Convert array of indices to 1-hot encoded numpy array
Let’s say I have a 1d numpy array
Let’s say I have a 1d numpy array
I am reading two columns of a csv file using pandas readcsv() and then assigning the values to a dictionary. The columns contain strings of numbers and letters. Occasionally there are cases where a cell is empty. In my opinion, the value read to that dictionary entry should be None but instead nan is assigned. Surely None is more descriptive of an empty cell as it has a null value, whereas nan just says that the value read is not a number.
I have installed Python 2.5.4, Numpy 1.5.0 win32, Matplotlib 1.0.0 win32, pywin32 218. Still not able to plot graphs in Python. Here is the error I am getting :
While implementing a Kronecker-product for pedagogical reasons (without using the obvious and readily available np.kron()), I obtained a 4 dimensional array as an intermediate result, which I’ve to reshape to get the final result.
The implicit conversion of a Python sequence of variable-length lists into a NumPy array cause the array to be of type object.
I have a set of data and I want to compare which line describes it best (polynomials of different orders, exponential or logarithmic).
I have a list of 3-tuples representing a set of points in 3D space. I want to plot a surface that covers all these points.
How can I get from a plot in Python an exact value on y – axis? I have two arrays vertical_data and gradient(temperature_data) and I plotted them as:
How do I convert a NumPy array to a Python List (for example [[1,2,3],[4,5,6]] ), and do it reasonably fast?
I’ve got a strange situation.