This quiz covers the following topics:

- Working with numerical data in Python
- Going from Python lists to Numpy arrays
- Multi-dimensional Numpy arrays and their benefits
- Array operations, broadcasting, indexing, and slicing
- Working with CSV data files using Numpy

Numerical Computing with Numpy

What is a NumPy array?


A student, Hari ran the below code on his Computer's IDE but got wrong answer so he asked his friend Manisha to run the code. When Manisha tried to run the code on a different IDE on her computer, she got the correct answer on the same code. What could be the possible reason behind this discrepancy? 

Code:
```
arr1 = list(range(1000000))
arr2 = list(range(1000000, 2000000))
arr1_np = np.array(arr1)
arr2_np = np.array(arr2)
print(np.dot(arr1_np, arr2_np))
```


What is the output of the following code?

```
print(np.array([[[
    [[11, 12, 13], 
     [13, 14, 15]], 
    [[15, 16, 17], 
     [17, 18, 19.5]]]
    ]]).ndim)
```

What is the output of the following code?

```
arr1 = np.array([[0, 1, 2],
                 [3, 4, 5]])
arr2 = np.array([[6, 7, 8],
                 [9, 10, 11]])
print(np.concatenate((arr1, arr2), axis=1))
```


What is the output of the following code?

```
arr3 = np.array([
    [[11, 12, 8, 19], 
     [13, 21, 4, 19]], 
    
    [[5, 1, 7, 21], 
     [13, 9, 6, 1]], 
    
    [[9, 32, 18, -5],      
     [15, 25, 11, -6]]])
print(arr3[:2, 1].sum())
```

Match the following and choose the correct option. (np means the NumPy library)
1. The function for uniformly distributed random number
2. The function used to create a NumPy array with an equally spaced number in a range
3. The function that creates a normally distributed random number
4. The function used to create a NumPy array filled with a fixed value
5. The function that used to create a NumPy array with a given range and step value
6. The function used to create a NumPy array filled with 0's

A. `np.range()`

B. `np.random.random()`

C. `np.random.randn()`

D. `np.random.rand()`

E. `np.arange()`

F. `np.fill_value()`

G. `np.full()`

H. `np.fillna()`

I. `np.zeros()`

J. `np.linspace()`

Consider 2 numpy arrays a and b defined as follows,

```
a = [[0, 1, 2, 3, 4],
    [5, 6, 7, 8, 9]]
b = [[1, 1, 1, 1, 1],
    [1, 1, 1, 1, 1]]
```
What will be the code so that we get a third array c from the above two arrays?

```
c = [[0, 1, 2, 3, 4, 1, 1, 1, 1, 1],
    [5, 6, 7, 8, 9, 1, 1, 1, 1, 1]]
```

Match the following arrays to their shape:

1. `np.array([[1, 2, 3, 4], [5, 6, 7, 8]])`

2. `np.array([1, 2, 3, 4])`

3. `np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])`

4. `np.array([[7,8,9,10,11],[1,3,1,71,21]])`

a. (2, 2, 2)

b. (2,4)

c. (2,5)

d. (4,)

e. (4,2)

What is the datatype of a numpy array?

Which of the following are NumPy applications?


What is the output of the following code?

`arr = [[1, 2], [2, 3], [3., 4, 5]]`

`print(np.array(arr).dtype)`

Given are the arrays:

`a=np.array([[1,2],[4,5]])`

`b=np.array([[7,8],[9,10]])`

Match the following operations with their results: 

a. `np.multiply()`

b. `np.dot()`

c. `np.cross()`

(i.) ```array([[25, 28],
       [73, 82]])```

(ii.) ```array([[ 7, 16],
       [36, 50]])```

(iii.) ```array([-6, -5])```

What are multi-dimensional NumPy arrays?


What is dot product?


Match the following terms with their definitions:

1. List 

2. Array 

3. Multi-dimensional array 

4. Vector 

5. Scalar


a. A data structure in Python that is a mutable, or changeable, ordered sequence of elements

b. A collection of common type of data structures having elements with the same data type

c. A technique of defining and storing the data in a format with more than two dimensions (2D)

d. A one-dimensional array of lists

e. A single value representing one unit of data

How is a NumPy array different from a list?

Match the following types of arrays with their examples:

1. zero vector

2. 1D array

3. 2D array

4. 3D array

a. `array([0, 0, 0, 0, 0])`

b. `np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])`

c. `[[522, 96], [378, 276], [349, 741], [238, 439]]`

d. `[[[12, 43], [2, 12]], [[23, 51], [53, 67]]]`

Match the following terms with their working:
1. csv

2. genfromtxt

3. concatenate

4. reshape

a. A _____ file typically stores tabular data (numbers and text) in plain text, in which case each line will have the same number of fields.

b. The _____ used to load data from a text file, with missing values handled as specified.

c. The arrays should have the same number of dimensions, and the same length along each except the dimension used for ____.

d. A _____ function shapes an array without changing the data of the array.

Which of the following is not a NumPy arithmetic operator? 



Given are the following matrices: 
```
a=np.array([[1,2],
            [3,4]])

b=np.array([[1,2],
            [3,4]])
```
Match the resulting matrices to their operations respectively:

a. ```array([[ 7, 10],
       [15, 22]])```

b. ```array([[ 1,  4],
       [ 9, 16]])```

c. ```array([[10, 14],
       [14, 20]])```

d. ```array([[ 1,  6],
       [ 6, 16]])```

1. `a@b`

2. `a*b`  

3. `a.T@b` 

4. `a*b.T`

Which of the following are valid NumPy operations for array broadcasting?

What is the result of the given operation?

`arr1 = np.array([[11, 24, 36], [13, 45, 52]])`
`arr2 = np.array([[21, 52, 33], [11, 27, 75]])`

`arr1 == arr2`

Given are the following two arrays:
```

arr1 = np.array([[6, 2, 7, 4], 
                 [5, 3, 5, 8], 
                 [4, 4, 6, 1]]) 
arr2 = arr3 = np.array([[1, 2, 3, 4], 
                 [5, 6, 7, 8], 
                 [9, 1, 2, 3]])
```

The result of (arr1==arr2).sum() is 


What is the difference between indexing and slicing?


Which of the following are true? 

Choose the correct statements about `rand` and `randn`.

Match the following Numpy methods to their results:
 
a. `np.full([2, 3], 42)` 

b. `np.arange(10, 90, 3)`

c. `np.linspace(3, 27, 9)`


1. ```array([ 3.,  6.,  9., 12., 15., 18., 21., 24., 27.])```

2. `array([10, 13, 16, 19, 22, 25, 28, 31, 34, 37, 40, 43, 46, 49, 52, 55, 58,`
       `61, 64, 67, 70, 73, 76, 79, 82, 85, 88])`

3. `array([[42, 42, 42],`
       `[42, 42, 42]])`


Which of the following statements are true?

You can use ___ function to view the contents of the file using Python.


Match the following file modes with their working:

a. `open(‘file.txt’,mode=’w’)`

b. `open(‘file.txt’,mode=’x’)`

c. `open(‘file.txt’,mode=’a’)`

d. `open(‘file.txt’,mode=’t')`

1. create a new file and open it for writing

2. open for writing, truncating the file first

3. open for writing, appending to the end of the file if it exists

4. open the files in text mode (default)

What is the working of the following code?

Code:
```
with open('./data.txt') as file2:
    file2_contents = file2.read()
    print(file2_contents)
```

Match the following functions to their working:

a. `close()` 

b. `readlines()` 

c. `zip()` 

d. `strip()` 

e. `split()`

1. A method to read a file line-by-line

2. A method to close the file

3. A method that combines the contents of two or more iterables

4. A method that removes spaces at the beginning and at the end of the string

5. A method that divides a string into a list of strings after breaking the given string by the specified separator

What are the differences between a CSV and an Excel workbook? 