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Scientific Computing with Python

Scientific Computing with Python

By : Führer, Claus Fuhrer, Solem, Verdier
4.5 (15)
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Scientific Computing with Python

Scientific Computing with Python

4.5 (15)
By: Führer, Claus Fuhrer, Solem, Verdier

Overview of this book

Python has tremendous potential within the scientific computing domain. This updated edition of Scientific Computing with Python features new chapters on graphical user interfaces, efficient data processing, and parallel computing to help you perform mathematical and scientific computing efficiently using Python. This book will help you to explore new Python syntax features and create different models using scientific computing principles. The book presents Python alongside mathematical applications and demonstrates how to apply Python concepts in computing with the help of examples involving Python 3.8. You'll use pandas for basic data analysis to understand the modern needs of scientific computing, and cover data module improvements and built-in features. You'll also explore numerical computation modules such as NumPy and SciPy, which enable fast access to highly efficient numerical algorithms. By learning to use the plotting module Matplotlib, you will be able to represent your computational results in talks and publications. A special chapter is devoted to SymPy, a tool for bridging symbolic and numerical computations. By the end of this Python book, you'll have gained a solid understanding of task automation and how to implement and test mathematical algorithms within the realm of scientific computing.
Table of Contents (23 chapters)
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20
About Packt
22
References

2.4.2 Operations on strings and string methods

The addition of several strings results in their concatenation:

last_name = 'Carlsson'
first_name = 'Johanna'
full_name = first_name + ' ' + last_name
# returns 'Johanna Carlsson'

Consequently, multiplication by an integer is repeated addition:

game = 2 * 'Yo' # returns 'YoYo'

Multiplication by floating-point or complex numbers is undefined and results in a TypeError.

When strings are compared, lexicographical order applies and the uppercase form precedes the lowercase form of the same letter:

'Anna' > 'Arvi' # returns false 
'ANNA' < 'anna' # returns true
'10B' < '11A' # returns true

Among the variety of string methods, we will mention here only the most important ones:

  • Splitting a string: This method generates a list from a string by using a single or multiple blanks as separators. Alternatively, an argument can be given by specifying a particular substring as a separator:
text = 'quod erat demonstrandum'
text.split() # returns ['quod', 'erat', 'demonstrandum']
table = 'Johan;Carlsson;19890327'
table.split(';') # returns ['Johan','Carlsson','19890327']
king = 'CarlXVIGustaf'
king.split('XVI') # returns ['Carl','Gustaf']
  • Joining a list to a string: This is the reverse operation of splitting:
sep = ';'
sep.join(['Johan','Carlsson','19890327'])
# returns 'Johan;Carlsson;19890327'
  • Searching in a string: This method returns the first index in the string, where a given search substring starts:
birthday = '20101210'
birthday.find('10') # returns 2

If the search string is not found, the return value of the method is -1.

  • String formatting: This method inserts values of variables or results of expressions into a string. It is so important that we devote the following subsection to it. 
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