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Basics of Pandas python library

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1. Basic Dataframes Operations

   • Create Dataframe from a dictionary Sample Notebook
   • Create Dataframe by inserting rows in an iterative way Sample Notebook
   • Create Dataframe with randomly generated data Sample Notebook
   • Create Dataframe from a csv file Sample Notebook
   • Change Dataframe column names Sample Notebook
   • Chose specific columns from a DataFrame Sample Notebook
   • Delete drop columns or extract columns from Dataframe Sample Notebook

2. Manipulating Dataframe

   • Iterate over a dataframe Sample Notebook
   • Apply function to dataframe row wise Sample Notebook
   • Apply function to a specific column of dataframe Sample Notebook
   • Find and replace a value in Dataframe Sample Notebook

3. Split and Merge Dataframes

   • Merge dataframes by columns using join Sample Notebook
   • Merge dataframes by columns on index Sample Notebook
   • Merge dataframe and split again Sample Notebook
   • Group by a dataframe and iterate over grouped series Sample Notebook

4. Convert columns

   • Get binary columns in a DataFrame Sample Notebook
   • Convert categorical columns to integer columns using label encoding Sample Notebook
   • Reduce high dimentionality from categorical column Sample Notebook
   • Convert categorical column to one hot encoded column Sample Notebook

5. Split column

   • Split column usiong a delimiter Sample Notebook
   • Split a column using delimter and one hot encode the values Sample Notebook

6. Adding capabilities to pandas.DataFrame class

   • Extend pandas.DataFrame class to store additional value(s). Sample Notebook