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8 Must-Know Python Topics for Data Science

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The first thing that you will learn in the field of Data Science is Python programming language. There are multiple Python libraries such as NumPy, Pandas, and SciPy which are used by Data Scientists to perform their day-to-day tasks. Those who are looking to make a career in the field of Data Science must go for Python Training in Noida to have a better understanding of the language.

In this blog, we are going to throw some light on important topics of Python that you should know before kick-starting your professional career. We will try our best to explain in the best possible way. However, to know about them in detail, you can connect with experts.

Important Python Topics 

  • Functions : 

In Python, functions are considered as the building blocks. One can create functions using the def keyword. They can be used to perform different tasks. To have an idea of what it does without seeing the code one can assign descriptive names to functions. 

  • Strings : 

To get familiar with the basics of Python, Strings are also important to know. They contain alphanumerical values that are enclosed in q quotation marks. There are different methods through which you can manipulate strings. In the field of Data Science strings are used to create or manipulate textual data in any dataset. 

  • Integers and Floating-Point Numbers : 

In Data Science, you have to work with numbers and Python provides a representation (data types) for various types of numbers. They are classified into integers and floating-point numbers. To have in-depth knowledge about the same, you can enroll for Python Training in Delhi from a prestigious institute. 

  • Classes : 

Classes are used to define a type of object such as integers, lists, and dictionaries in Python. They possess information on data attributes and methods (procedural attributes). Therefore, it is also an important topic while studying Python. 

  • Lists : 

Lists in Python are represented as collections of data points in square brackets. Lists can be used to store one or different data types. One of the major reasons that they are most commonly used is that they are mutable. You can update the items on a list easily. 

  • Dictionaries

In Dictionaries, there is an unordered collection of key-value pairs. The keys should be immutable and unique, on the other hand, values can be of any type. If you are creating dictionaries, then you can key-value pairs in curly brackets. 

  • Sets : 

Sets in Python refer to the collection of distinct hashable objects. To create sets, you have to put objects separated by commas in curly brackets. In sets, there are no repeated elements. 

  • Tuples : 

Tuples are also immutable and they consist of values in parenthesis and are separated by commas. However, they can also be created without using the parenthesis. 

Apart from this, there are different important concepts that you must know before entering the field of Data Science. That’s why you can connect with our expert trainers to get a better understanding.


Python is a versatile programming language that is not only used by Data Scientists but by other professions too. Therefore, we will highly recommend you enroll in Python Online Training to ease out your professional journey. At ShapeMySkills institute, you can connect with certified and experienced trainers to get in-depth knowledge about the same. By having a good understanding of programming language, you can also start your career as Python Developer In the Upcoming Year as such professions are in great demand. We will be glad to hear out from you and to help you to clear all your doubts and queries. So, without any hesitation, feel free to connect with us!

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