Data Science is one of the most important fields of study or technology to say, that businesses highly rely on. By leveraging the power of data science, organizations have been able to scale their businesses that were previously not possible. Now as the technology has advanced even further, there are several data science tools available that have made extracting meaningful insights out of raw data and presenting them in a clear and concise manner even easier.
Therefore, now more and more companies are trying to inculcate a culture of data science in their organization, and looking to hire skilled and certified data science professionals.
If you are someone looking to make a career in data science, then the most basic thing you need to learn in your data science education journey is Python programming language. So, let us dive deep to understand how you can learn to perform data science tasks with Python.
Brief Introduction to Data Science and Python
Data Science refers to the use of technology that involves the collection, cleaning, processing, and analysis of raw data to extract meaningful insights that can help business leaders make data-driven decision-making and boost their organization’s efficiency and productivity. Data Science can also be used to solve any kind of business problem or introduce any kind of trending products and services in the market. Data Science has been so popular that it is growing at a CAGR of approximately 19.2% to reach a market value of $345 billion by 2030 (according to Market Research Future).
Whereas Python’s popularity in data science also cannot be ignored. Almost 75% of data science professionals use Python to do their regular chores. It is one of the most versatile, readable, and in-demand programming languages. It consists of an extensive library and helps data scientists solve complex concepts in fewer lines of code. According to Indeed, there are more than 2 million Python jobs vacant now, and also if you look for data science jobs for beginners, Python is a mandatory requirement. So, in this era learning Python will never go in vain.
Why is Python widely used in Data Science?
There are several advantages of using Python for Data Science that make it a popular choice for learning in a data science career.
- As Python is a very versatile programming language, it allows seamless integration across various domains such as web development, machine learning, etc.
- Because it has clear and concise syntax, Python is considered great for its readability thus making it easy to understand and maintain.
- Consists of extensive libraries specialized for data science such as NumPy, Pandas, Matplotlib, Seaborn, etc.
These distinguishing features make Python a stand-out programming language for data science and you will definitely encounter it in your data science education.
How to set up Python for Data Science?
To use Python for data science you must set up a conducive environment by following these simple steps:
- Install Python by visiting Python’s official website and downloading the latest version.
- Select the right Integrated Development Environment (IDE) from Jupyter Notebooks, Spyder, VSCode, etc. Each of them has its own pros and cons that you can consider as per your preferences and workflow.
- Now use virtual environments and create isolated spaces for your projects.
That’s it. You are now ready to use Python for all your data science work.
Data Manipulation with Python
With the help of NumPy, and Pandas, data science professionals can easily handle large datasets. Python thus helps to read and write data from different file formats. Data manipulation also includes common operations on data sets such as filtering rows based on specific conditions, sorting data as required, merging data sets, etc.
Data Visualization with Python
Data Visualization is an important part of the data science career where you need to present the extracted insights in a simple to understand visuals for non-technical audiences. Matplotlib and Seaborn are some of the popular data visualization libraries in Python
Statistical Analysis with Python
Python is also a great tool to perform data science statistical analysis with libraries such as SciPy and StatsModels. It can be used to conduct hypothesis testing, calculate p-values, and perform regression analysis easily
Introduction to machine learning with Python
Machine learning is an important part of data science education. Machine learning helps in building predictive models, and to recognize patterns in data. Python’s Scikit-learn library provides a wide range of tools to perform machine-learning tasks.
Conclusion
In short, if you are starting out on your data science career, then Python is an indistinguishable data science skill that you must learn. You can learn it through several online courses, data science certifications, full-time or part-time college courses, online tutorials, etc. It doesn’t matter how you learn Python, you will have to use it in all your data science jobs. You can learn advanced use of Python in data science through some of the best certification programs available. So, enroll now and start your data science journey today.
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