Master Python and Data Analysis

09/04/2025

50 Days of Python: A Challenge a Day

The concept is simple: do one or two challenges a day for just 50 days.

💡 Why challenges?

Well, without hands-on practice, you won’t internalize Python’s syntax or logic. For example, you might understand a for loop in theory, but if you don’t use it to solve a real problem, you will not fully grasp its capabilities and limitations.

📍 Here is a challenge from the book:

A school has asked you to write a program that will calculate teachers' salaries. The program should ask the user to enter the teacher’s name, the number of periods taught in a month, and the rate per period. The monthly salary is calculated by multiplying the number of periods by the monthly rate. The current monthly rate per period is $20. If a teacher has more than 100 periods in a month, everything above 100 is overtime. Overtime is $25 per period. For example, if a teacher has taught 105 periods, their gross monthly salary should be $2,125. Write a function called "your_salary" that calculates a teacher’s gross salary. The function should return the teacher’s name, periods taught, and gross salary. Here is how you should format your output:

Teacher: John Kelly,
Periods: 105
Gross salary: 2,125

Can you solve it?

Whether you like it or not, the next 50 days are going to pass. After 50 days, you can still be where you are today, or you could be 50 times better.

📍 The choice is yours.

04/02/2025

Python tip;

💡 How can you tell which variables in a function are local?

Local variables are variables that have a local scope. These are variables that have been defined inside a function. Python has a built-in function that you can use to return all the local variables in a function. The built-in function is the local() function. This function returns a dictionary that represents the current local symbol table. The keys of this dictionary are the names of the local variables, and the values are the values of the local variables. Here is an example of how you can use this function:

02/02/2025

Python tip;

💡 Avoid Unintended Side Effects with Default Arguments

A common pitfall in Python involves mutable default arguments in function definitions. In the example below, we have defined a function with a default argument, which is an empty list. This leads to unpredictable behavior.

Have you noticed what is happening here? Each subsequent call to the function without explicitly providing a my_list argument will reuse this same list object, leading to unexpected results.

In this code, when we call the function for the first time without providing an argument for the my_list variable, the function appends 1 to my_list, and it returns my_list. The result1 variable now contains [1]. When we call the function the second time, it appends 2 to the same list (now [1, 2]) and returns it. When we call the function the third time, it appends 3 to the same list (now [1, 2, 3]) and returns it. So, each subsequent call to append_to_list modifies the same default list, which accumulates elements from previous calls. This is unexpected behavior if you assume that each call to the append_to_list function starts with an empty list.

The reason for this behavior is that the default value for the my_list variable is created only once, at the time the function is defined. This default list is then used and modified every time the function is called without explicitly passing a value for my_list.

28/05/2024

Python tip;

I have an object; how can I Pythonically tell if it is callable?

A callable object is anything that you can call using parentheses () and optionally pass arguments to. These objects essentially act like functions and can be executed to produce some output or perform an action. To know if an object is callable, you can use the built-in callable() function. The callable() function takes an object as an argument and returns a Boolean value indicating whether the object is callable or not. Below, we use the function to check if the two objects, a string and a function, are callable:

09/05/2024

Python tip;

Did you know that the sort() method is stable?

source: Python Tips and Tricks: A Collection of 100 Basic & Intermediate Tips & Tricks

https://benjaminb.gumroad.com/l/avijr

08/05/2024

Data Analysis Project: Five Key Questions to Make Your Project Shine

Introduction One of the most exciting things about working with data is its practical nature, which includes its ability to solve real-world problems. If you are aspiring to be a data analyst, at some point you will have to prove your proficiency in data analysis by completing a project. When doing....

07/05/2024

This is what cleaning a date column may look like using SQL. 👇

I think Python pandas is better than SQL in this area, but SQL is still widely used, so for data analysts, it is necessary to learn it.

**A data analyst must learn both Python and SQL.

06/05/2024

50 Days of Data Analysis with Python (40% off; use discount code: DATA40)

According to Forbes, data analysis is one of the high-income skills to learn in 2024. There is no better way to become proficient at data analysis than by getting your hands dirty and tackling some challenges. Start your 50-day journey today.

Master Data Analysis with Python: The Ultimate 50-Day Challenge BookAre you an aspiring data analyst, data scientist, or business analyst?Are you a self-taught data analyst who is looking to apply your newfound skills to practical data analysis tasks?Are you looking for a structured, practical, and....

19/04/2024

Want to learn Python in a fun and effective way?

Do you want to improve your Python skills by committing to doing a challenge or two a day for 50 days?

Then you need "50 Days of Python: A Challenge a Day."

Imagine building a Python script that calculates teachers' salaries—a perfect way to practice loops and conditional statements!

This unique book extensively covers Python fundamentals at the basic and intermediate levels. It offers a fun and engaging approach to learning Python. With bite-sized daily challenges, you'll:
✅ Master the fundamentals of Python step-by-step
✅ Improve your problem-solving skills by conquering practical coding tasks
✅ Build the confidence and skills you need to do great things with Python

Here's what you'll get:
✅ Over 80 engaging challenges to keep you motivated
✅ Daily practice to solidify your learning
✅ A clear path to mastering Python and achieving your coding goals.

Many have tried this book and have loved its engaging and non-intimidating challenges.

Stop wishing; start coding!

Ready to start your Python journey? Grab your copy of "50 Days of Python: A Challenge a Day" today!

Master Python Fundamentals Through Tackling Daily ChallengesImagine mastering Python fundamentals by completing a challenge or two each day. Well, you don't need to imagine any longer. This book offers a unique set of challenges designed to help you grasp the essentials of the Python language as you...

15/04/2024

Do you want to improve your Python skills by committing to doing a challenge or two a day for 50 days?

Then you need "50 Days of Python: A Challenge a Day."

Imagine building a Python script that calculates teachers' salaries – a perfect way to practice loops and conditional statements!

This unique book extensively covers Python fundamentals at the basic and intermediate levels. It offers a fun and engaging approach to learning Python. With bite-sized daily challenges, you'll:
✅ Master the fundamentals of Python step-by-step
✅ Improve your problem-solving skills by conquering practical coding tasks
✅ Build the confidence and skills you need to do great things with Python

Here's what you'll get:

✅ Over 80 engaging challenges to keep you motivated
✅ Daily practice to solidify your learning
✅ A clear path to mastering Python and achieving your coding goals.

Many have tried this book and have loved its engaging and non-intimidating challenges.

Stop wishing, start coding!

Ready to start your Python journey? Grab your copy of "50 Days of Python: A Challenge a Day" today!

https://analyticalpy.com/50-days-of-python/

12/04/2024

💎 Creating great visualizations is cool but prioritize data cleaning and preprocessing

The hard part is transforming your data so that it can be visualized. Organizations usually collect data in a messy way. This means that when the data is thrown at a data analyst, it will need a whole lot of cleaning and preprocessing. This makes learning to clean and preprocess data a crucial skill to master.

I would suggest spending more time learning about the tools available for cleaning and preprocessing data than creating fancy plots. Learn the Python tools available for cleaning and preprocessing data.

Guess what! All great visualizations are built on clean and transformed data.

11/04/2024

Python tip;

Magic Methods

Magic methods have double underscores at the beginning and end of their names (e.g., __str__, __add__). These special methods allow us to customize the behavior of the class when certain operations are performed on it. This is known as operator overloading. For example, the __str__ method is called when we use the built-in print() function on an object of the class and allows us to define what should be printed. See the example below: