Chapter I.pptx
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Python is widely used for data science and analysis tasks. Approximately 40% of data scientists use Python in their daily work to collect, analyze, and report data from various sources. Large organizations such as NASA, Google, and CERN also rely heavily on Python for programming tasks. Python has become popular for data science due to its many prebuilt libraries for tasks like data manipulation and visualization, its simplicity, extensive community support, growing popularity, and platform independence.
Chapter I.pptx
- 1. The Role of Python for Data Science In the United States, over 36,000 weather forecasts are issued every day, covering 800 different regions and cities. All that analysis, collection, and reporting of data from different sources. about 40% of data scientists use Python in their day-to-day work for computing, analyzing and reporting of data. Big organizations such as NASA, Google, and CERN also use Python for almost every purpose of programming.
- 2. The Role of Python for Data Science All About Data Analysis Data analysis is the method of accumulating important data and processing that data to get useful insights. A data scientist utilizes the major techniques that are related to data manipulation and data visualization. Python vs R: Which is Good for Data Science? Both Python and R are popular choices for data scientists. Both languages have some pros and cons when it comes to data-centric software development services. While both of these languages are competing to be the language of choice for data scientists, let’s have a quick look at their share and compare 2016 with 2017. Now the below-mentioned picture shows the number of jobs that are related to data science by any programming languages. Data Source: StackOverflow Also, it is seen that Python developers are more loyal to this platform. Have a look at below stats:
- 3. The Role of Python for Data Science Why is Python Awesome for Data Science? five exciting things about Python that makes it the best programming language for data scientists. 1. Prebuilt Libraries One of the most important characteristics of Python is the list of libraries and frameworks that makes coding easier and saves a lot of development time 2. Simplicity Python is well known for its incisive and readable code. Also, no other language can compete with it for being easy to use and simple. 3. Enough support Python is an open-source programming language supported by a plethora of resources as well as high- quality documentation. 4. Popularity Since python is among the topmost programming languages as it is simple to understand syntax structure. 5. Not Platform Specific It can be said that this language is not platform-specific. Instead, it is platform-independent.