@@ -2711,6 +2711,31 @@ def argmax(self):
27112711
27122712 If the minimum is achieved in multiple locations, the first row position is returned.
27132713
2714+ **Examples:**
2715+
2716+ >>> import bigframes.pandas as bpd
2717+ >>> bpd.options.display.progress_bar = None
2718+
2719+ Consider dataset containing cereal calories.
2720+
2721+ >>> s = bpd.Series({'Corn Flakes': 100.0, 'Almond Delight': 110.0,
2722+ ... 'Cinnamon Toast Crunch': 120.0, 'Cocoa Puff': 110.0})
2723+ >>> s
2724+ Corn Flakes 100.0
2725+ Almond Delight 110.0
2726+ Cinnamon Toast Crunch 120.0
2727+ Cocoa Puff 110.0
2728+ dtype: Float64
2729+
2730+ >>> s.argmax()
2731+ 2
2732+
2733+ >>> s.argmin()
2734+ 0
2735+
2736+ The maximum cereal calories is the third element and the minimum cereal
2737+ calories is the first element, since series is zero-indexed.
2738+
27142739 Returns:
27152740 Series: Row position of the maximum value.
27162741 """
@@ -2722,6 +2747,31 @@ def argmin(self):
27222747
27232748 If the maximum is achieved in multiple locations, the first row position is returned.
27242749
2750+ **Examples:**
2751+
2752+ >>> import bigframes.pandas as bpd
2753+ >>> bpd.options.display.progress_bar = None
2754+
2755+ Consider dataset containing cereal calories.
2756+
2757+ >>> s = bpd.Series({'Corn Flakes': 100.0, 'Almond Delight': 110.0,
2758+ ... 'Cinnamon Toast Crunch': 120.0, 'Cocoa Puff': 110.0})
2759+ >>> s
2760+ Corn Flakes 100.0
2761+ Almond Delight 110.0
2762+ Cinnamon Toast Crunch 120.0
2763+ Cocoa Puff 110.0
2764+ dtype: Float64
2765+
2766+ >>> s.argmax()
2767+ 2
2768+
2769+ >>> s.argmin()
2770+ 0
2771+
2772+ The maximum cereal calories is the third element and the minimum cereal
2773+ calories is the first element, since series is zero-indexed.
2774+
27252775 Returns:
27262776 Series: Row position of the minimum value.
27272777 """
@@ -2971,6 +3021,19 @@ def is_monotonic_increasing(self) -> bool:
29713021 """
29723022 Return boolean if values in the object are monotonically increasing.
29733023
3024+ **Examples:**
3025+
3026+ >>> import bigframes.pandas as bpd
3027+ >>> bpd.options.display.progress_bar = None
3028+
3029+ >>> s = bpd.Series([1, 2, 2])
3030+ >>> s.is_monotonic_increasing
3031+ True
3032+
3033+ >>> s = bpd.Series([3, 2, 1])
3034+ >>> s.is_monotonic_increasing
3035+ False
3036+
29743037 Returns:
29753038 bool: Boolean.
29763039 """
@@ -2981,6 +3044,19 @@ def is_monotonic_decreasing(self) -> bool:
29813044 """
29823045 Return boolean if values in the object are monotonically decreasing.
29833046
3047+ **Examples:**
3048+
3049+ >>> import bigframes.pandas as bpd
3050+ >>> bpd.options.display.progress_bar = None
3051+
3052+ >>> s = bpd.Series([3, 2, 2, 1])
3053+ >>> s.is_monotonic_decreasing
3054+ True
3055+
3056+ >>> s = bpd.Series([1, 2, 3])
3057+ >>> s.is_monotonic_decreasing
3058+ False
3059+
29843060 Returns:
29853061 bool: Boolean.
29863062 """
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