How to plot empirical cdf (ecdf)
How can I plot the empirical CDF of an array of numbers in matplotlib in Python? I’m looking for the cdf analog of pylab’s “hist” function.
scipy
Sparse matrix slicing using list of int
I’m writing a machine learning algorithm on huge & sparse data (my matrix is of shape (347, 5 416 812 801) but very sparse, only 0.13% of the data is non zero.
ImportError: cannot import name NUMPY_MKL
I am trying to run the following simple code
plotting results of hierarchical clustering ontop of a matrix of data in python
How can I plot a dendrogram right on top of a matrix of values, reordered appropriately to reflect the clustering, in Python? An example is the following figure:
How to calculate the inverse of the normal cumulative distribution function in python?
How do I calculate the inverse of the cumulative distribution function (CDF) of the normal distribution in Python?
Fitting a closed curve to a set of points
I have a set of points pts which form a loop and it looks like this:
How to share numpy random state of a parent process with child processes?
I set numpy random seed at the beginning of my program. During the program execution I run a function multiple times using multiprocessing.Process. The function uses numpy random functions to draw random numbers. The problem is that Process gets a copy of the current environment. Therefore, each process is running independently and they all start with the same random seed as the parent environment.
Populate a Pandas SparseDataFrame from a SciPy Sparse Matrix
I noticed Pandas now has support for Sparse Matrices and Arrays. Currently, I create DataFrame()s like this:
Fitting a Normal distribution to 1D data
I have a 1 dimensional array. I can compute the “mean” and “standard deviation” of this sample and plot the “Normal distribution” but I have a problem:
How to display a 3D plot of a 3D array isosurface in matplotlib mplot3D or similar?
I have a 3-dimensional numpy array. I’d like to display (in matplotlib) a nice 3D plot of an isosurface of this array (or more strictly, display an isosurface of the 3D scalar field defined by interpolating between the sample points).