NestedFrame

Constructor

NestedFrame(*args, **kwargs)

A Pandas Dataframe extension with support for nested structure.

Helpful Properties

NestedFrame.nested_columns	retrieves the base column names for all nested dataframes
NestedFrame.base_columns	Returns the list of base (non-nested) column names
NestedFrame.all_columns	returns a dictionary of columns for each base/nested dataframe

Nesting

NestedFrame.join_nested(obj, name, *[, how, ...])	Packs input object to a nested column and adds it to the NestedFrame
NestedFrame.nest_lists(columns, name)	Creates a new NestedFrame where the specified list-value columns are packed into a nested column.
NestedFrame.from_flat(df, base_columns[, ...])	Creates a NestedFrame with base and nested columns from a flat dataframe.
NestedFrame.from_lists(df[, base_columns, ...])	Creates a NestedFrame with base and nested columns from a flat dataframe.

Extended Pandas.DataFrame Interface

Note

The NestedFrame extends the Pandas.DataFrame interface, so all methods of Pandas.DataFrame are available. The following methods are a mix of newly added methods and extended methods from Pandas DataFrame to support NestedFrame functionality. Please reference the Pandas documentation for more information. https://pandas.pydata.org/docs/reference/frame.html

NestedFrame.get_subcolumns([nested_columns])	Returns a set of all subcolumn names from a set of nested columns, including dot notation
NestedFrame.eval(expr, *[, inplace])	Evaluate a string describing operations on NestedFrame columns.
NestedFrame.query(expr, *[, inplace])	Query the columns of a NestedFrame with a boolean expression.
NestedFrame.dropna(*, axis, , ] = 0, how, , ...)	Remove missing values for one layer of the NestedFrame.
NestedFrame.sort_values(by, *[, axis, ...])	Sort by the values along either axis.
NestedFrame.map_rows(func[, columns, ...])	Takes a function and applies it to each top-level row of the NestedFrame.
NestedFrame.drop([labels, axis, index, ...])	Drop specified labels from rows or columns.
NestedFrame.min([exclude_nest, numeric_only])	Return the minimum value of each column as a series, including nested columns with prefix to indicate the source column.
NestedFrame.max([exclude_nest, numeric_only])	Return the maximum value of each column as a series, including nested columns with prefix to indicate the source column.
NestedFrame.describe([exclude_nest, ...])	Generate descriptive statistics, including nested columns with prefix to indicate the source.
NestedFrame.explode(column[, ignore_index])	Transform each element of a list-like base column to a row, replicating index values.
NestedFrame.fillna([value, axis, inplace, limit])	Fill NA/NaN values using the specified method for base and nested columns.

I/O

NestedFrame.to_parquet(path[, large_list])	Creates parquet file(s) with the data of a NestedFrame, either as a single parquet file where each nested dataset is packed into its own column or as an individual parquet file for each layer.
NestedFrame.to_pandas([list_struct, large_list])	Convert to an ordinal pandas DataFrame, with no NestedDtype series.
read_parquet(data[, columns, ...])	Load a parquet object from a file path into a NestedFrame.
from_pyarrow(table[, reject_nesting, ...])	Load a pyarrow Table object into a NestedFrame.