pandas.DataFrame.quantile¶
- DataFrame.quantile(q=0.5, axis=0, numeric_only=True, interpolation='linear')¶
Return values at the given quantile over requested axis, a la numpy.percentile.
Parameters: q : float or array-like, default 0.5 (50% quantile)
0 <= q <= 1, the quantile(s) to compute
axis : {0, 1, ‘index’, ‘columns’} (default 0)
0 or ‘index’ for row-wise, 1 or ‘columns’ for column-wise
interpolation : {‘linear’, ‘lower’, ‘higher’, ‘midpoint’, ‘nearest’}
New in version 0.18.0.
This optional parameter specifies the interpolation method to use, when the desired quantile lies between two data points i and j:
- linear: i + (j - i) * fraction, where fraction is the fractional part of the index surrounded by i and j.
- lower: i.
- higher: j.
- nearest: i or j whichever is nearest.
- midpoint: (i + j) / 2.
Returns: quantiles : Series or DataFrame
- If q is an array, a DataFrame will be returned where the index is q, the columns are the columns of self, and the values are the quantiles.
- If q is a float, a Series will be returned where the index is the columns of self and the values are the quantiles.
Examples
>>> df = DataFrame(np.array([[1, 1], [2, 10], [3, 100], [4, 100]]), columns=['a', 'b']) >>> df.quantile(.1) a 1.3 b 3.7 dtype: float64 >>> df.quantile([.1, .5]) a b 0.1 1.3 3.7 0.5 2.5 55.0