Overview

Dataset statistics

Number of variables12
Number of observations8760
Missing cells1195
Missing cells (%)1.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory924.0 KiB
Average record size in memory108.0 B

Variable types

Numeric12

Dataset

Description한국농어촌공사 새만금유역 가력도 수위계측정보에 대한 데이터로 해수, 담수의 수위정보를 일별, 분단위 등의 항목을 제공합니다.
Author한국농어촌공사
URLhttps://www.data.go.kr/data/15052514/fileData.do

Alerts

00분 is highly overall correlated with 10분 and 7 other fieldsHigh correlation
10분 is highly overall correlated with 00분 and 7 other fieldsHigh correlation
20분 is highly overall correlated with 00분 and 7 other fieldsHigh correlation
30분 is highly overall correlated with 00분 and 7 other fieldsHigh correlation
40분 is highly overall correlated with 00분 and 7 other fieldsHigh correlation
50분 is highly overall correlated with 00분 and 7 other fieldsHigh correlation
시간최소 is highly overall correlated with 00분 and 7 other fieldsHigh correlation
시간최대 is highly overall correlated with 00분 and 7 other fieldsHigh correlation
시간평균 is highly overall correlated with 00분 and 7 other fieldsHigh correlation
00분 has 134 (1.5%) missing valuesMissing
10분 has 136 (1.6%) missing valuesMissing
20분 has 138 (1.6%) missing valuesMissing
30분 has 136 (1.6%) missing valuesMissing
40분 has 136 (1.6%) missing valuesMissing
50분 has 134 (1.5%) missing valuesMissing
시간최소 has 127 (1.4%) missing valuesMissing
시간최대 has 127 (1.4%) missing valuesMissing
시간평균 has 127 (1.4%) missing valuesMissing
시간 has 365 (4.2%) zerosZeros

Reproduction

Analysis started2024-03-14 15:22:03.357607
Analysis finished2024-03-14 15:22:41.264442
Duration37.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables


Real number (ℝ)

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.5260274
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size77.1 KiB
2024-03-15T00:22:41.359259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q310
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.4480481
Coefficient of variation (CV)0.5283533
Kurtosis-1.207056
Mean6.5260274
Median Absolute Deviation (MAD)3
Skewness-0.010458195
Sum57168
Variance11.889036
MonotonicityIncreasing
2024-03-15T00:22:41.553905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 744
8.5%
3 744
8.5%
5 744
8.5%
7 744
8.5%
8 744
8.5%
10 744
8.5%
12 744
8.5%
4 720
8.2%
6 720
8.2%
9 720
8.2%
Other values (2) 1392
15.9%
ValueCountFrequency (%)
1 744
8.5%
2 672
7.7%
3 744
8.5%
4 720
8.2%
5 744
8.5%
6 720
8.2%
7 744
8.5%
8 744
8.5%
9 720
8.2%
10 744
8.5%
ValueCountFrequency (%)
12 744
8.5%
11 720
8.2%
10 744
8.5%
9 720
8.2%
8 744
8.5%
7 744
8.5%
6 720
8.2%
5 744
8.5%
4 720
8.2%
3 744
8.5%


Real number (ℝ)

Distinct31
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.720548
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size77.1 KiB
2024-03-15T00:22:41.799953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18
median16
Q323
95-th percentile29
Maximum31
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.7967491
Coefficient of variation (CV)0.55957013
Kurtosis-1.1931508
Mean15.720548
Median Absolute Deviation (MAD)8
Skewness0.0075224375
Sum137712
Variance77.382795
MonotonicityNot monotonic
2024-03-15T00:22:42.040585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 288
 
3.3%
16 288
 
3.3%
28 288
 
3.3%
27 288
 
3.3%
26 288
 
3.3%
25 288
 
3.3%
24 288
 
3.3%
23 288
 
3.3%
22 288
 
3.3%
21 288
 
3.3%
Other values (21) 5880
67.1%
ValueCountFrequency (%)
1 288
3.3%
2 288
3.3%
3 288
3.3%
4 288
3.3%
5 288
3.3%
6 288
3.3%
7 288
3.3%
8 288
3.3%
9 288
3.3%
10 288
3.3%
ValueCountFrequency (%)
31 168
1.9%
30 264
3.0%
29 264
3.0%
28 288
3.3%
27 288
3.3%
26 288
3.3%
25 288
3.3%
24 288
3.3%
23 288
3.3%
22 288
3.3%

시간
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.5
Minimum0
Maximum23
Zeros365
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size77.1 KiB
2024-03-15T00:22:42.365845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q15.75
median11.5
Q317.25
95-th percentile22
Maximum23
Range23
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation6.9225817
Coefficient of variation (CV)0.60196363
Kurtosis-1.2041763
Mean11.5
Median Absolute Deviation (MAD)6
Skewness0
Sum100740
Variance47.922137
MonotonicityNot monotonic
2024-03-15T00:22:42.575584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 365
 
4.2%
13 365
 
4.2%
23 365
 
4.2%
22 365
 
4.2%
21 365
 
4.2%
20 365
 
4.2%
19 365
 
4.2%
18 365
 
4.2%
17 365
 
4.2%
16 365
 
4.2%
Other values (14) 5110
58.3%
ValueCountFrequency (%)
0 365
4.2%
1 365
4.2%
2 365
4.2%
3 365
4.2%
4 365
4.2%
5 365
4.2%
6 365
4.2%
7 365
4.2%
8 365
4.2%
9 365
4.2%
ValueCountFrequency (%)
23 365
4.2%
22 365
4.2%
21 365
4.2%
20 365
4.2%
19 365
4.2%
18 365
4.2%
17 365
4.2%
16 365
4.2%
15 365
4.2%
14 365
4.2%

00분
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1213
Distinct (%)14.1%
Missing134
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean-1.5979774
Minimum-3.87
Maximum3.532
Zeros0
Zeros (%)0.0%
Negative8614
Negative (%)98.3%
Memory size77.1 KiB
2024-03-15T00:22:42.857679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-3.87
5-th percentile-1.944
Q1-1.735
median-1.589
Q3-1.517
95-th percentile-1.149
Maximum3.532
Range7.402
Interquartile range (IQR)0.218

Descriptive statistics

Standard deviation0.25909699
Coefficient of variation (CV)-0.16214058
Kurtosis26.222524
Mean-1.5979774
Median Absolute Deviation (MAD)0.095
Skewness2.3169646
Sum-13784.153
Variance0.067131249
MonotonicityNot monotonic
2024-03-15T00:22:43.110199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1.604 46
 
0.5%
-1.549 46
 
0.5%
-1.58 45
 
0.5%
-1.544 45
 
0.5%
-1.524 43
 
0.5%
-1.526 43
 
0.5%
-1.531 42
 
0.5%
-1.583 42
 
0.5%
-1.612 41
 
0.5%
-1.56 41
 
0.5%
Other values (1203) 8192
93.5%
(Missing) 134
 
1.5%
ValueCountFrequency (%)
-3.87 1
< 0.1%
-3.179 1
< 0.1%
-2.489 1
< 0.1%
-2.301 1
< 0.1%
-2.3 1
< 0.1%
-2.256 1
< 0.1%
-2.25 1
< 0.1%
-2.231 1
< 0.1%
-2.199 1
< 0.1%
-2.175 1
< 0.1%
ValueCountFrequency (%)
3.532 1
< 0.1%
1.263 1
< 0.1%
0.447 1
< 0.1%
0.342 1
< 0.1%
0.22 1
< 0.1%
0.17 1
< 0.1%
0.097 1
< 0.1%
0.079 1
< 0.1%
0.076 1
< 0.1%
0.075 1
< 0.1%

10분
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1250
Distinct (%)14.5%
Missing136
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean-1.5990363
Minimum-3.87
Maximum1.211
Zeros0
Zeros (%)0.0%
Negative8612
Negative (%)98.3%
Memory size77.1 KiB
2024-03-15T00:22:43.404246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-3.87
5-th percentile-1.947
Q1-1.73425
median-1.59
Q3-1.517
95-th percentile-1.14315
Maximum1.211
Range5.081
Interquartile range (IQR)0.21725

Descriptive statistics

Standard deviation0.25560557
Coefficient of variation (CV)-0.15984976
Kurtosis9.4209487
Mean-1.5990363
Median Absolute Deviation (MAD)0.094
Skewness1.4601481
Sum-13790.089
Variance0.065334207
MonotonicityNot monotonic
2024-03-15T00:22:43.719656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1.605 49
 
0.6%
-1.517 47
 
0.5%
-1.518 46
 
0.5%
-1.562 46
 
0.5%
-1.548 41
 
0.5%
-1.607 41
 
0.5%
-1.61 39
 
0.4%
-1.515 39
 
0.4%
-1.549 39
 
0.4%
-1.54 39
 
0.4%
Other values (1240) 8198
93.6%
(Missing) 136
 
1.6%
ValueCountFrequency (%)
-3.87 1
< 0.1%
-3.086 1
< 0.1%
-2.957 1
< 0.1%
-2.73 1
< 0.1%
-2.698 1
< 0.1%
-2.695 1
< 0.1%
-2.584 1
< 0.1%
-2.522 1
< 0.1%
-2.497 1
< 0.1%
-2.491 1
< 0.1%
ValueCountFrequency (%)
1.211 1
< 0.1%
0.355 1
< 0.1%
0.314 1
< 0.1%
0.304 1
< 0.1%
0.204 1
< 0.1%
0.18 1
< 0.1%
0.111 1
< 0.1%
0.089 1
< 0.1%
0.068 1
< 0.1%
0.05 1
< 0.1%

20분
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1222
Distinct (%)14.2%
Missing138
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean-1.5990552
Minimum-3.259
Maximum0.269
Zeros0
Zeros (%)0.0%
Negative8613
Negative (%)98.3%
Memory size77.1 KiB
2024-03-15T00:22:43.964298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-3.259
5-th percentile-1.946
Q1-1.733
median-1.5895
Q3-1.517
95-th percentile-1.145
Maximum0.269
Range3.528
Interquartile range (IQR)0.216

Descriptive statistics

Standard deviation0.25021439
Coefficient of variation (CV)-0.15647639
Kurtosis7.0888762
Mean-1.5990552
Median Absolute Deviation (MAD)0.0935
Skewness1.4251644
Sum-13787.054
Variance0.062607241
MonotonicityNot monotonic
2024-03-15T00:22:44.210942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1.546 42
 
0.5%
-1.611 41
 
0.5%
-1.61 41
 
0.5%
-1.519 40
 
0.5%
-1.6 40
 
0.5%
-1.608 40
 
0.5%
-1.549 40
 
0.5%
-1.555 40
 
0.5%
-1.547 40
 
0.5%
-1.522 39
 
0.4%
Other values (1212) 8219
93.8%
(Missing) 138
 
1.6%
ValueCountFrequency (%)
-3.259 1
< 0.1%
-2.694 1
< 0.1%
-2.684 1
< 0.1%
-2.586 1
< 0.1%
-2.519 1
< 0.1%
-2.451 1
< 0.1%
-2.306 1
< 0.1%
-2.297 1
< 0.1%
-2.294 1
< 0.1%
-2.256 1
< 0.1%
ValueCountFrequency (%)
0.269 1
< 0.1%
0.201 1
< 0.1%
0.167 1
< 0.1%
0.122 1
< 0.1%
0.106 1
< 0.1%
0.053 1
< 0.1%
0.045 1
< 0.1%
0.038 1
< 0.1%
0.023 1
< 0.1%
-0.014 1
< 0.1%

30분
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1230
Distinct (%)14.3%
Missing136
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean-1.5990904
Minimum-2.524
Maximum0.211
Zeros0
Zeros (%)0.0%
Negative8616
Negative (%)98.4%
Memory size77.1 KiB
2024-03-15T00:22:44.709893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2.524
5-th percentile-1.945
Q1-1.732
median-1.589
Q3-1.518
95-th percentile-1.149
Maximum0.211
Range2.735
Interquartile range (IQR)0.214

Descriptive statistics

Standard deviation0.24756102
Coefficient of variation (CV)-0.15481364
Kurtosis6.5982373
Mean-1.5990904
Median Absolute Deviation (MAD)0.094
Skewness1.4339949
Sum-13790.556
Variance0.061286458
MonotonicityNot monotonic
2024-03-15T00:22:45.132133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1.518 46
 
0.5%
-1.602 44
 
0.5%
-1.577 44
 
0.5%
-1.546 43
 
0.5%
-1.527 42
 
0.5%
-1.605 42
 
0.5%
-1.534 41
 
0.5%
-1.531 41
 
0.5%
-1.583 41
 
0.5%
-1.524 41
 
0.5%
Other values (1220) 8199
93.6%
(Missing) 136
 
1.6%
ValueCountFrequency (%)
-2.524 1
< 0.1%
-2.493 1
< 0.1%
-2.438 1
< 0.1%
-2.429 1
< 0.1%
-2.358 1
< 0.1%
-2.307 1
< 0.1%
-2.295 1
< 0.1%
-2.29 1
< 0.1%
-2.249 1
< 0.1%
-2.208 1
< 0.1%
ValueCountFrequency (%)
0.211 1
< 0.1%
0.149 1
< 0.1%
0.126 1
< 0.1%
0.119 1
< 0.1%
0.055 1
< 0.1%
0.053 1
< 0.1%
0.038 1
< 0.1%
0.011 1
< 0.1%
-0.008 1
< 0.1%
-0.029 1
< 0.1%

40분
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1236
Distinct (%)14.3%
Missing136
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean-1.5982222
Minimum-2.703
Maximum3.939
Zeros0
Zeros (%)0.0%
Negative8614
Negative (%)98.3%
Memory size77.1 KiB
2024-03-15T00:22:45.541450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2.703
5-th percentile-1.94585
Q1-1.733
median-1.589
Q3-1.517
95-th percentile-1.15115
Maximum3.939
Range6.642
Interquartile range (IQR)0.216

Descriptive statistics

Standard deviation0.25662167
Coefficient of variation (CV)-0.16056696
Kurtosis31.441104
Mean-1.5982222
Median Absolute Deviation (MAD)0.096
Skewness2.5467016
Sum-13783.068
Variance0.065854684
MonotonicityNot monotonic
2024-03-15T00:22:45.992586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1.512 44
 
0.5%
-1.59 43
 
0.5%
-1.608 43
 
0.5%
-1.61 43
 
0.5%
-1.553 42
 
0.5%
-1.611 41
 
0.5%
-1.533 40
 
0.5%
-1.518 39
 
0.4%
-1.541 39
 
0.4%
-1.612 39
 
0.4%
Other values (1226) 8211
93.7%
(Missing) 136
 
1.6%
ValueCountFrequency (%)
-2.703 1
< 0.1%
-2.515 1
< 0.1%
-2.275 1
< 0.1%
-2.252 1
< 0.1%
-2.24 1
< 0.1%
-2.228 1
< 0.1%
-2.224 1
< 0.1%
-2.217 1
< 0.1%
-2.216 1
< 0.1%
-2.213 1
< 0.1%
ValueCountFrequency (%)
3.939 1
< 0.1%
0.814 1
< 0.1%
0.218 1
< 0.1%
0.131 1
< 0.1%
0.118 1
< 0.1%
0.113 1
< 0.1%
0.065 2
< 0.1%
0.012 1
< 0.1%
0.007 1
< 0.1%
-0.002 1
< 0.1%

50분
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1234
Distinct (%)14.3%
Missing134
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean-1.5978763
Minimum-2.685
Maximum0.893
Zeros0
Zeros (%)0.0%
Negative8617
Negative (%)98.4%
Memory size77.1 KiB
2024-03-15T00:22:46.417665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2.685
5-th percentile-1.944
Q1-1.734
median-1.588
Q3-1.517
95-th percentile-1.14925
Maximum0.893
Range3.578
Interquartile range (IQR)0.217

Descriptive statistics

Standard deviation0.25005841
Coefficient of variation (CV)-0.15649422
Kurtosis7.684859
Mean-1.5978763
Median Absolute Deviation (MAD)0.095
Skewness1.5415942
Sum-13783.281
Variance0.06252921
MonotonicityNot monotonic
2024-03-15T00:22:47.026684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1.531 50
 
0.6%
-1.512 46
 
0.5%
-1.549 44
 
0.5%
-1.528 43
 
0.5%
-1.53 42
 
0.5%
-1.546 42
 
0.5%
-1.58 39
 
0.4%
-1.608 39
 
0.4%
-1.55 39
 
0.4%
-1.518 39
 
0.4%
Other values (1224) 8203
93.6%
(Missing) 134
 
1.5%
ValueCountFrequency (%)
-2.685 1
< 0.1%
-2.496 1
< 0.1%
-2.469 1
< 0.1%
-2.321 1
< 0.1%
-2.313 1
< 0.1%
-2.307 1
< 0.1%
-2.284 1
< 0.1%
-2.275 1
< 0.1%
-2.196 1
< 0.1%
-2.186 1
< 0.1%
ValueCountFrequency (%)
0.893 1
< 0.1%
0.228 1
< 0.1%
0.153 1
< 0.1%
0.1 2
< 0.1%
0.098 1
< 0.1%
0.081 1
< 0.1%
0.075 1
< 0.1%
0.022 1
< 0.1%
-0.006 1
< 0.1%
-0.015 1
< 0.1%

시간최소
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1204
Distinct (%)13.9%
Missing127
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean-1.5810242
Minimum-2.151
Maximum3.939
Zeros0
Zeros (%)0.0%
Negative8615
Negative (%)98.3%
Memory size77.1 KiB
2024-03-15T00:22:47.657020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2.151
5-th percentile-1.929
Q1-1.713
median-1.579
Q3-1.51
95-th percentile-1.1262
Maximum3.939
Range6.09
Interquartile range (IQR)0.203

Descriptive statistics

Standard deviation0.26644467
Coefficient of variation (CV)-0.16852662
Kurtosis46.97214
Mean-1.5810242
Median Absolute Deviation (MAD)0.088
Skewness3.6594369
Sum-13648.982
Variance0.070992764
MonotonicityNot monotonic
2024-03-15T00:22:48.281794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1.608 48
 
0.5%
-1.518 47
 
0.5%
-1.601 47
 
0.5%
-1.512 46
 
0.5%
-1.524 46
 
0.5%
-1.549 44
 
0.5%
-1.528 44
 
0.5%
-1.561 43
 
0.5%
-1.602 43
 
0.5%
-1.546 42
 
0.5%
Other values (1194) 8183
93.4%
(Missing) 127
 
1.4%
ValueCountFrequency (%)
-2.151 5
0.1%
-2.15 10
0.1%
-2.149 9
0.1%
-2.148 2
 
< 0.1%
-2.147 3
 
< 0.1%
-2.146 4
 
< 0.1%
-2.143 1
 
< 0.1%
-2.142 2
 
< 0.1%
-2.141 2
 
< 0.1%
-2.139 2
 
< 0.1%
ValueCountFrequency (%)
3.939 1
< 0.1%
3.532 1
< 0.1%
1.263 1
< 0.1%
1.211 1
< 0.1%
0.893 1
< 0.1%
0.814 1
< 0.1%
0.447 1
< 0.1%
0.355 1
< 0.1%
0.304 1
< 0.1%
0.228 1
< 0.1%

시간최대
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1302
Distinct (%)15.1%
Missing127
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean-1.6221131
Minimum-3.87
Maximum0.17
Zeros0
Zeros (%)0.0%
Negative8627
Negative (%)98.5%
Memory size77.1 KiB
2024-03-15T00:22:48.897101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-3.87
5-th percentile-2.004
Q1-1.767
median-1.603
Q3-1.525
95-th percentile-1.168
Maximum0.17
Range4.04
Interquartile range (IQR)0.242

Descriptive statistics

Standard deviation0.26242165
Coefficient of variation (CV)-0.16177766
Kurtosis6.8345838
Mean-1.6221131
Median Absolute Deviation (MAD)0.106
Skewness0.83805208
Sum-14003.702
Variance0.068865123
MonotonicityNot monotonic
2024-03-15T00:22:49.337051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1.549 53
 
0.6%
-1.531 51
 
0.6%
-1.614 46
 
0.5%
-1.607 42
 
0.5%
-1.524 42
 
0.5%
-1.61 40
 
0.5%
-1.613 38
 
0.4%
-2.15 38
 
0.4%
-1.58 38
 
0.4%
-1.544 37
 
0.4%
Other values (1292) 8208
93.7%
(Missing) 127
 
1.4%
ValueCountFrequency (%)
-3.87 2
< 0.1%
-3.259 1
< 0.1%
-3.179 1
< 0.1%
-3.086 1
< 0.1%
-2.957 1
< 0.1%
-2.73 1
< 0.1%
-2.703 1
< 0.1%
-2.698 1
< 0.1%
-2.695 1
< 0.1%
-2.685 1
< 0.1%
ValueCountFrequency (%)
0.17 1
< 0.1%
0.1 1
< 0.1%
0.097 1
< 0.1%
0.079 1
< 0.1%
0.037 1
< 0.1%
0.002 1
< 0.1%
-0.015 1
< 0.1%
-0.022 1
< 0.1%
-0.039 1
< 0.1%
-0.068 1
< 0.1%

시간평균
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1222
Distinct (%)14.2%
Missing127
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean-1.5979596
Minimum-2.237
Maximum0.201
Zeros0
Zeros (%)0.0%
Negative8625
Negative (%)98.5%
Memory size77.1 KiB
2024-03-15T00:22:49.767045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2.237
5-th percentile-1.944
Q1-1.73
median-1.591
Q3-1.518
95-th percentile-1.142
Maximum0.201
Range2.438
Interquartile range (IQR)0.212

Descriptive statistics

Standard deviation0.24713601
Coefficient of variation (CV)-0.15465723
Kurtosis6.642512
Mean-1.5979596
Median Absolute Deviation (MAD)0.094
Skewness1.4982971
Sum-13795.185
Variance0.061076207
MonotonicityNot monotonic
2024-03-15T00:22:50.204591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1.61 49
 
0.6%
-1.546 44
 
0.5%
-1.585 41
 
0.5%
-1.515 41
 
0.5%
-1.533 41
 
0.5%
-1.555 40
 
0.5%
-1.606 39
 
0.4%
-1.613 38
 
0.4%
-1.584 38
 
0.4%
-1.562 37
 
0.4%
Other values (1212) 8225
93.9%
(Missing) 127
 
1.4%
ValueCountFrequency (%)
-2.237 1
 
< 0.1%
-2.207 2
 
< 0.1%
-2.178 1
 
< 0.1%
-2.176 1
 
< 0.1%
-2.168 1
 
< 0.1%
-2.167 1
 
< 0.1%
-2.162 1
 
< 0.1%
-2.151 5
 
0.1%
-2.15 11
0.1%
-2.149 13
0.1%
ValueCountFrequency (%)
0.201 1
< 0.1%
0.158 1
< 0.1%
0.112 2
< 0.1%
0.053 1
< 0.1%
0.043 1
< 0.1%
0.037 1
< 0.1%
0.023 1
< 0.1%
-0.009 1
< 0.1%
-0.035 1
< 0.1%
-0.069 1
< 0.1%

Interactions

2024-03-15T00:22:37.838567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:04.640456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:07.266618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:09.376811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:11.649520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:14.859153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:18.021298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:21.241084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:24.605843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:27.849621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:31.108041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:34.321926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:38.097096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:04.902108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:07.426523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:09.775136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:11.876146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:15.114315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:18.287112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:21.503330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:24.872354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:28.116045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:31.366807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:34.592863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:38.359866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:05.165527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:07.592041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:09.944499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:12.127568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:15.377193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:18.556768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:21.765418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:25.139276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:28.390683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:31.632745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:34.866410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:38.612783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:05.415709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:07.763718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:10.088447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:12.385834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:15.627902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:18.816116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:22.014911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:25.396051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:28.650095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:31.887594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:35.129968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:38.886922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:05.687262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:07.938578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:10.266555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:12.660433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:15.894652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:19.093150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:22.286648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:25.669427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:28.931039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:32.157468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:35.414330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:39.143863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:05.964523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:08.098964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:10.421283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:12.937665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:16.150364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:19.355627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:22.548542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:25.935118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:29.195680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:32.418700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:35.685284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:39.311286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:06.159815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:08.329989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:10.614041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:13.220153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:16.413755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:19.621609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:23.010396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:26.206607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:29.470395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:32.691468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:35.958967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:39.467530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:06.321531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:08.516868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:10.822567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:13.487204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:16.674967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:19.884145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:23.268250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:26.473279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:29.734847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:32.962924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:36.421073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:39.640702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:06.494171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:08.692199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:10.992022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:13.760109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:16.944077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:20.159780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:23.538991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:26.746261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:30.013600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:33.237407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:36.710268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:39.854010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:06.671479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:08.866953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:11.163342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:14.039569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:17.217300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:20.437030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:23.812944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:27.025884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:30.289160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:33.517716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:36.992044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:40.056306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:06.842232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:09.037237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:11.327009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:14.314946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:17.480719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:20.704827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:24.076870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:27.299433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:30.564337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:33.781989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:37.271057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:40.236498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:07.034071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:09.220374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:11.501598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:14.599467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:17.766173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:20.986148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:24.355710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:27.588129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:30.849061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:34.066342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:22:37.566648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T00:22:50.490225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시간00분10분20분30분40분50분시간최소시간최대시간평균
1.0000.0000.0000.3490.4870.5340.6170.3870.5880.3290.5360.638
0.0001.0000.0000.2210.3240.3710.4200.2430.3860.2300.3710.428
시간0.0000.0001.0000.0920.0870.0880.1460.0590.1530.0870.1240.153
00분0.3490.2210.0921.0000.7640.7290.8130.6420.8030.8510.7980.789
10분0.4870.3240.0870.7641.0000.9420.9280.8030.9080.8360.9540.939
20분0.5340.3710.0880.7290.9421.0000.9570.8270.9150.7700.9520.966
30분0.6170.4200.1460.8130.9280.9571.0000.8850.9670.8020.9570.985
40분0.3870.2430.0590.6420.8030.8270.8851.0000.8390.8930.7920.898
50분0.5880.3860.1530.8030.9080.9150.9670.8391.0000.8120.9320.966
시간최소0.3290.2300.0870.8510.8360.7700.8020.8930.8121.0000.7660.817
시간최대0.5360.3710.1240.7980.9540.9520.9570.7920.9320.7661.0000.951
시간평균0.6380.4280.1530.7890.9390.9660.9850.8980.9660.8170.9511.000
2024-03-15T00:22:50.828459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시간00분10분20분30분40분50분시간최소시간최대시간평균
1.0000.0120.000-0.045-0.046-0.045-0.048-0.047-0.045-0.054-0.033-0.044
0.0121.0000.0000.0830.0830.0810.0810.0820.0800.0820.0820.081
시간0.0000.0001.0000.0160.0100.0090.0050.002-0.0040.0090.0060.006
00분-0.0450.0830.0161.0000.9820.9740.9690.9610.9550.9770.9570.980
10분-0.0460.0830.0100.9821.0000.9840.9800.9740.9690.9810.9620.990
20분-0.0450.0810.0090.9740.9841.0000.9850.9790.9750.9800.9640.989
30분-0.0480.0810.0050.9690.9800.9851.0000.9830.9800.9800.9630.988
40분-0.0470.0820.0020.9610.9740.9790.9831.0000.9850.9800.9610.988
50분-0.0450.080-0.0040.9550.9690.9750.9800.9851.0000.9790.9560.985
시간최소-0.0540.0820.0090.9770.9810.9800.9800.9800.9791.0000.9380.985
시간최대-0.0330.0820.0060.9570.9620.9640.9630.9610.9560.9381.0000.977
시간평균-0.0440.0810.0060.9800.9900.9890.9880.9880.9850.9850.9771.000

Missing values

2024-03-15T00:22:40.449815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T00:22:40.740173image/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.
2024-03-15T00:22:41.036387image/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

시간00분10분20분30분40분50분시간최소시간최대시간평균
0110-1.533-1.534-1.539-1.541-1.538-1.539-1.533-1.541-1.537
1111-1.541-1.539-1.54-1.543-1.545-1.543-1.539-1.545-1.541
2112-1.541-1.542-1.542-1.54-1.54-1.538-1.538-1.542-1.54
3113-1.537-1.537-1.539-1.542-1.543-1.542-1.537-1.543-1.54
4114-1.544-1.541-1.542-1.539-1.536-1.535-1.535-1.544-1.539
5115-1.537-1.54-1.537-1.536-1.535-1.535-1.535-1.54-1.536
6116-1.536-1.534-1.535-1.534-1.536-1.534-1.534-1.536-1.534
7117-1.534-1.533-1.534-1.534-1.533-1.534-1.533-1.534-1.533
8118-1.531-1.53-1.529-1.531-1.532-1.534-1.529-1.534-1.531
9119-1.533-1.533-1.533-1.532-1.534-1.533-1.532-1.534-1.533
시간00분10분20분30분40분50분시간최소시간최대시간평균
8750123114-1.88-1.831-1.818-1.773-1.731-1.718-1.718-1.88-1.791
8751123115-1.68-1.67-1.677-1.636-1.593-1.614-1.593-1.68-1.645
8752123116-1.599-1.608-1.593-1.624-1.593-1.583-1.583-1.624-1.6
8753123117-1.565-1.589-1.602-1.582-1.577-1.555-1.555-1.602-1.578
8754123118-1.571-1.549-1.555-1.571-1.58-1.58-1.549-1.58-1.567
8755123119-1.577-1.565-1.571-1.577-1.586-1.593-1.565-1.593-1.578
8756123120-1.58-1.583-1.577-1.586-1.586-1.583-1.577-1.586-1.582
8757123121-1.587-1.593-1.599-1.593-1.586-1.59-1.586-1.599-1.591
8758123122-1.583-1.593-1.586-1.593-1.583-1.586-1.583-1.593-1.587
8759123123-1.583<NA><NA><NA><NA><NA>-1.583-1.583-1.583