Help on function read_csv in module verticapy.utilities:

read_csv(path:str, schema:str='', table_name:str='', sep:str=',', header:bool=True, header_names:list=[], dtype:dict={}, na_rep:str='', quotechar:str='"', escape:str='\x17', genSQL:bool=False, parse_nrows:int=-1, insert:bool=False, temporary_table:bool=False, temporary_local_table:bool=True, gen_tmp_table_name:bool=True, ingest_local:bool=True)
    ---------------------------------------------------------------------------
    Ingests a CSV file using flex tables.
    
    Parameters
    ----------
    path: str
            Absolute path where the CSV file is located.
    schema: str, optional
            Schema where the CSV file will be ingested.
    table_name: str, optional
            The final relation/table name. If unspecified, the the name is set to the 
        name of the file or parent directory.
    sep: str, optional
            Column separator.
    header: bool, optional
            If set to False, the parameter 'header_names' will be to use to name the 
            different columns.
    header_names: list, optional
            List of the columns names.
    dtype: dict, optional
        Dictionary of the user types. Providing a dictionary can increase 
        ingestion speed and precision; instead of parsing the file to guess 
        the different types, VerticaPy will use the input types.
    na_rep: str, optional
            Missing values representation.
    quotechar: str, optional
            Char which is enclosing the str values.
    escape: str, optional
            Separator between each record.
    genSQL: bool, optional
            If set to True, the SQL code for creating the final table will be 
            generated but not executed. It is a good way to change the final
            relation types or to customize the data ingestion.
    parse_nrows: int, optional
            If this parameter is greater than 0. A new file of 'parse_nrows' lines
            will be created and ingested first to identify the data types. It will be
            then dropped and the entire file will be ingested. The data types identification
            will be less precise but this parameter can make the process faster if the
            file is heavy.
    insert: bool, optional
            If set to True, the data will be ingested to the input relation. Be sure
            that your file has a header corresponding to the name of the relation
            columns, otherwise ingestion will fail.
    temporary_table: bool, optional
        If set to True, a temporary table will be created.
    temporary_local_table: bool, optional
        If set to True, a temporary local table will be created. The parameter 'schema'
        must be empty, otherwise this parameter is ignored.
    gen_tmp_table_name: bool, optional
        Sets the name of the temporary table. This parameter is only used when the 
        parameter 'temporary_local_table' is set to True and if the parameters 
        "table_name" and "schema" are unspecified.
    ingest_local: bool, optional
        If set to True, the file will be ingested from the local machine.
    
    Returns
    -------
    vDataFrame
            The vDataFrame of the relation.
    
    See Also
    --------
    read_json : Ingests a JSON file into the Vertica database.

The table "public"."iris" has been successfully created.

CREATE TABLE "public"."iris"("Id" Integer, "SepalLengthCm" Numeric(5,2), "SepalWidthCm" Numeric(5,2), "PetalLengthCm" Numeric(5,2), "PetalWidthCm" Numeric(5,2), "Species" Varchar(30))
COPY "public"."iris"("Id", "SepalLengthCm", "SepalWidthCm", "PetalLengthCm", "PetalWidthCm", "Species") FROM {} DELIMITER ',' NULL '' ENCLOSED BY '"' ESCAPE AS '' SKIP 1

Help on function read_json in module verticapy.utilities:

read_json(path:str, schema:str='', table_name:str='', usecols:list=[], new_name:dict={}, insert:bool=False, temporary_table:bool=False, temporary_local_table:bool=True, gen_tmp_table_name:bool=True, ingest_local:bool=True)
    ---------------------------------------------------------------------------
    Ingests a JSON file using flex tables.
    
    Parameters
    ----------
    path: str
            Absolute path where the JSON file is located.
    schema: str, optional
            Schema where the JSON file will be ingested.
    table_name: str, optional
            Final relation name.
    usecols: list, optional
            List of the JSON parameters to ingest. The other ones will be ignored. If
            empty all the JSON parameters will be ingested.
    new_name: dict, optional
            Dictionary of the new columns name. If the JSON file is nested, it is advised
            to change the final names as special characters will be included.
            For example, {"param": {"age": 3, "name": Badr}, "date": 1993-03-11} will 
            create 3 columns: "param.age", "param.name" and "date". You can rename these 
            columns using the 'new_name' parameter with the following dictionary:
            {"param.age": "age", "param.name": "name"}
    insert: bool, optional
            If set to True, the data will be ingested to the input relation. The JSON
            parameters must be the same than the input relation otherwise they will
            not be ingested.
    temporary_table: bool, optional
        If set to True, a temporary table will be created.
    temporary_local_table: bool, optional
        If set to True, a temporary local table will be created. The parameter 'schema'
        must be empty, otherwise this parameter is ignored.
    gen_tmp_table_name: bool, optional
        Sets the name of the temporary table. This parameter is only used when the 
        parameter 'temporary_local_table' is set to True and if the parameters 
        "table_name" and "schema" are unspecified.
    ingest_local: bool, optional
        If set to True, the file will be ingested from the local machine.
    
    Returns
    -------
    vDataFrame
            The vDataFrame of the relation.
    
    See Also
    --------
    read_csv : Ingests a CSV file into the Vertica database.

The table "public"."iris" has been successfully created.