pandas.DataFrame.quantile#

DataFrame.quantile(q=0.5,axis=0,numeric_only=False,interpolation='linear',method='single')[source]#

Return values at the given quantile over requested axis.

Parameters:

qfloat or array-like, default 0.5 (50% quantile)

Value between 0 <= q <= 1, the quantile(s) to compute.

axis{0 or ‘index’, 1 or ‘columns’}, default 0

Equals 0 or ‘index’ for row-wise, 1 or ‘columns’ for column-wise.

numeric_onlybool, default False

Include onlyfloat,int orboolean data.

Changed in version 2.0.0:The default value ofnumeric_only is nowFalse.

interpolation{‘linear’, ‘lower’, ‘higher’, ‘midpoint’, ‘nearest’}

This optional parameter specifies the interpolation method to use,when the desired quantile lies between two data pointsi andj:

• linear:i + (j - i) * fraction, wherefraction is thefractional part of the index surrounded byi andj.

• lower:i.

• higher:j.

• nearest:i orj whichever is nearest.

• midpoint: (i +j) / 2.

method{‘single’, ‘table’}, default ‘single’

Whether to compute quantiles per-column (‘single’) or over all columns(‘table’). When ‘table’, the only allowed interpolation methods are‘nearest’, ‘lower’, and ‘higher’.

Returns:

Series or DataFrame

Ifq is an array, a DataFrame will be returned where the

index isq, the columns are the columns of self, and thevalues are the quantiles.

Ifq is a float, a Series will be returned where the

index is the columns of self and the values are the quantiles.

See also

core.window.rolling.Rolling.quantile

Rolling quantile.

numpy.percentile

Numpy function to compute the percentile.

Examples

>>>df=pd.DataFrame(np.array([[1,1],[2,10],[3,100],[4,100]]),...columns=['a','b'])>>>df.quantile(.1)a    1.3b    3.7Name: 0.1, dtype: float64>>>df.quantile([.1,.5])       a     b0.1  1.3   3.70.5  2.5  55.0

Specifyingmethod=’table’ will compute the quantile over all columns.

>>>df.quantile(.1,method="table",interpolation="nearest")a    1b    1Name: 0.1, dtype: int64>>>df.quantile([.1,.5],method="table",interpolation="nearest")     a    b0.1  1    10.5  3  100

Specifyingnumeric_only=False will also compute the quantile ofdatetime and timedelta data.

>>>df=pd.DataFrame({'A':[1,2],...'B':[pd.Timestamp('2010'),...pd.Timestamp('2011')],...'C':[pd.Timedelta('1 days'),...pd.Timedelta('2 days')]})>>>df.quantile(0.5,numeric_only=False)A                    1.5B    2010-07-02 12:00:00C        1 days 12:00:00Name: 0.5, dtype: object