It can also help you create SharePoint or SharePoint-related demos. You can create data to test SharePoint and to simulate and recreate specific scenarios in which you use multiple SharePoint features. The tool can be used to populate SharePoint On-Premises or SharePoint Online.
To avoid manually creating a mock SharePoint environment or banging your head against the wall coming up with a PowerShell script, try generating sample data with Acceleratio.SPDG.Īcceleratio.SPDG is an open-source tool designed to generate mock data for SharePoint.
#Demo data generator how to
How to generate sample content and populate SharePoint? This can be done manually, by entering mock data into your SharePoint, but creating all the users, fake web applications, sites, and site collections can take a lot of time.įurthermore, it will be hard to successfully use all the SharePoint features in order to test out their capabilities fully or simulate specific scenarios. When developing and testing tools for SharePoint, it’s always good to have your SharePoint stocked with proper demo content. Now let’s discuss Acceleratio.SPDG it a bit further. Whether you need sample data for testing purposes or demos, we’ve come up with a tool that can help generate mock SharePoint data in just a few minutes. | 5 | 68 | 21900 | 2 | 31300 | 3 | 0 | 1 | 0.Many of you have probably been wondering how to create sample data and populate SharePoint. | user_id | age | car_price | car_age | income | education | gender | crashes | probability | true_labes | TypeError: import_optional_dependency() got an unexpected keyword argument 'errors' > 3 ne = import_optional_dependency("numexpr", errors="warn") ~\anaconda3\lib\site-packages\pandas\core\computation\check.py in ġ from pat._optional import import_optional_dependency
~\anaconda3\lib\site-packages\pandas\core\computation\expressions.py in ~\anaconda3\lib\site-packages\pandas\core\ops\array_ops.py in _na_arithmetic_op(left, right, op, is_cmp)ġ38 def _na_arithmetic_op(left, right, op, is_cmp: bool = False):ġ40 Return the result of evaluating op on the passed in values. ~\anaconda3\lib\site-packages\pandas\core\ops\array_ops.py in comparison_op(left, right, op)Ģ48 lvalues = ensure_wrapped_if_datetimelike(left)Ģ49 rvalues = ensure_wrapped_if_datetimelike(right)Ģ51 rvalues = lib.item_from_zerodim(rvalues) ~\anaconda3\lib\site-packages\pandas\core\series.py in _cmp_method(self, other, op) ~\anaconda3\lib\site-packages\pandas\core\arraylike.py in _lt_(self, other)ģ6 return self._cmp_method(other, operator.ne) TypeError Traceback (most recent call last)Ĥ plt.rcParams = (10, 6) If temp = possibilities or temp = possibilities or temp = possibilities: If temp = possibilities or temp = possibilities:
tried with lru_cache for recursion, didn't work. Once there is a gap with a couple of zeros geometric progression will not help, I would require the previous fig(from Cache) to recalculate Traded_q.
#Demo data generator code
Turns out the code is generating correct Traded_quantity when there is no zero in Marker. Whenever there will be a BUY, the traded quantity will be calculated using the last batch from Traded_quantity times turtle. For 0th Row, Traded_quantity should be zero (because the Marker is zero)įor 1st Row, Traded_quantity should be (1x1) + (1x2) = 3 (Marker 2 will be split into 1 and 1, First 1 will be multiplied with the base_quantity>1x1, Second 1 will be multiplied with the result from first 1 times turtle>1x2), then we make a sum of these two numbers)įor 2nd Row, Traded_quantity should be zero (because the Marker is zero)įor 3rd Row, Traded_quantity should be (2x2) = 4(Marker 1 will be multiplied with the last split from row 1 time turtle i.e 2x2)įor 4th Row, Traded_quantity should be zero(because the Marker is zero)įor 5th Row, Traded_quantity should be (4x2)+(4x2x2)+(4x2x2x2) = 56(Marker 3 will be split into 1,1 and 1, First 1 will be multiplied with the last split from row3 times turtle >4x2, Second 1 will be multiplied with the result from first 1 with turtle>8x2), third 1 will be multiplied with the result from second 1 with turtle>16x2) then we make a sum of these three numbers)įor 6th Row, Traded_quantity should be (32x2)+(32x2x2)+(32x2x2x2)+(32x2x2x2x2)+(32x2x2x2x2x2) = 8128