Logo Iris 1.12

Previous topic

iris.palette

Next topic

iris.plot

This Page

iris.pandas

Provide conversion to and from Pandas data structures.

See also: http://pandas.pydata.org/

In this module:

iris.pandas.as_cube(pandas_array, copy=True, calendars=None)

Convert a Pandas array into an Iris cube.

Args:

  • pandas_array - A Pandas Series or DataFrame.

Kwargs:

  • copy - Whether to make a copy of the data.

    Defaults to True.

  • calendars - A dict mapping a dimension to a calendar.

    Required to convert datetime indices/columns.

Example usage:

as_cube(series, calendars={0: cf_units.CALENDAR_360_DAY})
as_cube(data_frame, calendars={1: cf_units.CALENDAR_GREGORIAN})

Note

This function will copy your data by default.

↑ top ↑

iris.pandas.as_data_frame(cube, copy=True)

Convert a 2D cube to a Pandas DataFrame.

Args:

  • cube - The cube to convert to a Pandas DataFrame.

Kwargs:

  • copy - Whether to make a copy of the data.

    Defaults to True. Must be True for masked data and some data types (see notes below).

Note

This function will copy your data by default. If you have a large array that cannot be copied, make sure it is not masked and use copy=False.

Note

Pandas will sometimes make a copy of the array, for example when creating from an int32 array. Iris will detect this and raise an exception if copy=False.

↑ top ↑

iris.pandas.as_series(cube, copy=True)

Convert a 1D cube to a Pandas Series.

Args:

  • cube - The cube to convert to a Pandas Series.

Kwargs:

  • copy - Whether to make a copy of the data.

    Defaults to True. Must be True for masked data.

Note

This function will copy your data by default. If you have a large array that cannot be copied, make sure it is not masked and use copy=False.