Filtering a Dataset How to Work with Each Function

Filtering a Dataset: How to Work with Each Function

When working with a large dataset, filtering can be a powerful tool to help you focus on the most relevant information for your analysis. In this documentation, we’ll walk you through how to use the following functions to filter a dataset.

 

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Filter a dataset using the UI

1. Start by navigating to the dataset you want to filter.
2. Once there, click on the top right button with the filter icon.

3. This will bring up a menu where you can add a name for the view to help you identify the query.

4. Choose the appropriate filters under the “Include filters” section, such as country, job title, or date.

5. Once you’ve selected the filters you want, click the “create subset” button to create the filtered view.

 

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Select

Use the select filter function to select one or more exact matches of a value from a pre-defined list. For example, if you want to filter your dataset by country or region, you can use this function to select one or more exact values you’re interested in. This function is particularly useful when you have a pre-defined set of values to choose from, such as a list of countries or regions. By selecting one or more values from the list, you can easily filter your dataset to include only the records that match the selected values.

 

 

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Boolean

This filter function allows you to filter by boolean values, such as true or false. This can be useful if you’re looking for specific records that meet certain criteria, such as whether a social media profile is verified. For example, you could use the boolean filter to search for verified profiles or to find profiles that have not yet been verified.

 

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Date

Use the date filter function to filter by a range of dates, such as all records between two specific dates. To choose a specific date, you can set the start date and end date to the same date, but make sure the end date is one day after the start date. For example, if you want to filter by January 1st, 2022, set the start date to 1/1/2022 and the end date to 1/2/2022. This function can be helpful if you’re analyzing trends over time or if you want to filter by specific events that occurred during a certain date range.

 

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Number

Using these filter options, you can easily filter your dataset by numerical values based on various criteria. Here’s an explanation of each option and an example of how it can be used:

1. Is: This option matches records with an exact numerical value. For example, if you want to filter orders that have a total amount of $100, you can use the is option to match records with a value of 100.
2. Not: This option matches records that do not have the specified numerical value. For example, if you want to filter orders that do not have a total amount of $100, you can use the not option to match records that have a value other than 100.
3. Exist: This option filters records with a non-empty numerical value for a specific field. For example, if you want to filter orders that have a total amount, you can use the existing option to match records that have a value for the total amount field.
4. List (exact match): This option matches records with an exact numerical value from a pre-defined list. For example, if you want to filter orders that have a total amount of $100 or$200, you can use the list option to match records with those specific values.
5. Lower than: This option matches records with a numerical value lower than the specified value. For example, if you want to filter orders that have a total amount less than $100, you can use the lower than the option to match records with a value less than 100.
6. Lower or equal to: This option matches records with a numerical value lower than or equal to the specified value. For example, if you want to filter orders with a total amount less than or equal to $100, you can use the lower or equal option to match records with a value of 100 or less.
7. Greater than: This option matches records with a numerical value greater than the specified value. For example, if you want to filter orders with a total amount greater than $100, you can use the greater than option to match records with a value greater than 100.
8. Greater or equal to: This option matches records with a numerical value greater than or equal to the specified value. For example, if you want to filter orders that have a total amount greater than or equal to $100, you can use the greater or equal to option to match records with a value of 100 or greater.

 

 

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String

Use the string filter function to filter by string values using one of the following options: is, not, exist, list (exact match), or includes.

1. The is option matches the exact value of a string, while the not option matches all strings that do not contain the specified value.
2. The exist option filters records with a non-empty string value for a specific field.
3. The list option matches the exact values of a string from a pre-defined list that you can paste into the UI.
4. The includes option matches any records that include the specified string value, regardless of whether the value is an exact match. This function can be useful if you’re looking for specific patterns or keywords in your dataset, or if you want to filter by a specific set of values.

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Creating Rule-Based Group Filters

This feature allows users to create rule-based group filters in a dataset. To create a group filter, the user can click on the “+Add filter” dropdown and then click on “Add group”. Users can nest more filters within a group by using “Add group”.

 

For example, a user can create a rule-based group filter in an Amazon electronics dataset where the “Category” is “Electronics”, the “Country” is “US”, and the “Brand” is either “Dell” or “Apple”.

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Limitations

1. Groups cannot be nested within other groups, so users cannot “add group” in the “Add filter” component of the group.
2. users can create a maximum of two groups per filter, and once the second group is added, the dropdown arrow at the “Add filter” will disappear and the user won’t be able to add another group.

If you need to do more complex queries that exceed these limitations, please reach out to your account manager for assistance. They can help you to create custom queries and filters that meet your specific needs.

 

By understanding how to work with each of these functions, you can quickly and easily filter your dataset to find the information that’s most relevant to your analysis. Whether you’re looking for specific records, trying to identify trends, or analyzing patterns, filtering can help you get the answers you need.