Here are some typical data manipulation tasks you can do in Querri
You'll find very often when working with data that you need to "fix" some things before your graphs and analysis start to make sense, or just because you're moving that data around. Here are some examples of the types of things you can do in Querri to handle data cleanliness issues.-
Filtering Rows — Extract specific data based on criteria.
- e.g., "Can you show me all transactions over $1,000 from last month?"
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Selecting Columns — Isolate specific fields or attributes.
- e.g., "I only want to see the customer names and their purchase totals."
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Grouping and Aggregation — Summarize data based on categories.
- e.g., "What's the average monthly spend for each of our customer segments?"
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Pivot Tables — Reorganize data for a different view.
- e.g., "Can you display monthly sales data with products as columns and regions as rows?"
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Merging Data — Combine information from different sources.
- e.g., "Join the customer data with their recent purchase history."
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Handling Missing Values — Address gaps in the data.
- e.g., "Replace any missing values in the product ratings with the average rating."
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Data Transformation — Adjust data values or create new fields.
- e.g., "Create a new column showing profit margins based on revenue and cost columns."
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Sorting Data — Arrange data in a particular order.
- e.g., "List products in descending order based on total sales."
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Renaming Columns — Update column headers or names.
- e.g., "Change the column name from 'CustomerID' to 'Client ID'."
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Setting Index — Designate a specific column as a reference for rows.
- e.g., "Use the 'Transaction ID' as the main index for the sales data."
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Date Parsing and Manipulation — Convert and work with date and time fields.
- e.g., "Extract the month and year from the 'Purchase Date' column to analyze monthly trends."
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String Manipulation — Alter text-based data.
- e.g., "Split the 'Full Name' column into two separate columns for 'First Name' and 'Last Name'."