Class DataFrameUtils

class gpudb\_dataframe.DataFrameUtils

classmethod sql\_to\_df(db: GPUdb, sql: str, sql\_params: list = \[], batch\_size: int = 5000, sql\_opts: dict = {"{"}{"}"}, show\_progress: bool = False) → DataFrame | None

Create a pd.Dataframe from the results of a SQL query.

Parameters

db (GPUdb) –

a GPUdb instance

sql (str) –

the SQL query

sql\_params (list) –

the query parameters. Defaults to None.

batch\_size (int) –

the batch size for the SQL execution results. Defaults to BATCH\_SIZE.

sql\_opts (dict) –

the SQL options as a dict. Defaults to None.

show\_progress (bool) –

whether to display progress or not. Defaults to False.

Raises

GPUdbException –

If the SQL query failed

Returns

pd.DataFrame –

a Pandas pd.Dataframe or None if the SQL query has returned no results

classmethod table\_to\_df(db: GPUdb, table\_name: str, batch\_size: int = 5000, show\_progress: bool = False) → DataFrame | None

Convert a Kinetica table into a pd.Dataframe and load data into it.

Parameters

db (GPUdb) –

a GPUdb instance

table\_name (str) –

name of the Kinetica table

batch\_size (int) –

the batch size for the SQL execution results. Defaults to BATCH\_SIZE.

show\_progress (bool) –

whether to display progress or not. Defaults to False.

Returns

pd.Dataframe –

Returns a Pandas pd.Dataframe created from the Kinetica table

classmethod table\_type\_as\_df(gpudb\_table: GPUdbTable) → DataFrame

Convert the type schema (column list) of a GPUdbTable into a pd.Dataframe.

Parameters

gpudb\_table (GPUdbTable) –

a GPUdbTable instance

Returns

pd.DataFrame –

a Pandas pd.Dataframe created by analyzing the table column types

classmethod df\_to\_table(df: DataFrame, db: GPUdb, table\_name: str, column\_types: dict = {"{"}{"}"}, clear\_table: bool = False, create\_table: bool = True, load\_data: bool = True, show\_progress: bool = False, batch\_size: int = 5000, \*\*kwargs) → GPUdbTable

Load a pd.Dataframe into a table; optionally dropping any existing table, creating it if it doesn’t exist, and loading data into it; and then returning a GPUdbTable reference to the table.

Parameters

df (pd.DataFrame) –

The Pandas pd.Dataframe to load into a table

db (GPUdb) –

GPUdb instance

table\_name (str) –

Name of the target Kinetica table for the pd.Dataframe loading

column\_types (dict) –

Optional Kinetica column properties to apply to the column type definitions inferred from the pd.Dataframe; map of column name to a list of column properties for that column, excluding the inferred base type. Defaults to empty map. For example:

``` { "middle_name": [ 'char64', 'nullable' ], "state": [ 'char2', 'dict' ] } ```

clear\_table (bool) –

Whether to drop an existing table of the same name or not before creating this one. Defaults to False.

create\_table (bool) –

Whether to create the table if it doesn’t exist or not. Defaults to True.

load\_data (bool) –

Whether to load data into the target table or not. Defaults to True.

show\_progress (bool) –

Whether to show progress of the operation on the console. Defaults to False.

batch\_size (int) –

The number of records at a time to load into the target table. Defaults to BATCH\_SIZE.

Raises

GPUdbException –

If the pd.Dataframe is empty, the table doesn’t exist and create\_table is False, or the data ingest fails

Returns

GPUdbTable –

a GPUdbTable instance created from the pd.Dataframe passed in

classmethod df\_insert\_into\_table(df: DataFrame, gpudb\_table: GPUdbTable, batch\_size: int = 5000, show\_progress: bool = False) → int

Load a Pandas pd.Dataframe into a GPUdbTable.

Parameters

df (pd.Dataframe) –

a Pandas pd.Dataframe

gpudb\_table (GPUdbTable) –

a GPUdbTable instance

batch\_size (int) –

a batch size to use for loading data into the table. Defaults to BATCH\_SIZE.

show\_progress (bool) –

whether to show progress of the operation. Defaults to False.

Raises

GPUdbException –

If the data ingest fails

Returns

int –

the number of rows of the pd.Dataframe actually inserted into the Kinetica table