Overview

Dataset statistics

Number of variables9
Number of observations262
Missing cells29
Missing cells (%)1.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.6 KiB
Average record size in memory76.5 B

Variable types

Numeric4
Text1
Categorical4

Dataset

Description송산면 농막 현황은 대지위치, 지목, 대지면적, 건축면적, 연면적, 용도, 구조, 적법 및 불법 여부를 제공합니다.
Author경기도 화성시
URLhttps://www.data.go.kr/data/15100165/fileData.do

Alerts

건축면적 is highly overall correlated with 연면적High correlation
연면적 is highly overall correlated with 건축면적High correlation
용도(기타용도) is highly imbalanced (74.2%)Imbalance
대지면적 has 28 (10.7%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:02:00.436889
Analysis finished2023-12-12 17:02:02.932216
Duration2.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct262
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean131.5
Minimum1
Maximum262
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-13T02:02:03.014720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14.05
Q166.25
median131.5
Q3196.75
95-th percentile248.95
Maximum262
Range261
Interquartile range (IQR)130.5

Descriptive statistics

Standard deviation75.777085
Coefficient of variation (CV)0.5762516
Kurtosis-1.2
Mean131.5
Median Absolute Deviation (MAD)65.5
Skewness0
Sum34453
Variance5742.1667
MonotonicityStrictly increasing
2023-12-13T02:02:03.172400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
166 1
 
0.4%
168 1
 
0.4%
169 1
 
0.4%
170 1
 
0.4%
171 1
 
0.4%
172 1
 
0.4%
173 1
 
0.4%
174 1
 
0.4%
175 1
 
0.4%
Other values (252) 252
96.2%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
262 1
0.4%
261 1
0.4%
260 1
0.4%
259 1
0.4%
258 1
0.4%
257 1
0.4%
256 1
0.4%
255 1
0.4%
254 1
0.4%
253 1
0.4%

대지위치(농막)
Text

Distinct261
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-13T02:02:03.582052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length20.423664
Min length17

Characters and Unicode

Total characters5351
Distinct characters46
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

Unique260 ?
Unique (%)99.2%

Sample

1st row경기도 화성시 송산면 지화리 170-1
2nd row경기도 화성시 송산면 용포리 427
3rd row경기도 화성시 송산면 용포리 738-11
4th row경기도 화성시 송산면 마산리 183-7
5th row경기도 화성시 송산면 삼존리 1240-1
ValueCountFrequency (%)
경기도 262
20.0%
송산면 262
20.0%
화성시 262
20.0%
독지리 27
 
2.1%
고정리 26
 
2.0%
삼존리 26
 
2.0%
용포리 24
 
1.8%
고포리 21
 
1.6%
쌍정리 20
 
1.5%
봉가리 20
 
1.5%
Other values (266) 363
27.6%
2023-12-13T02:02:04.219564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1051
19.6%
산 281
 
5.3%
화 277
 
5.2%
송 277
 
5.2%
경 262
 
4.9%
도 262
 
4.9%
성 262
 
4.9%
시 262
 
4.9%
면 262
 
4.9%
기 262
 
4.9%
Other values (36) 1893
35.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3153
58.9%
Space Separator 1051
 
19.6%
Decimal Number 975
 
18.2%
Dash Punctuation 172
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 281
8.9%
화 277
8.8%
송 277
8.8%
경 262
8.3%
도 262
8.3%
성 262
8.3%
시 262
8.3%
면 262
8.3%
기 262
8.3%
리 262
8.3%
Other values (24) 484
15.4%
Decimal Number
ValueCountFrequency (%)
1 197
20.2%
2 137
14.1%
5 107
11.0%
3 102
10.5%
4 90
9.2%
6 87
8.9%
0 75
 
7.7%
8 69
 
7.1%
7 65
 
6.7%
9 46
 
4.7%
Space Separator
ValueCountFrequency (%)
1051
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 172
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3153
58.9%
Common 2198
41.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 281
8.9%
화 277
8.8%
송 277
8.8%
경 262
8.3%
도 262
8.3%
성 262
8.3%
시 262
8.3%
면 262
8.3%
기 262
8.3%
리 262
8.3%
Other values (24) 484
15.4%
Common
ValueCountFrequency (%)
1051
47.8%
1 197
 
9.0%
- 172
 
7.8%
2 137
 
6.2%
5 107
 
4.9%
3 102
 
4.6%
4 90
 
4.1%
6 87
 
4.0%
0 75
 
3.4%
8 69
 
3.1%
Other values (2) 111
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3153
58.9%
ASCII 2198
41.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1051
47.8%
1 197
 
9.0%
- 172
 
7.8%
2 137
 
6.2%
5 107
 
4.9%
3 102
 
4.6%
4 90
 
4.1%
6 87
 
4.0%
0 75
 
3.4%
8 69
 
3.1%
Other values (2) 111
 
5.1%
Hangul
ValueCountFrequency (%)
산 281
8.9%
화 277
8.8%
송 277
8.8%
경 262
8.3%
도 262
8.3%
성 262
8.3%
시 262
8.3%
면 262
8.3%
기 262
8.3%
리 262
8.3%
Other values (24) 484
15.4%

지목
Categorical

Distinct5
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
전
152 
답
96 
과수원
 
12
임야
 
1
목장용지
 
1

Length

Max length4
Median length1
Mean length1.1068702
Min length1

Unique

Unique2 ?
Unique (%)0.8%

Sample

1st row전
2nd row답
3rd row답
4th row답
5th row답

Common Values

ValueCountFrequency (%)
전 152
58.0%
답 96
36.6%
과수원 12
 
4.6%
임야 1
 
0.4%
목장용지 1
 
0.4%

Length

2023-12-13T02:02:04.402529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:02:04.546427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전 152
58.0%
답 96
36.6%
과수원 12
 
4.6%
임야 1
 
0.4%
목장용지 1
 
0.4%

대지면적
Real number (ℝ)

MISSING 

Distinct205
Distinct (%)87.6%
Missing28
Missing (%)10.7%
Infinite0
Infinite (%)0.0%
Mean1259.0184
Minimum60
Maximum7077
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-13T02:02:04.693412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum60
5-th percentile242
Q1556
median938.5
Q31599.25
95-th percentile3343.65
Maximum7077
Range7017
Interquartile range (IQR)1043.25

Descriptive statistics

Standard deviation1074.2088
Coefficient of variation (CV)0.8532114
Kurtosis7.0061196
Mean1259.0184
Median Absolute Deviation (MAD)449
Skewness2.2802302
Sum294610.3
Variance1153924.6
MonotonicityNot monotonic
2023-12-13T02:02:04.887208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
661.0 6
 
2.3%
331.0 3
 
1.1%
495.0 3
 
1.1%
1359.0 3
 
1.1%
827.0 3
 
1.1%
826.0 3
 
1.1%
1874.0 2
 
0.8%
304.0 2
 
0.8%
850.0 2
 
0.8%
810.0 2
 
0.8%
Other values (195) 205
78.2%
(Missing) 28
 
10.7%
ValueCountFrequency (%)
60.0 1
0.4%
109.0 1
0.4%
113.0 1
0.4%
122.4 1
0.4%
124.0 1
0.4%
159.0 1
0.4%
177.0 1
0.4%
212.0 1
0.4%
222.0 1
0.4%
227.0 1
0.4%
ValueCountFrequency (%)
7077.0 1
0.4%
6213.0 1
0.4%
5560.0 1
0.4%
5223.0 1
0.4%
5115.0 1
0.4%
4460.0 1
0.4%
3970.0 1
0.4%
3841.0 1
0.4%
3822.0 1
0.4%
3714.3 1
0.4%

건축면적
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)7.3%
Missing1
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean17.63728
Minimum5.4
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-13T02:02:05.061471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.4
5-th percentile12
Q118
median18
Q318
95-th percentile19.5
Maximum20
Range14.6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.9010974
Coefficient of variation (CV)0.10778859
Kurtosis15.416165
Mean17.63728
Median Absolute Deviation (MAD)0
Skewness-3.676551
Sum4603.33
Variance3.6141714
MonotonicityNot monotonic
2023-12-13T02:02:05.193821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
18.0 219
83.6%
12.0 9
 
3.4%
20.0 6
 
2.3%
19.5 4
 
1.5%
15.0 4
 
1.5%
19.8 3
 
1.1%
19.04 2
 
0.8%
14.0 2
 
0.8%
9.0 2
 
0.8%
8.92 1
 
0.4%
Other values (9) 9
 
3.4%
ValueCountFrequency (%)
5.4 1
 
0.4%
7.2 1
 
0.4%
8.92 1
 
0.4%
9.0 2
 
0.8%
12.0 9
 
3.4%
14.0 2
 
0.8%
15.0 4
 
1.5%
16.0 1
 
0.4%
17.0 1
 
0.4%
18.0 219
83.6%
ValueCountFrequency (%)
20.0 6
 
2.3%
19.98 1
 
0.4%
19.93 1
 
0.4%
19.8 3
 
1.1%
19.72 1
 
0.4%
19.5 4
 
1.5%
19.2 1
 
0.4%
19.04 2
 
0.8%
18.5 1
 
0.4%
18.0 219
83.6%

연면적
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.569962
Minimum0
Maximum20
Zeros1
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-13T02:02:05.350039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12
Q118
median18
Q318
95-th percentile19.5
Maximum20
Range20
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.1880649
Coefficient of variation (CV)0.12453441
Kurtosis23.442869
Mean17.569962
Median Absolute Deviation (MAD)0
Skewness-4.3311697
Sum4603.33
Variance4.787628
MonotonicityNot monotonic
2023-12-13T02:02:05.544274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
18.0 219
83.6%
12.0 9
 
3.4%
20.0 6
 
2.3%
19.5 4
 
1.5%
15.0 4
 
1.5%
19.8 3
 
1.1%
9.0 2
 
0.8%
14.0 2
 
0.8%
19.04 2
 
0.8%
7.2 1
 
0.4%
Other values (10) 10
 
3.8%
ValueCountFrequency (%)
0.0 1
 
0.4%
5.4 1
 
0.4%
7.2 1
 
0.4%
8.92 1
 
0.4%
9.0 2
 
0.8%
12.0 9
3.4%
14.0 2
 
0.8%
15.0 4
1.5%
16.0 1
 
0.4%
17.0 1
 
0.4%
ValueCountFrequency (%)
20.0 6
 
2.3%
19.98 1
 
0.4%
19.93 1
 
0.4%
19.8 3
 
1.1%
19.72 1
 
0.4%
19.5 4
 
1.5%
19.2 1
 
0.4%
19.04 2
 
0.8%
18.5 1
 
0.4%
18.0 219
83.6%

용도(기타용도)
Categorical

IMBALANCE 

Distinct8
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
임시창고(농막)
223 
농막
32 
임시창고(농막)
 
2
임시창고-농막
 
1
농막(임시창고)
 
1
Other values (3)
 
3

Length

Max length9
Median length8
Mean length7.2519084
Min length2

Unique

Unique5 ?
Unique (%)1.9%

Sample

1st row농막
2nd row임시창고(농막)
3rd row임시창고(농막)
4th row임시창고(농막)
5th row임시창고-농막

Common Values

ValueCountFrequency (%)
임시창고(농막) 223
85.1%
농막 32
 
12.2%
임시창고(농막) 2
 
0.8%
임시창고-농막 1
 
0.4%
농막(임시창고) 1
 
0.4%
(농막) 1
 
0.4%
농사용임시창고 1
 
0.4%
농사용 임시창고 1
 
0.4%

Length

2023-12-13T02:02:06.109594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:02:06.251391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
임시창고(농막 225
85.6%
농막 33
 
12.5%
임시창고-농막 1
 
0.4%
농막(임시창고 1
 
0.4%
농사용임시창고 1
 
0.4%
농사용 1
 
0.4%
임시창고 1
 
0.4%

구조(기타구조)
Categorical

Distinct10
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
컨테이너
112 
컨테이너조
75 
<NA>
67 
콘테이너
 
2
조립식
 
1
Other values (5)
 
5

Length

Max length7
Median length4
Mean length4.3015267
Min length3

Unique

Unique6 ?
Unique (%)2.3%

Sample

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

Common Values

ValueCountFrequency (%)
컨테이너 112
42.7%
컨테이너조 75
28.6%
<NA> 67
25.6%
콘테이너 2
 
0.8%
조립식 1
 
0.4%
파이프천막 1
 
0.4%
합성수지 1
 
0.4%
비닐하우스 1
 
0.4%
강파이프/천막 1
 
0.4%
켄터이너 1
 
0.4%

Length

2023-12-13T02:02:06.406150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:02:06.577960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
컨테이너 112
42.7%
컨테이너조 75
28.6%
na 67
25.6%
콘테이너 2
 
0.8%
조립식 1
 
0.4%
파이프천막 1
 
0.4%
합성수지 1
 
0.4%
비닐하우스 1
 
0.4%
강파이프/천막 1
 
0.4%
켄터이너 1
 
0.4%

적법여부
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
적법
162 
불법
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row불법
2nd row적법
3rd row적법
4th row불법
5th row불법

Common Values

ValueCountFrequency (%)
적법 162
61.8%
불법 100
38.2%

Length

2023-12-13T02:02:06.728385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:02:06.821665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
적법 162
61.8%
불법 100
38.2%

Interactions

2023-12-13T02:02:02.086528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:02:00.849164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:02:01.242698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:02:01.634826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:02:02.174490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:02:00.938204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:02:01.328521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:02:01.755794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:02:02.281385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:02:01.027239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:02:01.425721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:02:01.855816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:02:02.441827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:02:01.138613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:02:01.524017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:02:01.963925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:02:06.888298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번지목대지면적건축면적연면적용도(기타용도)구조(기타구조)적법여부
연번1.0000.1550.1310.1650.1690.3770.6160.000
지목0.1551.0000.1720.0000.0000.0000.0000.000
대지면적0.1310.1721.0000.0000.0000.0000.5340.197
건축면적0.1650.0000.0001.0000.9750.6210.5070.068
연면적0.1690.0000.0000.9751.0000.7660.3830.124
용도(기타용도)0.3770.0000.0000.6210.7661.0000.0730.210
구조(기타구조)0.6160.0000.5340.5070.3830.0731.0000.000
적법여부0.0000.0000.1970.0680.1240.2100.0001.000
2023-12-13T02:02:07.008588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
적법여부용도(기타용도)구조(기타구조)지목
적법여부1.0000.1550.0000.000
용도(기타용도)0.1551.0000.0390.000
구조(기타구조)0.0000.0391.0000.000
지목0.0000.0000.0001.000
2023-12-13T02:02:07.114559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번대지면적건축면적연면적지목용도(기타용도)구조(기타구조)적법여부
연번1.000-0.141-0.0110.0040.0630.1890.3360.000
대지면적-0.1411.0000.0010.0010.0700.0000.1950.148
건축면적-0.0110.0011.0000.9860.0000.3640.2950.067
연면적0.0040.0010.9861.0000.0000.3680.2930.063
지목0.0630.0700.0000.0001.0000.0000.0000.000
용도(기타용도)0.1890.0000.3640.3680.0001.0000.0390.155
구조(기타구조)0.3360.1950.2950.2930.0000.0391.0000.000
적법여부0.0000.1480.0670.0630.0000.1550.0001.000

Missing values

2023-12-13T02:02:02.589272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:02:02.744490image/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.
2023-12-13T02:02:02.858823image/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

연번대지위치(농막)지목대지면적건축면적연면적용도(기타용도)구조(기타구조)적법여부
01경기도 화성시 송산면 지화리 170-1전1835.019.519.5농막컨테이너불법
12경기도 화성시 송산면 용포리 427답<NA>18.018.0임시창고(농막)컨테이너적법
23경기도 화성시 송산면 용포리 738-11답<NA>18.018.0임시창고(농막)컨테이너적법
34경기도 화성시 송산면 마산리 183-7답<NA>18.018.0임시창고(농막)컨테이너불법
45경기도 화성시 송산면 삼존리 1240-1답2683.818.018.0임시창고-농막컨테이너불법
56경기도 화성시 송산면 중송리 502전<NA>9.09.0임시창고(농막)컨테이너적법
67경기도 화성시 송산면 쌍정리 1226-1전<NA>18.018.0임시창고(농막)컨테이너적법
78경기도 화성시 송산면 쌍정리 1177전<NA>18.018.0임시창고(농막)컨테이너적법
89경기도 화성시 송산면 중송리 23전<NA>18.018.0임시창고(농막)컨테이너불법
910경기도 화성시 송산면 고포리 670-1전<NA>9.09.0임시창고(농막)컨테이너적법
연번대지위치(농막)지목대지면적건축면적연면적용도(기타용도)구조(기타구조)적법여부
252253경기도 화성시 송산면 용포리 6전2770.018.018.0임시창고(농막)컨테이너조적법
253254경기도 화성시 송산면 독지리 578-1전320.015.015.0임시창고(농막)컨테이너조적법
254255경기도 화성시 송산면 독지리 768답1476.012.012.0임시창고(농막)컨테이너조적법
255256경기도 화성시 송산면 육일리 431-2전2352.018.018.0임시창고(농막)컨테이너조불법
256257경기도 화성시 송산면 고포리 680-5답441.018.018.0임시창고(농막)컨테이너조불법
257258경기도 화성시 송산면 고포리 648-46전810.019.7219.72임시창고(농막)컨테이너조적법
258259경기도 화성시 송산면 삼존리 1213답122.418.018.0임시창고(농막)<NA>적법
259260경기도 화성시 송산면 칠곡리 246-1전665.018.018.0농막<NA>적법
260261경기도 화성시 송산면 마산리 579-12전1060.017.017.0임시창고(농막)컨테이너조적법
261262경기도 화성시 송산면 고포리 635답843.018.018.0임시창고(농막)컨테이너조불법