You can run this notebook in a live session or view it on Github.
Visualization Gallery¶
This notebook shows common visualization issues encountered in xarray.
[1]:
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
import xarray as xr
%matplotlib inline
Load example dataset:
[2]:
ds = xr.tutorial.load_dataset("air_temperature")
---------------------------------------------------------------------------
PermissionError Traceback (most recent call last)
File /usr/lib/python3/dist-packages/pooch/utils.py:262, in make_local_storage(path, env)
258 if action == "create":
259 # When running in parallel, it's possible that multiple jobs will
260 # try to create the path at the same time. Use exist_ok to avoid
261 # raising an error.
--> 262 os.makedirs(path, exist_ok=True)
263 else:
File /usr/lib/python3.13/os.py:217, in makedirs(name, mode, exist_ok)
216 try:
--> 217 makedirs(head, exist_ok=exist_ok)
218 except FileExistsError:
219 # Defeats race condition when another thread created the path
File /usr/lib/python3.13/os.py:217, in makedirs(name, mode, exist_ok)
216 try:
--> 217 makedirs(head, exist_ok=exist_ok)
218 except FileExistsError:
219 # Defeats race condition when another thread created the path
File /usr/lib/python3.13/os.py:227, in makedirs(name, mode, exist_ok)
226 try:
--> 227 mkdir(name, mode)
228 except OSError:
229 # Cannot rely on checking for EEXIST, since the operating system
230 # could give priority to other errors like EACCES or EROFS
PermissionError: [Errno 13] Permission denied: '/sbuild-nonexistent'
The above exception was the direct cause of the following exception:
PermissionError Traceback (most recent call last)
Cell In[2], line 1
----> 1 ds = xr.tutorial.load_dataset("air_temperature")
File /usr/lib/python3/dist-packages/xarray/tutorial.py:213, in load_dataset(*args, **kwargs)
176 def load_dataset(*args, **kwargs) -> Dataset:
177 """
178 Open, load into memory, and close a dataset from the online repository
179 (requires internet).
(...)
211 load_dataset
212 """
--> 213 with open_dataset(*args, **kwargs) as ds:
214 return ds.load()
File /usr/lib/python3/dist-packages/xarray/tutorial.py:165, in open_dataset(name, cache, cache_dir, engine, **kws)
162 downloader = pooch.HTTPDownloader(headers=headers)
164 # retrieve the file
--> 165 filepath = pooch.retrieve(
166 url=url, known_hash=None, path=cache_dir, downloader=downloader
167 )
168 ds = _open_dataset(filepath, engine=engine, **kws)
169 if not cache:
File /usr/lib/python3/dist-packages/pooch/core.py:227, in retrieve(url, known_hash, fname, path, processor, downloader, progressbar)
222 action, verb = download_action(full_path, known_hash)
224 if action in ("download", "update"):
225 # We need to write data, so create the local data directory if it
226 # doesn't already exist.
--> 227 make_local_storage(path)
229 get_logger().info(
230 "%s data from '%s' to file '%s'.",
231 verb,
232 url,
233 str(full_path),
234 )
236 if downloader is None:
File /usr/lib/python3/dist-packages/pooch/utils.py:276, in make_local_storage(path, env)
272 if env is not None:
273 message.append(
274 f"Use environment variable '{env}' to specify a different location."
275 )
--> 276 raise PermissionError(" ".join(message)) from error
PermissionError: [Errno 13] Permission denied: '/sbuild-nonexistent' | Pooch could not create data cache folder '/sbuild-nonexistent/.cache/xarray_tutorial_data'. Will not be able to download data files.
Multiple plots and map projections¶
Control the map projection parameters on multiple axes
This example illustrates how to plot multiple maps and control their extent and aspect ratio.
For more details see this discussion on github.
[3]:
air = ds.air.isel(time=[0, 724]) - 273.15
# This is the map projection we want to plot *onto*
map_proj = ccrs.LambertConformal(central_longitude=-95, central_latitude=45)
p = air.plot(
transform=ccrs.PlateCarree(), # the data's projection
col="time",
col_wrap=1, # multiplot settings
aspect=ds.dims["lon"] / ds.dims["lat"], # for a sensible figsize
subplot_kws={"projection": map_proj},
) # the plot's projection
# We have to set the map's options on all axes
for ax in p.axes.flat:
ax.coastlines()
ax.set_extent([-160, -30, 5, 75])
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
Cell In[3], line 1
----> 1 air = ds.air.isel(time=[0, 724]) - 273.15
3 # This is the map projection we want to plot *onto*
4 map_proj = ccrs.LambertConformal(central_longitude=-95, central_latitude=45)
NameError: name 'ds' is not defined
Centered colormaps¶
Xarray’s automatic colormaps choice
[4]:
air = ds.air.isel(time=0)
f, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(8, 6))
# The first plot (in kelvins) chooses "viridis" and uses the data's min/max
air.plot(ax=ax1, cbar_kwargs={"label": "K"})
ax1.set_title("Kelvins: default")
ax2.set_xlabel("")
# The second plot (in celsius) now chooses "BuRd" and centers min/max around 0
airc = air - 273.15
airc.plot(ax=ax2, cbar_kwargs={"label": "°C"})
ax2.set_title("Celsius: default")
ax2.set_xlabel("")
ax2.set_ylabel("")
# The center doesn't have to be 0
air.plot(ax=ax3, center=273.15, cbar_kwargs={"label": "K"})
ax3.set_title("Kelvins: center=273.15")
# Or it can be ignored
airc.plot(ax=ax4, center=False, cbar_kwargs={"label": "°C"})
ax4.set_title("Celsius: center=False")
ax4.set_ylabel("")
# Make it nice
plt.tight_layout()
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
Cell In[4], line 1
----> 1 air = ds.air.isel(time=0)
3 f, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(8, 6))
5 # The first plot (in kelvins) chooses "viridis" and uses the data's min/max
NameError: name 'ds' is not defined
Control the plot’s colorbar¶
Use cbar_kwargs
keyword to specify the number of ticks. The spacing
kwarg can be used to draw proportional ticks.
[5]:
air2d = ds.air.isel(time=500)
# Prepare the figure
f, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(14, 4))
# Irregular levels to illustrate the use of a proportional colorbar
levels = [245, 250, 255, 260, 265, 270, 275, 280, 285, 290, 310, 340]
# Plot data
air2d.plot(ax=ax1, levels=levels)
air2d.plot(ax=ax2, levels=levels, cbar_kwargs={"ticks": levels})
air2d.plot(
ax=ax3, levels=levels, cbar_kwargs={"ticks": levels, "spacing": "proportional"}
)
# Show plots
plt.tight_layout()
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
Cell In[5], line 1
----> 1 air2d = ds.air.isel(time=500)
3 # Prepare the figure
4 f, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(14, 4))
NameError: name 'ds' is not defined
Multiple lines from a 2d DataArray¶
Use xarray.plot.line
on a 2d DataArray to plot selections as multiple lines.
See plotting.multiplelines
for more details.
[6]:
air = ds.air - 273.15 # to celsius
# Prepare the figure
f, (ax1, ax2) = plt.subplots(1, 2, figsize=(8, 4), sharey=True)
# Selected latitude indices
isel_lats = [10, 15, 20]
# Temperature vs longitude plot - illustrates the "hue" kwarg
air.isel(time=0, lat=isel_lats).plot.line(ax=ax1, hue="lat")
ax1.set_ylabel("°C")
# Temperature vs time plot - illustrates the "x" and "add_legend" kwargs
air.isel(lon=30, lat=isel_lats).plot.line(ax=ax2, x="time", add_legend=False)
ax2.set_ylabel("")
# Show
plt.tight_layout()
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
Cell In[6], line 1
----> 1 air = ds.air - 273.15 # to celsius
3 # Prepare the figure
4 f, (ax1, ax2) = plt.subplots(1, 2, figsize=(8, 4), sharey=True)
NameError: name 'ds' is not defined