python numpy ndarray element-wise mean
You can just use np.mean directly:
>>> np.mean([a, b, c], axis=0)array([ 30., 20., 30.])
Pandas DataFrames have built in operations to get column and row means. The following code may help you:
import pandas and numpyimport pandas as pdimport numpy as np# Define a DataFramedf = pd.DataFrame([np.arange(1,5), np.arange(6,10),np.arange(11,15)])# Get column means by adding the '.mean' argument# to the name of your pandas Data Frame# and specifying the axiscolumn_means = df.mean(axis = 0)'''print(column_means)0 6.01 7.02 8.03 9.0dtype: float64''' # Get row means by adding the '.mean' argument# to the name of your pandas Data Frame# and specifying the axisrow_means = df.mean(axis = 1)'''print(row_means)0 2.51 7.52 12.5dtype: float64'''