Getting Started
Figure 1
To run the access test
1. visit https://broad.io/cb-python-access-test
2. click “Copy to Drive” and create your own copy of
Python_workshop_data_access_test.ipynb
Figure 2
If you see this dialog box, click “Connect to Google Drive”
Figure 3
Authorize access for the google account you’re using for this
workshop. There will be several prompts to grant access. You’ll need to grant
Google all the permissions it requests to make your google drive
accessible to Colab.
Figure 4
Once access has been granted, go back to the access test
notebook, click the ▶️ symbol on the left hand side of the first code
cell. You’ve successfully loaded data if you see a dataframe appear
beneath the code cell
Figure 5
![Partial listing of example notebooks offered by Google colab](fig/colab_resources.png)
Figure 6
![Are you still there prompt](fig/are_you_still_there.png)
Figure 7
![View of newly created notebook](fig/new_colab_notebook.png)
Variables and Types
Lists
Built-in Functions and Help
Libraries & Pandas
For Loops
Figure 1
![Loop variable 'num' being assigned the value of each element in the list odds in turn and then being printed](fig/for_loop.png)
Looping Over Data Sets
Conditionals
Writing Functions
Data Visualisation
Figure 1
![Line plot of zip code, ytd, year, and circulation numbers over time from the albany DataFrame](fig/albany-plot-1.png)
Figure 2
![Line plot of the Albany Park branch circulation showing a big drop from 2013 to 2014.](fig/albany-circ-3.png)
Figure 3
![Line plot of the Albany Park branch circulation with matplotlib styles applied.](fig/albany-circ-labeling-5.png)
Figure 4
![Area plot of the Albany Park branch circulation.](fig/albany-circ-area-7.png)
Figure 5
![histogram of the Albany branch circulation.](fig/albany-circ-hist-9.png)
Figure 6
![image showing the circulation of the Chinatown branch over ten years](fig/chinatown_circulation.png)
Chinatown plot
Figure 7
![image showing the circulation of the Uptown branch with labels](fig/uptown_plot.png)
Uptown plot
Figure 8
![a bar plot of the top five branch circulation figures](fig/top_five_circ.png)
Top five circulation branches
Using Pandas
Tidy Data with Pandas
Figure 1
![image showing variables in columns, observations in rows, and values in cellssan](fig/tidy-1.png)
Tidy Data