Package: autoesda
autoESDAA Python package that automates the exploratory spatial data analysis (ESDA) process by summarising the results into an HTML report.Table of ContentsIntroductionKey featuresInstallationDependanciesUsageExamplesContributingLicenseReferencesCredits1. IntroductionExploratory spatial data analysis (ESDA) is a term used to describe a various functions used to gain a surface-level understanding of a spatial dataset. Currently the ESDA process is repetative as each of these functions need to be calculated individually. This makes it quite a time consumining process and also includes a large margain for human-induced errors. Additionally, results are not often easily viewed side-by-side for easy comparison and sharing with people who may not have the technical skills to do so.autoesdais the solution to this by allowing the user to execute one line of code to generate an information-rich HTML report that can easily be shared with others.2. Key featuresHTML output reportExtent mapDataset overview(coordinate system, number of rows/columns, which rows/columns have been included/excluded in the report)Descriptive statistics(count, mean, standard deviation, minimum/maximum, 25th/50th/75thpercentiles)Sample of datasetBoxplotHistogramMoran's I simulation(moran's I, number of features, p-value, z-score, number of permutations)Local Indicator of Spatial Autocorrelation(local scatterplot, LISA cluster map)Choropleth maps(quantiles, equal intervals, natural breaks, and percentiles classification schemes)Correlation(correlation matrix/heatmap, pairwise plot)3. Installationautoesdais available onPyPI, to installautoesda, run this command in your terminal:pip install autoesdageopandasis a primary dependancy ofautoesdaand there are known challenges assosciated with using pip to install geopandas. The recommended strategy is thus, to useautoesdain aconda environment.For advanced users, you can followthisdocumentation which will guide you through the geopandas installation by downloading theunofficial binary filesof some of thegeopandasdependancies.autoesdais also available onconda-forge. If you haveAnacondaorMinicondainstalled on your computer you can use this command in your Anaconda/Miniconda prompt:conda install autoesda4. Dependanciesgeopandaspysalmatplotliblibpysalesdasplotseaborn5. UsageTo start off with, you need to ensure that you have imported bothgeopandasandautoesda.import geopandas as gpd
import autoesdaOnce both libraries have been sucessfully imported, you can import your dataset as a GeoDataFrame. This is done usinggeopandas. To read more about compatible file types, read the geopandasdocumentation. In this example, a shapefile is imported.gdf = gpd.read_file(r'example-file-path\example-shapefile.shp')Once your data is stored in a GeoDataFrame, you can generate the report.autoesda.generate_report(gdf)The report will be saved to your working file directory.6. ExamplesView theexample report7. ContributingClickhereto report bugsClickhereto request a new featureIf you would like to assist with fixing bugs, further development or writing documentation you are most welcome to do so. Use theissuespage to guide what you can assist with.In order to make a contribution you will need to:Fork the autoesda repository on GitHub.Clone your fork locally.Commit your changes to your branch on GitHubOnce you are satsfied that your work is suitable, submit a pull request through the GitHub website.8. LicenseThis software is available under the BSD-3-Clause license.For more information, see theLICENSEfile which contains details on the history of this software, terms & conditions for usage, and a disclaimer of all warranties.9. ReferencesBe on the lookout for a journal article titledTowards an open source python library for automated exploratory spatial data analysis (ESDA)which is to be published in the ISPRS XXIV Archives. Please reference this article whenever you refer to the autoesda library.10. CreditsThis package was created withCookiecutterand thegiswqs/pypackageproject template.