Updated the dependency versions referred to in code & docs

README.rst

@@ -30,20 +30,20 @@ The required dependencies to use the software are:
 
 * Python >= 2.7
 * setuptools
-* Numpy >= 1.11.2
+* Numpy >= 1.11
 * SciPy >= 0.17
 * Nibabel >= 2.0.2
 * Nilearn >= 0.4.0
-* Pandas >= 0.15.0
+* Pandas >= 0.18.0
 * Sklearn >= 0.18.0
 * Patsy >= 0.4.1
 
 If you are using nilearn plotting functionalities or running the
 examples, matplotlib >= 1.5.1 is required.
 
-If you want to run the tests, you need nose >= 1.2.1 and coverage >= 3.6.
+If you want to run the tests, you need nose >= 1.2.1 and coverage >= 3.7.
 
-If you want to download openneuro datasets Boto3 >= 1.0.0 is required
+If you want to download openneuro datasets Boto3 >= 1.2 is required
 
 
 Install

doc/conf.py

@@ -284,8 +284,8 @@
     'reference_url'     : {
         'nilearn': 'http://nilearn.github.io',
         'matplotlib': 'http://matplotlib.org',
-        'numpy': 'http://docs.scipy.org/doc/numpy-1.6.0',
-        'scipy': 'http://docs.scipy.org/doc/scipy-0.11.0/reference',
+        'numpy': 'http://docs.scipy.org/doc/numpy-1.11.0',
+        'scipy': 'http://docs.scipy.org/doc/scipy-0.17.0/reference',
         'nibabel': 'http://nipy.org/nibabel',
         'sklearn': 'http://scikit-learn.org/stable',
         'patsy': 'http://patsy.readthedocs.io/en/latest/',

nistats/second_level_model.py

@@ -244,8 +244,6 @@ def fit(self, second_level_input, confounds=None, design_matrix=None):
         # sort a pandas dataframe by subject_label to avoid inconsistencies
         # with the design matrix row order when automatically extracting maps
         if isinstance(second_level_input, pd.DataFrame):
-            # Avoid pandas df.sort_value to keep compatibility with numpy 1.8
-            # also pandas df.sort since it is completely deprecated.
             columns = second_level_input.columns.tolist()
             column_index = columns.index('subject_label')
             sorted_matrix = sorted(