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‎README.md‎

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@@ -30,11 +30,11 @@
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- [<span class="toc-section-number">2.17</span> (Optional) Things we didn't talk about](#optional-things-we-didnt-talk-about)
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- [<span class="toc-section-number">2.18</span> (Optional) Introspecting on the DataFrame object](#optional-introspecting-on-the-dataframe-object)
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- [<span class="toc-section-number">3</span> Building Programs (Week 3)](#building-programs-week-3)
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- [<span class="toc-section-number">3.1</span> Notebooks vs Python scripts](#notebooks-vs-python-scripts)
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- [<span class="toc-section-number">3.2</span> (Optional) Python from the terminal](#optional-python-from-the-terminal)
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- [<span class="toc-section-number">3.3</span> Looping Over Data Sets](#looping-over-data-sets)
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- [<span class="toc-section-number">3.4</span> Conditionals](#conditionals)
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- [<span class="toc-section-number">3.5</span> Writing Functions](#writing-functions)
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- [<span class="toc-section-number">3.1</span> Looping Over Data Sets](#looping-over-data-sets)
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- [<span class="toc-section-number">3.2</span> Conditionals](#conditionals)
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- [<span class="toc-section-number">3.3</span> Writing Functions](#writing-functions)
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- [<span class="toc-section-number">3.4</span> Notebooks vs Python scripts](#notebooks-vs-python-scripts)
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- [<span class="toc-section-number">3.5</span> (Optional) Python from the terminal](#optional-python-from-the-terminal)
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- [<span class="toc-section-number">3.6</span> (Optional) Use pathlib to write code that works across operating systems](#optional-use-pathlib-to-write-code-that-works-across-operating-systems)
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- [<span class="toc-section-number">3.7</span> (Optional) Generic file handling](#optional-generic-file-handling)
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- [<span class="toc-section-number">3.8</span> (Optional) Text processing and data cleanup](#optional-text-processing-and-data-cleanup)
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Capture the results of your filter in a new file, rather than overwriting your original data.
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``` python
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# Save to a new CSV, preserving your original data
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data.to_csv('gapminder_gdp_europe_grouped.csv')
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1. Create a new subdirectory called "processed" using the editor's file interface.
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# If you don't want to preserve row names:
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data.to_csv('gapminder_gdp_europe_grouped.csv', index=False)
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```
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2. Save your data as a CSV in the subdirectory
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``` python
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# Save to a new CSV, preserving your original data
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data.to_csv('gapminder_gdp_europe_grouped.csv')
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# If you don't want to preserve row names:
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data.to_csv('gapminder_gdp_europe_grouped.csv', index=False)
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```
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## Working with missing data
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# Building Programs (Week 3)
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## Notebooks vs Python scripts
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### Differences between .ipynb and .py
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1. Export notebook to .py file
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2. Move .py file into data directory
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3. Compare files in TextEdit/Notepad
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### Workflow differences between notebooks and scripts
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Broadly, a trade-off between managing big code bases and making it easy to experiment. See: <https://github.com/elliewix/Ways-Of-Installing-Python/blob/master/ways-of-installing.md#why-do-you-need-a-specific-tool>
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1. Interactive testing and debugging
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2. Graphics integration
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3. Version control
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4. Remote scripts
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## (Optional) Python from the terminal
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1. Python is an interactive interpreter (REPL)
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``` bash
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python
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```
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2. Python is a command line program
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``` python
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# hello.py
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print("Hello!")
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```
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``` bash
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python hello.py
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```
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3. (Optional) Python programs can accept command line arguments as inputs
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1. List of command line inputs: `sys.argv` (<https://docs.python.org/3/library/sys.html#sys.argv>)
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2. Utility for working with arguments: `argparse` (<https://docs.python.org/3/library/argparse.html>)
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## Looping Over Data Sets
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### File paths as an example of increasing abstraction in program development
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``` python
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def print_date(year, month, day):
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joined = '/'.join([year, month, day])
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print(joined)
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"""Print the formatted date. This works with strings or integers."""
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formatted_date = f"{year}/{month}/{day}"
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print(formatted_date)
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print_date(1871, 3, 19)
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```
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<https://matplotlib.org/stable/gallery/mplot3d/lorenz_attractor.html>
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## Notebooks vs Python scripts
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### Differences between .ipynb and .py
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1. Export notebook to .py file
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2. Move .py file into data directory
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3. Compare files in TextEdit/Notepad
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### Workflow differences between notebooks and scripts
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Broadly, a trade-off between managing big code bases and making it easy to experiment. See: <https://github.com/elliewix/Ways-Of-Installing-Python/blob/master/ways-of-installing.md#why-do-you-need-a-specific-tool>
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1. Interactive testing and debugging
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2. Graphics integration
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3. Version control
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4. Remote scripts
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## (Optional) Python from the terminal
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1. Python is an interactive interpreter (REPL)
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``` bash
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python
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```
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2. Python is a command line program
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``` python
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# hello.py
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print("Hello!")
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```
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``` bash
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python hello.py
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```
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3. (Optional) Python programs can accept command line arguments as inputs
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1. List of command line inputs: `sys.argv` (<https://docs.python.org/3/library/sys.html#sys.argv>)
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2. Utility for working with arguments: `argparse` (<https://docs.python.org/3/library/argparse.html>)
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## (Optional) Use pathlib to write code that works across operating systems
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1. Pathlib provides cross-platform path objects

‎README.org‎

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@@ -1447,13 +1447,15 @@ print(z_bool)
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** Write output
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Capture the results of your filter in a new file, rather than overwriting your original data.
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#+BEGIN_SRC python
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# Save to a new CSV, preserving your original data
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data.to_csv('gapminder_gdp_europe_grouped.csv')
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1. Create a new subdirectory called "processed" using the editor's file interface.
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2. Save your data as a CSV in the subdirectory
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#+BEGIN_SRC python
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# Save to a new CSV, preserving your original data
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data.to_csv('gapminder_gdp_europe_grouped.csv')
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# If you don't want to preserve row names:
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data.to_csv('gapminder_gdp_europe_grouped.csv', index=False)
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#+END_SRC
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# If you don't want to preserve row names:
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data.to_csv('gapminder_gdp_europe_grouped.csv', index=False)
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#+END_SRC
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** Working with missing data
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*** By default, most numerical operations ignore missing data
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#+END_SRC
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* Building Programs (Week 3)
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** Notebooks vs Python scripts
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*** Differences between .ipynb and .py
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1. Export notebook to .py file
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2. Move .py file into data directory
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3. Compare files in TextEdit/Notepad
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*** Workflow differences between notebooks and scripts
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Broadly, a trade-off between managing big code bases and making it easy to experiment. See: https://github.com/elliewix/Ways-Of-Installing-Python/blob/master/ways-of-installing.md#why-do-you-need-a-specific-tool
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1. Interactive testing and debugging
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2. Graphics integration
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3. Version control
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4. Remote scripts
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** (Optional) Python from the terminal
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1. Python is an interactive interpreter (REPL)
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#+BEGIN_SRC bash
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python
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#+END_SRC
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2. Python is a command line program
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#+BEGIN_SRC python
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# hello.py
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print("Hello!")
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#+END_SRC
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#+BEGIN_SRC bash
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python hello.py
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#+END_SRC
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3. (Optional) Python programs can accept command line arguments as inputs
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1. List of command line inputs: ~sys.argv~ (https://docs.python.org/3/library/sys.html#sys.argv)
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2. Utility for working with arguments: ~argparse~ (https://docs.python.org/3/library/argparse.html)
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** Looping Over Data Sets
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*** File paths as an example of increasing abstraction in program development
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1. File paths as literal strings
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1. Positional arguments
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#+BEGIN_SRC python
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def print_date(year, month, day):
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joined = '/'.join([year, month, day])
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print(joined)
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"""Print the formatted date. This works with strings or integers."""
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formatted_date = f"{year}/{month}/{day}"
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print(formatted_date)
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print_date(1871, 3, 19)
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#+END_SRC
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*** (Optional) A worked example: The Lorenz attractor
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https://matplotlib.org/stable/gallery/mplot3d/lorenz_attractor.html
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** Notebooks vs Python scripts
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*** Differences between .ipynb and .py
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1. Export notebook to .py file
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2. Move .py file into data directory
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3. Compare files in TextEdit/Notepad
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*** Workflow differences between notebooks and scripts
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Broadly, a trade-off between managing big code bases and making it easy to experiment. See: https://github.com/elliewix/Ways-Of-Installing-Python/blob/master/ways-of-installing.md#why-do-you-need-a-specific-tool
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1. Interactive testing and debugging
2284+
2. Graphics integration
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3. Version control
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4. Remote scripts
2287+
2288+
** (Optional) Python from the terminal
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1. Python is an interactive interpreter (REPL)
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#+BEGIN_SRC bash
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python
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#+END_SRC
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2. Python is a command line program
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#+BEGIN_SRC python
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# hello.py
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print("Hello!")
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#+END_SRC
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#+BEGIN_SRC bash
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python hello.py
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#+END_SRC
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3. (Optional) Python programs can accept command line arguments as inputs
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1. List of command line inputs: ~sys.argv~ (https://docs.python.org/3/library/sys.html#sys.argv)
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2. Utility for working with arguments: ~argparse~ (https://docs.python.org/3/library/argparse.html)
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** (Optional) Use pathlib to write code that works across operating systems
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1. Pathlib provides cross-platform path objects
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#+BEGIN_SRC python
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#+BEGIN_SRC bash
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pandoc -f org -t gfm --toc --toc-depth=2 --wrap=none -N -s README.org -o README.md
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# Add section headers
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# Add section headers. These don't appear to work as links on the github.io website
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pandoc -f org -t gfm --toc --toc-depth=2 --wrap=none -s --lua-filter ./pandoc-section-number-filter.lua README.org -o README.md
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#+END_SRC
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