@@ -51,7 +51,7 @@ Creating a ``DataFrame`` by passing a dict of objects that can be converted to s
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' F' : ' foo' })
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df2
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- The columns of the resulting ``DataFrame `` have different
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+ The columns of the resulting ``DataFrame `` have different
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:ref: `dtypes <basics.dtypes >`.
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.. ipython :: python
@@ -65,7 +65,7 @@ will be completed:
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.. ipython ::
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@verbatim
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- In [1]: df2.<TAB>
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+ In [1]: df2.<TAB> # noqa: E225, E999
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df2.A df2.bool
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df2.abs df2.boxplot
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df2.add df2.C
@@ -495,7 +495,7 @@ Another example that can be given is:
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Append
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~~~~~~
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- Append rows to a dataframe. See the :ref: `Appending <merging.concatenation >`
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+ Append rows to a dataframe. See the :ref: `Appending <merging.concatenation >`
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section.
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.. ipython :: python
@@ -528,14 +528,14 @@ See the :ref:`Grouping section <groupby>`.
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' D' : np.random.randn(8 )})
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df
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- Grouping and then applying the :meth: `~DataFrame.sum ` function to the resulting
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+ Grouping and then applying the :meth: `~DataFrame.sum ` function to the resulting
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groups.
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.. ipython :: python
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df.groupby(' A' ).sum()
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- Grouping by multiple columns forms a hierarchical index, and again we can
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+ Grouping by multiple columns forms a hierarchical index, and again we can
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apply the ``sum `` function.
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.. ipython :: python
@@ -671,7 +671,7 @@ Convert the raw grades to a categorical data type.
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df[" grade" ] = df[" raw_grade" ].astype(" category" )
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df[" grade" ]
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- Rename the categories to more meaningful names (assigning to
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+ Rename the categories to more meaningful names (assigning to
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``Series.cat.categories `` is inplace!).
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.. ipython :: python
@@ -720,7 +720,7 @@ See the :ref:`Plotting <visualization>` docs.
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@savefig series_plot_basic.png
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ts.plot()
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- On a DataFrame, the :meth: `~DataFrame.plot ` method is a convenience to plot all
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+ On a DataFrame, the :meth: `~DataFrame.plot ` method is a convenience to plot all
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of the columns with labels:
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.. ipython :: python
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