Python for Accounting. A Modern Guide Python Programming in Accounting

Description

Contents Introduction What this book is about Whom this book is for Why read this book A quick tour of Python's data tools How to use this book Roadmap Getting set up Installing Python on your computer Setting up your local workspace Using JupyterLab Using Anaconda Navigator Python ABCs A quick look at Python code Variables and operators Everything is an object Point me to the values The cycle of a variable's life Operators Python's built-in data types Integers Floating-point numbers Booleans The None type Strings Associated built-in functions Python's built-in collections Lists Overthinking: Tuples and sets Dictionaries Membership operators Associated built-in functions Control flow If-else statements Loops List comprehensions Functions Defining functions Parameters and arguments Return values Modules, packages, and libraries Modules and packages Libraries How to find help Jupyter notebook helpers Finding help online Overthinking: code style Naming variables and functions Breaking long lines of code Spacing around operators Code comments Working with tables Pandas in a nutshell Getting started Reading data from spreadsheets Preparing and transforming data Visualizing data Writing data to a spreadsheet Tables, columns, and values Series DataFrame Index and axes Values and types Reading and writing Excel files Reading Excel files Inspecting data Writing Excel files Slicing, filtering, and sorting tables Selecting columns Removing columns Selecting rows and columns Filtering data Sorting data Project: Organizing sales data by channel Adding and modifying columns Adding columns Renaming columns Replacing values Assigning new values to a table slice Filter and edit Summarizing data Counting unique values Averages and numerical summaries High-level table information Cleaning data Dealing with missing values Dealing with duplicate rows Converting column data types Project: Reading and cleaning a QuickBooks general ledger Working with text columns Revisiting Python strings String methods in pandas String data types in pandas Overthinking: Regular expressions Working with date columns Revisiting Python dates Date columns Pandas date methods Pandas date arithmetic Overthinking: Timezones Applying custom functions Applying functions to columns Overthinking: Functions without a name Applying functions to rows Overthinking: Other function parameters Project: Mining product reviews Concatenating tables Row-wise concatenation Column-wise concatenation Appending rows to a DataFrame Joining tables How joins work Joins in pandas Inner, outer, left, and right joins More joining options Project: Filling missing product names in the sales data Groups and pivot tables How group operations work Group operations in pandas Stacking and unstacking Pivot tables Overthinking: Changing how DataFrames are displayed Setting display options Styling tables Visualizing data Plotting with matplotlib Elements of a matplotlib plot Plotting basics Adjusting plot details Overthinking: Styles, colors, and fonts Project: Making a waterfall plot from a cash flow statement Other plotting libraries Plotting with pandas Plotting with seaborn Using matplotlib, pandas and seaborn together Overthinking: Interactive plots Sales analysis project Setting up your project Files and folders Documenting your analysis Preparing data Product and cost data Sales data Finding answers Channel profits Category profits Channel and category profits Product profits Sharing results Next steps