proportions written lesson done

3-Data-Visualization/12-visualization-proportions/README.md

@@ -3,10 +3,8 @@
 In this lesson, you will use a different nature-focused dataset to visualize proportions, such as how many different types of fungi populate a given dataset about mushrooms. Let's explore these fascinating fungi using a dataset sourced from Audubon listing details about 23 species of gilled mushrooms in the Agaricus and Lepiota families. You will experiment with tasty visualizations such as:
 
 - Pie charts 🥧
-- Waffle charts 🧇
 - Donut charts 🍩
-  as well as
-- Stacked bar charts
+- Waffle charts 🧇
 
 ## Pre-Lecture Quiz
 
@@ -66,17 +64,98 @@ Now, if you print out the mushrooms data, you can see that it has been grouped i
 
 If you follow the order presented in this table to create your class category labels, you can build a pie chart:
 
+## Pie!
+
 ```python
 labels=['Edible','Poisonous']
 plt.pie(edibleclass['population'],labels=labels,autopct='%.1f %%')
 plt.title('Edible?')
 plt.show()
 ```
-Voila, a pie chart showing the proportions of this data according to these two classes of mushroom. It's quite important to get the order of labels correct, especially here, so be sure to verify the order the label array is built!
+Voila, a pie chart showing the proportions of this data according to these two classes of mushroom. It's quite important to get the order of labels correct, especially here, so be sure to verify the order with which the label array is built!
 
 ![pie chart](images/pie1.png)
 
+## Donuts!
+
+A somewhat more visually interesting pie chart is a donut chart, which is a pie chart with a hole in the middle. Let's look at our data using this method.
+
+Take a look at the various habitats where mushrooms grow.
+
+```python
+habitat=mushrooms.groupby(['habitat']).count()
+habitat
+```
+Here, you are grouping your data by habitat. There are 7 listed, so use those as labels for your donut chart:
+
+```python
+labels=['Grasses','Leaves','Meadows','Paths','Urban','Waste','Wood']
+
+plt.pie(habitat['class'], labels=labels,
+        autopct='%1.1f%%', pctdistance=0.85)
+  
+center_circle = plt.Circle((0, 0), 0.40, fc='white')
+fig = plt.gcf()
+
+fig.gca().add_artist(center_circle)
+  
+plt.title('Mushroom Habitats')
+  
+plt.show()
+```
+
+![donut chart](images/donut.png)
+
+This code draws a chart and a center circle, then adds that center circle in. Edit the width of the center circle by changing `0.40` to another value.
+
+Donut charts can be tweaked several ways to change the labels. The labels in particular can be highlighted for readability. Learn more in the [docs](https://matplotlib.org/stable/gallery/pie_and_polar_charts/pie_and_donut_labels.html?highlight=donut).
+
+Now that you know how to group your data and then display it as a pie or donut, you can explore other types of charts. Try a waffle chart, which is just a different way of exploring quantity.
+## Waffles!
+
+A 'waffle' type chart is a different way to visualize quantities as a 2D array of squares. Try visualizing the different quantities of mushroom cap colors in this dataset. To do this, you need to install a helper library called [PyWaffle](https://pypi.org/project/pywaffle/) and use Matplotlib:
+
+```python
+pip install pywaffle
+```
+
+Select a segment of your data to group:
+
+```python
+capcolor=mushrooms.groupby(['cap-color']).count()
+capcolor
+```
+
+Create a waffle chart by creating labels and then grouping your data:
+
+```python
+import pandas as pd
+import matplotlib.pyplot as plt
+from pywaffle import Waffle
+  
+data ={'color': ['brown', 'buff', 'cinnamon', 'green', 'pink', 'purple', 'red', 'white', 'yellow'],
+    'amount': capcolor['class']
+     }
+  
+df = pd.DataFrame(data)
+  
+fig = plt.figure(
+    FigureClass = Waffle,
+    rows = 100,
+    values = df.amount,
+    labels = list(df.color),
+    figsize = (30,30),
+    colors=["brown", "tan", "maroon", "green", "pink", "purple", "red", "whitesmoke", "yellow"],
+)
+```
+
+Using a waffle chart, you can plainly see the proportions of cap color of this mushroom dataset. Interestingly, there are many green-capped mushrooms!
+
+![waffle chart](images/waffle.png)
+
+✅ Pywaffle supports icons within the charts that use any icon available in [Font Awesome](https://fontawesome.com/). Do some experiments to create an even more interesting waffle chart using icons instead of squares.
 
+In this lesson you learned three ways to visualize proportions. First, you need to group your data into categories and then decide which is the best way to display the data - pie, donut, or waffle. All are delicious and gratify the user with an instant snapshot of a dataset.
 
 
 ## 🚀 Challenge