raphaelvallat

import numpy as np
import multiprocessing
from joblib import Parallel, delayed
from scipy.spatial.distance import pdist, squareform

def _dcorr(y, n2, A, dcov2_xx):
    """Helper function for distance correlation bootstrapping.
    """
    # Pairwise Euclidean distances
    b = squareform(pdist(y, metric='euclidean'))

raphaelvallat

'''
Non-parametric computation of entropy and mutual-information

Adapted by G Varoquaux for code created by R Brette, itself
from several papers (see in the code).

These computations rely on nearest-neighbor statistics
'''
import numpy as np

raphaelvallat

# List unique values in a DataFrame column
# h/t @makmanalp for the updated syntax!
df['Column Name'].unique()

# Convert Series datatype to numeric (will error if column has non-numeric values)
# h/t @makmanalp
pd.to_numeric(df['Column Name'])

# Convert Series datatype to numeric, changing non-numeric values to NaN
# h/t @makmanalp for the updated syntax!