Data Science: The four (and a half) metrics to understand your model
Forecast Bias, Mean Absolute Error, Mean Squared Error and Root of it, Symmetric Mean Absolute Percentage Error: use them and be sure that you produce the best models...
Toolbox: K-means algorithm
K-means clustering class for local experiments...
Data Science: Leave GeoPandas and Create Beautiful Map with pyGMT
How to create a beautiful map with Python and pyGMT...
Toolbox: Get all files of a specific type from a given directory in Python
How to get a list of paths to the files with a specific extension in Python....
Toolbox: Dask – Drop Rows with Specific Substrings
Remove rows with a specific substring from Dask DataFrame...
Data Science: Interpolate Air Quality Measurements with Python
How to get dense and continuous map from point observations in Python...
Toolbox: Check if the text from DataFrame is a part of another phrase with Python and Pandas
Test if a record from DataFrame is a part of other phrase...
Data Engineering: The Test Coverage for the Scientific Software
In this tutorial, we will learn about the different types of tests that could cover the scientific package. We are going to create unit and functional tests for the code developed within the Pyinterpolate package. We see how to use Jupyter Notebooks and additional tutorial...
Toolbox: MongoDB nested bson to the flattened DataFrame
How to read and flatten nested bson files with Python and pandas....
Spatial Interpolation 101: Interpolation in Three Dimensions with Python and IDW algorithm. The Mercury Concentration in Mediterranean Sea.
Move from the 2D interpolation into the 3D interpolation with the Inverse Distance Weighting algorithm....