Numpy > np.lookfor('create array') > create arrayを含むdocstringを持つ関数を列挙する

```txt: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。

- [numpy.lookfor @ SciPy.org](https://docs.scipy.org/doc/numpy/reference/generated/numpy.lookfor.html)


試してみた。

https://ideone.com/nACl43

```py
import numpy as np
 
np.lookfor('create array')
```

```txt: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
```