NumPy Commands
Importing NumPy
Before any of the following commands are used, the NumPy library must be imported into Sage. This is done with the command
import numpy
You may also assign numpy a different name for convenience, such as np, using as:
import numpy as np
After importation, any numpy commands must be preceded by the name of the import and a dot operator like so: np.array()
NumPy Commands
This section assumes a basic knowledge of Python 2.
- Numpy Constants Constants defined in the NumPy package.
- Importing specialized NumPy packages Importing NumPy subclass packages.
N-Dimensional Arrays
Basic commands for NumPy's core function, the ndarray object.
- The N-Dimensional Array Using NumPy to create an array of n dimensions.
- Indexing in ndarray objects Using indices for multidimensional arrays.
- Accessing Attributes of N-Dimensional Arrays How to access information about an ndarray object.
- Evaluating Booleans in an N-Dimensional Array Using the all and any methods to evaluate an ndarray of bool data.
- Sum and Prod commands on ndarrays Using the ndarray sum and prod commands.
Statistics
- Finding the minimum and maximum of an ndarray object How to find the minimum and maximum values of an ndarray object.
- Finding the standard deviation and variance of an ndarray Using the std and var commands to find the standard deviation and variance of an ndarray.
- Finding the percentile of a value in an ndarray Using the percentile and nanpercentile commands to find the percentile of an item in an ndarray.
- Median of an ndarray Finding the median of an ndarray object.
- Average of an ndarray Finding the average of an ndarray object.
Boolean Logic in NumPy
- Evaluating Booleans in an N-Dimensional Array Using the all and any methods to evaluate an ndarray of bool data.
- Testing ndarray objects for equivalence Using the array-equiv command to test ndarray objects for equivalence.
- Testing for Infinite Values Using numpy.isinf to test a value for infinity.
- Testing for Finite Values Using numpy.isfinite to test a value for finiteness.
- Testing for NaN values Using numpy.isnan to test for a Not a Number value, such as $\frac{1}{0}$.