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POpandas DataFrame combine_first and update methods have strange behavior
 

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  1. POpandas DataFrame combine_first and update methods have strange behavior
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    <p>I'm running into a strange issue (or intended?) where <code>combine_first</code> or <code>update</code> are causing values stored as <code>bool</code> to be upcasted into <code>float64</code>s if the argument supplied is not supplying the boolean columns.</p> <p>Example workflow in ipython:</p> <pre><code>In [144]: test = pd.DataFrame([[1,2,False,True],[4,5,True,False]], columns=['a','b','isBool', 'isBool2']) In [145]: test Out[145]: a b isBool isBool2 0 1 2 False True 1 4 5 True False In [147]: b = pd.DataFrame([[45,45]], index=[0], columns=['a','b']) In [148]: b Out[148]: a b 0 45 45 In [149]: test.update(b) In [150]: test Out[150]: a b isBool isBool2 0 45 45 0 1 1 4 5 1 0 </code></pre> <p>Was this meant to be the behavior of the <code>update</code> function? I would think that if nothing was specified that <code>update</code> wouldn't mess with the other columns.</p> <hr> <p><strong>EDIT</strong>: I started tinkering around a little more. The plot thickens. If I insert one more command: <code>test.update([])</code> before running <code>test.update(b)</code>, boolean behavior works at the cost of numbers upcasted as <code>objects</code>. This also applies to DSM's simplified example.</p> <p>Based on <a href="https://github.com/pydata/pandas/blob/master/pandas/core/frame.py#L3830" rel="nofollow">panda's source code</a>, it looks like the reindex_like method is creating a DataFrame of dtype <code>object</code>, while reindex_like <code>b</code> creates a DataFrame of dtype <code>float64</code>. Since <code>object</code> is more general, subsequent operations work with bools. Unfortunately running <code>np.log</code> on the numerical columns will fail with an <code>AttributeError</code>. </p>
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    1. COSimpler example: `df = pd.DataFrame([True, False]); df.update({})`.
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