tablesample¶

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tablesample(values: dict = {}, 
            dtype: dict = {},
            count: int = 0, 
            offset: int = 0,
            percent: dict = {})

The tablesample is the transition from 'Big Data' to 'Small Data'. This object was created to have a nice way of displaying the results and to not have any dependency to any other module. It stores the aggregated result in memory and has some useful method to transform it to pandas.DataFrame or vDataFrame.

Parameters¶

Name	Type	Optional	Description
values	dict	✓	Dictionary of columns (keys) and their values. The dictionary must be similar to the following one: {"column1": [val1, ..., valm], ... "columnk": [val1, ..., valm]}
dtype	dict	✓	Columns data types.
count	int	✓	Number of elements if we had to load the entire dataset. It is used only for rendering purposes.
offset	int	✓	Number of elements which had been skipped if we had to load the entire dataset. It is used only for rendering purposes.
percent	dict	✓	Dictionary of missing values (Used to display the percent bars)

Attributes¶

The tablesample attributes are the same than the parameters.

Methods¶

Name	Description
transpose	Transposes the tablesample.
to_list	Converts the tablesample to a list.
to_numpy	Converts the tablesample to a numpy array.
to_pandas	Converts the tablesample to a pandas DataFrame.
to_sql	Generates the SQL query associated with the tablesample.
to_vdf	Converts the tablesample to a vDataFrame.

Example¶

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from verticapy.utilities import *
dataset = tablesample(values = {"index": [0, 1, 2],
                                "name": ["Badr", "Fouad", "Colin"],
                                "first_name": ["Ouali", "Teban", "Mahony"]})
display(dataset)

	name	first_name
0	Badr	Ouali
1	Fouad	Teban
2	Colin	Mahony

Rows: 1-3 | Columns: 3