Overview

Dataset statistics

Number of variables5
Number of observations500
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.7 KiB
Average record size in memory40.3 B

Variable types

Numeric5

Alerts

A has unique valuesUnique
B has unique valuesUnique
C has unique valuesUnique
D has unique valuesUnique
E has unique valuesUnique

Reproduction

Analysis started2023-10-17 16:52:27.193805
Analysis finished2023-10-17 16:52:28.795854
Duration1.6 second
Software versionydata-profiling vv4.6.0
Download configurationconfig.json

Variables

A
Real number (ℝ)

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.49543507
Minimum0.00030045276
Maximum0.99973954
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2023-10-17T16:52:28.845829image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum0.00030045276
5-th percentile0.05268262
Q10.23518649
median0.49553595
Q30.73297498
95-th percentile0.95502914
Maximum0.99973954
Range0.99943908
Interquartile range (IQR)0.49778849

Descriptive statistics

Standard deviation0.28888303
Coefficient of variation (CV)0.58308958
Kurtosis-1.2077931
Mean0.49543507
Median Absolute Deviation (MAD)0.24744852
Skewness0.0073463686
Sum247.71753
Variance0.083453404
MonotonicityNot monotonic
2023-10-17T16:52:28.937105image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.9123773696 1
 
0.2%
0.1822912661 1
 
0.2%
0.04221593086 1
 
0.2%
0.437539841 1
 
0.2%
0.4949160024 1
 
0.2%
0.7430619116 1
 
0.2%
0.747026617 1
 
0.2%
0.9922498346 1
 
0.2%
0.2653240534 1
 
0.2%
0.8392998618 1
 
0.2%
Other values (490) 490
98.0%
ValueCountFrequency (%)
0.0003004527611 1
0.2%
0.0006595066706 1
0.2%
0.001221379946 1
0.2%
0.001778018246 1
0.2%
0.004483759248 1
0.2%
0.007395285132 1
0.2%
0.0170238208 1
0.2%
0.02269142051 1
0.2%
0.02439892344 1
0.2%
0.02572323172 1
0.2%
ValueCountFrequency (%)
0.9997395371 1
0.2%
0.9965352575 1
0.2%
0.9959153121 1
0.2%
0.993388122 1
0.2%
0.9928348636 1
0.2%
0.9922498346 1
0.2%
0.9860100322 1
0.2%
0.9842306898 1
0.2%
0.9830847127 1
0.2%
0.9827384227 1
0.2%

B
Real number (ℝ)

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.49864636
Minimum0.0007974987
Maximum0.99616033
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2023-10-17T16:52:29.096355image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum0.0007974987
5-th percentile0.058643133
Q10.24987986
median0.49572387
Q30.75515206
95-th percentile0.94014462
Maximum0.99616033
Range0.99536283
Interquartile range (IQR)0.5052722

Descriptive statistics

Standard deviation0.28646773
Coefficient of variation (CV)0.57449078
Kurtosis-1.2158301
Mean0.49864636
Median Absolute Deviation (MAD)0.25843702
Skewness-0.018562855
Sum249.32318
Variance0.082063762
MonotonicityNot monotonic
2023-10-17T16:52:29.187496image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.3494372827 1
 
0.2%
0.5488344279 1
 
0.2%
0.04437753658 1
 
0.2%
0.4292897527 1
 
0.2%
0.2003538164 1
 
0.2%
0.1656711917 1
 
0.2%
0.9863358819 1
 
0.2%
0.3053478316 1
 
0.2%
0.2620572899 1
 
0.2%
0.007681955407 1
 
0.2%
Other values (490) 490
98.0%
ValueCountFrequency (%)
0.0007974987036 1
0.2%
0.0008565128505 1
0.2%
0.005774322909 1
0.2%
0.006829200229 1
0.2%
0.007681955407 1
0.2%
0.009000283808 1
0.2%
0.009150412193 1
0.2%
0.01012503001 1
0.2%
0.01265530646 1
0.2%
0.01326520112 1
0.2%
ValueCountFrequency (%)
0.9961603272 1
0.2%
0.9933206768 1
0.2%
0.9907701455 1
0.2%
0.9895438873 1
0.2%
0.9864222141 1
0.2%
0.9863358819 1
0.2%
0.9819203886 1
0.2%
0.9799585522 1
0.2%
0.9771914901 1
0.2%
0.9768014768 1
0.2%

C
Real number (ℝ)

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.50880604
Minimum0.0022439975
Maximum0.99924172
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2023-10-17T16:52:29.276044image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum0.0022439975
5-th percentile0.040830953
Q10.25849105
median0.51170531
Q30.75992126
95-th percentile0.95457249
Maximum0.99924172
Range0.99699772
Interquartile range (IQR)0.5014302

Descriptive statistics

Standard deviation0.29312895
Coefficient of variation (CV)0.57611137
Kurtosis-1.1687135
Mean0.50880604
Median Absolute Deviation (MAD)0.25011724
Skewness-0.046475317
Sum254.40302
Variance0.08592458
MonotonicityNot monotonic
2023-10-17T16:52:29.366383image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.4066392478 1
 
0.2%
0.2306712848 1
 
0.2%
0.04836361858 1
 
0.2%
0.681241831 1
 
0.2%
0.002243997535 1
 
0.2%
0.3631408075 1
 
0.2%
0.1128628977 1
 
0.2%
0.6200980028 1
 
0.2%
0.1974666706 1
 
0.2%
0.6357556883 1
 
0.2%
Other values (490) 490
98.0%
ValueCountFrequency (%)
0.002243997535 1
0.2%
0.003157928075 1
0.2%
0.004925086114 1
0.2%
0.007244102835 1
0.2%
0.01018886619 1
0.2%
0.01077130788 1
0.2%
0.01089866988 1
0.2%
0.01167588753 1
0.2%
0.0118852124 1
0.2%
0.01698453111 1
0.2%
ValueCountFrequency (%)
0.9992417151 1
0.2%
0.9990638616 1
0.2%
0.9981999699 1
0.2%
0.9975971491 1
0.2%
0.9970930383 1
0.2%
0.9943912363 1
0.2%
0.9875333907 1
0.2%
0.9871538226 1
0.2%
0.9868653218 1
0.2%
0.9864069388 1
0.2%

D
Real number (ℝ)

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.49653887
Minimum0.00085668269
Maximum0.99989941
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2023-10-17T16:52:29.455168image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum0.00085668269
5-th percentile0.04431548
Q10.26010052
median0.50213364
Q30.73455927
95-th percentile0.94867395
Maximum0.99989941
Range0.99904273
Interquartile range (IQR)0.47445874

Descriptive statistics

Standard deviation0.28488407
Coefficient of variation (CV)0.57373972
Kurtosis-1.1618095
Mean0.49653887
Median Absolute Deviation (MAD)0.23792519
Skewness-0.040668012
Sum248.26944
Variance0.081158936
MonotonicityNot monotonic
2023-10-17T16:52:29.546000image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.6627296453 1
 
0.2%
0.6406925938 1
 
0.2%
0.798758382 1
 
0.2%
0.5099180337 1
 
0.2%
0.6802140079 1
 
0.2%
0.8276290968 1
 
0.2%
0.6256638755 1
 
0.2%
0.08904203394 1
 
0.2%
0.9702698035 1
 
0.2%
0.4845237306 1
 
0.2%
Other values (490) 490
98.0%
ValueCountFrequency (%)
0.0008566826885 1
0.2%
0.002443802794 1
0.2%
0.003126000344 1
0.2%
0.003132595047 1
0.2%
0.003227453535 1
0.2%
0.003299138128 1
0.2%
0.01013139628 1
0.2%
0.01341571943 1
0.2%
0.01463371977 1
0.2%
0.01600607501 1
0.2%
ValueCountFrequency (%)
0.9998994079 1
0.2%
0.9937614152 1
0.2%
0.9888264496 1
0.2%
0.9878607869 1
0.2%
0.9832224172 1
0.2%
0.9795803848 1
0.2%
0.9795381199 1
0.2%
0.9779773242 1
0.2%
0.9779238728 1
0.2%
0.9720170904 1
0.2%

E
Real number (ℝ)

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.49030725
Minimum0.0018877418
Maximum0.99918564
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2023-10-17T16:52:29.635172image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum0.0018877418
5-th percentile0.045118727
Q10.231728
median0.48869632
Q30.7329397
95-th percentile0.95545469
Maximum0.99918564
Range0.9972979
Interquartile range (IQR)0.50121169

Descriptive statistics

Standard deviation0.29354232
Coefficient of variation (CV)0.59869056
Kurtosis-1.2237054
Mean0.49030725
Median Absolute Deviation (MAD)0.25060421
Skewness0.040512947
Sum245.15362
Variance0.086167094
MonotonicityNot monotonic
2023-10-17T16:52:29.725208image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.392554122 1
 
0.2%
0.9887538291 1
 
0.2%
0.2328846927 1
 
0.2%
0.853194561 1
 
0.2%
0.3509521174 1
 
0.2%
0.2654463515 1
 
0.2%
0.4883977585 1
 
0.2%
0.3122929266 1
 
0.2%
0.1738920924 1
 
0.2%
0.1772971773 1
 
0.2%
Other values (490) 490
98.0%
ValueCountFrequency (%)
0.001887741751 1
0.2%
0.002054330638 1
0.2%
0.007129799923 1
0.2%
0.01202354295 1
0.2%
0.017308705 1
0.2%
0.02150966904 1
0.2%
0.02703845558 1
0.2%
0.02792648803 1
0.2%
0.0286561577 1
0.2%
0.02923416677 1
0.2%
ValueCountFrequency (%)
0.9991856368 1
0.2%
0.9887538291 1
0.2%
0.9869227748 1
0.2%
0.9823019479 1
0.2%
0.981953111 1
0.2%
0.9811818931 1
0.2%
0.9798882589 1
0.2%
0.9797712342 1
0.2%
0.978799562 1
0.2%
0.9785741114 1
0.2%

Interactions

2023-10-17T16:52:28.425707image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-17T16:52:27.273268image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-17T16:52:27.609462image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-17T16:52:27.880992image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-17T16:52:28.155089image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-17T16:52:28.480033image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-17T16:52:27.393448image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-17T16:52:27.663276image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-17T16:52:27.934849image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-17T16:52:28.210066image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-17T16:52:28.533785image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-17T16:52:27.447091image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-17T16:52:27.719813image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-17T16:52:27.989453image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-17T16:52:28.263930image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-17T16:52:28.588221image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-17T16:52:27.501313image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-17T16:52:27.773128image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-17T16:52:28.045423image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-17T16:52:28.318782image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-17T16:52:28.641835image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-17T16:52:27.555235image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-17T16:52:27.827466image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-17T16:52:28.100878image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-17T16:52:28.372169image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Correlations

2023-10-17T16:52:29.783001image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ABCDE
A1.0000.011-0.026-0.005-0.024
B0.0111.000-0.076-0.0060.041
C-0.026-0.0761.000-0.1220.034
D-0.005-0.006-0.1221.000-0.009
E-0.0240.0410.034-0.0091.000

Missing values

2023-10-17T16:52:28.714762image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
A simple visualization of nullity by column.
2023-10-17T16:52:28.772509image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

ABCDE
00.9123770.3494370.4066390.6627300.392554
10.1393420.6138170.0397600.3471750.605141
20.8053400.5872260.2661070.5875230.107320
30.3978640.0068290.8113550.1176180.655246
40.0501820.6228300.8066980.2945640.746388
50.7265920.7541760.4149720.8642890.716423
60.7074570.5648150.3672600.9489590.192186
70.1206650.0090000.6509860.7627780.312734
80.9620570.4803880.3020800.0415560.742361
90.7408600.6827650.2906250.3427820.419509
ABCDE
4900.0756700.9933210.1835950.1819840.731698
4910.7152440.2404620.5326050.1806790.261704
4920.6594590.4425460.4366890.8202040.028656
4930.8024320.5236850.0308330.7393170.021510
4940.1157430.9550090.0049250.8140600.914674
4950.2835330.5049290.6203170.6253690.109938
4960.7359710.0227320.2572090.7402900.410284
4970.6191690.3668630.7202000.9538510.927936
4980.2357640.8095900.7829740.4617640.644029
4990.8854510.6211760.2078000.5018940.932532