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Fixed #12661: more clarification in the where statement #12671

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Fixed #12661: more clarification in the where statement #12671

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Fixed #12661: more clarification in the where statement
prabhjotsumman Mar 20, 2016
16de918
explanation to where clause
prabhjotsumman Mar 20, 2016
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9 changes: 8 additions & 1 deletion doc/source/10min.rst
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Expand Up @@ -282,7 +282,14 @@ Using a single column's values to select data.

df[df.A > 0]

A ``where`` operation for getting.
A ``where`` is an attribute of the DataFrame class which helps in getting the results
based upon the conditional statement that was passed as an argument.
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So these are not the same at all. I would expand this section and say this is implemented by where internally. Then show an example (and explain the use of where)

In [3]:    dates = pd.date_range('20130101', periods=6)

In [4]:    dates
Out[4]: DatetimeIndex(['2013-01-01', '2013-01-02', '2013-01-03', '2013-01-04', '2013-01-05', '2013-01-06'], dtype='datetime64[ns]', freq='D')

In [5]:    df = pd.DataFrame(np.random.randn(6,4), index=dates, columns=list('ABCD'))

In [6]:    df
Out[6]: 
                   A         B         C         D
2013-01-01 -1.508166 -0.854516  0.148661  1.348457
2013-01-02 -0.890669 -0.329699  0.991305  0.087812
2013-01-03  1.169071 -1.126267 -0.609362 -0.496550
2013-01-04  1.402877 -1.093240  0.038879 -0.042461
2013-01-05 -2.529996  0.570596 -0.556111 -1.365104
2013-01-06  0.036625 -0.241288  0.154433 -1.564450

In [7]: df[df.A>0]
Out[7]: 
                   A         B         C         D
2013-01-03  1.169071 -1.126267 -0.609362 -0.496550
2013-01-04  1.402877 -1.093240  0.038879 -0.042461
2013-01-06  0.036625 -0.241288  0.154433 -1.564450

In [8]: df.where(df>0)
Out[8]: 
                   A         B         C         D
2013-01-01       NaN       NaN  0.148661  1.348457
2013-01-02       NaN       NaN  0.991305  0.087812
2013-01-03  1.169071       NaN       NaN       NaN
2013-01-04  1.402877       NaN  0.038879       NaN
2013-01-05       NaN  0.570596       NaN       NaN
2013-01-06  0.036625       NaN  0.154433       NaN

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"this is implemented by where internally" @jreback I don't think this is needed in the 10min section, which we should keep as a simple intro. But it can maybe be added in the boolean indexing section in the indexing docs

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ok that sounds fine. this is too much for 10min.


.. ipython:: python

df.where(df>0)

It is similar to the statement.

.. ipython:: python

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