Why Learn Python for Data Science?

As the IT industry is spreading its branches, there is a growing demand for Python. Day by day the demand for Data Science is also increasing. Data Science is a must-learn skill in the latest trend and Python is important for it. Let’s see why.

Data Science is one of the most demanding fields. It has a promising career in the future. It continues to evolve as one of the most claiming fields for professionals. Data Science has problem-solving capabilities. It has the advanced talent of analyzing a large set of data. It can capture, maintain, process, analyze, and communicate.

Data Science is used to extract information from various forms of data. It provides you with a wide range of techniques to extract information.

Data Science is Enhancing the use of Python

Python is the most widely used language in IT industries. One of the reasons behind the popularity of Python is its intense use in Data Science. Python is the best-suited language for Data Science. It is chosen for data science because of the following reasons:

• Python is an open-source programming language.
• It is simple, flexible, extensible, and portable.
• Its code syntax is highly readable and can be written in fewer lines of code. Hence, it is time-saving.
• Python provides many libraries and frameworks for Data Science, Machine learning, Artificial Intelligence, Data Analysis, Image processing, Audio processing, etc.

Python has now become the go-to language for Data Science. It has a bulk of utilities in the field of Data Science. It is also used in statistical analysis. Python has made the evolution of various IT fields easy.

Various Python Libraries for Data Science

Python contains a large number of libraries that are beneficial for Data Science. These libraries consist of functions that can perform special functions for Data Science. The list of libraries is:

• Pandas
• NumPy
• Scikit-Learn
• Seaborn
• Matplotlib
• SciPy
• TensorFlow
• PyBrain

Basics of Python for Data Science

Python is one of the best languages to study Data Science. There are some basics of Python that are necessary to learn. Python contains variables, data types, operators, loops, control statements, etc. There is no need to declare variables in Python. It is a reserved space in the memory. There is a variety of data types like numeric, string, character, set, dictionary, etc.

Python program for Data Science begins with Data loading.

Loading of data is the first task to load the data into the program. For this very first step, the Pandas library is the most useful. Pandas contain functions that are suitable to load data into the Python program. After this, the nest task to check for any impurities in the data. So, we explore the data.

Cleansing of data takes place then. We either remove the null values or replace them with other significant values.

After the cleaning of data, the Visualization of data takes place. Using visualization techniques, we understand the relationship between various aspects of data. At last, the result is drawn. We hence make the conclusions and frame the solution.

Conclusion

We have seen why python is important for data science. Python is very simple are easy to read the language. It is highly flexible. Due to its high readability, it is one of the most demanding languages. These are the reasons Python is extensively useful in Data Science. Python can perform various tasks for Machine Learning and Artificial Intelligence. It can open all doors for you. It has a plethora of libraries that a data scientist needs. Hence, Python plays an important role in the field of Data Science.