An intro to data analysis with programming

Class steps

• What is programming?

  • Telling your computer what to do, generally using written instructions called code

• How is your computer put together?

  • GUI vs no GUI
  • Wizard of OZ -- now you are the wizard

• Your friend, the command line

• Your shape-shifting, loyal best friend, the prompt (alebrije?)

• cd, ls stuff from TechRaking

• What is a program?

  • A set of written instructions
  • A recipe written like a poem

  The worst poems ever written

  there's nothing like the feeling unique when you find the record you seek

  read me a line of the spreadsheet, please tell me about infectious disease!

• Ways to run code

  • Shell
  • File

print('See Jane run.')
print('Run, Jane, run.')
print("Run the program many times until it doesn't crash.")

• Errors are good now.
  • Read from the bottom up
  • Look for things that are your fault
• Jupyter
• spaces and punctuation -- what do they mean?
• variables and data types

my_name = 'Mike' my_age = 38 my_license_plate = 'DWZ 147'

• operators addition vs. concatenation 2 + 2 'Hello' + 'world' '2' + '2'

= vs. == 2 + 2 == 4 2 + 2 == 5 2 + 2 != 5

• conditionals

my_num = 2 if my_num == 6: print('Yes, it does.')

else: print('No, that would make no sense.')

• iterables my_list_of_nums = [2, 3, 1, 7, 894] my_list_of_dog_names = ['Reggie', 'Sadie', 'Charlotte']

• loops for thingy in my_list_of_nums: print(thingy)

for thingy in my_list_of_dog_names: print(thingy)

total = 0 for thingy in my_list_of_nums: total += thingy total

• Functions and methods

A function is a little factory: You put raw materials in, do some work, and something comes out.

def my_factory(first_ingredient, second_ingredient): final_product = first_ingredient + second_ingredient return final_product

my_factory(2, 2) my_factory(7, 3)

• Pandas/what are modules import pandas as pd

• Read a CSV

• Join/Merge

• Group by

• Sort

• Basic chart

Bootstrapping steps

We have installed several software packages in order to conduct the training and so you can work with these tools on your own.

• pip
• pyenv
• pyenv-virtualenv
• pandas
• vega
• altair

Step-by-step instructions to reproduce the environment (Mac-only)

• Mac dev tools/Xcode thingy

• build-essential

• homebrew

• pip

• Dependencies?

• Check out repository

• install requirements.txt

# First, test to see what might already be installed
brew install  # If it doesn't say "command not found" brew might already be installed
pip install  # If it doesn't say "command not found" pip might already be installed

/usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
brew update

brew install pip  # Not sure if this will cover the pyenv pip or not -- we'll find out!
# Or, if brew install pip doesn't work...
brew install python # Don't do this if brew install pip worked.

brew install pyenv
echo 'export PYENV_ROOT="$HOME/.pyenv"' >> ~/.bash_profile
echo 'export PATH="$PYENV_ROOT/bin:$PATH"' >> ~/.bash_profile
echo -e 'if command -v pyenv 1>/dev/null 2>&1; then\n  eval "$(pyenv init -)"\nfi' >> ~/.bash_profile
exec "$SHELL"
# (Open new Terminal tab)
pyenv install 3.7.0
brew install pyenv-virtualenv
echo 'eval "$(pyenv virtualenv-init -)"' >> ~/.bash_profile
exec "$SHELL"
# (Open new Terminal tab)
pyenv virtualenv 3.7.0 jupyterpandas
mkdir ~/Documents/Reveal
cd ~/Documents/Reveal/
# (Sign up for github account if you dont' have one.)
git config --global user.name "Human readable name"
git config --global user.email "email@email.com"
git clone https://github.com/cirlabs/JupyterPandasTraining.git
cd JupyterPandasTraining
pip install -r requirements.txt