title: Pandas.mean() TypeError: Could not convert to numeric
body: <p>I am working on a project where I imported data from SQL into a pandas DataFrame. This seems to go swimmingly, but when I take the pandas.mean() it throws a TypeError saying that a concatenated list of the values cannot be converted to numeric (see below):</p>
  
  <p>Example Dataframe:</p>
  
  <pre><code>df =
    ProductSKU OverallHeight-ToptoBottom
  0   AAI2185                      74.5
  1   AAI2275                        47
  2   AAI2686                      56.5
  3  AASA1002                     73.23
  4  AASA1032                     39.37
  5  AASA1039                     72.44
  6  AASA1099                      75.6
  7  AASA1101                        38
  8  ABCM1910                        69
  9  ABCM1980                        72
  </code></pre>
  
  <p>Function Call:</p>
  
  <pre><code>def summarizeTagData(df, tag):
      avgValue = df.loc[:,tag].dropna().mean()             &lt;--- Breaks here
      stdevValue = df.loc[:,tag].dropna().std()
      lowerBound = max(avgValue-(3*stdevValue),0)
      upperBound = (avgValue+(3*stdevValue))
      outsideRangeCount = df[df[tag]&gt;upperBound].shape[0]
      missingDataCount = df[df[tag].isnull()].shape[0]
      dataDict = {"Average":avgValue
              , "StDev":stdevValue
              , "UpperBound":upperBound
              , "LowerBound":lowerBound
              , "OutsideRange":outsideRangeCount
              , "MissingData":missingDataCount
              }
      return dataDict
  </code></pre>
  
  <p>Console Output:</p>
  
  <pre><code>summarizeTagData(df, 'OverallHeight-ToptoBottom')
      Traceback (most recent call last):
  
    File "&lt;ipython-input-22-f1f26a0a0520&gt;", line 1, in &lt;module&gt;
      summarizeTagData(df, 'OverallHeight-ToptoBottom')
  
    File "C:/Users/tmori/Google Drive/Projects/Product Dimension Accuracy/ProductDataTag_Analysis.py", line 23, in summarizeTagData
      avgValue = df.loc[:,tag].dropna().mean()
  
    File "C:\Program Files\Anaconda\lib\site-packages\pandas\core\generic.py", line 5310, in stat_func
      numeric_only=numeric_only)
  
    ... 
  
    File "C:\Program Files\Anaconda\lib\site-packages\pandas\core\nanops.py", line 293, in nanmean
      the_sum = _ensure_numeric(values.sum(axis, dtype=dtype_sum))
  
    File "C:\Program Files\Anaconda\lib\site-packages\pandas\core\nanops.py", line 743, in _ensure_numeric
      raise TypeError('Could not convert %s to numeric' % str(x))
  
  TypeError: Could not convert 74.54756.573.2339.3772.4475.6386972 to numeric
  </code></pre>
  
  <p>The strangest thing (and what I cannot figure out), is that it works perfectly fine when I import the same data through a CSV. It only breaks when I load it through SQL, could there be something I did incorrectly there?</p>
  
  <p>Best,
  Tom</p>