Overview

Dataset statistics

Number of variables18
Number of observations1047
Missing cells1037
Missing cells (%)5.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory155.4 KiB
Average record size in memory152.0 B

Variable types

DateTime1
TimeSeries10
Numeric6
Categorical1

Timeseries statistics

Number of series10
Time series length1047
Starting point2016-01-01 00:00:00
Ending point2018-11-12 00:00:00
Period1 day
2024-04-22T16:46:22.386004image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-22T16:46:22.842036image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Alerts

Gust has 94 (9.0%) missing valuesMissing
SnowDepth has 943 (90.1%) missing valuesMissing
MeanTemp is non stationaryNon stationary
MinTemp is non stationaryNon stationary
MaxTemp is non stationaryNon stationary
DewPoint is non stationaryNon stationary
Year is non stationaryNon stationary
Month is non stationaryNon stationary
Day is non stationaryNon stationary
Day_Of_Year is non stationaryNon stationary
Week is non stationaryNon stationary
MeanTemp is seasonalSeasonal
MinTemp is seasonalSeasonal
MaxTemp is seasonalSeasonal
DewPoint is seasonalSeasonal
Month is seasonalSeasonal
Day is seasonalSeasonal
Day_Of_Year is seasonalSeasonal
Week is seasonalSeasonal
Datetime has unique valuesUnique
Percipitation has 337 (32.2%) zerosZeros
Rain has 529 (50.5%) zerosZeros
SnowIce has 965 (92.2%) zerosZeros

Reproduction

Analysis started2024-04-22 20:46:00.926630
Analysis finished2024-04-22 20:46:22.233702
Duration21.31 seconds
Software versionydata-profiling vv4.7.0
Download configurationconfig.json

Variables

Datetime
Date

UNIQUE 

Distinct1047
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
Minimum2016-01-01 00:00:00
Maximum2018-11-12 00:00:00
2024-04-22T16:46:23.073810image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-22T16:46:23.182620image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

MeanTemp
Numeric time series

NON STATIONARY  SEASONAL 

Distinct974
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.012483
Minimum7.9333333
Maximum87.8
Zeros0
Zeros (%)0.0%
Memory size16.4 KiB
2024-04-22T16:46:23.411649image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum7.9333333
5-th percentile29.73
Q143.442857
median57.45
Q372.684524
95-th percentile80.8925
Maximum87.8
Range79.866667
Interquartile range (IQR)29.241667

Descriptive statistics

Standard deviation16.867902
Coefficient of variation (CV)0.29586332
Kurtosis-0.90087123
Mean57.012483
Median Absolute Deviation (MAD)14.8
Skewness-0.2624232
Sum59692.07
Variance284.52613
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.3201654326
2024-04-22T16:46:23.626605image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2024-04-22T16:46:24.107500image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Gap statistics

number of gaps0
min0
max0
mean0
std0
2024-04-22T16:46:24.286376image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
39.85714286 3
 
0.3%
77.25714286 2
 
0.2%
45.9 2
 
0.2%
75.18571429 2
 
0.2%
48.4 2
 
0.2%
63.32857143 2
 
0.2%
50.7 2
 
0.2%
36.48571429 2
 
0.2%
47.61666667 2
 
0.2%
75.225 2
 
0.2%
Other values (964) 1026
98.0%
ValueCountFrequency (%)
7.933333333 1
0.1%
10.65714286 1
0.1%
12 1
0.1%
12.62857143 1
0.1%
16.11428571 1
0.1%
16.65714286 1
0.1%
17.38571429 1
0.1%
17.98571429 1
0.1%
18.61428571 1
0.1%
18.65 1
0.1%
ValueCountFrequency (%)
87.8 1
0.1%
87.15 1
0.1%
86.74285714 1
0.1%
86.04285714 1
0.1%
85.3 2
0.2%
85.25 1
0.1%
85.05 1
0.1%
84.9 1
0.1%
84.625 1
0.1%
84.6 1
0.1%
2024-04-22T16:46:23.803459image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ACF and PACF

MinTemp
Numeric time series

NON STATIONARY  SEASONAL 

Distinct961
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.077053
Minimum0.66666667
Maximum81.185714
Zeros0
Zeros (%)0.0%
Memory size16.4 KiB
2024-04-22T16:46:24.621793image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0.66666667
5-th percentile22.53619
Q137.621429
median49.7
Q365.557143
95-th percentile73.93
Maximum81.185714
Range80.519048
Interquartile range (IQR)27.935714

Descriptive statistics

Standard deviation16.553619
Coefficient of variation (CV)0.33056297
Kurtosis-0.90469304
Mean50.077053
Median Absolute Deviation (MAD)14.057143
Skewness-0.22554798
Sum52430.675
Variance274.02232
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.06471607934
2024-04-22T16:46:24.838363image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2024-04-22T16:46:25.330661image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Gap statistics

number of gaps0
min0
max0
mean0
std0
2024-04-22T16:46:25.505568image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
63 4
 
0.4%
56.225 3
 
0.3%
63.5 3
 
0.3%
30.95714286 3
 
0.3%
66.725 3
 
0.3%
76 3
 
0.3%
44.5 3
 
0.3%
62.8 3
 
0.3%
41.12857143 2
 
0.2%
72.5 2
 
0.2%
Other values (951) 1018
97.2%
ValueCountFrequency (%)
0.6666666667 1
0.1%
5.585714286 1
0.1%
7.942857143 1
0.1%
8.671428571 1
0.1%
9.616666667 1
0.1%
10.32857143 1
0.1%
10.42857143 1
0.1%
10.64285714 1
0.1%
11.08333333 1
0.1%
11.82 1
0.1%
ValueCountFrequency (%)
81.18571429 1
0.1%
78.51428571 1
0.1%
78.275 1
0.1%
78.225 1
0.1%
77.98571429 1
0.1%
77.78571429 1
0.1%
77.64285714 1
0.1%
77.41428571 1
0.1%
77.31428571 1
0.1%
77.24285714 1
0.1%
2024-04-22T16:46:25.023612image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ACF and PACF

MaxTemp
Numeric time series

NON STATIONARY  SEASONAL 

Distinct962
Distinct (%)91.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65.830537
Minimum18.714286
Maximum96
Zeros0
Zeros (%)0.0%
Memory size16.4 KiB
2024-04-22T16:46:25.832692image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum18.714286
5-th percentile37.131429
Q151.959524
median66.95
Q381.439286
95-th percentile89.67119
Maximum96
Range77.285714
Interquartile range (IQR)29.479762

Descriptive statistics

Standard deviation17.320238
Coefficient of variation (CV)0.26310339
Kurtosis-0.90533429
Mean65.830537
Median Absolute Deviation (MAD)14.666667
Skewness-0.31095872
Sum68924.573
Variance299.99064
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.2766479037
2024-04-22T16:46:26.044152image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2024-04-22T16:46:26.730623image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Gap statistics

number of gaps0
min0
max0
mean0
std0
2024-04-22T16:46:26.909898image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
82.25 4
 
0.4%
40.4 3
 
0.3%
84 3
 
0.3%
61.11666667 3
 
0.3%
92.75 3
 
0.3%
86 3
 
0.3%
63.5 2
 
0.2%
44.85714286 2
 
0.2%
42.67142857 2
 
0.2%
39.18571429 2
 
0.2%
Other values (952) 1020
97.4%
ValueCountFrequency (%)
18.71428571 1
0.1%
19.6 1
0.1%
20 1
0.1%
21.01428571 1
0.1%
23.05714286 1
0.1%
23.6 1
0.1%
23.94285714 1
0.1%
24.32857143 1
0.1%
25.31666667 1
0.1%
26.02857143 1
0.1%
ValueCountFrequency (%)
96 2
0.2%
95.175 1
0.1%
94.81428571 1
0.1%
94.7 1
0.1%
94.57142857 1
0.1%
94.225 1
0.1%
94.2 1
0.1%
94.15714286 1
0.1%
93.91428571 1
0.1%
93.6 1
0.1%
2024-04-22T16:46:26.216592image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ACF and PACF

DewPoint
Numeric time series

NON STATIONARY  SEASONAL 

Distinct898
Distinct (%)85.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.1305
Minimum-14.2
Maximum75.35
Zeros0
Zeros (%)0.0%
Memory size16.4 KiB
2024-04-22T16:46:27.247568image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-14.2
5-th percentile11.3775
Q129.675
median45.4
Q360.3875
95-th percentile70.8875
Maximum75.35
Range89.55
Interquartile range (IQR)30.7125

Descriptive statistics

Standard deviation18.900957
Coefficient of variation (CV)0.42829693
Kurtosis-0.80386119
Mean44.1305
Median Absolute Deviation (MAD)15.275
Skewness-0.34466509
Sum46204.633
Variance357.24619
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.2125589646
2024-04-22T16:46:27.469717image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2024-04-22T16:46:27.954332image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Gap statistics

number of gaps0
min0
max0
mean0
std0
2024-04-22T16:46:28.126356image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
59.5 5
 
0.5%
69.925 4
 
0.4%
58.5 4
 
0.4%
50.5 4
 
0.4%
67.6 4
 
0.4%
60.375 3
 
0.3%
66.5 3
 
0.3%
25.9 3
 
0.3%
65.8 3
 
0.3%
37.3 3
 
0.3%
Other values (888) 1011
96.6%
ValueCountFrequency (%)
-14.2 1
0.1%
-5.625 1
0.1%
-5.25 1
0.1%
-4.125 1
0.1%
-1.625 1
0.1%
-0.9 1
0.1%
-0.5 1
0.1%
-0.475 1
0.1%
1.375 1
0.1%
1.433333333 1
0.1%
ValueCountFrequency (%)
75.35 1
0.1%
74.625 1
0.1%
74.475 1
0.1%
74.3 1
0.1%
74.225 1
0.1%
73.825 1
0.1%
73.7 1
0.1%
73.45 1
0.1%
73.4 1
0.1%
73.4 1
0.1%
2024-04-22T16:46:27.639712image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ACF and PACF

Percipitation
Real number (ℝ)

ZEROS 

Distinct301
Distinct (%)28.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.17983631
Minimum0
Maximum24.9975
Zeros337
Zeros (%)32.2%
Negative0
Negative (%)0.0%
Memory size16.4 KiB
2024-04-22T16:46:28.335613image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.0083333333
Q30.065357143
95-th percentile0.5465
Maximum24.9975
Range24.9975
Interquartile range (IQR)0.065357143

Descriptive statistics

Standard deviation1.3763088
Coefficient of variation (CV)7.6531198
Kurtosis245.80808
Mean0.17983631
Median Absolute Deviation (MAD)0.0083333333
Skewness15.23043
Sum188.28862
Variance1.894226
MonotonicityNot monotonic
2024-04-22T16:46:28.446017image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 337
32.2%
0.001428571429 41
 
3.9%
0.002857142857 28
 
2.7%
0.004285714286 27
 
2.6%
0.01 27
 
2.6%
0.005714285714 20
 
1.9%
0.008571428571 16
 
1.5%
0.007142857143 16
 
1.5%
0.0025 15
 
1.4%
0.01428571429 11
 
1.1%
Other values (291) 509
48.6%
ValueCountFrequency (%)
0 337
32.2%
0.001428571429 41
 
3.9%
0.001666666667 9
 
0.9%
0.002 1
 
0.1%
0.0025 15
 
1.4%
0.002857142857 28
 
2.7%
0.003333333333 6
 
0.6%
0.004285714286 27
 
2.6%
0.005 10
 
1.0%
0.005714285714 20
 
1.9%
ValueCountFrequency (%)
24.9975 2
0.2%
17.36 1
0.1%
14.49428571 1
0.1%
14.38142857 1
0.1%
1.484285714 1
0.1%
1.438571429 1
0.1%
1.431428571 1
0.1%
1.1575 1
0.1%
1.135714286 1
0.1%
1.135 1
0.1%

WindSpeed
Real number (ℝ)

Distinct662
Distinct (%)63.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.7968502
Minimum1.8333333
Maximum17.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.4 KiB
2024-04-22T16:46:28.550243image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1.8333333
5-th percentile2.92
Q14.1571429
median5.3142857
Q36.9791667
95-th percentile10.11
Maximum17.4
Range15.566667
Interquartile range (IQR)2.8220238

Descriptive statistics

Standard deviation2.2159932
Coefficient of variation (CV)0.3822754
Kurtosis0.79565455
Mean5.7968502
Median Absolute Deviation (MAD)1.3714286
Skewness0.90309565
Sum6069.3021
Variance4.9106261
MonotonicityNot monotonic
2024-04-22T16:46:28.663771image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.4 10
 
1.0%
5.3 8
 
0.8%
5.2 7
 
0.7%
6.4 6
 
0.6%
5.128571429 6
 
0.6%
5.871428571 6
 
0.6%
5 5
 
0.5%
4.557142857 5
 
0.5%
4.9 5
 
0.5%
5.928571429 5
 
0.5%
Other values (652) 984
94.0%
ValueCountFrequency (%)
1.833333333 1
0.1%
1.9 1
0.1%
2.1 1
0.1%
2.166666667 1
0.1%
2.171428571 1
0.1%
2.183333333 2
0.2%
2.185714286 1
0.1%
2.26 1
0.1%
2.271428571 1
0.1%
2.28 1
0.1%
ValueCountFrequency (%)
17.4 1
0.1%
13.425 1
0.1%
12.91666667 1
0.1%
12.66666667 1
0.1%
12.6 1
0.1%
12.43333333 1
0.1%
12.33333333 1
0.1%
12.3 1
0.1%
12.21428571 1
0.1%
12.16666667 1
0.1%

MaxSustainedWind
Real number (ℝ)

Distinct541
Distinct (%)51.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.25847
Minimum6.05
Maximum31.775
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.4 KiB
2024-04-22T16:46:28.781724image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum6.05
5-th percentile8.986
Q111.346667
median13.75
Q316.475
95-th percentile22.1705
Maximum31.775
Range25.725
Interquartile range (IQR)5.1283333

Descriptive statistics

Standard deviation3.9845213
Coefficient of variation (CV)0.27944942
Kurtosis0.85827954
Mean14.25847
Median Absolute Deviation (MAD)2.55
Skewness0.84631505
Sum14928.618
Variance15.87641
MonotonicityNot monotonic
2024-04-22T16:46:28.898839image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12 11
 
1.1%
15 11
 
1.1%
9.7 8
 
0.8%
12.475 8
 
0.8%
14 8
 
0.8%
13.8 7
 
0.7%
14.7 7
 
0.7%
12.78 7
 
0.7%
9.4 7
 
0.7%
12.8 7
 
0.7%
Other values (531) 966
92.3%
ValueCountFrequency (%)
6.05 1
0.1%
6.44 1
0.1%
6.525 1
0.1%
6.933333333 1
0.1%
7 2
0.2%
7.2 2
0.2%
7.4 1
0.1%
7.475 2
0.2%
7.56 1
0.1%
7.58 1
0.1%
ValueCountFrequency (%)
31.775 1
0.1%
30.84 1
0.1%
29.7 1
0.1%
27.76 1
0.1%
27.06 1
0.1%
26.95 1
0.1%
26.36666667 1
0.1%
26.25 1
0.1%
26.18 1
0.1%
25.75 1
0.1%

Gust
Real number (ℝ)

MISSING 

Distinct408
Distinct (%)42.8%
Missing94
Missing (%)9.0%
Infinite0
Infinite (%)0.0%
Mean24.338737
Minimum14
Maximum54
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.4 KiB
2024-04-22T16:46:29.010947image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile15.9
Q119.666667
median23.3
Q327.775
95-th percentile35.863333
Maximum54
Range40
Interquartile range (IQR)8.1083333

Descriptive statistics

Standard deviation6.3090563
Coefficient of variation (CV)0.25921872
Kurtosis1.1971504
Mean24.338737
Median Absolute Deviation (MAD)4.025
Skewness0.92935538
Sum23194.817
Variance39.804192
MonotonicityNot monotonic
2024-04-22T16:46:29.131653image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15.9 23
 
2.2%
17.1 23
 
2.2%
27 22
 
2.1%
15 20
 
1.9%
21 19
 
1.8%
20 18
 
1.7%
19 13
 
1.2%
18 11
 
1.1%
18.1 11
 
1.1%
19.55 10
 
1.0%
Other values (398) 783
74.8%
(Missing) 94
 
9.0%
ValueCountFrequency (%)
14 9
 
0.9%
14.5 1
 
0.1%
14.95 1
 
0.1%
15 20
1.9%
15.45 2
 
0.2%
15.55 2
 
0.2%
15.7 1
 
0.1%
15.9 23
2.2%
16 1
 
0.1%
16.05 5
 
0.5%
ValueCountFrequency (%)
54 1
 
0.1%
51.1 1
 
0.1%
49.9 1
 
0.1%
47 1
 
0.1%
46 1
 
0.1%
45.7 1
 
0.1%
45.1 2
0.2%
44.1 1
 
0.1%
42.36666667 1
 
0.1%
42 4
0.4%

Rain
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.24884022
Minimum0
Maximum1
Zeros529
Zeros (%)50.5%
Negative0
Negative (%)0.0%
Memory size16.4 KiB
2024-04-22T16:46:29.234033image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.5
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation0.31081683
Coefficient of variation (CV)1.2490619
Kurtosis0.031330003
Mean0.24884022
Median Absolute Deviation (MAD)0
Skewness1.0334144
Sum260.53571
Variance0.096607103
MonotonicityNot monotonic
2024-04-22T16:46:29.321937image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 529
50.5%
0.5714285714 115
 
11.0%
1 78
 
7.4%
0.4285714286 72
 
6.9%
0.5 71
 
6.8%
0.1428571429 57
 
5.4%
0.2857142857 37
 
3.5%
0.3333333333 26
 
2.5%
0.1666666667 22
 
2.1%
0.25 20
 
1.9%
Other values (2) 20
 
1.9%
ValueCountFrequency (%)
0 529
50.5%
0.1428571429 57
 
5.4%
0.1666666667 22
 
2.1%
0.25 20
 
1.9%
0.2857142857 37
 
3.5%
0.3333333333 26
 
2.5%
0.4285714286 72
 
6.9%
0.5 71
 
6.8%
0.5714285714 115
 
11.0%
0.6666666667 7
 
0.7%
ValueCountFrequency (%)
1 78
7.4%
0.75 13
 
1.2%
0.6666666667 7
 
0.7%
0.5714285714 115
11.0%
0.5 71
6.8%
0.4285714286 72
6.9%
0.3333333333 26
 
2.5%
0.2857142857 37
 
3.5%
0.25 20
 
1.9%
0.1666666667 22
 
2.1%

SnowDepth
Numeric time series

MISSING 

Distinct41
Distinct (%)39.4%
Missing943
Missing (%)90.1%
Infinite0
Infinite (%)0.0%
Mean3.3003205
Minimum1.2
Maximum26.2
Zeros0
Zeros (%)0.0%
Memory size16.4 KiB
2024-04-22T16:46:29.494237image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1.2
5-th percentile1.2
Q11.2
median1.7833333
Q34.0416667
95-th percentile7.855
Maximum26.2
Range25
Interquartile range (IQR)2.8416667

Descriptive statistics

Standard deviation3.9719329
Coefficient of variation (CV)1.2034992
Kurtosis14.536024
Mean3.3003205
Median Absolute Deviation (MAD)0.58333333
Skewness3.5032006
Sum343.23333
Variance15.776251
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.000618527948
2024-04-22T16:46:29.653815image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
2024-04-22T16:46:29.989233image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Gap statistics

number of gaps8
min2 weeks and 2 days
max38 weeks and 4 days
mean11 weeks, 2 days and 21 hours
std16 weeks, 3 days and 5 hours
2024-04-22T16:46:30.105368image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
1.2 40
 
3.8%
2 7
 
0.7%
1.6 5
 
0.5%
2.1 4
 
0.4%
1.466666667 4
 
0.4%
1.733333333 3
 
0.3%
1.833333333 3
 
0.3%
5.366666667 2
 
0.2%
4.7 2
 
0.2%
2.366666667 2
 
0.2%
Other values (31) 32
 
3.1%
(Missing) 943
90.1%
ValueCountFrequency (%)
1.2 40
3.8%
1.466666667 4
 
0.4%
1.6 5
 
0.5%
1.733333333 3
 
0.3%
1.833333333 3
 
0.3%
2 7
 
0.7%
2.1 4
 
0.4%
2.366666667 2
 
0.2%
2.466666667 1
 
0.1%
2.55 1
 
0.1%
ValueCountFrequency (%)
26.2 1
0.1%
19.93333333 1
0.1%
17.73333333 1
0.1%
15.6 1
0.1%
11.93333333 1
0.1%
7.9 1
0.1%
7.6 1
0.1%
7.5 1
0.1%
7.366666667 1
0.1%
7.1 1
0.1%
2024-04-22T16:46:29.745898image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ACF and PACF

SnowIce
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.031950698
Minimum0
Maximum1
Zeros965
Zeros (%)92.2%
Negative0
Negative (%)0.0%
Memory size16.4 KiB
2024-04-22T16:46:30.259823image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.42857143
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.12004406
Coefficient of variation (CV)3.7571655
Kurtosis15.336567
Mean0.031950698
Median Absolute Deviation (MAD)0
Skewness3.9452355
Sum33.452381
Variance0.014410577
MonotonicityNot monotonic
2024-04-22T16:46:30.345881image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 965
92.2%
0.5714285714 21
 
2.0%
0.4285714286 17
 
1.6%
0.5 14
 
1.3%
0.1428571429 14
 
1.3%
0.2857142857 7
 
0.7%
0.1666666667 5
 
0.5%
0.3333333333 2
 
0.2%
0.6666666667 1
 
0.1%
1 1
 
0.1%
ValueCountFrequency (%)
0 965
92.2%
0.1428571429 14
 
1.3%
0.1666666667 5
 
0.5%
0.2857142857 7
 
0.7%
0.3333333333 2
 
0.2%
0.4285714286 17
 
1.6%
0.5 14
 
1.3%
0.5714285714 21
 
2.0%
0.6666666667 1
 
0.1%
1 1
 
0.1%
ValueCountFrequency (%)
1 1
 
0.1%
0.6666666667 1
 
0.1%
0.5714285714 21
 
2.0%
0.5 14
 
1.3%
0.4285714286 17
 
1.6%
0.3333333333 2
 
0.2%
0.2857142857 7
 
0.7%
0.1666666667 5
 
0.5%
0.1428571429 14
 
1.3%
0 965
92.2%

Year
Numeric time series

NON STATIONARY 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2016.9522
Minimum2016
Maximum2018
Zeros0
Zeros (%)0.0%
Memory size16.4 KiB
2024-04-22T16:46:30.759376image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum2016
5-th percentile2016
Q12016
median2017
Q32018
95-th percentile2018
Maximum2018
Range2
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.80605514
Coefficient of variation (CV)0.00039964017
Kurtosis-1.4557537
Mean2016.9522
Median Absolute Deviation (MAD)1
Skewness0.086838482
Sum2111749
Variance0.64972488
MonotonicityIncreasing
Augmented Dickey-Fuller test p-value0.8212922152
2024-04-22T16:46:30.965052image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
2024-04-22T16:46:31.453723image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Gap statistics

number of gaps0
min0
max0
mean0
std0
2024-04-22T16:46:31.632940image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
2016 366
35.0%
2017 365
34.9%
2018 316
30.2%
ValueCountFrequency (%)
2016 366
35.0%
2017 365
34.9%
2018 316
30.2%
ValueCountFrequency (%)
2018 316
30.2%
2017 365
34.9%
2016 366
35.0%
2024-04-22T16:46:31.135320image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ACF and PACF

Month
Numeric time series

NON STATIONARY  SEASONAL 

Distinct12
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.2827125
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Memory size16.4 KiB
2024-04-22T16:46:31.951506image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.3425121
Coefficient of variation (CV)0.53201736
Kurtosis-1.1605185
Mean6.2827125
Median Absolute Deviation (MAD)3
Skewness0.033004239
Sum6578
Variance11.172387
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.1072808217
2024-04-22T16:46:32.146297image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
2024-04-22T16:46:32.610426image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Gap statistics

number of gaps0
min0
max0
mean0
std0
2024-04-22T16:46:32.784623image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
1 93
8.9%
3 93
8.9%
5 93
8.9%
7 93
8.9%
8 93
8.9%
10 93
8.9%
4 90
8.6%
6 90
8.6%
9 90
8.6%
2 85
8.1%
Other values (2) 134
12.8%
ValueCountFrequency (%)
1 93
8.9%
2 85
8.1%
3 93
8.9%
4 90
8.6%
5 93
8.9%
6 90
8.6%
7 93
8.9%
8 93
8.9%
9 90
8.6%
10 93
8.9%
ValueCountFrequency (%)
12 62
5.9%
11 72
6.9%
10 93
8.9%
9 90
8.6%
8 93
8.9%
7 93
8.9%
6 90
8.6%
5 93
8.9%
4 90
8.6%
3 93
8.9%
2024-04-22T16:46:32.306798image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ACF and PACF

Day
Numeric time series

NON STATIONARY  SEASONAL 

Distinct31
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.625597
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Memory size16.4 KiB
2024-04-22T16:46:33.104450image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation8.817419
Coefficient of variation (CV)0.56429326
Kurtosis-1.1984504
Mean15.625597
Median Absolute Deviation (MAD)8
Skewness0.023973957
Sum16360
Variance77.746878
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0
2024-04-22T16:46:33.305083image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
2024-04-22T16:46:33.786912image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Gap statistics

number of gaps0
min0
max0
mean0
std0
2024-04-22T16:46:33.960841image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
1 35
 
3.3%
8 35
 
3.3%
2 35
 
3.3%
12 35
 
3.3%
10 35
 
3.3%
9 35
 
3.3%
11 35
 
3.3%
7 35
 
3.3%
6 35
 
3.3%
5 35
 
3.3%
Other values (21) 697
66.6%
ValueCountFrequency (%)
1 35
3.3%
2 35
3.3%
3 35
3.3%
4 35
3.3%
5 35
3.3%
6 35
3.3%
7 35
3.3%
8 35
3.3%
9 35
3.3%
10 35
3.3%
ValueCountFrequency (%)
31 20
1.9%
30 31
3.0%
29 32
3.1%
28 34
3.2%
27 34
3.2%
26 34
3.2%
25 34
3.2%
24 34
3.2%
23 34
3.2%
22 34
3.2%
2024-04-22T16:46:33.474282image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ACF and PACF

Day_Of_Year
Numeric time series

NON STATIONARY  SEASONAL 

Distinct366
Distinct (%)35.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean175.78032
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Memory size16.4 KiB
2024-04-22T16:46:34.456573image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile18
Q188
median175
Q3262
95-th percentile339.7
Maximum366
Range365
Interquartile range (IQR)174

Descriptive statistics

Standard deviation102.09362
Coefficient of variation (CV)0.5808023
Kurtosis-1.1506947
Mean175.78032
Median Absolute Deviation (MAD)87
Skewness0.040276136
Sum184042
Variance10423.107
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.08480824932
2024-04-22T16:46:34.672507image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2024-04-22T16:46:35.165786image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Gap statistics

number of gaps0
min0
max0
mean0
std0
2024-04-22T16:46:35.361164image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
1 3
 
0.3%
210 3
 
0.3%
217 3
 
0.3%
216 3
 
0.3%
215 3
 
0.3%
214 3
 
0.3%
213 3
 
0.3%
212 3
 
0.3%
211 3
 
0.3%
209 3
 
0.3%
Other values (356) 1017
97.1%
ValueCountFrequency (%)
1 3
0.3%
2 3
0.3%
3 3
0.3%
4 3
0.3%
5 3
0.3%
6 3
0.3%
7 3
0.3%
8 3
0.3%
9 3
0.3%
10 3
0.3%
ValueCountFrequency (%)
366 1
0.1%
365 2
0.2%
364 2
0.2%
363 2
0.2%
362 2
0.2%
361 2
0.2%
360 2
0.2%
359 2
0.2%
358 2
0.2%
357 2
0.2%
2024-04-22T16:46:34.849817image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ACF and PACF

Week
Numeric time series

NON STATIONARY  SEASONAL 

Distinct53
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.541547
Minimum1
Maximum53
Zeros0
Zeros (%)0.0%
Memory size16.4 KiB
2024-04-22T16:46:35.711182image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q113
median25
Q338
95-th percentile49
Maximum53
Range52
Interquartile range (IQR)25

Descriptive statistics

Standard deviation14.584623
Coefficient of variation (CV)0.57101564
Kurtosis-1.1506374
Mean25.541547
Median Absolute Deviation (MAD)12
Skewness0.040925543
Sum26742
Variance212.71123
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.01882483098
2024-04-22T16:46:35.925635image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2024-04-22T16:46:36.430490image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Gap statistics

number of gaps0
min0
max0
mean0
std0
2024-04-22T16:46:36.603823image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
26 21
 
2.0%
35 21
 
2.0%
1 21
 
2.0%
27 21
 
2.0%
28 21
 
2.0%
29 21
 
2.0%
30 21
 
2.0%
31 21
 
2.0%
32 21
 
2.0%
33 21
 
2.0%
Other values (43) 837
79.9%
ValueCountFrequency (%)
1 21
2.0%
2 21
2.0%
3 21
2.0%
4 21
2.0%
5 21
2.0%
6 21
2.0%
7 21
2.0%
8 21
2.0%
9 21
2.0%
10 21
2.0%
ValueCountFrequency (%)
53 3
 
0.3%
52 14
1.3%
51 14
1.3%
50 14
1.3%
49 14
1.3%
48 14
1.3%
47 14
1.3%
46 15
1.4%
45 21
2.0%
44 21
2.0%
2024-04-22T16:46:36.111798image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ACF and PACF

Season
Categorical

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
Spring
279 
Summer
279 
Winter
257 
Autumn
232 

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6282
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
Spring 279
26.6%
Summer 279
26.6%
Winter 257
24.5%
Autumn 232
22.2%

Length

2024-04-22T16:46:36.808735image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T16:46:36.899434image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
spring 279
26.6%
summer 279
26.6%
winter 257
24.5%
autumn 232
22.2%

Most occurring characters

ValueCountFrequency (%)
r 815
13.0%
m 790
12.6%
n 768
12.2%
u 743
11.8%
S 558
8.9%
i 536
8.5%
e 536
8.5%
t 489
7.8%
p 279
 
4.4%
g 279
 
4.4%
Other values (2) 489
7.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5235
83.3%
Uppercase Letter 1047
 
16.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 815
15.6%
m 790
15.1%
n 768
14.7%
u 743
14.2%
i 536
10.2%
e 536
10.2%
t 489
9.3%
p 279
 
5.3%
g 279
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
S 558
53.3%
W 257
24.5%
A 232
22.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 6282
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 815
13.0%
m 790
12.6%
n 768
12.2%
u 743
11.8%
S 558
8.9%
i 536
8.5%
e 536
8.5%
t 489
7.8%
p 279
 
4.4%
g 279
 
4.4%
Other values (2) 489
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6282
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 815
13.0%
m 790
12.6%
n 768
12.2%
u 743
11.8%
S 558
8.9%
i 536
8.5%
e 536
8.5%
t 489
7.8%
p 279
 
4.4%
g 279
 
4.4%
Other values (2) 489
7.8%