bigframes.streaming.StreamingDataFrame#

class bigframes.streaming.StreamingDataFrame(df: DataFrame, *, create_key=0)[source]#

Two-dimensional, size-mutable, potentially heterogeneous tabular data.

Data structure also contains labeled axes (rows and columns). Arithmetic operations align on both row and column labels. Can be thought of as a dict-like container for Series objects. The primary pandas data structure.

Note

The bigframes.streaming module is a preview feature, and subject to change.

Currently only supports basic projection, filtering and preview operations.

__getitem__(*args, **kwargs)[source]#

Gets the specified column(s) from the StreamingDataFrame.

Parameters:

key (index) Index or list of indices. It can be a column label, a list of column labels, a Series of booleans or a pandas Index of desired column labels

Returns:

Value(s) at the requested index(es).

Return type:

bigframes.pandas.Series or Any

__repr__(*args, **kwargs)[source]#

Converts a StreamingDataFrame to a string. Calls to_pandas.

Only represents the first bigframes.options.display.max_rows.

__setitem__(*args, **kwargs)[source]#

Modify or insert a column into the StreamingDataFrame.

Note

This does not modify the original table the StreamingDataFrame was derived from.

Parameters:

• key (column index) It can be a new column to be inserted, or an existing column to be modified.

• value (scalar, Sequence, StreamingDataFrame, or Series) Value to be assigned to the column

rename(*args, **kwargs)[source]#

Rename columns.

Dict values must be unique (1-to-1). Labels not contained in a dict will be left as-is. Extra labels listed dont throw an error.

Parameters:

• columns (Mapping) Dict-like from old column labels to new column labels.

• inplace (bool) Default False. Whether to modify the StreamingDataFrame rather than creating a new one.

Returns:

StreamingDataFrame with the renamed axis labels or None if inplace=True.

Return type:

bigframes.pandas.DataFrame | None

Raises:

KeyError If any of the labels is not found.