Description
Introduction. This homework is the second in a two assignment arc intended to introduce you to
dealing with data that is stored on disk in csv format using pandas. In this assignment, you will
reproduce figures from the web created by the National Snow and Ice Data Center (NSIDC) and Japan’s
version, the Arctic Data Archive System (ADS). The NSIDC plot is the way they used to do it, better than
their current version. The ADS site will be changing soon, so who knows how long that link will work.
Plus, they made their plots worse. We’ll recreate the old style.
Instructions. Create a module named hw8.py. Below is the spec for seven functions. Implement them
and upload your module to D2L Assignments.
Testing. Download hw8_test.py and auxiliary testing files and put them in the same folder as your
hw8.py module. Each of the first three functions is worth 20% of your total score. You do not directly
receive points for main, but it has to work correctly or you will get no points for two of your other
functions. You can examine the test module in a text editor to understand better what your code should
do. The test module is part of the spec. The test file we will use to grade your program will be different
and may uncover failings in your work not evident upon testing with the provided file. Add any
necessary tests to make sure your code works in all cases.
Documentation. Your module must contain a header docstring containing your name, your section
leader’s name, the date, ISTA 131 Hw8, and a brief summary of the module. Each function must
contain a docstring. Each docstring should include a description of the function’s purpose, the name,
type, and purpose of each parameter, and the type and meaning of the function’s return value.
Grading. Your module will be graded on correctness, documentation, and coding style. Code should be
clear and concise. You will only lose style points if your code is a real mess. Include inline comments to
explain tricky lines and summarize sections of code.
Collaboration. Collaboration is allowed. You are responsible for your learning. Depending too much on
others will hurt you on the tests. “Helping” others too much harms them in reality. Cite any
sources/collaborators in your header docstring. Leaving this out is dishonest.
Resources.
http://nsidc.org/arcticseaicenews/
https://ads.nipr.ac.jp/vishop/#/extent
http://pandas.pydata.org/pandas-docs/stable/api.html
https://docs.python.org/3/tutorial/datastructures.html
http://matplotlib.org/users/mathtext.html
http://matplotlib.org/api/axes_api.html
get_column_labels: Cut-and-paste this one from hw7, if you want to use it.
get_2019: This function reads the data from data_2019.csv, which looks like this:
and returns a Series that looks like this:
I used get_column_labels as the first step in constructing the index for my Series, but you
may do it however you see fit.
extract_fig_1_frame: This function takes the DataFrame you created in hw5, which looks like
this:
It contains data for each day of the year from 1979 through 2018. Return a DataFrame that looks like
this:
The mean row contains the mean of the data in a given column, the two_s row contains 2 × the
standard deviation of the column.
extract_fig_2_frame: This function takes the DataFrame you created in hw7 (illustrated at the
bottom of the previous page) and returns a frame that looks like this:
The values are the decadal means for that date. The 2010’s values are the means for the years 2010-
2018.
make_fig_1: This function takes a figure 1 frame and a hw5 frame, and creates a figure that looks
like the image on the following page. The rubric for this figure:
• +4: the gray area looks like the image. It must not be bordered with visible lines.
• +2 each: the three curves look like the image.
• +4: the y-axis title looks like the image. Superscripts required for any title points.
• +2: correct x-axis tick labels.
• +4: legend looks like the image. Plus/minus symbol required for any legend points.
make_fig_2: This function takes a figure 2 frame and creates a figure that looks like the image on the
following page. The rubric for this figure:
• +2 each: the five curves look like the image.
• +4: the y-axis title looks like the image. Superscripts required for any title points.
• +2: correct x-axis tick labels.
• +4: legend looks like the image.
main: Read the data in the file data_79_18.csv into a frame, recreating the hw7 frame. Make a
figure 1 frame and a figure 2 frame. Make the figures (don’t forget to call plt.figure() in between)
and call plt.show() at the end.
