Getting Started
  • Installing Python and Python libraries
  • Python editors - Spyder and iPython
Downloading Many Files with Python
  • Section introduction
  • Navigating through FTP directory trees with Python
  • Storing Python code
  • Creating an FTP function
  • Downloading an FTP file
  • About the next lecture
  • Practice No.1: Creating an FTP File Downloader
Extracting Data from Archive Files
  • Extracting ZIP, TAR, GZ and other archive file formats
  • Extracting RAR files
  • Practice No.2: Creating a Batch Archive Extractor
Working with TXT and CSV Files
  • Section introduction
  • Reading delimited TXT and CSV files
  • Reading Excel files
  • Exporting data from Python to files
  • Reading fixed width TXT files
  • Exporting data back to HTML and other file formats
  • Data Analysis Exercise 1
  • Data Analysis Exercise 1: Solution
Getting Started with Pandas
  • Get started with Pandas
  • Practice No.3: Calculating and Adding Columns to CSV Files
  • Data Analysis Exercise 2
  • Data Analysis Exercise 2: Solution
Merging Data
  • Practical No.4: Concatenating multiple CSV files
  • Data Analysis Exercise 3
  • Data Analysis Exercise 3: Solution
  • Practice No. 5: Joining Data Based on a Matching Column
  • Data Analysis Exercise 4
  • Data Analysis Exercise 4: Solution
  • Data Analysis Exercise 5
  • Solution: 5 of 6
Data Aggregation
  • Practice No. 6: Pivoting Large Amounts of Data
Visualizing Data
  • Data visualization with Python
  • More visualization techniques
  • Practice No. 7: Producing Image Files
  • Data Analysis Exercise 6
  • Data Analysis Exercise 6: Solution
Mapping Spatial Data
  • Programmatically creating KML Google Earth files with Python
  • Practice No, 8: Creating KML Google Earth fIles from CSV data
Putting everything together
  • User interaction
  • Exercise: User interaction
  • Exercise: User interaction: Solution
  • Practice No. 9: Polishing the Program, I
  • Practice No. 10: Polishing the Program, II
  • Practice No. 11: Creating Python Modules
Bonus Section: Using Python in Jupyter Notebooks to Boost Productivity
  • Getting started with Jupyter Notebooks
  • Data cleaning project, Part I
  • Data cleaning project, Part II
  • Bonus Lecture