Welcome to Trinket’s Python Online IDE to run your Python code! Here, you can copy/paste code from various Python exercises available on our website and run it live, edit, or watch results. The specialty of this online IDE is you can not only use all standard Python 3 features but also test your Pandas DataFrames and plot graphs using data analysis libraries like Matplotlib.
Get Started with the Python Online IDE
Get ready to run your Python code. Just wait a few seconds, it may take to pop up…
By the way, if you are looking to start your coding journey with some simple exercises, then pick anyone from the below set. Go through the solution part, run the code in the above Python IDE, and analyze the output. Try to re-implement it with a different logic, which is your style.
Exercise 1: Reverse a String
What do we have to do in this exercise?
This exercise aims to create a function that reverses a given string.
def rev_str(s):
return s[::-1]
# Test the function
input_str = "Python is fun!"
rev_result = rev_str(input_str)
print(f"Actual String: {input_str}")
print(f"New String: {rev_result}")How did we achieve it?
We defined a function reverse_string using Python’s string slicing to reverse the input string. The test demonstrates the reversal of the provided string.
Now, just chip this code into the Python online IDE provided above. Run Python code, enjoy watching it run, and edit in your way.
Exercise 2: Fibonacci Sequence
What is our task in this exercise?
This exercise involves creating a function to generate the Fibonacci sequence up to a specified number n.
def gen_fibonacci(n):
fib_seq = [0, 1]
while fib_seq[-1] + fib_seq[-2] <= n:
fib_seq.append(fib_seq[-1] + fib_seq[-2])
return fib_seq
# Test the function
n_val = 20
result = gen_fibonacci(n_val)
print(f"Fibonacci sequence up to {n_val}: {result}")How did we achieve it?
We crafted a function generate_fibonacci using a while loop to extend the Fibonacci sequence until the last element is greater than the specified number n.
Now, copy the code into the Python online IDE shown above. Run this Python code, have fun watching it run, and edit at your own will.
Exercise 3: Check for Palindrome
What do we have to achieve?
This exercise focuses on checking if a given word is a palindrome.
def is_it_palindrome(word):
return word == word[::-1]
# Test the function
test_word = "level"
print(f"Is '{test_word}' a palindrome? {is_it_palindrome(test_word)}")How did we achieve it?
We designed a function is_palindrome that compares a word with its reverse to determine if it reads the same backward.
Click here to go to the Online Python IDE to run code.
Exercise 4: Prime Numbers
What do we have to achieve?
Generate a list of prime numbers up to a specified limit using a function.
def gen_primes(limit):
primes = [2]
for num in range(3, limit + 1):
if all(num % i != 0 for i in range(2, int(num**0.5) + 1)):
primes.append(num)
return primes
# Test the function
limit_value = 30
prime_result = gen_primes(limit_value)
print(f"Prime numbers up to {limit_value}: {prime_result}")How did we achieve it?
We implemented a function generate_primes using a for loop and a primality-checking condition to create a list of prime numbers within the specified limit.
Now, copy the above lines into the Python online IDE. Press the Run “▶” button to run Python code, watch the result, and edit as you wish.
Exercise 5: Count Words in a Sentence
What do we have to achieve?
Count the occurrences of each word in a sentence using a dictionary.
def word_ctr(sentence):
wc = {}
words = sentence.split()
for word in words:
wc[word] = wc.get(word, 0) + 1
return wc
# Test the function
sample_text = "This is a test. This test is for counting words."
result = word_ctr(sample_text)
# Print formatted output
print("Word count:")
for word, count in result.items():
print(f"{word}: {count}")How did we achieve it?
We created a function count_words utilizing a dictionary to store and count occurrences of each word in the provided sentence.
Copy and Run Python Code in the Online IDE.
Exercise 6: List Comprehensions
What do we have to do in this exercise?
Practice using list comprehensions to generate a list of squares for even numbers.
sqrs_of_evens = [x**2 for x in range(1, 11) if x % 2 == 0]
print(f"Squares of even numbers: {sqrs_of_evens}")Copy and Run Python Code in the Online IDE.
How did we achieve it?
We employed a list comprehension to create a concise list of squares for even numbers between 1 and 10.
Exercise 7: Dictionary Manipulation
What is the goal of this exercise?
Find the highest scorer in a dictionary using a function.
def highest_scorer(scores):
return max(scores, key=scores.get)
# Test the function
student_scores = {"Ram": 85, "Rahim": 92, "Vikas": 78, "Nawab": 95}
top_scorer_result = highest_scorer(student_scores)
print(f"The student with the highest score is: {top_scorer_result}")How did we achieve it?
We implemented a function highest_scorer to find the key (student name) with the highest value (score) in a dictionary.
Copy and Run Python Code in the Online IDE.
Exercise 8: File Handling
What is the goal of this exercise?
Read from a text file, count word occurrences, and return the top 3 most frequent words.
def top_words(fl):
wc = {}
with open(fl, 'r') as file:
for line in file:
words = line.split()
for word in words:
# Remove trailing punctuation (e.g., dots)
word = word.rstrip('.,?!')
# Convert the word to lowercase to make it case-insensitive
word = word.lower()
wc[word] = wc.get(word, 0) + 1
sort_wc = sorted(wc.items(), key=lambda x: x[1], reverse=True)
top_3_words = sort_wc[:3]
return top_3_words
# Create a sample text file with dummy data
with open("test_data.txt", 'w') as dummy_file:
dummy_file.write("Check my online Python IDE. I can run Python code. This IDE is free for online coding. It makes me learn Python.\n")
# Test the function
test_file = "test_data.txt"
result = top_words(test_file)
# Print formatted output
print("Top 3 most frequent words:")
for word, count in result:
print(f"{word}: {count}")How did we achieve it?
We created a function top_words that reads from a text file, counts word occurrences using a dictionary, and returns the top 3 most frequent words. We have used Python lambda and sorted functions.
Copy and Run Python Code in the Online IDE.
Exercise 9: Classes and Objects
What is the task in this exercise?
Our goal is to create a Python class, DataAnalyzer, using the pandas library, to load and analyze data from a CSV file.
import pandas as pds
# Create a sample CSV file with data
sample_csv = {
'Name': ['Ram', 'Shyam', 'Rahim', 'Karim', 'James'],
'Age': [25, 30, 22, 35, 28],
'Salary': [50000, 60000, 45000, 70000, 55000]
}
dfr = pds.DataFrame(sample_csv)
dfr.to_csv('sample_csv.csv', index=False)
class DataAnalyzer:
def __init__(self, data_file):
self.data_file = data_file
self.data = None
def load_data(self):
try:
self.data = pds.read_csv(self.data_file)
print(f"Data loaded successfully from '{self.data_file}'.")
except FileNotFoundError:
print(f"Error: File '{self.data_file}' not found. Please provide a valid file path.")
def analyze_data(self):
if self.data is not None:
print("\nPerforming basic data analysis:")
print(f"Number of rows: {len(self.data)}")
print(f"Column names: {list(self.data.columns)}")
print("\nSummary statistics:")
print(self.data.describe())
else:
print("No data to analyze. Please load data first.")
# Create an instance of the DataAnalyzer class
daz = DataAnalyzer("sample_csv.csv")
# Load and analyze data
daz.load_data()
daz.analyze_data()How did we solve it?
We achieved this by creating a class, DataAnalyzer that loads data from a CSV file and performs simple data analysis using pandas. This makes it easy for users to analyze datasets in a structured and reusable way.
Copy and Run Python Code in the Online IDE.
Exercise 10: Exception Handling
What is the aim of this exercise?
Take user input for a number, handle exceptions for invalid input, and return the square of the number.
def square_input():
try:
num = float(input("Enter a number: "))
result = num**2
return result
except ValueError:
return "Invalid input. Please enter a valid number."
# Test the function
squared_input_result = square_input()
print(f"Result: {squared_input_result}")How did we achieve it?
We created a function square_input that takes user input, handles potential errors (like non-numeric input), and returns the square of the input.
Copy and Run Python Code in the Online IDE.
Feel free to explore and practice these exercises to strengthen your Python skills!
Python 3 FAQs
Go through the following frequently asked questions related to Python 2, Python 3, online Python IDE, and running the Python code.
Q: Why use Python 3 instead of Python 2?
A: Python 3 has better features like improved text handling and syntax. It’s a good idea to switch to Python 3 for access to these enhancements and to keep up with the latest Python developments. Updating your code to Python 3 ensures compatibility with newer tools and libraries.
Q: How do I update my Python 2 code to Python 3?
A: You can use tools like 2to3 to help with the transition, but it’s important to go through your code manually. Python 3’s transition guide provides tips for a smoother process. Remember, it’s a one-way transition.
Q: Can Python 3 run Python 2 code?
A: No, Python 3 and Python 2 aren’t buddies. If you have Python 2 code, you’ll need to make changes to run it with Python 3. Think of it like speaking different dialects.
Python Data Analysis FAQs:
Q: What are the main libraries for data analysis in Python?
A: Python’s data analysis toolbox includes Pandas for data wrangling, NumPy for number crunching, and Matplotlib, Seaborn, and Scikit-learn for visualizing and working with data. These tools are like your superhero squad for data analysis.
Q: How do I handle missing data in Pandas?
A: Pandas library powers your coding with functions like – dropna() that cleans up missing values and fillna() for patching them up. Handling missing data is crucial for getting accurate insights from your datasets.
Q: What’s the difference between a DataFrame and a Series in Pandas?
A: Think of a Series as a single column and a data frame as a whole table. A data frame is made up of several Series. It’s like breaking down your data into manageable pieces for analysis.
Run Python Code Online FAQs:
Q: Can I code in Python online without installing it locally?
A: Yes, platforms like Replit and Trinket let you write and run Python code in your web browser. No need to install Python on your computer. It’s like having a coding playground online.
Q: Are online Python interpreters safe to run code?
A: Yep, reputable online interpreters make sure your code plays in a safe sandbox. But, be cautious when running code from strangers. Safety first!
Q: How can I share my Python code online for collaboration?
A: Use platforms like GitHub or Replit to share your code with others. It’s like passing notes in class, but with code. Perfect for working together on projects or learning from each other.
Happy coding!
