"""
HoloViews makes data analysis and visualization simple
======================================================
HoloViews lets you focus on what you are trying to explore and convey, not on
the process of plotting.
HoloViews
- supports a wide range of data sources including Pandas, Dask, XArray
Rapids cuDF, Streamz, Intake, Geopandas, NetworkX and Ibis.
- supports the plotting backends Bokeh (default), Matplotlib and Plotly.
- allows you to drop into the rest of the
HoloViz ecosystem when more power or flexibility is needed.
For basic data exploration we recommend using the higher level hvPlot package,
which provides the familiar Pandas `.plot` api. You can drop into HoloViews
when needed.
To learn more check out https://holoviews.org/. To report issues or contribute
go to https://github.com/holoviz/holoviews. To join the community go to
https://discourse.holoviz.org/.
How to use HoloViews in 3 simple steps
--------------------------------------
Work with the data source you already know and ❤️
>>> import pandas as pd
>>> station_info = pd.read_csv('https://raw.githubusercontent.com/holoviz/holoviews/main/examples/assets/station_info.csv')
Import HoloViews and configure your plotting backend
>>> import holoviews as hv
>>> hv.extension('bokeh')
Annotate your data
>>> scatter = (
... hv.Scatter(station_info, kdims='services', vdims='ridership')
... .redim(
... services=hv.Dimension("services", label='Services'),
... ridership=hv.Dimension("ridership", label='Ridership'),
... )
... .opts(size=10, color="red", responsive=True)
... )
>>> scatter
In a notebook this will display a nice scatter plot.
Note that the `kdims` (The key dimension(s)) represents the independent
variable(s) and the `vdims` (value dimension(s)) the dependent variable(s).
For more check out https://holoviews.org/getting_started/Introduction.html
How to get help
---------------
You can understand the structure of your objects by printing them.
>>> print(scatter)
:Scatter [services] (ridership)
You can get extensive documentation using `hv.help`.
>>> hv.help(scatter)
In a notebook or ipython environment the usual
- `help` and `?` will provide you with documentation.
- `TAB` and `SHIFT+TAB` completion will help you navigate.
To ask the community go to https://discourse.holoviz.org/.
To report issues go to https://github.com/holoviz/holoviews.
"""
import os
import sys
import param
__version__ = str(param.version.Version(fpath=__file__, archive_commit="$Format:%h$",
reponame="holoviews"))
from . import util # noqa (API import)
from .core import archive, config # noqa (API import)
from .core.boundingregion import BoundingBox # noqa (API import)
from .core.dimension import Dimension # noqa (API import)
from .core.element import Element, Collator # noqa (API import)
from .core.layout import (Layout, NdLayout, Empty, # noqa (API import)
AdjointLayout)
from .core.ndmapping import NdMapping # noqa (API import)
from .core.options import (Options, Store, Cycle, # noqa (API import)
Palette, StoreOptions)
from .core.overlay import Overlay, NdOverlay # noqa (API import)
from .core.spaces import (HoloMap, Callable, DynamicMap, # noqa (API import)
GridSpace, GridMatrix)
from .operation import Operation # noqa (API import)
from .element import *
from .element import __all__ as elements_list
from .selection import link_selections # noqa (API import)
from .util import (extension, renderer, output, opts, # noqa (API import)
render, save)
from .util.transform import dim # noqa (API import)
from .util.warnings import HoloviewsDeprecationWarning, HoloviewsUserWarning # noqa: F401
from .util._versions import show_versions # noqa: F401
# Suppress warnings generated by NumPy in matplotlib
# Expected to be fixed in next matplotlib release
import warnings
warnings.filterwarnings("ignore",
message="elementwise comparison failed; returning scalar instead")
if "IPython" in sys.modules:
from .ipython import notebook_extension
extension = notebook_extension
else:
class notebook_extension(param.ParameterizedFunction):
def __call__(self, *args, **kwargs):
raise Exception("Jupyter notebook not available: use hv.extension instead.")
if '_pyodide' in sys.modules:
from .pyodide import in_jupyterlite, pyodide_extension
# The notebook_extension is needed inside jupyterlite,
# so the override is only done if we are not inside jupyterlite.
if in_jupyterlite():
extension.inline = False
else:
extension = pyodide_extension
del pyodide_extension, in_jupyterlite
# A single holoviews.rc file may be executed if found.
for rcfile in [os.environ.get("HOLOVIEWSRC", ''),
os.path.abspath(os.path.join(os.path.split(__file__)[0],
'..', 'holoviews.rc')),
"~/.holoviews.rc",
"~/.config/holoviews/holoviews.rc"]:
filename = os.path.expanduser(rcfile)
if os.path.isfile(filename):
with open(filename, encoding='utf8') as f:
code = compile(f.read(), filename, 'exec')
try:
exec(code)
except Exception as e:
print(f"Warning: Could not load {filename!r} [{str(e)!r}]")
del f, code
break
del filename
[docs]def help(obj, visualization=True, ansi=True, backend=None,
recursive=False, pattern=None):
"""
Extended version of the built-in help that supports parameterized
functions and objects. A pattern (regular expression) may be used to
filter the output and if recursive is set to True, documentation for
the supplied object is shown. Note that the recursive option will
only work with an object instance and not a class.
If ansi is set to False, all ANSI color
codes are stripped out.
"""
backend = backend if backend else Store.current_backend
info = Store.info(obj, ansi=ansi, backend=backend, visualization=visualization,
recursive=recursive, pattern=pattern, elements=elements_list)
msg = ("\nTo view the visualization options applicable to this "
"object or class, use:\n\n"
" holoviews.help(obj, visualization=True)\n\n")
if info:
print((msg if visualization is False else '') + info)
else:
import pydoc
pydoc.help(obj)
def __getattr__(name):
if name == "annotate":
# Lazy loading Panel
from .annotators import annotate
return annotate
raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
del os, rcfile, warnings