#!/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