title: Multiple Pandas column of lists, want to expand and create a row for each list element
body: <p>I have a dataframe with multiple cells containing lists of multiple values. Rather than storing multiple values in a cell, I'd like to expand the data frame so that each item in the list gets its own row with the same values in all other columns. I have sample code and output attach and the goal I am trying to achieve</p>
  <pre><code>import pandas as pd
  import numpy as np
  df=pd.DataFrame({'OBJECTID':[1,2,3,4,5],
                'CRASH_KEY':[20191088662,20191088664,20191088668,20191088677,20191088678],
                'CASENUMBER':[20191088662,20191088664,20191088668,20191088677,20191088679],
                'routeId':[list(np.random.randn(3).round(2)) for i in range(5)],
                'measure':[list(np.random.randn(3).round(2)) for i in range(5)],
                'SPEED_LIMIT':[list(np.random.randn(3).round(2)) for i in range(5)],
                'distance':[list(np.random.randn(3).round(2)) for i in range(5)],})
  </code></pre>
  <p>df
  my output</p>
  <pre><code>OBJECTID    CRASH_KEY   CASENUMBER  ...                measure           SPEED_LIMIT               distance
   0         1  20191088662  20191088662  ...   [-0.24, -0.78, -0.7]   [-1.28, 0.11, -0.7]   [-0.98, 0.06, -1.07]
   1         2  20191088664  20191088664  ...   [-0.94, -0.98, 1.31]  [-1.26, 1.31, -2.24]  [-1.21, -1.21, -0.35]
   2         3  20191088668  20191088668  ...  [-0.21, -0.99, -0.25]  [-1.36, -0.59, 0.02]   [0.22, -1.36, -0.64]
   3         4  20191088677  20191088677  ...    [0.31, -0.56, 0.95]  [-0.92, -1.04, 0.59]      [1.88, 0.3, 0.95]
   4         5  20191088678  20191088679  ...    [-0.07, 1.02, 2.14]  [-0.49, -0.66, 0.07]   [-0.27, -0.12, 0.36]
  </code></pre>
  <p>This is what I am trying to achieve</p>
  <pre><code>         OBJECTID    CRASH_KEY   CASENUMBER  measure SPEED_LIMIT  distance
      0         1  20191088662  20191088662   -0.24      -1.28    -0.98
      1         1  20191088662  20191088662   -0.78       0.11     0.06
      2         1  20191088662  20191088662    -0.7      -0.7     -1.07
  </code></pre>