title: multiple array to dataframe pandas
body: <p>So, I am iterating through a dictionary and taking a bunch of values out as a array -  Trying to make a Dataframe with each observation as a separate row.</p>
  <pre><code>X1 =[]
  for k,v in DF_grp:
      date = v['Date'].astype(datetime)
      usage = v['Usage'].astype(float)
      comm = v['comm'].astype(float)
      mdf = pd.DataFrame({'Id' : k[0],'date':date,'usage':usage, 'comm':comm})
      mdf['used_ratio'] = ((mdf['used']/mdf['comm']).round(2))*100
      ts = pd.Series(mdf['usage'].values, index=mdf['date']).sort_index(ascending=True)
      ts2 = pd.Series(mdf['used_ratio'].values, index = mdf['date']).sort_index(ascending=True)
      ts2 = ts2.dropna()
      data = ts2.values.copy()
      if len(data) == 10:
          X1 =np.append(X1,data, axis=0)
          print(X1)
  
  [0,0,0,0,1,0,0,0,1]
  [1,2,3,4,5,6,7,8,9]
  [0,5,6,7,8,9,1,2,3]
  ....
  </code></pre>
  <p>similarly, so the question is how do I capture all these arrays in a single DataFrame so that it looks like below:</p>
  <pre><code>[[0,0,0,0,1,0,0,0,1]] --- #row 1 in dataframe 
  [[1,2,3,4,5,6,7,8,9]] --- #row 2 in dataframe
  </code></pre>
  <p>If the same task can be divided further ?
  There are more thank 500K arrays in the dataset.
  Thank You</p>