Xarray sel example. You may need to change the path to rasm.

Xarray sel example. In this example, ‘x’ has five elements, but two of them are NaN, so the resulting DataArray object having a single element containing the value ‘3’, which represents the number of non-null elements in x. interp(coords=None, method='linear', assume_sorted=False, kwargs=None, **coords_kwargs) [source] # Interpolate a DataArray onto new coordinates. tutorial. As xarray objects can store coordinates corresponding to each dimension of an array, label-based Xarray for multidimensional gridded data In the previous set of lectures, we saw how Pandas provided a way to keep track of additional “metadata” surrounding tabular datasets, including “indexes” for each row and labels for each column. Xarray N-D labeled arrays and datasets in Python Xarray is an open source project and Python package that introduces labels in the form of dimensions, coordinates, and attributes on top of raw NumPy-like arrays, which allows for more intuitive, more concise, and less error-prone user experience. To begin, import numpy, pandas and xarra Oct 6, 2025 · See also Dataset. Pointwise (Vectorized) Indexing. Pandas Indexes are powerful and suitable for Oct 6, 2025 · Here are some quick examples of what you can do with xarray. To begin, import numpy, pandas and xarray using their customary abbreviations: Jan 2, 2025 · Quick overview # Here are some quick examples of what you can do with xarray. Understand the difference between NumPy and Xarray indexing behavior. sel(lat=slice(min_lat, max_lat), lon=slice(min_lon, max_lon)) seems to work. Under the hood, this method is powered by using pandas’s powerful Index A major use case for xarray is multi-dimensional time-series data. For more details and examples, refer to the relevant chapters in the main part of the documentation. Here is an example of how to easily manipulate a toy weather dataset using xarray and other recommended Python libraries: Ex Oct 10, 2025 · xarray. nc below. One of chunks or chunks_kwargs must be provided. . The most basic way to access elements of a DataArray object is to use Pytho However, some caution is in order: when done repeatedly, this type of indexing is significantly slower than using sel(). Returns: chunked (xarray. stack(dim=None, create_index=True, index_cls=<class 'xarray. At the moment, I help myself with shifting the grid, then selecting: d['lon']. Parameters: dim (mapping of Hashable to sequence of Sep 4, 2025 · Here are some quick examples of what you can do with xarray. Nov 8, 2019 · Since the x and y dimensions are not the lat/lon values, it doesn't seem that the ds. If a local copy is found then always use that to avoid network traffic. Indexing and selecting data xarray offers extremely flexible indexing routines that combine the best features of NumPy and pandas for data selection. Accordingly, we’ve copied many of features that make working with time-series data in pandas such a joy to xarray. If you only provide integers, slices, or unlabeled arrays (array without dimension names, such as np. What if you want to get a range of points? You can use the slice() function with . core. Therefore, we Jan 2, 2025 · Indexing and selecting data # Xarray offers extremely flexible indexing routines that combine the best features of NumPy and pandas for data selection. Suppose we have a netCDF or xarray. Load example dataset: Multiple plots and map projecti Oct 6, 2025 · xarray. time. Under the hood, this method is powered by using pandas’s powerful Index Jan 4, 2022 · You can access the closest datapoint to a specific latitude/longitude using: lat = #yourlatitude lon = #yourlongitude ds_loc = ds. This would retrieve the same data point as all the previous examples. drop_sel(labels=None, *, errors='raise', **labels_kwargs) [source] # Drop index labels from this dataset. It shares a similar API to NumPy and Pandas and supports both Dask and NumPy arrays under the hood. Xarray # 12. Mar 1, 2025 · Quick overview # Here are some quick examples of what you can do with xarray. However, sometimes we need to select non-continuous time periods, such as certain months over several years. sel(indexers=None, method=None, tolerance=None, drop=False, **indexers_kwargs) ¶ Return a new DataArray whose data is given by selecting index labels along the specified dimension (s). Data Structures # DataArray # xarray. Parameters: indexers (dict, optional) – A Accessing and manipulating data in Xarray An xarray Dataset typically consists of multiple DataArrays. Example: import numpy as np import xarray as xr data = Oct 6, 2025 · You can run this notebook in a live session or view it on Github. Read and write netCDF files using Xarray. Xarray's sel() method allows you to specify coordinates at multiple dimentions to extract the array value. indexes. See also: What parts of xarray are considered public API? and How stable is Xarray’s API?. When we use slice with the sel method, it provides an efficient way to select a range of dates. The most basic way to access elements of a DataArray object is to use Python’s [] syntax, such as array[i, j], where i and j are both integers. open_dataset("Phytoplankton. 12. Jan 2, 2025 · Quick overview # Here are some quick examples of what you can do with xarray. stack # DataArray. Under the hood, this method is powered by using pandas’s powerful Index objects Indexing and selecting data ¶ xarray offers extremely flexible indexing routines that combine the best features of NumPy and pandas for data selection. Multidimensional DataArray # If we are just dealing with 1D data, pandas and xarray have very similar capabilities. Mar 20, 2025 · xarray. dt. Oct 6, 2025 · For example, with dask as the default chunked array type, this method would pass additional kwargs to dask. from_array(). loc, as we don't need to remember the dimension order. In most cases, Welcome to the Xarray Tutorial! # Xarray is an open source project and Python package that makes working with labelled multi-dimensional arrays simple, efficient, and fun! 📖 On this Jupyter Book website you’ll find easy-to-run tutorial notebooks for Xarray. is_leap_year, da. But what if we want to do a calculation that involves grouping over one of these physical coordinates (rather than the logical coordinates), for example, calculating the mean temperature at each latitude. Examples include automatic labelling of plots with descriptive names and units if proper metadata is Oct 6, 2025 · You can run this notebook in a live session Binder or view it on Github. Our example dataset has 7 of them (u-component_of_wind_isobaric, LambertConformal_Projection, lat, lon, Geopotential_height_isobaric, v-component_of_wind_isobaric, Temperature_isobaric). Conditional Control of datetime Index # Conditional Control of datetime Index in xarray # In Unit 3, we demonstrated how to use the sel method with slice to select data with a continuous temporal or spatial range. 2. sel or . As an example, let's define a DataArray ds: # Define the dimensions. As xarray objects can store coordinates corresponding to each dimension of an array, label-based What’s New Overview: Why xarray? Frequently Asked Questions Examples Installation Data Structures Indexing and selecting data Computation GroupBy: split-apply-combine Reshaping and reorganizing data Combining data Time series data Working with pandas Serialization and IO Parallel computing with dask Plotting API reference Top-level functions Dataset DataArray xarray. dayofyear==60) result = da. g. Scale out to many machines by deploying Xarray with Dask on an HPC cluster, in the cloud, or with Kubernetes. plot. For the above (my) example, I would write aus = d. Experimental API that should not be relied upon. Xarray is particularly useful for geospatial data because Xarray also supports label-based indexing, just like pandas. Revision 5a28b89d. See also: What parts of xarray are considered public API? Top-level functions # Jan 7, 2022 · I am writing a program that will open Meteorological NetCDF data, slice it for a given region and then do some calculations, for example: data =xr. sel(indexers=None, method=None, tolerance=None, drop=False, **indexers_kwargs) [source] # Returns a new dataset with each array indexed by tick labels along the specified dimension (s). Is there a xarray-centric method to locate the point nearest a desired lat/lon by referencing the multi-dimensional lat/lon dimensions? For example, I want to pluck out the SPEED value nearest lat=21. Out-of-range values are filled with NaN, unless specified otherwise via Dec 21, 2023 · Geospatial data processing at scale with Xarray, Dask, and Pangeo. In your case, something like the following example should work. DataArray Attributes API reference # This page provides an auto-generated summary of xarray’s API. Overview # Xarray is a powerful Python library designed for working with multi-dimensional labeled datasets, often used in fields such as climate science, oceanography, and remote sensing. ARGO floats collect one Boolean Indexing & Masking # Learning Objectives # The concept of boolean masks Dropping/Masking data using where Using isin for creating a boolean mask Overview # Boolean masking, known as boolean indexing, is a functionality in Python that enables the filtering of values based on a specific condition. Index subclass which implements the logic so that . sel(lat=slice(-44,-10), lon=slice(110, 155)) The problem is areas at the wrapping border, for example: gb = d. Pandas Indexes are powerful and suitable for Oct 6, 2025 · You can run this notebook in a live session Binder or view it on Github. Overview # In the previous notebooks, we learned basic forms of indexing with Xarray, including positional and label-based indexing, datetime indexing, and nearest Dec 22, 2021 · Once the feature is available, you could create a specific xarray. © Copyright 2014-2018, xarray Developers. interp # DataArray. sel(self, indexers: Mapping [Hashable, Any] = None, method: str = None, tolerance=None, drop: bool = False, **indexers_kwargs: Any) → 'DataArray' ¶ Return a new DataArray whose data is given by selecting index labels along the specified dimension (s). sel Indexing Tutorial material on indexing with Xarray objects Indexing and Selecting Data Tutorial material on basics of indexing Oct 6, 2025 · The above example allowed us to visualize the data on a regular latitude-longitude grid. line() calls matplotlib. In contrast to Dataset. pyplot as plt import xarray as xr data = xr. Dataset objects which represent remote sensing images for the same grid over one year, but cover areas of different sizes: ds1: xarray. Jan 3, 2025 · The user guide provides in-depth information on the key concepts of Xarray with useful background information and explanation. Parameters: labels (mapping of hashable to Any) – Index labels to drop Feb 6, 2023 · MVCE confirmation Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray. 2 and lon Oct 1, 2025 · Ready to deepen your understanding of Xarray? Visit the user guide for detailed explanations of the data model, common computational patterns, and more. The above example shows the usage of slice for datetime indexing. New dimensions will be added at the end, and the corresponding coordinate variables will be combined into a MultiIndex. DatasetCoarsen DataArray. isel(indexers=None, drop=False, missing_dims='raise', **indexers_kwargs) [source] # Returns a new dataset with each array indexed along the specified dimension (s). It provides a high-level interface for manipulating and analyzing datasets that can be thought of as extensions of NumPy arrays. , 1-dimensional arrays of numbers Oct 6, 2025 · See also computation. ndarray or numpy-like array holding the array’s values dims: dimension names for each axis (e. , ('x', 'y', 'z')) coords: a dict-like container of arrays (coordinates) that label each point (e. drop_sel(dayofyear=60) But for non leap year this would drop the 1st of March. sel() will also select the nearest labels around a given range for a coordinate (or fill the first and/or last items with nan if the nearest elements are beyond a given tolerance). Oct 6, 2025 · You can run this notebook in a live session or view it on Github. ds. isel # Dataset. In most cases, xarray. Similar to Panda's loc and iloc methods, XArray provides sel and isel methods. Under the hood, this method is powered by using pandas’s powerful Index objects. xarray. Xarray offers extremely flexible indexing routines that combine the best features of NumPy and pandas for data selection. You may need to change the path to rasm. Index objects. values>180] -= 360 d = d. open_mfdataset with Dask: import xarray as xr # Specify the path to your netCDF files (can use a wildcard for multiple files) Mar 11, 2020 · This did not work correctly for me when using CMIP netCDF data. Dataset of monthly mean data and we want to calculate the seasonal average. Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result. Let's select the temperature anomany values for the last time step. As xarray objects can store coordinates corresponding to each dimension of an array, label-based Oct 19, 2023 · Xarray’s built-in support for label-based indexing (e. sel(method=None, tolerance=None, drop=False, **indexers) ¶ Returns a new dataset with each array indexed by tick labels along the specified dimension (s). isel() can be considered analogous to . Oct 6, 2025 · See also computation. isel methods are more convenient than . isel(). This allows us to fetch values based on the value of the coordinate, not the numerical index. rolling. Performs univariate or multivariate interpolation of a Dataset onto new coordinates, utilizing either NumPy or SciPy interpolation routines. In these cases, it is not useful to select with slice. DataArray) Oct 6, 2025 · Xarray can leverage metadata that follows the Climate and Forecast (CF) conventions if present. We have our coordinates in a GeoDataFrame, we can use Panda's to_xarray() method to convert the X and Y coordinates to a DataArray. drop_sel # Dataset. values[d['lon']. isel fails silently. Calculating Seasonal Averages from Time Series of Monthly Means # Author: Joe Hamman The data used for this example can be found in the xarray-data repository. Dataset. Mar 19, 2023 · I am just surprised that xarray developers added an example as introduction to xarray but then didnt show how to work with it. iloc[]. GRIB Data Example # GRIB format is commonly used to disseminate atmospheric model data. Return a new DataArray whose data is given by selecting index labels along the specified dimension (s). Return a new DataArray whose dataset is given by selecting index labels along the specified dimension (s). With xarray and the cfgrib engine, GRIB data can easily be analyzed and visualized. sel # Dataset. Nov 19, 2019 · FYI, in xarray, probably . Here are some examples for using Xarray with Dask at scale: Zonal averaging with the NOAA National Water Model CMIP6 Precipitation Frequency Analysis Using Dask + Cloud Optimized GeoTIFFs Find more examples at the Project Pythia cookbook gallery. open_dataset(name, cache=True, cache_dir=None, *, engine=None, **kws) [source] # Open a dataset from the online repository (requires internet). But replacing your ds. Whether you’re new to Xarray or a seasoned user we hope you’ll learn something new and get a head start on your own projects by Indexing and selecting data ¶ xarray offers extremely flexible indexing routines that combine the best features of NumPy and pandas for data selection. sel(lat=slice(50, 60), lon=slice(351, 3)) Of course, this returns an empty array, as 351>3. ARGO floats are autonomous robotic instruments that collect Temperature, Salinity, and Pressure data from the ocean. Parameters: labels (mapping of hashable to Any) – Index labels to drop Mar 20, 2025 · Quick overview # Here are some quick examples of what you can do with xarray. This method selects values from each array using its __getitem__ method, except this method does not require knowing the order of each array’s dimensions. sel(indexers=None, method=None, tolerance=None, drop=False, **indexers_kwargs) [source] # Return a new DataArray whose data is given by selecting index labels along the specified dimension (s). dropna() is a method in xarray that can be used to remove missing or null values from an xarray object. As xarray objects can store coordinates corresponding to each dimension of an array, label-based Oct 6, 2025 · For example, xarray. loc` attribute: . In contrast to DataArray. plot passing in the index and the array values as x and y, respectively. DataArray. Vectorized Indexing # Like numpy and pandas, xarray supports indexing many array elements at once in a vectorized manner. isel DataArray. To do Advanced Indexing # Learning Objectives # Orthogonal vs. Available datasets: "air_temperature": NCEP reanalysis subset "air_temperature_gradient": NCEP reanalysis subset with approximate x,y Reading and writing files # Xarray supports direct serialization and IO to several file formats, from simple Pickle files to the more flexible netCDF format (recommended). **chunks_kwargs ({dim: chunks, }, optional) – The keyword arguments form of chunks. To begin, import numpy, pandas and xarra Indexing and selecting data ¶ xarray offers extremely flexible indexing routines that combine the best features of NumPy and pandas for data selection. Oct 6, 2025 · Returns a new dataset with each array indexed by tick labels along the specified dimension (s). sel and . As xarray objects can store coordinates corresponding to each dimension of an array, label-based However, it is often much more powerful to use xarray’s . sel ¶ DataArray. Note that . This Xarray with Dask Arrays Xarray is an open source project and Python package that extends the labeled data functionality of Pandas to N-dimensional array-like datasets. Oct 6, 2025 · Return a new DataArray whose data is given by selecting index labels along the specified dimension (s). sel ¶ Dataset. isel(latitude = 200) will return a subset along the 200th latitude value. To do label based indexing, use the :py:attr:`~xarray. PandasIndex object, the query method of which simply calls the underlying pandas Index object's get_loc Overview Xarray is a powerful Python library designed for working with multi-dimensional labeled datasets, often used in fields such as climate science, oceanography, and remote sensing. It adds the lat and lon dimensions to time_bnds, lat_bnds and lon_bnds, potentially giving a larger file than when we started. This notebook shows common visualization issues encountered in xarray. ipython:: python da. where(~mask, drop=True) Jan 24, 2020 · I have data inside an xarray. In this example, we use real data from ocean profiling floats. Oct 6, 2025 · API reference # This page provides an auto-generated summary of xarray’s API. DataArray objects. sel(latitude=40, method=”nearest”)) and alignment operations relies on pandas. Jan 1, 2001 · Indexing and selecting data in xarray by coordinate value is typically done using the sel() method. As xarray objects can store coordinates corresponding to each dimension of an array, label-based sel(coordinate_name = coordinate_value): value selection — xarray syntax for selecting data based on its value in that dimension For example, we can call out the value of green in the top leftmost pixel of the image dataset. In most cases, Oct 6, 2025 · xarray. Complete example — the example is self-contained, including all data and the text of any traceback. pyplot. Index` under the hood, label based indexing is very fast. sel(latitude=26,longi Nov 9, 2021 · With drop_sel you need to give the exact value in the index: da. See also: What parts of xarray are considered public API? Top-level functions # Xarray Interpolation, Groupby, Resample, Rolling, and Coarsen In this lesson, we cover some more advanced aspects of xarray. nc") darmstadt = data. Because we use a :py:class:`pandas. sel() method can be used by itself in this case. Dataset Dimensions:time: 365 lat Jan 3, 2025 · A major use case for xarray is multi-dimensional time-series data. sel # DataArray. xarray ’s real potential comes with multidimensional data. XArray provides a very powerful way to select subsets of data, using similar framework as Pandas. Understand that there are many packages that build on top of xarray We’ll start by reviewing the various components of the Xarray data Jan 3, 2025 · Xarray’s built-in support for label-based indexing (e. Do not try to assign values when using any of the indexing methods isel or sel: Assigning values with the chained indexing using . open_dataset # xarray. It has several key properties: values: a numpy. By the end of the lesson, we will be able to: Understand the basic data structures in Xarray Inspect DataArray and Dataset objects. Xarray, a Python library for labeled multi-dimensional arrays, integrates with Dask to handle large raster data (HDF5, Zarr, NetCDF). They just switched to other simpler data structures and didnt really follow through with more code to show how to work with example they created. 20. This makes label based indexing Sep 4, 2025 · API reference # This page provides an auto-generated summary of xarray’s API. coarsen Reshaping via coarsen User guide describing coarsen() Coarsen large arrays User guide on block arrgragation coarsen() Windowed Computations Tutorial on windowed computation using coarsen() May 1, 2023 · In Python, I have two xarray. where command with cropped_ds = ds. Everything is explained in much more detail in the rest of the documentation. DataArray that I want to manipulate, however, it do not manage to change individual entries in the DataArray. the 'nearness' matching is handled by each index's query method; most indices in xarray are various types of Pandas indices wrapped by an xr. Indexing and selecting data # Xarray offers extremely flexible indexing routines that combine the best features of NumPy and pandas for data selection. array. sel() and . sel() method to use label-based indexing. Since DataArray dimensions have names, these methods allow you to specify which dimension to query. Dec 22, 2023 · Here’s an example of how you might use xarray. logical_and(da. Jan 3, 2025 · Indexing and selecting data # Xarray offers extremely flexible indexing routines that combine the best features of NumPy and pandas for data selection. ndarray, list, but not DataArray() or Variable Xarray in 45 minutes # In this lesson, we cover the basics of Xarray data structures. Xarray is particularly useful for geospatial data because it supports labeled xarray. isel, indexers for this method should use labels instead of integers. sortby(d['lon']) Oct 6, 2025 · xarray. sel(latitude = lat, longitude = lon, method = 'nearest') isel is used to access point by index, ie: ds_loc = ds. Examples of data which one might want organise in a grouped or hierarchical manner include: Simulation data at multiple resolutions, Observational data about the same system but from multiple different Feb 6, 2023 · MVCE confirmation Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray. sel(lat= Jan 26, 2022 · 4 xarray's selection algorithms do work for each dimension of the data independently. Xarray includes a large and growing library of domain-agnostic functions for advanced analytics and Oct 8, 2025 · xarray. Oct 4, 2024 · xarray is a Python package designed to work with multi-dimensional labeled data, particularly useful for geospatial data such as urban engineering, climate, traffic engineering, weather, and Oct 6, 2025 · xarray. 1. In a remote-sensing context, time Apr 13, 2024 · MVCE confirmation Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray. Built with Sphinx using a theme provided by Read the Docs. Returns a new dataset with each array indexed by tick labels along the specified dimension (s). To begin, import numpy, pandas and xarray using their customary abbreviations: Oct 6, 2025 · xarray. xarray (pronounced "ex-array", formerly known as xray) is an open source project and Python package that makes working with labelled multi-dimensional arrays simple, efficient, and fun! Jun 16, 2020 · Here is my code: import numpy as np import pandas as pd import matplotlib. PandasMultiIndex'>, **dim_kwargs) [source] # Stack any number of existing dimensions into a single new dimension. DataArray is xarray’s implementation of a labeled, multi-dimensional array. open_dataset(SomeFile) SlicedData = data. sel(latitude=40, method="nearest")) and alignment operations relies on pandas. phyc. To drop safely all 29th of Feb, I would probably use something like: mask = np. To begin, import numpy, pandas and xarray using their customary abbreviations: Why Hierarchical Data? # Many real-world datasets are composed of multiple differing components, and it can often be useful to think of these in terms of a hierarchy of related groups of data. So to make a line plot with blue triangles a matplotlib format string can be used: Working with time in xarray Products used: s2_l2a Keywords analysis; time series, data used; sentinel-2, data methods; groupby,:index: data methods; nearest, index: data methods; interpolating, data methods; resampling, data methods; compositing Background Time series data is a series of data points usually captured at successively spaced points in time. loc[] and . loc["2000-01-01":"2000-01-02", "IA"] In this example, the selected is a subpart of the array in the range '2000-01-01':'2000-01-02' along Jan 3, 2025 · API reference # This page provides an auto-generated summary of xarray’s API. These features, together with Pandas’ many useful routines for all kinds of data munging and analysis, have made Pandas one of the most popular Examples # If you’re new to using Xarray with Dask, we recommend the Xarray + Dask Tutorial. A boolean mask refers to a binary array or a boolean-valued (True / False) array that is Aug 24, 2025 · 4. Pointwise indexing in Xarray to extract data at a collection of points. 5nj roq emfdd arp qiqw mz quqamkc moir7z suf0t 0bzwa