Overview

Dataset statistics

Number of variables19
Number of observations623
Missing cells157
Missing cells (%)1.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory94.4 KiB
Average record size in memory155.2 B

Variable types

Categorical12
Text4
DateTime1
Numeric2

Dataset

Description성남시 주요 도로변(교통삼, 횡단보도 등)에 설치된 여름철 무더위 그늘막 설치 현황으로 설치장소, 소재지 등을 제공합니다.
URLhttps://www.data.go.kr/data/15043080/fileData.do

Alerts

기준년도 has constant value ""Constant
시군명 has constant value ""Constant
당해년도 운영시작일자 has constant value ""Constant
당해년도 운영종료일자 has constant value ""Constant
데이터기준일자 has constant value ""Constant
관리기관 전화번호 is highly overall correlated with 위도 and 4 other fieldsHigh correlation
관리기관 is highly overall correlated with 위도 and 5 other fieldsHigh correlation
읍면동명 is highly overall correlated with 위도 and 4 other fieldsHigh correlation
위도 is highly overall correlated with 경도 and 4 other fieldsHigh correlation
경도 is highly overall correlated with 위도 and 4 other fieldsHigh correlation
높이_m is highly overall correlated with 펼침지름_m and 2 other fieldsHigh correlation
펼침지름_m is highly overall correlated with 높이_mHigh correlation
구분 is highly overall correlated with 위도 and 5 other fieldsHigh correlation
원단 is highly imbalanced (91.2%)Imbalance
소재지도로명주소 has 109 (17.5%) missing valuesMissing
소재지지번주소 has 48 (7.7%) missing valuesMissing

Reproduction

Analysis started2023-12-12 13:50:32.671980
Analysis finished2023-12-12 13:50:35.261575
Duration2.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023
623 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023
2nd row2023
3rd row2023
4th row2023
5th row2023

Common Values

ValueCountFrequency (%)
2023 623
100.0%

Length

2023-12-12T22:50:35.334678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:50:35.473333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 623
100.0%

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
성남시
623 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
성남시 623
100.0%

Length

2023-12-12T22:50:35.601300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:50:35.760678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성남시 623
100.0%

읍면동명
Categorical

HIGH CORRELATION 

Distinct50
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
위례동
54 
백현동
 
32
구미동
 
31
삼평동
 
29
운중동
 
28
Other values (45)
449 

Length

Max length5
Median length3
Mean length3.5184591
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row신흥1동
2nd row신흥1동
3rd row신흥1동
4th row신흥2동
5th row신흥2동

Common Values

ValueCountFrequency (%)
위례동 54
 
8.7%
백현동 32
 
5.1%
구미동 31
 
5.0%
삼평동 29
 
4.7%
운중동 28
 
4.5%
정자1동 22
 
3.5%
중앙동 21
 
3.4%
고등동 21
 
3.4%
판교동 21
 
3.4%
신흥2동 17
 
2.7%
Other values (40) 347
55.7%

Length

2023-12-12T22:50:35.882637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
위례동 54
 
8.7%
백현동 32
 
5.1%
구미동 31
 
5.0%
삼평동 29
 
4.7%
운중동 28
 
4.5%
정자1동 22
 
3.5%
중앙동 21
 
3.4%
고등동 21
 
3.4%
판교동 21
 
3.4%
신흥2동 17
 
2.7%
Other values (40) 347
55.7%

관리번호
Text

Distinct622
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-12-12T22:50:36.121970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length22
Mean length10.208668
Min length5

Characters and Unicode

Total characters6360
Distinct characters151
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique621 ?
Unique (%)99.7%

Sample

1st row수정로(신흥1동-3)
2nd row산성대로(신흥1동-1)
3rd row산성대로(신흥1동-2)
4th row공원로(신흥2동-3)
5th row공원로(신흥2동-8)
ValueCountFrequency (%)
앞 11
 
1.6%
도촌남로 4
 
0.6%
둔촌대로 4
 
0.6%
금광동 3
 
0.4%
도촌동 3
 
0.4%
수정로(태평2동-3 2
 
0.3%
산성대로 2
 
0.3%
하대원동 2
 
0.3%
은행동 2
 
0.3%
상대원1동 2
 
0.3%
Other values (653) 655
94.9%
2023-12-12T22:50:36.492945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 633
 
10.0%
- 610
 
9.6%
( 433
 
6.8%
) 431
 
6.8%
로 424
 
6.7%
1 399
 
6.3%
2 233
 
3.7%
대 165
 
2.6%
3 154
 
2.4%
정 116
 
1.8%
Other values (141) 2762
43.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3556
55.9%
Decimal Number 1255
 
19.7%
Dash Punctuation 610
 
9.6%
Open Punctuation 433
 
6.8%
Close Punctuation 431
 
6.8%
Space Separator 68
 
1.1%
Uppercase Letter 6
 
0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 633
 
17.8%
로 424
 
11.9%
대 165
 
4.6%
정 116
 
3.3%
성 110
 
3.1%
례 86
 
2.4%
위 86
 
2.4%
남 84
 
2.4%
교 74
 
2.1%
수 72
 
2.0%
Other values (122) 1706
48.0%
Decimal Number
ValueCountFrequency (%)
1 399
31.8%
2 233
18.6%
3 154
 
12.3%
4 98
 
7.8%
5 79
 
6.3%
6 72
 
5.7%
7 65
 
5.2%
9 58
 
4.6%
8 55
 
4.4%
0 42
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
C 3
50.0%
I 1
 
16.7%
K 1
 
16.7%
A 1
 
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 610
100.0%
Open Punctuation
ValueCountFrequency (%)
( 433
100.0%
Close Punctuation
ValueCountFrequency (%)
) 431
100.0%
Space Separator
ValueCountFrequency (%)
68
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3556
55.9%
Common 2798
44.0%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 633
 
17.8%
로 424
 
11.9%
대 165
 
4.6%
정 116
 
3.3%
성 110
 
3.1%
례 86
 
2.4%
위 86
 
2.4%
남 84
 
2.4%
교 74
 
2.1%
수 72
 
2.0%
Other values (122) 1706
48.0%
Common
ValueCountFrequency (%)
- 610
21.8%
( 433
15.5%
) 431
15.4%
1 399
14.3%
2 233
 
8.3%
3 154
 
5.5%
4 98
 
3.5%
5 79
 
2.8%
6 72
 
2.6%
68
 
2.4%
Other values (5) 221
 
7.9%
Latin
ValueCountFrequency (%)
C 3
50.0%
I 1
 
16.7%
K 1
 
16.7%
A 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3556
55.9%
ASCII 2804
44.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 633
 
17.8%
로 424
 
11.9%
대 165
 
4.6%
정 116
 
3.3%
성 110
 
3.1%
례 86
 
2.4%
위 86
 
2.4%
남 84
 
2.4%
교 74
 
2.1%
수 72
 
2.0%
Other values (122) 1706
48.0%
ASCII
ValueCountFrequency (%)
- 610
21.8%
( 433
15.4%
) 431
15.4%
1 399
14.2%
2 233
 
8.3%
3 154
 
5.5%
4 98
 
3.5%
5 79
 
2.8%
6 72
 
2.6%
68
 
2.4%
Other values (9) 227
 
8.1%

설치장소명
Text

Distinct583
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-12-12T22:50:36.846258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length31
Mean length12.616372
Min length2

Characters and Unicode

Total characters7860
Distinct characters393
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

Unique553 ?
Unique (%)88.8%

Sample

1st row교보빌딩 앞
2nd row신흥사거리 비와이씨 앞 교통섬
3rd row수진역 3번출구 방향 교통섬
4th row신흥동 2460-1 횡단보도
5th row두산아파트 103동
ValueCountFrequency (%)
앞 277
 
16.5%
횡단보도 92
 
5.5%
교통섬 37
 
2.2%
건너편 37
 
2.2%
맞은편 34
 
2.0%
사거리 23
 
1.4%
정문 17
 
1.0%
옆 16
 
1.0%
방면 14
 
0.8%
고등동 12
 
0.7%
Other values (783) 1116
66.6%
2023-12-12T22:50:37.415662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1061
 
13.5%
앞 303
 
3.9%
동 283
 
3.6%
1 211
 
2.7%
리 163
 
2.1%
0 150
 
1.9%
교 144
 
1.8%
단 141
 
1.8%
도 137
 
1.7%
2 136
 
1.7%
Other values (383) 5131
65.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5457
69.4%
Space Separator 1061
 
13.5%
Decimal Number 980
 
12.5%
Open Punctuation 121
 
1.5%
Close Punctuation 120
 
1.5%
Uppercase Letter 56
 
0.7%
Dash Punctuation 46
 
0.6%
Other Punctuation 13
 
0.2%
Lowercase Letter 4
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 303
 
5.6%
동 283
 
5.2%
리 163
 
3.0%
교 144
 
2.6%
단 141
 
2.6%
도 137
 
2.5%
거 130
 
2.4%
사 126
 
2.3%
보 108
 
2.0%
횡 99
 
1.8%
Other values (345) 3823
70.1%
Uppercase Letter
ValueCountFrequency (%)
S 10
17.9%
G 7
12.5%
K 6
10.7%
C 6
10.7%
B 4
 
7.1%
D 3
 
5.4%
A 3
 
5.4%
U 3
 
5.4%
L 2
 
3.6%
R 2
 
3.6%
Other values (7) 10
17.9%
Decimal Number
ValueCountFrequency (%)
1 211
21.5%
0 150
15.3%
2 136
13.9%
3 118
12.0%
5 99
10.1%
4 72
 
7.3%
6 54
 
5.5%
9 48
 
4.9%
8 46
 
4.7%
7 46
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 11
84.6%
& 1
 
7.7%
? 1
 
7.7%
Lowercase Letter
ValueCountFrequency (%)
e 2
50.0%
u 1
25.0%
c 1
25.0%
Space Separator
ValueCountFrequency (%)
1061
100.0%
Open Punctuation
ValueCountFrequency (%)
( 121
100.0%
Close Punctuation
ValueCountFrequency (%)
) 120
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5457
69.4%
Common 2343
29.8%
Latin 60
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 303
 
5.6%
동 283
 
5.2%
리 163
 
3.0%
교 144
 
2.6%
단 141
 
2.6%
도 137
 
2.5%
거 130
 
2.4%
사 126
 
2.3%
보 108
 
2.0%
횡 99
 
1.8%
Other values (345) 3823
70.1%
Latin
ValueCountFrequency (%)
S 10
16.7%
G 7
11.7%
K 6
10.0%
C 6
10.0%
B 4
 
6.7%
D 3
 
5.0%
A 3
 
5.0%
U 3
 
5.0%
L 2
 
3.3%
R 2
 
3.3%
Other values (10) 14
23.3%
Common
ValueCountFrequency (%)
1061
45.3%
1 211
 
9.0%
0 150
 
6.4%
2 136
 
5.8%
( 121
 
5.2%
) 120
 
5.1%
3 118
 
5.0%
5 99
 
4.2%
4 72
 
3.1%
6 54
 
2.3%
Other values (8) 201
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5457
69.4%
ASCII 2403
30.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1061
44.2%
1 211
 
8.8%
0 150
 
6.2%
2 136
 
5.7%
( 121
 
5.0%
) 120
 
5.0%
3 118
 
4.9%
5 99
 
4.1%
4 72
 
3.0%
6 54
 
2.2%
Other values (28) 261
 
10.9%
Hangul
ValueCountFrequency (%)
앞 303
 
5.6%
동 283
 
5.2%
리 163
 
3.0%
교 144
 
2.6%
단 141
 
2.6%
도 137
 
2.5%
거 130
 
2.4%
사 126
 
2.3%
보 108
 
2.0%
횡 99
 
1.8%
Other values (345) 3823
70.1%

소재지도로명주소
Text

MISSING 

Distinct420
Distinct (%)81.7%
Missing109
Missing (%)17.5%
Memory size5.0 KiB
2023-12-12T22:50:37.739520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length42.5
Mean length28.342412
Min length1

Characters and Unicode

Total characters14568
Distinct characters239
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique369 ?
Unique (%)71.8%

Sample

1st row경기도 성남시 수정구 수정로 150 (신흥동)
2nd row경기도 성남시 수정구 산성대로 241 (신흥동)
3rd row경기도 성남시 수정구 산성대로 199 (수진동)
4th row경기도 성남시 수정구 공원로 360 (신흥동, 두산아파트)
5th row경기도 성남시 수정구 공원로 340 (신흥동, 청구아파트)
ValueCountFrequency (%)
성남시 483
 
15.7%
경기도 482
 
15.7%
분당구 286
 
9.3%
수정구 126
 
4.1%
중원구 71
 
2.3%
정자동 48
 
1.6%
창곡동 40
 
1.3%
구미동 39
 
1.3%
야탑동 30
 
1.0%
신흥동 23
 
0.7%
Other values (558) 1443
47.0%
2023-12-12T22:50:38.258701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3097
21.3%
성 562
 
3.9%
남 541
 
3.7%
구 530
 
3.6%
시 493
 
3.4%
도 492
 
3.4%
경 483
 
3.3%
기 482
 
3.3%
동 479
 
3.3%
로 472
 
3.2%
Other values (229) 6937
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8899
61.1%
Space Separator 3097
 
21.3%
Decimal Number 1489
 
10.2%
Open Punctuation 436
 
3.0%
Close Punctuation 436
 
3.0%
Other Punctuation 180
 
1.2%
Dash Punctuation 21
 
0.1%
Uppercase Letter 10
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 562
 
6.3%
남 541
 
6.1%
구 530
 
6.0%
시 493
 
5.5%
도 492
 
5.5%
경 483
 
5.4%
기 482
 
5.4%
동 479
 
5.4%
로 472
 
5.3%
분 310
 
3.5%
Other values (207) 4055
45.6%
Decimal Number
ValueCountFrequency (%)
1 308
20.7%
2 223
15.0%
3 161
10.8%
5 143
9.6%
4 137
9.2%
6 127
8.5%
7 122
 
8.2%
0 104
 
7.0%
9 97
 
6.5%
8 67
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
K 2
20.0%
G 2
20.0%
I 2
20.0%
L 2
20.0%
B 1
10.0%
S 1
10.0%
Other Punctuation
ValueCountFrequency (%)
, 179
99.4%
. 1
 
0.6%
Space Separator
ValueCountFrequency (%)
3097
100.0%
Open Punctuation
ValueCountFrequency (%)
( 436
100.0%
Close Punctuation
ValueCountFrequency (%)
) 436
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8899
61.1%
Common 5659
38.8%
Latin 10
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 562
 
6.3%
남 541
 
6.1%
구 530
 
6.0%
시 493
 
5.5%
도 492
 
5.5%
경 483
 
5.4%
기 482
 
5.4%
동 479
 
5.4%
로 472
 
5.3%
분 310
 
3.5%
Other values (207) 4055
45.6%
Common
ValueCountFrequency (%)
3097
54.7%
( 436
 
7.7%
) 436
 
7.7%
1 308
 
5.4%
2 223
 
3.9%
, 179
 
3.2%
3 161
 
2.8%
5 143
 
2.5%
4 137
 
2.4%
6 127
 
2.2%
Other values (6) 412
 
7.3%
Latin
ValueCountFrequency (%)
K 2
20.0%
G 2
20.0%
I 2
20.0%
L 2
20.0%
B 1
10.0%
S 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8899
61.1%
ASCII 5669
38.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3097
54.6%
( 436
 
7.7%
) 436
 
7.7%
1 308
 
5.4%
2 223
 
3.9%
, 179
 
3.2%
3 161
 
2.8%
5 143
 
2.5%
4 137
 
2.4%
6 127
 
2.2%
Other values (12) 422
 
7.4%
Hangul
ValueCountFrequency (%)
성 562
 
6.3%
남 541
 
6.1%
구 530
 
6.0%
시 493
 
5.5%
도 492
 
5.5%
경 483
 
5.4%
기 482
 
5.4%
동 479
 
5.4%
로 472
 
5.3%
분 310
 
3.5%
Other values (207) 4055
45.6%

소재지지번주소
Text

MISSING 

Distinct506
Distinct (%)88.0%
Missing48
Missing (%)7.7%
Memory size5.0 KiB
2023-12-12T22:50:38.580402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length43
Mean length21.513043
Min length18

Characters and Unicode

Total characters12370
Distinct characters141
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique456 ?
Unique (%)79.3%

Sample

1st row경기도 성남시 수정구 신흥동 5542-5
2nd row경기도 성남시 수정구 신흥동 4224
3rd row경기도 성남시 수정구 수진동 2201
4th row경기도 성남시 수정구 신흥동 2460-1
5th row경기도 성남시 수정구 신흥동 2024
ValueCountFrequency (%)
경기도 575
19.5%
성남시 575
19.5%
분당구 342
 
11.6%
수정구 134
 
4.6%
중원구 99
 
3.4%
정자동 54
 
1.8%
창곡동 49
 
1.7%
구미동 47
 
1.6%
야탑동 40
 
1.4%
백현동 33
 
1.1%
Other values (526) 994
33.8%
2023-12-12T22:50:39.055998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2907
23.5%
구 623
 
5.0%
동 590
 
4.8%
성 588
 
4.8%
남 585
 
4.7%
도 579
 
4.7%
시 578
 
4.7%
경 576
 
4.7%
기 575
 
4.6%
1 389
 
3.1%
Other values (131) 4380
35.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7235
58.5%
Space Separator 2907
23.5%
Decimal Number 1966
 
15.9%
Dash Punctuation 209
 
1.7%
Open Punctuation 18
 
0.1%
Close Punctuation 18
 
0.1%
Other Punctuation 13
 
0.1%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 623
 
8.6%
동 590
 
8.2%
성 588
 
8.1%
남 585
 
8.1%
도 579
 
8.0%
시 578
 
8.0%
경 576
 
8.0%
기 575
 
7.9%
분 354
 
4.9%
당 354
 
4.9%
Other values (113) 1833
25.3%
Decimal Number
ValueCountFrequency (%)
1 389
19.8%
5 265
13.5%
2 257
13.1%
4 183
9.3%
3 171
8.7%
6 161
8.2%
7 160
8.1%
0 131
 
6.7%
8 128
 
6.5%
9 121
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
K 2
50.0%
B 1
25.0%
S 1
25.0%
Space Separator
ValueCountFrequency (%)
2907
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 209
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Other Punctuation
ValueCountFrequency (%)
, 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7235
58.5%
Common 5131
41.5%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 623
 
8.6%
동 590
 
8.2%
성 588
 
8.1%
남 585
 
8.1%
도 579
 
8.0%
시 578
 
8.0%
경 576
 
8.0%
기 575
 
7.9%
분 354
 
4.9%
당 354
 
4.9%
Other values (113) 1833
25.3%
Common
ValueCountFrequency (%)
2907
56.7%
1 389
 
7.6%
5 265
 
5.2%
2 257
 
5.0%
- 209
 
4.1%
4 183
 
3.6%
3 171
 
3.3%
6 161
 
3.1%
7 160
 
3.1%
0 131
 
2.6%
Other values (5) 298
 
5.8%
Latin
ValueCountFrequency (%)
K 2
50.0%
B 1
25.0%
S 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7235
58.5%
ASCII 5135
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2907
56.6%
1 389
 
7.6%
5 265
 
5.2%
2 257
 
5.0%
- 209
 
4.1%
4 183
 
3.6%
3 171
 
3.3%
6 161
 
3.1%
7 160
 
3.1%
0 131
 
2.6%
Other values (8) 302
 
5.9%
Hangul
ValueCountFrequency (%)
구 623
 
8.6%
동 590
 
8.2%
성 588
 
8.1%
남 585
 
8.1%
도 579
 
8.0%
시 578
 
8.0%
경 576
 
8.0%
기 575
 
7.9%
분 354
 
4.9%
당 354
 
4.9%
Other values (113) 1833
25.3%

설치일자
Date

Distinct60
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
Minimum2018-03-01 00:00:00
Maximum2023-08-09 00:00:00
2023-12-12T22:50:39.247685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:39.433208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

높이_m
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
3.6
195 
3.5
118 
3.3
93 
3
65 
3.4
59 
Other values (10)
93 

Length

Max length4
Median length3
Mean length2.7752809
Min length1

Unique

Unique5 ?
Unique (%)0.8%

Sample

1st row3.3
2nd row3.3
3rd row3.3
4th row3.3
5th row3.3

Common Values

ValueCountFrequency (%)
3.6 195
31.3%
3.5 118
18.9%
3.3 93
14.9%
3 65
 
10.4%
3.4 59
 
9.5%
3.8 41
 
6.6%
3550 20
 
3.2%
18
 
2.9%
3000 6
 
1.0%
<NA> 3
 
0.5%
Other values (5) 5
 
0.8%

Length

2023-12-12T22:50:39.597000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3.6 195
32.2%
3.5 118
19.5%
3.3 93
15.4%
3 65
 
10.7%
3.4 59
 
9.8%
3.8 41
 
6.8%
3550 20
 
3.3%
3000 6
 
1.0%
na 3
 
0.5%
3.7 1
 
0.2%
Other values (4) 4
 
0.7%

펼침지름_m
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
5
227 
4
178 
3
123 
4.4
50 
4400
26 
Other values (6)
 
19

Length

Max length4
Median length1
Mean length1.3418941
Min length1

Unique

Unique3 ?
Unique (%)0.5%

Sample

1st row5
2nd row5
3rd row5
4th row5
5th row5

Common Values

ValueCountFrequency (%)
5 227
36.4%
4 178
28.6%
3 123
19.7%
4.4 50
 
8.0%
4400 26
 
4.2%
3.5 12
 
1.9%
2
 
0.3%
2.5 2
 
0.3%
3500 1
 
0.2%
3.3 1
 
0.2%

Length

2023-12-12T22:50:39.738602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5 227
36.6%
4 178
28.7%
3 123
19.8%
4.4 50
 
8.1%
4400 26
 
4.2%
3.5 12
 
1.9%
2.5 2
 
0.3%
3500 1
 
0.2%
3.3 1
 
0.2%
5.4 1
 
0.2%

원단
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
매쉬
612 
메쉬
 
9
아크릴
 
2

Length

Max length3
Median length2
Mean length2.0032103
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
매쉬 612
98.2%
메쉬 9
 
1.4%
아크릴 2
 
0.3%

Length

2023-12-12T22:50:39.878732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:50:39.996881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
매쉬 612
98.2%
메쉬 9
 
1.4%
아크릴 2
 
0.3%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct607
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.407693
Minimum37.336192
Maximum37.474515
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-12T22:50:40.117705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.336192
5-th percentile37.346339
Q137.373802
median37.405993
Q337.442351
95-th percentile37.469539
Maximum37.474515
Range0.1383228
Interquartile range (IQR)0.0685489

Descriptive statistics

Standard deviation0.038299472
Coefficient of variation (CV)0.0010238395
Kurtosis-1.1582138
Mean37.407693
Median Absolute Deviation (MAD)0.03452001
Skewness-0.052565215
Sum23304.993
Variance0.0014668496
MonotonicityNot monotonic
2023-12-12T22:50:40.251047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4729 5
 
0.8%
37.4274 3
 
0.5%
37.43 2
 
0.3%
37.4088178 2
 
0.3%
37.3751372 2
 
0.3%
37.4444434 2
 
0.3%
37.4459915 2
 
0.3%
37.4430943 2
 
0.3%
37.43031953 2
 
0.3%
37.4302 2
 
0.3%
Other values (597) 599
96.1%
ValueCountFrequency (%)
37.3361923 1
0.2%
37.3366268 1
0.2%
37.3373015 1
0.2%
37.3374736 1
0.2%
37.337515 1
0.2%
37.3376753 1
0.2%
37.3377569 1
0.2%
37.3381114 1
0.2%
37.3383366 1
0.2%
37.3384322 1
0.2%
ValueCountFrequency (%)
37.4745151 1
 
0.2%
37.474035 1
 
0.2%
37.4740186 1
 
0.2%
37.4739078 1
 
0.2%
37.4736688 1
 
0.2%
37.47349797 1
 
0.2%
37.473 1
 
0.2%
37.4729 5
0.8%
37.4726 1
 
0.2%
37.47243824 1
 
0.2%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct607
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.127
Minimum127.0023
Maximum127.17914
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-12T22:50:40.449103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.0023
5-th percentile127.08613
Q1127.11144
median127.1265
Q3127.1445
95-th percentile127.16396
Maximum127.17914
Range0.1768358
Interquartile range (IQR)0.03306325

Descriptive statistics

Standard deviation0.023793734
Coefficient of variation (CV)0.00018716506
Kurtosis0.84369735
Mean127.127
Median Absolute Deviation (MAD)0.0167
Skewness-0.42107694
Sum79200.124
Variance0.00056614176
MonotonicityNot monotonic
2023-12-12T22:50:40.589220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1524 3
 
0.5%
127.0939 3
 
0.5%
127.1004 2
 
0.3%
127.1228248 2
 
0.3%
127.1436 2
 
0.3%
127.1217622 2
 
0.3%
127.1492302 2
 
0.3%
127.1480161 2
 
0.3%
127.1454762 2
 
0.3%
127.1507466 2
 
0.3%
Other values (597) 601
96.5%
ValueCountFrequency (%)
127.0023 1
0.2%
127.0681349 1
0.2%
127.0681663 1
0.2%
127.0681993 1
0.2%
127.0682503 1
0.2%
127.068429 1
0.2%
127.0687556 1
0.2%
127.0689919 1
0.2%
127.0690765 1
0.2%
127.0692122 2
0.3%
ValueCountFrequency (%)
127.1791358 1
0.2%
127.1790266 1
0.2%
127.1787735 1
0.2%
127.1744027 1
0.2%
127.1743183 1
0.2%
127.1743053 1
0.2%
127.1740905 1
0.2%
127.1736781 1
0.2%
127.1729678 1
0.2%
127.1729555 1
0.2%

당해년도 운영시작일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-05-20
623 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-05-20
2nd row2023-05-20
3rd row2023-05-20
4th row2023-05-20
5th row2023-05-20

Common Values

ValueCountFrequency (%)
2023-05-20 623
100.0%

Length

2023-12-12T22:50:40.744815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:50:40.842612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-05-20 623
100.0%

당해년도 운영종료일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-09-30
623 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-30
2nd row2023-09-30
3rd row2023-09-30
4th row2023-09-30
5th row2023-09-30

Common Values

ValueCountFrequency (%)
2023-09-30 623
100.0%

Length

2023-12-12T22:50:40.949027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:50:41.066006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-30 623
100.0%

관리기관
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
분당구 건설과
347 
수정구 건설과
162 
중원구 건설과
114 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수정구 건설과
2nd row수정구 건설과
3rd row수정구 건설과
4th row수정구 건설과
5th row수정구 건설과

Common Values

ValueCountFrequency (%)
분당구 건설과 347
55.7%
수정구 건설과 162
26.0%
중원구 건설과 114
 
18.3%

Length

2023-12-12T22:50:41.172759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:50:41.271920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건설과 623
50.0%
분당구 347
27.8%
수정구 162
 
13.0%
중원구 114
 
9.1%

관리기관 전화번호
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
031-729-7341
347 
031-729-5341
162 
031-729-6341
68 
031-729-6342
46 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row031-729-5341
2nd row031-729-5341
3rd row031-729-5341
4th row031-729-5341
5th row031-729-5341

Common Values

ValueCountFrequency (%)
031-729-7341 347
55.7%
031-729-5341 162
26.0%
031-729-6341 68
 
10.9%
031-729-6342 46
 
7.4%

Length

2023-12-12T22:50:41.398676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:50:41.507349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
031-729-7341 347
55.7%
031-729-5341 162
26.0%
031-729-6341 68
 
10.9%
031-729-6342 46
 
7.4%

구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
고정형
292 
고정형
268 
스마트형
63 

Length

Max length4
Median length4
Mean length3.5698234
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
고정형 292
46.9%
고정형 268
43.0%
스마트형 63
 
10.1%

Length

2023-12-12T22:50:41.629494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:50:41.732367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고정형 560
89.9%
스마트형 63
 
10.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-08-17
623 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-17
2nd row2023-08-17
3rd row2023-08-17
4th row2023-08-17
5th row2023-08-17

Common Values

ValueCountFrequency (%)
2023-08-17 623
100.0%

Length

2023-12-12T22:50:41.853483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:50:41.961070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-17 623
100.0%

Interactions

2023-12-12T22:50:34.149310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:33.926305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:34.275283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:34.044478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:50:42.025973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동명설치일자높이_m펼침지름_m원단위도경도관리기관관리기관 전화번호구분
읍면동명1.0000.9070.7440.6030.7540.9930.9401.0000.9880.903
설치일자0.9071.0000.9640.8810.5570.8240.7530.9870.9740.955
높이_m0.7440.9641.0000.8710.3590.5210.4970.7470.7030.745
펼침지름_m0.6030.8810.8711.0000.0000.3950.4850.5610.5000.652
원단0.7540.5570.3590.0001.0000.2610.1390.4060.1530.385
위도0.9930.8240.5210.3950.2611.0000.6820.8360.7940.777
경도0.9400.7530.4970.4850.1390.6821.0000.7430.8490.725
관리기관1.0000.9870.7470.5610.4060.8360.7431.0001.0000.915
관리기관 전화번호0.9880.9740.7030.5000.1530.7940.8491.0001.0000.624
구분0.9030.9550.7450.6520.3850.7770.7250.9150.6241.000
2023-12-12T22:50:42.139040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
높이_m펼침지름_m관리기관 전화번호구분관리기관읍면동명원단
높이_m1.0000.5960.4790.5690.5720.3040.213
펼침지름_m0.5961.0000.3240.4850.3920.2340.000
관리기관 전화번호0.4790.3241.0000.6430.9990.8900.144
구분0.5690.4850.6431.0000.6440.7000.139
관리기관0.5720.3920.9990.6441.0000.9610.150
읍면동명0.3040.2340.8900.7000.9611.0000.500
원단0.2130.0000.1440.1390.1500.5001.000
2023-12-12T22:50:42.264375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도읍면동명높이_m펼침지름_m원단관리기관관리기관 전화번호구분
위도1.0000.6830.8420.2390.1800.1600.7420.6130.654
경도0.6831.0000.6920.2440.2530.0870.6410.5220.616
읍면동명0.8420.6921.0000.3040.2340.5000.9610.8900.700
높이_m0.2390.2440.3041.0000.5960.2130.5720.4790.569
펼침지름_m0.1800.2530.2340.5961.0000.0000.3920.3240.485
원단0.1600.0870.5000.2130.0001.0000.1500.1440.139
관리기관0.7420.6410.9610.5720.3920.1501.0000.9990.644
관리기관 전화번호0.6130.5220.8900.4790.3240.1440.9991.0000.643
구분0.6540.6160.7000.5690.4850.1390.6440.6431.000

Missing values

2023-12-12T22:50:34.453548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:50:35.036499image/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.
2023-12-12T22:50:35.199816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

기준년도시군명읍면동명관리번호설치장소명소재지도로명주소소재지지번주소설치일자높이_m펼침지름_m원단위도경도당해년도 운영시작일자당해년도 운영종료일자관리기관관리기관 전화번호구분데이터기준일자
02023성남시신흥1동수정로(신흥1동-3)교보빌딩 앞경기도 성남시 수정구 수정로 150 (신흥동)경기도 성남시 수정구 신흥동 5542-52018-07-013.35매쉬37.442078127.1363682023-05-202023-09-30수정구 건설과031-729-5341고정형2023-08-17
12023성남시신흥1동산성대로(신흥1동-1)신흥사거리 비와이씨 앞 교통섬경기도 성남시 수정구 산성대로 241 (신흥동)경기도 성남시 수정구 신흥동 42242018-07-023.35매쉬37.439876127.1442162023-05-202023-09-30수정구 건설과031-729-5341고정형2023-08-17
22023성남시신흥1동산성대로(신흥1동-2)수진역 3번출구 방향 교통섬경기도 성남시 수정구 산성대로 199 (수진동)경기도 성남시 수정구 수진동 22012018-07-023.35매쉬37.437791127.1405492023-05-202023-09-30수정구 건설과031-729-5341고정형2023-08-17
32023성남시신흥2동공원로(신흥2동-3)신흥동 2460-1 횡단보도<NA>경기도 성남시 수정구 신흥동 2460-12018-07-013.35매쉬37.444662127.1557822023-05-202023-09-30수정구 건설과031-729-5341고정형2023-08-17
42023성남시신흥2동공원로(신흥2동-8)두산아파트 103동경기도 성남시 수정구 공원로 360 (신흥동, 두산아파트)경기도 성남시 수정구 신흥동 20242019-08-013.35매쉬37.444088127.1497632023-05-202023-09-30수정구 건설과031-729-5341고정형2023-08-17
52023성남시신흥2동공원로(신흥2동-9)청구아파트 상가동경기도 성남시 수정구 공원로 340 (신흥동, 청구아파트)경기도 성남시 수정구 신흥동 2464-12020-05-043.85매쉬37.443423127.1511912023-05-202023-09-30수정구 건설과031-729-5341고정형2023-08-17
62023성남시신흥2동수정로(신흥2동-1)성남초등학교앞 교차로 수정구청측 교통섬경기도 성남시 수정구 수정로 251 (신흥동)경기도 성남시 수정구 신흥동 113-22019-05-013.35매쉬37.446456127.1452622023-05-202023-09-30수정구 건설과031-729-5341고정형2023-08-17
72023성남시신흥2동수정로(신흥2동-7)세븐일레븐 앞경기도 성남시 수정구 수정로 259 (신흥동)경기도 성남시 수정구 신흥동 74-22019-08-013.34매쉬37.448027127.1450942023-05-202023-09-30수정구 건설과031-729-5341고정형2023-08-17
82023성남시신흥2동희망로(신흥2동-6)산성동삼거리 셀레스빌 앞경기도 성남시 수정구 수정로 318 (신흥동)경기도 성남시 수정구 신흥동 1252019-05-013.35매쉬37.452064127.1494722023-05-202023-09-30수정구 건설과031-729-5341고정형2023-08-17
92023성남시신흥2동공원로(신흥2동-10)두산아파트 상가동경기도 성남시 수정구 공원로 360 (신흥동, 두산아파트)경기도 성남시 수정구 신흥동 20242020-05-043.85매쉬37.444897127.1482792023-05-202023-09-30수정구 건설과031-729-5341고정형2023-08-17
기준년도시군명읍면동명관리번호설치장소명소재지도로명주소소재지지번주소설치일자높이_m펼침지름_m원단위도경도당해년도 운영시작일자당해년도 운영종료일자관리기관관리기관 전화번호구분데이터기준일자
6132023성남시운중동운중동-19판교대장초 사거리(판교대장초 방향)경기도 성남시 분당구 대장동 187-12023-06-0534.4매쉬37.367712127.070872023-05-202023-09-30분당구 건설과031-729-7341스마트형2023-08-17
6142023성남시운중동운중동-20힐스테이트 엘포레 4단지 정문경기도 성남시 분당구 대장동 250-22023-06-0534.4매쉬37.365107127.0700572023-05-202023-09-30분당구 건설과031-729-7341스마트형2023-08-17
6152023성남시운중동운중동-21힐스테이트 엘포레 4단지(12단지 맞은편)경기도 성남시 분당구 대장동 산 102023-06-0534.4매쉬37.365124127.0708892023-05-202023-09-30분당구 건설과031-729-7341스마트형2023-08-17
6162023성남시운중동운중동-22푸르지오 1단지 정문 앞경기도 성남시 분당구 대장동 52-22023-06-0534.4매쉬37.373668127.0703282023-05-202023-09-30분당구 건설과031-729-7341스마트형2023-08-17
6172023성남시운중동운중동-23푸르지오 1단지 정문 맞은편경기도 성남시 분당구 대장동 73-22023-06-0534.4매쉬37.373551127.0702052023-05-202023-09-30분당구 건설과031-729-7341스마트형2023-08-17
6182023성남시운중동운중동-24푸르지오 2단지 정문 앞경기도 성남시 분당구 대장동 712023-06-0534.4매쉬37.37422127.0692122023-05-202023-09-30분당구 건설과031-729-7341스마트형2023-08-17
6192023성남시운중동운중동-25푸르지오 2단지 정문 맞은편경기도 성남시 분당구 대장동 산 19-12023-06-0534.4매쉬37.374032127.0692122023-05-202023-09-30분당구 건설과031-729-7341스마트형2023-08-17
6202023성남시운중동운중동-261단지 102동 앞(삼거리방면)경기도 성남시 분당구 대장동 42023-06-0534.4매쉬37.372877127.0709232023-05-202023-09-30분당구 건설과031-729-7341스마트형2023-08-17
6212023성남시운중동운중동-27삼거리방면경기도 성남시 분당구 대장동 42023-06-0534.4매쉬37.372802127.0707282023-05-202023-09-30분당구 건설과031-729-7341스마트형2023-08-17
6222023성남시운중동운중동-28삼거리방면경기도 성남시 분당구 대장동 42023-06-0534.4매쉬37.372677127.070872023-05-202023-09-30분당구 건설과031-729-7341스마트형2023-08-17