Data Analysis with Python and Pandas


Data Analysis with Python and Pandas. data analysis with Python,Visualize datasets

100,00  10,00 

The name of this course is Data Analysis with Python and Pandas. The knowledge you will get with this indescribable online course is astonishing. data analysis with Python,Visualize datasets.
Not only will you be able to deeply internalize the concepts, but also their application in different fields won’t ever be a problem. The instructor is Stone River eLearning, one of the very best experts in this field.

Description of this course: Data Analysis with Python and Pandas

Course Description Python programmers are some of the most sought-after employees in the tech world, and Python itself is fast becoming one of the most popular programming languages. One of the best applications of Python however is data analysis; which also happens to be something that employers can’t get enough of. Gaining skills in one or the other is a guaranteed way to boost your employability – but put the two together and you’ll be unstoppable!Become and expert data analyserLearn efficient python data analysis Manipulate data sets quickly and easily Master python data mining Gain a skillset in Python that can be used for various other applicationsPython data analytics made SimpleThis course contains 51 lectures and 6 hours of content, specially created for those with an interest in data analysis, programming, or the Python programming language. Merienda you have Python installed and are ordinario with the language, you’ll be all set to go. The course begins with covering the fundamentals of Pandas (the library of data structures you’ll be using) before delving into the most important functions you’ll need for data analysis; creating and navigating data frames, indexing, visualising, and so on. Next, you’ll get into the more intricate operations run in conjunction with Pandas including data manipulation, logical categorising, statistical functions and applications, and more. Missing data, combining data, working with databases, and advanced operations like resampling, correlation, mapping and buffering will also be covered.By the end of this course, you’ll have not only have grasped the fundamental concepts of data analysis, but through using Python to analyse and manipulate your data, you’ll have gained a highly specific and much in demand skill set that you can put to a variety of practical used for just about any business in the world. Tools UsedPython: Python is a caudillo purpose programming language with a focus on readability and concise code, making it a great language for new coders to learn. Learning Python gives a solid foundation for learning more advanced coding languages, and allows for a wide variety of applications.Pandas: Pandas is a free, open source library that provides high-performance, easy to use data structures and data analysis tools for Python; specifically, numerical tables and time series. If your project involves lots of numerical data, Pandas is for you.NumPy: Like Pandas, NumPy is another library of high level mathematical functions. The difference with NumPy however is that was specifically created as an extension to the Python programming language, intended to support large multi-dimensional arrays and matrices.

Requirements of this course: Data Analysis with Python and Pandas

What are the requirements? Students should have Python installed Students should be ordinario with the Python programming language, specifically Python 3+

What will you learn in this course: Data Analysis with Python and Pandas?

What am I going to get from this course? Input and output data from a variety of data types Manipulate data sets quickly and efficiently Visualize datasets Apply logic to data sets Combine datasets Handle for missing and erroneous data

Target audience of this course: Data Analysis with Python and Pandas

Who is the target audience? Those interested in data analysis with Python People looking for methods to normalize the handling of multiple data types and databases Those interested in efficient data manipulation Those brand new to programming or Python should not take this course