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Data Analysis with Python and Pandas
Introduction to the Course
Course Introduction (4:11)
Getting Pandas and Fundamentals (9:08)
Section Conclusion (2:41)
Introduction to Pandas
Section introduction (0:48)
Creating and Navigating a Dataframe (8:34)
Slices, head and tail (7:59)
Indexing (7:27)
Visualizing The Data (9:19)
Converting To Python List Or Pandas Series (4:15)
Section Conclusion (1:38)
IO Tools
Section introduction (2:12)
Read Csv And To Csv (9:26)
io operations (5:23)
Read_hdf and to_hdf (8:25)
Read Json And To Json (9:54)
Read Pickle And To Pickle (11:41)
Section Conclusion (3:52)
Pandas Operations
Section introduction (2:04)
Column Manipulation (Operatings on columns, creating new ones) (7:27)
Column and Dataframe logical categorization (7:12)
Statistical Functions Against Data (7:34)
Moving and rolling statistics (10:00)
Rolling apply (8:54)
Section Outro (3:17)
Handling for Missing Data / Outliers
Section Intro (3:13)
drop na (6:48)
Filling Forward And Backward Na (11:09)
detecting outliers (12:38)
Section Conclusion (5:17)
Combining Dataframes
Section Introduction (3:53)
Concatenation (9:17)
Appending data frames (7:06)
Merging dataframes (9:43)
Joining dataframes (9:40)
Section Conclusion (4:29)
Advanced Operations
Section Introduction (2:48)
Basic Sorting (8:56)
Sorting by multiple rules (8:34)
Resampling basics time and how (mean, sum etc) (10:03)
Resampling to ohlc (7:12)
Correlation and Covariance Part 1 (10:03)
Correlation and Covariance Part 2 (11:56)
Mapping custom functions (9:23)
Graphing percent change of income groups (7:23)
Buffering basics (10:12)
Buffering Into And Out Of Hdf5 (10:03)
Section Conclusion (3:00)
Working with Databases
Section Introduction (1:00)
Writing to reading from database into a data frame (10:24)
Resampling data and preparing graph (7:54)
Finishing Manipulation And Graph (9:32)
Section and course Conclusion (5:27)
Graphing percent change of income groups
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