I query a database and save result as a dataframe which I then transform by factorize with pivot_table. This works fine when database query returns data but it throws an error when no data is returned(this is to be expected). How to catch this exception and return empty dataframe? 
#When dataframe is non-empty, transformation works fine:
print df
   sale name  year
0   41  Jason  2012
1   24  Molly  2012
2   31  Jason  2013
3   32  Jason  2014
4   31  Molly  2014
df['groups'] = (pd.factorize(df.year)[0] + 1).astype(str)
df1 = (df.pivot_table(index='name', columns='groups', values=['sale', 'year']))
df1.columns = [''.join(col) for col in df1.columns]
print (df1)
       sale1  sale2  sale3   year1   year2   year3
name                                              
Jason   41.0   31.0   32.0  2012.0  2013.0  2014.0
Molly   24.0    NaN   31.0  2012.0     NaN  2014.0
#But when dataframe is empty, factorize by pivot_table throws error
df  = pd.DataFrame(columns=['sales','name','year'])
df1 = (df.pivot_table(index='name', columns='groups', values=['sale', 'year']))
df1.columns = [''.join(col) for col in df1.columns]
print (df1)
DataError: No numeric types to aggregate
We can use the dropna() function of the pandas DataFrame class to remove all the NaN values in the DataFrame. Then we apply the empty property on the DataFrame object to check the result and it will return True.
If Series/DataFrame is empty, return True, if not return False. Return series without null values. Return DataFrame with labels on given axis omitted where (all or any) data are missing. If Series/DataFrame contains only NaNs, it is still not considered empty.
In order to check missing values in Pandas DataFrame, we use a function isnull() and notnull(). Both function help in checking whether a value is NaN or not. These function can also be used in Pandas Series in order to find null values in a series.
isEmpty. Returns True if this DataFrame is empty.
try:
    df1 = df.pivot_table(index='name', columns='name', values=['sale', 'year'])
except pd.core.groupby.DataError:
    df1 = pd.DataFrame()
except:
    raise
Credits to brenbarn who found the error name for dataerror at How can I catch a pandas DataError?
You should probably check whether the dataframe is empty or not
if df.empty:
    return df
before calling pivot_table
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