Gain insights into using Python for mechanical and aerospace engineering. Learn about basics, graphing techniques, airfoil plotting, and dynamic pressure and orbital modeling in 2D and 3D.

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In this course, you will learn about the Python programming language in the context of mechanical and aerospace engineering. 

You will start with the basics of Python, like variables, collections, and different types of loops. Once you have the basics out of the way, the real fun begins. You will learn how to: graph thrust available and thrust required, graph dynamic pressure during a rocket launch, and how to plot airfoil coordinates. 

Towards the end, you will get a strong overview of orbital parameters and learn how to model both 2D and 3D static orbits. Once you’ve completed this course, you will have a better understanding of Python and how it works in the context of mechanical/aerospace engineering.

Python for Mechanical and Aerospace Engineering

# Marking Max Q
You also want to mark on the graph what the maximum pressure is and where it occurs; by marking this point, you can say at what time Max Q occurs and what value the maximum dynamic pressure reaches. You will use the built-in `max()` function to determine the greatest number in `y_values`, and you will use the `index()` function to determine where that value is in the `x_values`. Then, you can use that index to find out what elapsed time the highest value corresponds to. It is important to note that the index is the **_location_** in the `list` of where the Max Q is in `y_values` and the time at which it occurs in `x_values`; it is not the time at which Max Q occurs, nor is it the value of Max Q. 

```python
max_val = max(y_values)
ind = y_values.index(max_val)
```

So, `x_values[ind]` is the time at which Max Q occurs, and `y_values[ind]` is the value of Max Q. You will use `plt.annotate()` function to add an arrow pointing to the max value and to add a label with the value and time at which Max Q occurs. In Python:

```python
plt.annotate('{:,2E} psf @ {} s'.format(max_val, x_values[ind]),
             xy=(x_values[ind] + 2, max_val),
             xytext=(x_values[ind] + 15, max_val + 1E5),
             arrowprops=dict(facecolor='blue', shrink=0.05))
```

Since the value will be in billions, let’s round the value to 2 decimal points and use scientific notation, which is what `{:,2E}` is doing. The `plt.annotate()` argument accepts the label text (which is populated with Max Q and the time at which it occurs), x and y values to start the arrow, x and y values to start the label text, and a dictionary for `arrowprops` to customize the arrow color and direction. The final step is some housekeeping to label the axes, create a chart title, create the legend, and show the plot that you have been creating. 

```python
plt.xlabel('Time (s)')
plt.ylabel('Pressure (psf)')
plt.title('Dynamic pressure as a function of time')
plt.legend()
plt.show()
```

# Seeing your work

Hit run, and let’s see your creation!

Develop the code for the dynamic pressure experienced by a rocket during launch.

Getting Comfortable with Python

FizzBuzz

Graphing Thrust Available and Thrust Required

Graphing Dynamic Pressure During a Rocket Launch

Getting and Plotting Airfoil Coordinates

Modeling a 2-Body Orbit in 2D and 3D

Unit Conversions

Introduction to Web Scraping

Modeling Camera Shutter Effect

Writing Reports with Pweave

The End

Dynamic Pressure for an Average Rocket

Marking Max Q