Data Visualization using Python Libraries

Intro

Hi class! My name is Adison, and I'm going to try and get you started in Python and two of its libraries to make more customizable data visualizations that may come in handy in this coming assignment or in the future.

I've been coding off and on for the last year and have only been learning these libraries during the last few weeks, so I'm no expert, but hopefully, this will be a helpful guide. Feel free to reach out with any questions. Youtube and online forums are also great, as Python has a huge online community.

We will be working with these libraries and tools.

Deepnote

Jupyter Notebook Blocks

This is a text block, or a Markdown block! Deepnote allows you to quickly choose 4 headings or a paragraph block. You can also customize it further with Bold font and bullet lists by using the Markdown option. There is a markdown cheatsheet in the block actions button in the tool ribbon.

print("""This is a code block! I can use it to run my code by clicking "Run Notebook" at the top which will run all the cells (blocks), or the "play button" on the tool ribbon to the right of this if you only want to run this cell.""") # Go ahead and run this cell

This is a code block! I can use it to run my code by clicking "Run Notebook"
at the top which will run all the cells (blocks), or the "play button"  on the tool ribbon
to the right of this if you only want to run this cell.

Importing Libraries

To use these tools, we first have to import them from the Python Library.

import pandas as pd import matplotlib.pyplot as plt

Reading our Data

This is useful for large data sets but isn't necessary for matplotlib if you have smaller data sets you can enter manually.

data_frame = pd.read_csv('/work/bestsellers.csv') # variable name: "data_frame" # command: "pd.read_csv(argument)" # argument: "/work/bestsellers.csv"

We can now view our data frame to make sure it looks correct.

# simply type in the variable name and run the cell data_frame

Nameobject

Publication Manual of the American Psychological Association, 6th Edition1.8%

StrengthsFinder 2.01.6%

349 others96.5%

Authorobject

Jeff Kinney2.2%

Suzanne Collins2%

246 others95.8%

10-Day Green Smoothie Cleanse

JJ Smith

11/22/63: A Novel

Stephen King

12 Rules for Life: An Antidote to Chaos

Jordan B. Peterson

1984 (Signet Classics)

George Orwell

5,000 Awesome Facts (About Everything!) (National Geographic Kids)

National Geographic Kids

A Dance with Dragons (A Song of Ice and Fire)

George R. R. Martin

A Game of Thrones / A Clash of Kings / A Storm of Swords / A Feast of Crows / A Dance with Dragons

George R. R. Martin

A Gentleman in Moscow: A Novel

Amor Towles

A Higher Loyalty: Truth, Lies, and Leadership

James Comey

A Man Called Ove: A Novel

Fredrik Backman

Making visualizations!

Let's do it already!

ages = [20,25,30,35,40,45] # setting your x values salary = [22000, 34000, 50000, 72000, 90000, 105000] # y values plt.plot(ages,salary, linewidth=2 , marker='*', color='red') # with the plot I've altered the linewidth, which marker to use for each data point, # and the color of the line plt.grid() # added a grid plt.title('Example line plot') # added a title plt.xlabel('Ages') # X axis label plt.ylabel('Salary in $') # Y axis label # There are a ton more customizations to make that will really set your visualization apart

Saving or Embedding

To save your image, simply right-click the image and click "save image as..". To share your block with a web link, click the last button on the tool ribbon to the right of this cell and select "Share block". Now you can choose to include the code associated with the visualization, or not depending on who you are sharing it with.

You can also share the entire Notebook by either sharing a link that allows varying degrees of access, or exporting the notebook as a PDF. This can all be done by using the "Share & publish" button in the top right corner.

Conclusion

This concludes this extremely brief introduction to Python and only one of its useful data visualization libraries (there are many more). Please reach out with any questions and hopefully I can point you in the right direction. Coding this stuff can be really challenging at times, especially when it's syntax errors like leaving out a comma or quotations, but like I said, Python has a huge online community with tutorials and documentation to reference as you figure all this out.

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