title: Initialize empty Pandas series and conditionally add to it
body: <p>I have a pandas DataFrame named <code>X</code> as shown below. </p>
  
  <pre><code>X = pd.DataFrame({
      'month_1': [1, 0, 0, 0, 0],
      'month_2': [0, 1, 0, 0, 0],
      'age': [1, 2, 3, 4, 5]
  })
  months = X['month_1'] + X['month_2']
  age = X['age']
  </code></pre>
  
  <p>I want to create an equation that adds up series from <code>X</code> based on whether that term from <code>keep</code> is True or False. The code below works. </p>
  
  <pre><code>keep={'seasonality':True, 'age':True}
  
  equation = months
  if keep['age']:
      equation = equation + age
  
  print(equation)
  
  0    2
  1    3
  2    3
  3    4
  4    5
  dtype: int64
  </code></pre>
  
  <p>However, I can't get it to work if I initialize <code>equation</code> with an empty series and then add terms based on <code>keep</code>. When I try to do this I get NaN values. How can I do this?</p>
  
  <pre><code>keep={'seasonality':True, 'age':True}
  
  equation = pd.Series([])
  if keep['seasonality']:
      equation = equation + months
  if keep['age']:
      equation = equation + age
  
  print(equation)
  
  0   NaN
  1   NaN
  2   NaN
  3   NaN
  4   NaN
  dtype: float64
  </code></pre>