* Stefan Blumentrath <[email protected]> [2018-08-23 07:23:12 +0000]:
Dear Nikos, Can you give us a bit more context? What is it you want to achieve? How are you using r.stats and what is it you want to do with the output? Personally, I am not too familiar with performance implications of NumPy vs. plain Python, but rather use NumPy for convenience in matrix/table operations (avoiding pandas)...
```
for category in categories:
statistics_filename = prefix + '_' + category
r.stats(input=(base,reclassified),
output=statistics_filename,
flags='ncapl',
separator=',',
quiet=True)
```
Instead, I want to (modify the above so as to) collect/direct all
iterations in one output file.
The question, finally, seems to be: use Python's 'csv' library or prefer
NumPy? The number of records might reach tens of thousands (or more).
Nikos
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