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DOC: fix typos in missing.rst
xref #16972
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doc/source/missing_data.rst

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@@ -36,7 +36,7 @@ When / why does data become missing?
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Some might quibble over our usage of *missing*. By "missing" we simply mean
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**na** or "not present for whatever reason". Many data sets simply arrive with
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**NA** or "not present for whatever reason". Many data sets simply arrive with
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missing data, either because it exists and was not collected or it never
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existed. For example, in a collection of financial time series, some of the time
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series might start on different dates. Thus, values prior to the start date
@@ -63,12 +63,12 @@ to handling missing data. While ``NaN`` is the default missing value marker for
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reasons of computational speed and convenience, we need to be able to easily
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detect this value with data of different types: floating point, integer,
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boolean, and general object. In many cases, however, the Python ``None`` will
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arise and we wish to also consider that "missing" or "na".
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arise and we wish to also consider that "missing" or "not available" or "NA".
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.. note::
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Prior to version v0.10.0 ``inf`` and ``-inf`` were also
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considered to be "na" in computations. This is no longer the case by
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considered to be "NA" in computations. This is no longer the case by
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default; use the ``mode.use_inf_as_na`` option to recover it.
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.. _missing.isna:
@@ -206,7 +206,7 @@ with missing data.
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Filling missing values: fillna
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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The **fillna** function can "fill in" NA values with non-na data in a couple
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The **fillna** function can "fill in" NA values with non-NA data in a couple
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of ways, which we illustrate:
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**Replace NA with a scalar value**
@@ -220,7 +220,7 @@ of ways, which we illustrate:
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**Fill gaps forward or backward**
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Using the same filling arguments as :ref:`reindexing <basics.reindexing>`, we
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can propagate non-na values forward or backward:
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can propagate non-NA values forward or backward:
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.. ipython:: python
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@@ -540,7 +540,7 @@ String/Regular Expression Replacement
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<http://docs.python.org/2/reference/lexical_analysis.html#string-literals>`__
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if this is unclear.
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Replace the '.' with ``nan`` (str -> str)
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Replace the '.' with ``NaN`` (str -> str)
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.. ipython:: python
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pandas/core/frame.py

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@@ -3213,7 +3213,7 @@ def isna(self):
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def isnull(self):
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return super(DataFrame, self).isnull()
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@Appender(_shared_docs['isna'] % _shared_doc_kwargs)
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@Appender(_shared_docs['notna'] % _shared_doc_kwargs)
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def notna(self):
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return super(DataFrame, self).notna()
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pandas/core/generic.py

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@@ -4534,7 +4534,7 @@ def asof(self, where, subset=None):
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# Action Methods
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_shared_docs['isna'] = """
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Return a boolean same-sized object indicating if the values are na.
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Return a boolean same-sized object indicating if the values are NA.
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See Also
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--------
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_shared_docs['notna'] = """
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Return a boolean same-sized object indicating if the values are
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not na.
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not NA.
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See Also
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--------

pandas/core/indexes/base.py

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@@ -1852,7 +1852,7 @@ def isna(self):
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Returns
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-------
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a boolean array of whether my values are na
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a boolean array of whether my values are NA
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See also
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--------
@@ -1870,7 +1870,7 @@ def notna(self):
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Returns
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-------
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a boolean array of whether my values are not na
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a boolean array of whether my values are not NA
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See also
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--------

pandas/core/series.py

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@@ -2792,7 +2792,7 @@ def isna(self):
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def isnull(self):
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return super(Series, self).isnull()
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@Appender(generic._shared_docs['isna'] % _shared_doc_kwargs)
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@Appender(generic._shared_docs['notna'] % _shared_doc_kwargs)
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def notna(self):
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return super(Series, self).notna()
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