diff --git a/episodes/conditionals.md b/episodes/conditionals.md
index 1616e805..ee656f23 100644
--- a/episodes/conditionals.md
+++ b/episodes/conditionals.md
@@ -76,6 +76,52 @@ for checkout in checkouts:
Notice that our `else` statement led to a false output that says 10 is under the limit. We can address this by adding a different kind of `else` statement.
+::::::::::::::::::::::::::::::::::::::: challenge
+
+## Age conditionals
+
+Write a Python program that checks the age of a user to determine if they will receive a youth or adult library card. The program should:
+
+1. Store `age` in a variable.
+2. Use an `if` statement to check if the age is 16 or older. If true, print "You are eligible for an adult library card."
+3. Use an `else` statement to print "You are eligible for a youth library card" if the age is less than 16.
+
+If you finish early, try this challenge:
+
+- In a new cell, adapt your program to loop through a list of age values, testing each age with the same output as above.
+
+::::::::::::::: solution
+
+## Solution
+
+For parts 1 to 3:
+
+```python
+age = 25
+
+if age >= 16:
+ print('You are eligible for an adult library card.')
+else:
+ print('You are eligible for a youth library card.')
+```
+
+For the challenge:
+```python
+ages = [10, 16, 30, 65]
+
+for age in ages:
+ if age >= 16:
+ print('You are eligible for an adult library card.')
+ else:
+ print('You are eligible for a youth library card.')
+```
+
+
+:::::::::::::::::::::::::
+
+::::::::::::::::::::::::::::::::::::::::::::::::::
+
+
## Use `elif` to specify additional tests.
You can use `elif` (short for "else if") to provide several alternative choices, each with its own test. An `elif` statement should always be associated with an `if` statement, and must come before the `else` statement (which is the catch all).
@@ -153,52 +199,6 @@ for user in users:
*Warning*: 120 is over the grad limit.
```
-::::::::::::::::::::::::::::::::::::::: challenge
-
-## Age conditionals
-
-Write a Python program that checks the age of a user to determine if they will receive a youth or adult library card. The program should:
-
-1. Store `age` in a variable.
-2. Use an `if` statement to check if the age is 16 or older. If true, print "You are eligible for an adult library card."
-3. Use an `else` statement to print "You are eligible for a youth library card" if the age is less than 16.
-
-If you finish early, try this challenge:
-
-- In a new cell, adapt your program to loop through a list of age values, testing each age with the same output as above.
-
-::::::::::::::: solution
-
-## Solution
-
-For parts 1 to 3:
-
-```python
-age = 25
-
-if age >= 16:
- print('You are eligible for an adult library card.')
-else:
- print('You are eligible for a youth library card.')
-```
-
-For the challenge:
-```python
-ages = [10, 16, 30, 65]
-
-for age in ages:
- if age >= 16:
- print('You are eligible for an adult library card.')
- else:
- print('You are eligible for a youth library card.')
-```
-
-
-:::::::::::::::::::::::::
-
-::::::::::::::::::::::::::::::::::::::::::::::::::
-
-
::::::::::::::::::::::::::::::::::::::: challenge
## Conditional logic: Fill in the blanks
diff --git a/episodes/data-visualisation.md b/episodes/data-visualisation.md
index 0b834a02..f2a9accf 100644
--- a/episodes/data-visualisation.md
+++ b/episodes/data-visualisation.md
@@ -138,55 +138,6 @@ albany['circulation'].plot(kind='hist', bins=20,
{alt="histogram of the Albany branch circulation."}
-## Use Plotly for interactive plots
-
-Let’s switch back to the full DataFrame in `df_long` and use another
-plotting package in Python called Plotly.
-
-```python
-import plotly.express as px
-```
-
-Now we can visualize how circulation counts have changed over time for selected branches. This can be especially useful for identifying trends, seasonality, or data anomalies. We willfirst create a subset of our data to look at branches starting with the letter 'A'. Feel free to select different branches. After subsetting, we will sort our new DataFrame by date and then plot our data by date and circulation count.
-
-``` python
-# Creating a line plot for a few selected branches to avoid clutter
-selected_branches = df_long[df_long['branch'].isin(['Altgeld',
- 'Archer Heights',
- 'Austin',
- 'Austin-Irving',
- 'Avalon'])]
-selected_branches = selected_branches.sort_values(by='date')
-```
-
-``` python
-fig = px.line(selected_branches, x=selected_branches.index, y='circulation', color='branch', title='Circulation Over Time for Selected Branches')
-fig.show()
-```
-
-Here is a view of the [interactive output of the Plotly line chart](learners/line_plot_int.html).
-
-
-One advantage that Plotly provides over Matplotlib is that it has some interactive features out of the box. Hover your cursor over the lines in the output to find out more granular data about specific branches over time.
-
-
-### Bar plots with Plotly
-
-Let’s use a barplot to compare the distribution of circulation counts
-among branches. We first need to group our data by branch and sum up the circulation counts. Then we can use the bar plot to show the
-distribution of total circulation over branches.
-
-``` python
-# Aggregate circulation by branch
-total_circulation_by_branch = df_long.groupby('branch')['circulation'].sum().reset_index()
-
-# Create a bar plot
-fig = px.bar(total_circulation_by_branch, x='branch', y='circulation', title='Total Circulation by Branch')
-fig.show()
-```
-
-Here is a view of the [interactive output of the Plotly bar chart](learners/bar_plot_int.html).
-
::::::::::::::::::::::::::::::::::::::: challenge
## Plotting with Pandas
@@ -248,6 +199,56 @@ uptown['circulation'].plot(title='Uptown Circulation',
::::::::::::::::::::::::::::::::::::::::::::::::::
+
+## Use Plotly for interactive plots
+
+Let’s switch back to the full DataFrame in `df_long` and use another
+plotting package in Python called Plotly.
+
+```python
+import plotly.express as px
+```
+
+Now we can visualize how circulation counts have changed over time for selected branches. This can be especially useful for identifying trends, seasonality, or data anomalies. We willfirst create a subset of our data to look at branches starting with the letter 'A'. Feel free to select different branches. After subsetting, we will sort our new DataFrame by date and then plot our data by date and circulation count.
+
+``` python
+# Creating a line plot for a few selected branches to avoid clutter
+selected_branches = df_long[df_long['branch'].isin(['Altgeld',
+ 'Archer Heights',
+ 'Austin',
+ 'Austin-Irving',
+ 'Avalon'])]
+selected_branches = selected_branches.sort_values(by='date')
+```
+
+``` python
+fig = px.line(selected_branches, x=selected_branches.index, y='circulation', color='branch', title='Circulation Over Time for Selected Branches')
+fig.show()
+```
+
+Here is a view of the [interactive output of the Plotly line chart](learners/line_plot_int.html).
+
+
+One advantage that Plotly provides over Matplotlib is that it has some interactive features out of the box. Hover your cursor over the lines in the output to find out more granular data about specific branches over time.
+
+
+### Bar plots with Plotly
+
+Let’s use a barplot to compare the distribution of circulation counts
+among branches. We first need to group our data by branch and sum up the circulation counts. Then we can use the bar plot to show the
+distribution of total circulation over branches.
+
+``` python
+# Aggregate circulation by branch
+total_circulation_by_branch = df_long.groupby('branch')['circulation'].sum().reset_index()
+
+# Create a bar plot
+fig = px.bar(total_circulation_by_branch, x='branch', y='circulation', title='Total Circulation by Branch')
+fig.show()
+```
+
+Here is a view of the [interactive output of the Plotly bar chart](learners/bar_plot_int.html).
+
::::::::::::::::::::::::::::::::::::::: challenge
## Plot the top five branches
diff --git a/episodes/for-loops.md b/episodes/for-loops.md
index 5313fbb8..c9fd5279 100644
--- a/episodes/for-loops.md
+++ b/episodes/for-loops.md
@@ -163,6 +163,38 @@ for number in range(0,3):
2
```
+::::::::::::::::::::::::::::::::::::::: challenge
+
+## Use range() in a loop
+
+Print out the numbers 10, 11, 12, 13, 14, 15, using range() in a `for` loop.
+
+::::::::::::::: solution
+
+## Solution
+
+```python
+
+for num in range(10, 16):
+ print(num)
+
+```
+
+```output
+10
+11
+12
+13
+14
+15
+```
+
+
+:::::::::::::::::::::::::
+
+::::::::::::::::::::::::::::::::::::::::::::::::::
+
+
## Accumulators
A common loop pattern is to initialize an *accumulator* variable to zero, an empty string, or an empty list before the loop begins. Then the loop updates the accumulator variable with values from a collection.
@@ -249,37 +281,6 @@ for veg in vegetables:
::::::::::::::::::::::::::::::::::::::::::::::::::
::::::::::::::::::::::::::::::::::::::: challenge
-## Use range() in a loop
-
-Print out the numbers 10, 11, 12, 13, 14, 15, using range() in a `for` loop.
-
-::::::::::::::: solution
-
-## Solution
-
-```python
-
-for num in range(10, 16):
- print(num)
-
-```
-
-```output
-10
-11
-12
-13
-14
-15
-```
-
-
-:::::::::::::::::::::::::
-
-::::::::::::::::::::::::::::::::::::::::::::::::::
-
-::::::::::::::::::::::::::::::::::::::: challenge
-
## Use a string index in a loop
How would you loop through a list with the values 'red', 'green', and 'blue' to create the acronym `rgb`, pulling from the first letters in each string? Print the acronym when the loop is finished.
diff --git a/episodes/getting-started.md b/episodes/getting-started.md
index bfff0174..2aa17a0b 100644
--- a/episodes/getting-started.md
+++ b/episodes/getting-started.md
@@ -18,7 +18,7 @@ exercises: 5
- How can I identify and use key features of JupyterLab to create and manage a Python notebook?
- How do I run Python code in JupyterLab, and how can I see and interpret the results?
--
+
::::::::::::::::::::::::::::::::::::::::::::::::::
## Why Python?
@@ -151,7 +151,7 @@ If you move your cursor back to the first cell, just after the `7 * 3` code, and
```python
7 * 3
-2 +1
+2 + 1
```
While Python runs both calculations Juypter will only display the output from the last line of code in a specific cell, unless you tell it to do otherwise.
diff --git a/episodes/libraries.md b/episodes/libraries.md
index da7bceab..05da8950 100644
--- a/episodes/libraries.md
+++ b/episodes/libraries.md
@@ -155,6 +155,51 @@ Many popular libraries have common aliases. For example:
Using these common aliases can make it easier to work with existing documentation and tutorials.
+::::::::::::::::::::::::::::::::::::::: challenge
+
+## Importing With Aliases
+
+1. Fill in the blanks so that the program below prints `0123456789`.
+2. Rewrite the program so that it uses `import` *without* `as`.
+3. Which form do you find easier to read?
+
+```python
+import string as s
+numbers = ____.digits
+print(____)
+```
+
+::::::::::::::: solution
+
+## Solution
+
+```python
+import string as s
+numbers = s.digits
+print(numbers)
+```
+
+can be written as
+
+```python
+import string
+numbers = string.digits
+print(numbers)
+```
+
+Since you just wrote the code and are familiar with it, you might actually
+find the first version easier to read. But when trying to read a huge piece
+of code written by someone else, or when getting back to your own huge piece
+of code after several months, non-abbreviated names are often easier, expect
+where there are clear abbreviation conventions.
+
+
+
+:::::::::::::::::::::::::
+
+::::::::::::::::::::::::::::::::::::::::::::::::::
+
+
## Pandas
`Pandas` is a widely-used Python library for statistics using tabular data.
Essentially, it gives you access to 2-dimensional tables whose columns have names and can have different data types. We can start using pandas by reading a `Comma Separated Values` (CSV) data file with the function `pd.read_csv()`. The function `.read_csv()` expects as an argument the path to and name of the file to be read. This returns a dataframe that you can assign to a variable.
@@ -321,50 +366,6 @@ This gives us, for example, the count, minimum, maximum, and mean values from ea
::::::::::::::::::::::::::::::::::::::: challenge
-## Importing With Aliases
-
-1. Fill in the blanks so that the program below prints `0123456789`.
-2. Rewrite the program so that it uses `import` *without* `as`.
-3. Which form do you find easier to read?
-
-```python
-import string as s
-numbers = ____.digits
-print(____)
-```
-
-::::::::::::::: solution
-
-## Solution
-
-```python
-import string as s
-numbers = s.digits
-print(numbers)
-```
-
-can be written as
-
-```python
-import string
-numbers = string.digits
-print(numbers)
-```
-
-Since you just wrote the code and are familiar with it, you might actually
-find the first version easier to read. But when trying to read a huge piece
-of code written by someone else, or when getting back to your own huge piece
-of code after several months, non-abbreviated names are often easier, expect
-where there are clear abbreviation conventions.
-
-
-
-:::::::::::::::::::::::::
-
-::::::::::::::::::::::::::::::::::::::::::::::::::
-
-::::::::::::::::::::::::::::::::::::::: challenge
-
## Locating the Right Module
Given the variables `year`, `month` and `day`, how would you generate a date in the standard iso format:
diff --git a/episodes/lists.md b/episodes/lists.md
index 1c3a5faf..425fed38 100644
--- a/episodes/lists.md
+++ b/episodes/lists.md
@@ -58,6 +58,61 @@ First item: marc
The first three items: ['marc', 'frbr', 'mets']
```
+::::::::::::::::::::::::::::::::::::::: challenge
+
+## Lists: Length and Indexing
+1. Create a list named `colors` containing the strings 'red', 'blue', and 'green'.
+2. Print the length of the list.
+3. Print the first color using indexing.
+
+::::::::::::::: solution
+
+## Solution
+```python
+colors = ['red', 'blue', 'green']
+print(len(colors))
+print(colors[0])
+```
+
+:::::::::::::::::::::::::
+
+::::::::::::::::::::::::::::::::::::::::::::::::::
+
+:::::::::::::::::::::::::::::::::::::: challenge
+
+## List slicing
+1. Create a list of numbers defined as [1, 2, 3, 4, 5, 6].
+2. Print the first three items in the list using slicing.
+3. Print the last three items using slicing.
+
+::::::::::::::: solution
+
+## Solution
+```python
+numbers = [1, 2, 3, 4, 5, 6]
+print(numbers[0:3])
+print(numbers[3:6])
+```
+```output
+[1, 2, 3]
+[4, 5, 6]
+```
+
+You can also leave the first and last elements in a slice blank to refer to the first and last elements in a list:
+
+```python
+print(numbers[:3])
+print(numbers[3:])
+```
+```output
+[1, 2, 3]
+[4, 5, 6]
+```
+
+:::::::::::::::::::::::::
+
+::::::::::::::::::::::::::::::::::::::::::::::::::
+
## Reassign list values with their index.
Use an index value along with your list variable to replace a value from the list.
@@ -172,60 +227,6 @@ animals before: ['dog', 'bird', 'shark', 'dog']
animals after: ['bird', 'shark', 'dog']
```
-::::::::::::::::::::::::::::::::::::::: challenge
-
-## Lists: Length and Indexing
-1. Create a list named `colors` containing the strings 'red', 'blue', and 'green'.
-2. Print the length of the list.
-3. Print the first color using indexing.
-
-::::::::::::::: solution
-
-## Solution
-```python
-colors = ['red', 'blue', 'green']
-print(len(colors))
-print(colors[0])
-```
-
-:::::::::::::::::::::::::
-
-::::::::::::::::::::::::::::::::::::::::::::::::::
-
-:::::::::::::::::::::::::::::::::::::: challenge
-
-## List slicing
-1. Create a list of numbers defined as [1, 2, 3, 4, 5, 6].
-2. Print the first three items in the list using slicing.
-3. Print the last three items using slicing.
-
-::::::::::::::: solution
-
-## Solution
-```python
-numbers = [1, 2, 3, 4, 5, 6]
-print(numbers[0:3])
-print(numbers[3:6])
-```
-```output
-[1, 2, 3]
-[4, 5, 6]
-```
-
-You can also leave the first and last elements in a slice blank to refer to the first and last elements in a list:
-
-```python
-print(numbers[:3])
-print(numbers[3:])
-```
-```output
-[1, 2, 3]
-[4, 5, 6]
-```
-
-:::::::::::::::::::::::::
-
-::::::::::::::::::::::::::::::::::::::::::::::::::
::::::::::::::::::::::::::::::::::::::: challenge
diff --git a/episodes/looping-data-sets.md b/episodes/looping-data-sets.md
index 8b9665fc..5e9170b7 100644
--- a/episodes/looping-data-sets.md
+++ b/episodes/looping-data-sets.md
@@ -54,6 +54,27 @@ print(f"all csv files in data directory: {glob.glob('data/*.csv')}")
all csv files in data directory: ['data/2011_circ.csv', 'data/2016_circ.csv', 'data/2017_circ.csv', 'data/2022_circ.csv', 'data/2018_circ.csv', 'data/2019_circ.csv', 'data/2012_circ.csv', 'data/2013_circ.csv', 'data/2021_circ.csv', 'data/2020_circ.csv', 'data/2015_circ.csv', 'data/2014_circ.csv']
```
+::::::::::::::::::::::::::::::::::::::: challenge
+
+## Determining Matches
+
+Which of these files would be matched by the expression `glob.glob('data/*circ.csv')`?
+
+1. `data/2011_circ.csv`
+2. `data/2012_circ_stats.csv`
+3. `circ/2013_circ.csv`
+4. Both 1 and 3
+
+::::::::::::::: solution
+
+## Solution
+
+Only item 1 is matched by the wildcard expression `data/*circ.csv`.
+
+:::::::::::::::::::::::::
+
+::::::::::::::::::::::::::::::::::::::::::::::::::
+
## Use `glob` and `for` to process batches of files.
Now we can use glob in a `for` loop to create DataFrames from all of the CSV files in the `data` directory. To use tools like `glob` it helps if files are named and stored consistently so that simple patterns will find the right data. You can learn more about how to name files to improve machine-readability from the [Open Science Foundation article on file naming](https://help.osf.io/article/146-file-naming).
@@ -102,6 +123,37 @@ data/2021_circ.csv 271811
data/2022_circ.csv 301340
```
+::::::::::::::::::::::::::::::::::::::: challenge
+
+## Minimum circulation per year
+
+Modify the following code to print out the lowest value in the `ytd` column from each year/file.
+
+```python
+import pandas as pd
+for csv in sorted(glob.glob('data/*.csv')):
+ data = pd.read_csv(____)
+ print(csv, data['____'].____())
+
+```
+
+::::::::::::::: solution
+
+## Solution
+
+```python
+import pandas as pd
+for csv in sorted(glob.glob('data/*.csv')):
+ data = pd.read_csv(csv)
+ print(csv, data['ytd'].min())
+
+```
+
+:::::::::::::::::::::::::
+
+::::::::::::::::::::::::::::::::::::::::::::::::::
+
+
## Appending DataFrames to a list
@@ -192,56 +244,6 @@ f'Number of rows in df: {len(df)}'
'Number of rows in df: 963'
```
-::::::::::::::::::::::::::::::::::::::: challenge
-
-## Determining Matches
-
-Which of these files would be matched by the expression `glob.glob('data/*circ.csv')`?
-
-1. `data/2011_circ.csv`
-2. `data/2012_circ_stats.csv`
-3. `circ/2013_circ.csv`
-4. Both 1 and 3
-
-::::::::::::::: solution
-
-## Solution
-
-Only item 1 is matched by the wildcard expression `data/*circ.csv`.
-
-:::::::::::::::::::::::::
-
-::::::::::::::::::::::::::::::::::::::::::::::::::
-
-::::::::::::::::::::::::::::::::::::::: challenge
-
-## Minimum circulation per year
-
-Modify the following code to print out the lowest value in the `ytd` column from each year/file.
-
-```python
-import pandas as pd
-for csv in sorted(glob.glob('data/*.csv')):
- data = pd.read_csv(____)
- print(csv, data['____'].____())
-
-```
-
-::::::::::::::: solution
-
-## Solution
-
-```python
-import pandas as pd
-for csv in sorted(glob.glob('data/*.csv')):
- data = pd.read_csv(csv)
- print(csv, data['ytd'].min())
-
-```
-
-:::::::::::::::::::::::::
-
-::::::::::::::::::::::::::::::::::::::::::::::::::
::::::::::::::::::::::::::::::::::::::: challenge
diff --git a/episodes/pandas.md b/episodes/pandas.md
index e73f7829..2035aa3b 100644
--- a/episodes/pandas.md
+++ b/episodes/pandas.md
@@ -129,6 +129,38 @@ type(df['year'])
pandas.core.series.Series
```
+::::::::::::::::::::::::::::::::::::::: challenge
+
+## Displaying rows and columns
+
+How would you use slicing and column names to select the following subsets of rows and columns from the circulation DataFrame?
+
+1. The city column.
+2. Rows 10 to 20.
+3. Rows 20 to 30 from the zip code column.
+
+::::::::::::::: solution
+
+## Solution
+
+```python
+#1
+df['city']
+
+#2
+df[10:21]
+
+#3
+df['zip code'][20:31]
+
+```
+
+
+:::::::::::::::::::::::::
+
+::::::::::::::::::::::::::::::::::::::::::::::::::
+
+
## Summary statistics on columns
A pandas Series is a one-dimensional array, like a column in a spreadsheet, while a pandas DataFrame is a two-dimensional tabular data structure with labeled axes, similar to a spreadsheet. One of the advantages of pandas is that we can use built-in functions like `max()`, `min()`, `mean()`, and `sum()` to provide summary statistics across Series such as columns. Since it can be difficult to get a sense of the range of data in a large DataFrame by looking over the whole thing manually, these functions can help us understand our dataset quickly and ask specific questions.
@@ -256,6 +288,59 @@ year branch
Name: ytd, dtype: int64
```
+::::::::::::::::::::::::::::::::::::::: challenge
+
+## Unique items
+
+How would you display:
+
+1. all of the unique zip codes in the dataset?
+2. the number of unique zip codes in the dataset?
+
+
+::::::::::::::: solution
+
+## Solution
+
+```python
+
+#1
+df['zip code'].unique()
+
+#2
+df['zip code'].nunique()
+
+```
+:::::::::::::::::::::::::
+::::::::::::::::::::::::::::::::::::::::::::::::::
+
+::::::::::::::::::::::::::::::::::::::: challenge
+
+## Summary statistics and groupby()
+
+We can apply `mean()` to pandas series' in the same way we used `sum()`, `min()`, and `max()` above. How would you display the following?
+
+1. the mean number of ytd checkouts grouped by zip code?
+2. the mean number of ytd checkouts grouped by zip code, and sorted from smallest to largest?
+
+
+::::::::::::::: solution
+
+## Solution
+
+```python
+#1
+df.groupby('zip code')['ytd'].mean()
+
+#2
+df.groupby('zip code')['ytd'].mean().sort_values()
+
+```
+:::::::::::::::::::::::::
+::::::::::::::::::::::::::::::::::::::::::::::::::
+
+
+
## Use .iloc[] and .loc[] to select DataFrame locations.
You can point to specific locations in a DataFrame using two-dimensional numerical indexes with `.iloc[]`.
@@ -284,6 +369,25 @@ Branch: Albany Park
YTD circ: 120059
```
+::::::::::::::::::::::::::::::::::::::: challenge
+
+## Using loc()
+
+How would you use `loc()` to select rows 20 to 30 from the zip code column (the same rows as the last example in the challenge above)?
+
+Tip: slices use "non-inclusive" indexing -- so require you to ask for `df[10:21]` to see row 20, but `loc()` uses inclusive indexing.
+
+::::::::::::::: solution
+
+## Solution
+
+```python
+df.loc[20:30, 'zip code']
+
+```
+:::::::::::::::::::::::::
+::::::::::::::::::::::::::::::::::::::::::::::::::
+
## Save DataFrames
You might want to export the series of usage by year and branch that we just created so that you can share it with colleagues. Pandas includes a variety of methods that begin with `.to_...` that allow us to convert and export data in different ways. First, let's save our series as a DataFrame so we can view the output in a better format in our Jupyter notebook.
@@ -335,107 +439,6 @@ df.to_pickle('data/all_years.pkl')
```
-::::::::::::::::::::::::::::::::::::::: challenge
-
-## Displaying rows and columns
-
-How would you use slicing and column names to select the following subsets of rows and columns from the circulation DataFrame?
-
-1. The city column.
-2. Rows 10 to 20.
-3. Rows 20 to 30 from the zip code column.
-
-::::::::::::::: solution
-
-## Solution
-
-```python
-#1
-df['city']
-
-#2
-df[10:21]
-
-#3
-df['zip code'][20:31]
-
-```
-
-
-:::::::::::::::::::::::::
-::::::::::::::::::::::::::::::::::::::::::::::::::
-
-
-::::::::::::::::::::::::::::::::::::::: challenge
-
-## Using loc()
-
-How would you use `loc()` to select rows 20 to 30 from the zip code column (the same rows as the last example in the challenge above)?
-
-Tip: slices use "non-inclusive" indexing -- so require you to ask for `df[10:21]` to see row 20, but `loc()` uses inclusive indexing.
-
-::::::::::::::: solution
-
-## Solution
-
-```python
-df.loc[20:30, 'zip code']
-
-```
-:::::::::::::::::::::::::
-::::::::::::::::::::::::::::::::::::::::::::::::::
-
-::::::::::::::::::::::::::::::::::::::: challenge
-
-## Unique items
-
-How would you display:
-
-1. all of the unique zip codes in the dataset?
-2. the number of unique zip codes in the dataset?
-
-
-::::::::::::::: solution
-
-## Solution
-
-```python
-
-#1
-df['zip code'].unique()
-
-#2
-df['zip code'].nunique()
-
-```
-:::::::::::::::::::::::::
-::::::::::::::::::::::::::::::::::::::::::::::::::
-
-::::::::::::::::::::::::::::::::::::::: challenge
-
-## Summary statistics and groupby()
-
-We can apply `mean()` to pandas series' in the same way we used `sum()`, `min()`, and `max()` above. How would you display the following?
-
-1. the mean number of ytd checkouts grouped by zip code?
-2. the mean number of ytd checkouts grouped by zip code, and sorted from smallest to largest?
-
-
-::::::::::::::: solution
-
-## Solution
-
-```python
-#1
-df.groupby('zip code')['ytd'].mean()
-
-#2
-df.groupby('zip code')['ytd'].mean().sort_values()
-
-```
-:::::::::::::::::::::::::
-::::::::::::::::::::::::::::::::::::::::::::::::::
-
:::::::::::::::::::::::::::::::::::::::: keypoints
diff --git a/episodes/tidy.md b/episodes/tidy.md
index 993ea974..edef5e0e 100644
--- a/episodes/tidy.md
+++ b/episodes/tidy.md
@@ -264,6 +264,42 @@ df_long.groupby(['branch', 'month'])['circulation'].agg(['sum', 'mean'])
984 rows × 2 columns
+::::::::::::::::::::::::::::::::::::::: challenge
+
+## Tidy Data Principles
+
+How would you reorganize the following table about research data workshops to follow the three tidy data principles?
+
+1. Every column holds a single variable.
+2. Every row represents a single observation.
+3. Every cell contains a single value.
+
+| Date | Length | Content | Instructor |
+|------------|---------|-------------|------------|
+| 2023-01-15 | 30 min | RDM, DMP | CH |
+| 2023-02-02 | 2 hours | Python, RDM | CH, TD |
+| 2023-02-03 | 90 min | Python | SP |
+
+You can use each content unit (e.g., RDM, DMP, Python) as an observation, and breakdown the length of time or instructor initials to match the content unit however you like.
+
+
+::::::::::::::: solution
+
+## Solution
+
+| Year | Month | Day | Length (min) | Content | Instructor |
+|------|-------|-----|--------------|---------|------------|
+| 2023 | 01 | 15 | 20 | RDM | CH |
+| 2023 | 01 | 15 | 10 | DMP | CH |
+| 2023 | 02 | 02 | 100 | Python | TD |
+| 2023 | 02 | 02 | 20 | RDM | CH |
+| 2023 | 02 | 03 | 100 | Python | SP |
+
+:::::::::::::::::::::::::
+
+::::::::::::::::::::::::::::::::::::::::::::::::::
+
+
## Adding a Date Column
In order to plot this data over time in the data visualization we need to do three things to prepare it. First, we need to combine the year and month columns into its own column. Second, convert the new date column to a [datetime](https://docs.python.org/3/library/datetime.html) objec using the Pandas `to_datetime` function. Third, we assign the date column as our index for the data. These steps will set up our data for plotting.
@@ -338,41 +374,6 @@ df_long.to_pickle('data/df_long.pkl')
```
::::::::::::::::::::::::::::::::::::::: challenge
-## Tidy Data Principles
-
-How would you reorganize the following table about research data workshops to follow the three tidy data principles?
-
-1. Every column holds a single variable.
-2. Every row represents a single observation.
-3. Every cell contains a single value.
-
-| Date | Length | Content | Instructor |
-|------------|---------|-------------|------------|
-| 2023-01-15 | 30 min | RDM, DMP | CH |
-| 2023-02-02 | 2 hours | Python, RDM | CH, TD |
-| 2023-02-03 | 90 min | Python | SP |
-
-You can use each content unit (e.g., RDM, DMP, Python) as an observation, and breakdown the length of time or instructor initials to match the content unit however you like.
-
-
-::::::::::::::: solution
-
-## Solution
-
-| Year | Month | Day | Length (min) | Content | Instructor |
-|------|-------|-----|--------------|---------|------------|
-| 2023 | 01 | 15 | 20 | RDM | CH |
-| 2023 | 01 | 15 | 10 | DMP | CH |
-| 2023 | 02 | 02 | 100 | Python | TD |
-| 2023 | 02 | 02 | 20 | RDM | CH |
-| 2023 | 02 | 03 | 100 | Python | SP |
-
-:::::::::::::::::::::::::
-
-::::::::::::::::::::::::::::::::::::::::::::::::::
-
-::::::::::::::::::::::::::::::::::::::: challenge
-
## Subsetting df_long
Using df_long, create a new DataFrame, `low_circ', that only includes branches with circulation numbers lower than 500 per month. When you create a subset DataFrame, show the following columns: branch, circulation, month, and year. Next, eliminate the rows when the circulation is equal to 0.
diff --git a/episodes/variables.md b/episodes/variables.md
index 3e4c1d49..c0d77f2b 100644
--- a/episodes/variables.md
+++ b/episodes/variables.md
@@ -74,6 +74,42 @@ f'{name} is {age} years old'
'Ahmed is 42 years old'
```
+::::::::::::::::::::::::::::::::::::::: challenge
+
+## F-string Syntax
+
+Use an f-string to construct output in Python by filling in the blanks with variables and f-string syntax to tell Christina how old she will be in 10 years.
+
+Tip: You can combine variables and mathematical expressions in an f-string in the same way you can in variable assignment. We'll see more examples of dynamic f-string output as we go through the lesson.
+
+```python
+name = 'Christina'
+age = 23
+
+f'{____}, you will be ______ in 10 years.'
+```
+
+::::::::::::::: solution
+
+## Solution
+
+```python
+f'{name}, you will be {age + 10} in 10 years.'
+
+```
+
+```output
+'Christina, you will be 33 in 10 years.'
+
+```
+
+
+
+:::::::::::::::::::::::::
+
+::::::::::::::::::::::::::::::::::::::::::::::::::
+
+
## Variables must be created before they are used.
If a variable doesn't exist yet, or if the name has been misspelled, Python reports an error called a `NameError`.
@@ -155,164 +191,116 @@ TypeError Traceback (most recent call last)
TypeError: unsupported operand type(s) for -: 'str' and 'str'
```
-## Use an index to get a single character from a string.
+::::::::::::::::::::::::::::::::::::::: challenge
-We can reference the specific location of a character (individual letters, numbers, and so on) in a string by using its index position. In Python, each character in a string (first, second, etc.) is given a number, which is called an index. Indexes begin from 0 rather than 1. We can use an index in square brackets to refer to the character at that position.
+## Fractions
-```python
-library = 'Alexandria'
-library[0]
-```
+What type of value is 3.4?
+How can you find out?
-```output
-A
-```
+::::::::::::::: solution
-## Use a slice to get multiple characters from a string.
+## Solution
-A slice is a part of a string that we can reference using `[start:stop]`, where `start` is the index of the first character we want and `stop` is the last character. Referencing a string slice does not change the contents of the original string. Instead, the slice returns a copy of the part of the original string we want.
+It is a floating-point number (often abbreviated "float").
```python
-library[0:3]
+print(type(3.4))
```
```output
-Ale
+
```
-Note that in the example above, `library[0:3]` begins with zero, which refers to the first element in the string, and ends with a 3. When working with slices the end point is interpreted as going up to, *but not including* the index number provided. In other words, the character in the index position of 3 in the string `Alexandria` is `x`, so the slice `[0:3]` will go up to but not include that character, and therefore give us `Ale`.
+:::::::::::::::::::::::::
-## Use the built-in function `len` to find the length of a string.
+::::::::::::::::::::::::::::::::::::::::::::::::::
-The `len()`function will tell us the length of an item. In the case of a string, it will tell us how many characters are in the string.
+::::::::::::::::::::::::::::::::::::::: challenge
-```python
-len('Babel')
-```
+## Automatic Type Conversion
-```output
-5
-```
+What type of value is 3.25 + 4?
-## Variables only change value when something is assigned to them.
+::::::::::::::: solution
-Once a Python variable is assigned it will not change value unless the code is run again. The value of `older_age` below does not get updated when we change the value of `age` to `50`, for example:
+## Solution
+
+It is a float: integers are automatically converted to floats as necessary.
```python
-age = 42
-older_age = age + 3
-age = 50
-f'Older age is {older_age} and age is {age}'
+result = 3.25 + 4
+print(result, 'is', type(result))
```
```output
-Older age is 45 and age is 50
+7.25 is
```
-A variable in Python is analogous to a sticky note with a name written on it: assigning a value to a variable is like putting a sticky note on a particular value. When we assigned the variable `older_age`, it was like we put a sticky note with the name `older_age` on the value of `45`. Remember, `45` was the result of `age + 3` because `age` at that point in the code was equal to `42`. The `older_age` sticky note (variable) was never attached to (assigned to) another value, so it doesn't change when the `age` variable is updated to be `50`.
-
-::::::::::::::::::::::::::::::::::::::: challenge
-
-## F-string Syntax
-
-Use an f-string to construct output in Python by filling in the blanks with variables and f-string syntax to tell Christina how old she will be in 10 years.
+:::::::::::::::::::::::::
-Tip: You can combine variables and mathematical expressions in an f-string in the same way you can in variable assignment. We'll see more examples of dynamic f-string output as we go through the lesson.
+::::::::::::::::::::::::::::::::::::::::::::::::::
-```python
-name = 'Christina'
-age = 23
-f'{____}, you will be ______ in 10 years.'
-```
-::::::::::::::: solution
+## Use an index to get a single character from a string.
-## Solution
+We can reference the specific location of a character (individual letters, numbers, and so on) in a string by using its index position. In Python, each character in a string (first, second, etc.) is given a number, which is called an index. Indexes begin from 0 rather than 1. We can use an index in square brackets to refer to the character at that position.
```python
-f'{name}, you will be {age + 10} in 10 years.'
-
+library = 'Alexandria'
+library[0]
```
```output
-'Christina, you will be 33 in 10 years.'
-
+A
```
+## Use a slice to get multiple characters from a string.
-
-:::::::::::::::::::::::::
-
-::::::::::::::::::::::::::::::::::::::::::::::::::
-
-::::::::::::::::::::::::::::::::::::::: challenge
-
-## Swapping Values
-
-Draw a table showing the values of the variables in this program
-after each statement is executed.
-In simple terms, what do the last three lines of this program do?
+A slice is a part of a string that we can reference using `[start:stop]`, where `start` is the index of the first character we want and `stop` is the last character. Referencing a string slice does not change the contents of the original string. Instead, the slice returns a copy of the part of the original string we want.
```python
-x = 1.0
-y = 3.0
-swap = x
-x = y
-y = swap
+library[0:3]
```
-::::::::::::::: solution
-
-## Solution
-
-```
-swap = x # x = 1.0 y = 3.0 swap = 1.0
-x = y # x = 3.0 y = 3.0 swap = 1.0
-y = swap # x = 3.0 y = 1.0 swap = 1.0
+```output
+Ale
```
-These three lines exchange the values in `x` and `y` using the `swap`
-variable for temporary storage. This is a fairly common programming idiom.
-
-
-:::::::::::::::::::::::::
-
-::::::::::::::::::::::::::::::::::::::::::::::::::
+Note that in the example above, `library[0:3]` begins with zero, which refers to the first element in the string, and ends with a 3. When working with slices the end point is interpreted as going up to, *but not including* the index number provided. In other words, the character in the index position of 3 in the string `Alexandria` is `x`, so the slice `[0:3]` will go up to but not include that character, and therefore give us `Ale`.
::::::::::::::::::::::::::::::::::::::: challenge
-## Predicting Values
-
-What is the final value of `position` in the program below?
-(Try to predict the value without running the program,
-then check your prediction.)
-
-```python
-initial = "left"
-position = initial
-initial = "right"
-```
-
-::::::::::::::: solution
+## Slicing
-## Solution
+We know how to slice using an explicit start and end point:
```python
-initial = "left" # Initial is assigned the string "left"
-position = initial # Position is assigned the variable initial, currently "left"
-initial = "right" # Initial is assigned the string "right"
-print(position)
+library_name = 'Library of Babel'
+f'library_name[1:3] is: {library_name[1:3]}'
```
-
```output
-left
+'library_name[1:3] is: ib'
```
-The last assignment to position was "left"
+But we can also use implicit and negative index values when we define a slice. Try the following (replacing `low` and `high` with index positions of your choosing) to figure out how these different forms of slicing work:
+
+1. What does `library_name[low:]` (without a value after the colon) do?
+2. What does `library_name[:high]` (without a value before the colon) do?
+3. What does `library_name[:]` (just a colon) do?
+4. What does `library_name[number:negative-number]` do?
+::::::::::::::: solution
+## Solution
+1. It will slice the string, starting at the `low` index and stopping at the end of the string.
+2. It will slice the string, starting at the beginning on the string, and ending an element before the `high` index.
+3. It will print the entire string.
+4. It will slice the string, starting the `number` index, and ending a distance of the absolute value of `negative-number` elements from the end of the string.
+
+
:::::::::::::::::::::::::
::::::::::::::::::::::::::::::::::::::::::::::::::
@@ -345,88 +333,102 @@ TypeError: 'int' object is not subscriptable
::::::::::::::::::::::::::::::::::::::::::::::::::
-::::::::::::::::::::::::::::::::::::::: challenge
-
-## Slicing
+## Use the built-in function `len` to find the length of a string.
-We know how to slice using an explicit start and end point:
+The `len()`function will tell us the length of an item. In the case of a string, it will tell us how many characters are in the string.
```python
-library_name = 'Library of Babel'
-f'library_name[1:3] is: {library_name[1:3]}'
+len('Babel')
```
+
```output
-'library_name[1:3] is: ib'
+5
```
-But we can also use implicit and negative index values when we define a slice. Try the following (replacing `low` and `high` with index positions of your choosing) to figure out how these different forms of slicing work:
-
-1. What does `library_name[low:]` (without a value after the colon) do?
-2. What does `library_name[:high]` (without a value before the colon) do?
-3. What does `library_name[:]` (just a colon) do?
-4. What does `library_name[number:negative-number]` do?
-
-::::::::::::::: solution
+## Variables only change value when something is assigned to them.
-## Solution
+Once a Python variable is assigned it will not change value unless the code is run again. The value of `older_age` below does not get updated when we change the value of `age` to `50`, for example:
-1. It will slice the string, starting at the `low` index and stopping at the end of the string.
-2. It will slice the string, starting at the beginning on the string, and ending an element before the `high` index.
-3. It will print the entire string.
-4. It will slice the string, starting the `number` index, and ending a distance of the absolute value of `negative-number` elements from the end of the string.
-
-
+```python
+age = 42
+older_age = age + 3
+age = 50
+f'Older age is {older_age} and age is {age}'
+```
-:::::::::::::::::::::::::
+```output
+Older age is 45 and age is 50
+```
-::::::::::::::::::::::::::::::::::::::::::::::::::
+A variable in Python is analogous to a sticky note with a name written on it: assigning a value to a variable is like putting a sticky note on a particular value. When we assigned the variable `older_age`, it was like we put a sticky note with the name `older_age` on the value of `45`. Remember, `45` was the result of `age + 3` because `age` at that point in the code was equal to `42`. The `older_age` sticky note (variable) was never attached to (assigned to) another value, so it doesn't change when the `age` variable is updated to be `50`.
::::::::::::::::::::::::::::::::::::::: challenge
-## Fractions
+## Swapping Values
-What type of value is 3.4?
-How can you find out?
+Draw a table showing the values of the variables in this program
+after each statement is executed.
+In simple terms, what do the last three lines of this program do?
+
+```python
+x = 1.0
+y = 3.0
+swap = x
+x = y
+y = swap
+```
::::::::::::::: solution
## Solution
-It is a floating-point number (often abbreviated "float").
-
-```python
-print(type(3.4))
```
-
-```output
-
+swap = x # x = 1.0 y = 3.0 swap = 1.0
+x = y # x = 3.0 y = 3.0 swap = 1.0
+y = swap # x = 3.0 y = 1.0 swap = 1.0
```
+These three lines exchange the values in `x` and `y` using the `swap`
+variable for temporary storage. This is a fairly common programming idiom.
+
+
:::::::::::::::::::::::::
::::::::::::::::::::::::::::::::::::::::::::::::::
::::::::::::::::::::::::::::::::::::::: challenge
-## Automatic Type Conversion
+## Predicting Values
-What type of value is 3.25 + 4?
+What is the final value of `position` in the program below?
+(Try to predict the value without running the program,
+then check your prediction.)
+
+```python
+initial = "left"
+position = initial
+initial = "right"
+```
::::::::::::::: solution
## Solution
-It is a float: integers are automatically converted to floats as necessary.
-
```python
-result = 3.25 + 4
-print(result, 'is', type(result))
+initial = "left" # Initial is assigned the string "left"
+position = initial # Position is assigned the variable initial, currently "left"
+initial = "right" # Initial is assigned the string "right"
+print(position)
```
```output
-7.25 is
+left
```
+The last assignment to position was "left"
+
+
+
:::::::::::::::::::::::::
::::::::::::::::::::::::::::::::::::::::::::::::::
diff --git a/episodes/writing-functions.md b/episodes/writing-functions.md
index a865e002..37732c00 100644
--- a/episodes/writing-functions.md
+++ b/episodes/writing-functions.md
@@ -125,6 +125,34 @@ print(f'result of call is: {result}')
result of call is: None
```
+::::::::::::::::::::::::::::::::::::::: challenge
+
+## Create a function
+
+Write a function called `addition` that takes two parameters and returns their sum. After defining the function, call it with several arguments and print out the results.
+
+
+::::::::::::::: solution
+
+## Solution
+
+```python
+def addition(x, y):
+ return x + y
+
+addition(3, 6)
+```
+
+```output
+9
+
+```
+
+:::::::::::::::::::::::::
+
+::::::::::::::::::::::::::::::::::::::::::::::::::
+
+
## Variable scope
When we define a variable inside of a function in Python, it's known as a `local` variable, which means that it's not visible to -- or known by -- the rest of the program. Variables that we define outside of functions are `global` and are therefore visible throughout the program, *including* from within other functions. The part of a program in which a variable is visible is called its *scope*.
@@ -169,67 +197,6 @@ Cell In[22], line 4
NameError: name 'days_overdue' is not defined
```
-## Use docstrings to provide online help.
-
-If the first thing in a function is a string that isn’t assigned to a variable, that string is attached to the function as its documentation. This kind of documentation at the beginning of a function is called a `docstring`.
-
-```python
-def fahr_to_celsius(temp):
- "Input a fahrenheit temperature and return the value in celsius"
- return ((temp - 32) * (5/9))
-```
-
-This is helpful because we can now ask Python’s built-in help system to show us the documentation for the function:
-
-```python
-help(fahr_to_celsius)
-```
-
-```output
-Help on function fahr_to_celsius in module __main__:
-
-fahr_to_celsius(temp)
- Input a fahrenheit temperature and return the value in celsius
-```
-
-We don’t need to use triple quotes when we write a docstring, but if we do, we can break the string across multiple lines:
-
-```python
-def fahr_to_celsius(temp):
- """Convert fahrenheit values to celsius
- Input a value in fahrenheit
- Output a value in celsius"""
- return ((temp - 32) * (5/9))
-```
-
-
-::::::::::::::::::::::::::::::::::::::: challenge
-
-## Create a function
-
-Write a function called `addition` that takes two parameters and returns their sum. After defining the function, call it with several arguments and print out the results.
-
-
-::::::::::::::: solution
-
-## Solution
-
-```python
-def addition(x, y):
- return x + y
-
-addition(3, 6)
-```
-
-```output
-9
-
-```
-
-:::::::::::::::::::::::::
-
-::::::::::::::::::::::::::::::::::::::::::::::::::
-
::::::::::::::::::::::::::::::::::::::: challenge
## Conditional statements within functions
@@ -317,6 +284,41 @@ Local variables:
::::::::::::::::::::::::::::::::::::::::::::::::::
+
+## Use docstrings to provide online help.
+
+If the first thing in a function is a string that isn’t assigned to a variable, that string is attached to the function as its documentation. This kind of documentation at the beginning of a function is called a `docstring`.
+
+```python
+def fahr_to_celsius(temp):
+ "Input a fahrenheit temperature and return the value in celsius"
+ return ((temp - 32) * (5/9))
+```
+
+This is helpful because we can now ask Python’s built-in help system to show us the documentation for the function:
+
+```python
+help(fahr_to_celsius)
+```
+
+```output
+Help on function fahr_to_celsius in module __main__:
+
+fahr_to_celsius(temp)
+ Input a fahrenheit temperature and return the value in celsius
+```
+
+We don’t need to use triple quotes when we write a docstring, but if we do, we can break the string across multiple lines:
+
+```python
+def fahr_to_celsius(temp):
+ """Convert fahrenheit values to celsius
+ Input a value in fahrenheit
+ Output a value in celsius"""
+ return ((temp - 32) * (5/9))
+```
+
+
::::::::::::::::::::::::::::::::::::::: challenge
## CSVs to Pandas function