Filtering phone numbers from a specific country, such as El Salvador, can be easily handled using Python libraries. El Salvador’s phone numbers typically start with the country code +503 and contain 8 digits after the code. Identifying these numbers programmatically can be useful in data cleaning, customer segmentation, or communication targeting. Python offers powerful tools like phonenumbers, re (regular expressions), and pandas to process and filter such data from raw input files or databases.
One of the most reliable tools for this task is the phonenumbers library, a Python port of Google’s libphonenumber. This library helps validate, format, and parse el-salvador phone number list phone numbers. To filter for El Salvador numbers, you can load your dataset, parse each number, and check if the region is identified as "SV" (El Salvador). For example:
This function will return True for valid El Salvador numbers and ignore invalid or foreign entries.
Alternatively, if your dataset is unstructured or if you want a faster approach without installing extra libraries, regular expressions (regex) can be used. A simple regex pattern to match El Salvador numbers might look like this: r"\+503\s?\d{4}[-\s]?\d{4}". This will match strings starting with +503 followed by 8 digits, optionally separated by a space or hyphen. Here's a quick example using the re module:
This method is lighter but less intelligent—it won't validate the phone number like the phonenumbers library does.
For large datasets, especially in CSV or Excel files, pandas can help process and filter entries. You can apply the validation function across a DataFrame column:
This gives you a clean subset of valid El Salvador numbers ready for further analysis or export. In conclusion, whether you prefer smart validation with phonenumbers or quick filtering with regex, Python offers flexible options to clean and extract country-specific phone numbers with ease.