Overview

Dataset statistics

Number of variables8
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.0 KiB
Average record size in memory71.3 B

Variable types

Categorical2
Numeric6

Alerts

관측소명 is highly overall correlated with 당년 누적 강우량(mm) and 2 other fieldsHigh correlation
댐명 is highly overall correlated with 당년 누적 강우량(mm) and 2 other fieldsHigh correlation
관측일 is highly overall correlated with 전년 누적 강우량(mm) and 1 other fieldsHigh correlation
당년 누적 강우량(mm) is highly overall correlated with 전년 누적 강우량(mm) and 2 other fieldsHigh correlation
전년 누적 강우량(mm) is highly overall correlated with 관측일 and 4 other fieldsHigh correlation
예년 평균 누적 강우량(mm) is highly overall correlated with 관측일 and 1 other fieldsHigh correlation
강우량(mm) has 91 (91.0%) zerosZeros
전년 강우량(mm) has 91 (91.0%) zerosZeros
당년 누적 강우량(mm) has 53 (53.0%) zerosZeros
전년 누적 강우량(mm) has 36 (36.0%) zerosZeros
예년 평균 누적 강우량(mm) has 8 (8.0%) zerosZeros

Reproduction

Analysis started2023-12-10 14:00:20.542924
Analysis finished2023-12-10 14:00:27.450021
Duration6.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

댐명
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
광동
17 
괴산
17 
구천
17 
군위
17 
군남
16 
Other values (2)
16 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
광동 17
17.0%
괴산 17
17.0%
구천 17
17.0%
군위 17
17.0%
군남 16
16.0%
감포 15
15.0%
남강 1
 
1.0%

Length

2023-12-10T23:00:27.554451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:00:27.830358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광동 17
17.0%
괴산 17
17.0%
구천 17
17.0%
군위 17
17.0%
군남 16
16.0%
감포 15
15.0%
남강 1
 
1.0%

관측소명
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
거제시(구천댐)
17 
경주시(감포댐)
15 
군위군(군위댐)
12 
연천군(군남댐)
10 
태백시(상사미동)
9 
Other values (6)
37 

Length

Max length9
Median length8
Mean length7.93
Min length6

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row경주시(감포댐)
2nd row경주시(감포댐)
3rd row경주시(감포댐)
4th row경주시(감포댐)
5th row경주시(감포댐)

Common Values

ValueCountFrequency (%)
거제시(구천댐) 17
17.0%
경주시(감포댐) 15
15.0%
군위군(군위댐) 12
12.0%
연천군(군남댐) 10
10.0%
태백시(상사미동) 9
9.0%
괴산댐(FTP) 9
9.0%
삼척시(광동댐) 8
8.0%
내속리(전) 8
8.0%
연천군(횡산리) 6
 
6.0%
군위군(양지리) 5
 
5.0%

Length

2023-12-10T23:00:28.058139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
거제시(구천댐 17
17.0%
경주시(감포댐 15
15.0%
군위군(군위댐 12
12.0%
연천군(군남댐 10
10.0%
태백시(상사미동 9
9.0%
괴산댐(ftp 9
9.0%
삼척시(광동댐 8
8.0%
내속리(전 8
8.0%
연천군(횡산리 6
 
6.0%
군위군(양지리 5
 
5.0%

관측일
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20190118
Minimum20190102
Maximum20190131
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T23:00:28.242731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20190102
5-th percentile20190102
Q120190110
median20190118
Q320190127
95-th percentile20190131
Maximum20190131
Range29
Interquartile range (IQR)17

Descriptive statistics

Standard deviation9.5641587
Coefficient of variation (CV)4.7370494 × 10-7
Kurtosis-1.3814445
Mean20190118
Median Absolute Deviation (MAD)8.5
Skewness-0.19619979
Sum2.0190118 × 109
Variance91.473131
MonotonicityNot monotonic
2023-12-10T23:00:28.450505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
20190131 7
 
7.0%
20190106 6
 
6.0%
20190112 6
 
6.0%
20190114 6
 
6.0%
20190102 6
 
6.0%
20190108 6
 
6.0%
20190127 6
 
6.0%
20190110 6
 
6.0%
20190126 6
 
6.0%
20190104 6
 
6.0%
Other values (11) 39
39.0%
ValueCountFrequency (%)
20190102 6
6.0%
20190104 6
6.0%
20190106 6
6.0%
20190108 6
6.0%
20190110 6
6.0%
20190112 6
6.0%
20190114 6
6.0%
20190116 2
 
2.0%
20190117 3
3.0%
20190118 3
3.0%
ValueCountFrequency (%)
20190131 7
7.0%
20190130 5
5.0%
20190129 4
4.0%
20190128 6
6.0%
20190127 6
6.0%
20190126 6
6.0%
20190124 6
6.0%
20190122 4
4.0%
20190121 3
3.0%
20190120 2
 
2.0%

강우량(mm)
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.555
Minimum0
Maximum15
Zeros91
Zeros (%)91.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T23:00:28.633761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4
Maximum15
Range15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.239335
Coefficient of variation (CV)4.0348378
Kurtosis24.480839
Mean0.555
Median Absolute Deviation (MAD)0
Skewness4.8109686
Sum55.5
Variance5.0146212
MonotonicityNot monotonic
2023-12-10T23:00:28.779220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.0 91
91.0%
4.0 2
 
2.0%
6.0 1
 
1.0%
0.5 1
 
1.0%
10.0 1
 
1.0%
2.0 1
 
1.0%
15.0 1
 
1.0%
3.0 1
 
1.0%
11.0 1
 
1.0%
ValueCountFrequency (%)
0.0 91
91.0%
0.5 1
 
1.0%
2.0 1
 
1.0%
3.0 1
 
1.0%
4.0 2
 
2.0%
6.0 1
 
1.0%
10.0 1
 
1.0%
11.0 1
 
1.0%
15.0 1
 
1.0%
ValueCountFrequency (%)
15.0 1
 
1.0%
11.0 1
 
1.0%
10.0 1
 
1.0%
6.0 1
 
1.0%
4.0 2
 
2.0%
3.0 1
 
1.0%
2.0 1
 
1.0%
0.5 1
 
1.0%
0.0 91
91.0%

전년 강우량(mm)
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.395
Minimum0
Maximum11
Zeros91
Zeros (%)91.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T23:00:28.939337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3.05
Maximum11
Range11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.5362538
Coefficient of variation (CV)3.8892501
Kurtosis26.803229
Mean0.395
Median Absolute Deviation (MAD)0
Skewness4.8756964
Sum39.5
Variance2.3600758
MonotonicityNot monotonic
2023-12-10T23:00:29.092447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.0 91
91.0%
2.0 2
 
2.0%
4.5 1
 
1.0%
1.0 1
 
1.0%
3.0 1
 
1.0%
7.0 1
 
1.0%
4.0 1
 
1.0%
5.0 1
 
1.0%
11.0 1
 
1.0%
ValueCountFrequency (%)
0.0 91
91.0%
1.0 1
 
1.0%
2.0 2
 
2.0%
3.0 1
 
1.0%
4.0 1
 
1.0%
4.5 1
 
1.0%
5.0 1
 
1.0%
7.0 1
 
1.0%
11.0 1
 
1.0%
ValueCountFrequency (%)
11.0 1
 
1.0%
7.0 1
 
1.0%
5.0 1
 
1.0%
4.5 1
 
1.0%
4.0 1
 
1.0%
3.0 1
 
1.0%
2.0 2
 
2.0%
1.0 1
 
1.0%
0.0 91
91.0%

당년 누적 강우량(mm)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.52
Minimum0
Maximum17
Zeros53
Zeros (%)53.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T23:00:29.241854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile10.5
Maximum17
Range17
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.7537321
Coefficient of variation (CV)1.4895762
Kurtosis3.447887
Mean2.52
Median Absolute Deviation (MAD)0
Skewness1.8905096
Sum252
Variance14.090505
MonotonicityNot monotonic
2023-12-10T23:00:29.556401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.0 53
53.0%
3.0 17
 
17.0%
4.0 8
 
8.0%
10.5 7
 
7.0%
2.0 6
 
6.0%
5.0 3
 
3.0%
10.0 2
 
2.0%
16.5 1
 
1.0%
6.0 1
 
1.0%
9.0 1
 
1.0%
ValueCountFrequency (%)
0.0 53
53.0%
2.0 6
 
6.0%
3.0 17
 
17.0%
4.0 8
 
8.0%
5.0 3
 
3.0%
6.0 1
 
1.0%
9.0 1
 
1.0%
10.0 2
 
2.0%
10.5 7
 
7.0%
16.5 1
 
1.0%
ValueCountFrequency (%)
17.0 1
 
1.0%
16.5 1
 
1.0%
10.5 7
7.0%
10.0 2
 
2.0%
9.0 1
 
1.0%
6.0 1
 
1.0%
5.0 3
 
3.0%
4.0 8
8.0%
3.0 17
17.0%
2.0 6
 
6.0%

전년 누적 강우량(mm)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.875
Minimum0
Maximum40
Zeros36
Zeros (%)36.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T23:00:29.794933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4.5
Q318
95-th percentile40
Maximum40
Range40
Interquartile range (IQR)18

Descriptive statistics

Standard deviation13.597641
Coefficient of variation (CV)1.2503578
Kurtosis-0.20591932
Mean10.875
Median Absolute Deviation (MAD)4.5
Skewness1.0910966
Sum1087.5
Variance184.89583
MonotonicityNot monotonic
2023-12-10T23:00:29.994671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0.0 36
36.0%
40.0 10
 
10.0%
31.0 8
 
8.0%
18.0 7
 
7.0%
3.0 6
 
6.0%
6.0 5
 
5.0%
19.0 5
 
5.0%
5.5 4
 
4.0%
4.0 4
 
4.0%
7.0 3
 
3.0%
Other values (7) 12
 
12.0%
ValueCountFrequency (%)
0.0 36
36.0%
1.0 3
 
3.0%
2.0 1
 
1.0%
3.0 6
 
6.0%
4.0 4
 
4.0%
5.0 2
 
2.0%
5.5 4
 
4.0%
6.0 5
 
5.0%
7.0 3
 
3.0%
7.5 1
 
1.0%
ValueCountFrequency (%)
40.0 10
10.0%
31.0 8
8.0%
27.0 1
 
1.0%
19.0 5
5.0%
18.0 7
7.0%
16.0 2
 
2.0%
15.0 2
 
2.0%
7.5 1
 
1.0%
7.0 3
 
3.0%
6.0 5
5.0%

예년 평균 누적 강우량(mm)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct73
Distinct (%)73.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.22
Minimum0
Maximum55.7
Zeros8
Zeros (%)8.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T23:00:30.218730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.375
median5.1
Q315.95
95-th percentile34.155
Maximum55.7
Range55.7
Interquartile range (IQR)14.575

Descriptive statistics

Standard deviation12.262573
Coefficient of variation (CV)1.1998604
Kurtosis2.9481766
Mean10.22
Median Absolute Deviation (MAD)4.65
Skewness1.7263146
Sum1022
Variance150.37071
MonotonicityNot monotonic
2023-12-10T23:00:30.420186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 8
 
8.0%
0.4 4
 
4.0%
3.1 3
 
3.0%
4.6 3
 
3.0%
1.1 3
 
3.0%
0.5 2
 
2.0%
1.0 2
 
2.0%
18.1 2
 
2.0%
1.9 2
 
2.0%
4.0 2
 
2.0%
Other values (63) 69
69.0%
ValueCountFrequency (%)
0.0 8
8.0%
0.1 2
 
2.0%
0.3 1
 
1.0%
0.4 4
4.0%
0.5 2
 
2.0%
1.0 2
 
2.0%
1.1 3
 
3.0%
1.2 1
 
1.0%
1.3 2
 
2.0%
1.4 1
 
1.0%
ValueCountFrequency (%)
55.7 1
1.0%
52.5 1
1.0%
47.6 1
1.0%
44.3 1
1.0%
37.1 1
1.0%
34.0 1
1.0%
31.7 1
1.0%
31.2 1
1.0%
27.3 1
1.0%
26.1 1
1.0%

Interactions

2023-12-10T23:00:25.801712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:20.951467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:21.634392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:22.981529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:23.838195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:24.788938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:25.933768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:21.049913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:21.762631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:23.131837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:23.995241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:24.961169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:26.074860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:21.155158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:21.908693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:23.284645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:24.171689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:25.108203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:26.309134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:21.240705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:22.047639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:23.423218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:24.327749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:25.260643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:26.640098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:21.368497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:22.252680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:23.571858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:24.476865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:25.418044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:26.885510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:21.516040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:22.840194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:23.708750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:24.648705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:25.609275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:00:30.630869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
댐명관측소명관측일강우량(mm)전년 강우량(mm)당년 누적 강우량(mm)전년 누적 강우량(mm)예년 평균 누적 강우량(mm)
댐명1.0001.0000.0000.8070.0000.9180.9420.518
관측소명1.0001.0000.0000.6270.0000.7960.8860.609
관측일0.0000.0001.0000.3060.1600.3150.2900.469
강우량(mm)0.8070.6270.3061.0000.0000.9350.8330.386
전년 강우량(mm)0.0000.0000.1600.0001.0000.0000.0000.372
당년 누적 강우량(mm)0.9180.7960.3150.9350.0001.0000.9380.688
전년 누적 강우량(mm)0.9420.8860.2900.8330.0000.9381.0000.722
예년 평균 누적 강우량(mm)0.5180.6090.4690.3860.3720.6880.7221.000
2023-12-10T23:00:30.842704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관측소명댐명
관측소명1.0000.978
댐명0.9781.000
2023-12-10T23:00:31.059287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관측일강우량(mm)전년 강우량(mm)당년 누적 강우량(mm)전년 누적 강우량(mm)예년 평균 누적 강우량(mm)댐명관측소명
관측일1.0000.155-0.0970.4870.6850.7460.0000.000
강우량(mm)0.1551.000-0.0990.4140.1580.1280.4080.364
전년 강우량(mm)-0.097-0.0991.000-0.0720.0810.0700.0000.000
당년 누적 강우량(mm)0.4870.414-0.0721.0000.6650.4980.5750.545
전년 누적 강우량(mm)0.6850.1580.0810.6651.0000.8350.6320.673
예년 평균 누적 강우량(mm)0.7460.1280.0700.4980.8351.0000.2880.309
댐명0.0000.4080.0000.5750.6320.2881.0000.978
관측소명0.0000.3640.0000.5450.6730.3090.9781.000

Missing values

2023-12-10T23:00:27.131659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:00:27.356377image/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.

Sample

댐명관측소명관측일강우량(mm)전년 강우량(mm)당년 누적 강우량(mm)전년 누적 강우량(mm)예년 평균 누적 강우량(mm)
0감포경주시(감포댐)201901316.00.016.531.031.7
1감포경주시(감포댐)201901080.04.50.05.54.0
2감포경주시(감포댐)201901280.00.010.531.027.3
3감포경주시(감포댐)201901240.00.010.531.024.7
4감포경주시(감포댐)201901200.50.010.531.018.1
5감포경주시(감포댐)201901040.00.00.00.01.9
6감포경주시(감포댐)201901260.00.010.531.025.3
7감포경주시(감포댐)201901060.00.00.00.03.3
8감포경주시(감포댐)201901270.00.010.531.026.1
9감포경주시(감포댐)201901300.00.010.531.031.2
댐명관측소명관측일강우량(mm)전년 강우량(mm)당년 누적 강우량(mm)전년 누적 강우량(mm)예년 평균 누적 강우량(mm)
90군위군위군(양지리)201901100.00.00.00.00.5
91군위군위군(양지리)201901160.05.05.05.01.9
92군위군위군(군위댐)201901290.00.04.018.08.4
93군위군위군(군위댐)201901280.00.04.018.07.2
94군위군위군(군위댐)201901270.00.04.018.07.1
95군위군위군(군위댐)201901180.00.04.018.03.1
96군위군위군(양지리)201901190.00.05.015.02.4
97군위군위군(군위댐)201901170.011.04.018.03.1
98군위군위군(군위댐)201901260.00.04.018.06.8
99남강함양군(의탄리)2019013111.00.017.027.011.9