Edit: documenting a solution to my own question. I'm trying to load a multisheet ExcelDataSet through the Catalog. I'm trying to load all sheets this way,

my_excel_file:
  type: pandas.ExcelDataSet
  filepath: some-excel-file.xlsx
  load_args:
    sheet_name: None

and I get

Worksheet named 'None' not found

Is there a way to load all sheets through the catalog? Yes Edit: Not documented fully in Kedro, but in case someone comes across this, reminder to use YAML API syntax for

None

which is

null

or

~

or . Thanks in advance!

hi -- newbie question 🙈 How do you concat your sheets afterwards ? Defining a

pd.concat

node with the dict as input ? Or is there a more direct way of concatenating sheets, if needed ?

Precisely using pd.concat. In the concatenation node, using dict.values() which gives you a list of DataFrames, assuming the schema is uniform across the sheets (otherwise you get errors). Otherwise, you can address the sheets by dict["sheet_name(s)"]. Bear in mind the description of the obj argument.

objs: sequence or mapping of Series or DataFrame objects
If a mapping is passed, the sorted keys will be used as the keys argument, unless it is passed, in which case the values will be selected (see below). Any None objects will be dropped silently unless they are all None in which case a ValueError will be raised.

Thank you very much for your detailed answer ! That's what I had done, and there was precisely one last different column causing me issues (+ a bad pandas dtype inference in the shortest table).

You can add the dtype argument in the catalog for your dataset if you know the desired type for that column. Then handle the different column conditionally based on the dictionary key (sheet name) or column name