Overview

Dataset statistics

Number of variables16
Number of observations3006
Missing cells4053
Missing cells (%)8.4%
Duplicate rows214
Duplicate rows (%)7.1%
Total size in memory387.6 KiB
Average record size in memory132.0 B

Variable types

Categorical3
Text5
Numeric4
Boolean3
DateTime1

Dataset

Description자전거 보관소 현황(제공표준)
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=6T98794V0223GQQ9O1P421484027&infSeq=1

Alerts

수리대설치여부 has constant value ""Constant
Dataset has 214 (7.1%) duplicate rowsDuplicates
위도 is highly overall correlated with 시군명High correlation
경도 is highly overall correlated with 시군명High correlation
설치연도 is highly overall correlated with 시군명 and 2 other fieldsHigh correlation
시군명 is highly overall correlated with 위도 and 5 other fieldsHigh correlation
설치형태 is highly overall correlated with 설치연도 and 1 other fieldsHigh correlation
차양막설치여부 is highly overall correlated with 시군명High correlation
공기주입기비치여부 is highly overall correlated with 공기주입기유형High correlation
공기주입기유형 is highly overall correlated with 설치연도 and 2 other fieldsHigh correlation
공기주입기비치여부 is highly imbalanced (51.4%)Imbalance
공기주입기유형 is highly imbalanced (69.8%)Imbalance
소재지도로명주소 has 510 (17.0%) missing valuesMissing
설치연도 has 2137 (71.1%) missing valuesMissing
차양막설치여부 has 1406 (46.8%) missing valuesMissing

Reproduction

Analysis started2024-04-29 13:03:56.630212
Analysis finished2024-04-29 13:04:01.445453
Duration4.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
화성시
475 
부천시
436 
수원시
400 
성남시
362 
고양시
187 
Other values (20)
1146 

Length

Max length4
Median length3
Mean length3.0658683
Min length3

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
화성시 475
15.8%
부천시 436
14.5%
수원시 400
13.3%
성남시 362
12.0%
고양시 187
 
6.2%
파주시 178
 
5.9%
의정부시 117
 
3.9%
구리시 115
 
3.8%
의왕시 99
 
3.3%
양주시 89
 
3.0%
Other values (15) 548
18.2%

Length

2024-04-29T22:04:01.501000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
화성시 475
15.8%
부천시 436
14.5%
수원시 400
13.3%
성남시 362
12.0%
고양시 187
 
6.2%
파주시 178
 
5.9%
의정부시 117
 
3.9%
구리시 115
 
3.8%
의왕시 99
 
3.3%
양주시 89
 
3.0%
Other values (15) 548
18.2%

자전거보관소명
Text

Distinct2629
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
2024-04-29T22:04:01.716681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length28
Mean length8.489022
Min length2

Characters and Unicode

Total characters25518
Distinct characters567
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2317 ?
Unique (%)77.1%

Sample

1st row조리읍사무소
2nd row광탄면사무소
3rd row운정스포츠센터축구장 앞
4th row운정스포츠센터축구장 맞은편
5th row운정스포츠센터 정문 앞(좌측 약100m)
ValueCountFrequency (%)
앞 413
 
8.2%
옆 62
 
1.2%
출구 48
 
1.0%
버스정류장 44
 
0.9%
내 39
 
0.8%
주민센터 36
 
0.7%
주변 32
 
0.6%
공원 25
 
0.5%
1번출구 25
 
0.5%
뒤 24
 
0.5%
Other values (2855) 4299
85.2%
2024-04-29T22:04:02.086050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2043
 
8.0%
교 711
 
2.8%
동 645
 
2.5%
앞 563
 
2.2%
원 492
 
1.9%
학 424
 
1.7%
장 395
 
1.5%
정 390
 
1.5%
1 360
 
1.4%
공 350
 
1.4%
Other values (557) 19145
75.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20917
82.0%
Space Separator 2043
 
8.0%
Decimal Number 1479
 
5.8%
Close Punctuation 333
 
1.3%
Open Punctuation 333
 
1.3%
Uppercase Letter 229
 
0.9%
Dash Punctuation 84
 
0.3%
Other Punctuation 65
 
0.3%
Lowercase Letter 19
 
0.1%
Math Symbol 15
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 711
 
3.4%
동 645
 
3.1%
앞 563
 
2.7%
원 492
 
2.4%
학 424
 
2.0%
장 395
 
1.9%
정 390
 
1.9%
공 350
 
1.7%
주 348
 
1.7%
구 337
 
1.6%
Other values (497) 16262
77.7%
Uppercase Letter
ValueCountFrequency (%)
B 57
24.9%
S 53
23.1%
K 18
 
7.9%
P 18
 
7.9%
G 15
 
6.6%
T 14
 
6.1%
A 14
 
6.1%
C 8
 
3.5%
I 6
 
2.6%
D 5
 
2.2%
Other values (11) 21
 
9.2%
Lowercase Letter
ValueCountFrequency (%)
a 2
10.5%
e 2
10.5%
n 2
10.5%
m 2
10.5%
b 2
10.5%
k 2
10.5%
i 1
 
5.3%
z 1
 
5.3%
o 1
 
5.3%
l 1
 
5.3%
Other values (3) 3
15.8%
Decimal Number
ValueCountFrequency (%)
1 360
24.3%
2 273
18.5%
3 165
11.2%
5 148
10.0%
4 116
 
7.8%
0 98
 
6.6%
7 95
 
6.4%
6 89
 
6.0%
8 74
 
5.0%
9 61
 
4.1%
Other Punctuation
ValueCountFrequency (%)
, 38
58.5%
/ 14
 
21.5%
? 5
 
7.7%
. 4
 
6.2%
@ 1
 
1.5%
· 1
 
1.5%
& 1
 
1.5%
# 1
 
1.5%
Close Punctuation
ValueCountFrequency (%)
) 331
99.4%
] 2
 
0.6%
Open Punctuation
ValueCountFrequency (%)
( 331
99.4%
[ 2
 
0.6%
Space Separator
ValueCountFrequency (%)
2043
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%
Math Symbol
ValueCountFrequency (%)
~ 15
100.0%
Letter Number
ValueCountFrequency (%)
Ⅶ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20917
82.0%
Common 4352
 
17.1%
Latin 249
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 711
 
3.4%
동 645
 
3.1%
앞 563
 
2.7%
원 492
 
2.4%
학 424
 
2.0%
장 395
 
1.9%
정 390
 
1.9%
공 350
 
1.7%
주 348
 
1.7%
구 337
 
1.6%
Other values (497) 16262
77.7%
Latin
ValueCountFrequency (%)
B 57
22.9%
S 53
21.3%
K 18
 
7.2%
P 18
 
7.2%
G 15
 
6.0%
T 14
 
5.6%
A 14
 
5.6%
C 8
 
3.2%
I 6
 
2.4%
D 5
 
2.0%
Other values (25) 41
16.5%
Common
ValueCountFrequency (%)
2043
46.9%
1 360
 
8.3%
) 331
 
7.6%
( 331
 
7.6%
2 273
 
6.3%
3 165
 
3.8%
5 148
 
3.4%
4 116
 
2.7%
0 98
 
2.3%
7 95
 
2.2%
Other values (15) 392
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20915
82.0%
ASCII 4599
 
18.0%
Compat Jamo 2
 
< 0.1%
None 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2043
44.4%
1 360
 
7.8%
) 331
 
7.2%
( 331
 
7.2%
2 273
 
5.9%
3 165
 
3.6%
5 148
 
3.2%
4 116
 
2.5%
0 98
 
2.1%
7 95
 
2.1%
Other values (48) 639
 
13.9%
Hangul
ValueCountFrequency (%)
교 711
 
3.4%
동 645
 
3.1%
앞 563
 
2.7%
원 492
 
2.4%
학 424
 
2.0%
장 395
 
1.9%
정 390
 
1.9%
공 350
 
1.7%
주 348
 
1.7%
구 337
 
1.6%
Other values (496) 16260
77.7%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
100.0%
None
ValueCountFrequency (%)
· 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅶ 1
100.0%

소재지도로명주소
Text

MISSING 

Distinct2011
Distinct (%)80.6%
Missing510
Missing (%)17.0%
Memory size23.6 KiB
2024-04-29T22:04:02.371630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length18.018029
Min length12

Characters and Unicode

Total characters44973
Distinct characters303
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1651 ?
Unique (%)66.1%

Sample

1st row경기도 파주시 봉천로 64
2nd row경기도 파주시 광탄면 혜음로 1044
3rd row경기도 부천시 부흥로303번길 50
4th row경기도 부천시 심중로119번길 8
5th row경기도 부천시 심중로 121
ValueCountFrequency (%)
경기도 2496
 
22.8%
부천시 436
 
4.0%
성남시 362
 
3.3%
수원시 342
 
3.1%
분당구 269
 
2.5%
화성시 254
 
2.3%
고양시 187
 
1.7%
일산동구 118
 
1.1%
의정부시 108
 
1.0%
영통구 103
 
0.9%
Other values (1830) 6269
57.3%
2024-04-29T22:04:02.791552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8449
18.8%
시 2585
 
5.7%
경 2558
 
5.7%
기 2530
 
5.6%
도 2521
 
5.6%
로 2260
 
5.0%
1 1624
 
3.6%
2 1179
 
2.6%
구 999
 
2.2%
3 871
 
1.9%
Other values (293) 19397
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28121
62.5%
Space Separator 8449
 
18.8%
Decimal Number 8113
 
18.0%
Dash Punctuation 290
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 2585
 
9.2%
경 2558
 
9.1%
기 2530
 
9.0%
도 2521
 
9.0%
로 2260
 
8.0%
구 999
 
3.6%
성 765
 
2.7%
길 734
 
2.6%
천 687
 
2.4%
부 651
 
2.3%
Other values (281) 11831
42.1%
Decimal Number
ValueCountFrequency (%)
1 1624
20.0%
2 1179
14.5%
3 871
10.7%
5 749
9.2%
4 727
9.0%
6 652
8.0%
0 632
 
7.8%
7 601
 
7.4%
9 559
 
6.9%
8 519
 
6.4%
Space Separator
ValueCountFrequency (%)
8449
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 290
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28121
62.5%
Common 16852
37.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 2585
 
9.2%
경 2558
 
9.1%
기 2530
 
9.0%
도 2521
 
9.0%
로 2260
 
8.0%
구 999
 
3.6%
성 765
 
2.7%
길 734
 
2.6%
천 687
 
2.4%
부 651
 
2.3%
Other values (281) 11831
42.1%
Common
ValueCountFrequency (%)
8449
50.1%
1 1624
 
9.6%
2 1179
 
7.0%
3 871
 
5.2%
5 749
 
4.4%
4 727
 
4.3%
6 652
 
3.9%
0 632
 
3.8%
7 601
 
3.6%
9 559
 
3.3%
Other values (2) 809
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28121
62.5%
ASCII 16852
37.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8449
50.1%
1 1624
 
9.6%
2 1179
 
7.0%
3 871
 
5.2%
5 749
 
4.4%
4 727
 
4.3%
6 652
 
3.9%
0 632
 
3.8%
7 601
 
3.6%
9 559
 
3.3%
Other values (2) 809
 
4.8%
Hangul
ValueCountFrequency (%)
시 2585
 
9.2%
경 2558
 
9.1%
기 2530
 
9.0%
도 2521
 
9.0%
로 2260
 
8.0%
구 999
 
3.6%
성 765
 
2.7%
길 734
 
2.6%
천 687
 
2.4%
부 651
 
2.3%
Other values (281) 11831
42.1%

소재지지번주소
Text

Distinct2365
Distinct (%)78.7%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
2024-04-29T22:04:03.077101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length34
Mean length19.275449
Min length13

Characters and Unicode

Total characters57942
Distinct characters299
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

Unique1911 ?
Unique (%)63.6%

Sample

1st row경기도 파주시 조리읍 봉일천리 188-6
2nd row경기도 파주시 광탄면 신산리 134-1
3rd row경기도 파주시 와동동 1483
4th row경기도 파주시 와동동 1483
5th row경기도 파주시 와동동 1483
ValueCountFrequency (%)
경기도 3006
 
22.7%
화성시 475
 
3.6%
부천시 436
 
3.3%
수원시 400
 
3.0%
성남시 362
 
2.7%
분당구 269
 
2.0%
고양시 187
 
1.4%
반송동 183
 
1.4%
파주시 178
 
1.3%
영통구 129
 
1.0%
Other values (2668) 7623
57.5%
2024-04-29T22:04:03.514659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10246
17.7%
동 3145
 
5.4%
시 3067
 
5.3%
기 3035
 
5.2%
도 3024
 
5.2%
경 3008
 
5.2%
1 2354
 
4.1%
지 1955
 
3.4%
번 1888
 
3.3%
- 1636
 
2.8%
Other values (289) 24584
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34993
60.4%
Decimal Number 11036
 
19.0%
Space Separator 10246
 
17.7%
Dash Punctuation 1636
 
2.8%
Uppercase Letter 12
 
< 0.1%
Other Punctuation 7
 
< 0.1%
Open Punctuation 6
 
< 0.1%
Close Punctuation 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 3145
 
9.0%
시 3067
 
8.8%
기 3035
 
8.7%
도 3024
 
8.6%
경 3008
 
8.6%
지 1955
 
5.6%
번 1888
 
5.4%
구 1109
 
3.2%
성 883
 
2.5%
천 690
 
2.0%
Other values (264) 13189
37.7%
Decimal Number
ValueCountFrequency (%)
1 2354
21.3%
2 1321
12.0%
3 1157
10.5%
5 1109
10.0%
4 978
8.9%
8 894
 
8.1%
6 856
 
7.8%
7 826
 
7.5%
9 781
 
7.1%
0 760
 
6.9%
Uppercase Letter
ValueCountFrequency (%)
P 2
16.7%
I 2
16.7%
L 2
16.7%
U 1
8.3%
W 1
8.3%
T 1
8.3%
H 1
8.3%
S 1
8.3%
V 1
8.3%
Other Punctuation
ValueCountFrequency (%)
, 4
57.1%
. 3
42.9%
Space Separator
ValueCountFrequency (%)
10246
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1636
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34993
60.4%
Common 22937
39.6%
Latin 12
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 3145
 
9.0%
시 3067
 
8.8%
기 3035
 
8.7%
도 3024
 
8.6%
경 3008
 
8.6%
지 1955
 
5.6%
번 1888
 
5.4%
구 1109
 
3.2%
성 883
 
2.5%
천 690
 
2.0%
Other values (264) 13189
37.7%
Common
ValueCountFrequency (%)
10246
44.7%
1 2354
 
10.3%
- 1636
 
7.1%
2 1321
 
5.8%
3 1157
 
5.0%
5 1109
 
4.8%
4 978
 
4.3%
8 894
 
3.9%
6 856
 
3.7%
7 826
 
3.6%
Other values (6) 1560
 
6.8%
Latin
ValueCountFrequency (%)
P 2
16.7%
I 2
16.7%
L 2
16.7%
U 1
8.3%
W 1
8.3%
T 1
8.3%
H 1
8.3%
S 1
8.3%
V 1
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34993
60.4%
ASCII 22949
39.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10246
44.6%
1 2354
 
10.3%
- 1636
 
7.1%
2 1321
 
5.8%
3 1157
 
5.0%
5 1109
 
4.8%
4 978
 
4.3%
8 894
 
3.9%
6 856
 
3.7%
7 826
 
3.6%
Other values (15) 1572
 
6.8%
Hangul
ValueCountFrequency (%)
동 3145
 
9.0%
시 3067
 
8.8%
기 3035
 
8.7%
도 3024
 
8.6%
경 3008
 
8.6%
지 1955
 
5.6%
번 1888
 
5.4%
구 1109
 
3.2%
성 883
 
2.5%
천 690
 
2.0%
Other values (264) 13189
37.7%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct2522
Distinct (%)83.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.453212
Minimum36.932109
Maximum38.184665
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.5 KiB
2024-04-29T22:04:03.651853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.932109
5-th percentile37.199911
Q137.27887
median37.435769
Q337.602492
95-th percentile37.794873
Maximum38.184665
Range1.2525561
Interquartile range (IQR)0.32362268

Descriptive statistics

Standard deviation0.19968308
Coefficient of variation (CV)0.0053315341
Kurtosis-0.63021728
Mean37.453212
Median Absolute Deviation (MAD)0.16022561
Skewness0.35658388
Sum112584.36
Variance0.039873332
MonotonicityNot monotonic
2024-04-29T22:04:03.797096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.20675447 24
 
0.8%
37.20640468 12
 
0.4%
37.760141 11
 
0.4%
37.20083002 7
 
0.2%
37.21394625 6
 
0.2%
37.732376 6
 
0.2%
37.20563857 6
 
0.2%
37.19991112 6
 
0.2%
37.344808 5
 
0.2%
37.726326 5
 
0.2%
Other values (2512) 2918
97.1%
ValueCountFrequency (%)
36.93210859 1
< 0.1%
36.935183 1
< 0.1%
36.93716949 1
< 0.1%
36.941542 1
< 0.1%
36.95743948 1
< 0.1%
36.95803144 1
< 0.1%
36.97193583 1
< 0.1%
36.97646757 1
< 0.1%
36.97767742 1
< 0.1%
36.97866161 1
< 0.1%
ValueCountFrequency (%)
38.1846646709 1
< 0.1%
38.1013536125 1
< 0.1%
38.0267308428 1
< 0.1%
37.981263209 1
< 0.1%
37.94795336 1
< 0.1%
37.94652177 1
< 0.1%
37.946074 1
< 0.1%
37.94587589 1
< 0.1%
37.945837 1
< 0.1%
37.944682 1
< 0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct2520
Distinct (%)83.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.96972
Minimum126.44222
Maximum127.70603
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.5 KiB
2024-04-29T22:04:04.131566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.44222
5-th percentile126.74308
Q1126.79154
median127.01444
Q3127.0775
95-th percentile127.15006
Maximum127.70603
Range1.2638068
Interquartile range (IQR)0.2859586

Descriptive statistics

Standard deviation0.16766839
Coefficient of variation (CV)0.0013205384
Kurtosis1.0082418
Mean126.96972
Median Absolute Deviation (MAD)0.10374937
Skewness0.32986447
Sum381670.98
Variance0.02811269
MonotonicityNot monotonic
2024-04-29T22:04:04.261330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0630117 24
 
0.8%
127.0788197 12
 
0.4%
126.779958 11
 
0.4%
127.0723739 7
 
0.2%
127.1139695 6
 
0.2%
126.766461 6
 
0.2%
127.0424701 6
 
0.2%
127.0635805 6
 
0.2%
126.797897 5
 
0.2%
126.968722 5
 
0.2%
Other values (2510) 2918
97.1%
ValueCountFrequency (%)
126.442221 1
< 0.1%
126.5556828 1
< 0.1%
126.5900414 1
< 0.1%
126.6250021 1
< 0.1%
126.6258104 1
< 0.1%
126.6259084 1
< 0.1%
126.6260739 1
< 0.1%
126.6268882 1
< 0.1%
126.6270613 1
< 0.1%
126.6273949 1
< 0.1%
ValueCountFrequency (%)
127.7060278 2
0.1%
127.6476737 2
0.1%
127.6398559 2
0.1%
127.637163 2
0.1%
127.6351996 2
0.1%
127.6351138 2
0.1%
127.6323529 2
0.1%
127.6286863 1
< 0.1%
127.6249607 2
0.1%
127.6240845 2
0.1%

보관대수
Real number (ℝ)

Distinct153
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.34165
Minimum0
Maximum640
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size26.5 KiB
2024-04-29T22:04:04.393528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q17
median10
Q320
95-th percentile80
Maximum640
Range640
Interquartile range (IQR)13

Descriptive statistics

Standard deviation41.368238
Coefficient of variation (CV)1.8516197
Kurtosis57.553413
Mean22.34165
Median Absolute Deviation (MAD)5
Skewness6.2983667
Sum67159
Variance1711.3312
MonotonicityNot monotonic
2024-04-29T22:04:04.534652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 894
29.7%
7 227
 
7.6%
20 217
 
7.2%
1 192
 
6.4%
14 136
 
4.5%
5 128
 
4.3%
2 127
 
4.2%
30 77
 
2.6%
40 60
 
2.0%
6 56
 
1.9%
Other values (143) 892
29.7%
ValueCountFrequency (%)
0 1
 
< 0.1%
1 192
6.4%
2 127
4.2%
3 56
 
1.9%
4 49
 
1.6%
5 128
4.3%
6 56
 
1.9%
7 227
7.6%
8 35
 
1.2%
9 50
 
1.7%
ValueCountFrequency (%)
640 1
< 0.1%
576 1
< 0.1%
500 1
< 0.1%
499 1
< 0.1%
466 1
< 0.1%
369 1
< 0.1%
333 2
0.1%
332 1
< 0.1%
320 2
0.1%
319 1
< 0.1%

설치연도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct27
Distinct (%)3.1%
Missing2137
Missing (%)71.1%
Infinite0
Infinite (%)0.0%
Mean2011.0748
Minimum1995
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.5 KiB
2024-04-29T22:04:04.677451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1995
5-th percentile2002
Q12010
median2010
Q32013
95-th percentile2021
Maximum2021
Range26
Interquartile range (IQR)3

Descriptive statistics

Standard deviation4.6958333
Coefficient of variation (CV)0.0023349869
Kurtosis1.3794543
Mean2011.0748
Median Absolute Deviation (MAD)2
Skewness-0.23820503
Sum1747624
Variance22.05085
MonotonicityNot monotonic
2024-04-29T22:04:04.795209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
2010 362
 
12.0%
2012 92
 
3.1%
2017 72
 
2.4%
2008 57
 
1.9%
2021 51
 
1.7%
2002 42
 
1.4%
2014 36
 
1.2%
2016 23
 
0.8%
2009 23
 
0.8%
2013 20
 
0.7%
Other values (17) 91
 
3.0%
(Missing) 2137
71.1%
ValueCountFrequency (%)
1995 5
 
0.2%
1996 5
 
0.2%
1997 3
 
0.1%
1998 1
 
< 0.1%
1999 2
 
0.1%
2000 4
 
0.1%
2001 1
 
< 0.1%
2002 42
1.4%
2003 4
 
0.1%
2004 1
 
< 0.1%
ValueCountFrequency (%)
2021 51
1.7%
2020 4
 
0.1%
2019 5
 
0.2%
2018 5
 
0.2%
2017 72
2.4%
2016 23
 
0.8%
2015 13
 
0.4%
2014 36
 
1.2%
2013 20
 
0.7%
2012 92
3.1%

설치형태
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
거치형
1597 
<NA>
854 
단독형
378 
휀스형
 
112
기타
 
65

Length

Max length4
Median length3
Mean length3.262475
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 (%)
거치형 1597
53.1%
<NA> 854
28.4%
단독형 378
 
12.6%
휀스형 112
 
3.7%
기타 65
 
2.2%

Length

2024-04-29T22:04:04.918288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T22:04:05.013908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
거치형 1597
53.1%
na 854
28.4%
단독형 378
 
12.6%
휀스형 112
 
3.7%
기타 65
 
2.2%

차양막설치여부
Boolean

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)0.1%
Missing1406
Missing (%)46.8%
Memory size6.0 KiB
False
895 
True
705 
(Missing)
1406 
ValueCountFrequency (%)
False 895
29.8%
True 705
23.5%
(Missing) 1406
46.8%
2024-04-29T22:04:05.101699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

공기주입기비치여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
False
2689 
True
317 
ValueCountFrequency (%)
False 2689
89.5%
True 317
 
10.5%
2024-04-29T22:04:05.179620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

공기주입기유형
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
<NA>
2666 
수동식
 
158
기계식
 
105
기타
 
59
태양광식
 
18

Length

Max length4
Median length4
Mean length3.8732535
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2666
88.7%
수동식 158
 
5.3%
기계식 105
 
3.5%
기타 59
 
2.0%
태양광식 18
 
0.6%

Length

2024-04-29T22:04:05.286914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T22:04:05.391098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2666
88.7%
수동식 158
 
5.3%
기계식 105
 
3.5%
기타 59
 
2.0%
태양광식 18
 
0.6%

수리대설치여부
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
False
3006 
ValueCountFrequency (%)
False 3006
100.0%
2024-04-29T22:04:05.474082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

관리기관전화번호
Text

Distinct400
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
2024-04-29T22:04:05.647796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.259814
Min length9

Characters and Unicode

Total characters36853
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique329 ?
Unique (%)10.9%

Sample

1st row031-940-4655
2nd row031-940-4655
3rd row031-940-4655
4th row031-940-4655
5th row031-940-4655
ValueCountFrequency (%)
031-5189-4218 384
 
12.8%
031-729-3302 362
 
12.0%
031-940-4655 178
 
5.9%
031-8075-6315 142
 
4.7%
032-625-5623 113
 
3.8%
032-625-5793 100
 
3.3%
031-8082-6731 89
 
3.0%
031-980-2785 86
 
2.9%
031-828-2433 71
 
2.4%
031-790-6545 67
 
2.2%
Other values (390) 1414
47.0%
2024-04-29T22:04:05.995120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 6004
16.3%
3 5163
14.0%
0 4799
13.0%
1 4261
11.6%
2 4243
11.5%
5 2777
7.5%
8 2488
6.8%
9 2011
 
5.5%
6 1797
 
4.9%
4 1744
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30849
83.7%
Dash Punctuation 6004
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 5163
16.7%
0 4799
15.6%
1 4261
13.8%
2 4243
13.8%
5 2777
9.0%
8 2488
8.1%
9 2011
 
6.5%
6 1797
 
5.8%
4 1744
 
5.7%
7 1566
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 6004
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 36853
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 6004
16.3%
3 5163
14.0%
0 4799
13.0%
1 4261
11.6%
2 4243
11.5%
5 2777
7.5%
8 2488
6.8%
9 2011
 
5.5%
6 1797
 
4.9%
4 1744
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36853
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 6004
16.3%
3 5163
14.0%
0 4799
13.0%
1 4261
11.6%
2 4243
11.5%
5 2777
7.5%
8 2488
6.8%
9 2011
 
5.5%
6 1797
 
4.9%
4 1744
 
4.7%

관리기관명
Text

Distinct361
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
2024-04-29T22:04:06.180056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length13
Mean length8.2821025
Min length2

Characters and Unicode

Total characters24896
Distinct characters233
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique301 ?
Unique (%)10.0%

Sample

1st row파주시청
2nd row파주시청
3rd row파주시청
4th row파주시청
5th row파주시청
ValueCountFrequency (%)
경기도 1066
20.1%
화성시 439
 
8.3%
동부출장소 388
 
7.3%
성남시청 362
 
6.8%
고양시 187
 
3.5%
파주시청 178
 
3.4%
수원시 160
 
3.0%
도로과 151
 
2.8%
일산동구청 118
 
2.2%
신중동행정복지센터 113
 
2.1%
Other values (369) 2141
40.4%
2024-04-29T22:04:06.481001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 2399
 
9.6%
2297
 
9.2%
청 1691
 
6.8%
도 1347
 
5.4%
경 1093
 
4.4%
동 1087
 
4.4%
기 1080
 
4.3%
성 909
 
3.7%
정 562
 
2.3%
부 526
 
2.1%
Other values (223) 11905
47.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22570
90.7%
Space Separator 2297
 
9.2%
Decimal Number 24
 
0.1%
Uppercase Letter 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 2399
 
10.6%
청 1691
 
7.5%
도 1347
 
6.0%
경 1093
 
4.8%
동 1087
 
4.8%
기 1080
 
4.8%
성 909
 
4.0%
정 562
 
2.5%
부 526
 
2.3%
화 519
 
2.3%
Other values (214) 11357
50.3%
Decimal Number
ValueCountFrequency (%)
2 9
37.5%
1 9
37.5%
3 4
16.7%
5 1
 
4.2%
6 1
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
S 2
40.0%
K 2
40.0%
B 1
20.0%
Space Separator
ValueCountFrequency (%)
2297
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22570
90.7%
Common 2321
 
9.3%
Latin 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 2399
 
10.6%
청 1691
 
7.5%
도 1347
 
6.0%
경 1093
 
4.8%
동 1087
 
4.8%
기 1080
 
4.8%
성 909
 
4.0%
정 562
 
2.5%
부 526
 
2.3%
화 519
 
2.3%
Other values (214) 11357
50.3%
Common
ValueCountFrequency (%)
2297
99.0%
2 9
 
0.4%
1 9
 
0.4%
3 4
 
0.2%
5 1
 
< 0.1%
6 1
 
< 0.1%
Latin
ValueCountFrequency (%)
S 2
40.0%
K 2
40.0%
B 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22570
90.7%
ASCII 2326
 
9.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 2399
 
10.6%
청 1691
 
7.5%
도 1347
 
6.0%
경 1093
 
4.8%
동 1087
 
4.8%
기 1080
 
4.8%
성 909
 
4.0%
정 562
 
2.5%
부 526
 
2.3%
화 519
 
2.3%
Other values (214) 11357
50.3%
ASCII
ValueCountFrequency (%)
2297
98.8%
2 9
 
0.4%
1 9
 
0.4%
3 4
 
0.2%
S 2
 
0.1%
K 2
 
0.1%
B 1
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%

데이터기준일자
Date

Distinct24
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
Minimum2017-01-01 00:00:00
Maximum2024-04-23 00:00:00
2024-04-29T22:04:06.613316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:04:06.711763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

Interactions

2024-04-29T22:04:00.608182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:03:59.392487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:03:59.869498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:04:00.235635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:04:00.695557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:03:59.543228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:03:59.966282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:04:00.332377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:04:00.777082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:03:59.665932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:04:00.066527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:04:00.433363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:04:00.861079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:03:59.761361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:04:00.150939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:04:00.521849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-29T22:04:06.805044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명위도경도보관대수설치연도설치형태차양막설치여부공기주입기비치여부공기주입기유형데이터기준일자
시군명1.0000.9700.9550.4950.9220.8480.6400.4870.8631.000
위도0.9701.0000.7490.1270.6340.5140.5210.3770.3970.961
경도0.9550.7491.0000.0000.7860.4670.3620.1900.7760.946
보관대수0.4950.1270.0001.0000.3440.2550.0840.1380.0000.488
설치연도0.9220.6340.7860.3441.0000.7960.2350.3690.7090.917
설치형태0.8480.5140.4670.2550.7961.0000.5550.3650.6640.847
차양막설치여부0.6400.5210.3620.0840.2350.5551.0000.2890.1770.706
공기주입기비치여부0.4870.3770.1900.1380.3690.3650.2891.0000.9530.527
공기주입기유형0.8630.3970.7760.0000.7090.6640.1770.9531.0000.854
데이터기준일자1.0000.9610.9460.4880.9170.8470.7060.5270.8541.000
2024-04-29T22:04:06.935474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치형태공기주입기유형시군명차양막설치여부공기주입기비치여부
설치형태1.0000.3150.6500.3800.244
공기주입기유형0.3151.0000.6610.1170.801
시군명0.6500.6611.0000.5660.421
차양막설치여부0.3800.1170.5661.0000.187
공기주입기비치여부0.2440.8010.4210.1871.000
2024-04-29T22:04:07.032852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도보관대수설치연도시군명설치형태차양막설치여부공기주입기비치여부공기주입기유형
위도1.000-0.3120.0990.0530.8040.3330.4000.2890.245
경도-0.3121.000-0.248-0.0510.7450.3170.3620.1450.440
보관대수0.099-0.2481.000-0.0350.2130.1160.0710.1360.000
설치연도0.053-0.051-0.0351.0000.6820.6280.2340.2890.510
시군명0.8040.7450.2130.6821.0000.6500.5660.4210.661
설치형태0.3330.3170.1160.6280.6501.0000.3800.2440.315
차양막설치여부0.4000.3620.0710.2340.5660.3801.0000.1870.117
공기주입기비치여부0.2890.1450.1360.2890.4210.2440.1871.0000.801
공기주입기유형0.2450.4400.0000.5100.6610.3150.1170.8011.000

Missing values

2024-04-29T22:04:01.024392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-29T22:04:01.226846image/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.
2024-04-29T22:04:01.370036image/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

시군명자전거보관소명소재지도로명주소소재지지번주소위도경도보관대수설치연도설치형태차양막설치여부공기주입기비치여부공기주입기유형수리대설치여부관리기관전화번호관리기관명데이터기준일자
0파주시조리읍사무소경기도 파주시 봉천로 64경기도 파주시 조리읍 봉일천리 188-637.744649126.80511710<NA><NA><NA>Y수동식N031-940-4655파주시청2017-11-07
1파주시광탄면사무소경기도 파주시 광탄면 혜음로 1044경기도 파주시 광탄면 신산리 134-137.776148126.85131110<NA><NA><NA>Y수동식N031-940-4655파주시청2017-11-07
2파주시운정스포츠센터축구장 앞<NA>경기도 파주시 와동동 148337.732376126.76646110<NA><NA><NA>N<NA>N031-940-4655파주시청2017-11-07
3파주시운정스포츠센터축구장 맞은편<NA>경기도 파주시 와동동 148337.732376126.76646110<NA><NA><NA>N<NA>N031-940-4655파주시청2017-11-07
4파주시운정스포츠센터 정문 앞(좌측 약100m)<NA>경기도 파주시 와동동 148337.732376126.76646110<NA><NA><NA>N<NA>N031-940-4655파주시청2017-11-07
5파주시운정스포츠센터 정문맞은편(좌측 약50m)<NA>경기도 파주시 와동동 148337.732376126.76646110<NA><NA><NA>N<NA>N031-940-4655파주시청2017-11-07
6부천시한양프라자경기도 부천시 부흥로303번길 50경기도 부천시 중동 1128-2번지37.496743126.7759827<NA>거치형NN<NA>N032-625-5623신중동행정복지센터2022-01-01
7파주시한라7단지 701동대각선으로 맞은편<NA>경기도 파주시 와동동 148337.732376126.76646110<NA><NA><NA>N<NA>N031-940-4655파주시청2017-11-07
8파주시한라7단지 701동맞은편<NA>경기도 파주시 와동동 148337.732376126.76646110<NA><NA><NA>N<NA>N031-940-4655파주시청2017-11-07
9부천시중2 주민지원센터경기도 부천시 심중로119번길 8경기도 부천시 중동 1192-2번지37.493823126.76996810<NA>거치형NN<NA>N032-625-5623신중동행정복지센터2022-01-01
시군명자전거보관소명소재지도로명주소소재지지번주소위도경도보관대수설치연도설치형태차양막설치여부공기주입기비치여부공기주입기유형수리대설치여부관리기관전화번호관리기관명데이터기준일자
2996하남시남한고등학교 내경기도 하남시 신평로 25경기도 하남시 덕풍동 450번지37.536438127.20268364<NA><NA><NA>N<NA>N031-790-6545경기도 하남시청2023-07-04
2997하남시서부초등학교경기도 하남시 서하남로 161경기도 하남시 감일동 14-8번지37.515742127.162121<NA><NA><NA>N<NA>N031-790-6545경기도 하남시청2023-07-04
2998하남시풍산초등학교경기도 하남시 덕풍북로 100경기도 하남시 덕풍동 730번지37.554594127.20146430<NA><NA><NA>N<NA>N031-790-6545경기도 하남시청2023-07-04
2999하남시동부중학교경기도 하남시 신평로 15경기도 하남시 덕풍동 450-1번지37.535458127.20272430<NA><NA><NA>N<NA>N031-790-6545경기도 하남시청2023-07-04
3000하남시천현초등학교경기도 하남시 천현로 45경기도 하남시 신장동 529번지37.537903127.21628520<NA><NA><NA>N<NA>N031-790-6545경기도 하남시청2023-07-04
3001하남시신장중학교경기도 하남시 대청로59번길 37경기도 하남시 신장동 527-1번지37.542737127.21867530<NA><NA><NA>N<NA>N031-790-6545경기도 하남시청2023-07-04
3002하남시부영아파트 공원내경기도 하남시 대청로 109경기도 하남시 창우동 518-4번지37.539789127.22456114<NA><NA><NA>N<NA>N031-790-6545경기도 하남시청2023-07-04
3003하남시꿈나라공원 내<NA>경기도 하남시 창우동 520-537.537515127.22155614<NA><NA><NA>N<NA>N031-790-6545경기도 하남시청2023-07-04
3004하남시천현초교 꿈동산 공원 내경기도 하남시 천현로 55경기도 하남시 신장동 528-4번지37.538409127.21733414<NA><NA><NA>N<NA>N031-790-6545경기도 하남시청2023-07-04
3005하남시신평초교옆 공원<NA>경기도 하남시 신장동 59437.087207127.04670114<NA><NA><NA>N<NA>N031-790-6545경기도 하남시청2023-07-04

Duplicate rows

Most frequently occurring

시군명자전거보관소명소재지도로명주소소재지지번주소위도경도보관대수설치연도설치형태차양막설치여부공기주입기비치여부공기주입기유형수리대설치여부관리기관전화번호관리기관명데이터기준일자# duplicates
63화성시동탄복합문화센터<NA>경기도 화성시 반송동 10837.206405127.0788225<NA>거치형<NA>N<NA>N031-5189-4218경기도 화성시 동부출장소2024-01-224
0고양시웨스턴돔경기도 고양시 일산동구 정발산로 24경기도 고양시 일산동구 장항동 868번지37.655896126.77203920<NA>거치형<NA>N<NA>N031-8075-6315경기도 고양시 일산동구청2024-04-232
1성남시백궁교 밑(탄천좌안)경기도 성남시 분당구 성남대로 449경기도 성남시 분당구 정자동 28-137.375153127.10880812010거치형NN<NA>N031-729-3302성남시청2018-03-312
2수원시장안공원<NA>경기도 수원시 장안구 영화동 349-8637.287624127.0119910<NA><NA><NA>N<NA>N031-228-4188수원시 공원녹지사업소2021-12-312
3수원시장안문버스정류장경기도 수원시 장안구 팔달로 256-2경기도 수원시 장안구 영화동 349-737.288603127.01320210<NA><NA><NA>N<NA>N031-228-5492수원시 장안구청2021-12-312
4여주시강천체육공원경기도 여주시 강천면 귀안골 23경기도 여주시 강천면 간매리 524-1137.275228127.706028202011<NA><NA>N<NA>N031-887-2971경기도 여주시청2022-08-312
5여주시대신고등학교경기도 여주시 대신면 여양로 1196경기도 여주시 대신면 후포리 258-1번지37.364565127.607176122014<NA><NA>N<NA>N031-882-7631대신고등학교2022-08-312
6여주시상품중학교경기도 여주시 산북면 상품1길 28경기도 여주시 산북면 상품리 70-1번지37.402314127.440321102014<NA><NA>N<NA>N031-883-0003삼품중학교2022-08-312
7여주시세정중학교경기도 여주시 세종대왕면 양화로 691-4경기도 여주시 세종대왕면 매류리 373-6번지37.279962127.56357472014<NA><NA>N<NA>N031-882-4360세정중학교2022-08-312
8여주시세종국악당경기도 여주시 영릉로 125경기도 여주시 하동 107-12번지37.297268127.624961202014<NA><NA>N<NA>N031-887-3319경기도 여주시청2022-08-312