title: pd.to_numeric is not working in python
body: <p>I'm using Jupyter notebook. Default python kernel. 'numpy' and 'pandas' imported.</p>
  
  <p>This column is named 'Period'. The value contains numbers and text like "Period". The data type is 'object'. I would like to delete the rows in which the value of column 'Period' is not a number. 
  What I tried to do is to first convert the column from object to numeric.</p>
  
  <pre><code>pd.to_numeric(df['Period'],errors='coerce')
  </code></pre>
  
  <p>It returned a list of numbers and NaNs. The last line lies:</p>
  
  <pre><code>Name: Period, dtype: float64
  </code></pre>
  
  <p>If I checked again:</p>
  
  <pre><code>df['Period'].dtype
  </code></pre>
  
  <p>It returns:</p>
  
  <pre><code>dtype('O')
  </code></pre>
  
  <p>Apparently the converting did not actually work. Also with the following code, it dropped nothing. </p>
  
  <pre><code>df.dropna(subset=['Period'])
  </code></pre>
  
  <p>What do you think went wrong?</p>