3. Numpy

1. numpy(numerical python)

 - Python data analysis package for scientific computing
 - Provides various useful functionalities necessary for handling multidimensional arrays
 - Essential to master along with pandas for data analysis

 

2. ndarray

 - Comprehensive multidimensional array capable of containing data of the same data type
 - All elements of the ndarray must use the same data type, and the dimension of the array is called rank, while the size of each dimension is represented as a tuple called shape.
 - Example: In a 2-dimensional array with 3 rows and 2 columns, the rank is 3, and the shape is (3,2).

 

3. Example

  - numpy.array

 - numpy.arange(start value, end value, interval) or arange(end value)

 

 - reshape(a, newshape, order='C')

   -- Gives a new shape to an array without changing its data.

 

 - numpy. add(data1,data2)

 - numpy. subtract(data1,data2)

 - numpy.multiply(data1,data2)

 - numpy.dot(data1,data2)

 

 

320x100

 

Operation	Description
copyto(dst, src[, casting, where])	Copies values from one array to another, broadcasting as necessary.
shape(a)	Return the shape of an array.
reshape(a, newshape[, order])	Gives a new shape to an array without changing its data.
ravel(a[, order])	Return a contiguous flattened array.
ndarray.flat	A 1-D iterator over the array.
ndarray.flatten([order])	Return a copy of the array collapsed into one dimension.
moveaxis(a, source, destination)	Move axes of an array to new positions.
rollaxis(a, axis[, start])	Roll the specified axis backwards, until it lies in a given position.
swapaxes(a, axis1, axis2)	Interchange two axes of an array.
ndarray.T	View of the transposed array.
transpose(a[, axes])	Returns an array with axes transposed.
atleast_1d(*arys)	Convert inputs to arrays with at least one dimension.
atleast_2d(*arys)	View inputs as arrays with at least two dimensions.
atleast_3d(*arys)	View inputs as arrays with at least three dimensions.
broadcast	Produce an object that mimics broadcasting.
broadcast_to(array, shape[, subok])	Broadcast an array to a new shape.
broadcast_arrays(*args[, subok])	Broadcast any number of arrays against each other.
expand_dims(a, axis)	Expand the shape of an array.
squeeze(a[, axis])	Remove axes of length one from a.
asarray(a[, dtype, order, like])	Convert the input to an array.
asanyarray(a[, dtype, order, like])	Convert the input to an ndarray, but pass ndarray subclasses through.
asmatrix(data[, dtype])	Interpret the input as a matrix.
asfarray(a[, dtype])	Return an array converted to a float type.
asfortranarray(a[, dtype])	Return an array (ndim >= 1) laid out in Fortran order in memory.
ascontiguousarray(a[, dtype])	Return a contiguous array (ndim >= 1) in memory (C order).
asarray_chkfinite(a[, dtype, order])	Convert the input to an array, checking for NaNs or Infs.
require(a[, dtype, requirements, like])	Return an ndarray of the provided type that satisfies requirements.
concatenate([axis, out, dtype, casting])	Join a sequence of arrays along an existing axis.
stack(arrays[, axis, out, dtype, casting])	Join a sequence of arrays along a new axis.
block(arrays)	Assemble an nd-array from nested lists of blocks.
vstack(tup, *[, dtype, casting])	Stack arrays in sequence vertically (row wise).
hstack(tup, *[, dtype, casting])	Stack arrays in sequence horizontally (column wise).
dstack(tup)	Stack arrays in sequence depth wise (along third axis).
column_stack(tup)	Stack 1-D arrays as columns into a 2-D array.
row_stack(tup, *[, dtype, casting])	Stack arrays in sequence vertically (row wise).
split(ary, indices_or_sections[, axis])	Split an array into multiple sub-arrays as views into ary.
array_split(ary, indices_or_sections[, axis])	Split an array into multiple sub-arrays.
dsplit(ary, indices_or_sections)	Split array into multiple sub-arrays along the 3rd axis (depth).
hsplit(ary, indices_or_sections)	Split an array into multiple sub-arrays horizontally (column-wise).
vsplit(ary, indices_or_sections)	Split an array into multiple sub-arrays vertically (row-wise).
tile(A, reps)	Construct an array by repeating A the number of times given by reps.
repeat(a, repeats[, axis])	Repeat each element of an array after themselves.
delete(arr, obj[, axis])	Return a new array with sub-arrays along an axis deleted.
insert(arr, obj, values[, axis])	Insert values along the given axis before the given indices.
append(arr, values[, axis])	Append values to the end of an array.
resize(a, new_shape)	Return a new array with the specified shape.
trim_zeros(filt[, trim])	Trim the leading and/or trailing zeros from a 1-D array or sequence.
unique(ar[, return_index, return_inverse, ...])	Find the unique elements of an array.
flip(m[, axis])	Reverse the order of elements in an array along the given axis.
fliplr(m)	Reverse the order of elements along axis 1 (left/right).
flipud(m)	Reverse the order of elements along axis 0 (up/down).
roll(a, shift[, axis])	Roll array elements along a given axis.
rot90(m[, k, axes])	Rotate an array by 90 degrees in the plane specified by axes.