How do I create an empty pandas DataFrame with different data types assigned to each column?
<p><a href="https://stackoverflow.com/questions/30053329/elegant-way-to-create-empty-pandas-dataframe-with-nan-of-type-float">This post</a> provides an elegant way to create an empty pandas DataFrame of a specified data type.  And if you specify np.nan values when you initialize it, the data type is set to float:</p>

<pre><code>df_training_outputs = pd.DataFrame(np.nan, index=index, columns=column_names)
</code></pre>

<p>But I want to create an empty DataFrame with different data types in each column.  It seems the dtype keyword argument will only accept one. </p>

<p>Background: I am writing a script that generates data incrementally and so I need somewhere to store it during the execution of the script.  I thought an empty data frame (large enough to take all the expected data) would be the best way to do this.  This must be a fairly common tasks so if someone has a better way please advise.</p>