title: Apply scikit-learn murmurhash3_32 on a Pandas dataframe
body: <p>I try to apply murmurhash on a pandas dataframe.
  I wanted to use scikit-learn murmurhash3_32 (any other easy proposition would be appreciated).
  I tried</p>
  
  <pre><code>import pandas as pd
  from sklearn.utils.murmurhash import murmurhash3_32
  
  df = pd.DataFrame({'a': [100, 1000], 'b': [200, 2000]}, dtype='int32')
  df.apply(murmurhash3_32)
  </code></pre>
  
  <p>But I get </p>
  
  <blockquote>
    <p>TypeError: ("key 0     100\n1    1000\nName: a, dtype: int32 with type class 'pandas.core.series.Series' is not supported. Explicit conversion to bytes is required", 'occurred at index a')</p>
  </blockquote>
  
  <p>But Scikit is supposed to handle int32:
  <a href="https://scikit-learn.org/dev/modules/generated/sklearn.utils.murmurhash3_32.html#sklearn.utils.murmurhash3_32" rel="nofollow noreferrer">https://scikit-learn.org/dev/modules/generated/sklearn.utils.murmurhash3_32.html#sklearn.utils.murmurhash3_32</a></p>
  
  <p>Any idea or recommendation on it?</p>