Zonal Statistics Algorithm with Python in 4 Steps
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Zonal Statistics Algorithm with Python in 4 Steps

It is a common need to summarize information from a gridded dataset within an irregularly shaped area. While at first glance this may seem simple, reconciling differences between raster (gridded) and vector (polygon) datatypes can quickly become complicated. This article shows how to implement a zonal statistics algorithm in Python in 4 steps. Load raster…

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PyQGIS: Create Raster

In a previous tutorial I showed you how to access raster values and data with the Geospatial Data Abstraction Library (GDAL). This tutorial will show you how to create a raster with GDAL. Start by importing the gdal and osr Python modules. The osr module is used for handling spatial references. Also import numpy. Now…

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R: Save NetCDF as a CSV

Sometimes certain analysis may require data in a tabular format (as opposed to the gridded format of NetCDF). This tutorial will take you through how to convert a NetCDF (or other raster/gridded data) to an R data frame, which can then used for analysis or saved as a CSV file. Read the NetCDF file First,…

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numpy: Methods For Creating Arrays

It is tedious, and not practical, to manually type in values for array creation. In this tutorial we will go through methods for automating array creation and importing tabular data into numpy arrays. Creating empty arrays With numpy you don’t actually create an ‘empty’ array. But you can create an array without intializing specific values. This can be useful…

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numpy: Array shapes and reshaping arrays

We’ve gone through the basics to manually create arrays of different dimensions and shapes. There will be times that you will want to query array shapes, or automatically reshape arrays. This tutorial will show you how to use numpy.shape and numpy.reshape to query and alter array shapes for 1D, 2D, and 3D arrays. Different methods are required to find…

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numpy: Creating Arrays

Creating a simple array After numpy is installed, we can begin to create arrays. First, we’ll need to import numpy into our python project. Here I use the statement, import numpy as np, to limit my typing later. This code will allow me to use np in my script to represent instead of typing the full numpy everytime. Then, we can create a simpy…

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numpy: Install numpy

Check Installation First, check to see if you already have numpy installed. From the terminal, you can use pip to do this. If numpy is installed you will get output similar to this. If numpy is not installed no output will be shown. Install numpy numpy can be installed simply using pip. Check version You can check the numpy version using pip show as demonstrated above. Video tutorial This…

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R: Get data from a NetCDF

List the data attributes Accessing the var property of our netCDF varialbe will list the data attributes for the netCDF file. The output shows us this dataset has one data attribute with the name ‘data’. Which is contained within the names property of var. Calling the names property directly after the attributes() call gives the same result. We can get the name of specific…