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An analysis of Project Sidewalk user quality based on interaction logs

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sidewalk-quality-analysis

In this project, we aim to infer the quality of Project Sidewalk users based on their interactions with our system—both low-level interactions like mouse clicks and moves—as well as higher-level, more application related interactions (amount of panning on a street view image, etc.). More details are in our Dropbox folder ProjectSidewalk_PredictingUserQuality

Running the notebook locally using Anaconda

Follow the instructions below and consult the Managing Environments section in the conda docs for more details. There is also a nice conda cheetsheet here.

Step 1: Open your Anaconda terminal and go to the src dir

On Mac, this should be as simple as opening terminal (or, for example, use iterm2—my preferred terminal program).

On Windows, open the Anaconda Powershell Prompt.

Make sure you are in the root directory of this project. For example, for me (on my Windows), this is:

> pwd
D:\git\sidewalk-quality-analysis

Step 2: Create an environment from the environment.yml file

> conda env create -f environment.yml

This might take a few mins but should end with something like

done
#
# To activate this environment, use
#
#     $ conda activate sidewalk-quality-analysis
#
# To deactivate an active environment, use
#
#     $ conda deactivate

Optionally, if you'd like to list the active conda environments on your system and verify that the sidewalk-quality-analysis environment was created:

> conda env list

Step 3: Activate the environment

> conda activate sidewalk-quality-analysis

Step 4: Open jupyter notebook

Now you should see the command line prompt prefixed by the current environment: (sidewalk-quality-analysis). So, your command prompt should look like the following or something similar:

(sidewalk-quality-analysis)$

Now you can type in jupyter notebook and find analysis.ipynb.

(sidewalk-quality-analysis)$ jupyter notebook

In Jupyter Notebook environment, navigate to the analysis.ipynb file and open it.

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An analysis of Project Sidewalk user quality based on interaction logs

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