Pandas interpolate within a groupby
<p>I've got a dataframe with the following information:</p>

<pre><code>    filename    val1    val2
t                   
1   file1.csv   5       10
2   file1.csv   NaN     NaN
3   file1.csv   15      20
6   file2.csv   NaN     NaN
7   file2.csv   10      20
8   file2.csv   12      15
</code></pre>

<p>I would like to interpolate the values in the dataframe based on the indices, <strong>but only within each file group</strong>.</p>

<p>To interpolate, I would normally do</p>

<pre><code>df = df.interpolate(method="index")
</code></pre>

<p>And to group, I do</p>

<pre><code>grouped = df.groupby("filename")
</code></pre>

<p>I would like the interpolated dataframe to look like this:</p>

<pre><code>    filename    val1    val2
t                   
1   file1.csv   5       10
2   file1.csv   10      15
3   file1.csv   15      20
6   file2.csv   NaN     NaN
7   file2.csv   10      20
8   file2.csv   12      15
</code></pre>

<p>Where the NaN's are still present at t = 6 since they are the first items in the file2 group.</p>

<p>I suspect I need to use "apply", but haven't been able to figure out exactly how...</p>

<pre><code>grouped.apply(interp1d)
...
TypeError: __init__() takes at least 3 arguments (2 given)
</code></pre>

<p>Any help would be appreciated.</p>