Python package developed for the Lancaster Air Quality project.
Included are tools to:
- Import the dataset
- Convert the dataset to different formats
Note: Package requires >= Python 3.9
$ pip install LancasterAQ
# clone from github
$ git clone https://github.com/lgouldsbrough/LancasterAQ.git
# change directory into project root
$ cd LancasterAQ
# regular install
$ pip install .
# or
# development install
# $ pip install -e .
# pip install from github
pip install git+https://github.com/lgouldsbrough/LancasterAQ.git
# or `python -m pip ...` for environment safety
An introductory notebook can be found within the examples folder.
Note: requires Matplotlib and Seaborn packages.
import LancasterAQ as laq
# load tabular data
data = laq.TabularObject()
# OR load the graph object
data = laq.GraphObject()
A helper function is also available:
import LancasterAQ as laq
# load tabular data
data = laq.dataset('TabularObject')
# OR load the graph object
data = laq.dataset('GraphObject')
To avoid implicit data copies replace the data
object with the dataset function call.
For example: replace data.to_numpy()
with laq.TabularObject().to_numpy()
data = data.to_pandas()
data = data.to_geopandas()
data = data.to_numpy()
To avoid implicit data copies replace the data
object with the dataset function call.
For example: replace data.to_numpy()
with laq.GraphObject().to_numpy()
# returns the graph adjacency matrix as a numpy array
numpy_array = data.to_numpy()
# returns adjacency representation of graph as a dictionary of dictionaries
dict_of_dicts = data.to_dict()
# returns a list of edges in the graph
edge_list = data.to_edgelist()
# returns adjacency representation of graph as a dictionary of lists
dict_of_lists = data.to_dict_of_lists()
# returns the graph adjacency matrix as a scipy sparse array
scipy_sparse_array = data.to_scipy()
# returns json object of graph
data_json = data.to_json()