## What is the complexity of merging two sorted arrays?

The complexity is O(m log n). There are m iterations of the loop. Each insertion into a sorted array is an O(log n) operation. Therefore the overall complexity is O (m log n).

## How do you merge sorted arrays in Python?

Merge Sorted Array in Python
1. define i := 0, j := 0 and end := length of A – 1.
2. while end >= 0 and not A[end], end := end – 1.
3. while j < length of B. if i > end and not A[i], then A[i] := B[j], and increase j by 1. otherwise if A[i] > B[j], then perform shift(A, i), A[i] := B[j], increase end and j by 1. increase i by 1.

## How do I combine two arrays alternatively?

Logic To Merge Arrays a and b into c in Alternate positions

In the next for loop, we reset the value of i to 0, and k value is rest to 1. k value keeps incrementing by 2 for each iteration of for loop, while i value increments by 1 for each iteration of the for loop.

## What is the recurrence relation for merge sort?

In merge sort, we divide the array into two (nearly) equal halves and solve them recursively using merge sort only. Finally, we merge these two sub arrays using merge procedure which takes Θ(n) time as explained above. On solving this recurrence relation, we get T(n) = Θ(nlogn).

## How do I merge two arrays in Python?

NumPy’s concatenate function can be used to concatenate two arrays either row-wise or column-wise. Concatenate function can take two or more arrays of the same shape and by default it concatenates row-wise i.e. axis=0. The resulting array after row-wise concatenation is of the shape 6 x 3, i.e. 6 rows and 3 columns.

## How do you combine two arrays in Python?

Joining means putting contents of two or more arrays in a single array. In SQL we join tables based on a key, whereas in NumPy we join arrays by axes. We pass a sequence of arrays that we want to join to the concatenate() function, along with the axis. If axis is not explicitly passed, it is taken as 0.

## How do you merge two lists in Python?

In python, we can use the + operator to merge the contents of two lists into a new list. For example, We can use + operator to merge two lists i.e. It returned a new concatenated lists, which contains the contents of both list_1 and list_2.

## How do I combine two data frames?

When we concatenate DataFrames, we need to specify the axis. axis=0 tells pandas to stack the second DataFrame UNDER the first one. It will automatically detect whether the column names are the same and will stack accordingly. axis=1 will stack the columns in the second DataFrame to the RIGHT of the first DataFrame.

## How do you combine two lists in Python?

Ways to concatenate two lists in Python
1. Method #1 : Using Naive Method.
2. Method #2 : Using + operator.
3. Method #3 : Using list comprehension.
4. Method #4 : Using extend()
5. Method #5 : Using * operator.
6. Method #6 : Using itertools.chain()

## How do you merge three lists in Python?

1. Using Python itertools. chain() method. …
2. Using Python ‘*’ operator. Python ‘*’ operator provides a much efficient way to perform manipulation on the input lists and concatenate them together. …
3. Using Python “+” operator. Python ‘+’ operator can be used to concatenate the lists together.

## How do you flatten an array in Python?

flatten() function we can flatten a matrix to one dimension in python. order:’C’ means to flatten in row-major. ‘F’ means to flatten in column-major. ‘A’ means to flatten in column-major order if a is Fortran contiguous in memory, row-major order otherwise.

## How do you concatenate a dictionary in python?

Python Program to Concatenate Two Dictionaries Into One
1. Declare and initialize two dictionaries with some key-value pairs.
2. Use the update() function to add the key-value pair from the second dictionary to the first dictionary.
3. Print the final dictionary.
4. Exit.

## How do you merge two lists without duplicates in Python?

Use set() and list() to combine two lists while removing duplicates in the new list and keeping duplicates in original list. Call set(list_1) and set(list_2) to generate sets of the elements in list_1 and list_2 respectively which contain no duplicates.

## What does flatten () do in Python?

flatten() function. The flatten() function is used to get a copy of an given array collapsed into one dimension. ‘C’ means to flatten in row-major (C-style) order.

## How do you reshape an array in Numpy?

In order to reshape a numpy array we use reshape method with the given array.
1. Syntax : array.reshape(shape)
2. Argument : It take tuple as argument, tuple is the new shape to be formed.
3. Return : It returns numpy.ndarray.

## What is flattened array?

Flattening an array is a process of reducing the dimensionality of an array. In other words, it a process of reducing the number of dimensions of an array to a lower number.

## What is Ravel numpy?

ravel() in Python. The numpy module of Python provides a function called numpy. ravel, which is used to change a 2-dimensional array or a multi-dimensional array into a contiguous flattened array. The returned array has the same data type as the source array or input array.

## How do I convert an array of arrays into a flat 1D array numpy?

Use numpy. array. flatten() to convert a 2D NumPy array into a 1D array
1. print(array_2d)
2. array_1d = array_2d. flatten() flatten `array_2d`
3. print(array_1d)

## What is flatten Tensorflow?

Flattening a tensor means to remove all of the dimensions except for one. A Flatten layer in Keras reshapes the tensor to have a shape that is equal to the number of elements contained in the tensor. This is the same thing as making a 1d-array of elements.

## What is the difference between Ravel and flatten?

flatten always returns a copy. ravel returns a view of the original array whenever possible. This isn’t visible in the printed output, but if you modify the array returned by ravel, it may modify the entries in the original array. If you modify the entries in an array returned from flatten this will never happen.

## What is a contiguous array?

A contiguous array is just an array stored in an unbroken block of memory: to access the next value in the array, we just move to the next memory address.