Merge branch 'master' into quarto_mod5

Author: joelostblom

_quarto.yml

@@ -79,6 +79,87 @@ website:
           - text: '   12.1. Exercises'
             href: modules/module1/module1-32-practicing_bar_charts.qmd
           - href: modules/module1/module1-34-what_did_we_just_learn.qmd
+      - section: "**M2. Not So Scary Wrangling (Table Manipulation and Chaining)**"
+        contents:
+          - href: modules/module2/module2-00-module_learning_outcomes.qmd
+          - href: modules/module2/module2-01-reading_in_different_file_types.qmd
+          - text: '   1.1. Exercises'
+            href: modules/module2/module2-02-delimiter.qmd
+          - href: modules/module2/module2-06-arguments_for_reading_data.qmd
+          - text: '   2.1. Exercises'
+            href: modules/module2/module2-07-name_that_argument.qmd
+          - href: modules/module2/module2-09-column_renaming_and_dropping.qmd
+          - text: '   3.1. Exercises'
+            href: modules/module2/module2-10-column_editing_questions.qmd
+          - href: modules/module2/module2-13-column_arithmetic_and_creation.qmd
+          - text: '   4.1. Exercises'
+            href: modules/module2/module2-14-column_arithmetic_questions.qmd
+          - href: modules/module2/module2-16-data_filtering.qmd
+          - text: '   5.1. Exercises'
+            href: modules/module2/module2-17-filtering_question.qmd
+          - href: modules/module2/module2-20-conditional_value_replacement.qmd
+          - text: '   6.1. Exercises'
+            href: modules/module2/module2-21-practice_replacing_values.qmd
+          - href: modules/module2/module2-22-chaining_notation.qmd
+          - text: '   7.1. Exercises'
+            href: modules/module2/module2-23-chaining_true_false.qmd
+          - href: modules/module2/module2-25-grouping_and_aggregating.qmd
+          - text: '   8.1. Exercises'
+            href: modules/module2/module2-26-fruit_salad_grouping_and_aggregating.qmd
+          - href: modules/module2/module2-29-plotting_with_altair.qmd
+          - text: '   9.1. Exercises'
+            href: modules/module2/module2-30-plotting_a_groupby_object.qmd
+          - href: modules/module2/module2-31-what_did_we_just_learn.qmd
+      - section: "**M3. Tidy Data and Joining Dataframes**"
+        contents:
+          - href: modules/module3/module3-00-module_learning_outcomes.qmd
+          - href: modules/module3/module3-01-what_is_tidy_data.qmd
+          - text: '   1.1. Exercises'
+            href: modules/module3/module3-02-tidy_data_questions.qmd
+          - href: modules/module3/module3-05-statistical_questions_and_tidy_data.qmd
+          - text: '   2.1. Exercises'
+            href: modules/module3/module3-06-which_is_tidy.qmd
+          - href: modules/module3/module3-08-reshaping_with_pivot.qmd
+          - text: '   3.1. Exercises'
+            href: modules/module3/module3-09-pivoting_questions.qmd
+          - href: modules/module3/module3-11-reshaping_with_pivot_table.qmd
+          - text: '   4.1. Exercises'
+            href: modules/module3/module3-12-pivot_table_questions.qmd
+          - href: modules/module3/module3-14-reshaping_with_melt.qmd
+          - text: '   5.1. Exercises'
+            href: modules/module3/module3-15-melting_questions.qmd
+          - href: modules/module3/module3-17-concatenation.qmd
+          - text: '   6.1. Exercises'
+            href: modules/module3/module3-18-concat_questions.qmd
+          - href: modules/module3/module3-21-joining_dataframes_using_merge.qmd
+          - text: '   7.1. Exercises'
+            href: modules/module3/module3-22-merge_questions.qmd
+          - href: modules/module3/module3-25-what_did_we_just_learn.qmd
+      - section: "**M4. Python Without the \"Eek\" (Basic Python)**"
+        contents:
+          - href: modules/module4/module4-00-module_learning_outcomes.qmd
+          - href: modules/module4/module4-01-python_data_types.qmd
+          - text: '   1.1. Exercises'
+            href: modules/module4/module4-02-name_that_data_type.qmd
+          - href: modules/module4/module4-05-python_data_structures:_lists_tuples_and_sets.qmd
+          - text: '   2.1. Exercises'
+            href: modules/module4/module4-06-name_that_data_structure.qmd
+          - href: modules/module4/module4-10-python_data_structures:_dictionaries.qmd
+          - text: '   3.1. Exercises'
+            href: modules/module4/module4-11-dictionary_questions.qmd
+          - href: modules/module4/module4-14-dataframes_series_and_column_dtypes.qmd
+          - text: '   4.1. Exercises'
+            href: modules/module4/module4-15-name_that_type_dtype.qmd
+          - href: modules/module4/module4-18-python_operations.qmd
+          - text: '   5.1. Exercises'
+            href: modules/module4/module4-19-output_or_error_with_operations.qmd
+          - href: modules/module4/module4-21-operations_with_columns.qmd
+          - text: '   6.1. Exercises'
+            href: modules/module4/module4-22-whats_that_output_with_column_operations.qmd
+          - href: modules/module4/module4-23-splitting_a_column.qmd
+          - text: '   7.1. Exercises'
+            href: modules/module4/module4-24-practice_operations_with_dataframe_columns.qmd
+          - href: modules/module4/module4-25-what_did_we_just_learn.qmd
       - section: "**Module 5: Making Choices and Repeating Iterations**"
         contents:
           - href: modules/module5/module5-00-module_learning_outcomes.qmd
@@ -141,4 +222,4 @@ format:
     history: false
     menu: false
     execute:
-      echo: true
+      echo: true

data/candy_bars2.csv

@@ -0,0 +1,6 @@
+name,calories,fat,sugar
+Coffee Crisp,260,13,25
+Butterfinger,798,30,72
+Skor,209,12,23
+Smarties,210,6,33
+Twix,250,12,25

data/candybars-h.csv

@@ -0,0 +1 @@
+This dataset was created by Hayley Boyce in February 2020.,,,,,,,,,,Note this is not a complete dataset and there are many other candybars that are in existance ,,,,,,,,,,name,weight,chocolate,peanuts,caramel,nougat,cookie_wafer_rice,coconut,white_chocolate,multi,available_canada_americaCoffee Crisp,50,1,0,0,0,1,0,0,0,CanadaButterfinger,184,1,1,1,0,0,0,0,0,AmericaSkor,39,1,0,1,0,0,0,0,0,BothSmarties,45,1,0,0,0,0,0,0,1,CanadaTwix,58,1,0,1,0,1,0,0,1,BothReeses Peanutbutter Cups ,43,1,1,0,0,0,0,0,1,Both3 Musketeers,54,1,0,0,1,0,0,0,0,AmericaKinder Surprise,20,1,0,0,0,0,0,1,0,CanadaM & M,48,1,1,0,0,0,0,0,1,BothGlosettes,50,1,0,0,0,0,0,0,1,CanadaKitKat,45,1,0,0,0,1,0,0,1,BothBabe Ruth,60,1,1,1,1,0,0,0,0,AmericaCaramilk,52,1,0,1,0,0,0,0,0,CanadaAero,42,1,0,0,0,0,0,0,0,CanadaMars,51,1,0,1,1,0,0,0,0,BothPayday,52,0,1,1,0,0,0,0,0,AmericaSnickers,48,1,1,1,1,0,0,0,0,BothCrunchie,26,1,0,0,0,0,0,0,0,CanadaWonderbar ,58,1,1,1,0,0,0,0,0,Canada100 Grand ,43,1,0,1,0,1,0,0,0,AmericaTake 5,43,1,1,1,0,1,0,0,0,AmericaWhatchamacallits,45,1,1,0,0,1,0,0,0,AmericaAlmond Joy,46,1,0,0,0,0,1,0,0,AmericaOh Henry,51,1,1,1,0,0,0,0,0,BothCookies and Cream,43,0,0,0,0,1,0,1,0,Both

data/candybars-text.txt

@@ -0,0 +1,26 @@
+name	weight	chocolate	peanuts	caramel	nougat	cookie_wafer_rice	coconut	white_chocolate	multi	available_canada_america
+Coffee Crisp	50	1	0	0	0	1	0	0	0	Canada
+Butterfinger	184	1	1	1	0	0	0	0	0	America
+Skor	39	1	0	1	0	0	0	0	0	Both
+Smarties	45	1	0	0	0	0	0	0	1	Canada
+Twix	58	1	0	1	0	1	0	0	1	Both
+Reeses Peanutbutter Cups 	43	1	1	0	0	0	0	0	1	Both
+3 Musketeers	54	1	0	0	1	0	0	0	0	America
+Kinder Surprise	20	1	0	0	0	0	0	1	0	Canada
+M & M	48	1	1	0	0	0	0	0	1	Both
+Glosettes	50	1	0	0	0	0	0	0	1	Canada
+KitKat	45	1	0	0	0	1	0	0	1	Both
+Babe Ruth	60	1	1	1	1	0	0	0	0	America
+Caramilk	52	1	0	1	0	0	0	0	0	Canada
+Aero	42	1	0	0	0	0	0	0	0	Canada
+Mars	51	1	0	1	1	0	0	0	0	Both
+Payday	52	0	1	1	0	0	0	0	0	America
+Snickers	48	1	1	1	1	0	0	0	0	Both
+Crunchie	26	1	0	0	0	0	0	0	0	Canada
+Wonderbar 	58	1	1	1	0	0	0	0	0	Canada
+100 Grand 	43	1	0	1	0	1	0	0	0	America
+Take 5	43	1	1	1	0	1	0	0	0	America
+Whatchamacallits	45	1	1	0	0	1	0	0	0	America
+Almond Joy	46	1	0	0	0	0	1	0	0	America
+Oh Henry	51	1	1	1	0	0	0	0	0	Both
+Cookies and Cream	43	0	0	0	0	1	0	1	0	Both

data/cereal2.csv

@@ -0,0 +1,78 @@
+name,mfr_type,type,calories,protein,fat,sodium,fiber,carbo,sugars,potass,vitamins,shelf,weight,cups,rating
+100% Bran,N-Cold,Cold,70,4,1,130,10,5,6,280,25,3,1,0.33,68.402973
+100% Natural Bran,Q-Cold,Cold,120,3,5,15,2,8,8,135,0,3,1,1,33.983679
+All-Bran,K-Cold,Cold,70,4,1,260,9,7,5,320,25,3,1,0.33,59.425505
+All-Bran with Extra Fiber,K-Cold,Cold,50,4,0,140,14,8,0,330,25,3,1,0.5,93.704912
+Almond Delight,R-Cold,Cold,110,2,2,200,1,14,8,1,25,3,1,0.75,34.384843
+Apple Cinnamon Cheerios,G-Cold,Cold,110,2,2,180,1.5,10.5,10,70,25,1,1,0.75,29.509541
+Apple Jacks,K-Cold,Cold,110,2,0,125,1,11,14,30,25,2,1,1,33.174094
+Basic 4,G-Cold,Cold,130,3,2,210,2,18,8,100,25,3,1.33,0.75,37.038562
+Bran Chex,R-Cold,Cold,90,2,1,200,4,15,6,125,25,1,1,0.67,49.120253
+Bran Flakes,P-Cold,Cold,90,3,0,210,5,13,5,190,25,3,1,0.67,53.313813
+Cap'n'Crunch,Q-Cold,Cold,120,1,2,220,0,12,12,35,25,2,1,0.75,18.042851
+Cheerios,G-Cold,Cold,110,6,2,290,2,17,1,105,25,1,1,1.25,50.764999
+Cinnamon Toast Crunch,G-Cold,Cold,120,1,3,210,0,13,9,45,25,2,1,0.75,19.823573
+Clusters,G-Cold,Cold,110,3,2,140,2,13,7,105,25,3,1,0.5,40.400208
+Cocoa Puffs,G-Cold,Cold,110,1,1,180,0,12,13,55,25,2,1,1,22.736446
+Corn Chex,R-Cold,Cold,110,2,0,280,0,22,3,25,25,1,1,1,41.445019
+Corn Flakes,K-Cold,Cold,100,2,0,290,1,21,2,35,25,1,1,1,45.863324
+Corn Pops,K-Cold,Cold,110,1,0,90,1,13,12,20,25,2,1,1,35.782791
+Count Chocula,G-Cold,Cold,110,1,1,180,0,12,13,65,25,2,1,1,22.396513
+Cracklin' Oat Bran,K-Cold,Cold,110,3,3,140,4,10,7,160,25,3,1,0.5,40.448772
+Cream of Wheat (Quick),N-Hot,Hot,100,3,0,80,1,21,0,1,0,2,1,1,64.533816
+Crispix,K-Cold,Cold,110,2,0,220,1,21,3,30,25,3,1,1,46.895644
+Crispy Wheat & Raisins,G-Cold,Cold,100,2,1,140,2,11,10,120,25,3,1,0.75,36.176196
+Double Chex,R-Cold,Cold,100,2,0,190,1,18,5,80,25,3,1,0.75,44.330856
+Froot Loops,K-Cold,Cold,110,2,1,125,1,11,13,30,25,2,1,1,32.207582
+Frosted Flakes,K-Cold,Cold,110,1,0,200,1,14,11,25,25,1,1,0.75,31.435973
+Frosted Mini-Wheats,K-Cold,Cold,100,3,0,0,3,14,7,100,25,2,1,0.8,58.345141
+Fruit & Fibre Dates; Walnuts; and Oats,P-Cold,Cold,120,3,2,160,5,12,10,200,25,3,1.25,0.67,40.917047
+Fruitful Bran,K-Cold,Cold,120,3,0,240,5,14,12,190,25,3,1.33,0.67,41.015492
+Fruity Pebbles,P-Cold,Cold,110,1,1,135,0,13,12,25,25,2,1,0.75,28.025765
+Golden Crisp,P-Cold,Cold,100,2,0,45,0,11,15,40,25,1,1,0.88,35.252444
+Golden Grahams,G-Cold,Cold,110,1,1,280,0,15,9,45,25,2,1,0.75,23.804043
+Grape Nuts Flakes,P-Cold,Cold,100,3,1,140,3,15,5,85,25,3,1,0.88,52.076897
+Grape-Nuts,P-Cold,Cold,110,3,0,170,3,17,3,90,25,3,1,0.25,53.371007
+Great Grains Pecan,P-Cold,Cold,120,3,3,75,3,13,4,100,25,3,1,0.33,45.811716
+Honey Graham Ohs,Q-Cold,Cold,120,1,2,220,1,12,11,45,25,2,1,1,21.871292
+Honey Nut Cheerios,G-Cold,Cold,110,3,1,250,1.5,11.5,10,90,25,1,1,0.75,31.072217
+Honey-comb,P-Cold,Cold,110,1,0,180,0,14,11,35,25,1,1,1.33,28.742414
+Just Right Crunchy  Nuggets,K-Cold,Cold,110,2,1,170,1,17,6,60,100,3,1,1,36.523683
+Just Right Fruit & Nut,K-Cold,Cold,140,3,1,170,2,20,9,95,100,3,1.3,0.75,36.471512
+Kix,G-Cold,Cold,110,2,1,260,0,21,3,40,25,2,1,1.5,39.241114
+Life,Q-Cold,Cold,100,4,2,150,2,12,6,95,25,2,1,0.67,45.328074
+Lucky Charms,G-Cold,Cold,110,2,1,180,0,12,12,55,25,2,1,1,26.734515
+Maypo,A-Hot,Hot,100,4,1,0,0,16,3,95,25,2,1,1,54.850917
+Muesli Raisins; Dates; & Almonds,R-Cold,Cold,150,4,3,95,3,16,11,170,25,3,1,1,37.136863
+Muesli Raisins; Peaches; & Pecans,R-Cold,Cold,150,4,3,150,3,16,11,170,25,3,1,1,34.139765
+Mueslix Crispy Blend,K-Cold,Cold,160,3,2,150,3,17,13,160,25,3,1.5,0.67,30.313351
+Multi-Grain Cheerios,G-Cold,Cold,100,2,1,220,2,15,6,90,25,1,1,1,40.105965
+Nut&Honey Crunch,K-Cold,Cold,120,2,1,190,0,15,9,40,25,2,1,0.67,29.924285
+Nutri-Grain Almond-Raisin,K-Cold,Cold,140,3,2,220,3,21,7,130,25,3,1.33,0.67,40.69232
+Nutri-grain Wheat,K-Cold,Cold,90,3,0,170,3,18,2,90,25,3,1,1,59.642837
+Oatmeal Raisin Crisp,G-Cold,Cold,130,3,2,170,1.5,13.5,10,120,25,3,1.25,0.5,30.450843
+Post Nat. Raisin Bran,P-Cold,Cold,120,3,1,200,6,11,14,260,25,3,1.33,0.67,37.840594
+Product 19,K-Cold,Cold,100,3,0,320,1,20,3,45,100,3,1,1,41.50354
+Puffed Rice,Q-Cold,Cold,50,1,0,0,0,13,0,15,0,3,0.5,1,60.756112
+Puffed Wheat,Q-Cold,Cold,50,2,0,0,1,10,0,50,0,3,0.5,1,63.005645
+Quaker Oat Squares,Q-Cold,Cold,100,4,1,135,2,14,6,110,25,3,1,0.5,49.511874
+Quaker Oatmeal,Q-Hot,Hot,100,5,2,0,2.7,1,1,110,0,1,1,0.67,50.828392
+Raisin Bran,K-Cold,Cold,120,3,1,210,5,14,12,240,25,2,1.33,0.75,39.259197
+Raisin Nut Bran,G-Cold,Cold,100,3,2,140,2.5,10.5,8,140,25,3,1,0.5,39.7034
+Raisin Squares,K-Cold,Cold,90,2,0,0,2,15,6,110,25,3,1,0.5,55.333142
+Rice Chex,R-Cold,Cold,110,1,0,240,0,23,2,30,25,1,1,1.13,41.998933
+Rice Krispies,K-Cold,Cold,110,2,0,290,0,22,3,35,25,1,1,1,40.560159
+Shredded Wheat,N-Cold,Cold,80,2,0,0,3,16,0,95,0,1,0.83,1,68.235885
+Shredded Wheat 'n'Bran,N-Cold,Cold,90,3,0,0,4,19,0,140,0,1,1,0.67,74.472949
+Shredded Wheat spoon size,N-Cold,Cold,90,3,0,0,3,20,0,120,0,1,1,0.67,72.801787
+Smacks,K-Cold,Cold,110,2,1,70,1,9,15,40,25,2,1,0.75,31.230054
+Special K,K-Cold,Cold,110,6,0,230,1,16,3,55,25,1,1,1,53.131324
+Strawberry Fruit Wheats,N-Cold,Cold,90,2,0,15,3,15,5,90,25,2,1,1,59.363993
+Total Corn Flakes,G-Cold,Cold,110,2,1,200,0,21,3,35,100,3,1,1,38.839746
+Total Raisin Bran,G-Cold,Cold,140,3,1,190,4,15,14,230,100,3,1.5,1,28.592785
+Total Whole Grain,G-Cold,Cold,100,3,1,200,3,16,3,110,100,3,1,1,46.658844
+Triples,G-Cold,Cold,110,2,1,250,0,21,3,60,25,3,1,0.75,39.106174
+Trix,G-Cold,Cold,110,1,1,140,0,13,12,25,25,2,1,1,27.753301
+Wheat Chex,R-Cold,Cold,100,3,1,230,3,17,3,115,25,1,1,0.67,49.787445
+Wheaties,G-Cold,Cold,100,3,1,200,3,17,3,110,25,1,1,1,51.592193
+Wheaties Honey Gold,G-Cold,Cold,110,2,1,200,1,16,8,60,25,1,1,0.75,36.187559

data/foods.xlsx

@@ -0,0 +1,6 @@
+name,calories,fat,sugar
+Butterfinger,798,30,72
+Skor,209,12,23
+Twix,250,12,25
+Coffee Crisp,260,13,25
+Smarties,210,6,33

data/snacksize_candybars.csv

@@ -9,7 +9,6 @@ dependencies:
     - scipy
     - matplotlib
     - jupyter
-    - quarto
+    - quarto=1.6.43
     - pip
-
-
+    - openpyxl

environment.yaml

@@ -77,27 +77,19 @@ Now we can use `.value_counts()` on this `mfr_column` variable to reference it,
 ---
 
 ```{python}
-mfr_col_wrong = cereal[['mfr']]
-mfr_col_wrong
+mfr_col_dataframe = cereal[['mfr']]
+mfr_col_dataframe
 ```
 
 <br>
 
-```python
-mfr_col_wrong.value_counts()
+```{python}
+mfr_col_dataframe.value_counts()
 ```
 
-```out
-AttributeError: 'DataFrame' object has no attribute 'value_counts'
-
-Detailed traceback: 
-  File "<string>", line 1, in <module>
-  File "/usr/local/lib/python3.7/site-packages/pandas/core/generic.py", line 5274, in __getattr__
-    return object.__getattribute__(self, name)
-```
 
 :::{.notes} 
-If we did instead use double square brackets with `pd.value_counts()`, we would get an error. So it is important to take care and remember when you are using `value_counts()`, you only use one set of square brackets.
+`value_counts()` can also be called on a DataFrame to count unique rows.
 :::
 
 ---

modules/module1/slides/module1_29.qmd

@@ -0,0 +1,29 @@
+---
+format:
+  html:
+    page-layout: full
+---
+
+# 0. Module Learning Outcomes
+
+::: {.panel-tabset .nav-pills}
+
+## Video
+
+<iframe
+    class="video"
+    src="https://www.youtube.com/embed/rn5t62Utn4U?start=0&end=29&rel=0" 
+    title="Module 2 Video - Module Learning Outcomes"
+    frameborder="0"
+    allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
+    allowfullscreen
+></iframe>
+
+## Slides
+
+<iframe
+    class="slide-deck"
+    src="slides/module2_00.html"
+></iframe>
+
+:::