Pandas¶
-
class
openpnm.io.
Pandas
[source]¶ Bases:
openpnm.io.GenericIO.GenericIO
Combines all data arrays into a Pandas DataFrame object
The structure of a DataFrame is a very close match to OpenPNMs data storage. Each key becomes a column header in the Dataframe, and each pore or throat entry becomes a row.
Limitations of the DataFrame are the inability to have multidimensional data in a single column. The methods on a DataFrame are also oriented towards time-series data.
Nonetheless, Pandas offers many useful features such as performing statistical analysis on property. DataFrames also offer many options for exporting to other file formats, so if a format is not yet supported by OpenPNM, this could be an solution.
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classmethod
export_data
(network=None, phases=[], join=False, delim=' | ')[source]¶ Convert the Network (and optionally Phase) data to Pandas DataFrames.
- Parameters
network (OpenPNM Network Object) – The network containing the data to be stored
phases (list of OpenPNM Phase Objects) – The data on each supplied phase will be added to DataFrame
join (boolean) – If
False
(default), two DataFrames are returned with pore data in one, and throat data in the other. IfTrue
the pore and throat data are combined into a single DataFrame. This can be problematic as it will put NaNs into all the pore columns which are shorter than the throat columns.
- Returns
Pandas
DataFrame
object containing property and label data in eachcolumn. If
join
was False (default) the two DataFrames arereturned i a named tuple, or else a single DataFrame with pore and
throat data in the same file, despite the column length being
different.
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classmethod