Using Dataiku
- Hello, I take time of these few moments of respite to write a post on this subject that many of my collaborators meet and whihch I have already confronted this problem with Dataiku's staff but which h…
Last answer by CoreySHi @Grixis6
please feel free to utilize the Product Ideas board. The Product Ideas board is here to let you share and exchange your ideas on how to improve Dataiku. Here are some resources to help get you started:Suggest an idea I hope this helps!
Last answer by CoreySHi @Grixis6
please feel free to utilize the Product Ideas board. The Product Ideas board is here to let you share and exchange your ideas on how to improve Dataiku. Here are some resources to help get you started:Suggest an idea I hope this helps!
- Hi all, I would like to unfold/dummify all of my categorical columns. I'm able to do that one column at a time using the Unfold recipe but I'm searching for automated way to do all of them without add…Last answer by
Last answer by AlexGoSarina's way is definitely the recommended option, but if you want to try with the visual recipes you can also try something like 'concatenate' and then 'Create dummy columns by splitting'. You would have to ensure none of your columns had the same data though.
The column view in the Prepare recipe can help you easily filter and select the 'Text' fields and then concatenate with a unique delimiter such as '||'
Then you can run the Create Dummy Columns by Splitting:
- I have a csv file in my flow which I would like to export as a tab file. Is it possible using a python recipe? If so, what would that recipe be? Thanks! Operating system used: WindowsSolution bySolution by dgraham
Hi @raia
,You could export the dataset in your flow, and download it as a TSV (Tab Separated Values) formatted file, by clicking on the "Export" button, then specifying "\t" as the separator.
Additionally, from a Python code recipe, you could output the CSV dataset to a managed folder as a TSV file using the Pandas Python library, as shown in the below example code:
import dataiku import pandas as pd, numpy as np from dataiku import pandasutils as pdu # Read recipe inputs comma_separated_file = dataiku.Dataset("comma_separated_file") df = comma_separated_file.get_dataframe() # the name of the tab file file_name = 'tab_separated_file.tsv' # Write recipe outputs output_folder = dataiku.Folder("output_folder") with output_folder.get_writer(f"/{file_name}") as writer: writer.write(df.to_csv(sep='\t', encoding='utf-8', index=False).encode("utf-8"))