fix documentation!

Author: vangj

docs/source/_code/dataframe-tip.py

@@ -3,6 +3,7 @@
 import pandas as pd
 
 from pypair.association import binary_binary
+from pypair.util import corr
 
 
 def get_data(n_rows=1000, n_cols=5):
@@ -16,8 +17,8 @@ def get_data(n_rows=1000, n_cols=5):
     tanimoto = lambda a, b: binary_binary(a, b, measure='tanimoto_i')
 
     df = get_data()
-    jaccard_corr = df.corr(method=jaccard)
-    tanimoto_corr = df.corr(method=tanimoto)
+    jaccard_corr = corr(df, jaccard)
+    tanimoto_corr = corr(df, tanimoto)
 
     print(jaccard_corr)
     print('-' * 15)

docs/source/quickstart.rst

@@ -80,7 +80,7 @@ Here's a recipe in using multiprocessing to compute pairwise association with bi
    :language: python
    :linenos:
 
-Here's another way to use a pandas Dataframe ``corr()`` method to speed up pairwise association computation.
+Here's a nifty utility method to create a correlation matrix. The input data frame must be all the same type and you must supply a function. Note that Pandas ``DataFrame.corr()`` no longer supports processing non-numeric data; fields that are not numeric will be simply skipped over. Why?
 
 .. literalinclude:: _code/dataframe-tip.py
    :language: python