DuckDB is an embeddable SQL OLAP Database Management System

duckdb.threadsafety bool¶

Indicates that this package is threadsafe

duckdb.apilevel int¶

Indicates which Python DBAPI version this package implements

duckdb.paramstyle str¶

Indicates which parameter style duckdb supports

duckdb.default_connection duckdb.DuckDBPyConnection¶

The connection that is used by default if you don’t explicitly pass one to the root methods in this module

exception duckdb.BinderException¶

Bases: ProgrammingError

exception duckdb.CastException¶

Bases: DataError

exception duckdb.CatalogException¶

Bases: ProgrammingError

exception duckdb.ConnectionException¶

Bases: OperationalError

exception duckdb.ConstraintException¶

Bases: IntegrityError

exception duckdb.ConversionException¶

Bases: DataError

exception duckdb.DataError¶

Bases: Error

class duckdb.DuckDBPyConnection¶

Bases: pybind11_object

append(self: duckdb.DuckDBPyConnection, table_name: str, df: pandas.DataFrame) → duckdb.DuckDBPyConnection¶

Append the passed Data.Frame to the named table

arrow(self: duckdb.DuckDBPyConnection, chunk_size: int = 1000000) → pyarrow.lib.Table¶

Fetch a result as Arrow table following execute()

begin(self: duckdb.DuckDBPyConnection) → duckdb.DuckDBPyConnection¶

Start a new transaction

close(self: duckdb.DuckDBPyConnection) → None¶

Close the connection

commit(self: duckdb.DuckDBPyConnection) → duckdb.DuckDBPyConnection¶

Commit changes performed within a transaction

cursor(self: duckdb.DuckDBPyConnection) → duckdb.DuckDBPyConnection¶

Create a duplicate of the current connection

property description¶

Get result set attributes, mainly column names

df(self: duckdb.DuckDBPyConnection, *, date_as_object: bool = False) → pandas.DataFrame¶

Fetch a result as Data.Frame following execute()

duplicate(self: duckdb.DuckDBPyConnection) → duckdb.DuckDBPyConnection¶

Create a duplicate of the current connection

execute(self: duckdb.DuckDBPyConnection, query: str, parameters: object = None, multiple_parameter_sets: bool = False) → duckdb.DuckDBPyConnection¶

Execute the given SQL query, optionally using prepared statements with parameters set

executemany(self: duckdb.DuckDBPyConnection, query: str, parameters: object = None) → duckdb.DuckDBPyConnection¶

Execute the given prepared statement multiple times using the list of parameter sets in parameters

fetch_arrow_table(self: duckdb.DuckDBPyConnection, chunk_size: int = 1000000) → pyarrow.lib.Table¶

Fetch a result as Arrow table following execute()

fetch_df(self: duckdb.DuckDBPyConnection, *, date_as_object: bool = False) → pandas.DataFrame¶

Fetch a result as Data.Frame following execute()

fetch_df_chunk(self: duckdb.DuckDBPyConnection, vectors_per_chunk: int = 1, *, date_as_object: bool = False) → pandas.DataFrame¶

Fetch a chunk of the result as Data.Frame following execute()

fetch_record_batch(self: duckdb.DuckDBPyConnection, chunk_size: int = 1000000) → pyarrow.lib.RecordBatchReader¶

Fetch an Arrow RecordBatchReader following execute()

fetchall(self: duckdb.DuckDBPyConnection) → list¶

Fetch all rows from a result following execute

fetchdf(self: duckdb.DuckDBPyConnection, *, date_as_object: bool = False) → pandas.DataFrame¶

Fetch a result as Data.Frame following execute()

fetchmany(self: duckdb.DuckDBPyConnection, size: int = 1) → list¶

Fetch the next set of rows from a result following execute

fetchnumpy(self: duckdb.DuckDBPyConnection) → dict¶

Fetch a result as list of NumPy arrays following execute

fetchone(self: duckdb.DuckDBPyConnection) → object¶

Fetch a single row from a result following execute

from_arrow(self: duckdb.DuckDBPyConnection, arrow_object: object) → duckdb.DuckDBPyRelation¶

Create a relation object from an Arrow object

from_csv_auto(self: duckdb.DuckDBPyConnection, file_name: str) → duckdb.DuckDBPyRelation¶

Create a relation object from the CSV file in file_name

from_df(self: duckdb.DuckDBPyConnection, df: pandas.DataFrame = None) → duckdb.DuckDBPyRelation¶

Create a relation object from the Data.Frame in df

from_parquet(self: duckdb.DuckDBPyConnection, file_name: str, binary_as_string: bool = False) → duckdb.DuckDBPyRelation¶

Create a relation object from the Parquet file in file_name

from_query(self: duckdb.DuckDBPyConnection, query: str, alias: str = 'query_relation') → duckdb.DuckDBPyRelation¶

Create a relation object from the given SQL query

from_substrait(self: duckdb.DuckDBPyConnection, proto: bytes) → duckdb.DuckDBPyRelation¶

Create a query object from protobuf plan

get_substrait(self: duckdb.DuckDBPyConnection, query: str) → duckdb.DuckDBPyRelation¶

Serialize a query to protobuf

get_substrait_json(self: duckdb.DuckDBPyConnection, query: str) → duckdb.DuckDBPyRelation¶

Serialize a query to protobuf on the JSON format

get_table_names(self: duckdb.DuckDBPyConnection, query: str) → Set[str]¶

Extract the required table names from a query

install_extension(self: duckdb.DuckDBPyConnection, extension: str, *, force_install: bool = False) → None¶

Install an extension by name

load_extension(self: duckdb.DuckDBPyConnection, extension: str) → None¶

Load an installed extension

query(self: duckdb.DuckDBPyConnection, query: str, alias: str = 'query_relation') → duckdb.DuckDBPyRelation¶

Run a SQL query. If it is a SELECT statement, create a relation object from the given SQL query, otherwise run the query as-is.

register(self: duckdb.DuckDBPyConnection, view_name: str, python_object: object) → duckdb.DuckDBPyConnection¶

Register the passed Python Object value for querying with a view

rollback(self: duckdb.DuckDBPyConnection) → duckdb.DuckDBPyConnection¶

Roll back changes performed within a transaction

table(self: duckdb.DuckDBPyConnection, table_name: str) → duckdb.DuckDBPyRelation¶

Create a relation object for the name’d table

table_function(self: duckdb.DuckDBPyConnection, name: str, parameters: object = None) → duckdb.DuckDBPyRelation¶

Create a relation object from the name’d table function with given parameters

unregister(self: duckdb.DuckDBPyConnection, view_name: str) → duckdb.DuckDBPyConnection¶

Unregister the view name

values(self: duckdb.DuckDBPyConnection, values: object) → duckdb.DuckDBPyRelation¶

Create a relation object from the passed values

view(self: duckdb.DuckDBPyConnection, view_name: str) → duckdb.DuckDBPyRelation¶

Create a relation object for the name’d view

class duckdb.DuckDBPyRelation¶

Bases: pybind11_object

abs(self: duckdb.DuckDBPyRelation, aggregation_columns: str) → duckdb.DuckDBPyRelation¶

Returns the absolute value for the specified columns.

aggregate(self: duckdb.DuckDBPyRelation, aggr_expr: str, group_expr: str = '') → duckdb.DuckDBPyRelation¶

Compute the aggregate aggr_expr by the optional groups group_expr on the relation

property alias¶

Get the name of the current alias

apply(self: duckdb.DuckDBPyRelation, function_name: str, function_aggr: str, group_expr: str = '', function_parameter: str = '', projected_columns: str = '') → duckdb.DuckDBPyRelation¶

Compute the function of a single column or a list of columns by the optional groups on the relation

arrow(self: duckdb.DuckDBPyRelation, batch_size: int = 1000000) → pyarrow.lib.Table¶

Execute and fetch all rows as an Arrow Table

property columns¶

Get the names of the columns of this relation.

count(self: duckdb.DuckDBPyRelation, count_aggr: str, group_expr: str = '') → duckdb.DuckDBPyRelation¶

Compute the aggregate count of a single column or a list of columns by the optional groups on the relation

create(self: duckdb.DuckDBPyRelation, table_name: str) → None¶

Creates a new table named table_name with the contents of the relation object

create_view(self: duckdb.DuckDBPyRelation, view_name: str, replace: bool = True) → duckdb.DuckDBPyRelation¶

Creates a view named view_name that refers to the relation object

cummax(self: duckdb.DuckDBPyRelation, aggregation_columns: str) → duckdb.DuckDBPyRelation¶

Returns the cumulative maximum of the aggregate column.

cummin(self: duckdb.DuckDBPyRelation, aggregation_columns: str) → duckdb.DuckDBPyRelation¶

Returns the cumulative minimum of the aggregate column.

cumprod(self: duckdb.DuckDBPyRelation, aggregation_columns: str) → duckdb.DuckDBPyRelation¶

Returns the cumulative product of the aggregate column.

cumsum(self: duckdb.DuckDBPyRelation, aggregation_columns: str) → duckdb.DuckDBPyRelation¶

Returns the cumulative sum of the aggregate column.

describe(self: duckdb.DuckDBPyRelation) → duckdb.DuckDBPyRelation¶

Gives basic statistics (e.g., min,max) and if null exists for each column of the relation.

df(self: duckdb.DuckDBPyRelation, *, date_as_object: bool = False) → pandas.DataFrame¶

Execute and fetch all rows as a pandas DataFrame

distinct(self: duckdb.DuckDBPyRelation) → duckdb.DuckDBPyRelation¶

Retrieve distinct rows from this relation object

property dtypes¶

Get the columns types of the result.

except_(self: duckdb.DuckDBPyRelation, other_rel: duckdb.DuckDBPyRelation) → duckdb.DuckDBPyRelation¶

Create the set except of this relation object with another relation object in other_rel

execute(self: duckdb.DuckDBPyRelation) → duckdb::DuckDBPyResult¶

Transform the relation into a result set

explain(self: duckdb.DuckDBPyRelation) → str¶

fetchall(self: duckdb.DuckDBPyRelation) → object¶

Execute and fetch all rows as a list of tuples

fetchmany(self: duckdb.DuckDBPyRelation, size: int = 1) → object¶

Execute and fetch the next set of rows as a list of tuples

fetchnumpy(self: duckdb.DuckDBPyRelation) → dict¶

Execute and fetch all rows as a Python dict mapping each column to one numpy arrays

fetchone(self: duckdb.DuckDBPyRelation) → object¶

Execute and fetch a single row as a tuple

filter(self: duckdb.DuckDBPyRelation, filter_expr: str) → duckdb.DuckDBPyRelation¶

Filter the relation object by the filter in filter_expr

insert(self: duckdb.DuckDBPyRelation, values: object) → None¶

Inserts the given values into the relation

insert_into(self: duckdb.DuckDBPyRelation, table_name: str) → None¶

Inserts the relation object into an existing table named table_name

intersect(self: duckdb.DuckDBPyRelation, other_rel: duckdb.DuckDBPyRelation) → duckdb.DuckDBPyRelation¶

Create the set intersection of this relation object with another relation object in other_rel

join(self: duckdb.DuckDBPyRelation, other_rel: duckdb.DuckDBPyRelation, condition: str, how: str = 'inner') → duckdb.DuckDBPyRelation¶

Join the relation object with another relation object in other_rel using the join condition expression in join_condition. Types supported are ‘inner’ and ‘left’

kurt(self: duckdb.DuckDBPyRelation, aggregation_columns: str, group_columns: str = '') → duckdb.DuckDBPyRelation¶

Returns the excess kurtosis of the aggregate column.

limit(self: duckdb.DuckDBPyRelation, n: int, offset: int = 0) → duckdb.DuckDBPyRelation¶

Only retrieve the first n rows from this relation object, starting at offset

mad(self: duckdb.DuckDBPyRelation, aggregation_columns: str, group_columns: str = '') → duckdb.DuckDBPyRelation¶

Returns the median absolute deviation for the aggregate columns. NULL values are ignored. Temporal types return a positive INTERVAL.

map(self: duckdb.DuckDBPyRelation, map_function: function) → duckdb.DuckDBPyRelation¶

Calls the passed function on the relation

max(self: duckdb.DuckDBPyRelation, max_aggr: str, group_expr: str = '') → duckdb.DuckDBPyRelation¶

Compute the aggregate max of a single column or a list of columns by the optional groups on the relation

mean(self: duckdb.DuckDBPyRelation, mean_aggr: str, group_expr: str = '') → duckdb.DuckDBPyRelation¶

Compute the aggregate mean of a single column or a list of columns by the optional groups on the relation

median(self: duckdb.DuckDBPyRelation, median_aggr: str, group_expr: str = '') → duckdb.DuckDBPyRelation¶

Compute the aggregate median of a single column or a list of columns by the optional groups on the relation

min(self: duckdb.DuckDBPyRelation, min_aggr: str, group_expr: str = '') → duckdb.DuckDBPyRelation¶

Compute the aggregate min of a single column or a list of columns by the optional groups on the relation

mode(self: duckdb.DuckDBPyRelation, aggregation_columns: str, group_columns: str = '') → duckdb.DuckDBPyRelation¶

Returns the most frequent value for the aggregate columns. NULL values are ignored.

order(self: duckdb.DuckDBPyRelation, order_expr: str) → duckdb.DuckDBPyRelation¶

Reorder the relation object by order_expr

prod(self: duckdb.DuckDBPyRelation, aggregation_columns: str, group_columns: str = '') → duckdb.DuckDBPyRelation¶

Calculates the product of the aggregate column.

project(self: duckdb.DuckDBPyRelation, project_expr: str) → duckdb.DuckDBPyRelation¶

Project the relation object by the projection in project_expr

quantile(self: duckdb.DuckDBPyRelation, q: str, quantile_aggr: str, group_expr: str = '') → duckdb.DuckDBPyRelation¶

Compute the quantile of a single column or a list of columns by the optional groups on the relation

query(self: duckdb.DuckDBPyRelation, virtual_table_name: str, sql_query: str) → duckdb.DuckDBPyRelation¶

Run the given SQL query in sql_query on the view named virtual_table_name that refers to the relation object

record_batch(self: duckdb.DuckDBPyRelation, batch_size: int = 1000000) → pyarrow.lib.RecordBatchReader¶

Execute and return an Arrow Record Batch Reader that yields all rows

sem(self: duckdb.DuckDBPyRelation, aggregation_columns: str, group_columns: str = '') → duckdb.DuckDBPyRelation¶

Returns the standard error of the mean of the aggregate column.

set_alias(self: duckdb.DuckDBPyRelation, alias: str) → duckdb.DuckDBPyRelation¶

Rename the relation object to new alias

property shape¶

Tuple of # of rows, # of columns in relation.

skew(self: duckdb.DuckDBPyRelation, aggregation_columns: str, group_columns: str = '') → duckdb.DuckDBPyRelation¶

Returns the skewness of the aggregate column.

std(self: duckdb.DuckDBPyRelation, std_aggr: str, group_expr: str = '') → duckdb.DuckDBPyRelation¶

Compute the standard deviation of a single column or a list of columns by the optional groups on the relation

sum(self: duckdb.DuckDBPyRelation, sum_aggr: str, group_expr: str = '') → duckdb.DuckDBPyRelation¶

Compute the aggregate sum of a single column or a list of columns by the optional groups on the relation

to_arrow_table(self: duckdb.DuckDBPyRelation, batch_size: int = 1000000) → pyarrow.lib.Table¶

Execute and fetch all rows as an Arrow Table

to_df(self: duckdb.DuckDBPyRelation, *, date_as_object: bool = False) → pandas.DataFrame¶

Execute and fetch all rows as a pandas DataFrame

property type¶

Get the type of the relation.

property types¶

Get the columns types of the result.

union(self: duckdb.DuckDBPyRelation, union_rel: duckdb.DuckDBPyRelation) → duckdb.DuckDBPyRelation¶

Create the set union of this relation object with another relation object in other_rel

unique(self: duckdb.DuckDBPyRelation, unique_aggr: str) → duckdb.DuckDBPyRelation¶

Number of distinct values in a column.

value_counts(self: duckdb.DuckDBPyRelation, value_counts_aggr: str, group_expr: str = '') → duckdb.DuckDBPyRelation¶

Count number of rows with each unique value of variable

var(self: duckdb.DuckDBPyRelation, var_aggr: str, group_expr: str = '') → duckdb.DuckDBPyRelation¶

Compute the variance of a single column or a list of columns by the optional groups on the relation

write_csv(self: duckdb.DuckDBPyRelation, file_name: str) → None¶

Write the relation object to a CSV file in file_name

class duckdb.DuckDBPyResult¶

Bases: pybind11_object

arrow(self: duckdb.DuckDBPyResult, chunk_size: int = 1000000) → pyarrow.lib.Table¶

Fetch all rows as an Arrow Table

close(self: duckdb.DuckDBPyResult) → None¶

description(self: duckdb.DuckDBPyResult) → list¶

df(self: duckdb.DuckDBPyResult, *, date_as_object: bool = False) → pandas.DataFrame¶

Fetch all rows as a pandas DataFrame

fetch_arrow_reader(self: duckdb.DuckDBPyResult, approx_batch_size: int) → pyarrow.lib.RecordBatchReader¶

Fetch all rows as an Arrow Record Batch Reader

fetch_arrow_table(self: duckdb.DuckDBPyResult, chunk_size: int = 1000000) → pyarrow.lib.Table¶

Fetch all rows as an Arrow Table

fetch_df(self: duckdb.DuckDBPyResult, *, date_as_object: bool = False) → pandas.DataFrame¶

Fetch all rows as a pandas DataFrame

fetch_df_chunk(self: duckdb.DuckDBPyResult, num_of_vectors: int = 1, *, date_as_object: bool = False) → pandas.DataFrame¶

Fetch a chunk of rows as a pandas DataFrame

fetchall(self: duckdb.DuckDBPyResult) → list¶

Fetch all rows as a list of tuples

fetchdf(self: duckdb.DuckDBPyResult, *, date_as_object: bool = False) → pandas.DataFrame¶

Fetch all rows as a pandas DataFrame

fetchmany(self: duckdb.DuckDBPyResult, size: int = 1) → list¶

Fetch the next set of rows as a list of tuples

fetchnumpy(self: duckdb.DuckDBPyResult) → dict¶

Fetch all rows as a Python dict mapping each column to one numpy arrays

fetchone(self: duckdb.DuckDBPyResult) → object¶

Fetch a single row as a tuple

exception duckdb.Error¶

Bases: Exception

exception duckdb.FatalException¶

Bases: Error

exception duckdb.IOException¶

Bases: OperationalError

exception duckdb.IntegrityError¶

Bases: Error

exception duckdb.InternalError¶

Bases: Error

exception duckdb.InternalException¶

Bases: InternalError

exception duckdb.InterruptException¶

Bases: Error

exception duckdb.InvalidInputException¶

Bases: ProgrammingError

exception duckdb.InvalidTypeException¶

Bases: ProgrammingError

exception duckdb.NotImplementedException¶

Bases: NotSupportedError

exception duckdb.NotSupportedError¶

Bases: Error

exception duckdb.OperationalError¶

Bases: Error

exception duckdb.OutOfMemoryException¶

Bases: OperationalError

exception duckdb.OutOfRangeException¶

Bases: DataError

exception duckdb.ParserException¶

Bases: ProgrammingError

exception duckdb.PermissionException¶

Bases: Error

exception duckdb.ProgrammingError¶

Bases: Error

exception duckdb.SequenceException¶

Bases: Error

exception duckdb.SerializationException¶

Bases: OperationalError

exception duckdb.StandardException¶

Bases: Error

exception duckdb.SyntaxException¶

Bases: ProgrammingError

exception duckdb.TransactionException¶

Bases: OperationalError

exception duckdb.TypeMismatchException¶

Bases: DataError

exception duckdb.ValueOutOfRangeException¶

Bases: DataError

exception duckdb.Warning¶

Bases: Exception

duckdb.aggregate(df: pandas.DataFrame, aggr_expr: str, group_expr: str = '', connection: duckdb.DuckDBPyConnection = None) → duckdb.DuckDBPyRelation¶

Compute the aggregate aggr_expr by the optional groups group_expr on Data.frame df

duckdb.alias(df: pandas.DataFrame, alias: str, connection: duckdb.DuckDBPyConnection = None) → duckdb.DuckDBPyRelation¶

Create a relation from Data.Frame df with the passed alias

duckdb.arrow(arrow_object: object, connection: duckdb.DuckDBPyConnection = None) → duckdb.DuckDBPyRelation¶

Create a relation object from an Arrow object

duckdb.connect(database: str = ':memory:', read_only: bool = False, config: object = None) → duckdb.DuckDBPyConnection¶

Create a DuckDB database instance. Can take a database file name to read/write persistent data and a read_only flag if no changes are desired

duckdb.df(df: pandas.DataFrame, connection: duckdb.DuckDBPyConnection = None) → duckdb.DuckDBPyRelation¶

Create a relation object from the Data.Frame df

duckdb.distinct(df: pandas.DataFrame, connection: duckdb.DuckDBPyConnection = None) → duckdb.DuckDBPyRelation¶

Compute the distinct rows from Data.Frame df

duckdb.filter(df: pandas.DataFrame, filter_expr: str, connection: duckdb.DuckDBPyConnection = None) → duckdb.DuckDBPyRelation¶

Filter the Data.Frame df by the filter in filter_expr

duckdb.from_arrow(arrow_object: object, connection: duckdb.DuckDBPyConnection = None) → duckdb.DuckDBPyRelation¶

Create a relation object from an Arrow object

duckdb.from_csv_auto(file_name: str, connection: duckdb.DuckDBPyConnection = None) → duckdb.DuckDBPyRelation¶

Creates a relation object from the CSV file in file_name

duckdb.from_df(df: pandas.DataFrame, connection: duckdb.DuckDBPyConnection = None) → duckdb.DuckDBPyRelation¶

Create a relation object from the Data.Frame df

duckdb.from_parquet(*args, **kwargs)¶

Overloaded function.

1. from_parquet(file_name: str, binary_as_string: bool, connection: duckdb.DuckDBPyConnection = None) -> duckdb.DuckDBPyRelation

Creates a relation object from the Parquet file in file_name

2. from_parquet(file_name: str, connection: duckdb.DuckDBPyConnection = None) -> duckdb.DuckDBPyRelation

Creates a relation object from the Parquet file in file_name

duckdb.from_query(query: str, alias: str = 'query_relation', connection: duckdb.DuckDBPyConnection = None) → duckdb.DuckDBPyRelation¶

Create a relation object from the given SQL query

duckdb.from_substrait(proto: bytes, connection: duckdb.DuckDBPyConnection = None) → duckdb.DuckDBPyRelation¶

Creates a query object from the substrait plan

duckdb.get_substrait(query: str, connection: duckdb.DuckDBPyConnection = None) → duckdb.DuckDBPyRelation¶

Serialize a query object to protobuf

duckdb.get_substrait_json(query: str, connection: duckdb.DuckDBPyConnection = None) → duckdb.DuckDBPyRelation¶

Serialize a query object to protobuf

duckdb.limit(df: pandas.DataFrame, n: int, connection: duckdb.DuckDBPyConnection = None) → duckdb.DuckDBPyRelation¶

Retrieve the first n rows from the Data.Frame df

duckdb.order(df: pandas.DataFrame, order_expr: str, connection: duckdb.DuckDBPyConnection = None) → duckdb.DuckDBPyRelation¶

Reorder the Data.Frame df by order_expr

duckdb.project(df: pandas.DataFrame, project_expr: str, connection: duckdb.DuckDBPyConnection = None) → duckdb.DuckDBPyRelation¶

Project the Data.Frame df by the projection in project_expr

duckdb.query(query: str, alias: str = 'query_relation', connection: duckdb.DuckDBPyConnection = None) → duckdb.DuckDBPyRelation¶

Run a SQL query. If it is a SELECT statement, create a relation object from the given SQL query, otherwise run the query as-is.

duckdb.query_df(df: pandas.DataFrame, virtual_table_name: str, sql_query: str, connection: duckdb.DuckDBPyConnection = None) → duckdb.DuckDBPyResult¶

Run the given SQL query in sql_query on the view named virtual_table_name that contains the content of Data.Frame df

class duckdb.token_type¶

Bases: pybind11_object

Members:

identifier

numeric_const

string_const

operator

keyword

comment

comment = <token_type.comment: 5>¶

identifier = <token_type.identifier: 0>¶

keyword = <token_type.keyword: 4>¶

property name¶

numeric_const = <token_type.numeric_const: 1>¶

operator = <token_type.operator: 3>¶

string_const = <token_type.string_const: 2>¶

property value¶

duckdb.tokenize(query: str) → object¶

Tokenizes a SQL string, returning a list of (position, type) tuples that can be used for e.g. syntax highlighting

duckdb.values(values: object, connection: duckdb.DuckDBPyConnection = None) → duckdb.DuckDBPyRelation¶

Create a relation object from the passed values

duckdb.write_csv(df: pandas.DataFrame, file_name: str, connection: duckdb.DuckDBPyConnection = None) → None¶

Write the Data.Frame df to a CSV file in file_name