To count distinct tags or words in a CSV column, open Perform calculation in Datablist, choose Count distinct values, and select the separator used inside each cell. The result lists each distinct value and its occurrence count.
For example, a cell containing sales, marketing contributes one occurrence to sales and one to marketing. Counting the entire cell instead would treat sales, marketing as a single value.
If your goal is to turn those comma-separated tags or emails into one value per row, use the CSV Rows Splitter before analyzing the file.
How many distinct words are in my CSV file?
Step 1: Import Your CSV or Excel File
Import your CSV or Excel file into Datablist and check that the tags appear in one column. See the CSV import guide if your file uses a different delimiter.
In the Datablist Application, create a new collection (using the "+" in the sidebar) to load your CSV file.
Follow the import wizard to get your CSV data in Datablist.
Step 2: Open the Calculation tool
Once the import is done, click on the column you want to count words in. Select Perform calculation.
The "Calculation" tool opens. Datablist provides several calculation algorithms.
For text columns:
- Count distinct values
- Total Words Count - Sum of all words
- Characters Count - Sum of all characters
For numeric columns:
Step 3: Count Distinct Words with or without a separator
Select Count distinct values. Under Splitting Rule, choose Split cell values by comma for comma-separated tags. Use Run on whole cell values when each cell contains one category or identifier.
Other splitting rules use a space, semicolon, dot, or custom separator. Choose the separator used within your column values, which may differ from the delimiter used to separate CSV columns.
Case-sensitive is off by default, so Sales and sales are counted together. Spaces around each split value are removed. Enable this option when capitalization distinguishes your values.
Then click Run calculation to start the process. A list of results appears in the drawer.
Step 4: Review
Review the analysis results directly within Datablist. For each term, a shortcut button appears on mouse hover to create a filter.
Occurrences are not the number of rows containing a tag
Suppose your Tags column contains these three cells:
| Row | Tags |
|---|---|
| 1 | sales, marketing |
| 2 | Sales, sales |
| 3 | marketing , support |
With comma splitting and Case-sensitive off, the result has three distinct tags: sales with 3 occurrences, marketing with 2, and support with 1. Row 2 contributes two occurrences of sales. Only two rows contain that tag.
Use this calculation for tag frequency. If you need the number of records containing a tag, review the matching rows instead of treating the occurrence count as a row count.
The splitter uses the separator literally. If a tag itself contains a comma, comma splitting will divide that tag too. CSV quoting protects a field during import; it does not make commas inside the imported cell special to this calculation. Use a different internal separator or clean the tags first.
When is Counting Distinct Words useful
Counting distinct words is useful for several tasks:
- Analyze tags in a product catalog - Example: A Tags column in a product catalog might contain values like "electronics, gadgets, accessories". Using the "Distinct words" feature gives you a summary of occurrences for each tag across the products.
- Text Analysis - Helps in text mining, sentiment analysis, and understanding frequency patterns. Example: Consider a survey asking for user opinions. Counting distinct words in the feedback column helps identify common sentiments and themes.
- Data Normalization - Identifies and reduces redundancy in datasets.
- Content Creation - Assists in keyword research and content optimization.