Overview

Dataset statistics

Number of variables11
Number of observations200
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.1 KiB
Average record size in memory97.7 B

Variable types

DateTime1
Numeric6
Categorical4

Alerts

경도값 has constant value ""Constant
측정주소 has constant value ""Constant
위도값 has constant value ""Constant
온도값 is highly overall correlated with 습도값 and 4 other fieldsHigh correlation
습도값 is highly overall correlated with 온도값 and 1 other fieldsHigh correlation
이산화탄소농도값 is highly overall correlated with 온도값 and 3 other fieldsHigh correlation
토양온도값 is highly overall correlated with 온도값 and 3 other fieldsHigh correlation
액상전기전도값 is highly overall correlated with 온도값 and 3 other fieldsHigh correlation
토양수분값 is highly overall correlated with 온도값 and 4 other fieldsHigh correlation
배지전기전도값 is highly imbalanced (54.9%)Imbalance
측정일시 has unique valuesUnique

Reproduction

Analysis started2023-12-10 06:12:46.175965
Analysis finished2023-12-10 06:12:54.667483
Duration8.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

측정일시
Date

UNIQUE 

Distinct200
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum2021-01-01 00:00:00
Maximum2021-01-01 16:35:00
2023-12-10T15:12:54.779239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:55.005419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

온도값
Real number (ℝ)

HIGH CORRELATION 

Distinct161
Distinct (%)80.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.47995
Minimum10.5
Maximum19.85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:12:55.226236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10.5
5-th percentile11.5295
Q112.18
median13.025
Q314.2275
95-th percentile17.7565
Maximum19.85
Range9.35
Interquartile range (IQR)2.0475

Descriptive statistics

Standard deviation1.8607003
Coefficient of variation (CV)0.13803466
Kurtosis1.7380186
Mean13.47995
Median Absolute Deviation (MAD)0.975
Skewness1.3479492
Sum2695.99
Variance3.4622055
MonotonicityNot monotonic
2023-12-10T15:12:55.427923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12.15 3
 
1.5%
12.56 3
 
1.5%
12.18 3
 
1.5%
13.1 2
 
1.0%
14.71 2
 
1.0%
14.53 2
 
1.0%
11.89 2
 
1.0%
12.72 2
 
1.0%
11.67 2
 
1.0%
11.51 2
 
1.0%
Other values (151) 177
88.5%
ValueCountFrequency (%)
10.5 1
0.5%
10.52 1
0.5%
10.58 1
0.5%
10.72 1
0.5%
10.85 1
0.5%
11.17 1
0.5%
11.18 1
0.5%
11.51 2
1.0%
11.52 1
0.5%
11.53 1
0.5%
ValueCountFrequency (%)
19.85 1
0.5%
19.36 1
0.5%
19.22 1
0.5%
19.13 1
0.5%
19.01 1
0.5%
18.8 1
0.5%
18.3 2
1.0%
18.12 1
0.5%
18.07 1
0.5%
17.74 1
0.5%

경도값
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
127.3205
200 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row127.3205
2nd row127.3205
3rd row127.3205
4th row127.3205
5th row127.3205

Common Values

ValueCountFrequency (%)
127.3205 200
100.0%

Length

2023-12-10T15:12:55.623320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:12:55.770701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
127.3205 200
100.0%

습도값
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean84.83
Minimum73
Maximum91
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:12:55.913478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum73
5-th percentile77
Q184
median85
Q386
95-th percentile89
Maximum91
Range18
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.1128038
Coefficient of variation (CV)0.036694611
Kurtosis3.5645424
Mean84.83
Median Absolute Deviation (MAD)1
Skewness-1.4788632
Sum16966
Variance9.6895477
MonotonicityNot monotonic
2023-12-10T15:12:56.082275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
85 61
30.5%
86 58
29.0%
84 18
 
9.0%
83 12
 
6.0%
89 11
 
5.5%
90 6
 
3.0%
87 4
 
2.0%
88 4
 
2.0%
80 4
 
2.0%
79 3
 
1.5%
Other values (8) 19
 
9.5%
ValueCountFrequency (%)
73 1
 
0.5%
74 2
 
1.0%
75 3
 
1.5%
76 3
 
1.5%
77 2
 
1.0%
79 3
 
1.5%
80 4
 
2.0%
81 2
 
1.0%
82 3
 
1.5%
83 12
6.0%
ValueCountFrequency (%)
91 3
 
1.5%
90 6
 
3.0%
89 11
 
5.5%
88 4
 
2.0%
87 4
 
2.0%
86 58
29.0%
85 61
30.5%
84 18
 
9.0%
83 12
 
6.0%
82 3
 
1.5%

이산화탄소농도값
Real number (ℝ)

HIGH CORRELATION 

Distinct93
Distinct (%)46.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean493.05
Minimum385
Maximum572
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:12:56.574865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum385
5-th percentile402
Q1437.75
median520
Q3534
95-th percentile541.2
Maximum572
Range187
Interquartile range (IQR)96.25

Descriptive statistics

Standard deviation52.139815
Coefficient of variation (CV)0.10574955
Kurtosis-1.1597927
Mean493.05
Median Absolute Deviation (MAD)19
Skewness-0.68339972
Sum98610
Variance2718.5603
MonotonicityNot monotonic
2023-12-10T15:12:56.774131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
520 8
 
4.0%
540 8
 
4.0%
533 7
 
3.5%
536 7
 
3.5%
530 6
 
3.0%
537 6
 
3.0%
539 6
 
3.0%
523 6
 
3.0%
541 5
 
2.5%
538 5
 
2.5%
Other values (83) 136
68.0%
ValueCountFrequency (%)
385 1
0.5%
387 1
0.5%
388 1
0.5%
397 1
0.5%
399 1
0.5%
400 2
1.0%
401 2
1.0%
402 2
1.0%
403 1
0.5%
404 1
0.5%
ValueCountFrequency (%)
572 1
 
0.5%
564 1
 
0.5%
561 1
 
0.5%
554 2
 
1.0%
549 1
 
0.5%
548 1
 
0.5%
546 1
 
0.5%
545 2
 
1.0%
541 5
2.5%
540 8
4.0%

토양온도값
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)14.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.2865
Minimum18.9
Maximum25.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:12:56.967090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18.9
5-th percentile19.5
Q119.7
median19.7
Q323.7
95-th percentile25.1
Maximum25.6
Range6.7
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.197593
Coefficient of variation (CV)0.10323881
Kurtosis-1.2115639
Mean21.2865
Median Absolute Deviation (MAD)0.2
Skewness0.74816958
Sum4257.3
Variance4.8294148
MonotonicityNot monotonic
2023-12-10T15:12:57.172236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
19.7 78
39.0%
19.5 33
16.5%
24.4 9
 
4.5%
25.4 8
 
4.0%
24.2 8
 
4.0%
24.7 7
 
3.5%
23.9 6
 
3.0%
25.1 5
 
2.5%
19.9 5
 
2.5%
23.7 5
 
2.5%
Other values (19) 36
18.0%
ValueCountFrequency (%)
18.9 1
 
0.5%
19.1 1
 
0.5%
19.5 33
16.5%
19.7 78
39.0%
19.9 5
 
2.5%
20.1 3
 
1.5%
20.3 2
 
1.0%
20.5 2
 
1.0%
20.9 1
 
0.5%
21.1 1
 
0.5%
ValueCountFrequency (%)
25.6 1
 
0.5%
25.4 8
4.0%
25.1 5
2.5%
24.9 4
2.0%
24.7 7
3.5%
24.4 9
4.5%
24.2 8
4.0%
23.9 6
3.0%
23.7 5
2.5%
23.5 2
 
1.0%

배지전기전도값
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
0.08
153 
0.09
43 
0.07
 
3
0.1
 
1

Length

Max length4
Median length4
Mean length3.995
Min length3

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row0.08
2nd row0.08
3rd row0.08
4th row0.08
5th row0.08

Common Values

ValueCountFrequency (%)
0.08 153
76.5%
0.09 43
 
21.5%
0.07 3
 
1.5%
0.1 1
 
0.5%

Length

2023-12-10T15:12:57.373269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:12:57.542017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.08 153
76.5%
0.09 43
 
21.5%
0.07 3
 
1.5%
0.1 1
 
0.5%

액상전기전도값
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7117
Minimum1.38
Maximum2.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:12:57.735443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.38
5-th percentile1.51
Q11.63
median1.72
Q31.79
95-th percentile1.9
Maximum2.08
Range0.7
Interquartile range (IQR)0.16

Descriptive statistics

Standard deviation0.11665829
Coefficient of variation (CV)0.068153465
Kurtosis0.69554865
Mean1.7117
Median Absolute Deviation (MAD)0.07
Skewness-0.13515345
Sum342.34
Variance0.013609156
MonotonicityNot monotonic
2023-12-10T15:12:58.103083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1.72 25
12.5%
1.74 24
12.0%
1.77 17
 
8.5%
1.79 17
 
8.5%
1.63 13
 
6.5%
1.82 11
 
5.5%
1.61 10
 
5.0%
1.7 10
 
5.0%
1.65 9
 
4.5%
1.59 8
 
4.0%
Other values (22) 56
28.0%
ValueCountFrequency (%)
1.38 1
 
0.5%
1.42 2
1.0%
1.43 2
1.0%
1.45 2
1.0%
1.49 2
1.0%
1.51 4
2.0%
1.52 1
 
0.5%
1.54 2
1.0%
1.55 2
1.0%
1.56 2
1.0%
ValueCountFrequency (%)
2.08 1
 
0.5%
2.02 3
 
1.5%
1.93 1
 
0.5%
1.91 1
 
0.5%
1.9 5
 
2.5%
1.87 5
 
2.5%
1.85 7
3.5%
1.82 11
5.5%
1.79 17
8.5%
1.77 17
8.5%

토양수분값
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.549
Minimum11.6
Maximum14.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:12:58.351946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11.6
5-th percentile11.7
Q112.075
median12.3
Q313.025
95-th percentile13.8
Maximum14.2
Range2.6
Interquartile range (IQR)0.95

Descriptive statistics

Standard deviation0.67593152
Coefficient of variation (CV)0.053863377
Kurtosis-0.60441797
Mean12.549
Median Absolute Deviation (MAD)0.35
Skewness0.78034972
Sum2509.8
Variance0.45688342
MonotonicityNot monotonic
2023-12-10T15:12:58.532964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
12.3 24
12.0%
12.2 23
 
11.5%
12.0 20
 
10.0%
12.1 18
 
9.0%
11.9 11
 
5.5%
12.7 11
 
5.5%
13.3 10
 
5.0%
13.7 10
 
5.0%
11.8 8
 
4.0%
11.7 6
 
3.0%
Other values (17) 59
29.5%
ValueCountFrequency (%)
11.6 5
 
2.5%
11.7 6
 
3.0%
11.8 8
 
4.0%
11.9 11
5.5%
12.0 20
10.0%
12.1 18
9.0%
12.2 23
11.5%
12.3 24
12.0%
12.4 5
 
2.5%
12.5 4
 
2.0%
ValueCountFrequency (%)
14.2 1
 
0.5%
14.1 2
 
1.0%
14.0 3
 
1.5%
13.9 2
 
1.0%
13.8 5
2.5%
13.7 10
5.0%
13.6 5
2.5%
13.5 3
 
1.5%
13.4 5
2.5%
13.3 10
5.0%

측정주소
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
세종특별자치시 연동면 예양리 842-9 10번지
200 

Length

Max length26
Median length26
Mean length26
Min length26

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row세종특별자치시 연동면 예양리 842-9 10번지
2nd row세종특별자치시 연동면 예양리 842-9 10번지
3rd row세종특별자치시 연동면 예양리 842-9 10번지
4th row세종특별자치시 연동면 예양리 842-9 10번지
5th row세종특별자치시 연동면 예양리 842-9 10번지

Common Values

ValueCountFrequency (%)
세종특별자치시 연동면 예양리 842-9 10번지 200
100.0%

Length

2023-12-10T15:12:58.702310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:12:58.832174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
세종특별자치시 200
20.0%
연동면 200
20.0%
예양리 200
20.0%
842-9 200
20.0%
10번지 200
20.0%

위도값
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
36.5719
200 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row36.5719
2nd row36.5719
3rd row36.5719
4th row36.5719
5th row36.5719

Common Values

ValueCountFrequency (%)
36.5719 200
100.0%

Length

2023-12-10T15:12:58.991940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:12:59.147573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
36.5719 200
100.0%

Interactions

2023-12-10T15:12:53.218698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:47.276966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:48.856456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:49.785931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:50.849526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:51.998644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:53.356063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:47.511474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:48.991726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:49.938060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:50.998283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:52.232934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:53.510200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:48.323314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:49.130832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:50.134357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:51.203316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:52.484877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:53.738786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:48.461106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:49.276037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:50.310600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:51.374208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:52.712755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:53.987855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:48.578382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:49.426676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:50.515794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:51.599999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:52.889933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:54.136533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:48.725641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:49.598137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:50.684858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:51.800847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:12:53.073785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:12:59.260462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
온도값습도값이산화탄소농도값토양온도값배지전기전도값액상전기전도값토양수분값
온도값1.0000.9390.8280.8540.4770.4640.720
습도값0.9391.0000.8140.8480.6080.3250.745
이산화탄소농도값0.8280.8141.0000.9070.5640.5100.760
토양온도값0.8540.8480.9071.0000.7020.5360.810
배지전기전도값0.4770.6080.5640.7021.0000.5130.632
액상전기전도값0.4640.3250.5100.5360.5131.0000.809
토양수분값0.7200.7450.7600.8100.6320.8091.000
2023-12-10T15:12:59.460140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
온도값습도값이산화탄소농도값토양온도값액상전기전도값토양수분값배지전기전도값
온도값1.000-0.652-0.8270.610-0.6730.7210.299
습도값-0.6521.0000.485-0.3240.422-0.5630.405
이산화탄소농도값-0.8270.4851.000-0.7390.707-0.7170.362
토양온도값0.610-0.324-0.7391.000-0.7060.7420.497
액상전기전도값-0.6730.4220.707-0.7061.000-0.8990.361
토양수분값0.721-0.563-0.7170.742-0.8991.0000.427
배지전기전도값0.2990.4050.3620.4970.3610.4271.000

Missing values

2023-12-10T15:12:54.330977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:12:54.570893image/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

측정일시온도값경도값습도값이산화탄소농도값토양온도값배지전기전도값액상전기전도값토양수분값측정주소위도값
02021-01-01 0:0013.1127.32058553019.50.081.7712.1세종특별자치시 연동면 예양리 842-9 10번지36.5719
12021-01-01 0:0513.16127.32058554019.50.081.7212.3세종특별자치시 연동면 예양리 842-9 10번지36.5719
22021-01-01 0:1013.19127.32058553319.50.081.7712.1세종특별자치시 연동면 예양리 842-9 10번지36.5719
32021-01-01 0:1513.27127.32058552319.50.081.7212.3세종특별자치시 연동면 예양리 842-9 10번지36.5719
42021-01-01 0:2013.29127.32058551719.70.081.7912.0세종특별자치시 연동면 예양리 842-9 10번지36.5719
52021-01-01 0:2513.36127.32058553819.50.081.7912.0세종특별자치시 연동면 예양리 842-9 10번지36.5719
62021-01-01 0:3013.45127.32058552719.50.081.7412.2세종특별자치시 연동면 예양리 842-9 10번지36.5719
72021-01-01 0:3513.55127.32058551719.70.081.7712.1세종특별자치시 연동면 예양리 842-9 10번지36.5719
82021-01-01 0:4013.51127.32058552019.50.092.0212.0세종특별자치시 연동면 예양리 842-9 10번지36.5719
92021-01-01 0:4513.46127.32058552819.50.081.7412.2세종특별자치시 연동면 예양리 842-9 10번지36.5719
측정일시온도값경도값습도값이산화탄소농도값토양온도값배지전기전도값액상전기전도값토양수분값측정주소위도값
1902021-01-01 15:5014.0127.32058944023.70.081.6312.7세종특별자치시 연동면 예양리 842-9 10번지36.5719
1912021-01-01 15:5514.15127.32059043723.50.081.7212.3세종특별자치시 연동면 예양리 842-9 10번지36.5719
1922021-01-01 16:0014.21127.32059043023.30.081.6312.7세종특별자치시 연동면 예양리 842-9 10번지36.5719
1932021-01-01 16:0513.95127.32058942523.30.081.6112.8세종특별자치시 연동면 예양리 842-9 10번지36.5719
1942021-01-01 16:1013.98127.32059042223.00.081.6712.5세종특별자치시 연동면 예양리 842-9 10번지36.5719
1952021-01-01 16:1514.19127.32059044723.00.081.6512.6세종특별자치시 연동면 예양리 842-9 10번지36.5719
1962021-01-01 16:2014.08127.32059145322.80.081.6312.7세종특별자치시 연동면 예양리 842-9 10번지36.5719
1972021-01-01 16:2513.91127.32059043922.60.081.6312.7세종특별자치시 연동면 예양리 842-9 10번지36.5719
1982021-01-01 16:3014.2127.32059144422.60.081.7712.1세종특별자치시 연동면 예양리 842-9 10번지36.5719
1992021-01-01 16:3514.04127.32059144222.60.081.6712.5세종특별자치시 연동면 예양리 842-9 10번지36.5719