Part 2 of a first-time training around time series forecasting aimed at Finance Analysts in my company, focused on model evaluation.

Time Series Forecasting 102 for Finance Analysts

Part 1 of a first-time training around time series forecasting aimed at Finance Analysts in my company, focused on identifying types of models used in modern forecasting.

Time Series Forecasting 101 for Finance Analysts

A few tips on making your Dash application look a little better

Dash (Plotly) tips - Latex, Google Fonts, and more

What would common SQL expressions look like in Julia DataFrames and Julia DataFramesMeta?

A SQL to Julia DataFrames Cheatsheet

How to build custom financial calendars that have 52 or 53 workweeks in a fiscal year (aka the 4-4-5 calendar) using `pandas`

Making Custom Fiscal 52/53 Workweek Calendars in Pandas

What it takes to update from a previous install of Julia on Mac/Linux

Updating Your Julia Installation (Mar 2022)

Merging two dataframes with pandas but only if certain conditions are true.

Python Pandas - Merging With Wildcards and Conditions

TLDR on how to make a corporate themed plotly template

Making a Basic Corporate Plotly Template

My steps for a fresh install of Windows Subsystem for Linux for Data Analysis

Getting Started with WSL for Data Analysis

Quick reference that shows options to add plotly charts to a markdown document

Adding Plotly Charts to Markdown

ggplot2 for Python is definitely a thing. Oh, and Altair's ok too.

'Tie Fighter' Errorbar Charts in Python with Plotnine and Altair

Basic shell scripting for everyday productivity.

Quick Bash Script for Complete Newbies

Code snippet to create a clean line chart to go in a Dash Card.

Clean Sparkline-style Line Chart for Dash Cards

Code snippet to create a starter KPI card with Dash Bootstrap Components

KPI Card with Dash Bootstrap Components

Code snippet to create a PnL (Profit and Loss Statement) Dataframe in Pandas

Make a Basic PnL Dataframe in Pandas

Getting started using the `forecast` package for time series data in R, as quickly as possible and no explanations.

Time Series Cheat Sheet in R

A collection of responses from Caitlin Hudon's twitter thread on 'how to ask a good data question.' (Updated 2020-03-15)

How to Ask Good Data Questions

My local data mart runs on MS SQL Server, and I want to pull data directly into R or Python for data analysis. This is **really** easy on Windows with its' built-in ODBC manager, but I spent a weekend figuring out how to do this after switching to OSX. A lot of documentation out there is old (from 2012), so I decided to make this for anyone still looking for an answer in 2019.

How to set up ODBC in Mac OS to connect to MS SQL Server for use with Python and R

Excel is still the lingua franca of Corporate Finance and is blazing fast for quick, ad-hoc analyses. I learned early on to use excel without a mouse, and with the Quick Access Toolbar and some macros, you can even make Excel feel like a video game!

Fast Excel with the Quick Access Toolbar

From [HBR: 3 Habits to Improve Critical Thinking](https://hbr.org/2019/05/3-simple-habits-to-improve-your-critical-thinking) by [Helen Lee Bouygues](hbr.org/search?term=helen%20lee%20bouygues). A good read for anyone looking to keep their critical thinking muscles sharp as told through stories from Bouygues' experience as a board member and consultant. They might seem obvious, but I'll admit that I don't always consider these.

Latest

Time Series Forecasting 102 for Finance Analysts

Time Series Forecasting 101 for Finance Analysts

Dash (Plotly) tips - Latex, Google Fonts, and more

A SQL to Julia DataFrames Cheatsheet

Making Custom Fiscal 52/53 Workweek Calendars in Pandas