# Data
numpy>=1.19.1
pandas>=1.1.0
scipy>=1.6.0

# Graphs + visualization
networkx>=2.4
pydotplus>=2.0.2
graphviz>=0.13.2


# Vizualisation
matplotlib>=3.4.3
seaborn>=0.11.0
ipython~=7.26.0
plotly>=5.2.1
# needed for plotly:
grandalf==0.7

# ML common
scikit-learn>=0.24.2


statsmodels>=0.9.0
mlxtend~=0.18.0
cvxopt>=1.2.6

dataclasses~=0.6

imbalanced-learn>=0.8.0
colorama>=0.4.4
pyod>=0.9.2

# needed for pyod:
combo
tqdm>=4.62.2
shap>=0.40.0
sqldf~=0.4.2

sklearn~=0.0