Showing posts with label Python Coding Challenge. Show all posts
Showing posts with label Python Coding Challenge. Show all posts

Sunday 25 February 2024

Python Coding challenge - Day 137 | What is the output of the following Python Code?

 


a = [1, 2, 3, 4]

b = [1, 2, 5]

print(a < b)

Two lists, a and b, are defined.

a is [1, 2, 3, 4]

b is [1, 2, 5]

The code uses the less-than (<) operator to compare the two lists a and b. This comparison is performed element-wise.

The first elements of both lists are equal (1 == 1).

The second elements are equal (2 == 2).

The third elements are different (3 in a and 5 in b).

The less-than comparison stops at the first differing element. Since 3 is less than 5, the entire comparison evaluates to True.

The result of the comparison is printed using print(a < b), and it will output True.

So, the output of the code is:

True

This is because, in lexicographical order, the list a is considered less than the list b due to the first differing element at index 2.

Friday 23 February 2024

Lists data structures in Python

 


Example 1: Creating a List

In [2]:
[1, 2, 3, 4, 5]
['apple', 'banana', 'orange']
[1, 'hello', 3.14, True]
[]

Example 2: Accessing Elements in a List

In [3]:
apple
5
[2, 3, 4]
['apple', 'banana']

Example 3: Modifying Elements in a List

In [4]:
['apple', 'grape', 'orange']
['apple', 'grape', 'orange', 'kiwi']
['apple', 'grape', 'orange', 'kiwi', 'mango']

Example 4: Removing Elements from a List

In [4]:
['apple', 'grape', 'kiwi', 'mango', 'pineapple']
Popped fruit: grape
['apple', 'kiwi', 'mango', 'pineapple']

Example 5: List Operations

In [5]:
4
True
[1, 2, 3, 4, 5, 6, 7, 8]

Example 6: List Iteration

In [6]:
Fruit: apple
Fruit: kiwi
Fruit: mango
Fruit: pineapple
Index: 0, Fruit: apple
Index: 1, Fruit: kiwi
Index: 2, Fruit: mango
Index: 3, Fruit: pineapple

Python Coding challenge - Day 136 | What is the output of the following Python Code?

 



The code creates a list data with elements [1, 2, 3, 4] and then creates a copy of this list called backup_data using the copy() method. After that, it modifies the fourth element of the original data list by setting it to 7. Finally, it prints the backup_data list.

Let's analyze the code step by step:

data = [1, 2, 3, 4]: Initializes a list named data with elements [1, 2, 3, 4].

backup_data = data.copy(): Creates a shallow copy of the data list and assigns it to backup_data. Both lists will initially contain the same elements.

data[3] = 7: Modifies the fourth element of the data list, changing it from 4 to 7.

print(backup_data): Prints the backup_data list. Since it's a copy made before the modification, it will not reflect the change made to the data list.

So, when you run this code, the output will be:

[1, 2, 3, 4]

This is because the modification of the data list does not affect the backup_data list, as it was created as a separate copy.

Thursday 22 February 2024

10-question multiple-choice quiz on Pandas


 1. What is Pandas?

a. A data visualization library

b. A web development framework

c. A data manipulation library

d. A machine learning framework


2.  What is the primary data structure in Pandas for one-dimensional labeled data?

a. Series

b. DataFrame

c. Array

d. List


3. How do you read a CSV file into a Pandas DataFrame?

a. pd.load_csv()

b. pd.read_csv()

c. pd.read_data()

d. pd.import_csv()


4. How do you select a specific column in a Pandas DataFrame?

a. df.column('ColumnName')

b. df.select('ColumnName')

c. df['ColumnName']

d. df.get('ColumnName')


5. What is the purpose of the head() method in Pandas?

a. It gives the first few rows of the DataFrame

b. It returns the last rows of the DataFrame

c. It displays a summary statistics of the DataFrame

d. It provides information about the columns in the DataFrame


6. How do you handle missing values in a Pandas DataFrame?

a. Use the fillna() method

b. Use the remove_na() method

c. Use the drop_na() method

d. Pandas automatically handles missing values


7. What function is used to group data in Pandas based on one or more columns?

a. groupby()

b. aggregate()

c. sort()

d. combine()


8. How do you merge two DataFrames in Pandas based on a common column?

a. df.merge()

b. df.join()

c. df.concat()

d. df.combine()


9. What does the describe() method in Pandas provide?

a. Descriptive statistics of the DataFrame

b. A list of unique values in each column

c. Information about data types in the DataFrame

d. A summary of missing values in the DataFrame


10. What is the purpose of the to_csv() method in Pandas?

a. It saves the DataFrame to a CSV file

b. It converts the DataFrame to a Series

c. It exports the DataFrame to an Excel file

d. It prints the DataFrame to the console


Answer:

1. c, 

2. a, 

3. b, 

4. c, 

5. a, 

6. a, 

7. a, 

8. a, 

9. a, 

10. a

Popular Posts

Categories

AI (23) Android (24) AngularJS (1) Assembly Language (2) aws (16) Azure (7) BI (10) book (3) Books (92) C (77) C# (12) C++ (82) Course (60) Coursera (167) coursewra (1) Cybersecurity (22) data management (9) Data Science (68) Data Strucures (6) Deep Learning (9) Django (6) Downloads (3) edx (2) Engineering (14) Excel (13) Factorial (1) Finance (5) flutter (1) FPL (17) Google (17) Hadoop (3) HTML&CSS (46) IBM (19) IoT (1) IS (25) Java (92) Leet Code (4) Machine Learning (37) Meta (18) MICHIGAN (4) microsoft (3) Pandas (3) PHP (20) Projects (29) Python (693) Python Coding Challenge (135) Questions (2) R (70) React (6) Scripting (1) security (3) Selenium Webdriver (2) Software (17) SQL (38) UX Research (1) web application (8)

Followers

Person climbing a staircase. Learn Data Science from Scratch: online program with 21 courses