I have a pandas dataframe in which one column of text strings contains comma-separated values. I want to split each CSV field and create a new row per entry (assume that CSV are clean and need only be split on ‘,’). For example, a should become b:
I need to find unique rows in a numpy.array.
I want to apply my custom function (it uses an if-else ladder) to these six columns (ERI_Hispanic, ERI_AmerInd_AKNatv, ERI_Asian, ERI_Black_Afr.Amer, ERI_HI_PacIsl, ERI_White) in each row of my dataframe.
Lets say I have a Python Numpy array a.
This is the error I am getting and, as far as I can tell, there is nothing useful on the error link to fix this.
I’m curious, whether there is any way to print formatted numpy.arrays, e.g., in a way similar to this:
What are the advantages of NumPy over regular Python lists?
I have two numpy arrays that define the x and y axes of a grid. For example:
I’m trying to run over the parameters space of a 6 parameter function to study its numerical behavior before trying to do anything complex with it, so I’m searching for an efficient way to do this.
This Python code: