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In the U.S., over 36,000 weather forecasts are issued every day that cover 800 different areas and cities. Though some people may complain about the inaccuracy of such forecasts when a sudden spell of rain messes with their picnic or outdoor sports plan, not many spare a thought about how accurate such forecasts often are. That’s exactly what the people at Forecastwatch.com (a leader in climate intelligence and business-critical weather) did.  They assembled all 36,000 forecasts, placed them in a database, and compared them to the actual conditions that existed on that particular day in that specific location. Forecasters around the country then take advantage of these results to improve their forecast models for the subsequent round. Those at Forecastwatch used Python to write a parser for collecting forecasts from other websites, an aggregation engine to assemble the data, and the website code to show the results. Though the company originally used PHP to build the website, it soon realized that it was much easier to only deal with a solitary language throughout. And there lies the beauty of Python, which has become essential for data analysis. Let’s delve deeper to understand what makes Python so popular in the field of data analysis.

In technical aspects, Python is a high-level, object-oriented programming language that comes with integrated dynamic semantics primarily for app and web development. Though it’s often compared to JavaScript, Ruby etc, the major thing that sets apart Python programming language from others is its simplicity. First released in 1991, Python has become one of the most popular programming languages across the globe.

As data has emerged as an integral part of business operations to attain a competitive edge, programming languages like Python and R have become extremely popular among data science professionals. With the advancements in the data science field, both Python and R programmers are becoming most sought after professionals and can enjoy a high-paying, fulfilling career.

With the emergence of data science, business success today heavily depends on the ability of deriving valuable insights from huge chunks of data. And businesses use these insights to develop their business strategies to grow and outperform competitors. In its simplest form, data science can be considered as a field where data is captured and analyzed to reach a logical solution. Previously only giant IT organizations were involved in this but today almost every business across industries like healthcare, finance, e-commerce etc are employing data science to make most out of the data they capture from different sources.

Are you looking to jumpstart your career in data science? Are you trying to make it big as a programmer? If you’ve answered these questions in the affirmative, perhaps you’re planning to get a Python certification. You may have probably seen or heard of Python certification programs being offered by reputed training institutes a lot of times.

You may have already heard that computer coding is one of the most crucial job skills in today’s tech landscape. Coding is infiltrating virtually almost every aspect of work and it’s becoming nearly indistinguishable from common work since tech-related tasks are becoming important parts of even those fields that are less technical. In other words, learning code gives you that much needed competitive edge in today’s job market, no matter whether you do it full-time or part-time. In this post, we’re going to discuss the reasons for which you must concentrate on learning code.

Whether you plan to enter the field of data science, or are already working in it and desire to further your career, devbootcamps can be your ideal bet. Thanks to the prevalent data science wave, data science certification has become one of the most preferred certifications today. Despite there being a huge demand for data scientists, which is increasing rapidly, there’s a huge shortfall in the number of experienced professionals who can fill the rising needs of employers. If you are wondering why there’s this huge shortage of data science professionals, perhaps the reason lies in businesses of all sizes having become aware of the true potential of data science.

In its simplest form, Python is a high-level programming language that’s primarily used for app and web development. Python programming language is relatively simple, which makes it easy to learn as it needs a unique syntax that focuses on readability. Python code can be read and translated by developers much easily compared to other languages.