When you purchase or download a global database from our platform, you will find that most of our datasets are provided in three universal file formats: .XLSX, .CSV, and .TXT. For the vast majority of tasks—like simply viewing, searching, or manually editing your data—we highly recommend using the .XLSX file.
However, depending on your project needs, you might want to use the other file types. To help you choose the best format for your workflow, here is a simple breakdown of how each file works, how to open them, and how to avoid common formatting mistakes.
XLSX (Microsoft Excel Spreadsheet)
What Makes It Great:
User-Friendly: This is the most intuitive format for manual viewing. Everything is laid out in a clean visual grid right away.
Rich Formatting: It supports useful spreadsheet features like font styles, column colors, and built-in text filtering.
Advanced Tools: You can easily run mathematical formulas, create data pivot tables, or build charts directly within the sheet.
How to Open It:
Open it directly on your desktop using Microsoft Excel or WPS Office.
Upload and edit it online using Google Sheets.
If you are a developer, you can also read and process it programmatically using specialized libraries.
Best Used For:
This format is ideal when you need to manually inspect rows of postal codes, look up specific regions, create internal reports, or spot-check address data without touching a line of code.
CSV (Comma-Separated Values)
What Makes It Great:
Simple Structure: A CSV file is just plain text. Every single row represents one record, and the different pieces of information (like city name and postal code) are separated by a basic comma.
Highly Universal: Almost every database manager, data analysis tool, or coding language on earth can read a CSV file perfectly.
Lightweight: Because it strips away all visual styling, the file size is incredibly small. This makes it perfect for handling massive datasets with hundreds of thousands of rows.
How to Open It:
Open it instantly with plain text tools like Notepad.
Ingest it into spreadsheet applications like Microsoft Excel or Google Sheets for filtering.
Directly import it into relational database platforms.
Best Used For:
CSV files are the industry standard for data exchange. If you need to move bulk data out of our files and seed it into your own database or online application backend, CSV is the fastest option. It is also perfect for loading data into data analysis tools like R or Python.
TXT (Plain Text)
What Makes It Great:
Maximum Freedom: Like CSV, a TXT file is raw, unstyled text. However, it doesn't force a strict comma layout, allowing for custom spacing or delimiters.
Zero Corruption: Plain text files never lock you out due to proprietary file damage or software version issues. They are completely readable on any device.
How to Open It:
Use any text utility or code editor installed on your system, such as Notepad, TextEdit, or Visual Studio Code.
Best Used For:
TXT files serve as an excellent fallback layer for custom scripts (like Python parsing tools). They are also ideal for storing simple text configurations, system logs, or displaying clean, human-readable reference data where strict database columns aren't mandatory.
Critical Setup Warning: Watch Your Encodings and Text Types
While flat files are highly compatible, opening large international datasets can occasionally cause visual errors if your software settings are wrong. Keep these two rules in mind:
1. The Language Encoding Trap (Fixing Chaotic Symbols)
Because we provide data for over 100 different nations, our files use UTF-8 text encoding to preserve international characters, foreign language text, and local regional accents. If you open a file and see unreadable, corrupted text symbols, the data is not broken. Your spreadsheet software is simply trying to read it using an old default local region setting (like ANSI). To fix this, always choose UTF-8 in your program's file import wizard. For highly specific regional languages, make sure to cross-reference the text guidelines included in your product documentation.
2. The Dropped Zeroes Trap (Fixing Postal Code Errors)
By default, programs like Microsoft Excel try to guess your data types. If a column contains only numbers, Excel will treat it as a standard "Number" rather than "Text." This creates a massive problem for postal codes. For example, if a postal code is 0100, Excel's default math logic will strip away the leading zero and display it incorrectly as 100. To prevent this data loss, always format your postal code columns as "Text" rather than "Numbers" during the file import process.