title: Interpolate data with multiple columns
body: <p>I am new to Python. I am trying to interpolate data values from a data set that looks like:
  a = [45.0,0.0017317314,-0.00274,...]
  [45.07,0.00173326,-0.002278,...]
  .
  .
  .</p>
  
  <p>I want to find the values of the data from the second to the last column at certain values of the data in the first column.</p>
  
  <p>I have tried the following code:</p>
  
  <pre><code>interp_data = np.interp(45.01,a[:,0],a[:,1])
  </code></pre>
  
  <p>as an initial try to find the value of one data point for one column. However, it returns the error 'object too deep for desired array'</p>
  
  <p>However, the following works in the shell</p>
  
  <pre><code>&gt;&gt;&gt; xp = [45.0, 45.074969417037, 45.224757625296, 45.523726383073]
  
  &gt;&gt;&gt; fp = [1.73145123922036E-002, 1.73326024230735E-002, 1.73689532454203E-002, 1.74423417607930E-002]
  
  &gt;&gt;&gt; import numpy
  
  &gt;&gt;&gt; numpy.interp(45.1, xp, fp)
  
  0.017338676881704793
  </code></pre>
  
  <p>Also, I would like to do this for multiple values as:</p>
  
  <pre><code>for i in range(len(a)):
  
   for j in range(a.shape[1]):
     interp_data = np.interp(values,a[:,j],a[:,j])
  </code></pre>
  
  <p>where values is an array of the data points at which I want to interpolate.</p>