Download e-book for kindle: Learn Python Visually by Ivelin Demirov

By Ivelin Demirov

ISBN-10: 1507727070

ISBN-13: 9781507727072

Examine Python Visually is a contemporary leap forward that makes studying programming extra intuitive, more uncomplicated, and enjoyable. utilizing the main easy method of studying that all of us inherently recognize from formative years, "Learn Python VISUALLY" solves the comprehension challenge that such a lot of different books can't appear to bridge. visible newbies keep info very in a different way than their left brained counter-parts, and hence reap the benefits of diverse techniques. complete colour illustrations aid reminiscence triggers as your mind by no means forgets a picture, metaphor or schema. Illustrations could make an international of distinction over strictly phrases on a web page! should you came upon your self suffering from programming, then this visible publication will be your resolution.

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About This booklet
• layout and troubleshoot desktop studying platforms for universal initiatives together with regression, category, and clustering
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Additional resources for Learn Python Visually

Sample text

It stands for Comma Separated Values, which almost explains all the formatting there is. ) Python has a module called csv that supports reading and writing CSV files in various dialects. Dialects are important because there is no standard CSV and different applications implement CSV in slightly different ways. A file's dialect is almost always recognizable by the first look into the file. Getting ready What we need for this recipe is the CSV file itself. csv. We assume that sample datafiles is in the same folder as the code reading it.

So even with decent file sizes, doing something as simple as the following code will work straight out of the box: with open('/tmp/my_big_file', 'r') as bigfile: for line in bigfile: # line based operation, like 'print line' 46 Chapter 2 But if we want to jump to a particular place in the file or do other nonsequential reading, we will need to use the handcrafted approach and use IO functions such as seek(), tell(), read(), and next() that allow enough flexibility for most users. Most of these functions are just bindings to C implementations (and are OS-specific), so they are fast, but their behavior can vary based on the OS we are running.

This can also come from an Excel export but can be the output of some custom software we must get our input from. The good thing is that usually this format can be read in almost the same way as CSV files, as the Python module csv supports so-called dialects that enable us to use the same principles to read variations of similar file formats—one of them being the tab delimited format. Getting ready We are already able to read CSV files. If not, please refer the Importing data from CSV recipe first.

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Learn Python Visually by Ivelin Demirov

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