Overview

Dataset statistics

Number of variables20
Number of observations193
Missing cells590
Missing cells (%)15.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory31.8 KiB
Average record size in memory168.7 B

Variable types

Categorical6
Text4
Numeric5
Unsupported3
DateTime1
Boolean1

Dataset

Description경기도 화학사고 대피 장소 목록
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=DSYCVFZBU997A803DAY431494959&infSeq=1

Alerts

광역시도명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
표지판설치동의여부 has constant value ""Constant
관할부서전화번호 is highly overall correlated with 정제우편번호 and 5 other fieldsHigh correlation
관할기관및부서명칭 is highly overall correlated with 정제우편번호 and 5 other fieldsHigh correlation
시군명 is highly overall correlated with 정제우편번호 and 5 other fieldsHigh correlation
수용면적 is highly overall correlated with 수용인원High correlation
수용인원 is highly overall correlated with 수용면적High correlation
정제우편번호 is highly overall correlated with 정제WGS84위도 and 3 other fieldsHigh correlation
정제WGS84위도 is highly overall correlated with 정제우편번호 and 3 other fieldsHigh correlation
정제WGS84경도 is highly overall correlated with 시군명 and 2 other fieldsHigh correlation
시설구분 is highly overall correlated with 시군명 and 2 other fieldsHigh correlation
대피장소담당자명 has 193 (100.0%) missing valuesMissing
대피장소담당자연락처 has 193 (100.0%) missing valuesMissing
비고 has 193 (100.0%) missing valuesMissing
정제도로명주소 has 3 (1.6%) missing valuesMissing
정제우편번호 has 2 (1.0%) missing valuesMissing
정제WGS84위도 has 3 (1.6%) missing valuesMissing
정제WGS84경도 has 3 (1.6%) missing valuesMissing
대피장소관리번호 has unique valuesUnique
대피장소명 has unique valuesUnique
대피장소담당자명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
대피장소담당자연락처 is an unsupported type, check if it needs cleaning or further analysisUnsupported
비고 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-12 23:57:06.419827
Analysis finished2024-03-12 23:57:09.615043
Duration3.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

광역시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
경기도
193 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 193
100.0%

Length

2024-03-13T08:57:09.661858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:57:09.731079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 193
100.0%

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
오산시
14 
고양시
14 
평택시
14 
용인시
14 
화성시
13 
Other values (26)
124 

Length

Max length4
Median length3
Mean length3.0518135
Min length3

Unique

Unique7 ?
Unique (%)3.6%

Sample

1st row여주시
2nd row연천군
3rd row오산시
4th row오산시
5th row오산시

Common Values

ValueCountFrequency (%)
오산시 14
 
7.3%
고양시 14
 
7.3%
평택시 14
 
7.3%
용인시 14
 
7.3%
화성시 13
 
6.7%
시흥시 12
 
6.2%
수원시 12
 
6.2%
이천시 11
 
5.7%
광주시 10
 
5.2%
군포시 7
 
3.6%
Other values (21) 72
37.3%

Length

2024-03-13T08:57:09.809868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
오산시 14
 
7.3%
평택시 14
 
7.3%
용인시 14
 
7.3%
고양시 14
 
7.3%
화성시 13
 
6.7%
시흥시 12
 
6.2%
수원시 12
 
6.2%
이천시 11
 
5.7%
광주시 10
 
5.2%
군포시 7
 
3.6%
Other values (21) 72
37.3%

대피장소관리번호
Text

UNIQUE 

Distinct193
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-03-13T08:57:10.037869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length7.2072539
Min length6

Characters and Unicode

Total characters1391
Distinct characters50
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique193 ?
Unique (%)100.0%

Sample

1st row여주-화학-1
2nd row연천-화학-1
3rd row오산-화학-1
4th row오산-화학-2
5th row오산-화학-3
ValueCountFrequency (%)
여주-화학-1 1
 
0.5%
안양-화학-6 1
 
0.5%
파주-화학-4 1
 
0.5%
의정부-화학-3 1
 
0.5%
이천-화학-1 1
 
0.5%
이천-화학-3 1
 
0.5%
이천-화학-8 1
 
0.5%
이천-화학-10 1
 
0.5%
이천-화학-11 1
 
0.5%
이천-화학-13 1
 
0.5%
Other values (183) 183
94.8%
2024-03-13T08:57:10.390465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 380
27.3%
화 206
14.8%
학 193
13.9%
1 75
 
5.4%
2 32
 
2.3%
양 28
 
2.0%
3 28
 
2.0%
천 25
 
1.8%
4 25
 
1.8%
주 24
 
1.7%
Other values (40) 375
27.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 782
56.2%
Dash Punctuation 380
27.3%
Decimal Number 229
 
16.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
화 206
26.3%
학 193
24.7%
양 28
 
3.6%
천 25
 
3.2%
주 24
 
3.1%
포 21
 
2.7%
산 18
 
2.3%
평 16
 
2.0%
성 15
 
1.9%
택 14
 
1.8%
Other values (29) 222
28.4%
Decimal Number
ValueCountFrequency (%)
1 75
32.8%
2 32
14.0%
3 28
 
12.2%
4 25
 
10.9%
5 16
 
7.0%
6 15
 
6.6%
7 11
 
4.8%
0 9
 
3.9%
9 9
 
3.9%
8 9
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 380
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 782
56.2%
Common 609
43.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
화 206
26.3%
학 193
24.7%
양 28
 
3.6%
천 25
 
3.2%
주 24
 
3.1%
포 21
 
2.7%
산 18
 
2.3%
평 16
 
2.0%
성 15
 
1.9%
택 14
 
1.8%
Other values (29) 222
28.4%
Common
ValueCountFrequency (%)
- 380
62.4%
1 75
 
12.3%
2 32
 
5.3%
3 28
 
4.6%
4 25
 
4.1%
5 16
 
2.6%
6 15
 
2.5%
7 11
 
1.8%
0 9
 
1.5%
9 9
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 782
56.2%
ASCII 609
43.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 380
62.4%
1 75
 
12.3%
2 32
 
5.3%
3 28
 
4.6%
4 25
 
4.1%
5 16
 
2.6%
6 15
 
2.5%
7 11
 
1.8%
0 9
 
1.5%
9 9
 
1.5%
Hangul
ValueCountFrequency (%)
화 206
26.3%
학 193
24.7%
양 28
 
3.6%
천 25
 
3.2%
주 24
 
3.1%
포 21
 
2.7%
산 18
 
2.3%
평 16
 
2.0%
성 15
 
1.9%
택 14
 
1.8%
Other values (29) 222
28.4%

시설구분
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
학교
100 
공공시설
28 
관공서
18 
체육관
18 
공공기관
 
10
Other values (7)
19 

Length

Max length10
Median length2
Mean length2.7668394
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row관공서
2nd row체육시설
3rd row학교
4th row기타시설
5th row기타시설

Common Values

ValueCountFrequency (%)
학교 100
51.8%
공공시설 28
 
14.5%
관공서 18
 
9.3%
체육관 18
 
9.3%
공공기관 10
 
5.2%
마을회관 4
 
2.1%
체육시설 3
 
1.6%
강당 3
 
1.6%
본관 3
 
1.6%
기타시설 2
 
1.0%
Other values (2) 4
 
2.1%

Length

2024-03-13T08:57:10.514034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
학교 100
51.8%
공공시설 28
 
14.5%
관공서 18
 
9.3%
체육관 18
 
9.3%
공공기관 10
 
5.2%
마을회관 4
 
2.1%
체육시설 3
 
1.6%
강당 3
 
1.6%
본관 3
 
1.6%
기타시설 2
 
1.0%
Other values (2) 4
 
2.1%

대피장소명
Text

UNIQUE 

Distinct193
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-03-13T08:57:10.715037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length7.015544
Min length4

Characters and Unicode

Total characters1354
Distinct characters201
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique193 ?
Unique (%)100.0%

Sample

1st row여주실내체육관
2nd row장남면 배드민턴장
3rd row운천초등학교
4th row오산스포츠센터
5th row죽미다목적체육관
ValueCountFrequency (%)
체육관 10
 
4.5%
행정복지센터 8
 
3.6%
다목적체육관 2
 
0.9%
여주실내체육관 1
 
0.4%
갈현초등학교 1
 
0.4%
녹양중학교 1
 
0.4%
이천사동초등학교 1
 
0.4%
효양고등학교 1
 
0.4%
신하초등학교 1
 
0.4%
아미초등학교 1
 
0.4%
Other values (196) 196
87.9%
2024-03-13T08:57:11.019371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 136
 
10.0%
학 135
 
10.0%
등 101
 
7.5%
초 84
 
6.2%
관 44
 
3.2%
중 38
 
2.8%
체 34
 
2.5%
육 34
 
2.5%
30
 
2.2%
터 23
 
1.7%
Other values (191) 695
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1316
97.2%
Space Separator 30
 
2.2%
Decimal Number 8
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 136
 
10.3%
학 135
 
10.3%
등 101
 
7.7%
초 84
 
6.4%
관 44
 
3.3%
중 38
 
2.9%
체 34
 
2.6%
육 34
 
2.6%
터 23
 
1.7%
센 22
 
1.7%
Other values (186) 665
50.5%
Decimal Number
ValueCountFrequency (%)
2 4
50.0%
3 2
25.0%
1 1
 
12.5%
4 1
 
12.5%
Space Separator
ValueCountFrequency (%)
30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1316
97.2%
Common 38
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 136
 
10.3%
학 135
 
10.3%
등 101
 
7.7%
초 84
 
6.4%
관 44
 
3.3%
중 38
 
2.9%
체 34
 
2.6%
육 34
 
2.6%
터 23
 
1.7%
센 22
 
1.7%
Other values (186) 665
50.5%
Common
ValueCountFrequency (%)
30
78.9%
2 4
 
10.5%
3 2
 
5.3%
1 1
 
2.6%
4 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1316
97.2%
ASCII 38
 
2.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 136
 
10.3%
학 135
 
10.3%
등 101
 
7.7%
초 84
 
6.4%
관 44
 
3.3%
중 38
 
2.9%
체 34
 
2.6%
육 34
 
2.6%
터 23
 
1.7%
센 22
 
1.7%
Other values (186) 665
50.5%
ASCII
ValueCountFrequency (%)
30
78.9%
2 4
 
10.5%
3 2
 
5.3%
1 1
 
2.6%
4 1
 
2.6%

상세시설명
Categorical

Distinct34
Distinct (%)17.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
체육관
88 
학교
34 
강당
20 
교사동
 
8
본관
 
4
Other values (29)
39 

Length

Max length17
Median length3
Mean length3.2124352
Min length2

Unique

Unique22 ?
Unique (%)11.4%

Sample

1st row실내체육관
2nd row체육시설
3rd row체육관
4th row체육관
5th row체육관

Common Values

ValueCountFrequency (%)
체육관 88
45.6%
학교 34
 
17.6%
강당 20
 
10.4%
교사동 8
 
4.1%
본관 4
 
2.1%
마을회관 4
 
2.1%
다목적실 3
 
1.6%
급식실 2
 
1.0%
본관 교실 전체 2
 
1.0%
대회의실 2
 
1.0%
Other values (24) 26
 
13.5%

Length

2024-03-13T08:57:11.136775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
체육관 88
43.3%
학교 34
 
16.7%
강당 20
 
9.9%
교사동 8
 
3.9%
본관 6
 
3.0%
다목적실 5
 
2.5%
마을회관 4
 
2.0%
교실 3
 
1.5%
대회의실 3
 
1.5%
다목적체육관 2
 
1.0%
Other values (25) 30
 
14.8%

수용면적
Real number (ℝ)

HIGH CORRELATION 

Distinct181
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1668.6839
Minimum33
Maximum13989
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-03-13T08:57:11.241199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33
5-th percentile190.2
Q1486
median774
Q31335
95-th percentile8471.8
Maximum13989
Range13956
Interquartile range (IQR)849

Descriptive statistics

Standard deviation2430.8988
Coefficient of variation (CV)1.456776
Kurtosis6.8117909
Mean1668.6839
Median Absolute Deviation (MAD)374
Skewness2.6534473
Sum322056
Variance5909268.8
MonotonicityNot monotonic
2024-03-13T08:57:11.343143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
616 2
 
1.0%
880 2
 
1.0%
718 2
 
1.0%
662 2
 
1.0%
665 2
 
1.0%
1200 2
 
1.0%
486 2
 
1.0%
309 2
 
1.0%
742 2
 
1.0%
1199 2
 
1.0%
Other values (171) 173
89.6%
ValueCountFrequency (%)
33 1
0.5%
39 1
0.5%
96 1
0.5%
119 1
0.5%
132 1
0.5%
141 1
0.5%
166 1
0.5%
175 1
0.5%
180 1
0.5%
186 1
0.5%
ValueCountFrequency (%)
13989 1
0.5%
10835 1
0.5%
10684 1
0.5%
9497 1
0.5%
9140 1
0.5%
9000 1
0.5%
8662 1
0.5%
8565 1
0.5%
8520 1
0.5%
8476 1
0.5%

수용인원
Real number (ℝ)

HIGH CORRELATION 

Distinct182
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1795.3679
Minimum30
Maximum16956
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-03-13T08:57:11.450893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile140.4
Q1442
median846
Q31376
95-th percentile9639
Maximum16956
Range16926
Interquartile range (IQR)934

Descriptive statistics

Standard deviation2811.0148
Coefficient of variation (CV)1.5657041
Kurtosis8.7496304
Mean1795.3679
Median Absolute Deviation (MAD)445
Skewness2.9391128
Sum346506
Variance7901804.3
MonotonicityNot monotonic
2024-03-13T08:57:11.559511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
840 2
 
1.0%
234 2
 
1.0%
899 2
 
1.0%
507 2
 
1.0%
374 2
 
1.0%
778 2
 
1.0%
936 2
 
1.0%
589 2
 
1.0%
201 2
 
1.0%
1099 2
 
1.0%
Other values (172) 173
89.6%
ValueCountFrequency (%)
30 1
0.5%
36 1
0.5%
40 1
0.5%
47 1
0.5%
54 1
0.5%
65 1
0.5%
100 1
0.5%
103 1
0.5%
120 1
0.5%
126 1
0.5%
ValueCountFrequency (%)
16956 1
0.5%
13133 1
0.5%
12950 1
0.5%
11510 1
0.5%
11079 1
0.5%
10499 1
0.5%
10327 1
0.5%
10264 1
0.5%
10000 1
0.5%
9810 1
0.5%

관할기관및부서명칭
Categorical

HIGH CORRELATION 

Distinct33
Distinct (%)17.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
평택시 환경지도과
14 
용인시청 기후에너지과
14 
고양시 환경정책과
14 
오산시 환경과
14 
환경사업소 환경지도과
13 
Other values (28)
124 

Length

Max length12
Median length11
Mean length9.1968912
Min length7

Unique

Unique9 ?
Unique (%)4.7%

Sample

1st row여주도시관리공단
2nd row연천군청 장남면사무소
3rd row오산시 환경과
4th row오산시 환경과
5th row오산시 환경과

Common Values

ValueCountFrequency (%)
평택시 환경지도과 14
 
7.3%
용인시청 기후에너지과 14
 
7.3%
고양시 환경정책과 14
 
7.3%
오산시 환경과 14
 
7.3%
환경사업소 환경지도과 13
 
6.7%
시흥시 환경정책과 12
 
6.2%
수원시청 환경정책과 12
 
6.2%
이천시 환경보호과 11
 
5.7%
광주시 수질정책과 10
 
5.2%
포천시 환경지도과 7
 
3.6%
Other values (23) 72
37.3%

Length

2024-03-13T08:57:11.693339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
환경정책과 55
 
14.3%
환경지도과 41
 
10.6%
환경과 37
 
9.6%
기후에너지과 18
 
4.7%
오산시 14
 
3.6%
평택시 14
 
3.6%
고양시 14
 
3.6%
용인시청 14
 
3.6%
환경사업소 13
 
3.4%
환경보호과 13
 
3.4%
Other values (34) 152
39.5%

관할부서전화번호
Categorical

HIGH CORRELATION 

Distinct33
Distinct (%)17.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
031-8036-6423
14 
031-8024-3786
14 
031-8075-2661
14 
031-324-2244
14 
031-5189-1923
13 
Other values (28)
124 

Length

Max length13
Median length12
Mean length12.331606
Min length12

Unique

Unique9 ?
Unique (%)4.7%

Sample

1st row031-880-4021
2nd row031-839-2710
3rd row031-8036-6423
4th row031-8036-6423
5th row031-8036-6423

Common Values

ValueCountFrequency (%)
031-8036-6423 14
 
7.3%
031-8024-3786 14
 
7.3%
031-8075-2661 14
 
7.3%
031-324-2244 14
 
7.3%
031-5189-1923 13
 
6.7%
031-310-5994 12
 
6.2%
031-228-3243 12
 
6.2%
031-644-2349 11
 
5.7%
031-760-3765 10
 
5.2%
031-538-3243 7
 
3.6%
Other values (23) 72
37.3%

Length

2024-03-13T08:57:11.805854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
031-8036-6423 14
 
7.3%
031-8075-2661 14
 
7.3%
031-324-2244 14
 
7.3%
031-8024-3786 14
 
7.3%
031-5189-1923 13
 
6.7%
031-310-5994 12
 
6.2%
031-228-3243 12
 
6.2%
031-644-2349 11
 
5.7%
031-760-3765 10
 
5.2%
031-980-5655 7
 
3.6%
Other values (23) 72
37.3%

대피장소담당자명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing193
Missing (%)100.0%
Memory size1.8 KiB

대피장소담당자연락처
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing193
Missing (%)100.0%
Memory size1.8 KiB

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum2023-12-31 00:00:00
Maximum2023-12-31 00:00:00
2024-03-13T08:57:11.882520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:57:11.950227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

표지판설치동의여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size325.0 B
True
193 
ValueCountFrequency (%)
True 193
100.0%
2024-03-13T08:57:12.018244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

비고
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing193
Missing (%)100.0%
Memory size1.8 KiB

정제도로명주소
Text

MISSING 

Distinct189
Distinct (%)99.5%
Missing3
Missing (%)1.6%
Memory size1.6 KiB
2024-03-13T08:57:12.190372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25.5
Mean length19.136842
Min length13

Characters and Unicode

Total characters3636
Distinct characters199
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

Unique188 ?
Unique (%)98.9%

Sample

1st row경기도 여주시 영릉로 123
2nd row경기도 연천군 장남면 장백로 244
3rd row경기도 오산시 운암로 116
4th row경기도 오산시 경기동로 33
5th row경기도 오산시 수청로 204-26
ValueCountFrequency (%)
경기도 190
 
21.7%
오산시 14
 
1.6%
평택시 14
 
1.6%
고양시 14
 
1.6%
화성시 13
 
1.5%
용인시 13
 
1.5%
수원시 12
 
1.4%
시흥시 12
 
1.4%
광주시 10
 
1.1%
이천시 10
 
1.1%
Other values (405) 572
65.4%
2024-03-13T08:57:12.508943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
684
18.8%
시 200
 
5.5%
경 197
 
5.4%
기 197
 
5.4%
도 194
 
5.3%
로 173
 
4.8%
1 115
 
3.2%
3 95
 
2.6%
2 95
 
2.6%
길 70
 
1.9%
Other values (189) 1616
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2284
62.8%
Space Separator 684
 
18.8%
Decimal Number 641
 
17.6%
Dash Punctuation 27
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 200
 
8.8%
경 197
 
8.6%
기 197
 
8.6%
도 194
 
8.5%
로 173
 
7.6%
길 70
 
3.1%
구 59
 
2.6%
번 53
 
2.3%
산 42
 
1.8%
양 41
 
1.8%
Other values (177) 1058
46.3%
Decimal Number
ValueCountFrequency (%)
1 115
17.9%
3 95
14.8%
2 95
14.8%
5 62
9.7%
7 59
9.2%
4 53
8.3%
0 49
7.6%
6 39
 
6.1%
8 38
 
5.9%
9 36
 
5.6%
Space Separator
ValueCountFrequency (%)
684
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2284
62.8%
Common 1352
37.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 200
 
8.8%
경 197
 
8.6%
기 197
 
8.6%
도 194
 
8.5%
로 173
 
7.6%
길 70
 
3.1%
구 59
 
2.6%
번 53
 
2.3%
산 42
 
1.8%
양 41
 
1.8%
Other values (177) 1058
46.3%
Common
ValueCountFrequency (%)
684
50.6%
1 115
 
8.5%
3 95
 
7.0%
2 95
 
7.0%
5 62
 
4.6%
7 59
 
4.4%
4 53
 
3.9%
0 49
 
3.6%
6 39
 
2.9%
8 38
 
2.8%
Other values (2) 63
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2284
62.8%
ASCII 1352
37.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
684
50.6%
1 115
 
8.5%
3 95
 
7.0%
2 95
 
7.0%
5 62
 
4.6%
7 59
 
4.4%
4 53
 
3.9%
0 49
 
3.6%
6 39
 
2.9%
8 38
 
2.8%
Other values (2) 63
 
4.7%
Hangul
ValueCountFrequency (%)
시 200
 
8.8%
경 197
 
8.6%
기 197
 
8.6%
도 194
 
8.5%
로 173
 
7.6%
길 70
 
3.1%
구 59
 
2.6%
번 53
 
2.3%
산 42
 
1.8%
양 41
 
1.8%
Other values (177) 1058
46.3%

정제지번주소
Text

Distinct192
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-03-13T08:57:12.778434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length23
Mean length20.595855
Min length15

Characters and Unicode

Total characters3975
Distinct characters172
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

Unique191 ?
Unique (%)99.0%

Sample

1st row경기도 여주시 월송동 1번지
2nd row경기도 연천군 장남면 원당리 681-5번지
3rd row경기도 오산시 부산동 778-4번지
4th row경기도 오산시 오산동 40번지
5th row경기도 오산시 금암동 508번지
ValueCountFrequency (%)
경기도 193
 
21.7%
용인시 14
 
1.6%
고양시 14
 
1.6%
오산시 14
 
1.6%
평택시 14
 
1.6%
화성시 13
 
1.5%
수원시 12
 
1.3%
시흥시 12
 
1.3%
이천시 11
 
1.2%
광주시 10
 
1.1%
Other values (417) 583
65.5%
2024-03-13T08:57:13.132548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
697
17.5%
시 202
 
5.1%
지 201
 
5.1%
도 199
 
5.0%
기 198
 
5.0%
경 193
 
4.9%
번 192
 
4.8%
동 142
 
3.6%
1 117
 
2.9%
2 95
 
2.4%
Other values (162) 1739
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2495
62.8%
Space Separator 697
 
17.5%
Decimal Number 693
 
17.4%
Dash Punctuation 90
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 202
 
8.1%
지 201
 
8.1%
도 199
 
8.0%
기 198
 
7.9%
경 193
 
7.7%
번 192
 
7.7%
동 142
 
5.7%
리 71
 
2.8%
구 58
 
2.3%
산 45
 
1.8%
Other values (150) 994
39.8%
Decimal Number
ValueCountFrequency (%)
1 117
16.9%
2 95
13.7%
5 75
10.8%
4 70
10.1%
6 64
9.2%
3 63
9.1%
7 57
8.2%
8 56
8.1%
0 53
7.6%
9 43
 
6.2%
Space Separator
ValueCountFrequency (%)
697
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 90
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2495
62.8%
Common 1480
37.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 202
 
8.1%
지 201
 
8.1%
도 199
 
8.0%
기 198
 
7.9%
경 193
 
7.7%
번 192
 
7.7%
동 142
 
5.7%
리 71
 
2.8%
구 58
 
2.3%
산 45
 
1.8%
Other values (150) 994
39.8%
Common
ValueCountFrequency (%)
697
47.1%
1 117
 
7.9%
2 95
 
6.4%
- 90
 
6.1%
5 75
 
5.1%
4 70
 
4.7%
6 64
 
4.3%
3 63
 
4.3%
7 57
 
3.9%
8 56
 
3.8%
Other values (2) 96
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2495
62.8%
ASCII 1480
37.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
697
47.1%
1 117
 
7.9%
2 95
 
6.4%
- 90
 
6.1%
5 75
 
5.1%
4 70
 
4.7%
6 64
 
4.3%
3 63
 
4.3%
7 57
 
3.9%
8 56
 
3.8%
Other values (2) 96
 
6.5%
Hangul
ValueCountFrequency (%)
시 202
 
8.1%
지 201
 
8.1%
도 199
 
8.0%
기 198
 
7.9%
경 193
 
7.7%
번 192
 
7.7%
동 142
 
5.7%
리 71
 
2.8%
구 58
 
2.3%
산 45
 
1.8%
Other values (150) 994
39.8%

정제우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct174
Distinct (%)91.1%
Missing2
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean14732.288
Minimum10011
Maximum18616
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-03-13T08:57:13.248963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10011
5-th percentile10231
Q111947
median15055
Q317335
95-th percentile18527
Maximum18616
Range8605
Interquartile range (IQR)5388

Descriptive statistics

Standard deviation2864.8476
Coefficient of variation (CV)0.19446047
Kurtosis-1.4151064
Mean14732.288
Median Absolute Deviation (MAD)2541
Skewness-0.25178022
Sum2813867
Variance8207351.9
MonotonicityNot monotonic
2024-03-13T08:57:13.358740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11134 3
 
1.6%
15017 2
 
1.0%
15881 2
 
1.0%
10210 2
 
1.0%
10275 2
 
1.0%
17327 2
 
1.0%
17338 2
 
1.0%
18527 2
 
1.0%
13014 2
 
1.0%
12901 2
 
1.0%
Other values (164) 170
88.1%
ValueCountFrequency (%)
10011 1
0.5%
10017 1
0.5%
10024 1
0.5%
10039 1
0.5%
10057 1
0.5%
10068 1
0.5%
10110 1
0.5%
10210 2
1.0%
10223 1
0.5%
10239 1
0.5%
ValueCountFrequency (%)
18616 1
0.5%
18597 1
0.5%
18585 1
0.5%
18584 1
0.5%
18558 1
0.5%
18555 2
1.0%
18554 1
0.5%
18543 1
0.5%
18527 2
1.0%
18447 1
0.5%

정제WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct189
Distinct (%)99.5%
Missing3
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean37.406482
Minimum36.938494
Maximum37.991193
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-03-13T08:57:13.465246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.938494
5-th percentile37.04526
Q137.224459
median37.351855
Q337.618116
95-th percentile37.914062
Maximum37.991193
Range1.0526991
Interquartile range (IQR)0.39365683

Descriptive statistics

Standard deviation0.25867701
Coefficient of variation (CV)0.006915299
Kurtosis-0.5608921
Mean37.406482
Median Absolute Deviation (MAD)0.17987146
Skewness0.48702965
Sum7107.2315
Variance0.066913794
MonotonicityNot monotonic
2024-03-13T08:57:13.575413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.2415869398 2
 
1.0%
37.7750967923 1
 
0.5%
37.761749056 1
 
0.5%
37.2653108016 1
 
0.5%
37.2609568588 1
 
0.5%
37.258299303 1
 
0.5%
37.2242763179 1
 
0.5%
37.2567388863 1
 
0.5%
37.7112394188 1
 
0.5%
37.8922587327 1
 
0.5%
Other values (179) 179
92.7%
(Missing) 3
 
1.6%
ValueCountFrequency (%)
36.9384943381 1
0.5%
36.9624861144 1
0.5%
36.9652542427 1
0.5%
36.9662483727 1
0.5%
36.969040781 1
0.5%
36.9875627893 1
0.5%
36.990134068 1
0.5%
36.9905012064 1
0.5%
37.0013867509 1
0.5%
37.0400707535 1
0.5%
ValueCountFrequency (%)
37.9911934345 1
0.5%
37.9898533404 1
0.5%
37.9869266357 1
0.5%
37.9821124485 1
0.5%
37.9663190712 1
0.5%
37.9520892661 1
0.5%
37.9484074015 1
0.5%
37.9469128441 1
0.5%
37.9336890919 1
0.5%
37.9245821422 1
0.5%

정제WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct189
Distinct (%)99.5%
Missing3
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean127.014
Minimum126.55218
Maximum127.6229
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-03-13T08:57:13.692032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.55218
5-th percentile126.71268
Q1126.85247
median127.02584
Q3127.14919
95-th percentile127.45555
Maximum127.6229
Range1.0707193
Interquartile range (IQR)0.29671633

Descriptive statistics

Standard deviation0.21762287
Coefficient of variation (CV)0.001713377
Kurtosis-0.21802062
Mean127.014
Median Absolute Deviation (MAD)0.14649765
Skewness0.33927798
Sum24132.66
Variance0.047359712
MonotonicityNot monotonic
2024-03-13T08:57:13.819977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.4874850596 2
 
1.0%
126.7860075764 1
 
0.5%
127.0279338158 1
 
0.5%
127.4795750578 1
 
0.5%
127.4786289123 1
 
0.5%
127.4909669621 1
 
0.5%
127.427339622 1
 
0.5%
127.4059047031 1
 
0.5%
126.7343870576 1
 
0.5%
126.7600956773 1
 
0.5%
Other values (179) 179
92.7%
(Missing) 3
 
1.6%
ValueCountFrequency (%)
126.5521800784 1
0.5%
126.5837243594 1
0.5%
126.6088191384 1
0.5%
126.6245673648 1
0.5%
126.631336059 1
0.5%
126.6448926808 1
0.5%
126.6917838145 1
0.5%
126.6924749707 1
0.5%
126.7078350497 1
0.5%
126.7092835951 1
0.5%
ValueCountFrequency (%)
127.6228994282 1
0.5%
127.5047043225 1
0.5%
127.4941450525 1
0.5%
127.4914557069 1
0.5%
127.4909669621 1
0.5%
127.4874850596 2
1.0%
127.4857456592 1
0.5%
127.4795750578 1
0.5%
127.4786289123 1
0.5%
127.427339622 1
0.5%

Interactions

2024-03-13T08:57:08.600515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:57:07.183619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:57:07.585303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:57:07.928480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:57:08.252361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:57:08.682007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:57:07.272112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:57:07.658233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:57:07.997201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:57:08.322548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:57:08.751857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:57:07.375402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:57:07.733315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:57:08.063901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:57:08.403140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:57:08.812735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:57:07.443281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:57:07.796681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:57:08.124969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:57:08.471644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:57:08.886010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:57:07.515335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:57:07.862296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:57:08.189378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:57:08.534196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T08:57:13.915037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명시설구분상세시설명수용면적수용인원관할기관및부서명칭관할부서전화번호정제우편번호정제WGS84위도정제WGS84경도
시군명1.0000.9020.8690.3030.3121.0001.0000.9940.9550.954
시설구분0.9021.0000.8840.4290.5100.9020.9020.7220.5050.455
상세시설명0.8690.8841.0000.0000.2960.8950.8880.7650.5650.680
수용면적0.3030.4290.0001.0000.9890.2910.1340.3580.1690.241
수용인원0.3120.5100.2960.9891.0000.3520.1550.3130.0000.000
관할기관및부서명칭1.0000.9020.8950.2910.3521.0001.0000.9940.9560.952
관할부서전화번호1.0000.9020.8880.1340.1551.0001.0000.9940.9580.953
정제우편번호0.9940.7220.7650.3580.3130.9940.9941.0000.9110.866
정제WGS84위도0.9550.5050.5650.1690.0000.9560.9580.9111.0000.628
정제WGS84경도0.9540.4550.6800.2410.0000.9520.9530.8660.6281.000
2024-03-13T08:57:14.037791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관할부서전화번호관할기관및부서명칭상세시설명시군명시설구분
관할부서전화번호1.0000.9810.3830.9940.534
관할기관및부서명칭0.9811.0000.3940.9940.534
상세시설명0.3830.3941.0000.3590.499
시군명0.9940.9940.3591.0000.544
시설구분0.5340.5340.4990.5441.000
2024-03-13T08:57:14.118731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수용면적수용인원정제우편번호정제WGS84위도정제WGS84경도시군명시설구분상세시설명관할기관및부서명칭관할부서전화번호
수용면적1.0000.885-0.1830.079-0.0610.1060.1950.0000.0990.035
수용인원0.8851.000-0.2890.172-0.0690.1100.2420.1010.1240.044
정제우편번호-0.183-0.2891.000-0.9360.1820.8940.4010.3650.8900.890
정제WGS84위도0.0790.172-0.9361.000-0.1390.7050.2370.2170.7110.715
정제WGS84경도-0.061-0.0690.182-0.1391.0000.7020.2080.2900.6950.699
시군명0.1060.1100.8940.7050.7021.0000.5440.3590.9940.994
시설구분0.1950.2420.4010.2370.2080.5441.0000.4990.5340.534
상세시설명0.0000.1010.3650.2170.2900.3590.4991.0000.3940.383
관할기관및부서명칭0.0990.1240.8900.7110.6950.9940.5340.3941.0000.981
관할부서전화번호0.0350.0440.8900.7150.6990.9940.5340.3830.9811.000

Missing values

2024-03-13T08:57:09.201884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T08:57:09.400146image/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.
2024-03-13T08:57:09.551340image/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

광역시도명시군명대피장소관리번호시설구분대피장소명상세시설명수용면적수용인원관할기관및부서명칭관할부서전화번호대피장소담당자명대피장소담당자연락처데이터기준일자표지판설치동의여부비고정제도로명주소정제지번주소정제우편번호정제WGS84위도정제WGS84경도
0경기도여주시여주-화학-1관공서여주실내체육관실내체육관33001269여주도시관리공단031-880-4021<NA><NA>2023-12-31Y<NA>경기도 여주시 영릉로 123경기도 여주시 월송동 1번지1262537.293039127.622899
1경기도연천군연천-화학-1체육시설장남면 배드민턴장체육시설406491연천군청 장남면사무소031-839-2710<NA><NA>2023-12-31Y<NA>경기도 연천군 장남면 장백로 244경기도 연천군 장남면 원당리 681-5번지1105037.982112126.884541
2경기도오산시오산-화학-1학교운천초등학교체육관331401오산시 환경과031-8036-6423<NA><NA>2023-12-31Y<NA>경기도 오산시 운암로 116경기도 오산시 부산동 778-4번지1813237.155948127.079759
3경기도오산시오산-화학-2기타시설오산스포츠센터체육관467566오산시 환경과031-8036-6423<NA><NA>2023-12-31Y<NA>경기도 오산시 경기동로 33경기도 오산시 오산동 40번지1813137.158691127.075655
4경기도오산시오산-화학-3기타시설죽미다목적체육관체육관442536오산시 환경과031-8036-6423<NA><NA>2023-12-31Y<NA>경기도 오산시 수청로 204-26경기도 오산시 금암동 508번지1810937.17917127.043761
5경기도오산시오산-화학-4학교성호초등학교체육관332402오산시 환경과031-8036-6423<NA><NA>2023-12-31Y<NA>경기도 오산시 성호새싹길 8경기도 오산시 오산동 862-1번지1813537.15048127.070915
6경기도오산시오산-화학-6학교가수초등학교체육관276335오산시 환경과031-8036-6423<NA><NA>2023-12-31Y<NA>경기도 오산시 가수로 50경기도 오산시 가수동 25번지1812537.148132127.047833
7경기도오산시오산-화학-8학교오산중학교체육관250303오산시 환경과031-8036-6423<NA><NA>2023-12-31Y<NA>경기도 오산시 청학로 43경기도 오산시 청학동 26번지1811937.154308127.062605
8경기도오산시오산-화학-10학교오산초등학교체육관235285오산시 환경과031-8036-6423<NA><NA>2023-12-31Y<NA>경기도 오산시 가수로 16경기도 오산시 가수동 76번지1812537.145076127.050204
9경기도오산시오산-화학-11학교대호초등학교강당198240오산시 환경과031-8036-6423<NA><NA>2023-12-31Y<NA>경기도 오산시 궐리사로46번길 3경기도 오산시 궐동 661번지1812237.159104127.057892
광역시도명시군명대피장소관리번호시설구분대피장소명상세시설명수용면적수용인원관할기관및부서명칭관할부서전화번호대피장소담당자명대피장소담당자연락처데이터기준일자표지판설치동의여부비고정제도로명주소정제지번주소정제우편번호정제WGS84위도정제WGS84경도
183경기도이천시이천-화학-4학교부발중학교체육관84766993이천시 환경보호과031-644-2349<NA><NA>2023-12-31Y<NA>경기도 이천시 부발읍 죽당로 21경기도 이천시 부발읍 무촌리 58-1번지1732137.285305127.494145
184경기도이천시이천-화학-9학교이천사동중학교학교616507이천시 환경보호과031-644-2349<NA><NA>2023-12-31Y<NA>경기도 이천시 대월면 경충대로2003번길 124-87경기도 이천시 대월면 사동리 518번지1733837.241587127.487485
185경기도이천시이천-화학-12학교청강문화산업대학교학교43885319이천시 환경보호과031-644-2349<NA><NA>2023-12-31Y<NA><NA>경기도 이천시 마장면 청강가창로 389-9517390<NA><NA>
186경기도이천시이천-화학-14학교신둔초등학교학교772936이천시 환경보호과031-644-2349<NA><NA>2023-12-31Y<NA>경기도 이천시 신둔면 경충대로3150번길 82-3경기도 이천시 신둔면 수광리 262-1번지1730337.310289127.403525
187경기도파주시파주-화학-3학교마지초등학교강당802972파주시 환경보전과031-940-8472<NA><NA>2023-12-31Y<NA>경기도 파주시 적성면 칠중1길 39경기도 파주시 적성면 마지리 60-4번지1080337.952089126.919724
188경기도파주시파주-화학-5학교연풍초등학교체육관644780파주시 복지정책과031-954-2177<NA><NA>2023-12-31Y<NA>경기도 파주시 파주읍 연풍초교길 25경기도 파주시 파주읍 연풍리 427번지1083437.831047126.834866
189경기도평택시평택-화학-1학교현덕초등학교체육관8431027평택시 환경지도과031-8024-3786<NA><NA>2023-12-31Y<NA>경기도 평택시 현덕면 현덕로 1254경기도 평택시 현덕면 인광리 405-2번지1794636.965254126.921942
190경기도평택시평택-화학-4학교청담중학교교사동16942053평택시 환경지도과031-8024-3786<NA><NA>2023-12-31Y<NA>경기도 평택시 팽성읍 부용로56번길 20경기도 평택시 팽성읍 송화리 810번지1799136.962486127.063087
191경기도평택시평택-화학-12공공기관안중체육관체육관13351618평택시 환경지도과031-8024-3786<NA><NA>2023-12-31Y<NA>경기도 평택시 안중읍 서동대로 1555경기도 평택시 안중읍 학현리 495번지1781636.990501126.921492
192경기도평택시평택-화학-14관공서청북읍행정복지센터3층 다목적실231280평택시 환경지도과031-8024-3786<NA><NA>2023-12-31Y<NA>경기도 평택시 청북읍 청원로 2경기도 평택시 청북읍 현곡리 293-4번지1781237.040071126.934587