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Nov 22, 2023
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docs: code samples for dataframe.any, dataframe.all and dataframe.prod #223

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docs: code samples for dataframe.any, dataframe.all and dataframe.prod
Genesis929 Nov 20, 2023
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Update examples
Genesis929 Nov 21, 2023
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update example output
Genesis929 Nov 21, 2023
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Merge branch 'main' into huanc-stats-docstring-1
Genesis929 Nov 22, 2023
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85 changes: 84 additions & 1 deletion third_party/bigframes_vendored/pandas/core/frame.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2584,6 +2584,33 @@ def any(self, *, axis=0, bool_only: bool = False):
along a Dataframe axis that is True or equivalent (e.g. non-zero or
non-empty).

**Examples:**

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> df = bpd.DataFrame({"A": [True, True], "B": [False, False]})
>>> df
A B
0 True False
1 True False
<BLANKLINE>
[2 rows x 2 columns]

Checking if each column contains at least one True element(the default behavior without an explicit axis parameter).

>>> df.any()
A True
B False
dtype: boolean

Checking if each row contains at least one True element.

>>> df.any(axis=1)
0 True
1 True
dtype: boolean

Args:
axis ({index (0), columns (1)}):
Axis for the function to be applied on.
Expand All @@ -2604,6 +2631,33 @@ def all(self, axis=0, *, bool_only: bool = False):
along a DataFrame axis that is False or equivalent (e.g. zero or
empty).

**Examples:**

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> df = bpd.DataFrame({"A": [True, True], "B": [False, False]})
>>> df
A B
0 True False
1 True False
<BLANKLINE>
[2 rows x 2 columns]

Checking if all values in each column are True(the default behavior without an explicit axis parameter).

>>> df.all()
A True
B False
dtype: boolean

Checking across rows to see if all values are True.

>>> df.all(axis=1)
0 False
1 False
dtype: boolean

Args:
axis ({index (0), columns (1)}):
Axis for the function to be applied on.
Expand All @@ -2620,8 +2674,37 @@ def prod(self, axis=0, *, numeric_only: bool = False):
"""
Return the product of the values over the requested axis.

**Examples:**

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> df = bpd.DataFrame({"A": [1, 2, 3], "B": [4.5, 5.5, 6.5]})
>>> df
A B
0 1 4.5
1 2 5.5
2 3 6.5
<BLANKLINE>
[3 rows x 2 columns]

Calculating the product of each column(the default behavior without an explicit axis parameter).

>>> df.prod()
A 6.0
B 160.875
dtype: Float64

Calculating the product of each row.

>>> df.prod(axis=1)
0 4.5
1 11.0
2 19.5
dtype: Float64

Args:
aßxis ({index (0), columns (1)}):
axis ({index (0), columns (1)}):
Axis for the function to be applied on.
For Series this parameter is unused and defaults to 0.
numeric_only (bool. default False):
Expand Down