title: Pyspark equivalent of pandas all fuction
body: <p>I have a spark dataframe df:</p>
  <pre><code>   A    B     C     D
   True  True  True  True
   True  False True  True
   True  None  True  None
   True  NaN   NaN   False
   True  NaN   True  True
  </code></pre>
  <p>Is there a way in pyspark to get a fifth column based on rows A, B, C, D not having the value False in them but returning an int value or 1 for True and 0 for false. Hence:</p>
  <pre><code>   A    B     C     D     E
   True  True  True  True   1
   True  False True  True   0
   True  None  True  None   1
   True  NaN   NaN   False  0
   True  NaN   True  True   1
  </code></pre>
  <p>This can be acheived in a pandas dataframe with the function <code>df.all().astype(int)</code>.</p>
  <p>Any help for a pyspark equivalent would be most appreciated, please.</p>