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absl-py==0.10.0
cachetools==4.1.1
certifi==2020.6.20
chardet==3.0.4
fsspec==0.8.3
future==0.18.2
google-auth==1.22.1
google-auth-oauthlib==0.4.1
grpcio==1.32.0
idna==2.10

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An example analysis, which follows my project template.

Some data redacted.

Makefile

makefile controls all code (except the Rmd notebooks)

all: clean data process pool

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---
title: "A new analysis workflow"
output: github_document
---

# Organize your data processing program with MECE pieces

*MECE = Mutually exclusive, collectively exhaustive. From McKinsey*

## Summary

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Quick Start

Quickly deploy a Python-Flask app to Heroku from scratch with this tutorial:

• http://blog.shea.io/lightweight-python-apps-with-flask-twitter-bootstrap-and-heroku/

Bonus: nice styling with Bootstrap.

The above is one of the best tutorials I've seen - gives you exactly what you want and nothing you don't need. However, it may be just a tad outdated, so you may have to look at updated docs on heroku.

Examples

Here is one small Flask app that I built:

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A dplyr demo

This demo is meant to give you a flavor of dplyr's functions for data manipulation in R.

After this demo, you may consider using dplyr to make your data analysis easier, faster, and more fun.

Quick Start

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library(tibble)
library(dplyr)

## sample data
df <- frame_data(
    ~x, ~y,  ~z, ~x1, ~x2, ~x3, ~y1, ~y2, ~y99, ~z99, ~zz,
    99, 2,  3.6, 99, 2,  3.6, 99, 2,  3.6, 99, 2,
    99, 2,  3.6, 99, 2,  3.6, 99, 2,  3.6, 99, 2,
    99, 2,  3.6, 99, 2,  3.6, 99, 2,  3.6, 99, 2
)

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TMUX basic commands

Scroll down for more

tmux ls

tmux new -s mysession       # create new

tmux attach -t mysession    # or attach recent:  tmux a

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/* macro to convert variables to indicators*/
/* outputs dataset "df" with patid and the indicator only for easy later merge*/
/* v = var for indicator // n = name of new var(use same prefix with consecutive #s!!) */
%MACRO INDX(v=, n=);
   data df;
       set bmd;
       if &V > . then tt = 1; else tt =0;
       rename tt=&N;
       label
           &N = "&V 0/1"