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Update "PyData Ecosystem" to "Scientific Python Ecosystem" (#3447)
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README.md

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- Build a Pythonic API for GMT.
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- Interface with the GMT C API directly using ctypes (no system calls).
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- Support for rich display in the Jupyter notebook.
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- Integration with the [PyData ecosystem](https://pydata.org/): `numpy.ndarray` or `pandas.DataFrame` for
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data tables, `xarray.DataArray` for grids, and `geopandas.GeoDataFrame` for geographical data.
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- Integration with the [scientific Python ecosystem](https://scientific-python.org/): `numpy.ndarray` or
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`pandas.DataFrame` for data tables, `xarray.DataArray` for grids, and `geopandas.GeoDataFrame` for geographical data.
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## Quickstart
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examples/tutorials/advanced/date_time_charts.py

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#
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# In this example, instead of using a list of :class:`pandas.DatetimeIndex` objects,
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# ``x`` is initialized as an :class:`xarray.DataArray` object. This object provides a
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# wrapper around regular PyData formats. It also allows the data to have labeled
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# dimensions while supporting operations that use various pieces of metadata. The
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# following code uses :func:`pandas.date_range` to fill the DataArray with data, but
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# this is not essential for the creation of a valid DataArray.
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# wrapper around numpy ndarrays. It also allows the data to have labeled dimensions
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# while supporting operations that use various pieces of metadata. The following code
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# uses :func:`pandas.date_range` to fill the DataArray with data, but this is not
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# essential for the creation of a valid DataArray.
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x = xr.DataArray(data=pd.date_range(start="2020-01-01", periods=4, freq="Q"))
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y = [4, 7, 5, 6]

pygmt/__init__.py

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publication-quality maps and figures. It provides a Pythonic interface for the Generic
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Mapping Tools (GMT), a command-line program widely used across the Earth, Ocean, and
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Planetary sciences and beyond. Besides making GMT more accessible to new users, PyGMT
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aims to provide integration with the PyData ecosystem as well as support for rich
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display in Jupyter notebooks.
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aims to provide integration with the scientific Python ecosystem as well as support for
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rich display in Jupyter notebooks.
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Main Features
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-------------

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