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Introduction to Numpy

CBSE · Class 11 · Informatics Practices

NCERT Solutions for Introduction to Numpy — CBSE Class 11 Informatics Practices.

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EXERCISE

1What is NumPy ? How to install it?Show solution
NumPy stands for Numerical Python. It is a Python package used for data analysis and scientific computing. It uses a multidimensional array object and provides tools for working with arrays. To install it, type:

```bash
pip install NumPy
```

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2What is an array and how is it different from a list? What is the name of the built-in array class in NumPy ?Show solution
An array is a data type used to store multiple values using a single identifier. Its elements are of the same data type, are stored contiguously in memory, and are accessed by index.

A list in Python can contain elements of different data types, is not stored contiguously in memory, and does not support element-wise operations like arrays do.

The built-in array class in NumPy is called ndarray.

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3What do you understand by rank of an ndarray?Show solution
The rank of an `ndarray` means the number of dimensions or axes in the array. For example, a 1-D array has rank 1 and a 2-D array has rank 2.

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4(a)A 1-D array called zeros having 10 elements and all the elements are set to zero.Show solution
A 1-D array with 10 zero elements can be created using zeros():

```python
np.zeros(10)
```

This creates an array of 10 elements, all set to zero.

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4(b)A 1-D array called vowels having the elements 'a', 'e', 'i', 'o' and 'u'.Show solution
A 1-D array containing the vowels can be created from a list using `np.array()`:

```python
np.array(['a', 'e', 'i', 'o', 'u'])
```

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4(c)A 2-D array called ones having 2 rows and 5 columns and all the elements are set to 1 and dtype as int.Show solution
A 2-D array with 2 rows and 5 columns, all elements equal to 1, and data type int can be created as:

```python
np.ones((2, 5), dtype=int)
```

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4(d)Use nested Python lists to create a 2-D array called myarray1 having 3 rows and 3 columns and store the following data:
2.7, -2, -19
0, 3.4, 99.9
10.6, 0, 13Show solution
Use nested lists inside `np.array()`:

```python
np.array([[2.7, -2, -19], [0, 3.4, 99.9], [10.6, 0, 13]])
```

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4(e)A 2-D array called myarray2 using arange() having 3 rows and 5 columns with start value = 4, step size 4 and dtype as float.Show solution
We need 15 elements for a 3×53\times 5 array. Starting at 4 and increasing by 4 gives:

4,8,12,16,20,24,28,32,36,40,44,48,52,56,604, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, 48, 52, 56, 60

So the command is:

```python
np.arange(4, 64, 4, dtype=float).reshape(3, 5)
```

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5(a)Find the dimensions, shape, size, data type of the items and itemsize of arrays zeros, vowels, ones, myarray1 and myarray2.Show solution
Use these commands:

- zeros: `zeros.ndim`, `zeros.shape`, `zeros.size`, `zeros.dtype`, `zeros.itemsize`
- vowels: `vowels.ndim`, `vowels.shape`, `vowels.size`, `vowels.dtype`, `vowels.itemsize`
- ones: `ones.ndim`, `ones.shape`, `ones.size`, `ones.dtype`, `ones.itemsize`
- myarray1: `myarray1.ndim`, `myarray1.shape`, `myarray1.size`, `myarray1.dtype`, `myarray1.itemsize`
- myarray2: `myarray2.ndim`, `myarray2.shape`, `myarray2.size`, `myarray2.dtype`, `myarray2.itemsize`

These give the dimensions, shape, size, data type, and itemsize of each array.

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5(b)Reshape the array ones to have all the 10 elements in a single row.Show solution
To place all 10 elements of ones in a single row, reshape it to 1×101\times 10:

```python
ones.reshape(1, 10)
```

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5(c)Display the 2nd and 3rd element of the array vowels.Show solution
To display the 2nd and 3rd elements of a 1-D array, use slicing from index 1 to 3 (end index excluded):

```python
vowels[1:3]
```

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5(d)Display all elements in the 2nd and 3rd row of the array myarray1.Show solution
To display all elements in the 2nd and 3rd rows, select rows from index 1 to 3 and all columns:

```python
myarray1[1:3, :]
```

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5(e)Display the elements in the 1st and 2nd column of the array myarray1.Show solution
To display the elements in the 1st and 2nd columns of a 2-D array, select all rows and columns from index 0 to 2:

```python
myarray1[:, 0:2]
```

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5(f)Display the elements in the 1st column of the 2nd and 3rd row of the array myarray1.Show solution
To display the elements in the 1st column of the 2nd and 3rd rows, select rows from index 1 to 3 and column index 0:

```python
myarray1[1:3, 0]
```

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5(g)Reverse the array of vowels.Show solution
To reverse a 1-D array, use slicing with step −1-1:

```python
vowels[::-1]
```

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6(a)Divide all elements of array ones by 3.Show solution
To divide all elements of ones by 3, use element-wise division:

```python
ones / 3
```

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6(b)Add the arrays myarray1 and myarray2.Show solution
To add the two arrays element-wise, use:

```python
myarray1 + myarray2
```

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6(c)Subtract myarray1 from myarray2 and store the result in a new array.Show solution
To subtract myarray1 from myarray2, compute:

```python
myarray2 - myarray1
```

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6(d)Multiply myarray1 and myarray2 elementwise.Show solution
Element-wise multiplication is done using `*`:

```python
myarray1 * myarray2
```

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6(e)Do the matrix multiplication of myarray1 and myarray2 and store the result in a new array myarray3.Show solution
Matrix multiplication is done using the `@` operator:

```python
myarray1 @ myarray2
```

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6(f)Divide myarray1 by myarray2.Show solution
To divide myarray1 by myarray2 element-wise, use:

```python
myarray1 / myarray2
```

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6(g)Find the cube of all elements of myarray1 and divide the resulting array by 2.Show solution
First cube every element using ` 3`, then divide the resulting array by 2:

```python
(myarray1 3) / 2
```

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6(h)Find the square root of all elements of myarray2 and divide the resulting array by 2. The result should be rounded to two places of decimals.Show solution
Take the square root of each element of myarray2, divide by 2, then round to two decimal places:

```python
np.round(np.sqrt(myarray2) / 2, 2)
```

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7(a)Find the transpose of ones and myarray2.Show solution
The transpose of an array is obtained using `transpose()`:

```python
ones.transpose()
myarray2.transpose()
```

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7(b)Sort the array vowels in reverse.Show solution
First sort the array in ascending order using `sort()`, then reverse it with slicing `[::-1]`:

```python
vowels.sort()
vowels[::-1]
```

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7(c)Sort the array myarray1 such that it brings the lowest value of the column in the first row and so on.Show solution
Use `sort(axis=0)`. In a 2-D array, axis=0 means sorting column-wise, so the lowest value of each column comes in the first row.

```python
myarray1.sort(axis=0)
```

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8(a)Use NumPy.split() to split the array myarray2 into 5 arrays columnwise. Store your resulting arrays in myarray2A, myarray2B, myarray2C, myarray2D and myarray2E. Print the arrays myarray2A, myarray2B, myarray2C, myarray2D and myarray2E.
8(b)Split the array zeros at array index 2, 5, 7, 8 and store the resulting arrays in zerosA, zerosB, zerosC and zerosD and print them.
8(c)Concatenate the arrays myarray2A, myarray2B and myarray2C into an array having 3 rows and 3 columns.
9Create a 2-D array called myarray4 using arange() having 14 rows and 3 columns with start value = -1, step size 0.25 having. Split this array row wise into 3 equal parts and print the result.
10(a)Find the sum of all elements.
10(b)Find the sum of all elements row wise.
10(c)Find the sum of all elements column wise.
10(d)Find the max of all elements.
10(e)Find the min of all elements in each row.
10(f)Find the mean of all elements in each row.
10(g)Find the standard deviation column wise.
1Load the data in the file Iris.txt in a 2-D array called iris.
2Drop column whose index = 4 from the array iris.
3Display the shape, dimensions and size of iris.
4Split iris into three 2-D arrays, each array for a different species. Call them iris1, iris2, iris3.
5Print the three arrays iris1, iris2, iris3
6Create a 1-D array header having elements "sepal length", "sepal width", "petal length", "petal width", "Species No" in that order.
7Display the array header.
8Find the max, min, mean and standard deviation for the columns of the iris and store the results in the arrays iris_max, iris_min, iris_avg, iris_std, iris_var respectively. The results must be rounded to not more than two decimal places.
9Similarly find the max, min, mean and standard deviation for the columns of the iris1, iris2 and iris3 and store the results in the arrays with appropriate names.
10Check the minimum value for sepal length, sepal width, petal length and petal width of the three species in comparison to the minimum value of sepal length, sepal width, petal length and petal width for the data set as a whole and fill the table below with True if the species value is greater than the dataset value and False otherwise.
11Compare Iris setosa's average sepal width to that of Iris virginica.
12Compare Iris setosa's average petal length to that of Iris virginica.
13Compare Iris setosa's average petal width to that of Iris virginica.
14Save the array iris_avg in a comma separated file named IrisMeanValues.txt on the hard disk.
15Save the arrays iris_max, iris_avg, iris_min in a comma separated file named IrisStat.txt on the hard disk.

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Frequently Asked Questions

What are the important topics in Introduction to Numpy for CBSE Class 11 Informatics Practices?
Introduction to Numpy covers several key topics that are frequently asked in CBSE Class 11 board exams. Focus on the core concepts listed on this page and practise related questions to build confidence.
How to score full marks in Introduction to Numpy — CBSE Class 11 Informatics Practices?
Understand the core concepts first, then work through the 125 practice questions available for this chapter. Revise formulas and definitions regularly, and use flashcards for quick recall before the exam.
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