Overview

Dataset statistics

Number of variables8
Number of observations33
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory72.0 B

Variable types

Numeric3
Text3
Categorical1
DateTime1

Dataset

Description구로구 어린이보호구역 내 옐로카펫 설치 현황으로 옐로카펫은 초등학교 통학로에 위치한 횡단보도 바닥과 벽에 노란색 알루미늄 스티커를 부착해 외부와 구별된 공간을 만들어 어린이의 안전한 보행을 돕는 시설물이다.
Author서울특별시 구로구
URLhttps://www.data.go.kr/data/15039703/fileData.do

Alerts

데이터기준일자 has constant value ""Constant

Reproduction

Analysis started2023-12-12 09:06:24.263183
Analysis finished2023-12-12 09:06:25.926214
Duration1.66 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

설치연도
Real number (ℝ)

Distinct7
Distinct (%)21.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.5152
Minimum2016
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T18:06:25.988493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2016
5-th percentile2017
Q12018
median2019
Q32020
95-th percentile2022.4
Maximum2023
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.9059317
Coefficient of variation (CV)0.00094375708
Kurtosis-0.75093123
Mean2019.5152
Median Absolute Deviation (MAD)1
Skewness0.20584544
Sum66644
Variance3.6325758
MonotonicityIncreasing
2023-12-12T18:06:26.116170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2019 9
27.3%
2020 7
21.2%
2022 6
18.2%
2017 5
15.2%
2018 3
 
9.1%
2023 2
 
6.1%
2016 1
 
3.0%
ValueCountFrequency (%)
2016 1
 
3.0%
2017 5
15.2%
2018 3
 
9.1%
2019 9
27.3%
2020 7
21.2%
2022 6
18.2%
2023 2
 
6.1%
ValueCountFrequency (%)
2023 2
 
6.1%
2022 6
18.2%
2020 7
21.2%
2019 9
27.3%
2018 3
 
9.1%
2017 5
15.2%
2016 1
 
3.0%

설치장소
Text

Distinct29
Distinct (%)87.9%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-12T18:06:26.326218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length5.9090909
Min length3

Characters and Unicode

Total characters195
Distinct characters74
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row온수초
2nd row오류남초
3rd row덕의초
4th row구일초
5th row신도림초
ValueCountFrequency (%)
앞 3
 
6.4%
매봉초 2
 
4.3%
오류남초 2
 
4.3%
덕의초 2
 
4.3%
구로초 2
 
4.3%
정문 2
 
4.3%
횡단보도 2
 
4.3%
매화마을 1
 
2.1%
대각선 1
 
2.1%
항동초(연동로 1
 
2.1%
Other values (29) 29
61.7%
2023-12-12T18:06:26.717588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
초 28
 
14.4%
14
 
7.2%
구 8
 
4.1%
로 8
 
4.1%
동 7
 
3.6%
정 5
 
2.6%
( 5
 
2.6%
) 5
 
2.6%
오 4
 
2.1%
항 4
 
2.1%
Other values (64) 107
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 163
83.6%
Space Separator 14
 
7.2%
Decimal Number 6
 
3.1%
Open Punctuation 5
 
2.6%
Close Punctuation 5
 
2.6%
Uppercase Letter 2
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
초 28
 
17.2%
구 8
 
4.9%
로 8
 
4.9%
동 7
 
4.3%
정 5
 
3.1%
오 4
 
2.5%
항 4
 
2.5%
앞 4
 
2.5%
고 4
 
2.5%
매 3
 
1.8%
Other values (55) 88
54.0%
Decimal Number
ValueCountFrequency (%)
1 2
33.3%
6 2
33.3%
9 1
16.7%
2 1
16.7%
Uppercase Letter
ValueCountFrequency (%)
L 1
50.0%
G 1
50.0%
Space Separator
ValueCountFrequency (%)
14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 163
83.6%
Common 30
 
15.4%
Latin 2
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
초 28
 
17.2%
구 8
 
4.9%
로 8
 
4.9%
동 7
 
4.3%
정 5
 
3.1%
오 4
 
2.5%
항 4
 
2.5%
앞 4
 
2.5%
고 4
 
2.5%
매 3
 
1.8%
Other values (55) 88
54.0%
Common
ValueCountFrequency (%)
14
46.7%
( 5
 
16.7%
) 5
 
16.7%
1 2
 
6.7%
6 2
 
6.7%
9 1
 
3.3%
2 1
 
3.3%
Latin
ValueCountFrequency (%)
L 1
50.0%
G 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 163
83.6%
ASCII 32
 
16.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
초 28
 
17.2%
구 8
 
4.9%
로 8
 
4.9%
동 7
 
4.3%
정 5
 
3.1%
오 4
 
2.5%
항 4
 
2.5%
앞 4
 
2.5%
고 4
 
2.5%
매 3
 
1.8%
Other values (55) 88
54.0%
ASCII
ValueCountFrequency (%)
14
43.8%
( 5
 
15.6%
) 5
 
15.6%
1 2
 
6.2%
6 2
 
6.2%
9 1
 
3.1%
2 1
 
3.1%
L 1
 
3.1%
G 1
 
3.1%

설치개소
Categorical

Distinct3
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
1
20 
2
12 
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.0%

Sample

1st row1
2nd row1
3rd row1
4th row2
5th row1

Common Values

ValueCountFrequency (%)
1 20
60.6%
2 12
36.4%
3 1
 
3.0%

Length

2023-12-12T18:06:26.906220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:06:27.056525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 20
60.6%
2 12
36.4%
3 1
 
3.0%

도로명주소
Text

Distinct29
Distinct (%)87.9%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-12T18:06:27.280281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length18.181818
Min length15

Characters and Unicode

Total characters600
Distinct characters48
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row서울특별시 구로구 부일로 893
2nd row서울특별시 구로구 서해안로24길 22
3rd row서울특별시 구로구 고척로 213
4th row서울특별시 구로구 구일로 68
5th row서울특별시 구로구 신도림로19길 44
ValueCountFrequency (%)
서울특별시 33
25.0%
구로구 33
25.0%
연동로 4
 
3.0%
고척로 4
 
3.0%
213 3
 
2.3%
178 3
 
2.3%
구로중앙로27나길 2
 
1.5%
9 2
 
1.5%
22 2
 
1.5%
서해안로24길 2
 
1.5%
Other values (42) 44
33.3%
2023-12-12T18:06:27.730661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
83
13.8%
구 70
11.7%
로 69
11.5%
서 36
 
6.0%
특 33
 
5.5%
별 33
 
5.5%
시 33
 
5.5%
울 33
 
5.5%
2 21
 
3.5%
1 19
 
3.2%
Other values (38) 170
28.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 396
66.0%
Decimal Number 105
 
17.5%
Space Separator 99
 
16.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 70
17.7%
로 69
17.4%
서 36
9.1%
특 33
8.3%
별 33
8.3%
시 33
8.3%
울 33
8.3%
길 17
 
4.3%
척 7
 
1.8%
고 7
 
1.8%
Other values (26) 58
14.6%
Decimal Number
ValueCountFrequency (%)
2 21
20.0%
1 19
18.1%
3 12
11.4%
4 10
9.5%
7 10
9.5%
5 7
 
6.7%
6 7
 
6.7%
8 7
 
6.7%
9 7
 
6.7%
0 5
 
4.8%
Space Separator
ValueCountFrequency (%)
83
83.8%
  16
 
16.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 396
66.0%
Common 204
34.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 70
17.7%
로 69
17.4%
서 36
9.1%
특 33
8.3%
별 33
8.3%
시 33
8.3%
울 33
8.3%
길 17
 
4.3%
척 7
 
1.8%
고 7
 
1.8%
Other values (26) 58
14.6%
Common
ValueCountFrequency (%)
83
40.7%
2 21
 
10.3%
1 19
 
9.3%
  16
 
7.8%
3 12
 
5.9%
4 10
 
4.9%
7 10
 
4.9%
5 7
 
3.4%
6 7
 
3.4%
8 7
 
3.4%
Other values (2) 12
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 396
66.0%
ASCII 188
31.3%
None 16
 
2.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
83
44.1%
2 21
 
11.2%
1 19
 
10.1%
3 12
 
6.4%
4 10
 
5.3%
7 10
 
5.3%
5 7
 
3.7%
6 7
 
3.7%
8 7
 
3.7%
9 7
 
3.7%
Hangul
ValueCountFrequency (%)
구 70
17.7%
로 69
17.4%
서 36
9.1%
특 33
8.3%
별 33
8.3%
시 33
8.3%
울 33
8.3%
길 17
 
4.3%
척 7
 
1.8%
고 7
 
1.8%
Other values (26) 58
14.6%
None
ValueCountFrequency (%)
  16
100.0%

지번주소
Text

Distinct29
Distinct (%)87.9%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-12T18:06:27.980976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length18.69697
Min length16

Characters and Unicode

Total characters617
Distinct characters37
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row서울특별시 구로구 온수동 9-34
2nd row서울특별시 구로구 오류동 332-59
3rd row서울특별시 구로구 고척동 287-8
4th row서울특별시 구로구 구로동 685-221
5th row서울특별시 구로구 신도림동 302-65
ValueCountFrequency (%)
서울특별시 33
24.8%
구로구 33
24.8%
구로동 9
 
6.8%
고척동 7
 
5.3%
오류동 5
 
3.8%
항동 4
 
3.0%
신도림동 2
 
1.5%
천왕동 2
 
1.5%
160-3 2
 
1.5%
332-59 2
 
1.5%
Other values (30) 34
25.6%
2023-12-12T18:06:28.418923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
84
13.6%
구 75
 
12.2%
로 42
 
6.8%
서 33
 
5.3%
동 33
 
5.3%
특 33
 
5.3%
별 33
 
5.3%
시 33
 
5.3%
울 33
 
5.3%
- 24
 
3.9%
Other values (27) 194
31.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 361
58.5%
Decimal Number 131
 
21.2%
Space Separator 101
 
16.4%
Dash Punctuation 24
 
3.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 75
20.8%
로 42
11.6%
서 33
9.1%
동 33
9.1%
특 33
9.1%
별 33
9.1%
시 33
9.1%
울 33
9.1%
척 7
 
1.9%
고 7
 
1.9%
Other values (14) 32
8.9%
Decimal Number
ValueCountFrequency (%)
1 23
17.6%
3 20
15.3%
2 19
14.5%
6 14
10.7%
5 11
8.4%
7 11
8.4%
8 10
7.6%
9 9
 
6.9%
0 8
 
6.1%
4 6
 
4.6%
Space Separator
ValueCountFrequency (%)
84
83.2%
  17
 
16.8%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 361
58.5%
Common 256
41.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 75
20.8%
로 42
11.6%
서 33
9.1%
동 33
9.1%
특 33
9.1%
별 33
9.1%
시 33
9.1%
울 33
9.1%
척 7
 
1.9%
고 7
 
1.9%
Other values (14) 32
8.9%
Common
ValueCountFrequency (%)
84
32.8%
- 24
 
9.4%
1 23
 
9.0%
3 20
 
7.8%
2 19
 
7.4%
  17
 
6.6%
6 14
 
5.5%
5 11
 
4.3%
7 11
 
4.3%
8 10
 
3.9%
Other values (3) 23
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 361
58.5%
ASCII 239
38.7%
None 17
 
2.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
84
35.1%
- 24
 
10.0%
1 23
 
9.6%
3 20
 
8.4%
2 19
 
7.9%
6 14
 
5.9%
5 11
 
4.6%
7 11
 
4.6%
8 10
 
4.2%
9 9
 
3.8%
Other values (2) 14
 
5.9%
Hangul
ValueCountFrequency (%)
구 75
20.8%
로 42
11.6%
서 33
9.1%
동 33
9.1%
특 33
9.1%
별 33
9.1%
시 33
9.1%
울 33
9.1%
척 7
 
1.9%
고 7
 
1.9%
Other values (14) 32
8.9%
None
ValueCountFrequency (%)
  17
100.0%

위도
Real number (ℝ)

Distinct29
Distinct (%)87.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.49494
Minimum37.477016
Maximum37.511984
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T18:06:28.604646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.477016
5-th percentile37.477016
Q137.488961
median37.497309
Q337.504915
95-th percentile37.506476
Maximum37.511984
Range0.03496885
Interquartile range (IQR)0.01595441

Descriptive statistics

Standard deviation0.0096728253
Coefficient of variation (CV)0.00025797682
Kurtosis-0.79356869
Mean37.49494
Median Absolute Deviation (MAD)0.00762244
Skewness-0.32954689
Sum1237.333
Variance9.356355 × 10-5
MonotonicityNot monotonic
2023-12-12T18:06:28.794301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
37.47701554 2
 
6.1%
37.50603176 2
 
6.1%
37.50491523 2
 
6.1%
37.48968652 2
 
6.1%
37.49400506 1
 
3.0%
37.48896082 1
 
3.0%
37.48538076 1
 
3.0%
37.49730896 1
 
3.0%
37.50094407 1
 
3.0%
37.49746208 1
 
3.0%
Other values (19) 19
57.6%
ValueCountFrequency (%)
37.47701554 2
6.1%
37.47701589 1
3.0%
37.48145598 1
3.0%
37.48415943 1
3.0%
37.48420602 1
3.0%
37.48538076 1
3.0%
37.48607123 1
3.0%
37.48896082 1
3.0%
37.48968652 2
6.1%
37.49016566 1
3.0%
ValueCountFrequency (%)
37.51198439 1
3.0%
37.50714192 1
3.0%
37.50603176 2
6.1%
37.50602797 1
3.0%
37.50510665 1
3.0%
37.5050561 1
3.0%
37.50491523 2
6.1%
37.50094407 1
3.0%
37.49966003 1
3.0%
37.49897255 1
3.0%

경도
Real number (ℝ)

Distinct29
Distinct (%)87.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.85607
Minimum126.82075
Maximum126.89558
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T18:06:28.976122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.82075
5-th percentile126.82377
Q1126.83911
median126.85675
Q3126.87955
95-th percentile126.89124
Maximum126.89558
Range0.0748314
Interquartile range (IQR)0.04044

Descriptive statistics

Standard deviation0.024576743
Coefficient of variation (CV)0.00019373722
Kurtosis-1.3671814
Mean126.85607
Median Absolute Deviation (MAD)0.0201567
Skewness0.15187239
Sum4186.2504
Variance0.00060401631
MonotonicityNot monotonic
2023-12-12T18:06:29.142775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
126.8239854 2
 
6.1%
126.8573487 2
 
6.1%
126.8443653 2
 
6.1%
126.8391127 2
 
6.1%
126.8259667 1
 
3.0%
126.8955833 1
 
3.0%
126.8234361 1
 
3.0%
126.8396924 1
 
3.0%
126.8567476 1
 
3.0%
126.8865547 1
 
3.0%
Other values (19) 19
57.6%
ValueCountFrequency (%)
126.8207519 1
3.0%
126.8234361 1
3.0%
126.8239854 2
6.1%
126.8241103 1
3.0%
126.8259667 1
3.0%
126.8264392 1
3.0%
126.8370629 1
3.0%
126.8391127 2
6.1%
126.8396924 1
3.0%
126.841482 1
3.0%
ValueCountFrequency (%)
126.8955833 1
3.0%
126.8927802 1
3.0%
126.8902182 1
3.0%
126.8897631 1
3.0%
126.8880803 1
3.0%
126.8865547 1
3.0%
126.8865543 1
3.0%
126.8832546 1
3.0%
126.8795527 1
3.0%
126.8769043 1
3.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
Minimum2023-08-31 00:00:00
Maximum2023-08-31 00:00:00
2023-12-12T18:06:29.297882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:06:29.401367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T18:06:25.333452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:06:24.613833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:06:24.975451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:06:25.441294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:06:24.718749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:06:25.096009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:06:25.562101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:06:24.827647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:06:25.203039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:06:29.507508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치연도설치장소설치개소도로명주소지번주소위도경도
설치연도1.0000.5040.7110.0000.0000.0000.000
설치장소0.5041.0000.9000.9950.9951.0001.000
설치개소0.7110.9001.0000.9630.9630.3330.000
도로명주소0.0000.9950.9631.0001.0001.0001.000
지번주소0.0000.9950.9631.0001.0001.0001.000
위도0.0001.0000.3331.0001.0001.0000.504
경도0.0001.0000.0001.0001.0000.5041.000
2023-12-12T18:06:29.681122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치연도위도경도설치개소
설치연도1.000-0.213-0.2540.333
위도-0.2131.0000.3960.161
경도-0.2540.3961.0000.000
설치개소0.3330.1610.0001.000

Missing values

2023-12-12T18:06:25.705423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:06:25.870729image/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

설치연도설치장소설치개소도로명주소지번주소위도경도데이터기준일자
02016온수초1서울특별시 구로구 부일로 893서울특별시 구로구 온수동 9-3437.494005126.8259672023-08-31
12017오류남초1서울특별시 구로구 서해안로24길 22서울특별시 구로구 오류동 332-5937.489687126.8391132023-08-31
22017덕의초1서울특별시 구로구 고척로 213서울특별시 구로구 고척동 287-837.506028126.8573462023-08-31
32017구일초2서울특별시 구로구 구일로 68서울특별시 구로구 구로동 685-22137.493192126.8734732023-08-31
42017신도림초1서울특별시 구로구 신도림로19길 44서울특별시 구로구 신도림동 302-6537.511984126.8832552023-08-31
52017고산초1서울특별시 구로구 중앙로 6서울특별시 구로구 고척동 76-38037.498973126.8647732023-08-31
62018구로초1서울특별시 구로구 구로중앙로27나길 9서울특별시 구로구 구로동 44337.497462126.8865542023-08-31
72018세곡초2서울특별시 구로구 고척로33길 34서울특별시 구로구 고척동 253-12937.505056126.849122023-08-31
82018동구로초2서울특별시 구로구 구로중앙로14길 43서울특별시 구로구 구로동 9337.494071126.892782023-08-31
92019미래초1서울특별시 구로구 새말로 73서울특별시 구로구 구로동 556-137.505107126.888082023-08-31
설치연도설치장소설치개소도로명주소지번주소위도경도데이터기준일자
232020오정초1서울특별시 구로구 경인로2길 10서울특별시 구로구 오류동 108-2837.490166126.8264392023-08-31
242020매봉초1서울특별시 구로구 고척로21길 55서울특별시 구로구 개봉동 7-3737.504915126.8443652023-08-31
252022구로초2서울특별시 구로구 구로중앙로27나길 9서울특별시 구로구 구로동 44337.497462126.8865552023-08-31
262022고척초(시설 정문 앞 대각선 횡단보도)2서울특별시 구로구 경서로 31서울특별시 구로구 고척동 129-337.500944126.8567482023-08-31
272022덕의초2서울특별시 구로구 고척로 213서울특별시 구로구 고척동 21737.506032126.8573492023-08-31
282022항동초(연동로 169 매화마을 입구 앞)2서울특별시 구로구 연동로 178서울특별시 구로구 항동 160-337.477016126.8239852023-08-31
292022나비유치원2서울특별시 구로구 고척로 30서울특별시 구로구 오류동 11-1637.497309126.8396922023-08-31
302022항동어린이집2서울특별시 구로구 연동로 284서울특별시 구로구 항동 12-1937.485381126.8234362023-08-31
312023덕의초(고척로 216 앞(정문 옆 횡단보도))1서울특별시 구로구 고척로 213서울특별시 구로구 고척동 21737.506032126.8573492023-08-31
322023항동초(시설 정문 앞)2서울특별시 구로구 연동로 178서울특별시 구로구 항동 160-337.477016126.8239852023-08-31