#!/usr/bin/env python # coding: utf-8 # # Python for SAS Users # # Chapter orginization # # These chapters are meant to be read in order as they start with foundational concepts used to build up more complex ideas. # # Chapter 00 -- Motivation # # Chapter 01 -- Introduction # # Chapter 02 -- Data Sctructures # #        list # #        indexing # #        tuple # #        dictionary # #        sequences # #        set # #        Resources # # Chapter 03 -- Data Types and Formatting # #        Numerics # #        Boolean # #        Numerical Precision # #        Strings # #        String Slicing # #        String Formatting # #        Resources # # # Chapter 04 -- Pandas, Part 1 # #        Importing Packages # #        Series # #        DataFrames # #        Read .csv files # #        Inspection # #        Missing Values Identification # #        Missing Value Replacement # #        Resources # # # Chapter 05 -- Understanding Indexes # #        Indices # #        .iloc indexer # #        Setting and resetting Indicies # #        .loc indexer # #         Mixing .loc indexer with Boolean Operations # #         Altering DataFrame values using the .loc indexer # #        Conditionaly Apply Values Based on Another Column Value # #         .ix indexer # #         Indexing Issues # #         Resources # # # Chapter 06 Hierarchical Indexing # #        Multi Indexed Selection # #        xs() method for Cross-sections # #        Advanced Indexing with .loc Indexer # #        Using Boolean Operators with .loc Indexer # #        stack() and unstack() methods # #        Resources # # # Chapter 07 -- Pandas, Part 2 # #        SAS Sort/Merge with by-groups # #        Inner Join # #        Right Outer Join # #        Left Outer Join # #        Full Outer Join # #        Outer Join no Matched Keys # #        Outer Join no Matched Keys in Right # #        No Matched Keys in Left # #        Many-to-Many Join # # #        GroupBy: Split-Apply-Combine Introduction # #        Replace Missing Values with Group Mean # #        FIRST.variable and LAST.variable Processing # #         Resources # # Chapter 08 -- Date, Time and Timepart Objects # #        String Literal Mapped to datetime timestamp # #        date objects # #        strfime() and strptime() methods # #        dateutil.parser # #        time objects # #        timedelta objects # #        Resources # # Chapter 09 -- Panda Time Series and Date Handling # #        Creating and Manipulating a Fixed Frequency of Dates and Time Spans # #        Time-Series Walk-through # #        Returning Unique Levels of Categories # #        Return a Row Using a Minimum Value # # #        Return a Row Using a Maximum Value # #        Convert Time-Series from one Frequency to Another # #        Plotting with bokeh # #        Resources # # Chapter 10 -- GroupBy # #        Setting Display Options # #        Read 'pickled' DataFrame # #        Create GroupBy Object # #        GroupBy with Aggregations # #        Understanding Binning # #        Applying Functions to Groups # #        Applying Transformations to Groups # #        Top/Bottom N Processing # #        Resources # # Chapter 11 -- Panda Readers # #        pd.read_csv(URL) method # #        SQLAlchemy Under the Covers # #        read_sql_table() method # #        read_sql_query()method # #        DataFrame.to_sql() method # #        pd.read_sas() method # #        Resources # # Chapter 12 -- Additional Data Handling # #        Sort and Sort Sequences # #        Drop/Keep Columns # #        Rename Columns # #        Find Duplicate Values # #        Drop Duplicate Rows # #        Extract Duplicate Values # #        Add a New DataFrame Column # #        Cast Strings to Float # #        Concatenating DataFrames (Join) # #        Crosstabs # #        Sampling # #        Binning Continous Values # #        Save to Disk ('pickling') # #        Resources # # ## Navigation # # Return to Chapter List