1 - 9 of 9 Chapters
[Python is an open source programming language created by a Dutch programmer named Guido van Rossum. Named after the British comedy group Monty Python, Python is a high-level, interpreted, open source language and is one of the most sought-after and rapidly growing programming languages in the...
[In this chapter, we progress to some other essential concepts in Python - various types of containers, the methods that can be used with each of these containers, object-oriented programming, classes, and objects.]
[In this chapter, we discuss two modules in Python: re, which contains functions that can be applied for regular expressions, and SymPy, for solving mathematical problems in algebra, calculus, probability, and set theory. Concepts that we will learn in this chapter, like searching and replacing...
[In previous chapters, you were introduced to the Python language – the syntax, functions, conditional statements, data types, and different types of containers. You also reviewed more advanced concepts like regular expressions, handling of files, and solving mathematical problems with Python....
[NumPy, or Numerical Python, is a Python-based library for mathematical computations and processing arrays. Python does not support data structures in more than one dimension, with containers like lists, tuples, and dictionaries being unidimensional. The inbuilt data types and containers in...
[With the explosion of the Internet, social networks, mobile devices, and big data, the amount of data available is humongous. Managing and analyzing this data to derive meaningful inferences can drive decision making, improve productivity, and reduce costs. In the previous chapter, you learned...
[n the last chapter, we read about Pandas, the library with various functions for preparing data in order to make it ready for analysis and visualization. Visualization is a means to understand patterns in your data, identify outliers and other points of interest, and present our findings to an...
[In the last chapter, we looked at the various Python-based visualization libraries and how the functions from these libraries can be used to plot different graphs. Now, we aim to understand the practical applications of the concepts we have discussed so far with the help of case studies.]
[In the previous chapter, we learned about how to apply your knowledge of data analysis by solving some case studies.]
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