handle object type

tompollard · Jan 18, 2018 · d02b48d · d02b48d
1 parent a3fa260
commit d02b48d
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Showing 2 changed files with 7 additions and 6 deletions.
diff --git a/setup.py b/setup.py
@@ -22,7 +22,7 @@
     # Versions should comply with PEP440. For a discussion on single-sourcing
     # the version across setup.py and the project code, see
     # https://packaging.python.org/en/latest/single_source_version.html
-    version='0.3.2',                         
+    version='0.3.3',                         
 
     description='TableOne',
     long_description=long_description,

diff --git a/tableone.py b/tableone.py
@@ -4,7 +4,7 @@
 """
 
 __author__ = "Tom Pollard <tpollard@mit.edu>, Alistair Johnson"
-__version__ = "0.3.2"
+__version__ = "0.3.3"
 
 import pandas as pd
 import csv
@@ -79,9 +79,7 @@ def __init__(self, data, columns='autodetect', categorical='autodetect',
         # create tables of continuous and categorical variables
         if self.continuous:
             self._cont_describe = self._create_cont_describe(data)
-            # self._cont_describe_NEW = self._create_cont_describe_NEW(data)
             self._cont_table = self._create_cont_table(data)
-            # self._cont_table_NEW = self._create_cont_table_NEW(data)
 
         # combine continuous variables and categorical variables into table 1
         self.tableone = self._create_tableone(data)
@@ -130,14 +128,17 @@ def _create_cont_describe(self,data):
 
         if self.groupby:
             cont_data = data[self.continuous + [self.groupby]]
+            cont_data = cont_data.apply(pd.to_numeric, errors='ignore')
             df_cont = pd.pivot_table(cont_data,
                 columns=[self.groupby],
                 aggfunc=aggfuncs)
         else:
             # if no groupby, just add single group column
-            df_cont = data[self.continuous].apply(aggfuncs).T
+            df_cont = data[self.continuous].apply(pd.to_numeric, 
+                errors='ignore').apply(aggfuncs).T
             df_cont.columns.name = 'overall'
-            df_cont.columns = pd.MultiIndex.from_product([df_cont.columns, ['overall']])
+            df_cont.columns = pd.MultiIndex.from_product([df_cont.columns, 
+                ['overall']])
 
         df_cont.index.rename('variable',inplace=True)