Day 1 In-Class Assignment¶

✅ Put your name here

¶

Using Python and Jupyter Notebooks to plan your next visit to the Gateway Arch National Park¶

Looking up at the Gateway Arch

Credits: National Park Service

Learning goals for today's in-class assignment¶

  • Make sure you have correctly installed Python and Jupyter notebooks via miniconda
  • Check that you can run your first Python code
  • Extract trend informations from data visualization

⚠️ To keep your files organized, make a new folder for this course. Do not keep all your files jumbled in the Downloads folder.¶

  • Make a dedicated folder, where you'll keep all the Jupyter Notebooks and associated data sets

Part I: Introduction to Jupyter Notebooks¶

If you're reading this right now, it means you've already managed to get most of it working! We'll be working through how to download, run, save, and upload Jupyer Notebooks in class.

If you want to start using keyboard shortcuts in Jupyter Notebooks to make your life easier and more efficient, try pressing ESC to enter command mode and then press Ctrl + Shift + H. This will bring up the list of the keyboard shortcuts. Make note of these. As we move through the semester, you'll get used more and more these shortcuts.

  • The most important one (IMO): To make notebook cells that have Python code in them do something, hold down the Shift key and then press the Enter key.
  • Alternatively, you can click the play button  ▶  on the top menu.
  • Another useful shortcut is B to insert a blank cell below.

Remember to press Esc before trying any shortcut

✅  Task 1: Your first Jupyter navigation

  • Press Esc and then B to create and insert a new cell below.
  • Press Esc and then M to make this cell Markdown mode (not code).
  • In the new cell, write a short sentence on what you did last Winter Break.
  • To display the cell as normal text, press either Ctrl+Enter or Shift + Enter.

✅  Task 2: Your first Hello World!

  • Create and insert a new cell below
  • In the new cell, type print('Hello World!')
  • To run this code, again press either Ctrl + Enter or Shift + Enter.

We will learn much more Python throughout the sessions.

✅  Task 3: Edit an existing cell

  • Edit this cell by double clicking on it, or alternatively, click on it once and then press Enter
  • Then complete the sentence below:

For this course, I am looking forward to:

Part II: Introduction to Data Viz with Python¶

Computer-based visualization is widely used in biology to help understand and communicate data, to generate ideas and to gain insight into biological processes: Genomes, sequence alignments, phylogenies, macromolecular structures, systems biology data, and image-based data (O'Donoghue et al 2010).

Data visualization (data viz for short) is not limited to biology. Data viz can help us in general to:

  • Simplify complexity
  • Enhance decision-making
  • Improve communication
  • Reveal hidden insights
  • Engage and persuade

For this assignment, we will use Python and Data Viz to figure out which month would be the best month to visit the Gateway Arch National Park in St. Louis. The monthly visitor data was obtained from the National Park Service statistics.

Make sure you have downloaded the CSV file that came with this lesson.

In [1]:
# Just press Shift + Enter to run this cell
# Or click on the "Play/Run" button on the top menu

# Import libraries

import pandas as pd
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
In [2]:
# Just press Shift + Enter to run this cell
# Or click on the "Play/Run" button on the top menu

# Load and display the data

filename = 'Recreation Visitors By Month Gateway Arch NP.csv'
visits = pd.read_csv(filename, index_col=0)
visits
Out[2]:
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
Year
2024 58573 88836 236061 209455 224478 302480 533302 322088 166264 181075 124801 115639
2023 81397 95271 205586 200997 213062 309799 444863 246598 184624 174886 146410 119343
2022 37942 38975 107142 102741 111872 162685 543140 153348 108741 111471 80576 60141
2021 25026 21258 65025 61664 77152 117599 363556 118126 78848 84326 68249 64252
2020 51753 62958 54112 30000 31000 50905 33748 31610 32146 44372 33888 29529
2019 18962 51416 164238 138309 165964 296149 583866 208999 127764 122770 91836 85036
2018 40170 52068 136466 116666 143522 212462 634978 241684 154380 141037 90061 52686
2017 30163 30233 74140 91530 120796 186788 245532 217438 120806 115574 88069 77119
2016 16552 8387 8387 98719 138336 207288 264652 173446 120732 119830 83136 32390

✅  Task 4: Data interpretation I

Looking just at the table of numbers, can you quickly tell the following (do not spend more than 5 mins here; move on regardless of your progress):

  • What is the month with the most visitors?
  • How big is the gap between the most visited month vs the second most visited month?
  • Do all years follow the same trend?
  • Is there a year that looks very different than the rest?
  • Say you and your family want to visit the Gateway Arch National Park. Assuming that everybody can take time off anytime, what month would you suggest to go?

(Click on this cell and then press Enter to edit it)

✎ Your answers

🛑 STOP: Do not run the cell below just yet until you've finished Task 4¶

Now visualize the data¶

Let's now try to answer the same questions, but instead of looking purely at numbers, let's look at a plot based on these numbers.

In [3]:
# Just press Shift + Enter to run this cell
# Or click on the "Play/Run" button on the top menu

# Set up plot details

font_size = 12
color_list = ['lightgray', 'seagreen', 'indianred', 'tab:blue', 'palevioletred', 'gold', 'orange', 'gray', 'deepskyblue']
marker_list = ['o', 'D', 'P', '<', 'v', '>', '^', 's', 'X', 'h']
xaxis = list(range(visits.shape[1]))

# Making the plot pretty
fig, ax = plt.subplots(1, 1, figsize=(10,5), sharex=True)
ax.set_ylabel('No. of visitors', fontsize=font_size)
ax.set_title('Gateway Arch National Park', fontsize=font_size)
ax.set_facecolor('snow')
ax.tick_params(labelsize=font_size)
ax.set_xticks(xaxis, visits.columns)

# The actual data is plotted
for i in range(len(visits)):
    ax.plot(xaxis, visits.iloc[i], color=color_list[i], marker=marker_list[i], mec='k', ms=10, label=visits.index[i])
ax.legend(loc='upper right', fontsize=font_size, title='Year', title_fontsize='large', framealpha=1, facecolor='whitesmoke');
No description has been provided for this image

✅  Task 5: Data interpretation II

  • What is the month with the most visitors? Do you find it surprising or does it check out your intuition/experience? Explain.
  • How big is the gap between the most visited month vs the second most visited month?
  • Do all years follow the same trend? Is there a year that looks very different than the rest? If so, do you find it surprising or does it check out your intuition/experience? Explain.
  • Say you and your family want to visit the Gateway Arch National Park. Assuming that everybody can take time off anytime, what month would you suggest to go?

(Click on this cell and then press Enter to edit it)

✎ From the graph I above I see that..

✅  Task 6: Compare and contrast

Compare your experience between Task 4 and Task 5.

  • Which Task did you find easier?
  • Was there something that you noticed from the plot that you would have missed just looking at numbers?

(Click on this cell and then press Enter to edit it)

✎ Your answer

Assignment wrap-up¶

Please fill out form from the link below. You must log-in using your MU credentials. You must completely fill this out in order to receive credit for the assignment!

https://forms.office.com/r/cADesBUd7V¶

In [4]:
# Click on the link above if this cell fails to produce a survey form.

from IPython.display import HTML
HTML(
"""
<iframe 
	src="https://forms.office.com/r/cADesBUd7V" 
	width="800px" 
	height="600px" 
	frameborder="0" 
	marginheight="0" 
	marginwidth="0">
	Click the link above if this cell fails to produce a survey
</iframe>
"""
)
Out[4]:

Congratulations, you're done!¶

Save this notebook by going to the "File" tab on the top of the notebook and click "Save Notebook as". Alternatively, press Ctrl + Shift + S. Make sure to change "STUDENT" for your last name in the filename.

Submit this assignment by uploading it to the course Canvas web page. Go to the "In-class assignments" folder, find the assignment submission link for Day 1, and upload it there. Make sure you feel comfortable navigating within Jupyter.

Is there still time?¶

Feel free to start digging into the Pre-Class assignment for the next session. You will find it in the Canvas webpage.

See you next class!

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