Implement the chart visualization code. Specifically, complete generateAPTVis$(...)$ as described. Given a dataframe, and the "augmented" ordering $($we$\text{'}$ll use selectEncodings to do this$),$ return an Altair chart using the specified encodings. You may implement additional additional "helper" functions if needed. def generateAPTVis$($varbs$,$indf, hasEncodings$=$False$)$:input: indf $--$ the dataframe to encode. The assumption is that variables in varbsinput: hasEncodings $--$ if the varbs data already has the encoding column $($useful for testing$)$we assume each element in varbs already has an 'encoding' keyexceptions: EncodingException if there is an encoding failureif $($not hasEncodings$)$:

varbs $=$ selectEncodings$($varbs$)$toRet $=$ alt.Chart$($indf$)$return toRet order $=[\{"$variable$"$:$"$q$1",$"type":"Q$"\},$

$\{"$variable$"$:$"$q$2",$"type":"Q$"\},$

$\{"$variable$"$:$"$o$1",$"type":"$0"\}]$

display$($selectEncodings$($order$))$

generateAPTVis$($order$,$testingFrame$)$

For example, if the specification says:

$[\{\text{'}$variable$\text{'}$: $\text{'}$q$1\text{'},$ 'type': $\text{'}$Q$\text{'},$ 'encoding': $\text{'}$x$\text{'}\},$

$\{\text{'}$variable$\text{'}$: $\text{'}$q$2\text{'},$ 'type': $\text{'}$Q$\text{'},$ 'encoding': $\text{'}$y$\text{'}\},$

$\{\text{'}$variable$\text{'}$: $\text{'}$o$1\text{'},$ 'type': $\text{'}$O$\text{'},$ 'encoding': 'saturation'$\}]$

we want a visualization that looks something like:

Part $2\mathrm{.}3(30$ points$)$

Implement the chart visualization code. Specifically, complete generateAPTVis $(...)$ as described. Given a dataframe, and the "augmented" ordering

$($we$\text{'}$ll use selectEncodings to do this$),$ return an Altair chart using the specified encodings. You may implement additional additional "helper" functions

if needed.

For example, if the specification says:

$[\{\text{'}variable\text{'}$: $\text{'}q1\text{'},$ 'type': $\text{'}Q\text{'},$ 'encoding': $\text{'}x\text{'}\},$

$\{\text{'}variable\text{'}$: $\text{'}q2\text{'},$ 'type': $\text{'}Q\text{'},$ 'encoding': $\text{'}y\text{'}\},$

$\{\text{'}variable\text{'}$: $\text{'}o1\text{'},$ 'type': $\text{'}0\text{'},$ 'encoding': 'saturation'$\}]$

we want a visualization that looks something like:

Hints

You might want to find a way of creating Altair visualizations using loops $($see how to "extend" charts in Part $1$ above$)$

For colors, we recommend looking at the documentation for alt.Scale.

If you're not using "area" you might find that the points are quite small. We suggest hard coding a larger value so the points are visible.

Points are not filled, you might want to fill them so they are easier to read

def generateAPTVis$($varbs$,$indf,hasEncodings$=$False$)$:

# input: varbs $--$ the variables we want to encode in the format describe above

# input: indf $--$ the dataframe to encode. The assumption is that variables in varbs

# map to columns in indf

# input: hasEncodings $--$ if the varbs data already has the encoding column $($useful for testing$)$

# default is False, in which case we will call selectEncodings, if true

# we assume each element in varbs already has an 'encoding' key

# return: an approriate Altair vis

# exceptions: EncodingException if there is an encoding failure

# find the encodings

if $($not hasEncodings$)$:

varbs $=$ selectEncodings$($varbs$)$

# modify the following code as needed

toRet $=$ alt.Chart$($indf$)$

# YOUR CODE HERE

return toRet

# here's a sample test. You should expand on this to make sure your function works more generally

order $=[\{"$variable$"$:$"$q$1",$"type":"Q$"\},$

$\{"$variable$"$:$"$q$2",$"type":"Q$"\},$

$\{"$variable$"$:$"$o$1",$"type":"O$"\}]$

display$($selectEncodings$($order$))$

generateAPTVis$($order$,$testingFrame$)$