DescrStatsW.quantile()
statsmodels.stats.weightstats.DescrStatsW.quantile
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DescrStatsW.quantile(probs, return_pandas=True)
[source] -
Compute quantiles for a weighted sample.
Parameters: probs : array-like
A vector of probability points at which to calculate the quantiles. Each element of
probs
should fall in [0, 1].return_pandas : bool
If True, return value is a Pandas DataFrame or Series. Otherwise returns a ndarray.
Returns: quantiles : Series, DataFrame, or ndarray
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If return_pandas = True, returns one of the following:
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- data are 1d,
return_pandas
= True: a Series indexed by the probability points. - data are 2d,
return_pandas
= True: a DataFrame with the probability points as row index and the variables as column index.
- data are 1d,
If
return_pandas
= False, returns an ndarray containing the same values as the Series/DataFrame.Notes
To compute the quantiles, first, the weights are summed over exact ties yielding distinct data values y_1 < y_2 < ..., and corresponding weights w_1, w_2, .... Let s_j denote the sum of the first j weights, and let W denote the sum of all the weights. For a probability point p, if pW falls strictly between s_j and s_{j+1} then the estimated quantile is y_{j+1}. If pW = s_j then the estimated quantile is (y_j + y_{j+1})/2. If pW < p_1 then the estimated quantile is y_1.
References
SAS documentation for weighted quantiles:
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© 2009–2012 Statsmodels Developers
© 2006–2008 Scipy Developers
© 2006 Jonathan E. Taylor
Licensed under the 3-clause BSD License.
http://www.statsmodels.org/stable/generated/statsmodels.stats.weightstats.DescrStatsW.quantile.html