title: How to merge pandas.core.series.Series and numpy.int32 to pandas.core.frame.DataFrame?
body: <p>I have a df, On this data, I build some clustering model, and found the labels, the labels I get as an array, now I need the merge the data and labels</p>
  
  <pre><code>data = [['M', 10, 'red','apple'], 
          ['F', 15, 'blue','orange'], 
          ['M', 14, 'blue','apple'],
          ['M', 14, 'blue','apple'], 
          ['F', 14, 'blue','apple'], 
          ['M', 14, 'red',''], 
          ['M', 14, 'blue','banana'], 
          ['', 14, 'blue','apple']] 
  
  df = pd.DataFrame(data, columns = ['Gender', 'Age', 'Color','Fruit']) 
  </code></pre>
  
  <p>df is encoded as numbers, then, the labels is get as</p>
  
  <pre><code>df_encode = OneHotEncoder(df)
  kmeans = KMeans(n_clusters= 2)
  kmeans.fit(df_encode.values)
  labels = kmeans.labels_
  type(labels)
  Out[120]: numpy.ndarray
  labels
  Out[122]: array([1, 0, 1, 0, 1, 1, 0, 0])
  </code></pre>
  
  <p>i view both of them as follows</p>
  
  <pre><code>for i in range(len(df_encode)):
      print("coordinate:",df_encode.iloc[i], "label:", labels[i]) 
  </code></pre>
  
  <p>This gives output like</p>
  
  <pre><code>coordinate: 
  Gender      1.0
  Age        10.0
  Color       0.0
  Fruit       1.0
  label: 0
  </code></pre>
  
  <p>Here how should I merge label as a column in df_encode dataframe?</p>