fixing merge conflicts and re-running tests/Charts.ipynb

datascience/tables.py

@@ -14,7 +14,7 @@
 
 import numpy as np
 import matplotlib
-matplotlib.use('agg', warn=False)
+matplotlib.use('agg')
 import matplotlib.pyplot as plt
 import pandas
 import IPython
@@ -86,7 +86,19 @@ def from_rows(cls, rows, labels):
 
     @classmethod
     def from_records(cls, records):
-        """Create a table from a sequence of records (dicts with fixed keys)."""
+        """Create a table from a sequence of records (dicts with fixed keys).
+
+           Args:
+
+               records: A list of dictionaries with same keys.
+
+           Returns:
+
+               If the list is empty, it will return an empty table.
+               Otherwise, it will return a table with the dictionary's keys as the column name, and the corresponding data.
+               If the dictionaries do not have identical keys, the keys of the first dictionary in the list is used.
+
+           """
         if not records:
             return cls()
         labels = sorted(list(records[0].keys()))
@@ -158,7 +170,16 @@ def from_df(cls, df, keep_index=False):
 
     @classmethod
     def from_array(cls, arr):
-        """Convert a structured NumPy array into a Table."""
+        """Convert a structured NumPy array into a Table.
+
+           Args:
+ 
+               arr: A structured numpy array
+
+           Returns:
+
+               A table with the field names as the column names and the corresponding data. 
+        """
         return cls().with_columns([(f, arr[f]) for f in arr.dtype.names])
 
     #################
@@ -2650,12 +2671,12 @@ def prepare_hist_with_group(group):
         values_dict = collections.OrderedDict(values_dict)
         if left_end is not None or right_end is not None:
             if left_end is None:
-                if bins[0]:
+                if bins is not None and bins[0]:
                     left_end = bins[0]
                 else:
                     left_end = min([min(self.column(k)) for k in self.labels if np.issubdtype(self.column(k).dtype, np.number)])
             elif right_end is None:
-                if bins[-1]:
+                if bins is not None and bins[-1]:
                     right_end = bins[-1]
                 else:
                     right_end = max([max(self.column(k)) for k in self.labels if np.issubdtype(self.column(k).dtype, np.number)])

datascience/util.py

@@ -7,7 +7,7 @@
 import numpy as np
 import pandas as pd
 import matplotlib
-matplotlib.use('agg', warn=False)
+matplotlib.use('agg')
 import matplotlib.pyplot as plt
 from scipy import stats
 from scipy import optimize

datascience/version.py

@@ -1 +1 @@
-__version__ = '0.15.6'
+__version__ = '0.15.7'