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    \title{Chapter00 - Table Of Contents}
    
    
    

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    \begin{document}
    
    
    \maketitle
    
    

    
    Table of Contents

    The material consists of two parts, Python and R for SAS users.~These
chapters are meant to be read in order (within the respective part) as
they start with foundational concepts used to build up more complex
ideas.

Part 1 Python for SAS Users

~

Chapter00 -~Preface~

Chapter01 -~Table of Contents~

Chapter 1 -~Data Structures

list

indexing

tuple

dictionary

sequences

set

Resources

Chapter 2~-~Data Types and Formatting

Numerics

Boolean

Numerical Precision

Strings

String Slicing

String Formatting

Resources

Chapter 3 -~Pandas, Part 1

Importing Packages

Series

DataFrames

Read .csv files

Inspection

Missing Values Identification

Missing Value Replacement

Resources

Chapter 4 -~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 5 - 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 6 -~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 7 -~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 8 -~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 9 -~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 10 -~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 11~-~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

Part 2 - R for SAS Users

Work In Progress

~

    Navigation

 Return to Chapter List 


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