### Toolbox: Name and Frequency of unique elements from a List in Python

Count unique categories in a list...

### Create Travel Map with Python and PyGMT

Prepare map for Instagram post...

### Get more from Crime Rate data and other socio-economic indicators with Pyinterpolate

Transform low-resolution county aggregates into high-resolution input for your machine learning models and analysis....

### Toolbox: Get date n weeks from another date in Python

If you want to trim your weekly time series into training and test set, or create / check the date n weeks ahead or back then this function is for you!...

### Spatial Epidemiology: Baltic Sea and Algal Blooms – how to get data?

Dangerous and toxic algal blooms are a worldwide issue. Where do we get data to analyze those events?...

### Data Science: Moving Average or Moving Median for Data Filtering – Time Series

Moving Mean or Moving Median for Time Series filtering?...

### Geostatistics: Theoretical Variogram Models

Comparison of different semivariogram models...

### 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...

### Spatial Interpolation 101: Variance and Dataset Dimensions

The semivariance is a crucial concept of spatial statistics. We’ve made initial steps to understand it in the previous article when we discovered basic statistical parameters: the mean and the standard deviation. Here we are going a step further, and we look into the variance....

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