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Jun 14, 2019
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DOC: Fixing some more warnings #26810

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6096434
DOC: Fixing some more warnings
datapythonista Jun 12, 2019
3d43234
Addressing review comments
datapythonista Jun 12, 2019
b8ef9a2
Merge remote-tracking branch 'upstream/master' into doc_warns_2
Jun 13, 2019
bd5afaa
Removing matplotlib converters registration
Jun 13, 2019
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3 changes: 3 additions & 0 deletions doc/source/getting_started/10min.rst
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Expand Up @@ -713,6 +713,9 @@ See the :ref:`Plotting <visualization>` docs.

.. ipython:: python

# register converters to display dates in plots
pd.plotting.register_matplotlib_converters()
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This should not be added, the warning in the log is indicating a recent regression, see #26770


ts = pd.Series(np.random.randn(1000),
index=pd.date_range('1/1/2000', periods=1000))
ts = ts.cumsum()
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2 changes: 2 additions & 0 deletions doc/source/user_guide/advanced.rst
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Expand Up @@ -703,6 +703,8 @@ faster than fancy indexing.
%timeit arr[indexer]
%timeit arr.take(indexer, axis=0)

.. ipython:: python

ser = pd.Series(arr[:, 0])
%timeit ser.iloc[indexer]
%timeit ser.take(indexer)
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5 changes: 0 additions & 5 deletions doc/source/user_guide/cookbook.rst
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Expand Up @@ -1260,24 +1260,19 @@ The `method` argument within `DataFrame.corr` can accept a callable in addition
n = len(x)
a = np.zeros(shape=(n, n))
b = np.zeros(shape=(n, n))

for i in range(n):
for j in range(i + 1, n):
a[i, j] = abs(x[i] - x[j])
b[i, j] = abs(y[i] - y[j])

a += a.T
b += b.T

a_bar = np.vstack([np.nanmean(a, axis=0)] * n)
b_bar = np.vstack([np.nanmean(b, axis=0)] * n)

A = a - a_bar - a_bar.T + np.full(shape=(n, n), fill_value=a_bar.mean())
B = b - b_bar - b_bar.T + np.full(shape=(n, n), fill_value=b_bar.mean())
cov_ab = np.sqrt(np.nansum(A * B)) / n
std_a = np.sqrt(np.sqrt(np.nansum(A**2)) / n)
std_b = np.sqrt(np.sqrt(np.nansum(B**2)) / n)

return cov_ab / std_a / std_b

df = pd.DataFrame(np.random.normal(size=(100, 3)))
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4 changes: 4 additions & 0 deletions doc/source/user_guide/io.rst
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Expand Up @@ -4703,6 +4703,7 @@ See the documentation for `pyarrow <https://arrow.apache.org/docs/python/>`__ an
Write to a parquet file.

.. ipython:: python
:okwarning:
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yeah, this is fine.

Although, we should actually make sure to install the latest version of pyarrow (where this is fixed), but for some reason conda installs 0.11 instead of 0.13


df.to_parquet('example_pa.parquet', engine='pyarrow')
df.to_parquet('example_fp.parquet', engine='fastparquet')
Expand All @@ -4720,6 +4721,7 @@ Read from a parquet file.
Read only certain columns of a parquet file.

.. ipython:: python
:okwarning:

result = pd.read_parquet('example_fp.parquet',
engine='fastparquet', columns=['a', 'b'])
Expand All @@ -4742,6 +4744,7 @@ Serializing a ``DataFrame`` to parquet may include the implicit index as one or
more columns in the output file. Thus, this code:

.. ipython:: python
:okwarning:

df = pd.DataFrame({'a': [1, 2], 'b': [3, 4]})
df.to_parquet('test.parquet', engine='pyarrow')
Expand All @@ -4758,6 +4761,7 @@ If you want to omit a dataframe's indexes when writing, pass ``index=False`` to
:func:`~pandas.DataFrame.to_parquet`:

.. ipython:: python
:okwarning:

df.to_parquet('test.parquet', index=False)

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18 changes: 13 additions & 5 deletions doc/source/user_guide/missing_data.rst
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Expand Up @@ -348,14 +348,21 @@ that, by default, performs linear interpolation at missing data points.
np.random.seed(123456)
idx = pd.date_range('1/1/2000', periods=100, freq='BM')
ts = pd.Series(np.random.randn(100), index=idx)
ts[1:20] = np.nan
ts[1:5] = np.nan
ts[20:30] = np.nan
ts[60:80] = np.nan
ts = ts.cumsum()

.. ipython:: python

ts
ts.count()
@savefig series_before_interpolate.png
ts.interpolate().plot()
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should this be without the interpolate? As the above line is already included a couple of lines below

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good catch, I saw it when reviewing the rendered page, and thought I fixed it, but seems like I didn't


.. ipython:: python

ts.interpolate()
ts.interpolate().count()

@savefig series_interpolate.png
Expand Down Expand Up @@ -435,9 +442,9 @@ Compare several methods:

np.random.seed(2)

ser = pd.Series(np.arange(1, 10.1, .25)**2 + np.random.randn(37))
bad = np.array([4, 13, 14, 15, 16, 17, 18, 20, 29])
ser[bad] = np.nan
ser = pd.Series(np.arange(1, 10.1, .25) ** 2 + np.random.randn(37))
missing = np.array([4, 13, 14, 15, 16, 17, 18, 20, 29])
ser[missing] = np.nan
methods = ['linear', 'quadratic', 'cubic']

df = pd.DataFrame({m: ser.interpolate(method=m) for m in methods})
Expand All @@ -455,7 +462,7 @@ at the new values.
ser = pd.Series(np.sort(np.random.uniform(size=100)))

# interpolate at new_index
new_index = ser.index | pd.Index([49.25, 49.5, 49.75, 50.25, 50.5, 50.75])
new_index = pd.Float64Index(ser.index | pd.Index([49.25, 49.5, 49.75, 50.25, 50.5, 50.75]))
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I would leave this change out.

Yes, it is annoying that it fails, but this should work and is a regression we need to fix (and we actually catched this due to the docs).

If this is the final error that is remaining and blocking that we can start failing CI for errors/warnings in the docs, then we can do that or add a temporary :okexcept:, but we are not there yet I think.

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adding an :okexcept:, I'm trying to make this the last time in my life I fix lots of pandas doc warnings (it's not the first), so hopefully we can add the check soon

interp_s = ser.reindex(new_index).interpolate(method='pchip')
interp_s[49:51]

Expand All @@ -476,6 +483,7 @@ filled since the last valid observation:

ser = pd.Series([np.nan, np.nan, 5, np.nan, np.nan,
np.nan, 13, np.nan, np.nan])
ser

# fill all consecutive values in a forward direction
ser.interpolate()
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4 changes: 0 additions & 4 deletions doc/source/whatsnew/v0.17.0.rst
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Expand Up @@ -5,10 +5,6 @@ v0.17.0 (October 9, 2015)

{{ header }}

.. ipython:: python
:suppress:



This is a major release from 0.16.2 and includes a small number of API changes, several new features,
enhancements, and performance improvements along with a large number of bug fixes. We recommend that all
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4 changes: 0 additions & 4 deletions doc/source/whatsnew/v0.17.1.rst
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Expand Up @@ -5,10 +5,6 @@ v0.17.1 (November 21, 2015)

{{ header }}

.. ipython:: python
:suppress:



.. note::

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