Overview

Dataset statistics

Number of variables22
Number of observations1500
Missing cells2784
Missing cells (%)8.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory275.5 KiB
Average record size in memory188.1 B

Variable types

Text5
Categorical7
Numeric7
Unsupported1
Boolean1
DateTime1

Dataset

Description제주시 클린하우스 현황 데이터로 데이터코드, 구분명, 읍면동명, 단지명, 유형명, 도로명주소, 지번주소, 위도좌표, 경도좌표, 종량제수거함수, 재활용수거함수, 유리병수거함수, 스티로폼수거함수, 폐기건전지수거함수, 폐기형광등수거함수, 음식물수거함수, 음식물계량수거함수, CCTV설치수, 특이사항내용, 사진여부, 기타내용, 등록일시 데이터 제공
Author제주특별자치도 제주시
URLhttps://www.data.go.kr/data/15110514/fileData.do

Alerts

사진 여부 has constant value ""Constant
등록 일시 has constant value ""Constant
구분 명 is highly imbalanced (77.6%)Imbalance
유형 명 is highly imbalanced (50.5%)Imbalance
유리병 수거함 수 is highly imbalanced (57.7%)Imbalance
스티로폼 수거함 수 is highly imbalanced (51.2%)Imbalance
폐기 형광등 수거함 수 is highly imbalanced (50.9%)Imbalance
특이사항 내용 has 1500 (100.0%) missing valuesMissing
기타 내용 has 1284 (85.6%) missing valuesMissing
위도 좌표 is highly skewed (γ1 = 38.72983346)Skewed
경도 좌표 is highly skewed (γ1 = 38.72983346)Skewed
데이터 코드 has unique valuesUnique
특이사항 내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
종량제 수거함 수 has 44 (2.9%) zerosZeros
재활용 수거함 수 has 38 (2.5%) zerosZeros
음식물 수거함 수 has 146 (9.7%) zerosZeros
음식물 계량 수거함 수 has 164 (10.9%) zerosZeros
CCTV 설치 수 has 350 (23.3%) zerosZeros

Reproduction

Analysis started2023-12-12 14:03:46.544010
Analysis finished2023-12-12 14:03:47.349660
Duration0.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

데이터 코드
Text

UNIQUE 

Distinct1500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
2023-12-12T23:03:47.545241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters9000
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1500 ?
Unique (%)100.0%

Sample

1st rowCL0001
2nd rowCL0002
3rd rowCL0003
4th rowCL0004
5th rowCL0005
ValueCountFrequency (%)
cl0001 1
 
0.1%
cl1139 1
 
0.1%
cl1148 1
 
0.1%
cl1147 1
 
0.1%
cl1146 1
 
0.1%
cl1145 1
 
0.1%
cl1144 1
 
0.1%
cl1143 1
 
0.1%
cl1142 1
 
0.1%
cl1141 1
 
0.1%
Other values (1490) 1490
99.3%
2023-12-12T23:03:47.886482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 1500
16.7%
L 1500
16.7%
0 1377
15.3%
1 1107
12.3%
4 491
 
5.5%
3 482
 
5.4%
2 481
 
5.3%
5 461
 
5.1%
6 433
 
4.8%
9 391
 
4.3%
Other values (2) 777
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6000
66.7%
Uppercase Letter 3000
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1377
22.9%
1 1107
18.4%
4 491
 
8.2%
3 482
 
8.0%
2 481
 
8.0%
5 461
 
7.7%
6 433
 
7.2%
9 391
 
6.5%
8 389
 
6.5%
7 388
 
6.5%
Uppercase Letter
ValueCountFrequency (%)
C 1500
50.0%
L 1500
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6000
66.7%
Latin 3000
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1377
22.9%
1 1107
18.4%
4 491
 
8.2%
3 482
 
8.0%
2 481
 
8.0%
5 461
 
7.7%
6 433
 
7.2%
9 391
 
6.5%
8 389
 
6.5%
7 388
 
6.5%
Latin
ValueCountFrequency (%)
C 1500
50.0%
L 1500
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 1500
16.7%
L 1500
16.7%
0 1377
15.3%
1 1107
12.3%
4 491
 
5.5%
3 482
 
5.4%
2 481
 
5.3%
5 461
 
5.1%
6 433
 
4.8%
9 391
 
4.3%
Other values (2) 777
8.6%

구분 명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
클린하우스
1446 
재활용도움센터
 
54

Length

Max length7
Median length5
Mean length5.072
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
클린하우스 1446
96.4%
재활용도움센터 54
 
3.6%

Length

2023-12-12T23:03:48.008117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:03:48.098190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
클린하우스 1446
96.4%
재활용도움센터 54
 
3.6%

읍면동 명
Categorical

Distinct28
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
조천읍
138 
구좌읍
133 
애월읍
124 
이도2동
108 
한림읍
91 
Other values (23)
906 

Length

Max length8
Median length3
Mean length3.1886667
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
조천읍 138
 
9.2%
구좌읍 133
 
8.9%
애월읍 124
 
8.3%
이도2동 108
 
7.2%
한림읍 91
 
6.1%
연동 88
 
5.9%
한경면 87
 
5.8%
노형동 84
 
5.6%
아라동 76
 
5.1%
외도동 57
 
3.8%
Other values (18) 514
34.3%

Length

2023-12-12T23:03:48.190283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
조천읍 139
 
9.3%
구좌읍 133
 
8.9%
애월읍 124
 
8.3%
이도2동 108
 
7.2%
한림읍 91
 
6.1%
연동 88
 
5.9%
한경면 87
 
5.8%
노형동 84
 
5.6%
아라동 76
 
5.1%
외도동 57
 
3.8%
Other values (17) 513
34.2%

단지 명
Text

Distinct1435
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
2023-12-12T23:03:48.426378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length32
Mean length10.600667
Min length2

Characters and Unicode

Total characters15901
Distinct characters564
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1383 ?
Unique (%)92.2%

Sample

1st row리사무소 앞
2nd row영신연립 옆 한흥블럭사
3rd row왕수학교실 삼거리 (회성푸르니 아파트 앞)
4th row수타명가 남측
5th row대림하동길 마을 끝
ValueCountFrequency (%)
앞 257
 
7.2%
옆 123
 
3.4%
주차장 76
 
2.1%
노형동 72
 
2.0%
서측 70
 
2.0%
동측 61
 
1.7%
남측 56
 
1.6%
북측 55
 
1.5%
맞은편 51
 
1.4%
입구 49
 
1.4%
Other values (1955) 2698
75.6%
2023-12-12T23:03:48.951612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2103
 
13.2%
동 494
 
3.1%
앞 388
 
2.4%
측 350
 
2.2%
주 298
 
1.9%
장 290
 
1.8%
리 262
 
1.6%
1 238
 
1.5%
2 199
 
1.3%
원 199
 
1.3%
Other values (554) 11080
69.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12162
76.5%
Space Separator 2103
 
13.2%
Decimal Number 1070
 
6.7%
Open Punctuation 172
 
1.1%
Close Punctuation 168
 
1.1%
Dash Punctuation 124
 
0.8%
Uppercase Letter 76
 
0.5%
Lowercase Letter 13
 
0.1%
Other Punctuation 6
 
< 0.1%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 494
 
4.1%
앞 388
 
3.2%
측 350
 
2.9%
주 298
 
2.5%
장 290
 
2.4%
리 262
 
2.2%
원 199
 
1.6%
차 196
 
1.6%
옆 188
 
1.5%
서 185
 
1.5%
Other values (510) 9312
76.6%
Uppercase Letter
ValueCountFrequency (%)
G 12
15.8%
S 11
14.5%
M 9
11.8%
K 6
7.9%
P 5
 
6.6%
T 5
 
6.6%
C 4
 
5.3%
L 4
 
5.3%
A 4
 
5.3%
J 3
 
3.9%
Other values (9) 13
17.1%
Decimal Number
ValueCountFrequency (%)
1 238
22.2%
2 199
18.6%
3 106
9.9%
5 102
9.5%
0 93
 
8.7%
4 86
 
8.0%
7 65
 
6.1%
9 61
 
5.7%
8 61
 
5.7%
6 59
 
5.5%
Lowercase Letter
ValueCountFrequency (%)
m 8
61.5%
e 3
 
23.1%
k 1
 
7.7%
s 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
& 4
66.7%
/ 1
 
16.7%
@ 1
 
16.7%
Open Punctuation
ValueCountFrequency (%)
( 171
99.4%
[ 1
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 167
99.4%
] 1
 
0.6%
Space Separator
ValueCountFrequency (%)
2103
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 124
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12164
76.5%
Common 3648
 
22.9%
Latin 89
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 494
 
4.1%
앞 388
 
3.2%
측 350
 
2.9%
주 298
 
2.4%
장 290
 
2.4%
리 262
 
2.2%
원 199
 
1.6%
차 196
 
1.6%
옆 188
 
1.5%
서 185
 
1.5%
Other values (511) 9314
76.6%
Latin
ValueCountFrequency (%)
G 12
13.5%
S 11
12.4%
M 9
10.1%
m 8
 
9.0%
K 6
 
6.7%
P 5
 
5.6%
T 5
 
5.6%
C 4
 
4.5%
L 4
 
4.5%
A 4
 
4.5%
Other values (13) 21
23.6%
Common
ValueCountFrequency (%)
2103
57.6%
1 238
 
6.5%
2 199
 
5.5%
( 171
 
4.7%
) 167
 
4.6%
- 124
 
3.4%
3 106
 
2.9%
5 102
 
2.8%
0 93
 
2.5%
4 86
 
2.4%
Other values (10) 259
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12162
76.5%
ASCII 3737
 
23.5%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2103
56.3%
1 238
 
6.4%
2 199
 
5.3%
( 171
 
4.6%
) 167
 
4.5%
- 124
 
3.3%
3 106
 
2.8%
5 102
 
2.7%
0 93
 
2.5%
4 86
 
2.3%
Other values (33) 348
 
9.3%
Hangul
ValueCountFrequency (%)
동 494
 
4.1%
앞 388
 
3.2%
측 350
 
2.9%
주 298
 
2.5%
장 290
 
2.4%
리 262
 
2.2%
원 199
 
1.6%
차 196
 
1.6%
옆 188
 
1.5%
서 185
 
1.5%
Other values (510) 9312
76.6%
None
ValueCountFrequency (%)
㈜ 2
100.0%

유형 명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
비가림시설
1186 
거치대
217 
재활용도움센터
 
54
비가림시설/거치대
 
43

Length

Max length9
Median length5
Mean length4.8973333
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row비가림시설
2nd row비가림시설
3rd row비가림시설
4th row비가림시설
5th row비가림시설/거치대

Common Values

ValueCountFrequency (%)
비가림시설 1186
79.1%
거치대 217
 
14.5%
재활용도움센터 54
 
3.6%
비가림시설/거치대 43
 
2.9%

Length

2023-12-12T23:03:49.095573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:03:49.199544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
비가림시설 1186
79.1%
거치대 217
 
14.5%
재활용도움센터 54
 
3.6%
비가림시설/거치대 43
 
2.9%

도로명 주소
Text

Distinct1442
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
2023-12-12T23:03:49.599116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length22.422667
Min length17

Characters and Unicode

Total characters33634
Distinct characters212
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

Unique1385 ?
Unique (%)92.3%

Sample

1st row제주특별자치도 제주시 한림읍 한림리 1328-62
2nd row제주특별자치도 제주시 한림읍 한림리 1531-4
3rd row제주특별자치도 제주시 한림읍 한림리 1450-2
4th row제주특별자치도 제주시 한림읍 귀덕리 3008
5th row제주특별자치도 제주시 한림읍 대림리 1268-2
ValueCountFrequency (%)
제주특별자치도 1500
22.7%
제주시 1500
22.7%
조천읍 138
 
2.1%
구좌읍 133
 
2.0%
애월읍 124
 
1.9%
한림읍 90
 
1.4%
한경면 87
 
1.3%
노형동 42
 
0.6%
일도2동 30
 
0.5%
외도1동 26
 
0.4%
Other values (1620) 2939
44.5%
2023-12-12T23:03:50.572183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5441
16.2%
주 3026
 
9.0%
제 3007
 
8.9%
도 1694
 
5.0%
자 1533
 
4.6%
특 1500
 
4.5%
별 1500
 
4.5%
치 1500
 
4.5%
시 1500
 
4.5%
1 1356
 
4.0%
Other values (202) 11577
34.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21896
65.1%
Decimal Number 5644
 
16.8%
Space Separator 5441
 
16.2%
Dash Punctuation 653
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 3026
13.8%
제 3007
13.7%
도 1694
 
7.7%
자 1533
 
7.0%
특 1500
 
6.9%
별 1500
 
6.9%
치 1500
 
6.9%
시 1500
 
6.9%
길 619
 
2.8%
로 526
 
2.4%
Other values (190) 5491
25.1%
Decimal Number
ValueCountFrequency (%)
1 1356
24.0%
2 887
15.7%
3 609
10.8%
4 544
9.6%
5 476
 
8.4%
6 411
 
7.3%
7 360
 
6.4%
0 342
 
6.1%
8 338
 
6.0%
9 321
 
5.7%
Space Separator
ValueCountFrequency (%)
5441
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 653
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21896
65.1%
Common 11738
34.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 3026
13.8%
제 3007
13.7%
도 1694
 
7.7%
자 1533
 
7.0%
특 1500
 
6.9%
별 1500
 
6.9%
치 1500
 
6.9%
시 1500
 
6.9%
길 619
 
2.8%
로 526
 
2.4%
Other values (190) 5491
25.1%
Common
ValueCountFrequency (%)
5441
46.4%
1 1356
 
11.6%
2 887
 
7.6%
- 653
 
5.6%
3 609
 
5.2%
4 544
 
4.6%
5 476
 
4.1%
6 411
 
3.5%
7 360
 
3.1%
0 342
 
2.9%
Other values (2) 659
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21896
65.1%
ASCII 11738
34.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5441
46.4%
1 1356
 
11.6%
2 887
 
7.6%
- 653
 
5.6%
3 609
 
5.2%
4 544
 
4.6%
5 476
 
4.1%
6 411
 
3.5%
7 360
 
3.1%
0 342
 
2.9%
Other values (2) 659
 
5.6%
Hangul
ValueCountFrequency (%)
주 3026
13.8%
제 3007
13.7%
도 1694
 
7.7%
자 1533
 
7.0%
특 1500
 
6.9%
별 1500
 
6.9%
치 1500
 
6.9%
시 1500
 
6.9%
길 619
 
2.8%
로 526
 
2.4%
Other values (190) 5491
25.1%

지번 주소
Text

Distinct1436
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
2023-12-12T23:03:50.953960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length23.483333
Min length17

Characters and Unicode

Total characters35225
Distinct characters133
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

Unique1373 ?
Unique (%)91.5%

Sample

1st row제주특별자치도 제주시 한림읍 한림리 1328-62
2nd row제주특별자치도 제주시 한림읍 한림리 1531-4
3rd row제주특별자치도 제주시 한림읍 한림리 1450-2
4th row제주특별자치도 제주시 한림읍 귀덕리 3008
5th row제주특별자치도 제주시 한림읍 대림리 1268-2
ValueCountFrequency (%)
제주특별자치도 1500
22.7%
제주시 1500
22.7%
조천읍 139
 
2.1%
구좌읍 133
 
2.0%
애월읍 118
 
1.8%
한림읍 91
 
1.4%
연동 88
 
1.3%
한경면 87
 
1.3%
노형동 83
 
1.3%
이도2동 76
 
1.2%
Other values (1517) 2791
42.2%
2023-12-12T23:03:51.484359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5354
15.2%
제 3000
 
8.5%
주 3000
 
8.5%
도 1898
 
5.4%
1 1744
 
5.0%
자 1520
 
4.3%
특 1500
 
4.3%
별 1500
 
4.3%
치 1500
 
4.3%
시 1500
 
4.3%
Other values (123) 12709
36.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21271
60.4%
Decimal Number 7391
 
21.0%
Space Separator 5354
 
15.2%
Dash Punctuation 1209
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 3000
14.1%
주 3000
14.1%
도 1898
8.9%
자 1520
 
7.1%
특 1500
 
7.1%
별 1500
 
7.1%
치 1500
 
7.1%
시 1500
 
7.1%
동 906
 
4.3%
리 612
 
2.9%
Other values (111) 4335
20.4%
Decimal Number
ValueCountFrequency (%)
1 1744
23.6%
2 1338
18.1%
3 732
9.9%
4 633
 
8.6%
6 552
 
7.5%
5 532
 
7.2%
0 518
 
7.0%
7 463
 
6.3%
9 446
 
6.0%
8 433
 
5.9%
Space Separator
ValueCountFrequency (%)
5354
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1209
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21271
60.4%
Common 13954
39.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 3000
14.1%
주 3000
14.1%
도 1898
8.9%
자 1520
 
7.1%
특 1500
 
7.1%
별 1500
 
7.1%
치 1500
 
7.1%
시 1500
 
7.1%
동 906
 
4.3%
리 612
 
2.9%
Other values (111) 4335
20.4%
Common
ValueCountFrequency (%)
5354
38.4%
1 1744
 
12.5%
2 1338
 
9.6%
- 1209
 
8.7%
3 732
 
5.2%
4 633
 
4.5%
6 552
 
4.0%
5 532
 
3.8%
0 518
 
3.7%
7 463
 
3.3%
Other values (2) 879
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21271
60.4%
ASCII 13954
39.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5354
38.4%
1 1744
 
12.5%
2 1338
 
9.6%
- 1209
 
8.7%
3 732
 
5.2%
4 633
 
4.5%
6 552
 
4.0%
5 532
 
3.8%
0 518
 
3.7%
7 463
 
3.3%
Other values (2) 879
 
6.3%
Hangul
ValueCountFrequency (%)
제 3000
14.1%
주 3000
14.1%
도 1898
8.9%
자 1520
 
7.1%
특 1500
 
7.1%
별 1500
 
7.1%
치 1500
 
7.1%
시 1500
 
7.1%
동 906
 
4.3%
리 612
 
2.9%
Other values (111) 4335
20.4%

위도 좌표
Real number (ℝ)

SKEWED 

Distinct1427
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2232876.3
Minimum33.205603
Maximum3.3492643 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-12T23:03:51.662797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.205603
5-th percentile33.349472
Q133.476156
median33.493956
Q333.513913
95-th percentile33.548127
Maximum3.3492643 × 109
Range3.3492643 × 109
Interquartile range (IQR)0.037756485

Descriptive statistics

Standard deviation86477632
Coefficient of variation (CV)38.729253
Kurtosis1500
Mean2232876.3
Median Absolute Deviation (MAD)0.01863149
Skewness38.729833
Sum3.3493145 × 109
Variance7.4783808 × 1015
MonotonicityNot monotonic
2023-12-12T23:03:51.825242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.480389 4
 
0.3%
33.492132 4
 
0.3%
33.497799 3
 
0.2%
33.51833333 3
 
0.2%
33.481483 3
 
0.2%
33.4914 3
 
0.2%
33.51694444 2
 
0.1%
33.51638889 2
 
0.1%
33.4814438 2
 
0.1%
33.490455 2
 
0.1%
Other values (1417) 1472
98.1%
ValueCountFrequency (%)
33.2056031 1
0.1%
33.2925151 1
0.1%
33.2942251 1
0.1%
33.29577381 1
0.1%
33.29595124 1
0.1%
33.29694133 1
0.1%
33.2973739 1
0.1%
33.3003159 1
0.1%
33.30126639 1
0.1%
33.30148528 1
0.1%
ValueCountFrequency (%)
3349264301.0 1
0.1%
33.96355329 1
0.1%
33.96348567 1
0.1%
33.9627366 1
0.1%
33.9626726 1
0.1%
33.96253665 1
0.1%
33.96158439 1
0.1%
33.96142967 1
0.1%
33.96098478 1
0.1%
33.9595939 1
0.1%

경도 좌표
Real number (ℝ)

SKEWED 

Distinct1436
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8431045.3
Minimum126.16068
Maximum1.2646377 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-12T23:03:52.002119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.16068
5-th percentile126.23987
Q1126.44833
median126.51976
Q3126.57166
95-th percentile126.85056
Maximum1.2646377 × 1010
Range1.2646377 × 1010
Interquartile range (IQR)0.12333115

Descriptive statistics

Standard deviation3.2652805 × 108
Coefficient of variation (CV)38.729249
Kurtosis1500
Mean8431045.3
Median Absolute Deviation (MAD)0.06207975
Skewness38.729833
Sum1.2646568 × 1010
Variance1.0662057 × 1017
MonotonicityNot monotonic
2023-12-12T23:03:52.189785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.496403 4
 
0.3%
126.523882 4
 
0.3%
126.520886 3
 
0.2%
126.43029 3
 
0.2%
126.5386111 3
 
0.2%
126.469629 3
 
0.2%
126.5035726 2
 
0.1%
126.536289 2
 
0.1%
126.541046 2
 
0.1%
126.540336 2
 
0.1%
Other values (1426) 1472
98.1%
ValueCountFrequency (%)
126.160678 1
0.1%
126.16329 1
0.1%
126.16333 1
0.1%
126.1641409 1
0.1%
126.16635 1
0.1%
126.1678414 1
0.1%
126.16866 1
0.1%
126.1737807 1
0.1%
126.17533 1
0.1%
126.1787071 1
0.1%
ValueCountFrequency (%)
12646377258.0 1
0.1%
1126.835987 1
0.1%
131.2661111 1
0.1%
126.96882 1
0.1%
126.9684719 1
0.1%
126.966782 1
0.1%
126.9643322 1
0.1%
126.96262 1
0.1%
126.96023 1
0.1%
126.96008 1
0.1%

종량제 수거함 수
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.156
Minimum0
Maximum16
Zeros44
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-12T23:03:52.304669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q33
95-th percentile5
Maximum16
Range16
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.2881914
Coefficient of variation (CV)0.59749135
Kurtosis13.565182
Mean2.156
Median Absolute Deviation (MAD)1
Skewness2.4187248
Sum3234
Variance1.659437
MonotonicityNot monotonic
2023-12-12T23:03:52.413073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2 710
47.3%
1 363
24.2%
3 242
 
16.1%
4 61
 
4.1%
0 44
 
2.9%
5 38
 
2.5%
6 26
 
1.7%
8 6
 
0.4%
7 6
 
0.4%
9 2
 
0.1%
Other values (2) 2
 
0.1%
ValueCountFrequency (%)
0 44
 
2.9%
1 363
24.2%
2 710
47.3%
3 242
 
16.1%
4 61
 
4.1%
5 38
 
2.5%
6 26
 
1.7%
7 6
 
0.4%
8 6
 
0.4%
9 2
 
0.1%
ValueCountFrequency (%)
16 1
 
0.1%
11 1
 
0.1%
9 2
 
0.1%
8 6
 
0.4%
7 6
 
0.4%
6 26
 
1.7%
5 38
 
2.5%
4 61
 
4.1%
3 242
 
16.1%
2 710
47.3%

재활용 수거함 수
Real number (ℝ)

ZEROS 

Distinct15
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.2153333
Minimum0
Maximum15
Zeros38
Zeros (%)2.5%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-12T23:03:52.528084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q13
median4
Q35
95-th percentile7
Maximum15
Range15
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.6753615
Coefficient of variation (CV)0.3974446
Kurtosis4.0878168
Mean4.2153333
Median Absolute Deviation (MAD)1
Skewness0.89692811
Sum6323
Variance2.8068361
MonotonicityNot monotonic
2023-12-12T23:03:52.630845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
4 464
30.9%
5 381
25.4%
3 311
20.7%
6 104
 
6.9%
2 91
 
6.1%
7 39
 
2.6%
0 38
 
2.5%
8 23
 
1.5%
9 18
 
1.2%
1 14
 
0.9%
Other values (5) 17
 
1.1%
ValueCountFrequency (%)
0 38
 
2.5%
1 14
 
0.9%
2 91
 
6.1%
3 311
20.7%
4 464
30.9%
5 381
25.4%
6 104
 
6.9%
7 39
 
2.6%
8 23
 
1.5%
9 18
 
1.2%
ValueCountFrequency (%)
15 1
 
0.1%
13 1
 
0.1%
12 2
 
0.1%
11 8
 
0.5%
10 5
 
0.3%
9 18
 
1.2%
8 23
 
1.5%
7 39
 
2.6%
6 104
 
6.9%
5 381
25.4%

유리병 수거함 수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
1
1192 
2
182 
0
 
112
3
 
10
4
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 1192
79.5%
2 182
 
12.1%
0 112
 
7.5%
3 10
 
0.7%
4 4
 
0.3%

Length

2023-12-12T23:03:52.750950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:03:52.888437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1192
79.5%
2 182
 
12.1%
0 112
 
7.5%
3 10
 
0.7%
4 4
 
0.3%

스티로폼 수거함 수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
1
1109 
0
341 
2
 
49
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 1109
73.9%
0 341
 
22.7%
2 49
 
3.3%
3 1
 
0.1%

Length

2023-12-12T23:03:53.026129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:03:53.139026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1109
73.9%
0 341
 
22.7%
2 49
 
3.3%
3 1
 
0.1%

폐기 건전지 수거함 수
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
1
922 
0
567 
2
 
11

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row0

Common Values

ValueCountFrequency (%)
1 922
61.5%
0 567
37.8%
2 11
 
0.7%

Length

2023-12-12T23:03:53.270038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:03:53.407750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 922
61.5%
0 567
37.8%
2 11
 
0.7%

폐기 형광등 수거함 수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
1
1020 
0
411 
3
 
49
2
 
18
4
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row0

Common Values

ValueCountFrequency (%)
1 1020
68.0%
0 411
27.4%
3 49
 
3.3%
2 18
 
1.2%
4 2
 
0.1%

Length

2023-12-12T23:03:53.527678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:03:53.665954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1020
68.0%
0 411
27.4%
3 49
 
3.3%
2 18
 
1.2%
4 2
 
0.1%

음식물 수거함 수
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0353333
Minimum0
Maximum8
Zeros146
Zeros (%)9.7%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-12T23:03:53.792140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile4
Maximum8
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.1361978
Coefficient of variation (CV)0.55823673
Kurtosis0.53826477
Mean2.0353333
Median Absolute Deviation (MAD)1
Skewness0.32144299
Sum3053
Variance1.2909455
MonotonicityNot monotonic
2023-12-12T23:03:53.939452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2 657
43.8%
1 271
18.1%
3 270
18.0%
0 146
 
9.7%
4 128
 
8.5%
5 24
 
1.6%
6 3
 
0.2%
8 1
 
0.1%
ValueCountFrequency (%)
0 146
 
9.7%
1 271
18.1%
2 657
43.8%
3 270
18.0%
4 128
 
8.5%
5 24
 
1.6%
6 3
 
0.2%
8 1
 
0.1%
ValueCountFrequency (%)
8 1
 
0.1%
6 3
 
0.2%
5 24
 
1.6%
4 128
 
8.5%
3 270
18.0%
2 657
43.8%
1 271
18.1%
0 146
 
9.7%

음식물 계량 수거함 수
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.91466667
Minimum0
Maximum5
Zeros164
Zeros (%)10.9%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-12T23:03:54.082174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile1
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.38054535
Coefficient of variation (CV)0.41604813
Kurtosis17.530027
Mean0.91466667
Median Absolute Deviation (MAD)0
Skewness0.58794255
Sum1372
Variance0.14481477
MonotonicityNot monotonic
2023-12-12T23:03:54.212613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 1309
87.3%
0 164
 
10.9%
2 22
 
1.5%
3 2
 
0.1%
4 2
 
0.1%
5 1
 
0.1%
ValueCountFrequency (%)
0 164
 
10.9%
1 1309
87.3%
2 22
 
1.5%
3 2
 
0.1%
4 2
 
0.1%
5 1
 
0.1%
ValueCountFrequency (%)
5 1
 
0.1%
4 2
 
0.1%
3 2
 
0.1%
2 22
 
1.5%
1 1309
87.3%
0 164
 
10.9%

CCTV 설치 수
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6153333
Minimum0
Maximum12
Zeros350
Zeros (%)23.3%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-12T23:03:54.357453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q32
95-th percentile3
Maximum12
Range12
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1291065
Coefficient of variation (CV)0.69899288
Kurtosis6.3987848
Mean1.6153333
Median Absolute Deviation (MAD)0
Skewness0.86209446
Sum2423
Variance1.2748815
MonotonicityNot monotonic
2023-12-12T23:03:54.493926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2 874
58.3%
0 350
23.3%
1 126
 
8.4%
3 84
 
5.6%
4 51
 
3.4%
5 8
 
0.5%
6 3
 
0.2%
7 2
 
0.1%
12 1
 
0.1%
9 1
 
0.1%
ValueCountFrequency (%)
0 350
23.3%
1 126
 
8.4%
2 874
58.3%
3 84
 
5.6%
4 51
 
3.4%
5 8
 
0.5%
6 3
 
0.2%
7 2
 
0.1%
9 1
 
0.1%
12 1
 
0.1%
ValueCountFrequency (%)
12 1
 
0.1%
9 1
 
0.1%
7 2
 
0.1%
6 3
 
0.2%
5 8
 
0.5%
4 51
 
3.4%
3 84
 
5.6%
2 874
58.3%
1 126
 
8.4%
0 350
23.3%

특이사항 내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1500
Missing (%)100.0%
Memory size13.3 KiB

사진 여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
True
1500 
ValueCountFrequency (%)
True 1500
100.0%
2023-12-12T23:03:54.623587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

기타 내용
Text

MISSING 

Distinct107
Distinct (%)49.5%
Missing1284
Missing (%)85.6%
Memory size11.8 KiB
2023-12-12T23:03:54.866057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length31
Mean length12.259259
Min length1

Characters and Unicode

Total characters2648
Distinct characters158
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)33.3%

Sample

1st row21년4월 신설
2nd row지목확인 필요
3rd row21년10월 RFID 1대 추가
4th row2022.03.25 신설
5th row명월리 382-2 명월상동 팽나무 공터에서 이설
ValueCountFrequency (%)
비가림 41
 
8.7%
신설 31
 
6.6%
구형음식물쓰레기통 29
 
6.1%
설치 26
 
5.5%
이설 20
 
4.2%
21년6월 18
 
3.8%
21년5월 16
 
3.4%
신규 12
 
2.5%
21년9월 9
 
1.9%
추가 7
 
1.5%
Other values (149) 263
55.7%
2023-12-12T23:03:55.284710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
257
 
9.7%
1 161
 
6.1%
2 147
 
5.6%
설 99
 
3.7%
0 88
 
3.3%
가 77
 
2.9%
. 67
 
2.5%
림 66
 
2.5%
비 66
 
2.5%
월 61
 
2.3%
Other values (148) 1559
58.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1429
54.0%
Decimal Number 613
23.1%
Space Separator 257
 
9.7%
Uppercase Letter 137
 
5.2%
Other Punctuation 107
 
4.0%
Open Punctuation 40
 
1.5%
Close Punctuation 39
 
1.5%
Dash Punctuation 13
 
0.5%
Lowercase Letter 7
 
0.3%
Math Symbol 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
설 99
 
6.9%
가 77
 
5.4%
림 66
 
4.6%
비 66
 
4.6%
월 61
 
4.3%
년 59
 
4.1%
신 56
 
3.9%
이 47
 
3.3%
치 38
 
2.7%
음 35
 
2.4%
Other values (117) 825
57.7%
Decimal Number
ValueCountFrequency (%)
1 161
26.3%
2 147
24.0%
0 88
14.4%
5 58
 
9.5%
6 36
 
5.9%
3 32
 
5.2%
9 27
 
4.4%
7 23
 
3.8%
8 21
 
3.4%
4 20
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
C 52
38.0%
L 44
32.1%
D 8
 
5.8%
I 8
 
5.8%
F 8
 
5.8%
R 8
 
5.8%
T 4
 
2.9%
V 4
 
2.9%
X 1
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 67
62.6%
/ 38
35.5%
, 2
 
1.9%
Lowercase Letter
ValueCountFrequency (%)
m 5
71.4%
g 1
 
14.3%
k 1
 
14.3%
Space Separator
ValueCountFrequency (%)
257
100.0%
Open Punctuation
ValueCountFrequency (%)
( 40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Math Symbol
ValueCountFrequency (%)
> 5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1428
53.9%
Common 1075
40.6%
Latin 144
 
5.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
설 99
 
6.9%
가 77
 
5.4%
림 66
 
4.6%
비 66
 
4.6%
월 61
 
4.3%
년 59
 
4.1%
신 56
 
3.9%
이 47
 
3.3%
치 38
 
2.7%
음 35
 
2.5%
Other values (116) 824
57.7%
Common
ValueCountFrequency (%)
257
23.9%
1 161
15.0%
2 147
13.7%
0 88
 
8.2%
. 67
 
6.2%
5 58
 
5.4%
( 40
 
3.7%
) 39
 
3.6%
/ 38
 
3.5%
6 36
 
3.3%
Other values (9) 144
13.4%
Latin
ValueCountFrequency (%)
C 52
36.1%
L 44
30.6%
D 8
 
5.6%
I 8
 
5.6%
F 8
 
5.6%
R 8
 
5.6%
m 5
 
3.5%
T 4
 
2.8%
V 4
 
2.8%
g 1
 
0.7%
Other values (2) 2
 
1.4%
Han
ValueCountFrequency (%)
無 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1428
53.9%
ASCII 1219
46.0%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
257
21.1%
1 161
13.2%
2 147
12.1%
0 88
 
7.2%
. 67
 
5.5%
5 58
 
4.8%
C 52
 
4.3%
L 44
 
3.6%
( 40
 
3.3%
) 39
 
3.2%
Other values (21) 266
21.8%
Hangul
ValueCountFrequency (%)
설 99
 
6.9%
가 77
 
5.4%
림 66
 
4.6%
비 66
 
4.6%
월 61
 
4.3%
년 59
 
4.1%
신 56
 
3.9%
이 47
 
3.3%
치 38
 
2.7%
음 35
 
2.5%
Other values (116) 824
57.7%
CJK
ValueCountFrequency (%)
無 1
100.0%

등록 일시
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
Minimum2022-10-30 00:00:00
Maximum2022-10-30 00:00:00
2023-12-12T23:03:55.415367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:55.523901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Sample

데이터 코드구분 명읍면동 명단지 명유형 명도로명 주소지번 주소위도 좌표경도 좌표종량제 수거함 수재활용 수거함 수유리병 수거함 수스티로폼 수거함 수폐기 건전지 수거함 수폐기 형광등 수거함 수음식물 수거함 수음식물 계량 수거함 수CCTV 설치 수특이사항 내용사진 여부기타 내용등록 일시
0CL0001클린하우스한림읍리사무소 앞비가림시설제주특별자치도 제주시 한림읍 한림리 1328-62제주특별자치도 제주시 한림읍 한림리 1328-6233.4159126.26255461111413<NA>Y<NA>2022-10-30 00:00:00
1CL0002클린하우스한림읍영신연립 옆 한흥블럭사비가림시설제주특별자치도 제주시 한림읍 한림리 1531-4제주특별자치도 제주시 한림읍 한림리 1531-433.41095126.26376241111312<NA>Y<NA>2022-10-30 00:00:00
2CL0003클린하우스한림읍왕수학교실 삼거리 (회성푸르니 아파트 앞)비가림시설제주특별자치도 제주시 한림읍 한림리 1450-2제주특별자치도 제주시 한림읍 한림리 1450-233.41234126.26424341111313<NA>Y<NA>2022-10-30 00:00:00
3CL0004클린하우스한림읍수타명가 남측비가림시설제주특별자치도 제주시 한림읍 귀덕리 3008제주특별자치도 제주시 한림읍 귀덕리 300833.441225126.290265241111212<NA>Y<NA>2022-10-30 00:00:00
4CL0005클린하우스한림읍대림하동길 마을 끝비가림시설/거치대제주특별자치도 제주시 한림읍 대림리 1268-2제주특별자치도 제주시 한림읍 대림리 1268-233.427082126.279515141100112<NA>Y21년4월 신설2022-10-30 00:00:00
5CL0006클린하우스한림읍감협 맞은편비가림시설제주특별자치도 제주시 한림읍 명랑로 16제주특별자치도 제주시 한림읍 한림리 158233.41455126.26678341111313<NA>Y<NA>2022-10-30 00:00:00
6CL0007클린하우스한림읍한림공고 후문 옆비가림시설제주특별자치도 제주시 한림읍 동명리 1540-11제주특별자치도 제주시 한림읍 동명리 1540-1133.40563126.2689241111212<NA>Y<NA>2022-10-30 00:00:00
7CL0008클린하우스한림읍산아진동산비가림시설제주특별자치도 제주시 한림읍 한림남1길 29제주특별자치도 제주시 한림읍 한림리 158233.41231126.2677241111213<NA>Y<NA>2022-10-30 00:00:00
8CL0009클린하우스한림읍금악리 농협창고 주변비가림시설제주특별자치도 제주시 한림읍 금악리 2234-1제주특별자치도 제주시 한림읍 금악리 2234-133.361484126.295655131111112<NA>Y<NA>2022-10-30 00:00:00
9CL0010클린하우스한림읍천주교 버스정류소 옆비가림시설제주특별자치도 제주시 한림읍 대림리 1814제주특별자치도 제주시 한림읍 대림리 181433.41755126.26513341111312<NA>Y지목확인 필요2022-10-30 00:00:00
데이터 코드구분 명읍면동 명단지 명유형 명도로명 주소지번 주소위도 좌표경도 좌표종량제 수거함 수재활용 수거함 수유리병 수거함 수스티로폼 수거함 수폐기 건전지 수거함 수폐기 형광등 수거함 수음식물 수거함 수음식물 계량 수거함 수CCTV 설치 수특이사항 내용사진 여부기타 내용등록 일시
1490CL3007재활용도움센터구좌읍송당리재활용도움센터제주특별자치도 제주시 구좌읍 중산간동로 2202-14제주특별자치도 제주시 구좌읍 송당리 1565번지33.511429126.70106671211310<NA>Y신규2022-10-30 00:00:00
1491CL3008재활용도움센터구좌읍동복리재활용도움센터제주특별자치도 제주시 구좌읍 동복로 75-10제주특별자치도 제주시 구좌읍 동복리 1575-533.553743126.714105491113210<NA>Y신규2022-10-30 00:00:00
1492CL3009재활용도움센터구좌읍김녕리재활용도움센터제주특별자치도 제주시 구좌읍 김녕로8길 32-8제주특별자치도 제주시 구좌읍 김녕리 1793-333.551935126.748822491113312<NA>Y신규2022-10-30 00:00:00
1493CL3010클린하우스아라동한천저류지 소공원거치대제주특별자치도 제주시 오등동 1834-96제주특별자치도 제주시 오등동 1834-9633.447134126.522753130000000<NA>Y신규2022-10-30 00:00:00
1494CL3011재활용도움센터추자면대서리재활용도움센터제주특별자치도 제주시 추자면 대서리 147-16제주특별자치도 제주시 추자면 대서리 147-1633.961584126.294163470113214<NA>Y신규2022-10-30 00:00:00
1495CL5001재활용도움센터노형동노형동재활용도움센터제주특별자치도 제주시 수덕5길 34제주특별자치도 제주시 노형동 2612-233.485729126.47464461111510<NA>Y신규2022-10-30 00:00:00
1496CL5002재활용도움센터삼도1동미래컨벤션센터 동측재활용도움센터제주특별자치도 제주시 전농로1길 26제주특별자치도 제주시 삼도1동 715-1133.506445126.515313681113333<NA>Y신규(철거 후 생성)2022-10-30 00:00:00
1497CL5003클린하우스연동신제주마트 옆비가림시설제주특별자치도 제주시 신광로 87제주특별자치도 제주시 연동 274-5133.484508126.490521692101313<NA>Y신규2022-10-30 00:00:00
1498CL5004재활용도움센터노형동노형동 921 옆 원노형마을회관 동측 롯데마트 반대편재활용도움센터제주특별자치도 제주시 원노형2길 33-6제주특별자치도 제주시 노형동 92133.482627126.4822547101213451<NA>Y신규(철거 후 생성)2022-10-30 00:00:00
1499CL5005재활용도움센터일도1동남수각주차장 남쪽거치대제주특별자치도 제주시 성지로 32제주특별자치도 제주시 일도1동 1488-333.510407126.526929000000000<NA>Y신규(공사중)2022-10-30 00:00:00