Update "PyData Ecosystem" to "Scientific Python Ecosystem" (#3447)

README.md

@@ -45,8 +45,8 @@ widely used across the Earth, Ocean, and Planetary sciences and beyond.
 - Build a Pythonic API for GMT.
 - Interface with the GMT C API directly using ctypes (no system calls).
 - Support for rich display in the Jupyter notebook.
-- Integration with the [PyData ecosystem](https://pydata.org/): `numpy.ndarray` or `pandas.DataFrame` for
-  data tables, `xarray.DataArray` for grids, and `geopandas.GeoDataFrame` for geographical data.
+- Integration with the [scientific Python ecosystem](https://scientific-python.org/): `numpy.ndarray` or
+  `pandas.DataFrame` for data tables, `xarray.DataArray` for grids, and `geopandas.GeoDataFrame` for geographical data.
 
 ## Quickstart
 

examples/tutorials/advanced/date_time_charts.py

@@ -191,10 +191,10 @@
 #
 # In this example, instead of using a list of :class:`pandas.DatetimeIndex` objects,
 # ``x`` is initialized as an :class:`xarray.DataArray` object. This object provides a
-# wrapper around regular PyData formats. It also allows the data to have labeled
-# dimensions while supporting operations that use various pieces of metadata. The
-# following code uses :func:`pandas.date_range` to fill the DataArray with data, but
-# this is not essential for the creation of a valid DataArray.
+# wrapper around numpy ndarrays. It also allows the data to have labeled dimensions
+# while supporting operations that use various pieces of metadata. The following code
+# uses :func:`pandas.date_range` to fill the DataArray with data, but this is not
+# essential for the creation of a valid DataArray.
 
 x = xr.DataArray(data=pd.date_range(start="2020-01-01", periods=4, freq="Q"))
 y = [4, 7, 5, 6]

pygmt/__init__.py

@@ -3,8 +3,8 @@
 publication-quality maps and figures. It provides a Pythonic interface for the Generic
 Mapping Tools (GMT), a command-line program widely used across the Earth, Ocean, and
 Planetary sciences and beyond. Besides making GMT more accessible to new users, PyGMT
-aims to provide integration with the PyData ecosystem as well as support for rich
-display in Jupyter notebooks.
+aims to provide integration with the scientific Python ecosystem as well as support for
+rich display in Jupyter notebooks.
 
 Main Features
 -------------