Replace iterrows() with itertuples() for better performance

[SaFE-APIOpt]

howto-optimize-co2-footprint-cloud-application-in-azure/src/Auswertung/main.py

Line 32 in e7d5df7

for index, row in x.iterrows():

Current code:

for index, row in x.iterrows():
    ...

Recommended replacement:

for row in x.itertuples(index=True):
    ...

Using iterrows() returns each row as a Pandas Series, which introduces overhead from object creation, type inference, and dictionary-based access. Every row iteration allocates a new Series object and resolves columns via dynamic indexing, which can become a major performance bottleneck when iterating over large DataFrames.

On the other hand, itertuples() yields each row as a lightweight namedtuple, constructed in Cython. This avoids unnecessary object overhead and allows fast, attribute-style access to columns. It is significantly faster and more memory-efficient than iterrows(), making it the preferred method for row-wise access when mutation is not required.