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Add draft bash programming homework
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‎hw/homework.md‎

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Submit source code and write-up (including program output) through Sakai.
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## Instructions
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## Background
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A bunch of your friends really like wine, specifically Portuguese wine. One
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night you all are up all night debating on what physicohemical aspects of wine
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(like pH or acidity) make good wine. Being the sleuth you are, you find out
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that there happens to be [a study and dataset][wine] looking at just this!
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You are conveniently learning Python and bash scripting, and figured this may
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be a good opportunity to provide some evidence for what may be contributing to
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good wine.
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## Deliverables
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[wine]: http://archive.ics.uci.edu/ml/datasets/Wine+Qualityhttp://archive.ics.uci.edu/ml/datasets/Wine+Quality
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## Problem
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The study you reference looked at both red and white wine and you want to find
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out what makes good red and white wine. You wish to conduct a very simple
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analysis.
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## Instruction
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Create a bash script to automate the entirety of your data acquisition and
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analysis to faithfully reproduce your analysis. Your analysis will contain
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Python scripts as well.
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**Download Data**
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Use wget or cURL to help [download the data][data].
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| Wine Type | File Name |
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|-----------|-------------------------|
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| Red | `winequality-red.csv` |
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| White | `winequality-white.csv` |
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Download these data into a directory named `download`.
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**Hint**: Use `mkdir -p` to create a directory if it doesn't exist yet.
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[data]: http://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/
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**Convert Data**
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You like to deal with comma-separated files (CSVs). Unfortunately, you find out
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that the data comes in a "semi-colon" separated file.
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Use `sed` to convert these "semi-colon" separated files into a comma-separated
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files.
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Save these converted data into the directory `data`.
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**Subset Data**
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For your analysis you only want a couple physicochemical variables to check.
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There are a total of 12 variables, but you're only interested in:
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- Citric acid
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- Chlorides
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- pH
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- Alcohol
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- Quality (your outcome)
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In addition to these variables, you want only the good wine and the bad quality
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wine. Create four datasets, each with the threshold of 5 as being the cutoff
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for good wine.
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| File Name | Quality Threshold | Description |
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|-----------------------|-------------------|-------------------------|
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| `red_wine_poor.csv` | <= 5 | Poor quality red wine |
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| `red_wine_good.csv` | > 5 | Good quality red wine |
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| `white_wine_poor.csv` | <= 5 | Poor quality white wine |
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| `white_wine_good.csv` | > 5 | Good quality white wine |
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Put there four files into the `data` directory.
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**Compare Low and High Quality**
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Let's use Python to help us figure out what makes wine good or not.
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Create a Python function to read in data from a given path and calculate the
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average value of a given variable name.
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```python
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# Example use
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avg_chloride_results = calculate_avg_value(data, "chlorides")
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```
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You want to be lazy and automate as much as possible. So let's create a Python
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function that takes in an array of the file names and returns a dictionary.
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The dictionary will have four keys equal to just the file names they come from
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e.g. the key of `white_wine_good.csv` will be `white_wine_good`. The values of
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each key will be another dictionary with each key being the average value of
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one of the four variables we're interested in:
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- Citric acid
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- Chlorides
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- pH
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- Alcohol
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```python
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wine_paths = ["white_wine_good.csv", ...]
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avg_values = find_average_wines(wine_paths)
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```
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**Save Results**
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Write a Python function to save your dictionary of results to four separate
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files. Save your dictionaries as JavaScript Object Notation (JSON) files.
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Use the built-in `json` Python package. Here's a hint on using it.
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```python
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import json
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your_dictionary = {"some_date" : "date"}
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f = open('destFile.txt', 'w+')
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f.write(json.dumps(your_dictionary))
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f.close()
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```
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Save your four results into a directory `results`.
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**Challenge**
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You want to automate everything as much as possible, so you want to create a
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Makefile to make everything.
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```shell
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# Run the entire analysis
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make all
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# Remove all downloaded and intermediate files from data/, download/, results/
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make clean
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```
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## Homework File Structure
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To make things organized, please use the following structure for your data
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analysis.
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```
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.
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|-- analyze_wine.py
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|-- analysis.sh
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|-- data/
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|-- results/
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`-- download/
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```
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## Deliverables
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- A single bash script to automate your analysis
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- A Python script to calculate the average citric acid, chlorides, pH, and
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alcohol values of good and poor quality red and white wine.

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