Dataitem kinds

At the moment, we support the following kinds:

• table: represents a table

For each different kind, the Dataitem object has its own subclass with different spec and status attributes.

Table

The table kind indicates that the dataitem is a generic table. It's usefull if you intend to manipulate the dataitem as a dataframe, infact it has some methods to do so. The default dataframe framework we use to represent a table as dataframe is pandas.

Table spec parameters

Parameter	Type	Description	Default
path	str	Path of the dataitem, can be a local path or a remote path, a single filepath or a directory/partition.	required
schema	TableSchema	Frictionless table schema	None

Table methods

The table kind has the following additional methods:

as_df

Read dataitem file (csv or parquet) as a DataFrame from spec.path. If the dataitem is not local, it will be downloaded to a temporary folder named tmp_dir in the project context folder. If clean_tmp_path is True, the temporary folder will be deleted after the method is executed. It's possible to pass additional arguments to the this function. These keyword arguments will be passed to the DataFrame reader function such as pandas's read_csv or read_parquet.

Parameters:

Name	Type	Description	Default
file_format	str	Format of the file. (Supported csv and parquet).	None
engine	str	Dataframe framework, by default pandas.	None
clean_tmp_path	bool	If True, the temporary folder will be deleted.	True
**kwargs	dict	Keyword arguments passed to the read_df function.	{}

Returns:

Type	Description
Any	DataFrame.

write_df

Write DataFrame as parquet/csv/table into dataitem spec.path. keyword arguments will be passed to the DataFrame reader function such as pandas's to_csv or to_parquet.

Parameters:

Name	Type	Description	Default
df	Any	DataFrame to write.	required
extension	str	Extension of the file.	None
**kwargs	dict	Keyword arguments passed to the write_df function.	{}

Returns:

Type	Description
str	Path to the written dataframe.