Overview

Dataset statistics

Number of variables24
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.3 KiB
Average record size in memory216.4 B

Variable types

Categorical6
Text2
Numeric16

Dataset

Description샘플 데이터
Author경기콘텐츠진흥원
URLhttps://bigdata-region.kr/#/dataset/efb5347a-3fa8-4b78-adda-9517f3f4a57a

Alerts

기준년월 has constant value ""Constant
시도명 has constant value ""Constant
표준 편차 전체 인구 밀집도 has constant value ""Constant
표준 편차 관내 인구 밀집도 has constant value ""Constant
표준 편차 외국인 인구 밀집도 has constant value ""Constant
행정동명 has unique valuesUnique
행정동 코드 has unique valuesUnique
행정동 면적 has unique valuesUnique
전체 인구수 has unique valuesUnique
관내 인구수 has unique valuesUnique
외국인 인구수 has unique valuesUnique
전체 인구 순위 has unique valuesUnique
관내 인구 순위 has unique valuesUnique
외국인 인구 순위 has unique valuesUnique
전체 인구 밀집도 has unique valuesUnique
관내 인구 밀집도 has unique valuesUnique
유동 인구 지수지표 전체 인구 밀집도 has unique valuesUnique
유동 인구 지수지표 관내 인구 밀집도 has unique valuesUnique

Reproduction

Analysis started2023-12-10 13:56:44.908540
Analysis finished2023-12-10 13:56:45.280764
Duration0.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2019-01
30 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019-01
2nd row2019-01
3rd row2019-01
4th row2019-01
5th row2019-01

Common Values

ValueCountFrequency (%)
2019-01 30
100.0%

Length

2023-12-10T22:56:45.478998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:56:45.680865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019-01 30
100.0%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
경기도
30 

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 30
100.0%

Length

2023-12-10T22:56:45.925668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:56:46.087195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 30
100.0%

시군구명
Text

Distinct17
Distinct (%)56.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:56:46.297211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0333333
Min length3

Characters and Unicode

Total characters91
Distinct characters30
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)33.3%

Sample

1st row광명시
2nd row고양시
3rd row광주시
4th row김포시
5th row구리시
ValueCountFrequency (%)
성남시 7
23.3%
파주시 3
10.0%
안산시 2
 
6.7%
김포시 2
 
6.7%
화성시 2
 
6.7%
수원시 2
 
6.7%
고양시 2
 
6.7%
용인시 1
 
3.3%
의정부시 1
 
3.3%
이천시 1
 
3.3%
Other values (7) 7
23.3%
2023-12-10T22:56:46.843384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 29
31.9%
성 9
 
9.9%
남 8
 
8.8%
주 4
 
4.4%
파 3
 
3.3%
양 3
 
3.3%
원 2
 
2.2%
광 2
 
2.2%
평 2
 
2.2%
고 2
 
2.2%
Other values (20) 27
29.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 91
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 29
31.9%
성 9
 
9.9%
남 8
 
8.8%
주 4
 
4.4%
파 3
 
3.3%
양 3
 
3.3%
원 2
 
2.2%
광 2
 
2.2%
평 2
 
2.2%
고 2
 
2.2%
Other values (20) 27
29.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 91
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 29
31.9%
성 9
 
9.9%
남 8
 
8.8%
주 4
 
4.4%
파 3
 
3.3%
양 3
 
3.3%
원 2
 
2.2%
광 2
 
2.2%
평 2
 
2.2%
고 2
 
2.2%
Other values (20) 27
29.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 91
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 29
31.9%
성 9
 
9.9%
남 8
 
8.8%
주 4
 
4.4%
파 3
 
3.3%
양 3
 
3.3%
원 2
 
2.2%
광 2
 
2.2%
평 2
 
2.2%
고 2
 
2.2%
Other values (20) 27
29.7%

행정동명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:56:47.170807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.4333333
Min length3

Characters and Unicode

Total characters103
Distinct characters56
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row광명2동
2nd row능곡동
3rd row오포읍
4th row대곶면
5th row수택2동
ValueCountFrequency (%)
광명2동 1
 
3.3%
능곡동 1
 
3.3%
설악면 1
 
3.3%
향남읍 1
 
3.3%
감북동 1
 
3.3%
장안면 1
 
3.3%
진동면 1
 
3.3%
조리읍 1
 
3.3%
운정3동 1
 
3.3%
부발읍 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T22:56:47.738346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 22
21.4%
면 6
 
5.8%
2 5
 
4.9%
읍 4
 
3.9%
3 3
 
2.9%
정 3
 
2.9%
1 3
 
2.9%
신 2
 
1.9%
태 2
 
1.9%
곶 2
 
1.9%
Other values (46) 51
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 92
89.3%
Decimal Number 11
 
10.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 22
23.9%
면 6
 
6.5%
읍 4
 
4.3%
정 3
 
3.3%
신 2
 
2.2%
태 2
 
2.2%
곶 2
 
2.2%
대 2
 
2.2%
운 2
 
2.2%
오 2
 
2.2%
Other values (43) 45
48.9%
Decimal Number
ValueCountFrequency (%)
2 5
45.5%
3 3
27.3%
1 3
27.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 92
89.3%
Common 11
 
10.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 22
23.9%
면 6
 
6.5%
읍 4
 
4.3%
정 3
 
3.3%
신 2
 
2.2%
태 2
 
2.2%
곶 2
 
2.2%
대 2
 
2.2%
운 2
 
2.2%
오 2
 
2.2%
Other values (43) 45
48.9%
Common
ValueCountFrequency (%)
2 5
45.5%
3 3
27.3%
1 3
27.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 92
89.3%
ASCII 11
 
10.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 22
23.9%
면 6
 
6.5%
읍 4
 
4.3%
정 3
 
3.3%
신 2
 
2.2%
태 2
 
2.2%
곶 2
 
2.2%
대 2
 
2.2%
운 2
 
2.2%
오 2
 
2.2%
Other values (43) 45
48.9%
ASCII
ValueCountFrequency (%)
2 5
45.5%
3 3
27.3%
1 3
27.3%

행정동 코드
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1359226 × 109
Minimum4.111752 × 109
Maximum4.183038 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:56:47.968412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.111752 × 109
5-th percentile4.1123872 × 109
Q14.1135588 × 109
median4.129611 × 109
Q34.1495332 × 109
95-th percentile4.1725783 × 109
Maximum4.183038 × 109
Range71286000
Interquartile range (IQR)35974475

Descriptive statistics

Standard deviation21561195
Coefficient of variation (CV)0.0052131524
Kurtosis-0.64651182
Mean4.1359226 × 109
Median Absolute Deviation (MAD)16453500
Skewness0.54588233
Sum1.2407768 × 1011
Variance4.6488512 × 1014
MonotonicityNot monotonic
2023-12-10T22:56:48.159752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
4121052000 1
 
3.3%
4127355500 1
 
3.3%
4128164000 1
 
3.3%
4182031000 1
 
3.3%
4159025900 1
 
3.3%
4145058000 1
 
3.3%
4159037000 1
 
3.3%
4148040000 1
 
3.3%
4148026200 1
 
3.3%
4148057000 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
4111752000 1
3.3%
4111759000 1
3.3%
4113155000 1
3.3%
4113160000 1
3.3%
4113164000 1
3.3%
4113165000 1
3.3%
4113366000 1
3.3%
4113557000 1
3.3%
4113564000 1
3.3%
4115052000 1
3.3%
ValueCountFrequency (%)
4183038000 1
3.3%
4182031000 1
3.3%
4161025000 1
3.3%
4159037000 1
3.3%
4159025900 1
3.3%
4157035000 1
3.3%
4157034000 1
3.3%
4150025300 1
3.3%
4148057000 1
3.3%
4148040000 1
3.3%

행정동 면적
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.442667
Minimum0.26
Maximum141.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:56:48.422664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.26
5-th percentile0.525
Q12.055
median9.55
Q342.91
95-th percentile96.4955
Maximum141.02
Range140.76
Interquartile range (IQR)40.855

Descriptive statistics

Standard deviation35.033655
Coefficient of variation (CV)1.4332992
Kurtosis4.478142
Mean24.442667
Median Absolute Deviation (MAD)8.91
Skewness2.0934569
Sum733.28
Variance1227.357
MonotonicityNot monotonic
2023-12-10T22:56:48.638676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0.26 1
 
3.3%
1.44 1
 
3.3%
0.67 1
 
3.3%
141.02 1
 
3.3%
50.0 1
 
3.3%
13.22 1
 
3.3%
67.56 1
 
3.3%
43.43 1
 
3.3%
27.42 1
 
3.3%
5.87 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
0.26 1
3.3%
0.48 1
3.3%
0.58 1
3.3%
0.59 1
3.3%
0.61 1
3.3%
0.67 1
3.3%
1.44 1
3.3%
1.97 1
3.3%
2.31 1
3.3%
2.34 1
3.3%
ValueCountFrequency (%)
141.02 1
3.3%
120.17 1
3.3%
67.56 1
3.3%
51.99 1
3.3%
50.0 1
3.3%
46.82 1
3.3%
43.43 1
3.3%
43.24 1
3.3%
41.92 1
3.3%
27.42 1
3.3%

전체 인구수
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72919.215
Minimum591.42
Maximum243921.75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:56:48.847187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum591.42
5-th percentile7960.665
Q130847.208
median60079.74
Q391459.402
95-th percentile180933.18
Maximum243921.75
Range243330.33
Interquartile range (IQR)60612.195

Descriptive statistics

Standard deviation57262.511
Coefficient of variation (CV)0.78528699
Kurtosis1.6846687
Mean72919.215
Median Absolute Deviation (MAD)31268.25
Skewness1.2764138
Sum2187576.5
Variance3.2789951 × 109
MonotonicityNot monotonic
2023-12-10T22:56:49.050085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
7627.8 1
 
3.3%
39949.26 1
 
3.3%
25112.84 1
 
3.3%
76112.28 1
 
3.3%
243921.75 1
 
3.3%
86038.65 1
 
3.3%
86959.65 1
 
3.3%
591.42 1
 
3.3%
92959.32 1
 
3.3%
106473.01 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
591.42 1
3.3%
7627.8 1
3.3%
8367.5 1
3.3%
15839.31 1
3.3%
21953.43 1
3.3%
25112.84 1
3.3%
27169.52 1
3.3%
30422.82 1
3.3%
32120.37 1
3.3%
39949.26 1
3.3%
ValueCountFrequency (%)
243921.75 1
3.3%
187794.45 1
3.3%
172547.18 1
3.3%
151514.48 1
3.3%
122109.09 1
3.3%
106473.01 1
3.3%
101994.44 1
3.3%
92959.32 1
3.3%
86959.65 1
3.3%
86038.65 1
3.3%

관내 인구수
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33959.999
Minimum386.21
Maximum140982.11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:56:49.238658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum386.21
5-th percentile3808.492
Q113984.8
median23435.435
Q340180.932
95-th percentile99020.986
Maximum140982.11
Range140595.9
Interquartile range (IQR)26196.132

Descriptive statistics

Standard deviation32219.98
Coefficient of variation (CV)0.94876269
Kurtosis3.5165836
Mean33959.999
Median Absolute Deviation (MAD)14396.83
Skewness1.8225561
Sum1018800
Variance1.0381271 × 109
MonotonicityNot monotonic
2023-12-10T22:56:49.446182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
3149.8 1
 
3.3%
26082.09 1
 
3.3%
18551.69 1
 
3.3%
11574.84 1
 
3.3%
140982.11 1
 
3.3%
13926.54 1
 
3.3%
37890.01 1
 
3.3%
386.21 1
 
3.3%
49356.54 1
 
3.3%
68212.66 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
386.21 1
3.3%
3149.8 1
3.3%
4613.56 1
3.3%
6062.81 1
3.3%
9058.45 1
3.3%
9713.83 1
3.3%
11574.84 1
3.3%
13926.54 1
3.3%
14159.58 1
3.3%
16766.01 1
3.3%
ValueCountFrequency (%)
140982.11 1
3.3%
99607.08 1
3.3%
98304.65 1
3.3%
68212.66 1
3.3%
61940.05 1
3.3%
49356.54 1
3.3%
46360.08 1
3.3%
40872.52 1
3.3%
38106.17 1
3.3%
37890.01 1
3.3%

외국인 인구수
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1493.6697
Minimum47.65
Maximum7628.16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:56:49.711221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum47.65
5-th percentile121.7325
Q1480.77
median903.895
Q31200.91
95-th percentile6085.615
Maximum7628.16
Range7580.51
Interquartile range (IQR)720.14

Descriptive statistics

Standard deviation1938.6602
Coefficient of variation (CV)1.2979176
Kurtosis4.3076478
Mean1493.6697
Median Absolute Deviation (MAD)400.815
Skewness2.2590933
Sum44810.09
Variance3758403.2
MonotonicityNot monotonic
2023-12-10T22:56:49.991737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
424.5 1
 
3.3%
5132.19 1
 
3.3%
547.7 1
 
3.3%
155.75 1
 
3.3%
6865.69 1
 
3.3%
673.71 1
 
3.3%
2396.32 1
 
3.3%
47.65 1
 
3.3%
1115.62 1
 
3.3%
1047.16 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
47.65 1
3.3%
93.9 1
3.3%
155.75 1
3.3%
265.0 1
3.3%
315.14 1
3.3%
327.42 1
3.3%
424.5 1
3.3%
458.46 1
3.3%
547.7 1
3.3%
562.61 1
3.3%
ValueCountFrequency (%)
7628.16 1
3.3%
6865.69 1
3.3%
5132.19 1
3.3%
4633.91 1
3.3%
2396.32 1
3.3%
1449.68 1
3.3%
1381.37 1
3.3%
1229.34 1
3.3%
1115.62 1
3.3%
1072.96 1
3.3%

전체 인구 순위
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean265.86667
Minimum4
Maximum562
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:56:50.197275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile16.8
Q1140.25
median257.5
Q3406
95-th percentile545.75
Maximum562
Range558
Interquartile range (IQR)265.75

Descriptive statistics

Standard deviation172.97413
Coefficient of variation (CV)0.65060481
Kurtosis-1.135084
Mean265.86667
Median Absolute Deviation (MAD)141.5
Skewness0.20607063
Sum7976
Variance29920.051
MonotonicityNot monotonic
2023-12-10T22:56:50.403274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
548 1
 
3.3%
354 1
 
3.3%
458 1
 
3.3%
184 1
 
3.3%
4 1
 
3.3%
155 1
 
3.3%
153 1
 
3.3%
562 1
 
3.3%
136 1
 
3.3%
109 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
4 1
3.3%
15 1
3.3%
19 1
3.3%
42 1
3.3%
72 1
3.3%
109 1
3.3%
114 1
3.3%
136 1
3.3%
153 1
3.3%
155 1
3.3%
ValueCountFrequency (%)
562 1
3.3%
548 1
3.3%
543 1
3.3%
508 1
3.3%
471 1
3.3%
458 1
3.3%
438 1
3.3%
409 1
3.3%
397 1
3.3%
354 1
3.3%

관내 인구 순위
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean290.66667
Minimum4
Maximum561
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:56:50.589345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile9.9
Q1163
median302.5
Q3425.75
95-th percentile542.35
Maximum561
Range557
Interquartile range (IQR)262.75

Descriptive statistics

Standard deviation175.81364
Coefficient of variation (CV)0.60486345
Kurtosis-1.1567932
Mean290.66667
Median Absolute Deviation (MAD)135
Skewness-0.12436959
Sum8720
Variance30910.437
MonotonicityNot monotonic
2023-12-10T22:56:50.778791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
550 1
 
3.3%
277 1
 
3.3%
356 1
 
3.3%
468 1
 
3.3%
4 1
 
3.3%
427 1
 
3.3%
185 1
 
3.3%
561 1
 
3.3%
111 1
 
3.3%
45 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
4 1
3.3%
9 1
3.3%
11 1
3.3%
45 1
3.3%
63 1
3.3%
111 1
3.3%
131 1
3.3%
157 1
3.3%
181 1
3.3%
185 1
3.3%
ValueCountFrequency (%)
561 1
3.3%
550 1
3.3%
533 1
3.3%
523 1
3.3%
492 1
3.3%
487 1
3.3%
468 1
3.3%
427 1
3.3%
422 1
3.3%
388 1
3.3%

외국인 인구 순위
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean266.86667
Minimum10
Maximum551
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:56:50.963209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile14.25
Q1167.5
median243.5
Q3392.75
95-th percentile531.35
Maximum551
Range541
Interquartile range (IQR)225.25

Descriptive statistics

Standard deviation162.51997
Coefficient of variation (CV)0.60899314
Kurtosis-0.88722111
Mean266.86667
Median Absolute Deviation (MAD)116
Skewness0.078051069
Sum8006
Variance26412.74
MonotonicityNot monotonic
2023-12-10T22:56:51.172030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
415 1
 
3.3%
17 1
 
3.3%
368 1
 
3.3%
522 1
 
3.3%
12 1
 
3.3%
307 1
 
3.3%
60 1
 
3.3%
551 1
 
3.3%
187 1
 
3.3%
203 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
10 1
3.3%
12 1
3.3%
17 1
3.3%
22 1
3.3%
60 1
3.3%
127 1
3.3%
138 1
3.3%
161 1
3.3%
187 1
3.3%
197 1
3.3%
ValueCountFrequency (%)
551 1
3.3%
539 1
3.3%
522 1
3.3%
474 1
3.3%
456 1
3.3%
451 1
3.3%
415 1
3.3%
401 1
3.3%
368 1
3.3%
359 1
3.3%

전체 인구 밀집도
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14328.278
Minimum13.62
Maximum44540.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:56:51.397599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13.62
5-th percentile382.1165
Q14037.27
median9286.51
Q324377.36
95-th percentile37359.157
Maximum44540.2
Range44526.58
Interquartile range (IQR)20340.09

Descriptive statistics

Standard deviation12974.893
Coefficient of variation (CV)0.90554444
Kurtosis-0.51859016
Mean14328.278
Median Absolute Deviation (MAD)8072.57
Skewness0.77420698
Sum429848.34
Variance1.6834784 × 108
MonotonicityNot monotonic
2023-12-10T22:56:51.604054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
29337.69 1
 
3.3%
27742.54 1
 
3.3%
37481.85 1
 
3.3%
539.73 1
 
3.3%
4878.43 1
 
3.3%
6508.22 1
 
3.3%
1287.15 1
 
3.3%
13.62 1
 
3.3%
3390.2 1
 
3.3%
18138.5 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
13.62 1
3.3%
253.16 1
3.3%
539.73 1
3.3%
827.02 1
3.3%
1287.15 1
3.3%
2358.8 1
3.3%
3390.2 1
3.3%
4010.99 1
3.3%
4116.11 1
3.3%
4361.66 1
3.3%
ValueCountFrequency (%)
44540.2 1
3.3%
37481.85 1
3.3%
37209.2 1
3.3%
31899.87 1
3.3%
29337.69 1
3.3%
27742.54 1
3.3%
27309.16 1
3.3%
25179.58 1
3.3%
21970.7 1
3.3%
18138.5 1
3.3%

관내 인구 밀집도
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7848.1223
Minimum8.89
Maximum28381.16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:56:51.792593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.89
5-th percentile58.0505
Q11284.9475
median5196.395
Q312501.792
95-th percentile23379.651
Maximum28381.16
Range28372.27
Interquartile range (IQR)11216.845

Descriptive statistics

Standard deviation8071.0779
Coefficient of variation (CV)1.0284088
Kurtosis0.58061675
Mean7848.1223
Median Absolute Deviation (MAD)4754.735
Skewness1.0862189
Sum235443.67
Variance65142299
MonotonicityNot monotonic
2023-12-10T22:56:52.012171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
12114.62 1
 
3.3%
18112.56 1
 
3.3%
27689.09 1
 
3.3%
82.08 1
 
3.3%
2819.64 1
 
3.3%
1053.44 1
 
3.3%
560.83 1
 
3.3%
8.89 1
 
3.3%
1800.02 1
 
3.3%
11620.56 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
8.89 1
3.3%
38.39 1
3.3%
82.08 1
3.3%
322.49 1
3.3%
560.83 1
3.3%
881.27 1
3.3%
1053.44 1
3.3%
1149.32 1
3.3%
1691.83 1
3.3%
1800.02 1
3.3%
ValueCountFrequency (%)
28381.16 1
3.3%
27689.09 1
3.3%
18112.56 1
3.3%
16747.98 1
3.3%
16283.87 1
3.3%
15353.31 1
3.3%
14561.76 1
3.3%
12630.85 1
3.3%
12114.62 1
3.3%
11620.56 1
3.3%

외국인 밀집도
Real number (ℝ)

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean372.12533
Minimum1.1
Maximum3564.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:56:52.329974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1
5-th percentile4.394
Q143.2575
median145.62
Q3343.5725
95-th percentile1327.788
Maximum3564.02
Range3562.92
Interquartile range (IQR)300.315

Descriptive statistics

Standard deviation696.39705
Coefficient of variation (CV)1.8714046
Kurtosis15.899006
Mean372.12533
Median Absolute Deviation (MAD)118.05
Skewness3.7494073
Sum11163.76
Variance484968.85
MonotonicityNot monotonic
2023-12-10T22:56:52.873863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1.1 2
 
6.7%
1632.69 1
 
3.3%
85.77 1
 
3.3%
817.46 1
 
3.3%
137.31 1
 
3.3%
50.96 1
 
3.3%
35.47 1
 
3.3%
40.69 1
 
3.3%
178.39 1
 
3.3%
181.97 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
1.1 2
6.7%
8.42 1
3.3%
18.56 1
3.3%
25.64 1
3.3%
29.5 1
3.3%
35.47 1
3.3%
40.69 1
3.3%
50.96 1
3.3%
56.98 1
3.3%
77.37 1
3.3%
ValueCountFrequency (%)
3564.02 1
3.3%
1632.69 1
3.3%
955.13 1
3.3%
817.46 1
3.3%
543.34 1
3.3%
449.15 1
3.3%
406.89 1
3.3%
348.77 1
3.3%
327.98 1
3.3%
322.64 1
3.3%

전체 인구 밀집도 백분위
Real number (ℝ)

Distinct26
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.033333
Minimum1
Maximum89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:56:53.068332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.8
Q128
median42
Q369
95-th percentile84.55
Maximum89
Range88
Interquartile range (IQR)41

Descriptive statistics

Standard deviation26.077449
Coefficient of variation (CV)0.56649056
Kurtosis-1.1694631
Mean46.033333
Median Absolute Deviation (MAD)19.5
Skewness0.028256772
Sum1381
Variance680.03333
MonotonicityNot monotonic
2023-12-10T22:56:53.268623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
28 2
 
6.7%
34 2
 
6.7%
74 2
 
6.7%
42 2
 
6.7%
77 1
 
3.3%
5 1
 
3.3%
85 1
 
3.3%
9 1
 
3.3%
31 1
 
3.3%
16 1
 
3.3%
Other values (16) 16
53.3%
ValueCountFrequency (%)
1 1
3.3%
5 1
3.3%
9 1
3.3%
13 1
3.3%
16 1
3.3%
21 1
3.3%
26 1
3.3%
28 2
6.7%
29 1
3.3%
31 1
3.3%
ValueCountFrequency (%)
89 1
3.3%
85 1
3.3%
84 1
3.3%
80 1
3.3%
77 1
3.3%
74 2
6.7%
70 1
3.3%
66 1
3.3%
60 1
3.3%
59 1
3.3%

관내 인구 밀집도 백분위
Real number (ℝ)

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.066667
Minimum1
Maximum92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:56:53.472170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.9
Q124
median44.5
Q367.25
95-th percentile85.6
Maximum92
Range91
Interquartile range (IQR)43.25

Descriptive statistics

Standard deviation27.070704
Coefficient of variation (CV)0.60068129
Kurtosis-1.1624028
Mean45.066667
Median Absolute Deviation (MAD)22
Skewness0.04890892
Sum1352
Variance732.82299
MonotonicityNot monotonic
2023-12-10T22:56:53.727420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
28 2
 
6.7%
43 1
 
3.3%
91 1
 
3.3%
4 1
 
3.3%
34 1
 
3.3%
22 1
 
3.3%
17 1
 
3.3%
1 1
 
3.3%
64 1
 
3.3%
32 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
1 1
3.3%
2 1
3.3%
4 1
3.3%
12 1
3.3%
17 1
3.3%
21 1
3.3%
22 1
3.3%
23 1
3.3%
27 1
3.3%
28 2
6.7%
ValueCountFrequency (%)
92 1
3.3%
91 1
3.3%
79 1
3.3%
77 1
3.3%
76 1
3.3%
74 1
3.3%
71 1
3.3%
68 1
3.3%
65 1
3.3%
64 1
3.3%

외국인 인구 밀집도 백분위
Categorical

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2
8 
3
8 
4
6 
5
4 
1
4 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row2
3rd row2
4th row3
5th row4

Common Values

ValueCountFrequency (%)
2 8
26.7%
3 8
26.7%
4 6
20.0%
5 4
13.3%
1 4
13.3%

Length

2023-12-10T22:56:53.944619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:56:54.161551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 8
26.7%
3 8
26.7%
4 6
20.0%
5 4
13.3%
1 4
13.3%

표준 편차 전체 인구 밀집도
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
22586.78
30 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row22586.78
2nd row22586.78
3rd row22586.78
4th row22586.78
5th row22586.78

Common Values

ValueCountFrequency (%)
22586.78 30
100.0%

Length

2023-12-10T22:56:54.417710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:56:54.570836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
22586.78 30
100.0%

표준 편차 관내 인구 밀집도
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
12052.58
30 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row12052.58
2nd row12052.58
3rd row12052.58
4th row12052.58
5th row12052.58

Common Values

ValueCountFrequency (%)
12052.58 30
100.0%

Length

2023-12-10T22:56:54.717804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:56:54.870144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
12052.58 30
100.0%

표준 편차 외국인 인구 밀집도
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
716.52
30 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row716.52
2nd row716.52
3rd row716.52
4th row716.52
5th row716.52

Common Values

ValueCountFrequency (%)
716.52 30
100.0%

Length

2023-12-10T22:56:55.085724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:56:55.289720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
716.52 30
100.0%

유동 인구 지수지표 전체 인구 밀집도
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63.436667
Minimum0.06
Maximum197.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:56:55.450773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.06
5-th percentile1.6915
Q117.875
median41.115
Q3107.9275
95-th percentile165.4055
Maximum197.2
Range197.14
Interquartile range (IQR)90.0525

Descriptive statistics

Standard deviation57.445836
Coefficient of variation (CV)0.90556202
Kurtosis-0.51856824
Mean63.436667
Median Absolute Deviation (MAD)35.74
Skewness0.77421875
Sum1903.1
Variance3300.0241
MonotonicityNot monotonic
2023-12-10T22:56:55.644306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
129.89 1
 
3.3%
122.83 1
 
3.3%
165.95 1
 
3.3%
2.39 1
 
3.3%
21.6 1
 
3.3%
28.81 1
 
3.3%
5.7 1
 
3.3%
0.06 1
 
3.3%
15.01 1
 
3.3%
80.31 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
0.06 1
3.3%
1.12 1
3.3%
2.39 1
3.3%
3.66 1
3.3%
5.7 1
3.3%
10.44 1
3.3%
15.01 1
3.3%
17.76 1
3.3%
18.22 1
3.3%
19.31 1
3.3%
ValueCountFrequency (%)
197.2 1
3.3%
165.95 1
3.3%
164.74 1
3.3%
141.23 1
3.3%
129.89 1
3.3%
122.83 1
3.3%
120.91 1
3.3%
111.48 1
3.3%
97.27 1
3.3%
80.31 1
3.3%

유동 인구 지수지표 관내 인구 밀집도
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65.116
Minimum0.07
Maximum235.48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:56:55.876124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.07
5-th percentile0.482
Q110.665
median43.115
Q3103.7275
95-th percentile193.983
Maximum235.48
Range235.41
Interquartile range (IQR)93.0625

Descriptive statistics

Standard deviation66.966617
Coefficient of variation (CV)1.0284203
Kurtosis0.58063077
Mean65.116
Median Absolute Deviation (MAD)39.45
Skewness1.0862312
Sum1953.48
Variance4484.5278
MonotonicityNot monotonic
2023-12-10T22:56:56.086813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
100.51 1
 
3.3%
150.28 1
 
3.3%
229.74 1
 
3.3%
0.68 1
 
3.3%
23.39 1
 
3.3%
8.74 1
 
3.3%
4.65 1
 
3.3%
0.07 1
 
3.3%
14.93 1
 
3.3%
96.42 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
0.07 1
3.3%
0.32 1
3.3%
0.68 1
3.3%
2.68 1
3.3%
4.65 1
3.3%
7.31 1
3.3%
8.74 1
3.3%
9.54 1
3.3%
14.04 1
3.3%
14.93 1
3.3%
ValueCountFrequency (%)
235.48 1
3.3%
229.74 1
3.3%
150.28 1
3.3%
138.96 1
3.3%
135.11 1
3.3%
127.39 1
3.3%
120.82 1
3.3%
104.8 1
3.3%
100.51 1
3.3%
96.42 1
3.3%

유동 인구 지수지표 외국인밀집도
Real number (ℝ)

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.936
Minimum0.15
Maximum497.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:56:56.403624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.15
5-th percentile0.6135
Q16.0375
median20.32
Q347.9525
95-th percentile185.3135
Maximum497.41
Range497.26
Interquartile range (IQR)41.915

Descriptive statistics

Standard deviation97.192458
Coefficient of variation (CV)1.871389
Kurtosis15.898727
Mean51.936
Median Absolute Deviation (MAD)16.47
Skewness3.7493719
Sum1558.08
Variance9446.3739
MonotonicityNot monotonic
2023-12-10T22:56:56.857274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0.15 2
 
6.7%
227.87 1
 
3.3%
11.97 1
 
3.3%
114.09 1
 
3.3%
19.16 1
 
3.3%
7.11 1
 
3.3%
4.95 1
 
3.3%
5.68 1
 
3.3%
24.9 1
 
3.3%
25.4 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
0.15 2
6.7%
1.18 1
3.3%
2.59 1
3.3%
3.58 1
3.3%
4.12 1
3.3%
4.95 1
3.3%
5.68 1
3.3%
7.11 1
3.3%
7.95 1
3.3%
10.8 1
3.3%
ValueCountFrequency (%)
497.41 1
3.3%
227.87 1
3.3%
133.3 1
3.3%
114.09 1
3.3%
75.83 1
3.3%
62.69 1
3.3%
56.79 1
3.3%
48.68 1
3.3%
45.77 1
3.3%
45.03 1
3.3%

Sample

기준년월시도명시군구명행정동명행정동 코드행정동 면적전체 인구수관내 인구수외국인 인구수전체 인구 순위관내 인구 순위외국인 인구 순위전체 인구 밀집도관내 인구 밀집도외국인 밀집도전체 인구 밀집도 백분위관내 인구 밀집도 백분위외국인 인구 밀집도 백분위표준 편차 전체 인구 밀집도표준 편차 관내 인구 밀집도표준 편차 외국인 인구 밀집도유동 인구 지수지표 전체 인구 밀집도유동 인구 지수지표 관내 인구 밀집도유동 인구 지수지표 외국인밀집도
02019-01경기도광명시광명2동41210520000.267627.83149.8424.554855041529337.6912114.621632.697765522586.7812052.58716.52129.89100.51227.87
12019-01경기도고양시능곡동412816100012.51151514.4861940.051072.96426319712111.474951.2485.774943222586.7812052.58716.5253.6241.0811.97
22019-01경기도광주시오포읍416102500046.82187794.4599607.081381.371591384010.992127.4529.52830222586.7812052.58716.5217.7617.654.12
32019-01경기도김포시대곶면415703400043.24101994.4438106.174633.91114181222358.8881.27107.172121322586.7812052.58716.5210.447.3114.96
42019-01경기도구리시수택2동41310580000.5921953.439058.45265.047149247437209.215353.31449.158474422586.7812052.58716.52164.74127.3962.69
52019-01경기도김포시월곶면415703500051.9942996.9516766.01964.73337388226827.02322.4918.561312122586.7812052.58716.523.662.682.59
62019-01경기도성남시고등동411316400012.3280958.2414159.58702.031684222986571.291149.3256.983423222586.7812052.58716.5229.099.547.95
72019-01경기도성남시산성동41131600000.5815839.319713.83315.1450848745627309.1616747.98543.347477422586.7812052.58716.52120.91138.9675.83
82019-01경기도성남시시흥동411316500012.95122109.0921909.231001.98723242179429.271691.8377.374227222586.7812052.58716.5241.7514.0410.8
92019-01경기도성남시야탑3동41135640005.1144359.0827806.321229.343302611618680.845441.55240.584046322586.7812052.58716.5238.4345.1533.58
기준년월시도명시군구명행정동명행정동 코드행정동 면적전체 인구수관내 인구수외국인 인구수전체 인구 순위관내 인구 순위외국인 인구 순위전체 인구 밀집도관내 인구 밀집도외국인 밀집도전체 인구 밀집도 백분위관내 인구 밀집도 백분위외국인 인구 밀집도 백분위표준 편차 전체 인구 밀집도표준 편차 관내 인구 밀집도표준 편차 외국인 인구 밀집도유동 인구 지수지표 전체 인구 밀집도유동 인구 지수지표 관내 인구 밀집도유동 인구 지수지표 외국인밀집도
202019-01경기도의정부시의정부2동41150520002.3158164.8333637.67805.6626721727425179.5814561.76348.777071422586.7812052.58716.52111.48120.8248.68
212019-01경기도이천시부발읍415002530041.92172547.1898304.657628.161911104116.112345.05181.972832322586.7812052.58716.5218.2219.4625.4
222019-01경기도파주시운정3동41480570005.87106473.0168212.661047.161094520318138.511620.56178.396064322586.7812052.58716.5280.3196.4224.9
232019-01경기도파주시조리읍414802620027.4292959.3249356.541115.621361111873390.21800.0240.692628222586.7812052.58716.5215.0114.935.68
242019-01경기도파주시진동면414804000043.43591.42386.2147.6556256155113.628.891.111122586.7812052.58716.520.060.070.15
252019-01경기도화성시장안면415903700067.5686959.6537890.012396.32153185601287.15560.8335.471617222586.7812052.58716.525.74.654.95
262019-01경기도하남시감북동414505800013.2286038.6513926.54673.711554273076508.221053.4450.963422222586.7812052.58716.5228.818.747.11
272019-01경기도화성시향남읍415902590050.0243921.75140982.116865.6944124878.432819.64137.313134322586.7812052.58716.5221.623.3919.16
282019-01경기도가평군설악면4182031000141.0276112.2811574.84155.75184468522539.7382.081.194122586.7812052.58716.522.390.680.15
292019-01경기도고양시행신1동41281640000.6725112.8418551.69547.745835636837481.8527689.09817.468591522586.7812052.58716.52165.95229.74114.09