How to convert MF4 (MDF4) files to CSV or Excel
An MF4 file is built for loggers, not spreadsheets, so converting one to CSV or Excel takes a few decisions: which channels, which time base and how big the output will be. Here are the free ways to do it, how to do it in Vizalyze, and the pitfalls that catch most people.
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Step by step
Decide which channels you actually need
A logger file can hold thousands of channels, and a CSV with all of them is rarely useful. Write down the handful you need, plus the time range if you only need part of the recording.
Open the MF4 file in Vizalyze
Download the app, sign in for the 14-day trial of every feature and format (no credit card), and use Load to open the .mf4 file. MDF4 support is one of the extension formats, so it is included in the trial.
Pick channels in the Channel Browser
Search by name and select only the channels you need. If the file holds raw CAN frames, assign a DBC (or ARXML, KCD, SYM) database first so the frames become named physical signals.
Resample to a common time base
Channels in an MF4 file are often logged at different rates. Resample the selection to one time step so every column in the table shares the same timestamps. Choose a step that is not coarser than the fastest signal you care about.
Check the result before exporting
Plot a few channels against the originals and look for gaps or flat sections that come from interpolating across missing data.
Export to CSV or Excel
Export the processed table, choosing the delimiter and encoding for CSV. For Excel, keep in mind the worksheet row limit, and prefer CSV for very long recordings.
Free ways to convert MF4
asammdf is an open-source Python library with a free GUI. You can open a file, select channels and export to CSV or Excel from the interface, or script the same thing with the Python API. It is a solid answer if you are comfortable installing Python packages.
CSS Electronics provides free MF4 converters aimed at their own loggers, which turn MF4 into CSV and other formats, and several logger and measurement-hardware vendors ship their own free viewers and export tools. These work well when the file came from that vendor's hardware.
Vizalyze is useful when you want to resample, compare runs or process the data before the CSV, or when you want to do this repeatedly without writing a script. It reads MDF files through the asammdf library.
Pitfalls to watch for
Different sample rates per channel group: an MF4 file stores channels in groups, each with its own time stamps. A naive export either produces several separate tables or fills the gaps, so decide on a common time base on purpose and note which interpolation you used.
Huge files: a long recording at a high sample rate can produce a CSV that is slow to open and may exceed Excel's row limit. Select fewer channels, crop the time range or resample to a coarser step, and keep the original MF4 as the source of truth.
Raw CAN frames need a database: if the logger stored raw frames rather than decoded signals, the export contains arbitration IDs and data bytes, not speeds or temperatures. Assign a DBC file before exporting to get physical values.
Frequently asked questions
Can Excel open an MF4 file directly?
No. MF4 is a binary measurement format, so you need a converter or a viewer to export the channels you want as CSV or Excel first.
Why do my exported channels have different lengths?
Each channel group in an MF4 file has its own time stamps. Unless you resample to a common time base, channels logged at different rates do not line up row by row.
Does converting to CSV lose information?
It can. CSV has no place for channel metadata such as units, comments or conversion rules, and resampling changes the original sample times. Keep the MF4 original.
Do I have to write Python?
No. Vizalyze is a desktop app, so you select channels and export from the interface. Python with asammdf is a free alternative if you prefer scripting.