Apply Filter¶
You can use the Apply Filter function when you want to keep or remove certain rows of data from the View based on some condition(s). These conditions are also applicable in other Tasks.
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Fig. 100 Filter for Female on Column Gender¶
Quick Start¶
Let’s use the same dataset
as above to reach the final output using the Apply Filter rule.
Go to Transform > Label, Filter and Replace > Apply Filter.
Select Keep from the Keep/Remove option to include the values which satisfy the condition;
Select Gender from the column drop-down;
Select is from the operator list;
Select Value from the operand list;
Select the operand value Female;
Click Apply.
Fundamentals¶
In order to use filters effectively, let’s understand the following terminologies:
Condition¶
A condition is a statement against which every row of data is checked. The rows that satisfy the condition appear in the results.
Value or Column Value¶
A condition in Mammoth has two types of operands: Value and Common Value.
Value
A Value lets you build a condition attached to any value from the selected column. For example, in the Dataset in Fig. 100, we can filter the Gender data for one of the two values - “Female” or “Male”.
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Fig. 101 Selecting “Female” as value¶
Column Value
A Column Value lets you build a condition connected to values in another Column. For example, in the Dataset in Fig. 100, a Column Value operand can help compare the exam marks over two semesters for all students.
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Fig. 102 Selecting Column Value as Eng(Sem-2) for comparison¶
If we want to select the best performing students in Sem-1, we can build a condition comparing one (Sem-1) column with another (Sem-2) using the greater-than operator. The result is below:
Table 3 Output on comparison of marks¶ Student
Gender
English (Sem-1)
English (Sem-2)
Alice
Female
95
90
Chuck
Male
80
60
Building Complex Conditions¶
Let’s take a look at the Dataset in Fig. 100 . Suppose you want to filter the Gender data to show all “Female” exam marks in English in Sem-1 greater than 70. You’ll need to build two conditions for the Task using the AND or OR operation.To build multiple conditions, click on the ‘+’ icon.
To solve the problem above, create two conditions:
Gender is “Female”.
Value of English (Sem-1) column is greater than 70.
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Fig. 103 Building complex conditions¶
Setting “AND” on both conditions to true will get the desired result.
Or perhaps you want to select the students with average marks of more than 65 but less than 80 in English across both Semesters or who scored above 90 in Sem-1. From the defined selection criteria, this requires two conditions. But the first condition needs to compare the marks for both semesters which means there is a condition within a condition, also called a nested condition. To create a nested condition, click on the ‘→’ icon.
So, to solve the above problem, you can build a nested condition as:
English (Sem-1) is greater than 90
OR
Output of (Use ‘→’ icon to create nested condition) -
English (Sem-1) in between 65-80
AND
English (Sem-2) in between 65-80.

Fig. 104 Building nested conditions¶
Use “OR” and “AND” as the operators in between the conditions to get the desired result.
Supported Options¶
Keep/Remove: To filter for or against of the condition statement. The Keep option retains rows satisfying the condition while the Remove option removes the columns satisfying the condition.
Select a column: Shows a drop-down menu of all the columns. Select a column from the menu to build your condition on.
Select an operator: Contains a list of operations. These operations vary as per the datatype. Here’s the complete list of operations for different datatypes:
Operations for text columns:
Table 4 Operations for text columns¶ Operation type
Filters rows
is
matching the value
is NOT
not matching the value
contains
containing the value
does NOT contain
not containing the value
starts with
starting with the value
does NOT start with
not starting with the value
ends with
ending with the value
does NOT end with
not ending with the value
is empty
with no value in the selected column
is NOT empty
with value in the selected column
Operations for numeric columns:
Table 5 Operations for numeric columns¶ Operation type
Filters rows
is
matching the value
is NOT
not matching the value
is less than
containing value less than the specified value
is less than or equal to
containing value less than or equal to the specified value
is greater than
with a value greater than the specified value
is greater than or equal to
with a value greater than equal to the specified value
is the maximum value
containing the highest value for the selected column
is NOT the maximum value
containing values other than the highest value
is the minimum value
containing the lowest value for the selected column
is NOT the minimum value
containing values other than the lowest value
is empty
with no value in the selected column
is NOT empty
with value in the selected column
in between
with values in the specified range
Operations for date columns:
Table 6 Operations for date columns¶ Operation type
Filters rows
is
matching the value
is NOT
not matching the value
contains
containing the value
does NOT contain
not containing the value
starts with
starting with the value
does NOT start with
not starting with the value
ends with
ending with the value
does NOT end with
not ending with the value
is empty
with no value in the selected column
is NOT empty
with value in the selected column
Select an operand: Offers two options: Value and Common Value.
Operand for date type:
Table 7 Operands for date columns¶ Operand type
Filters rows
Date
matching the date
Date-Time in seconds
matching date and time to the second
Date/Minute
matching date and time to the minute
Date/Hour
matching date and time to the hour
Year/Month
matching the year and the month
Year
matching the year
Day of Month
matching the day of the month
Month
matching the month
Weekday
matching the weekday
Earliest single value
with the earliest date and the time
Latest single value
with the latest date and the time
Earliest Date-Time
with earliest date-time increased to a certain date-time
Latest Date-Time
with latest date-time decreased to a certain date-time
Add condition: You can build complex conditions using this. The Add condition option is present as the + sign next to the condition.
AND/OR: Operators for complex conditions. The And operator checks for rows statisfying all the conditions. The OR operator checks for rows satifying at least any one of the statements.
Note
Filtering does not delete data. It only filters the data for the next step of the pipeline. Filters can be modified or deleted;
You can make the text values case sensitive by clicking on the case-sensitive checkbox present below the last condition ;
Filter conditions are suggested based on current data in the View. It does not account for any future data the View may get. This could affect the filter results. For example, if you need to remove all those rows with a Column Value of -(hyphen) or _ (underscore) or if your current data in the View only has Values with - , the suggestions would reflect this. You need to explicitly add _ to account for any future data with this Value.
Apply Filter can also be applied via explore cards which filter out the Values but don’t add the rule to the Data Pipeline. From the explore card you can add it to the Pipeline and it will open the Apply Filter task pre-filled with the filter conditions matching the explore card selection.
You can place a condition outside the parentheses by clicking on ‘←’ icon.