Overview

Dataset statistics

Number of variables14
Number of observations612
Missing cells1309
Missing cells (%)15.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory71.2 KiB
Average record size in memory119.2 B

Variable types

Categorical1
Numeric5
Text6
Unsupported2

Dataset

Description화학물질 위해관리계획서 작성대상 사업장 현황
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=4USNM6KQXNYNQDAB2R1N29582162&infSeq=1

Alerts

연번 is highly overall correlated with 정제WGS84위도 and 1 other fieldsHigh correlation
정제WGS84위도 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
정제WGS84경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
소재지도로명주소 has 11 (1.8%) missing valuesMissing
연간하한취급량(톤) has 612 (100.0%) missing valuesMissing
연간상한취급량(톤) has 612 (100.0%) missing valuesMissing
주민대피시설주소 has 27 (4.4%) missing valuesMissing
주민대피시설거리(m) has 25 (4.1%) missing valuesMissing
정제WGS84위도 has 10 (1.6%) missing valuesMissing
정제WGS84경도 has 10 (1.6%) missing valuesMissing
연간하한취급량(톤) is an unsupported type, check if it needs cleaning or further analysisUnsupported
연간상한취급량(톤) is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 22:04:44.696101
Analysis finished2023-12-10 22:04:49.021190
Duration4.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
안산시
188 
시흥시
94 
평택시
89 
화성시
80 
안성시
22 
Other values (18)
139 

Length

Max length4
Median length3
Mean length3.0277778
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
안산시 188
30.7%
시흥시 94
15.4%
평택시 89
14.5%
화성시 80
13.1%
안성시 22
 
3.6%
이천시 18
 
2.9%
부천시 17
 
2.8%
용인시 16
 
2.6%
파주시 15
 
2.5%
남양주시 11
 
1.8%
Other values (13) 62
 
10.1%

Length

2023-12-11T07:04:49.088957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
안산시 188
30.7%
시흥시 94
15.4%
평택시 89
14.5%
화성시 80
13.1%
안성시 22
 
3.6%
이천시 18
 
2.9%
부천시 17
 
2.8%
용인시 16
 
2.6%
파주시 15
 
2.5%
남양주시 11
 
1.8%
Other values (13) 62
 
10.1%

연번
Real number (ℝ)

HIGH CORRELATION 

Distinct610
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean135.41552
Minimum1
Maximum280
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2023-12-11T07:04:49.205061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile12.155
Q165.775
median131.25
Q3207.025
95-th percentile265.145
Maximum280
Range279
Interquartile range (IQR)141.25

Descriptive statistics

Standard deviation81.74283
Coefficient of variation (CV)0.60364446
Kurtosis-1.2056197
Mean135.41552
Median Absolute Deviation (MAD)71
Skewness0.067249203
Sum82874.3
Variance6681.8903
MonotonicityNot monotonic
2023-12-11T07:04:49.328553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42.1 2
 
0.3%
186.1 2
 
0.3%
181.4 1
 
0.2%
180.1 1
 
0.2%
180.0 1
 
0.2%
181.2 1
 
0.2%
181.3 1
 
0.2%
181.0 1
 
0.2%
181.1 1
 
0.2%
181.5 1
 
0.2%
Other values (600) 600
98.0%
ValueCountFrequency (%)
1.0 1
0.2%
2.0 1
0.2%
2.1 1
0.2%
3.0 1
0.2%
3.1 1
0.2%
3.2 1
0.2%
3.3 1
0.2%
4.0 1
0.2%
4.1 1
0.2%
5.0 1
0.2%
ValueCountFrequency (%)
280.0 1
0.2%
279.1 1
0.2%
279.0 1
0.2%
278.1 1
0.2%
278.0 1
0.2%
277.1 1
0.2%
277.0 1
0.2%
276.2 1
0.2%
276.1 1
0.2%
276.0 1
0.2%

사업장명
Text

Distinct275
Distinct (%)44.9%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2023-12-11T07:04:49.567554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length16
Mean length8.4395425
Min length2

Characters and Unicode

Total characters5165
Distinct characters284
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)10.5%

Sample

1st row한국동서발전(주) 일산화력본부
2nd row한국수자원공사 고양권관리단 고양정수장
3rd row한국수자원공사 고양권관리단 고양정수장
4th row한국수자원공사 고양권관리단 일산정수장
5th row한국수자원공사 고양권관리단 일산정수장
ValueCountFrequency (%)
반월공장 17
 
2.0%
한국수자원공사 16
 
1.9%
에어프로덕츠코리아㈜ 14
 
1.7%
평택공장 14
 
1.7%
대덕전자㈜ 13
 
1.5%
시흥공장 10
 
1.2%
삼양화학실업㈜ 9
 
1.1%
2공장 9
 
1.1%
삼성전자㈜ 8
 
0.9%
강남제비스코㈜ 8
 
0.9%
Other values (298) 726
86.0%
2023-12-11T07:04:49.973033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 528
 
10.2%
232
 
4.5%
공 158
 
3.1%
장 154
 
3.0%
스 140
 
2.7%
이 125
 
2.4%
에 108
 
2.1%
아 95
 
1.8%
화 94
 
1.8%
리 91
 
1.8%
Other values (274) 3440
66.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4219
81.7%
Other Symbol 528
 
10.2%
Space Separator 232
 
4.5%
Uppercase Letter 107
 
2.1%
Decimal Number 23
 
0.4%
Lowercase Letter 20
 
0.4%
Close Punctuation 18
 
0.3%
Open Punctuation 18
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 158
 
3.7%
장 154
 
3.7%
스 140
 
3.3%
이 125
 
3.0%
에 108
 
2.6%
아 95
 
2.3%
화 94
 
2.2%
리 91
 
2.2%
업 89
 
2.1%
지 78
 
1.8%
Other values (244) 3087
73.2%
Uppercase Letter
ValueCountFrequency (%)
S 21
19.6%
G 16
15.0%
B 15
14.0%
P 10
9.3%
L 9
8.4%
D 8
 
7.5%
M 6
 
5.6%
N 5
 
4.7%
K 5
 
4.7%
R 3
 
2.8%
Other values (4) 9
8.4%
Lowercase Letter
ValueCountFrequency (%)
s 4
20.0%
i 2
10.0%
n 2
10.0%
m 2
10.0%
e 2
10.0%
t 2
10.0%
a 2
10.0%
l 2
10.0%
p 2
10.0%
Decimal Number
ValueCountFrequency (%)
2 18
78.3%
1 4
 
17.4%
3 1
 
4.3%
Other Symbol
ValueCountFrequency (%)
㈜ 528
100.0%
Space Separator
ValueCountFrequency (%)
232
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4745
91.9%
Common 291
 
5.6%
Latin 127
 
2.5%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 528
 
11.1%
공 158
 
3.3%
장 154
 
3.2%
스 140
 
3.0%
이 125
 
2.6%
에 108
 
2.3%
아 95
 
2.0%
화 94
 
2.0%
리 91
 
1.9%
업 89
 
1.9%
Other values (244) 3163
66.7%
Latin
ValueCountFrequency (%)
S 21
16.5%
G 16
12.6%
B 15
11.8%
P 10
 
7.9%
L 9
 
7.1%
D 8
 
6.3%
M 6
 
4.7%
N 5
 
3.9%
K 5
 
3.9%
s 4
 
3.1%
Other values (13) 28
22.0%
Common
ValueCountFrequency (%)
232
79.7%
2 18
 
6.2%
) 18
 
6.2%
( 18
 
6.2%
1 4
 
1.4%
3 1
 
0.3%
Han
ValueCountFrequency (%)
舊 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4217
81.6%
None 528
 
10.2%
ASCII 418
 
8.1%
CJK 2
 
< 0.1%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 528
100.0%
ASCII
ValueCountFrequency (%)
232
55.5%
S 21
 
5.0%
2 18
 
4.3%
) 18
 
4.3%
( 18
 
4.3%
G 16
 
3.8%
B 15
 
3.6%
P 10
 
2.4%
L 9
 
2.2%
D 8
 
1.9%
Other values (19) 53
 
12.7%
Hangul
ValueCountFrequency (%)
공 158
 
3.7%
장 154
 
3.7%
스 140
 
3.3%
이 125
 
3.0%
에 108
 
2.6%
아 95
 
2.3%
화 94
 
2.2%
리 91
 
2.2%
업 89
 
2.1%
지 78
 
1.8%
Other values (243) 3085
73.2%
CJK
ValueCountFrequency (%)
舊 2
100.0%

소재지도로명주소
Text

MISSING 

Distinct259
Distinct (%)43.1%
Missing11
Missing (%)1.8%
Memory size4.9 KiB
2023-12-11T07:04:50.193935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length19.996672
Min length13

Characters and Unicode

Total characters12018
Distinct characters177
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

Unique58 ?
Unique (%)9.7%

Sample

1st row경기도 고양시 일산동구 경의로 201
2nd row경기도 고양시 일산동구 대주로 326
3rd row경기도 고양시 일산동구 대주로 326
4th row경기도 고양시 덕양구 대주로 136
5th row경기도 고양시 덕양구 대주로 136
ValueCountFrequency (%)
경기도 601
 
21.1%
안산시 188
 
6.6%
단원구 180
 
6.3%
평택시 89
 
3.1%
시흥시 85
 
3.0%
화성시 79
 
2.8%
포승읍 39
 
1.4%
신원로 23
 
0.8%
안성시 21
 
0.7%
마도면 21
 
0.7%
Other values (427) 1519
53.4%
2023-12-11T07:04:50.541301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2244
18.7%
시 696
 
5.8%
도 641
 
5.3%
경 636
 
5.3%
기 631
 
5.3%
로 534
 
4.4%
1 470
 
3.9%
단 312
 
2.6%
2 307
 
2.6%
안 279
 
2.3%
Other values (167) 5268
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7534
62.7%
Space Separator 2244
 
18.7%
Decimal Number 2156
 
17.9%
Dash Punctuation 84
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 696
 
9.2%
도 641
 
8.5%
경 636
 
8.4%
기 631
 
8.4%
로 534
 
7.1%
단 312
 
4.1%
안 279
 
3.7%
산 277
 
3.7%
원 244
 
3.2%
구 233
 
3.1%
Other values (155) 3051
40.5%
Decimal Number
ValueCountFrequency (%)
1 470
21.8%
2 307
14.2%
3 238
11.0%
4 209
9.7%
5 174
 
8.1%
7 170
 
7.9%
8 169
 
7.8%
9 159
 
7.4%
0 140
 
6.5%
6 120
 
5.6%
Space Separator
ValueCountFrequency (%)
2244
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7534
62.7%
Common 4484
37.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 696
 
9.2%
도 641
 
8.5%
경 636
 
8.4%
기 631
 
8.4%
로 534
 
7.1%
단 312
 
4.1%
안 279
 
3.7%
산 277
 
3.7%
원 244
 
3.2%
구 233
 
3.1%
Other values (155) 3051
40.5%
Common
ValueCountFrequency (%)
2244
50.0%
1 470
 
10.5%
2 307
 
6.8%
3 238
 
5.3%
4 209
 
4.7%
5 174
 
3.9%
7 170
 
3.8%
8 169
 
3.8%
9 159
 
3.5%
0 140
 
3.1%
Other values (2) 204
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7534
62.7%
ASCII 4484
37.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2244
50.0%
1 470
 
10.5%
2 307
 
6.8%
3 238
 
5.3%
4 209
 
4.7%
5 174
 
3.9%
7 170
 
3.8%
8 169
 
3.8%
9 159
 
3.5%
0 140
 
3.1%
Other values (2) 204
 
4.5%
Hangul
ValueCountFrequency (%)
시 696
 
9.2%
도 641
 
8.5%
경 636
 
8.4%
기 631
 
8.4%
로 534
 
7.1%
단 312
 
4.1%
안 279
 
3.7%
산 277
 
3.7%
원 244
 
3.2%
구 233
 
3.1%
Other values (155) 3051
40.5%

소재지지번주소
Text

Distinct262
Distinct (%)42.8%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2023-12-11T07:04:50.794693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length37
Mean length21.620915
Min length16

Characters and Unicode

Total characters13232
Distinct characters167
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

Unique61 ?
Unique (%)10.0%

Sample

1st row경기도 고양시 일산동구 백석동 1143-1번지
2nd row경기도 고양시 일산동구 산황동 300번지
3rd row경기도 고양시 일산동구 산황동 300번지
4th row경기도 고양시 덕양구 대장동 223-1번지
5th row경기도 고양시 덕양구 대장동 223-1번지
ValueCountFrequency (%)
경기도 612
21.0%
안산시 189
 
6.5%
단원구 180
 
6.2%
시흥시 94
 
3.2%
평택시 89
 
3.1%
정왕동 80
 
2.8%
화성시 80
 
2.8%
성곡동 79
 
2.7%
목내동 45
 
1.5%
원시동 42
 
1.4%
Other values (432) 1419
48.8%
2023-12-11T07:04:51.180365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2297
 
17.4%
시 748
 
5.7%
도 654
 
4.9%
기 627
 
4.7%
지 616
 
4.7%
경 614
 
4.6%
번 601
 
4.5%
1 472
 
3.6%
동 413
 
3.1%
- 387
 
2.9%
Other values (157) 5803
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8143
61.5%
Decimal Number 2376
 
18.0%
Space Separator 2297
 
17.4%
Dash Punctuation 387
 
2.9%
Open Punctuation 12
 
0.1%
Close Punctuation 12
 
0.1%
Uppercase Letter 4
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 748
 
9.2%
도 654
 
8.0%
기 627
 
7.7%
지 616
 
7.6%
경 614
 
7.5%
번 601
 
7.4%
동 413
 
5.1%
원 265
 
3.3%
안 233
 
2.9%
구 224
 
2.8%
Other values (140) 3148
38.7%
Decimal Number
ValueCountFrequency (%)
1 472
19.9%
2 328
13.8%
3 251
10.6%
6 235
9.9%
4 235
9.9%
7 233
9.8%
5 203
8.5%
0 163
 
6.9%
8 137
 
5.8%
9 119
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
K 2
50.0%
S 2
50.0%
Space Separator
ValueCountFrequency (%)
2297
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 387
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8143
61.5%
Common 5085
38.4%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 748
 
9.2%
도 654
 
8.0%
기 627
 
7.7%
지 616
 
7.6%
경 614
 
7.5%
번 601
 
7.4%
동 413
 
5.1%
원 265
 
3.3%
안 233
 
2.9%
구 224
 
2.8%
Other values (140) 3148
38.7%
Common
ValueCountFrequency (%)
2297
45.2%
1 472
 
9.3%
- 387
 
7.6%
2 328
 
6.5%
3 251
 
4.9%
6 235
 
4.6%
4 235
 
4.6%
7 233
 
4.6%
5 203
 
4.0%
0 163
 
3.2%
Other values (5) 281
 
5.5%
Latin
ValueCountFrequency (%)
K 2
50.0%
S 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8143
61.5%
ASCII 5089
38.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2297
45.1%
1 472
 
9.3%
- 387
 
7.6%
2 328
 
6.4%
3 251
 
4.9%
6 235
 
4.6%
4 235
 
4.6%
7 233
 
4.6%
5 203
 
4.0%
0 163
 
3.2%
Other values (7) 285
 
5.6%
Hangul
ValueCountFrequency (%)
시 748
 
9.2%
도 654
 
8.0%
기 627
 
7.7%
지 616
 
7.6%
경 614
 
7.5%
번 601
 
7.4%
동 413
 
5.1%
원 265
 
3.3%
안 233
 
2.9%
구 224
 
2.8%
Other values (140) 3148
38.7%

취급사고대비물질명
Text

Distinct124
Distinct (%)20.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2023-12-11T07:04:51.399531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length222
Median length59
Mean length12.287582
Min length2

Characters and Unicode

Total characters7520
Distinct characters102
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)3.4%

Sample

1st row암모니아수
2nd row염소
3rd row염소
4th row염소
5th row염소
ValueCountFrequency (%)
황산 152
 
11.1%
염화수소 110
 
8.1%
암모니아 101
 
7.4%
아세트산에틸 99
 
7.2%
과산화수소 77
 
5.6%
메틸알코올 50
 
3.7%
염산 50
 
3.7%
염소 42
 
3.1%
실란 41
 
3.0%
톨루엔 38
 
2.8%
Other values (76) 606
44.4%
2023-12-11T07:04:51.834364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
754
 
10.0%
, 722
 
9.6%
산 541
 
7.2%
화 361
 
4.8%
소 357
 
4.7%
염 305
 
4.1%
아 289
 
3.8%
틸 271
 
3.6%
수 271
 
3.6%
트 228
 
3.0%
Other values (92) 3421
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5859
77.9%
Space Separator 754
 
10.0%
Other Punctuation 722
 
9.6%
Dash Punctuation 69
 
0.9%
Decimal Number 64
 
0.9%
Open Punctuation 26
 
0.3%
Close Punctuation 26
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 541
 
9.2%
화 361
 
6.2%
소 357
 
6.1%
염 305
 
5.2%
아 289
 
4.9%
틸 271
 
4.6%
수 271
 
4.6%
트 228
 
3.9%
에 173
 
3.0%
로 160
 
2.7%
Other values (82) 2903
49.5%
Decimal Number
ValueCountFrequency (%)
1 21
32.8%
4 14
21.9%
3 14
21.9%
2 13
20.3%
5 2
 
3.1%
Space Separator
ValueCountFrequency (%)
754
100.0%
Other Punctuation
ValueCountFrequency (%)
, 722
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 69
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5859
77.9%
Common 1661
 
22.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 541
 
9.2%
화 361
 
6.2%
소 357
 
6.1%
염 305
 
5.2%
아 289
 
4.9%
틸 271
 
4.6%
수 271
 
4.6%
트 228
 
3.9%
에 173
 
3.0%
로 160
 
2.7%
Other values (82) 2903
49.5%
Common
ValueCountFrequency (%)
754
45.4%
, 722
43.5%
- 69
 
4.2%
( 26
 
1.6%
) 26
 
1.6%
1 21
 
1.3%
4 14
 
0.8%
3 14
 
0.8%
2 13
 
0.8%
5 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5859
77.9%
ASCII 1661
 
22.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
754
45.4%
, 722
43.5%
- 69
 
4.2%
( 26
 
1.6%
) 26
 
1.6%
1 21
 
1.3%
4 14
 
0.8%
3 14
 
0.8%
2 13
 
0.8%
5 2
 
0.1%
Hangul
ValueCountFrequency (%)
산 541
 
9.2%
화 361
 
6.2%
소 357
 
6.1%
염 305
 
5.2%
아 289
 
4.9%
틸 271
 
4.6%
수 271
 
4.6%
트 228
 
3.9%
에 173
 
3.0%
로 160
 
2.7%
Other values (82) 2903
49.5%

연간하한취급량(톤)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing612
Missing (%)100.0%
Memory size5.5 KiB

연간상한취급량(톤)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing612
Missing (%)100.0%
Memory size5.5 KiB

주민대피시설명
Text

Distinct428
Distinct (%)69.9%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2023-12-11T07:04:52.133132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length7.2614379
Min length3

Characters and Unicode

Total characters4444
Distinct characters339
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique360 ?
Unique (%)58.8%

Sample

1st row백석도서관 인접 공터
2nd row백마고등학교 체육관
3rd row고양백석 체육센터
4th row능곡초등학교 강당
5th row화수고등학교 체육관
ValueCountFrequency (%)
실내대피 25
 
3.1%
체육관 17
 
2.1%
희망공원 15
 
1.8%
배나물야구장 10
 
1.2%
강당 10
 
1.2%
근린공원 9
 
1.1%
옥터초등학교 9
 
1.1%
원시운동장 9
 
1.1%
옥구공원 8
 
1.0%
마을회관 8
 
1.0%
Other values (484) 694
85.3%
2023-12-11T07:04:52.615432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
202
 
4.5%
교 191
 
4.3%
학 174
 
3.9%
원 133
 
3.0%
등 131
 
2.9%
초 123
 
2.8%
공 116
 
2.6%
장 98
 
2.2%
동 95
 
2.1%
관 80
 
1.8%
Other values (329) 3101
69.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4095
92.1%
Space Separator 202
 
4.5%
Decimal Number 86
 
1.9%
Uppercase Letter 25
 
0.6%
Close Punctuation 13
 
0.3%
Open Punctuation 13
 
0.3%
Other Symbol 9
 
0.2%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 191
 
4.7%
학 174
 
4.2%
원 133
 
3.2%
등 131
 
3.2%
초 123
 
3.0%
공 116
 
2.8%
장 98
 
2.4%
동 95
 
2.3%
관 80
 
2.0%
지 78
 
1.9%
Other values (302) 2876
70.2%
Uppercase Letter
ValueCountFrequency (%)
C 5
20.0%
K 4
16.0%
S 3
12.0%
V 2
 
8.0%
T 2
 
8.0%
M 2
 
8.0%
P 1
 
4.0%
R 1
 
4.0%
A 1
 
4.0%
G 1
 
4.0%
Other values (3) 3
12.0%
Decimal Number
ValueCountFrequency (%)
1 29
33.7%
2 24
27.9%
3 9
 
10.5%
4 8
 
9.3%
9 7
 
8.1%
7 4
 
4.7%
0 2
 
2.3%
6 2
 
2.3%
5 1
 
1.2%
Space Separator
ValueCountFrequency (%)
202
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 9
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4104
92.3%
Common 315
 
7.1%
Latin 25
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 191
 
4.7%
학 174
 
4.2%
원 133
 
3.2%
등 131
 
3.2%
초 123
 
3.0%
공 116
 
2.8%
장 98
 
2.4%
동 95
 
2.3%
관 80
 
1.9%
지 78
 
1.9%
Other values (303) 2885
70.3%
Common
ValueCountFrequency (%)
202
64.1%
1 29
 
9.2%
2 24
 
7.6%
) 13
 
4.1%
( 13
 
4.1%
3 9
 
2.9%
4 8
 
2.5%
9 7
 
2.2%
7 4
 
1.3%
0 2
 
0.6%
Other values (3) 4
 
1.3%
Latin
ValueCountFrequency (%)
C 5
20.0%
K 4
16.0%
S 3
12.0%
V 2
 
8.0%
T 2
 
8.0%
M 2
 
8.0%
P 1
 
4.0%
R 1
 
4.0%
A 1
 
4.0%
G 1
 
4.0%
Other values (3) 3
12.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4095
92.1%
ASCII 340
 
7.7%
None 9
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
202
59.4%
1 29
 
8.5%
2 24
 
7.1%
) 13
 
3.8%
( 13
 
3.8%
3 9
 
2.6%
4 8
 
2.4%
9 7
 
2.1%
C 5
 
1.5%
K 4
 
1.2%
Other values (16) 26
 
7.6%
Hangul
ValueCountFrequency (%)
교 191
 
4.7%
학 174
 
4.2%
원 133
 
3.2%
등 131
 
3.2%
초 123
 
3.0%
공 116
 
2.8%
장 98
 
2.4%
동 95
 
2.3%
관 80
 
2.0%
지 78
 
1.9%
Other values (302) 2876
70.2%
None
ValueCountFrequency (%)
㈜ 9
100.0%

주민대피시설주소
Text

MISSING 

Distinct404
Distinct (%)69.1%
Missing27
Missing (%)4.4%
Memory size4.9 KiB
2023-12-11T07:04:52.945760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length26
Mean length19.454701
Min length11

Characters and Unicode

Total characters11381
Distinct characters252
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

Unique324 ?
Unique (%)55.4%

Sample

1st row경기도 고양시 일산동구 일산로118
2nd row경기도 고양시 일산동구 백석로 155
3rd row경기도 고양시 일산동구 경의로 84
4th row경기도 고양시 덕양구 토당로67번길 66
5th row경기도 고양시 덕양구 화수로 51
ValueCountFrequency (%)
경기도 584
 
20.8%
안산시 186
 
6.6%
단원구 173
 
6.2%
시흥시 91
 
3.2%
평택시 82
 
2.9%
화성시 73
 
2.6%
포승읍 34
 
1.2%
성곡동 30
 
1.1%
안성시 21
 
0.7%
청북읍 20
 
0.7%
Other values (688) 1512
53.9%
2023-12-11T07:04:53.417880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2222
19.5%
시 696
 
6.1%
도 620
 
5.4%
기 603
 
5.3%
경 598
 
5.3%
로 420
 
3.7%
1 344
 
3.0%
안 257
 
2.3%
산 247
 
2.2%
원 232
 
2.0%
Other values (242) 5142
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7206
63.3%
Space Separator 2222
 
19.5%
Decimal Number 1813
 
15.9%
Dash Punctuation 90
 
0.8%
Close Punctuation 22
 
0.2%
Open Punctuation 22
 
0.2%
Uppercase Letter 5
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 696
 
9.7%
도 620
 
8.6%
기 603
 
8.4%
경 598
 
8.3%
로 420
 
5.8%
안 257
 
3.6%
산 247
 
3.4%
원 232
 
3.2%
구 226
 
3.1%
단 205
 
2.8%
Other values (224) 3102
43.0%
Decimal Number
ValueCountFrequency (%)
1 344
19.0%
2 229
12.6%
3 225
12.4%
5 166
9.2%
4 165
9.1%
6 163
9.0%
7 160
8.8%
8 135
 
7.4%
9 132
 
7.3%
0 94
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
S 2
40.0%
K 2
40.0%
A 1
20.0%
Space Separator
ValueCountFrequency (%)
2222
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 90
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Other Punctuation
ValueCountFrequency (%)
? 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7206
63.3%
Common 4170
36.6%
Latin 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 696
 
9.7%
도 620
 
8.6%
기 603
 
8.4%
경 598
 
8.3%
로 420
 
5.8%
안 257
 
3.6%
산 247
 
3.4%
원 232
 
3.2%
구 226
 
3.1%
단 205
 
2.8%
Other values (224) 3102
43.0%
Common
ValueCountFrequency (%)
2222
53.3%
1 344
 
8.2%
2 229
 
5.5%
3 225
 
5.4%
5 166
 
4.0%
4 165
 
4.0%
6 163
 
3.9%
7 160
 
3.8%
8 135
 
3.2%
9 132
 
3.2%
Other values (5) 229
 
5.5%
Latin
ValueCountFrequency (%)
S 2
40.0%
K 2
40.0%
A 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7206
63.3%
ASCII 4175
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2222
53.2%
1 344
 
8.2%
2 229
 
5.5%
3 225
 
5.4%
5 166
 
4.0%
4 165
 
4.0%
6 163
 
3.9%
7 160
 
3.8%
8 135
 
3.2%
9 132
 
3.2%
Other values (8) 234
 
5.6%
Hangul
ValueCountFrequency (%)
시 696
 
9.7%
도 620
 
8.6%
기 603
 
8.4%
경 598
 
8.3%
로 420
 
5.8%
안 257
 
3.6%
산 247
 
3.4%
원 232
 
3.2%
구 226
 
3.1%
단 205
 
2.8%
Other values (224) 3102
43.0%

주민대피시설거리(m)
Real number (ℝ)

MISSING 

Distinct240
Distinct (%)40.9%
Missing25
Missing (%)4.1%
Infinite0
Infinite (%)0.0%
Mean1926.4429
Minimum0
Maximum15300
Zeros3
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2023-12-11T07:04:53.563273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile123
Q1575
median1400
Q32650
95-th percentile5370
Maximum15300
Range15300
Interquartile range (IQR)2075

Descriptive statistics

Standard deviation1885.5263
Coefficient of variation (CV)0.97876051
Kurtosis7.8165287
Mean1926.4429
Median Absolute Deviation (MAD)910
Skewness2.1613911
Sum1130822
Variance3555209.3
MonotonicityNot monotonic
2023-12-11T07:04:53.733449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1700 18
 
2.9%
1300 17
 
2.8%
1500 15
 
2.5%
2300 15
 
2.5%
1000 15
 
2.5%
1600 13
 
2.1%
1200 12
 
2.0%
2100 11
 
1.8%
300 10
 
1.6%
1400 10
 
1.6%
Other values (230) 451
73.7%
(Missing) 25
 
4.1%
ValueCountFrequency (%)
0 3
0.5%
17 1
 
0.2%
20 2
0.3%
50 1
 
0.2%
52 1
 
0.2%
60 1
 
0.2%
70 2
0.3%
74 1
 
0.2%
79 1
 
0.2%
80 1
 
0.2%
ValueCountFrequency (%)
15300 1
0.2%
13200 1
0.2%
11000 1
0.2%
9800 1
0.2%
8900 1
0.2%
7980 1
0.2%
7800 2
0.3%
7700 2
0.3%
7520 2
0.3%
7500 1
0.2%

정제WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct260
Distinct (%)43.2%
Missing10
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean37.289979
Minimum36.959691
Maximum37.991166
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2023-12-11T07:04:54.166121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.959691
5-th percentile36.980651
Q137.171668
median37.303025
Q337.336183
95-th percentile37.8157
Maximum37.991166
Range1.0314756
Interquartile range (IQR)0.16451444

Descriptive statistics

Standard deviation0.21630918
Coefficient of variation (CV)0.005800732
Kurtosis1.7068142
Mean37.289979
Median Absolute Deviation (MAD)0.0778595
Skewness1.0855318
Sum22448.568
Variance0.04678966
MonotonicityNot monotonic
2023-12-11T07:04:54.314543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.2529797883 11
 
1.8%
37.3104450385 9
 
1.5%
37.1886742707 8
 
1.3%
37.3108571409 6
 
1.0%
37.3138202858 6
 
1.0%
37.0077477207 6
 
1.0%
37.0393690187 6
 
1.0%
37.3108557128 6
 
1.0%
37.1716681714 5
 
0.8%
37.297812242 5
 
0.8%
Other values (250) 534
87.3%
(Missing) 10
 
1.6%
ValueCountFrequency (%)
36.9596905456 2
0.3%
36.9611842833 2
0.3%
36.9613268389 2
0.3%
36.9620028703 2
0.3%
36.9641156187 2
0.3%
36.9664417128 2
0.3%
36.9678078418 2
0.3%
36.9679998066 1
0.2%
36.9719075103 1
0.2%
36.9748848949 2
0.3%
ValueCountFrequency (%)
37.9911661267 3
0.5%
37.9842121774 1
 
0.2%
37.9586976032 2
0.3%
37.9584646161 3
0.5%
37.9461345316 2
0.3%
37.8993041135 4
0.7%
37.894305289 3
0.5%
37.8755142858 2
0.3%
37.8660869374 1
 
0.2%
37.8533607323 2
0.3%

정제WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct260
Distinct (%)43.2%
Missing10
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean126.87615
Minimum126.5818
Maximum127.59315
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2023-12-11T07:04:54.471957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.5818
5-th percentile126.70265
Q1126.76145
median126.78756
Q3126.95438
95-th percentile127.24752
Maximum127.59315
Range1.011356
Interquartile range (IQR)0.19292913

Descriptive statistics

Standard deviation0.18872791
Coefficient of variation (CV)0.0014874972
Kurtosis1.5227905
Mean126.87615
Median Absolute Deviation (MAD)0.063578709
Skewness1.4339882
Sum76379.44
Variance0.035618226
MonotonicityNot monotonic
2023-12-11T07:04:54.624746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.4806834787 11
 
1.8%
126.7637818754 9
 
1.5%
126.6783706832 8
 
1.3%
126.7944387801 6
 
1.0%
126.7658931624 6
 
1.0%
126.7982169096 6
 
1.0%
127.0678643689 6
 
1.0%
126.792689641 6
 
1.0%
126.7638689102 5
 
0.8%
126.7998246488 5
 
0.8%
Other values (250) 534
87.3%
(Missing) 10
 
1.6%
ValueCountFrequency (%)
126.5817977055 3
 
0.5%
126.6284440434 2
 
0.3%
126.6704835021 2
 
0.3%
126.6716858171 3
 
0.5%
126.6776067793 1
 
0.2%
126.6783706832 8
1.3%
126.6959753124 1
 
0.2%
126.6977004696 1
 
0.2%
126.7009727595 2
 
0.3%
126.7018243514 2
 
0.3%
ValueCountFrequency (%)
127.593153731 1
 
0.2%
127.5042165942 2
 
0.3%
127.4806834787 11
1.8%
127.3943070064 3
 
0.5%
127.3690529305 1
 
0.2%
127.357539497 2
 
0.3%
127.3350858498 3
 
0.5%
127.2630872408 2
 
0.3%
127.2629851417 1
 
0.2%
127.2509103232 1
 
0.2%

사업자등록번호
Real number (ℝ)

Distinct250
Distinct (%)41.0%
Missing2
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean2.0992889 × 109
Minimum1.0181104 × 109
Maximum8.888501 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2023-12-11T07:04:54.790789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.0181104 × 109
5-th percentile1.2081345 × 109
Q11.2782356 × 109
median1.3481076 × 109
Q31.4181125 × 109
95-th percentile6.7487017 × 109
Maximum8.888501 × 109
Range7.8703906 × 109
Interquartile range (IQR)1.3987695 × 108

Descriptive statistics

Standard deviation1.8106803 × 109
Coefficient of variation (CV)0.8625208
Kurtosis4.313486
Mean2.0992889 × 109
Median Absolute Deviation (MAD)69997562
Skewness2.3504016
Sum1.2805662 × 1012
Variance3.2785632 × 1018
MonotonicityNot monotonic
2023-12-11T07:04:54.938040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3068200471 16
 
2.6%
8078800317 14
 
2.3%
6748701704 13
 
2.1%
1348109623 12
 
2.0%
1338507940 9
 
1.5%
6058103330 8
 
1.3%
1248100998 8
 
1.3%
1328303990 7
 
1.1%
1208117541 6
 
1.0%
1288149658 6
 
1.0%
Other values (240) 511
83.5%
ValueCountFrequency (%)
1018110436 4
0.7%
1018633055 1
 
0.2%
1018664320 1
 
0.2%
1018673756 2
0.3%
1058174316 2
0.3%
1058614410 1
 
0.2%
1128113675 2
0.3%
1138107346 2
0.3%
1138136157 3
0.5%
1138670766 1
 
0.2%
ValueCountFrequency (%)
8888500993 2
 
0.3%
8878102272 2
 
0.3%
8598501432 2
 
0.3%
8078800317 14
2.3%
7638800055 3
 
0.5%
7218500991 1
 
0.2%
7038800408 2
 
0.3%
6748701704 13
2.1%
6348100724 4
 
0.7%
6308500133 4
 
0.7%

Interactions

2023-12-11T07:04:48.020367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:04:45.713929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:04:46.234941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:04:47.048236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:04:47.531821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:04:48.125907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:04:45.816922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:04:46.618999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:04:47.139775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:04:47.623982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:04:48.262572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:04:45.921899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:04:46.732892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:04:47.241597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:04:47.717444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:04:48.358862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:04:46.030072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:04:46.832633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:04:47.335518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:04:47.802742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:04:48.456810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:04:46.137843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:04:46.934289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:04:47.428142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:04:47.904898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:04:55.062423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명연번주민대피시설거리(m)정제WGS84위도정제WGS84경도사업자등록번호
시군명1.0000.9380.0000.9740.9110.649
연번0.9381.0000.2080.8870.7860.457
주민대피시설거리(m)0.0000.2081.0000.0000.0000.000
정제WGS84위도0.9740.8870.0001.0000.8170.407
정제WGS84경도0.9110.7860.0000.8171.0000.442
사업자등록번호0.6490.4570.0000.4070.4421.000
2023-12-11T07:04:55.172452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번주민대피시설거리(m)정제WGS84위도정제WGS84경도사업자등록번호시군명
연번1.000-0.009-0.6820.350-0.1260.713
주민대피시설거리(m)-0.0091.0000.037-0.0870.0410.000
정제WGS84위도-0.6820.0371.000-0.3800.0850.847
정제WGS84경도0.350-0.087-0.3801.000-0.0820.639
사업자등록번호-0.1260.0410.085-0.0821.0000.301
시군명0.7130.0000.8470.6390.3011.000

Missing values

2023-12-11T07:04:48.638958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:04:48.821209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-11T07:04:48.950252image/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

시군명연번사업장명소재지도로명주소소재지지번주소취급사고대비물질명연간하한취급량(톤)연간상한취급량(톤)주민대피시설명주민대피시설주소주민대피시설거리(m)정제WGS84위도정제WGS84경도사업자등록번호
0고양시1.0한국동서발전(주) 일산화력본부경기도 고양시 일산동구 경의로 201경기도 고양시 일산동구 백석동 1143-1번지암모니아수<NA><NA>백석도서관 인접 공터경기도 고양시 일산동구 일산로11810037.645292126.7970231288522615
1고양시2.1한국수자원공사 고양권관리단 고양정수장경기도 고양시 일산동구 대주로 326경기도 고양시 일산동구 산황동 300번지염소<NA><NA>백마고등학교 체육관경기도 고양시 일산동구 백석로 155300037.647139126.813683068200471
2고양시2.0한국수자원공사 고양권관리단 고양정수장경기도 고양시 일산동구 대주로 326경기도 고양시 일산동구 산황동 300번지염소<NA><NA>고양백석 체육센터경기도 고양시 일산동구 경의로 84300037.647139126.813683068200471
3고양시3.1한국수자원공사 고양권관리단 일산정수장경기도 고양시 덕양구 대주로 136경기도 고양시 덕양구 대장동 223-1번지염소<NA><NA>능곡초등학교 강당경기도 고양시 덕양구 토당로67번길 66160037.63944126.8143183068200471
4고양시3.2한국수자원공사 고양권관리단 일산정수장경기도 고양시 덕양구 대주로 136경기도 고양시 덕양구 대장동 223-1번지염소<NA><NA>화수고등학교 체육관경기도 고양시 덕양구 화수로 51200037.63944126.8143183068200471
5고양시3.0한국수자원공사 고양권관리단 일산정수장경기도 고양시 덕양구 대주로 136경기도 고양시 덕양구 대장동 223-1번지염소<NA><NA>고양어울림누리경기도 고양시 덕양구 어울림로 33210037.63944126.8143183068200471
6고양시3.3한국수자원공사 고양권관리단 일산정수장경기도 고양시 덕양구 대주로 136경기도 고양시 덕양구 대장동 223-1번지염소<NA><NA>고양화정초등학교 체육관경기도 고양시 덕양구 화신로 333110037.63944126.8143183068200471
7광명시4.1광명시 환경수도사업소 노온정수장경기도 광명시 범안로 777-21경기도 광명시 노온사동 2-1번지염소<NA><NA>광명시민회관경기도 광명시 시청로 20450037.449103126.8562951338300865
8광명시4.0광명시 환경수도사업소 노온정수장경기도 광명시 범안로 777-21경기도 광명시 노온사동 2-1번지염소<NA><NA>광명스피돔경기도 광명시 광명로 721400037.449103126.8562951338300865
9군포시5.3강남제비스코㈜ 안양공장경기도 군포시 농심로 8경기도 군포시 당정동 284-1번지톨루엔<NA><NA>군포시 시민체육광장 1체육관경기도 군포시 산본로 267(금정동)150037.359861126.9519596058103330
시군명연번사업장명소재지도로명주소소재지지번주소취급사고대비물질명연간하한취급량(톤)연간상한취급량(톤)주민대피시설명주민대피시설주소주민대피시설거리(m)정제WGS84위도정제WGS84경도사업자등록번호
602화성시276.2진흥창고㈜경기도 화성시 남양읍 주석로 344경기도 화성시 남양읍 북양리 565-1번지아세트산에틸, 톨루엔, 염화벤질, 염화티오닐<NA><NA>한우마을 주차장경기도 화성시 남양읍 현대기아로 703-8130037.204821126.8634251438127440
603화성시276.0진흥창고㈜경기도 화성시 남양읍 주석로 344경기도 화성시 남양읍 북양리 565-1번지아세트산에틸, 톨루엔, 염화벤질, 염화티오닐<NA><NA>청룡초등학교 운동장경기도 화성시 남양읍 주석로 610223037.204821126.8634251438127440
604화성시276.1진흥창고㈜경기도 화성시 남양읍 주석로 344경기도 화성시 남양읍 북양리 565-1번지아세트산에틸, 톨루엔, 염화벤질, 염화티오닐<NA><NA>제이씨포리마 인접공터(주유소옆)경기도 화성시 남양읍 주럭로 394110037.204821126.8634251438127440
605화성시277.1청우화학㈜경기도 화성시 마도면 청원산단5길 149경기도 화성시 마도면 청원리 1477번지아세트산에틸<NA><NA>2호 근린공원경기도 화성시 마도면 청원산단5길 2770037.168479126.764171348169747
606화성시277.0청우화학㈜경기도 화성시 마도면 청원산단5길 149경기도 화성시 마도면 청원리 1477번지아세트산에틸<NA><NA>1호 근린공원경기도 화성시 마도면 청원산단8길 18640037.168479126.764171348169747
607화성시278.0한국수자원공사 화성권지사경기도 화성시 매송면 매송고색로503번길 235-41경기도 화성시 매송면 천천리 18번지염소<NA><NA>호매실가림리마을회관경기도 수원시 권선구 매송고색로 503번길 89221037.252517126.9476173068200471
608화성시278.1한국수자원공사 화성권지사경기도 화성시 매송면 매송고색로503번길 235-41경기도 화성시 매송면 천천리 18번지염소<NA><NA>천천리다목적회관경기도 화성시 매송면 매송고색로 375번길 11134037.252517126.9476173068200471
609화성시279.0한국지역난방공사 동탄지사경기도 화성시 동탄기흥로 166경기도 화성시 방교동 830번지암모니아<NA><NA>동탄6동 주민센터경기도 화성시 동탄산단8길 15-12(방교동 828)15037.175088127.0938351358217098
610화성시279.1한국지역난방공사 동탄지사경기도 화성시 동탄기흥로 166경기도 화성시 방교동 830번지암모니아<NA><NA>방교초등학교경기도 화성시 동탄산척로1길 1188037.175088127.0938351358217098
611화성시280.0한국지역난방공사 화성지사경기도 화성시 큰재봉길 16경기도 화성시 석우동 39번지암모니아, 염화 수소<NA><NA>예원초등학교 체육관경기도 화성시 동탄반석로 25985037.217776127.0799911248214484