Data Science is all you can see all over the internet, it might be job vacancies or training from the various institutions. Data Scientists’ requirements growing day by day and with the need the availability of Data Scientists is insufficient. Data Scientist needs to do coding, so he should learn a programming language. Python is the best programming language and mostly used by Data Scientists.
Python helps developers to build programs and prototypes, thereby speeding up the development process. When a project is about to become an analytical tool or application, more advanced languages such as Java or C can be translated if needed.
The simple use that makes Python available means that new data scientists tend to be drawn towards Python. So famous actually, Python’s favorite programming language is estimated by a whopping 48% of data scientists with five or having less than a few years of experience.
This number increases with increasing experience and the study is increased. For data scientists, Python has proved to be a fantastic starting point.
Python has been known for years as a simple programming language, however from a syntax standpoint. Python has a vast selection of libraries and resources as well. The outcome? You have a platform for programming that is useful for emerging technologies like machine learning and data science.
Professionals working with applications in data science do not want to get involved in complicated programming. You want to use programming language like Python, which are easy and anybody can use.
But why programmers go for Python and why it is loved and also why Data scientists need to learn Python. Let’s see the reasoning
Easy to Understand
Python is easy to understand because of the simple English syntax. Not only syntax are easy to understand but coding in Python is simple. Python functionalities are easy and simple
Flexibility in Python
Python is very flexible because of the following factors that are as follows
- A very high-level programming
- A huge community backing
- Easy to understand
- Easy programming
Python is extensible as compared to other programming languages. Python is very flexible for developing any app. If you are missing a few things you will surely get it in the new version of Python. From beginners to professionals Python is preferred all over the world. Any issue related to Python codes can be solved by a discussion on the forum as many programmers prefer Python. For developing an app if you have a team of programmers and if one of the programmers is having no programming background or is a C/C++ programmer still can work developing the app, as a Python programmer.
In-built Libraries and frameworks of Python
Python has a very huge collection of in-built libraries, modules, and frameworks. This is the best feature of Python through which you can develop a high quality app, games, websites, and also algorithm and computation needed for Artificial Intelligence, Data Science, and also in Neural Network and other. Few libraries are as follows
Used for data analysis and data handling. It provides a control for data manipulation control.
Used for numerical computing. A high-level math function, data manipulations, and others are
Used for scientific and technical computing. It is helpful in data optimization and modification, math, some special functions, and others.
Python use in developing the website and web app
With the help of Django and Flask frameworks and libraries are pretty useful for developing a website and web app. The speed at which the development is done is very fast with this Python framework and libraries. With Python, you can develop apps at a very high speed and it also ensures reliability and efficiency as compared to other languages like PHP and others
For web development, we may require
Large Community Backup
Python is open-source and free of cost as you all know so many prefer it, but the major reason is its simplicity and easy-to-understand features along with huge in-built libraries. Python is widely used by large and small companies so Python is widely developed according to the need of companies and recent technological trends. The various community also are backing Python because of this which leads to its development of Python version as per the requirements
Python usefulness in Automation
PyUnit the Python framework is also very useful for automation it is beneficial because of the modules that are in-built, for anyone unit testing will be easy and it is similar to other xUnit frameworks
It is very direct and easy, the programmers just need to name the terminal. The output is short and concise which is best for test cases executions, and we get test reports generated in a very short time
Few are the frameworks for Automation in Python
- Robot Framework
With Python your career growth and employment
Python is an exclusive coding language that is popular, widely used with huge community support. This has open up various job opportunities. Use of Python in different fields like
- Web Development
- Artificial Intelligence (AI)
- Neural Networks
- Deep Learning
- Machine learning
- Data Science
Python libraries used for various ways, that is to develop the game engine a Python libraries are dedicated. Because of these programmers are able to build games which are dress up games, puzzles, shooting, treasure hunt, and so on. Also, Machine Learning and Data Science uses and prefers Python. So you can easily tell that Python experts in the market are unlimited. Also, you can switch jobs easily as you various options. The job profiles that you are eligible for if you are a Python expert is as follows
- Python Developer
- Data Scientist
- Software Developer
- Game Developer
- Product Manager
- Financial Advisors
- Data Journalist
A very high salary package
As a Python professional your average start even it is low but as you go gaining experience you will gain a very high package. If you are very efficient in Python programming than a high salary package is not a problem. You can up to salary ranging from 10 to 15 lakh per annum and also more. So your expertise is your key to a high salary package.
Now let’s see the most basic needs for Data Science. Let us now consider the steps for solving Data Science processes for problem-solving that includes
- Data collection & cleansing
- Data exploration
- Data modeling
- Data visualization & interpretation
Data collection & cleansing
Python allows you to play with virtually all forms of data that is available in various formats, such as comma-separated value (CSV), tab-separated value (TSV), or web-based JSON.
Python will help you accomplish certain tasks easily with dedicated Python libraries, such as PyMySQL and BeautifulSoup, if you want to import SQL tables directly into your code or whether you want to scrap a site. First you can easily connect to a MySQL database to run queries and extract data, and second, read XML and HTML data. You will also need to take care of missing data sets during the data cleaning process and substitute values accordingly after extracting and replacing values.
If you ever get caught with a specific dataset, the powerful and dynamic Python community helps you find a solution by doing your Google search for that dataset and Python!
Now that the data are collected and sorted, ensure that all collected data are standardized. Now that you have clean data, find out the market problem to be addressed and turn it into a topic of data science.
In order to provide the required care, exploring the data to recognize and segregate their properties into various types such as numerical, orderly, nominal, categorical, etc.
If you categorize data by sort, NumPy and Pandas, the Python libraries for data analysis can allow you to unlock knowledge from data by manipulating it quickly and effectively.
It’s time to start AI and machine learning for data modeling now that the data is ready to be used.
This is a very important stage in the process of data science in which you try to minimize the data set dimensionality.
Python has several specialized libraries to help you tap the strength of the computer to carry out data modeling tasks.
Do you want to analyze the data numerically for modeling? Get in your toolkit with NumPy! SciPy allows science computation and calculations to be carried out easily. The Scikit-learn code library provides you with an intuitive and complex interface to apply machine-learning algorithms to your results.
When data modelling has stopped, data for actionable observations can be visualized and interpreted.
Data visualization & interpretation
The data visualization packages in Python are various. Matplotlib is the most commonly used library for simple graphs and charts. If you need advanced graphs that are beautifully built, you can try another library from Python, Plotly.
Another Python library, IPython, facilitates the visualization of interactive data and the use of a GUI toolkit. If you choose to insert your results in interactive Web pages, it will help you transform a wealth of HTML snippets from IPython or Jupyter.
After data visualization, it is extremely important to present the data and to make the results such that they are informed by the business questions you asked at the outset.
Now that you have the answer to your business questions and practical observations, you should note that your interpretations sound beneficial to your organization’s stakeholders.
Either predictive causal analysis or predictive analysis, Python has the tool to perform many powerful functions, regardless of what scientists are trying with Python. No wonder why Python was adopted by data scientists.
If you are Data Scientist you might be aware that you need to deal with numerous data, that needs to be processed to gain insight. In order to process data, we need algorithms that are easily available or developed with Python. So if you want to get a high salary packaged job in reputed companies you need to learn from the well-known and reputed institutes. 3RI Technologies is the best choice for joining Python Online Training, the counselors at 3RI will guide you toward the right course. Also, we offer 100% placement assistance through this many students are placed in well-known companies