動作環境
ideone (Python 3.5)
@ Scipy lecture notes, Edition 2017.1
https://www.scipy-lectures.org/_downloads/ScipyLectures-simple.pdf
p49
numpyのlookfor()というのがあるようだ。
試してみた。
import numpy as np
np.lookfor('create array')
run
Search results for 'create array'
---------------------------------
numpy.array
Create an array.
numpy.memmap
Create a memory-map to an array stored in a *binary* file on disk.
numpy.diagflat
Create a two-dimensional array with the flattened input as a diagonal.
numpy.fromiter
Create a new 1-dimensional array from an iterable object.
numpy.partition
Return a partitioned copy of an array.
numpy.ctypeslib.as_array
Create a numpy array from a ctypes array or a ctypes POINTER.
numpy.ma.diagflat
Create a two-dimensional array with the flattened input as a diagonal.
numpy.ma.make_mask
Create a boolean mask from an array.
numpy.ctypeslib.as_ctypes
Create and return a ctypes object from a numpy array. Actually
numpy.ma.mrecords.fromarrays
Creates a mrecarray from a (flat) list of masked arrays.
numpy.lib.format.open_memmap
Open a .npy file as a memory-mapped array.
numpy.ma.MaskedArray.__new__
Create a new masked array from scratch.
numpy.lib.arrayterator.Arrayterator
Buffered iterator for big arrays.
numpy.ma.mrecords.fromtextfile
Creates a mrecarray from data stored in the file `filename`.
numpy.asarray
Convert the input to an array.
numpy.ndarray
ndarray(shape, dtype=float, buffer=None, offset=0,
numpy.recarray
Construct an ndarray that allows field access using attributes.
numpy.chararray
chararray(shape, itemsize=1, unicode=False, buffer=None, offset=0,
numpy.pad
Pads an array.
numpy.asanyarray
Convert the input to an ndarray, but pass ndarray subclasses through.
numpy.copy
Return an array copy of the given object.
numpy.diag
Extract a diagonal or construct a diagonal array.
numpy.load
Load arrays or pickled objects from ``.npy``, ``.npz`` or pickled files.
numpy.sort
Return a sorted copy of an array.
numpy.array_equiv
Returns True if input arrays are shape consistent and all elements equal.
numpy.dtype
Create a data type object.
numpy.choose
Construct an array from an index array and a set of arrays to choose from.
numpy.nditer
Efficient multi-dimensional iterator object to iterate over arrays.
numpy.swapaxes
Interchange two axes of an array.
numpy.full_like
Return a full array with the same shape and type as a given array.
numpy.ones_like
Return an array of ones with the same shape and type as a given array.
numpy.empty_like
Return a new array with the same shape and type as a given array.
numpy.zeros_like
Return an array of zeros with the same shape and type as a given array.
numpy.asarray_chkfinite
Convert the input to an array, checking for NaNs or Infs.
numpy.diag_indices
Return the indices to access the main diagonal of an array.
numpy.chararray.tolist
a.tolist()
numpy.ma.choose
Use an index array to construct a new array from a set of choices.
numpy.savez_compressed
Save several arrays into a single file in compressed ``.npz`` format.
numpy.matlib.rand
Return a matrix of random values with given shape.
numpy.ma.empty_like
Return a new array with the same shape and type as a given array.
numpy.ma.make_mask_none
Return a boolean mask of the given shape, filled with False.
numpy.ma.mrecords.fromrecords
Creates a MaskedRecords from a list of records.
numpy.around
Evenly round to the given number of decimals.
numpy.source
Print or write to a file the source code for a NumPy object.
numpy.diagonal
Return specified diagonals.
numpy.einsum_path
Evaluates the lowest cost contraction order for an einsum expression by
numpy.histogram2d
Compute the bi-dimensional histogram of two data samples.
numpy.fft.ifft
Compute the one-dimensional inverse discrete Fourier Transform.
numpy.fft.ifftn
Compute the N-dimensional inverse discrete Fourier Transform.
numpy.busdaycalendar
A business day calendar object that efficiently stores information