CSV post-processing

Besides project scripts, QInsight also has an interactive Python console: Tools → Interpreter → Python. It behaves like a regular Python prompt (>>>) and shares the environment with the project scripts — so it sees the variables and everything the scripts have prepared.

📷 Image placeholder — the Python interpreter window.

Typical use: analyzing data exported to CSV.

Example: statistics from an export

>>> import csv
>>> with open(r"DataLogs\export.csv", encoding="utf-8") as f:
...     rows = list(csv.reader(f))[4:]       # skip the header
...     temps = [float(r[1]) for r in rows if r[1]]
...
>>> len(temps), min(temps), max(temps), sum(temps)/len(temps)
(18342, 21.4, 96.8, 64.271...)

With the pandas library installed, the work is even more convenient:

>>> import pandas as pd
>>> df = pd.read_csv(r"DataLogs\export.csv", skiprows=3)
>>> df["Oil temperature"].describe()

The console is available only with Use Python scripts enabled (see Python setup). It uses the Python configured in Preferences — install libraries (pandas, numpy…) into it normally via pip.

Next

The set of drivers, protocols, and controls can be extended with your own — Custom extensions.