Data type Detection

Data type detection is used to detect the date type of feature (column). It verifies and finds Date-time, URL, Email, Currency, Phone, Latitude degree, latitude seconds, latitude minutes, longitude deg, longitude Seconds, and longitude minutes data types. It returns a list of dictionaries that contain the column name and its type.
Sample output:

    

        
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         [{"name":"created_time","datatype":"DateTime"},{"name":"mail","datatype":"Email"},....]
    

DType Transformation

This ML operation generates new columns from URL, Email, Date-time and json type columns.

1. URL Transformation

   This operation splits URL column into eight columns for better processing and performance.

   Sample input:

   link
   https://www.google.in/library?fetch=query#fragment_part

   Sample output:

   link_url_protocol	https
   link_url_domain	www.google.in
   link_url_path	/library
   link_url_query	fetch=query
   link_url_fragment	fragment_part
   link_domain_tld	in
   link_domain_country	IN
   domain	www

2. Email Transformation

   This operation splits email column into three columns: first, middle, and last.
   Sample input:

   mail
   abc@zohocorp.com

   Sample output:

   mail_first	mail_middle	mail_last
   abc	zohocorp	com

3. Date time Transformation

   This operation splits date time column into nine columns for better processing.
   Sample input:\

   dt
   2021-11-29 11:52:59

   Sample output:

   dt_day_of_week	1
   dt_date_no	29
   dt_year_no	2021
   dt_month_no	11
   dt_business_day	1
   dt_week_no_year	48
   dt_day_of_year	333
   dt_AM_PM	AM
   dt_quarter_year	4

4. Flatten Json

   This operation flattens the JSON value so that JSON contains only key-value pairs without nesting for better processing.
   Sample input:

    

        
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         {
    "user":{
    "abc": {"id":1, "mail":"abc@zohocorp.com"}
    }
}

    

Sample output:

    

        
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         {
    "user_abc_id":1,
    "user_abc_mail":"abc@zohocorp.com"
}