Pandas for Data Analysis in Python Video Course

Curriculum For This Course

• 1. Introduction to the Course 1 Videos 00:00:49
  • Installation Instructions 00:49
• 2. IPython Notebooks and Raw Python Data Analysis 5 Videos 00:39:21
  • Tools of the Trade, The IPython Notebook 10:06
  • Maps 07:07
  • Filters 05:45
  • List Comprehensions 06:40
  • Lambda Functions 09:44
• 3. The Basics of NumPy 6 Videos 01:03:30
  • NumPy Array Basics 06:09
  • Boolean Selection 10:20
  • Helpful Methods and Shortcuts 12:59
  • Vectorization 07:08
  • Multi-Dimensional Arrays 14:12
  • Querying Slicing, Combining, and Splitting Arrays 12:42
• 4. Pandas Basics 1 Videos 00:10:40
  • General pandas Concepts 10:40
• 5. pandas Series 5 Videos 00:43:33
  • Overview of the pandas Series 07:25
  • Look Ups, Selections, and Indexing 11:01
  • Advanced Indexing Options 06:56
  • Handling NaN Values, Reindexing, Filling Methods and Series Addition 12:06
  • Series Multiplication, More Reindexing, and Mapping 06:05
• 6. pandas DataFrame 9 Videos 01:22:51
  • DataFrame Basics 10:04
  • Reading Files, Plotting, and Basic Methods 10:45
  • More Plotting, Joins, Basic DateTime Indexing, and Writing to Files 11:53
  • Adding & Reseting Columns, Mapping with Functions 07:14
  • More Mapping, Filling NaN values, Plotting, Correlations, and Histograms 10:17
  • More Plotting, Rolling Calculations, Basic DateTime Indexing 05:52
  • Analysis Concepts, Filling NaN Values, Cumulative Sums and Value Counts 09:20
  • Data Maintenance, Adding/ Removing Columns and Rows 08:18
  • Basic Grouping, Concepts of Aggregate Functions 09:08
• 7. BONUS: Advanced pandas Topics 4 Videos 00:45:10
  • pandas.IO.Data, Panels and Hierarchical Indexing 11:42
  • Advanced Reading Csvs/HTML, Binning, Categorical Data 12:43
  • Advanced Groupings and Aggregate Functions 07:56
  • More Grouping Functions including Apply and Transform 12:49