5 examples of 'pandas max' in Python

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137def max(x):
138 # x == N_aug x B x N_cls (x H x W)
139 return x.max(0, False).values
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33def max(self):
34 return self._max
60def max(self, **kwargs):
61 return self.data.max(**kwargs)
89@plot_function
90def max_(x: Union[pd.Series, List[pd.Series]], w: Union[Window, int] = Window(None, 0)) -> pd.Series:
91 """
92 Maximum value of series over given window
93
94 :param x: series: a timeseries or an array of timeseries
95 :param w: Window or int: size of window and ramp up to use. e.g. Window(22, 10) where 22 is the window size
96 and 10 the ramp up value. Window size defaults to length of series.
97 :return: timeseries of maximum value
98
99 **Usage**
100
101 Returns the maximum value of the series over each window.
102
103 If :math:`x` is a series:
104
105 :math:`R_t = max(X_{t-w+1}:X_t)`
106
107 where :math:`w` is the size of the rolling window.
108
109 If :math:`x` is an array of series:
110
111 :math:`R_t = max(X_{1, t-w+1}:X_{n, t})`
112
113 where :math:`w` is the size of the rolling window, and :math:`n` is the number of series.
114
115 If window is not provided, returns the maximum value over the full series. If the window size is greater than the
116 available data, will return maximum of available values.
117
118 **Examples**
119
120 Maximum value of price series over the last :math:`22` observations:
121
122 >>> prices = generate_series(100)
123 >>> max_(prices, 22)
124
125 **See also**
126
127 :func:`min_`
128
129 """
130 if isinstance(x, list):
131 x = pd.concat(x, axis=1).max(axis=1)
132 w = normalize_window(x, w)
133 assert x.index.is_monotonic_increasing, "series index is monotonic increasing"
134 if isinstance(w.w, pd.DateOffset):
135 values = [x.loc[(x.index > idx - w.w) & (x.index <= idx)].max() for idx in x.index]
136 return apply_ramp(pd.Series(values, index=x.index, dtype=np.dtype(float)), w)
137 else:
138 return apply_ramp(x.rolling(w.w, 0).max(), w)
90def max(self):
91 self._entry()
92 res = self._rdd.max()
93 return res

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