2015
Udemy
Ardit Sulce
3:50
English

Are you struggling to create a real-world Python program? Are you interested in using Python for working with any kind of data? You don't know where to start? Do you need to learn the basics and then jump into a real world program, all in one course?
If any of the above identifies with you, then this complete course is the Python course you have been looking for. In this complete course, you will learn how to program with Python starting from the basics and slowly shifting into practical concepts such as handling multiple files and data containing millions of rows and extracting and visualizing information from them.

Section 1: Getting Started
Introduction to the course
A few words about Python
Easily installing Python and its specialized libraries
Spyder and iPython
Section 2: Python Basics
Variables
Strings and numbers - Quiz 2
If, else, and indentation
Functions
Sequences
Collections
Working with sequences and strings
Iterating
Section 3: Working with Files and Folders
Working with files
Working with folders
Handling files easily
Manipulating directory paths
Iterating through files
Section 4: Downloading Files from FTP Sites
Section intro
Logging in to an FTP site and browsing through FTP files
Running Python code from the editor
Creating an FTP function
Downloading an FTP file
Practical No.1: Creating a FTP File Downloader
Section 5: Working with Archive Files
Extracting ZIP, TAR, GZ and other archive file formats
Extracting RAR files
Practical No.2: Creating a batch archive extractor
Section 6: Reading and Writing TXT and CSV Data Files
Section intro
Reading delimited TXT and CSV files
Exporting data back to files
Reading fixed width TXT files
Exporting data back to HTML and other fIle formats
Section 7: A tour with pandas
Introducing pandas - the great Python data analysis library
Practical No.4: Calculating and adding columns to CSV files
Section 8: Concatenating and Joining Tables of Data with Pandas
Practical No.5: Concatenating multiple CSV files
Practical No. 6: Joining data based on a matching column
Section 9: Pivoting Data
Practical No. 7: Pivoting large amounts of data
Section 10: Visualizing Data
How to perform visualizations in Python
More visualization techniques
Practical No. 8: Generating an image file graph
Section 11: Mapping Spatial Data
Creating KML Google Earth files
Practical No, 9: Creating KML Google Earth fIles from CSV
Section 12: Putting everything together
User interaction
Practical No. 9: Polishing the program, I
Practical No. 10: Polishing the program, II
Practical No. 11: Creating a Python module out of your program

Download File Size:923.58 MB

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