For all jupyter notebooks without a pyproject.toml file, conda/mamba has been used. Using Mamba is recommended as it is significantly faster than Conda. When installing mamba, conda is also installed since some commands are not usable in mamba. https://mamba.readthedocs.io/en/latest/installation/mamba-installation.html
For most notebooks an environment can be created with these packages:
mamba create -n bd python=3.11 ipywidgets ipykernel pyarrow openpyxl pandas matplotlib numpy scipy seaborn geopandas shapely scikit-learn
mamba activate bd
mamba install -c conda-forge scikit-learn-intelex
Scikit-learn-intelex is a library that makes scikit-learn faster for x86_64 processors (not just Intel processors).For more information about scikit-learn-intelex, check out this page.
Pyarrow adds support to pandas for Parquet files, openpyxl for Excel.
All other projects use Poetry.
Download the neerslag_ai folder from Teams and unpack it as follows:
Hierbij de code voor radar naar zuiveringseenheden, en hieronder start- stoppeilen van de gemalen. De Bassins worden leeggepompt als stelsel leeg is.
RUC0001 Start 7,1 mNAP Stop 6,6 mNAP RUC0008 Start 5,6 mNAP Stop 5,2 mNAP RUC0013 Start 6,35 mNAP Stop 6 mNAP RUC0014 Start 4,26 mNAP Stop 3,28 mNAP RUC0015 Start 4,58 mNAP Stop 3,94 mNAP RUC0027 Start 6,1 mNAP Stop 5,6 mNAP RUC0030 Start 4,35 mNAP Stop 4,1 mNAP