title: Pandera validate get all valid rows
body: <p>I am trying to use pandera library (I am very new with this) for pandas dataframe validation.
  What I want to do is to ignore the rows which are not valid as per the schema.
  How can I do that?</p>
  <p>for example:
  pandera schema looks like below:</p>
  <pre><code>import pandera as pa
  import pandas as pd
  
  schema: pa.DataFrameSchema = pa.DataFrameSchema(columns={
    'Col1': pa.Column(str),
    'Col2': pa.Column(float, checks=pa.Check(lambda x: (0 &lt;= x &lt;= 1)), nullable=True),
  })
  
  df: pd.DataFrame = pd.DataFrame({
      &quot;Col1&quot;: [&quot;1&quot;, &quot;2&quot;, &quot;3&quot;, nan],
      &quot;Col2&quot;: [0.3, 0.4, 5, 0.2],
  })
  </code></pre>
  <p>What I want to do is when I apply validation on the <code>df</code> I get a result:</p>
  <pre><code>   Col1  Col2
  0     1   0.3
  1     2   0.4
  </code></pre>
  <p>The other rows with error dropped.</p>