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convert collection to a single table (ExampleSet)
I'm using loop values and it generates different tables (ExampleSet) by value with the same attributes.
I need to have a table with all.
my out is
collection
table value 23:
USER_ID ITEM_ID
1 23
table value 54:
USER_ID ITEM_ID
1 54
...
I need this
ExampleSet
USER_ID ITEM_ID
1 23
1 54
... ...
Thanks
I need to have a table with all.
my out is
collection
table value 23:
USER_ID ITEM_ID
1 23
table value 54:
USER_ID ITEM_ID
1 54
...
I need this
ExampleSet
USER_ID ITEM_ID
1 23
1 54
... ...
Thanks
Tagged:
1
Answers
you've posted in the Development forum, so I'm assuming you want to know how to do it in Java. You will need to create a new ExampleSet with the same attributes as your existing sets have. You can then loop over each example (row) of each example set and add a row for each to the new one. See below for a quick example: In case you were looking for a solution inside RapidMiner Studio, just use the "Append" operator.
Regards,
Marco
Whats the solution?? I want single example set.
if you use Append correctly, it will give you an example set. This is working every time in hundreds of processes.
Please post a screenshot and the process XML if it doesn't work for you.
Regards,
Balázs
It sounds like you want to concatenate or combine the tables generated for different values into a single table in your Example Set. If you are using a programming language or a tool that supports loops, you can achieve this by appending the tables for each value. Here's a general example using Python and pandas:
</code>import pandas as pd # Initialize an empty DataFrame to store the combined tables combined_table = pd.DataFrame(columns=["USER_ID", "ITEM_ID"]) # Example loop (replace this with your actual loop) for value in [23, 54, ...]: # Add all your loop values # Assuming you have a function to generate each table based on the loop value table_for_value = generate_table(value) # Append the table for the current value to the combined_table combined_table = pd.concat([combined_table, table_for_value], ignore_index=True) # Display the combined table print(combined_table)</pre><div><br>In this example:<br><ul><li>Replace <code>[23, 54, ...]
with the actual values you are looping through.Replacegenerate_table(value)
with the function or code that generates the table for each value.Thepd.concat
function is used to concatenate the tables vertically (row-wise). Theignore_index=True
parameter ensures that the resulting DataFrame has a new index.Note: The exact implementation may vary based on the language or tool you are using. If you provide more details about your environment, I can offer a more specific solution.