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I have the following code in Python Jupyter:

Julia Code:

Given a dataframe with columns "a", "b", and "value", I'd like to sample N rows from each pair of ("a", "b"). In python pandas, this is easy to do with the following syntax:

I am trying to create a documentation for a Julia module using Documenter.jl. Now I imported a module which documenter cannot find for some reason. More explicitly: I imported SparseArrays.jl via import SparseArrays and am referencing SparseArrays.AbstractSparseArray in a docstring. (I also have SparseArrays.jl installed.) Yet I get ERROR: LoadError: UndefVarError: SparseArrays not defined. What's the reason and how can I fix this?

EDIT: This is what the relevant parts of the code look like:

In REPL mode, Julia lets you type a semicolon and run shell commands, i.e.

I'm trying to learn Recurrent Neural Networks (RNN) with Flux.jl in Julia by following along some tutorials, like Char RNN from the FluxML/model-zoo.

I managed to build and train a model containing some RNN cells, but am failing to evaluate the model after training.

Can someone point out what I'm missing for this code to evaluate a simple (untrained) RNN?

In a heatmap, how could I create a three-color gradient, with blue for negative values, red for positive values and white for zero, such that with many zero values, much of the heatmap would be white (and not light red as with the default gradient).

For the following example how do I compute the percentile / probability values / tail area in julia

I have a DataFrame in Julia and I want to create a new column that represents the difference between consecutive rows in a specific column. In python pandas, I would simply use df.series.diff(). Is there a Julia equivelant?

For example: