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Correct some typos #142

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Apr 21, 2023
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Correct some typos #142

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4 changes: 2 additions & 2 deletions docs/bestpractice.rst
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Expand Up @@ -6,7 +6,7 @@ We recommend seeking guidance from a statistician when using :py:mod:`tableone`
Data visualization
------------------

Plotting the distribution of each variable by group level via histograms, kernel density estimates and boxplots is a crucial component to data analysis pipelines. Vizualisation is often is the only way to detect problematic variables in many real-life scenarios. Some example plots are provided in the `tableone notebook <https://github.com/tompollard/tableone/blob/master/tableone.ipynb>`_.
Plotting the distribution of each variable by group level via histograms, kernel density estimates and boxplots is a crucial component to data analysis pipelines. Visualisation is often is the only way to detect problematic variables in many real-life scenarios. Some example plots are provided in the `tableone notebook <https://github.com/tompollard/tableone/blob/master/tableone.ipynb>`_.

Normally distributed variables
------------------------------
Expand Down Expand Up @@ -91,4 +91,4 @@ It should be noted that while we have tried to use best practices, automation of

.. [12] Šidák, Z. K. (1967). "Rectangular Confidence Regions for the Means of
Multivariate Normal Distributions". Journal of the American Statistical
Association. 62 (318): 626–633.
Association. 62 (318): 626–633.
2 changes: 1 addition & 1 deletion docs/contributing.rst
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Expand Up @@ -46,7 +46,7 @@ reStructuredText <http://sphinx.pocoo.org/rest.html>`__.
The documentation follows the
`NumPy Docstring Standard <https://github.com/numpy/numpy/blob/master/doc/HOWTO_DOCUMENT.rst.txt>`__,
which are parsed using the
`napolean extension for sphinx <http://www.sphinx-doc.org/en/1.5.1/ext/napoleon.html>`.
`napoleon extension for sphinx <http://www.sphinx-doc.org/en/1.5.1/ext/napoleon.html>`.

How to build the documentation
------------------------------
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2 changes: 1 addition & 1 deletion tableone/modality.py
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Expand Up @@ -769,7 +769,7 @@ def dip_and_closest_unimodal_from_cdf(xF, yF, plotting=False, verbose=False, eps
iH = np.arange(L, U+1)[iHH]

# Interpolate. First and last point are in both and does not need
# interpolation. Might cause trouble if included due to possiblity
# interpolation. Might cause trouble if included due to possibility
# of infinity slope at beginning or end of interval.
if iG[0] != iH[0] or iG[-1] != iH[-1]:
raise ValueError('Convex minorant and concave majorant should start and end at same points.')
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