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Blobs are little monsters that you can use to demonstrate data analysis procedures. They have a size, a weight, a color and a cuteness level. As you can see, a blob dataset contains all types of variables that you can find in the wild (nominal, ordinal and metric).
This generator creates a population of blobs. It delivers (a) an Excel data frame with every blob's properties, (b) a population plot that visualizes all blobs for presentation purposes and (c) a set of visualizations of the population data.
The population plot displays all blobs with color and size. In addition to that, it shows blob names. There are three different kinds of base images that can be used to visualize blobs.
The visualization plot inklude a histogram of blob size and blob weights, as well as a bar chart with cuteness level counts and a scatter plot of size and weight.
Blob populations can either have large (12) or small (1) variability, determined by the population's scatter index. Moreover, they can consist of a large number of monsters or can also be small, determined by the population's n.
You can generate a new population by calling:
from blob_creator.core import BlobFactory
# This instantiates a new blob factory
blob_factory = BlobFactory(n=20, scatter=12, kind="monster")
# This will create the blobs
blob_factory.create_blobs()
# This will export your dataset and your population plot to disk
blob_factory.export_data()
# Upload the csv file of the popoulation to share
# it with your students
blob_factory.upload_dataset()
# Finally, the output directory can be cleaned-up
blob_factory.delete_individual_pngs()
This package can be installed using Python's package index. Use the following command to do this:
pip install blob-creator
FAQs
Package to create dummy datasets for analysis tasks
We found that blob-creator demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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