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Converting String Variables to Numeric in Stata: The encode Command Explained

Discover how to successfully convert string variables to numeric in Stata using the `encode` command while maintaining labels. --- This video is based on the question https://stackoverflow.com/q/78127756/ asked by the user 'user1211188' ( https://stackoverflow.com/u/23560359/ ) and on the answer https://stackoverflow.com/a/78127811/ provided by the user 'Nick Cox' ( https://stackoverflow.com/u/1820446/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions. Visit these links for original content and any more details, such as alternate solutions, comments, revision history etc. For example, the original title of the Question was: Using encode command to convert string variable to numeric Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l... The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license. If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com. --- Converting String Variables to Numeric in Stata: The encode Command Explained When working with datasets in Stata, you may encounter the need to convert string variables to numeric ones. This conversion is essential for efficient data analysis and modeling. A common situation arises when a variable representing education levels is stored as a string, but you want to convert it to numeric while retaining the corresponding labels. In this guide, we'll explore how to use the encode command effectively and troubleshoot a common issue that may arise during the process. Understanding the Problem Imagine you have a dataset with a variable named education, which is represented in string format as follows: "primary" for 0 "secondary" for 1 "tertiary" for 2 After using the encode command, you expect to generate a new numeric variable (education_n) that retains these values as 0s, 1s, and 2s. However, you notice that instead of this expected outcome, the new variable stores the values as 3 for primary, 4 for secondary, and 5 for tertiary. This can be confusing and frustrating. Why is This Happening? The unexpected results stem from Stata's interpretation of the string data. If the string values in your variable don't perfectly match the labels you defined using the label define command, Stata will create new numeric labels starting from the highest number already present. Here’s why this might occur: Leading and Trailing Spaces: If your string variable has extra spaces before or after the text (e.g., " primary "), Stata interprets it differently. Use the trim() function to clean up your data before encoding. Case Sensitivity: Stata is case-sensitive. If your string variable uses upper-case letters (e.g., "Primary"), it won't match the defined labels ("primary"). Always ensure consistency in casing. Steps to Fix the Issue To resolve the problem and obtain the expected numeric values, follow these steps: Check for Spaces: Use the trim() function to eliminate any leading or trailing spaces in the education variable. Here's how you can do it: [[See Video to Reveal this Text or Code Snippet]] Normalize Case: Ensure all entries are in lowercase (or uppercase, depending on your label definition). You can convert the strings to lower case using: [[See Video to Reveal this Text or Code Snippet]] Encode Again: Once you've cleaned the data, you'll need to run the encode command anew: [[See Video to Reveal this Text or Code Snippet]] Validation: Check the new variable to confirm that it now holds the correct values: [[See Video to Reveal this Text or Code Snippet]] Conclusion Converting string variables to numeric in Stata offers numerous advantages, especially when it comes to data analysis. By mindful of the nuances of string encoding—namely, leading/trailing spaces and case sensitivity—you can avoid common pitfalls and successfully retain your intended labels. Following the steps provided will help you achieve the desired output without confusion. Happy coding!