Overview

Dataset statistics

Number of variables12
Number of observations8760
Missing cells976
Missing cells (%)0.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory924.0 KiB
Average record size in memory108.0 B

Variable types

Numeric12

Dataset

Description한국농어촌공사 새만금유역내 신시도에 대한 수위계측정보로 일별,10분단위, 최대, 최소, 평균값을 제공하고 있음
Author한국농어촌공사
URLhttps://www.data.go.kr/data/15052516/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 108 (1.2%) missing valuesMissing
10분 has 108 (1.2%) missing valuesMissing
20분 has 110 (1.3%) missing valuesMissing
30분 has 110 (1.3%) missing valuesMissing
40분 has 111 (1.3%) missing valuesMissing
50분 has 111 (1.3%) missing valuesMissing
시간최소 has 106 (1.2%) missing valuesMissing
시간최대 has 106 (1.2%) missing valuesMissing
시간평균 has 106 (1.2%) missing valuesMissing
시간 has 365 (4.2%) zerosZeros

Reproduction

Analysis started2024-03-14 16:34:04.650140
Analysis finished2024-03-14 16:34:45.473424
Duration40.82 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
2024-03-15T01:34:45.650676image/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
2024-03-15T01:34:46.026495image/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
2024-03-15T01:34:46.403907image/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
2024-03-15T01:34:46.809032image/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
2024-03-15T01:34:47.070150image/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
2024-03-15T01:34:47.310091image/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 

Distinct1290
Distinct (%)14.9%
Missing108
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean-1.6065018
Minimum-2.507
Maximum0.224
Zeros0
Zeros (%)0.0%
Negative8644
Negative (%)98.7%
Memory size77.1 KiB
2024-03-15T01:34:47.786112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2.507
5-th percentile-1.98645
Q1-1.747
median-1.586
Q3-1.511
95-th percentile-1.178
Maximum0.224
Range2.731
Interquartile range (IQR)0.236

Descriptive statistics

Standard deviation0.25298396
Coefficient of variation (CV)-0.15747505
Kurtosis6.0784498
Mean-1.6065018
Median Absolute Deviation (MAD)0.1
Skewness1.2059123
Sum-13899.454
Variance0.064000882
MonotonicityNot monotonic
2024-03-15T01:34:48.171631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1.588 45
 
0.5%
-1.527 43
 
0.5%
-1.522 42
 
0.5%
-1.554 41
 
0.5%
-1.537 41
 
0.5%
-1.53 37
 
0.4%
-1.525 37
 
0.4%
-1.552 37
 
0.4%
-1.506 36
 
0.4%
-1.582 36
 
0.4%
Other values (1280) 8257
94.3%
(Missing) 108
 
1.2%
ValueCountFrequency (%)
-2.507 1
< 0.1%
-2.501 1
< 0.1%
-2.42 1
< 0.1%
-2.409 1
< 0.1%
-2.407 1
< 0.1%
-2.382 1
< 0.1%
-2.381 1
< 0.1%
-2.379 1
< 0.1%
-2.374 1
< 0.1%
-2.373 1
< 0.1%
ValueCountFrequency (%)
0.224 1
< 0.1%
0.193 1
< 0.1%
0.16 1
< 0.1%
0.132 1
< 0.1%
0.077 1
< 0.1%
0.069 1
< 0.1%
0.034 1
< 0.1%
0.015 1
< 0.1%
-0.003 1
< 0.1%
-0.047 1
< 0.1%

10분
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1266
Distinct (%)14.6%
Missing108
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean-1.6079007
Minimum-2.508
Maximum0.199
Zeros0
Zeros (%)0.0%
Negative8644
Negative (%)98.7%
Memory size77.1 KiB
2024-03-15T01:34:48.437470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2.508
5-th percentile-1.98345
Q1-1.751
median-1.586
Q3-1.511
95-th percentile-1.1771
Maximum0.199
Range2.707
Interquartile range (IQR)0.24

Descriptive statistics

Standard deviation0.25309303
Coefficient of variation (CV)-0.15740588
Kurtosis6.0359312
Mean-1.6079007
Median Absolute Deviation (MAD)0.102
Skewness1.2079579
Sum-13911.557
Variance0.06405608
MonotonicityNot monotonic
2024-03-15T01:34:48.795125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1.532 42
 
0.5%
-1.586 40
 
0.5%
-1.53 39
 
0.4%
-1.524 38
 
0.4%
-1.541 38
 
0.4%
-1.525 37
 
0.4%
-1.518 37
 
0.4%
-1.505 36
 
0.4%
-1.587 36
 
0.4%
-1.519 36
 
0.4%
Other values (1256) 8273
94.4%
(Missing) 108
 
1.2%
ValueCountFrequency (%)
-2.508 1
< 0.1%
-2.507 1
< 0.1%
-2.396 1
< 0.1%
-2.393 1
< 0.1%
-2.392 1
< 0.1%
-2.388 1
< 0.1%
-2.387 1
< 0.1%
-2.383 1
< 0.1%
-2.379 1
< 0.1%
-2.357 1
< 0.1%
ValueCountFrequency (%)
0.199 1
< 0.1%
0.179 1
< 0.1%
0.165 1
< 0.1%
0.145 1
< 0.1%
0.087 1
< 0.1%
0.082 1
< 0.1%
0.026 1
< 0.1%
0.004 1
< 0.1%
-0.017 1
< 0.1%
-0.038 1
< 0.1%

20분
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1272
Distinct (%)14.7%
Missing110
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean-1.6079469
Minimum-2.978
Maximum0.211
Zeros0
Zeros (%)0.0%
Negative8642
Negative (%)98.7%
Memory size77.1 KiB
2024-03-15T01:34:49.248824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2.978
5-th percentile-1.982
Q1-1.752
median-1.586
Q3-1.51
95-th percentile-1.17745
Maximum0.211
Range3.189
Interquartile range (IQR)0.242

Descriptive statistics

Standard deviation0.2531408
Coefficient of variation (CV)-0.15743107
Kurtosis6.0659023
Mean-1.6079469
Median Absolute Deviation (MAD)0.103
Skewness1.1875995
Sum-13908.741
Variance0.064080266
MonotonicityNot monotonic
2024-03-15T01:34:49.516954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1.55 44
 
0.5%
-1.562 41
 
0.5%
-1.535 41
 
0.5%
-1.52 39
 
0.4%
-1.588 39
 
0.4%
-1.514 38
 
0.4%
-1.521 38
 
0.4%
-1.517 38
 
0.4%
-1.523 37
 
0.4%
-1.548 37
 
0.4%
Other values (1262) 8258
94.3%
(Missing) 110
 
1.3%
ValueCountFrequency (%)
-2.978 1
< 0.1%
-2.41 2
< 0.1%
-2.408 1
< 0.1%
-2.375 1
< 0.1%
-2.372 1
< 0.1%
-2.371 1
< 0.1%
-2.367 1
< 0.1%
-2.363 1
< 0.1%
-2.351 2
< 0.1%
-2.347 1
< 0.1%
ValueCountFrequency (%)
0.211 1
< 0.1%
0.174 1
< 0.1%
0.147 1
< 0.1%
0.121 1
< 0.1%
0.096 1
< 0.1%
0.09 1
< 0.1%
0.04 1
< 0.1%
0.018 1
< 0.1%
-0.029 1
< 0.1%
-0.061 2
< 0.1%

30분
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1284
Distinct (%)14.8%
Missing110
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean-1.6076951
Minimum-2.505
Maximum0.216
Zeros0
Zeros (%)0.0%
Negative8642
Negative (%)98.7%
Memory size77.1 KiB
2024-03-15T01:34:49.906472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2.505
5-th percentile-1.983
Q1-1.752
median-1.584
Q3-1.51
95-th percentile-1.1799
Maximum0.216
Range2.721
Interquartile range (IQR)0.242

Descriptive statistics

Standard deviation0.2530793
Coefficient of variation (CV)-0.15741747
Kurtosis5.9899041
Mean-1.6076951
Median Absolute Deviation (MAD)0.103
Skewness1.1933989
Sum-13906.563
Variance0.064049131
MonotonicityNot monotonic
2024-03-15T01:34:50.364707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1.526 43
 
0.5%
-1.53 42
 
0.5%
-1.552 41
 
0.5%
-1.514 39
 
0.4%
-1.522 39
 
0.4%
-1.515 39
 
0.4%
-1.519 37
 
0.4%
-1.505 36
 
0.4%
-1.582 36
 
0.4%
-1.548 36
 
0.4%
Other values (1274) 8262
94.3%
(Missing) 110
 
1.3%
ValueCountFrequency (%)
-2.505 1
< 0.1%
-2.423 1
< 0.1%
-2.421 1
< 0.1%
-2.408 1
< 0.1%
-2.384 2
< 0.1%
-2.379 1
< 0.1%
-2.349 1
< 0.1%
-2.34 2
< 0.1%
-2.339 2
< 0.1%
-2.337 1
< 0.1%
ValueCountFrequency (%)
0.216 1
< 0.1%
0.179 1
< 0.1%
0.157 1
< 0.1%
0.111 1
< 0.1%
0.088 1
< 0.1%
0.058 1
< 0.1%
0.05 1
< 0.1%
0.035 1
< 0.1%
-0.011 1
< 0.1%
-0.042 1
< 0.1%

40분
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1276
Distinct (%)14.8%
Missing111
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean-1.6067799
Minimum-2.436
Maximum0.221
Zeros0
Zeros (%)0.0%
Negative8641
Negative (%)98.6%
Memory size77.1 KiB
2024-03-15T01:34:50.876051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2.436
5-th percentile-1.988
Q1-1.75
median-1.584
Q3-1.51
95-th percentile-1.177
Maximum0.221
Range2.657
Interquartile range (IQR)0.24

Descriptive statistics

Standard deviation0.25283487
Coefficient of variation (CV)-0.15735501
Kurtosis6.0167839
Mean-1.6067799
Median Absolute Deviation (MAD)0.101
Skewness1.2017928
Sum-13897.039
Variance0.06392547
MonotonicityNot monotonic
2024-03-15T01:34:51.213675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1.518 46
 
0.5%
-1.52 44
 
0.5%
-1.542 42
 
0.5%
-1.528 40
 
0.5%
-1.522 40
 
0.5%
-1.54 39
 
0.4%
-1.556 39
 
0.4%
-1.517 39
 
0.4%
-1.562 38
 
0.4%
-1.551 38
 
0.4%
Other values (1266) 8244
94.1%
(Missing) 111
 
1.3%
ValueCountFrequency (%)
-2.436 1
< 0.1%
-2.425 1
< 0.1%
-2.407 1
< 0.1%
-2.401 1
< 0.1%
-2.4 1
< 0.1%
-2.387 1
< 0.1%
-2.365 1
< 0.1%
-2.352 1
< 0.1%
-2.351 1
< 0.1%
-2.347 1
< 0.1%
ValueCountFrequency (%)
0.221 1
< 0.1%
0.173 1
< 0.1%
0.154 1
< 0.1%
0.127 1
< 0.1%
0.092 1
< 0.1%
0.053 1
< 0.1%
0.052 1
< 0.1%
0.015 1
< 0.1%
-0.001 1
< 0.1%
-0.027 1
< 0.1%

50분
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1283
Distinct (%)14.8%
Missing111
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean-1.6058162
Minimum-2.44
Maximum0.24
Zeros0
Zeros (%)0.0%
Negative8641
Negative (%)98.6%
Memory size77.1 KiB
2024-03-15T01:34:51.567503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2.44
5-th percentile-1.989
Q1-1.749
median-1.582
Q3-1.51
95-th percentile-1.1756
Maximum0.24
Range2.68
Interquartile range (IQR)0.239

Descriptive statistics

Standard deviation0.2531719
Coefficient of variation (CV)-0.15765933
Kurtosis6.0307642
Mean-1.6058162
Median Absolute Deviation (MAD)0.1
Skewness1.1975062
Sum-13888.704
Variance0.064096011
MonotonicityNot monotonic
2024-03-15T01:34:52.020618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1.522 43
 
0.5%
-1.525 41
 
0.5%
-1.582 41
 
0.5%
-1.526 41
 
0.5%
-1.534 40
 
0.5%
-1.513 39
 
0.4%
-1.515 39
 
0.4%
-1.553 38
 
0.4%
-1.561 38
 
0.4%
-1.518 38
 
0.4%
Other values (1273) 8251
94.2%
(Missing) 111
 
1.3%
ValueCountFrequency (%)
-2.44 1
< 0.1%
-2.423 1
< 0.1%
-2.412 1
< 0.1%
-2.395 1
< 0.1%
-2.386 1
< 0.1%
-2.382 1
< 0.1%
-2.377 1
< 0.1%
-2.368 1
< 0.1%
-2.367 1
< 0.1%
-2.36 1
< 0.1%
ValueCountFrequency (%)
0.24 1
< 0.1%
0.18 1
< 0.1%
0.147 1
< 0.1%
0.109 1
< 0.1%
0.095 1
< 0.1%
0.063 1
< 0.1%
0.059 1
< 0.1%
0.004 1
< 0.1%
-0.015 1
< 0.1%
-0.04 1
< 0.1%

시간최소
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1252
Distinct (%)14.5%
Missing106
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean-1.5892921
Minimum-2.382
Maximum0.24
Zeros0
Zeros (%)0.0%
Negative8644
Negative (%)98.7%
Memory size77.1 KiB
2024-03-15T01:34:52.375972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2.382
5-th percentile-1.93735
Q1-1.721
median-1.576
Q3-1.5
95-th percentile-1.163
Maximum0.24
Range2.622
Interquartile range (IQR)0.221

Descriptive statistics

Standard deviation0.24835239
Coefficient of variation (CV)-0.15626604
Kurtosis6.8747417
Mean-1.5892921
Median Absolute Deviation (MAD)0.095
Skewness1.3902392
Sum-13753.734
Variance0.061678908
MonotonicityNot monotonic
2024-03-15T01:34:52.830229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1.535 44
 
0.5%
-1.559 44
 
0.5%
-1.517 42
 
0.5%
-1.582 42
 
0.5%
-1.561 41
 
0.5%
-1.514 41
 
0.5%
-1.525 40
 
0.5%
-1.511 39
 
0.4%
-1.583 38
 
0.4%
-1.524 38
 
0.4%
Other values (1242) 8245
94.1%
(Missing) 106
 
1.2%
ValueCountFrequency (%)
-2.382 1
< 0.1%
-2.379 1
< 0.1%
-2.374 1
< 0.1%
-2.341 2
< 0.1%
-2.335 1
< 0.1%
-2.306 1
< 0.1%
-2.286 1
< 0.1%
-2.261 1
< 0.1%
-2.259 2
< 0.1%
-2.257 1
< 0.1%
ValueCountFrequency (%)
0.24 1
< 0.1%
0.224 1
< 0.1%
0.18 1
< 0.1%
0.179 1
< 0.1%
0.147 1
< 0.1%
0.109 1
< 0.1%
0.063 1
< 0.1%
0.059 1
< 0.1%
0.034 1
< 0.1%
0.004 1
< 0.1%

시간최대
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1290
Distinct (%)14.9%
Missing106
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean-1.6229601
Minimum-2.978
Maximum0.193
Zeros0
Zeros (%)0.0%
Negative8648
Negative (%)98.7%
Memory size77.1 KiB
2024-03-15T01:34:53.246514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2.978
5-th percentile-2.032
Q1-1.773
median-1.593
Q3-1.52
95-th percentile-1.195
Maximum0.193
Range3.171
Interquartile range (IQR)0.253

Descriptive statistics

Standard deviation0.25777084
Coefficient of variation (CV)-0.15882758
Kurtosis5.3118215
Mean-1.6229601
Median Absolute Deviation (MAD)0.106
Skewness1.0247409
Sum-14045.097
Variance0.066445805
MonotonicityNot monotonic
2024-03-15T01:34:53.581864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1.588 43
 
0.5%
-1.532 42
 
0.5%
-1.52 40
 
0.5%
-1.595 39
 
0.4%
-1.541 39
 
0.4%
-1.554 38
 
0.4%
-1.528 38
 
0.4%
-1.523 38
 
0.4%
-1.525 38
 
0.4%
-1.538 38
 
0.4%
Other values (1280) 8261
94.3%
(Missing) 106
 
1.2%
ValueCountFrequency (%)
-2.978 1
< 0.1%
-2.508 1
< 0.1%
-2.44 1
< 0.1%
-2.425 1
< 0.1%
-2.42 1
< 0.1%
-2.412 1
< 0.1%
-2.409 1
< 0.1%
-2.408 1
< 0.1%
-2.407 1
< 0.1%
-2.4 1
< 0.1%
ValueCountFrequency (%)
0.193 1
< 0.1%
0.132 1
< 0.1%
0.095 1
< 0.1%
0.077 1
< 0.1%
0.069 1
< 0.1%
0.015 1
< 0.1%
-0.003 1
< 0.1%
-0.04 1
< 0.1%
-0.047 1
< 0.1%
-0.095 1
< 0.1%

시간평균
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1267
Distinct (%)14.6%
Missing106
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean-1.6065945
Minimum-2.414
Maximum0.213
Zeros0
Zeros (%)0.0%
Negative8646
Negative (%)98.7%
Memory size77.1 KiB
2024-03-15T01:34:53.849493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2.414
5-th percentile-1.98
Q1-1.74675
median-1.585
Q3-1.511
95-th percentile-1.17565
Maximum0.213
Range2.627
Interquartile range (IQR)0.23575

Descriptive statistics

Standard deviation0.2518264
Coefficient of variation (CV)-0.15674546
Kurtosis6.1020996
Mean-1.6065945
Median Absolute Deviation (MAD)0.1
Skewness1.2307119
Sum-13903.469
Variance0.063416536
MonotonicityNot monotonic
2024-03-15T01:34:54.291458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1.536 45
 
0.5%
-1.518 42
 
0.5%
-1.521 42
 
0.5%
-1.524 38
 
0.4%
-1.585 37
 
0.4%
-1.514 36
 
0.4%
-1.588 36
 
0.4%
-1.604 36
 
0.4%
-1.542 36
 
0.4%
-1.522 36
 
0.4%
Other values (1257) 8270
94.4%
(Missing) 106
 
1.2%
ValueCountFrequency (%)
-2.414 1
< 0.1%
-2.406 1
< 0.1%
-2.396 1
< 0.1%
-2.377 1
< 0.1%
-2.375 1
< 0.1%
-2.367 1
< 0.1%
-2.359 1
< 0.1%
-2.329 1
< 0.1%
-2.328 1
< 0.1%
-2.327 2
< 0.1%
ValueCountFrequency (%)
0.213 1
< 0.1%
0.155 1
< 0.1%
0.154 1
< 0.1%
0.107 1
< 0.1%
0.092 1
< 0.1%
0.088 1
< 0.1%
0.04 1
< 0.1%
0.028 1
< 0.1%
-0.02 1
< 0.1%
-0.052 1
< 0.1%

Interactions

2024-03-15T01:34:40.868722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:05.921215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:09.609796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:13.005868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:16.063519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:18.716854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:21.789109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:25.261119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:28.341909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:31.430791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:34.704828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:38.362363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:41.037277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:06.185721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:09.965711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:13.265438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:16.322017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:18.976619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:22.054752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:25.508031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:28.622009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:31.694017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:34.979785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:38.547849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:41.312375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:06.449344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:10.317059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:13.535665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:16.545006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:19.242790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:22.328790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:25.721496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:28.895742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:31.955525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:35.269928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:38.719628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:41.643642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:06.698878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:10.592608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:13.786346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:16.703146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:19.501706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:22.591686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:25.928068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:29.149409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:32.207200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:35.561505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:38.878838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:41.965657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:06.958903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:10.858042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:14.041629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:16.956422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:19.759802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:23.053739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:26.186243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:29.414645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:32.577332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:35.865531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:39.073720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:42.248345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:07.389901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:11.120100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:14.285491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:17.115005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:20.018173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:23.317808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:26.448761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:29.680349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:32.847901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:36.159007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:39.296005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:42.533993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:07.577976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:11.389863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:14.556179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:17.368869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:20.366431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:23.594852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:26.721070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:29.940525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:33.116524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:36.446962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:39.472955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:42.852802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:08.083714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:11.654733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:14.773138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:17.576772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:20.630263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:23.865530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:26.981008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:30.101012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:33.382948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:36.770149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:39.658661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:43.124625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:08.381036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:11.917319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:15.027817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:17.796712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:20.901022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:24.131729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:27.240698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:30.357486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:33.643289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:37.092136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:39.846606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:43.400980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:08.702698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:12.194377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:15.281722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:17.990019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:21.162544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:24.399134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:27.547310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:30.636803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:33.811937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:37.368890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:40.011160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:43.675444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:08.982095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:12.462885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:15.541323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:18.225986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:21.323479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:24.671657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:27.806317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:30.896346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:34.047278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:37.758440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:40.228036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:44.042264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:09.334038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:12.743690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:15.807190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:18.470243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:21.520403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:24.965679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:28.075782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:31.172839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:34.394490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:38.200892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:34:40.566759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T01:34:54.580135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시간00분10분20분30분40분50분시간최소시간최대시간평균
1.0000.0000.0000.6050.6050.5720.5970.5790.5770.5690.5560.569
0.0001.0000.0000.4110.4090.3720.4080.4060.4050.4070.3640.414
시간0.0000.0001.0000.1910.1900.1850.1980.1920.1940.1690.2040.190
00분0.6050.4110.1911.0000.9980.9770.9930.9850.9770.9830.9770.988
10분0.6050.4090.1900.9981.0000.9800.9970.9840.9780.9800.9800.986
20분0.5720.3720.1850.9770.9801.0000.9790.9750.9740.9750.9970.973
30분0.5970.4080.1980.9930.9970.9791.0000.9930.9880.9820.9820.989
40분0.5790.4060.1920.9850.9840.9750.9931.0000.9990.9930.9770.998
50분0.5770.4050.1940.9770.9780.9740.9880.9991.0000.9910.9750.996
시간최소0.5690.4070.1690.9830.9800.9750.9820.9930.9911.0000.9710.995
시간최대0.5560.3640.2040.9770.9800.9970.9820.9770.9750.9711.0000.975
시간평균0.5690.4140.1900.9880.9860.9730.9890.9980.9960.9950.9751.000
2024-03-15T01:34:54.916991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시간00분10분20분30분40분50분시간최소시간최대시간평균
1.0000.0120.000-0.051-0.049-0.052-0.054-0.054-0.055-0.064-0.041-0.053
0.0121.0000.0000.0700.0700.0700.0700.0690.0700.0730.0670.070
시간0.0000.0001.000-0.007-0.016-0.020-0.023-0.024-0.027-0.017-0.017-0.019
00분-0.0510.070-0.0071.0000.9910.9790.9700.9630.9570.9730.9810.984
10분-0.0490.070-0.0160.9911.0000.9940.9860.9770.9710.9760.9890.995
20분-0.0520.070-0.0200.9790.9941.0000.9940.9860.9800.9780.9870.997
30분-0.0540.070-0.0230.9700.9860.9941.0000.9950.9870.9800.9840.996
40분-0.0540.069-0.0240.9630.9770.9860.9951.0000.9950.9810.9790.993
50분-0.0550.070-0.0270.9570.9710.9800.9870.9951.0000.9800.9730.987
시간최소-0.0640.073-0.0170.9730.9760.9780.9800.9810.9801.0000.9550.983
시간최대-0.0410.067-0.0170.9810.9890.9870.9840.9790.9730.9551.0000.991
시간평균-0.0530.070-0.0190.9840.9950.9970.9960.9930.9870.9830.9911.000

Missing values

2024-03-15T01:34:44.441961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T01:34:44.835168image/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.
2024-03-15T01:34:45.215070image/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
0110-1.536-1.537-1.536-1.536-1.536-1.534-1.534-1.537-1.535
1111-1.536-1.534-1.535-1.533-1.531-1.532-1.531-1.536-1.533
2112-1.532-1.532-1.528-1.524-1.524-1.53-1.524-1.532-1.528
3113-1.531-1.532-1.53-1.53-1.531-1.53-1.53-1.532-1.53
4114-1.533-1.533-1.53-1.53-1.528-1.53-1.528-1.533-1.53
5115-1.528-1.525-1.524-1.523-1.525-1.521-1.521-1.528-1.524
6116-1.523-1.52-1.521-1.519-1.52-1.52-1.519-1.523-1.52
7117-1.521-1.52-1.52-1.52-1.522-1.528-1.52-1.528-1.521
8118-1.53-1.53-1.529-1.53-1.527-1.525-1.525-1.53-1.528
9119-1.525-1.53-1.531-1.53-1.529-1.526-1.525-1.531-1.528
시간00분10분20분30분40분50분시간최소시간최대시간평균
8750123114-1.908-1.893-1.875-1.839-1.798-1.76-1.76-1.908-1.845
8751123115-1.72-1.676-1.758-1.797-1.703-1.625-1.625-1.797-1.713
8752123116-1.582-1.456-1.483-1.583-1.601-1.595-1.456-1.601-1.55
8753123117-1.61-1.599-1.576-1.582-1.587-1.611-1.576-1.611-1.594
8754123118-1.604-1.611-1.596-1.591-1.583-1.59-1.583-1.611-1.595
8755123119-1.601-1.594-1.589-1.584-1.58-1.582-1.58-1.601-1.588
8756123120-1.578-1.583-1.586-1.584-1.582-1.582-1.578-1.586-1.582
8757123121-1.582-1.583-1.585-1.588-1.589-1.588-1.582-1.589-1.585
8758123122-1.587-1.585-1.583-1.578-1.584-1.59-1.578-1.59-1.584
8759123123-1.589<NA><NA><NA><NA><NA>-1.589-1.589-1.589