11T12:00:37.426612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-11T12:00:37.517993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 785
96.6%
0 28
 
3.4%

이정표설치개수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
785 
0
 
26
1
 
2

Length

Max length4
Median length4
Mean length3.896679
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 785
96.6%
0 26
 
3.2%
1 2
 
0.2%

Length

2024-04-11T12:00:37.618872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-11T12:00:37.736444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 785
96.6%
0 26
 
3.2%
1 2
 
0.2%

점자블럭설치개수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
790 
0
 
22
1
 
1

Length

Max length4
Median length4
Mean length3.9151292
Min length1

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> 790
97.2%
0 22
 
2.7%
1 1
 
0.1%

Length

2024-04-11T12:00:37.852480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-11T12:00:37.956254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 790
97.2%
0 22
 
2.7%
1 1
 
0.1%

관리기관명
Categorical

Distinct13
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
경기도 성남시 분당구청
369 
경기도 평택시청
246 
경기도 오산시청
59 
경기도 하남시청
46 
경기도 성남시 수정구청
45 
Other values (8)
48 

Length

Max length16
Median length12
Mean length10.184502
Min length8

Unique

Unique3 ?
Unique (%)0.4%

Sample

1st row경기도 성남시 수정구청
2nd row경기도 성남시 수정구청
3rd row경기도 성남시 수정구청
4th row경기도 성남시 수정구청
5th row경기도 성남시 수정구청

Common Values

ValueCountFrequency (%)
경기도 성남시 분당구청 369
45.4%
경기도 평택시청 246
30.3%
경기도 오산시청 59
 
7.3%
경기도 하남시청 46
 
5.7%
경기도 성남시 수정구청 45
 
5.5%
경기도 파주시청 17
 
2.1%
경기도 양주시청 도로과 10
 
1.2%
경기도 남양주시청 10
 
1.2%
경기도 수원시 팔달구청 건설과 4
 
0.5%
경기도 성남시 중원구청 4
 
0.5%
Other values (3) 3
 
0.4%

Length

2024-04-11T12:00:38.067639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 813
39.4%
성남시 418
20.2%
분당구청 369
17.9%
평택시청 246
 
11.9%
오산시청 59
 
2.9%
하남시청 46
 
2.2%
수정구청 45
 
2.2%
파주시청 17
 
0.8%
남양주시청 10
 
0.5%
도로과 10
 
0.5%
Other values (9) 32
 
1.5%

관리기관전화번호
Categorical

Distinct14
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
031-8024-4777
246 
031-729-8092
213 
031-729-7461
156 
031-8036-7704
59 
031-790-5947
46 
Other values (9)
93 

Length

Max length13
Median length12
Mean length12.387454
Min length12

Unique

Unique3 ?
Unique (%)0.4%

Sample

1st row031-729-5452
2nd row031-729-5452
3rd row031-729-5452
4th row031-729-5452
5th row031-729-5452

Common Values

ValueCountFrequency (%)
031-8024-4777 246
30.3%
031-729-8092 213
26.2%
031-729-7461 156
19.2%
031-8036-7704 59
 
7.3%
031-790-5947 46
 
5.7%
031-729-5452 45
 
5.5%
031-940-4644 17
 
2.1%
031-8082-6732 10
 
1.2%
031-590-2489 10
 
1.2%
031-228-7062 4
 
0.5%
Other values (4) 7
 
0.9%

Length

2024-04-11T12:00:38.180737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
031-8024-4777 246
30.3%
031-729-8092 213
26.2%
031-729-7461 156
19.2%
031-8036-7704 59
 
7.3%
031-790-5947 46
 
5.7%
031-729-5452 45
 
5.5%
031-940-4644 17
 
2.1%
031-8082-6732 10
 
1.2%
031-590-2489 10
 
1.2%
031-228-7062 4
 
0.5%
Other values (4) 7
 
0.9%

데이터기준일자
Categorical

Distinct10
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2023-10-19
418 
2023-07-24
246 
2023-09-19
59 
2022-06-01
46 
2023-11-15
 
17
Other values (5)
 
27

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row2023-10-19
2nd row2023-10-19
3rd row2023-10-19
4th row2023-10-19
5th row2023-10-19

Common Values

ValueCountFrequency (%)
2023-10-19 418
51.4%
2023-07-24 246
30.3%
2023-09-19 59
 
7.3%
2022-06-01 46
 
5.7%
2023-11-15 17
 
2.1%
2024-01-02 10
 
1.2%
2023-12-13 10
 
1.2%
2023-09-22 5
 
0.6%
2023-10-04 1
 
0.1%
2023-07-06 1
 
0.1%

Length

2024-04-11T12:00:38.292105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-11T12:00:38.394598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-10-19 418
51.4%
2023-07-24 246
30.3%
2023-09-19 59
 
7.3%
2022-06-01 46
 
5.7%
2023-11-15 17
 
2.1%
2024-01-02 10
 
1.2%
2023-12-13 10
 
1.2%
2023-09-22 5
 
0.6%
2023-10-04 1
 
0.1%
2023-07-06 1
 
0.1%

Sample

보행자전용도로명시도명시군구명법정동명지정일자운영방식구분평일운영시작시각평일운영종료시각주말운영시작시각주말운영종료시각보행자전용도로시작점위도보행자전용도로시작점경도보행자전용도로종료점위도보행자전용도로종료점경도자전거보행자겸용도로구분보행자전용도로폭보차분리여부지정목적관리점검일자관리점검결과유지보수내용영상정보기처리기기설치개수보안등설치개수횡단보도설치개수방호울타리설치개수차량진입억제용말뚝설치개수속도저감시설설치개수교통표지판설치개수이정표설치개수점자블럭설치개수관리기관명관리기관전화번호데이터기준일자
0고등동 소로1경기도성남시고등동<NA>전일제00:0023:5900:0023:5937.424078127.10042137.424364127.100428<NA>10.0<NA>보행환경개선2023-10-18합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 성남시 수정구청031-729-54522023-10-19
1고등동 소로2경기도성남시고등동<NA>전일제00:0023:5900:0023:5937.424892127.10091837.425153127.100922<NA>10.0<NA>보행환경개선2023-10-18합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 성남시 수정구청031-729-54522023-10-19
2고등동 소로11경기도성남시고등동<NA>전일제00:0023:5900:0023:5937.427548127.09451137.427696127.094642<NA>6.0<NA>보행환경개선2023-10-18합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 성남시 수정구청031-729-54522023-10-19
3고등동 소로10경기도성남시고등동<NA>전일제00:0023:5900:0023:5937.428314127.09422337.428441127.094019<NA>6.0<NA>보행환경개선2023-10-18합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 성남시 수정구청031-729-54522023-10-19
4고등동 소로9경기도성남시고등동<NA>전일제00:0023:5900:0023:5937.425529127.09966737.425274127.099663<NA>6.0<NA>보행환경개선2023-10-18합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 성남시 수정구청031-729-54522023-10-19
5고등동 소로8경기도성남시고등동<NA>전일제00:0023:5900:0023:5937.430246127.10150337.430437127.101573<NA>6.0<NA>보행환경개선2023-10-18합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 성남시 수정구청031-729-54522023-10-19
6고등동 소로3경기도성남시고등동<NA>전일제00:0023:5900:0023:5937.428071127.10160837.428065127.100995<NA>10.0<NA>보행환경개선2023-10-18합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 성남시 수정구청031-729-54522023-10-19
7고등동 소로4경기도성남시고등동<NA>전일제00:0023:5900:0023:5937.425499127.10167837.425272127.101662<NA>6.0<NA>보행환경개선2023-10-18합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 성남시 수정구청031-729-54522023-10-19
8고등동 소로5경기도성남시고등동<NA>전일제00:0023:5900:0023:5937.424323127.10190337.424335127.101622<NA>6.0<NA>보행환경개선2023-10-18합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 성남시 수정구청031-729-54522023-10-19
9고등동 소로6경기도성남시고등동<NA>전일제00:0023:5900:0023:5937.423558127.10182937.423573127.101544<NA>6.0<NA>보행환경개선2023-10-18합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 성남시 수정구청031-729-54522023-10-19
보행자전용도로명시도명시군구명법정동명지정일자운영방식구분평일운영시작시각평일운영종료시각주말운영시작시각주말운영종료시각보행자전용도로시작점위도보행자전용도로시작점경도보행자전용도로종료점위도보행자전용도로종료점경도자전거보행자겸용도로구분보행자전용도로폭보차분리여부지정목적관리점검일자관리점검결과유지보수내용영상정보기처리기기설치개수보안등설치개수횡단보도설치개수방호울타리설치개수차량진입억제용말뚝설치개수속도저감시설설치개수교통표지판설치개수이정표설치개수점자블럭설치개수관리기관명관리기관전화번호데이터기준일자
803하대원동 소로1경기도성남시하대원동<NA>전일제00:0023:5900:0023:5937.427941127.13470537.427807127.134687<NA>6.0<NA>보행환경개선2023-10-18합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 성남시 중원구청031-729-64522023-10-19
804금릉역로경기도파주시하지석동<NA>전일제00:0023:5900:0023:5937.751265126.76566437.758454126.763401<NA>6.0Y안전한 보행로 확보2020-10-05합격<NA>00000000<NA>경기도 파주시청031-940-46442023-11-15
805합정동 소로 3-387경기도평택시합정동<NA>전일제00:0023:5900:0023:5936.99033127.1139136.99015127.11396<NA>6.0N보행환경개선2023-02-28합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 평택시청031-8024-47772023-07-24
806합정동 소로 3-386경기도평택시합정동<NA>전일제00:0023:5900:0023:5936.98951127.1150736.98957127.11529<NA>6.0N보행환경개선2023-02-28합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 평택시청031-8024-47772023-07-24
807합정동 소로 2-619경기도평택시합정동<NA>전일제00:0023:5900:0023:5939.98806127.1136736.98761127.11402<NA>8.0N보행환경개선2023-02-28합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 평택시청031-8024-47772023-07-24
808합정동 소로 1-444경기도평택시합정동<NA>전일제00:0023:5900:0023:5936.98844127.1133236.98811127.11358<NA>20.0N보행환경개선2023-02-28합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 평택시청031-8024-47772023-07-24
809합정동 소로 2-616경기도평택시합정동<NA>전일제00:0023:5900:0023:5936.98999127.1121436.98965127.11228<NA>10.0N보행환경개선2023-02-28합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 평택시청031-8024-47772023-07-24
810합정동 소로 2-617경기도평택시합정동<NA>전일제00:0023:5900:0023:5936.98959127.1124136.98905127.11259<NA>8.0N보행환경개선2023-02-28합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 평택시청031-8024-47772023-07-24
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