Difficulties in setting column data types

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**Is your feature request related to a problem? Please describe.**
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If is very time consuming and frustating when you import data to train with lots of double values but it automatically identifies it as a string. You must then go by one by one to select the correct single data type for each one because it automatically thinks its a string.

Also, it should automatically assume that the data that is imported has headers. I do not even understand why this has to be stated. Why must you have an extra step here. I would say over 90% of the time, the data will have a header when importing from a CSV

**Describe the solution you'd like**
A clear and concise description of what you want to happen.
Create a better parsing method to distinguish between single and strings. If the cell contains only numbers, its a good indication that is a single.

And or, create a way to select multiple columns and change the datatype with just one click.

And or, the ability to save settings, or profiles that remembers the header names and remembers what data type a certain cell should be.

**Describe alternatives you've considered**
A clear and concise description of any alternative solutions or features you've considered.

I considered using python instead as I cant modify the schema explicitly by using the TextLoader when using automl.

**Additional context**
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Iniziate riproducendo il workflow di importazione CSV descritto nella issue e verificate come TextLoader e AutoML deducano attualmente le intestazioni e i tipi di colonna. Done dovrebbe essere definito come un comportamento mirato di parsing o modifica collettiva, con una gestione chiara delle colonne numeriche e delle intestazioni; la issue solleva inoltre i profili salvati come possibile funzionalità separata.

Scritto dal modello di indicizzazione a partire dal testo della issue.