5 examples of 'pandas max' in Python

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def max(x):
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    # x == N_aug x B x N_cls (x H x W)
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    return x.max(0, False).values

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def max(self):
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    return self._max

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def max(self, **kwargs):
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    return self.data.max(**kwargs)

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@plot_function
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def max_(x: Union[pd.Series, List[pd.Series]], w: Union[Window, int] = Window(None, 0)) -> pd.Series:
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    """
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    Maximum value of series over given window
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    :param x: series: a timeseries or an array of timeseries
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    :param w: Window or int: size of window and ramp up to use. e.g. Window(22, 10) where 22 is the window size
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              and 10 the ramp up value. Window size defaults to length of series.
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    :return: timeseries of maximum value
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    **Usage**
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    Returns the maximum value of the series over each window.
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    If :math:`x` is a series:
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    :math:`R_t = max(X_{t-w+1}:X_t)`
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    where :math:`w` is the size of the rolling window.
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    If :math:`x` is an array of series:
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    :math:`R_t = max(X_{1, t-w+1}:X_{n, t})`
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    where :math:`w` is the size of the rolling window, and :math:`n` is the number of series.
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    If window is not provided, returns the maximum value over the full series. If the window size is greater than the
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    available data, will return maximum of available values.
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    **Examples**
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    Maximum value of price series over the last :math:`22` observations:
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    >>> prices = generate_series(100)
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    >>> max_(prices, 22)
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    **See also**
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    :func:`min_`
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    """
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    if isinstance(x, list):
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        x = pd.concat(x, axis=1).max(axis=1)
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    w = normalize_window(x, w)
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    assert x.index.is_monotonic_increasing, "series index is monotonic increasing"
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    if isinstance(w.w, pd.DateOffset):
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        values = [x.loc[(x.index > idx - w.w) & (x.index <= idx)].max() for idx in x.index]
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        return apply_ramp(pd.Series(values, index=x.index, dtype=np.dtype(float)), w)
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    else:
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        return apply_ramp(x.rolling(w.w, 0).max(), w)

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def max(self):
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    self._entry()
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    res = self._rdd.max()
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    return res