Project dependencies may have API risk issues

[PyDeps]

Hi, In mlfinlab, inappropriate dependency versioning constraints can cause risks.

Below are the dependencies and version constraints that the project is using

numpy>=0.16.0
matplotlib>=3.0.0
pandas>=1.0.0
scikit-learn>=0.20.0
scipy>=1.2.0
statsmodels>=0.9.0
cython>=0.29
POT>=0.7.0
numba>=0.40.0
networkx>=2.2<2.6
dash>=1.0.0
dash-cytoscape>=0.1.0
dash-bootstrap-components>=0.10.0
jupyter-dash>=0.2.0
tensorflow>=2.0.0
joblib>=1.0.0
decorator>=4.0.0<5.0.0
analytics-python>=1.2.7
getmac>=0.8.0
codecov==2.1.11
coverage==5.4
pylint==2.6.0
sphinx==3.4.3
hudsonthames-sphinx-theme==0.1.5
sphinx-rtd-theme==0.5.2
releases==1.6.3

The version constraint == will introduce the risk of dependency conflicts because the scope of dependencies is too strict.
The version constraint No Upper Bound and * will introduce the risk of the missing API Error because the latest version of the dependencies may remove some APIs.

After further analysis, in this project,
The version constraint of dependency pandas can be changed to >=0.8.0,<=1.4.2.
The version constraint of dependency numba can be changed to >=0.26.0,<=0.55.2.

The above modification suggestions can reduce the dependency conflicts as much as possible,
and introduce the latest version as much as possible without calling Error in the projects.

The invocation of the current project includes all the following methods.

The calling methods from the pandas

pandas.to_datetime
pandas.Timestamp

The calling methods from the numba

numba.jit
numba.njit

The calling methods from the all methods

pandas.Timestamp
numba.jit
numpy.iinfo
pandas.to_datetime
numba.njit
sys.path.insert
isinstance
super.__init__
os.path.abspath
super
ValueError
numpy.random.RandomState
setuptools.setup

@developer
Could please help me check this issue?
May I pull a request to fix it?
Thank you very much.