The Checklist below is designed to help you recap on the Python topics covered at level 4 (KD4014).
Your personal checklist is generated below. You can also interact with me, choochoo-bot, using commands in this thread.
To list all possible choochoo commands type choochoo list commands in comment box below.
1) - [x] Create a new Jupyter Notebook |
2) - [x] Save and download a Jupyter Notebook |
3) - [ ] Create Markdown cells in a Jupyter Notebook |
4) - [ ] Run Python code in a Jupyter Notebook |
5) - [ ] Create in-line code comments using # |
9) - [ ] Explain the difference between integers and floats |
10) - [ ] Explain the difference between numeric values and strings |
11) - [ ] Convert between numbers and strings |
12) - [ ] Round a number to a specified number of decimal places |
13) - [ ] Use help() or ? (in Jupyter Notebooks) to access help documentation for a function |
14) - [ ] Descrive the difference between syntax errors and runtime errors |
15) - [ ] Create a Python list |
16) - [ ] Find the length of a list |
17) - [ ] Fetch an item from a list using list indexing |
18) - [ ] Fetch multiple item from a list using list slicing |
19) - [ ] Replace an item in a list with a new value |
20) - [ ] Identify the iterable, dummy variable and loop body in a For loop |
21) - [ ] Use a For loop to repeat a basic programming task |
22) - [ ] Use range to iterate over a sequence of numbers |
23) - [ ] Use if to control whether a block of code is executed |
24) - [ ] Combine a for loop and an if loop to implement a basic programming task |
25) - [ ] Use a combination of if, elif and else to implement a basic programming task |
26) - [ ] Test if a combination of things are true using and or or. |
32) - [ ] Read in data from a text file |
33) - [ ] Describe the difference between Numpy arrays and Python lists |
34) - [ ] Write a Numpy array to a text file |
35) - [ ] Create a one-dimensional Numpy array with zero-values |
36) - [ ] Create a two-dimensional Numpy array with zero-values |
37) - [ ] Create a one-dimensional Numpy array with pre-defined values |
38) - [ ] Create a Numpy array with evenly spaced numbers over a given interval |
39) - [ ] Create a Numpy array with evenly spaced numbers over a given interval in logspace |
40) - [ ] Combine the enumerate function with a for loop to populate a Numpy array |
41) - [ ] Use array indexing to select a single element from a 2D array |
42) - [ ] Use array slicing to select a column of a 2D array |
43) - [ ] Use array slicing to select a row of a 2D array |
44) - [ ] Generate a basic line plot |
45) - [ ] Generate a basic scatter plot |
46) - [ ] Label the plot with an x-axis label, y-axis label and title |
47) - [ ] Create a plot legend |
48) - [ ] Use a figure and subplots to group similar plots |
49) - [ ] Save a plot as a .png file |
50) - [ ] Use the least-squares method to fit a polynomial function to data |
51) - [ ] Plot the polynomial fit alongside the raw data for comparison |
52) - [ ] Use Numpy array operations to perform mathematical operations across an array |
53) - [ ] Use Numpy functions e.g. mean, max, min or round across one or more array axes. |
54) - [ ] Plot the uncertainty associated with a measurement using an errorbar |
Hello Student :wave:
Welcome to Choochoo the checklist tool! :train:
The Checklist below is designed to help you recap on the Python topics covered at level 4 (KD4014).
Your personal checklist is generated below. You can also interact with me, choochoo-bot, using commands in this thread. To list all possible choochoo commands type
choochoo list commandsin comment box below.Running Python | links |
1) - [x] Create a new Jupyter Notebook |
2) - [x] Save and download a Jupyter Notebook |
3) - [ ] Create Markdown cells in a Jupyter Notebook |
4) - [ ] Run Python code in a Jupyter Notebook |
5) - [ ] Create in-line code comments using
#|Variables and Assignment | links |
6) - [ ] Use variables to store values |
7) - [ ] Use
printto display values |8) - [ ] Use meaningful variable names |
Data Types and Type Conversion | links |
9) - [ ] Explain the difference between integers and floats |
10) - [ ] Explain the difference between numeric values and strings |
11) - [ ] Convert between numbers and strings |
Built-in Functions, Help and Errors | links |
12) - [ ] Round a number to a specified number of decimal places |
13) - [ ] Use
help()or?(in Jupyter Notebooks) to access help documentation for a function |14) - [ ] Descrive the difference between syntax errors and runtime errors |
Lists | links |
15) - [ ] Create a Python list |
16) - [ ] Find the length of a list |
17) - [ ] Fetch an item from a list using list indexing |
18) - [ ] Fetch multiple item from a list using list slicing |
19) - [ ] Replace an item in a list with a new value |
For Loops | links |
20) - [ ] Identify the iterable, dummy variable and loop body in a For loop |
21) - [ ] Use a For loop to repeat a basic programming task |
22) - [ ] Use range to iterate over a sequence of numbers |
Conditionals | links |
23) - [ ] Use
ifto control whether a block of code is executed |24) - [ ] Combine a
forloop and anifloop to implement a basic programming task |25) - [ ] Use a combination of
if,elifandelseto implement a basic programming task |26) - [ ] Test if a combination of things are true using
andoror. |Writing Functions | links |
27) - [ ] Define a simple function that returns a value |
28) - [ ] Call a custom-made function |
Variable scope | links |
29) - [ ] Explain the difference between local and global variables |
Libraries | links |
30) - [ ] Import a library |
31) - [ ] Import a library using an alias (nickname) |
Storing data in Numpy arrays | links |
32) - [ ] Read in data from a text file |
33) - [ ] Describe the difference between Numpy arrays and Python lists |
34) - [ ] Write a Numpy array to a text file |
35) - [ ] Create a one-dimensional Numpy array with zero-values |
36) - [ ] Create a two-dimensional Numpy array with zero-values |
37) - [ ] Create a one-dimensional Numpy array with pre-defined values |
38) - [ ] Create a Numpy array with evenly spaced numbers over a given interval |
39) - [ ] Create a Numpy array with evenly spaced numbers over a given interval in logspace |
40) - [ ] Combine the enumerate function with a
forloop to populate a Numpy array |Retrieving data from Numpy arrays | links |
41) - [ ] Use array indexing to select a single element from a 2D array |
42) - [ ] Use array slicing to select a column of a 2D array |
43) - [ ] Use array slicing to select a row of a 2D array |
Visualizing data with Matplotlib | links |
44) - [ ] Generate a basic line plot |
45) - [ ] Generate a basic scatter plot |
46) - [ ] Label the plot with an x-axis label, y-axis label and title |
47) - [ ] Create a plot legend |
48) - [ ] Use a figure and subplots to group similar plots |
49) - [ ] Save a plot as a
.pngfile |Analysing data using Numpy | links |
50) - [ ] Use the least-squares method to fit a polynomial function to data |
51) - [ ] Plot the polynomial fit alongside the raw data for comparison |
52) - [ ] Use Numpy array operations to perform mathematical operations across an array |
53) - [ ] Use Numpy functions e.g.
mean,max,minorroundacross one or more array axes. |54) - [ ] Plot the uncertainty associated with a measurement using an errorbar |
Code Quality | links |
55) - [ ] Use assertions to check for internal errors |
56) - [ ] Write docstrings to provide help messages |
57) - [ ] Print package version numbers to increase code reproducibility |
58) - [ ] Re-factor code to reduce code repetition and remove redundant code |