DOC: Use standard header for .rst files

Author: saurav-chakravorty

doc/source/10min.rst

@@ -1,24 +1,6 @@
 .. _10min:
 
-.. currentmodule:: pandas
-
-.. ipython:: python
-   :suppress:
-
-   import os
-   import numpy as np
-
-   import pandas as pd
-
-   np.random.seed(123456)
-   np.set_printoptions(precision=4, suppress=True)
-   pd.options.display.max_rows = 15
-
-   # portions of this were borrowed from the
-   # Pandas cheatsheet
-   # created during the PyData Workshop-Sprint 2012
-   # Hannah Chen, Henry Chow, Eric Cox, Robert Mauriello
-
+{{ header }}
 
 ********************
 10 Minutes to pandas
@@ -773,6 +755,7 @@ CSV
 .. ipython:: python
    :suppress:
 
+   import os
    os.remove('foo.csv')
 
 HDF5

doc/source/advanced.rst

@@ -1,15 +1,6 @@
 .. _advanced:
 
-.. currentmodule:: pandas
-
-.. ipython:: python
-   :suppress:
-
-   import numpy as np
-   import pandas as pd
-   np.random.seed(123456)
-   np.set_printoptions(precision=4, suppress=True)
-   pd.options.display.max_rows = 15
+{{ header }}
 
 ******************************
 MultiIndex / Advanced Indexing

doc/source/basics.rst

@@ -1,16 +1,7 @@
-.. currentmodule:: pandas
-
-.. ipython:: python
-   :suppress:
-
-   import numpy as np
-   import pandas as pd
-
-   np.set_printoptions(precision=4, suppress=True)
-   pd.options.display.max_rows = 15
-
 .. _basics:
 
+{{ header }}
+
 ==============================
  Essential Basic Functionality
 ==============================

doc/source/categorical.rst

@@ -1,16 +1,6 @@
 .. _categorical:
 
-.. currentmodule:: pandas
-
-.. ipython:: python
-   :suppress:
-
-   import numpy as np
-   import pandas as pd
-   np.random.seed(123456)
-   np.set_printoptions(precision=4, suppress=True)
-   pd.options.display.max_rows = 15
-
+{{ header }}
 
 ****************
 Categorical Data

doc/source/comparison_with_r.rst

@@ -1,12 +1,6 @@
-.. currentmodule:: pandas
 .. _compare_with_r:
 
-.. ipython:: python
-   :suppress:
-
-   import pandas as pd
-   import numpy as np
-   pd.options.display.max_rows = 15
+{{ header }}
 
 Comparison with R / R libraries
 *******************************

doc/source/comparison_with_sas.rst

@@ -14,8 +14,8 @@ As is customary, we import pandas and NumPy as follows:
 
 .. ipython:: python
 
-    import pandas as pd
-    import numpy as np
+    import pandas as pd    # noqa: F811
+    import numpy as np     # noqa: F811
 
 
 .. note::

doc/source/computation.rst

@@ -1,21 +1,7 @@
-.. currentmodule:: pandas
-
-.. ipython:: python
-   :suppress:
-
-   import numpy as np
-   import matplotlib.pyplot as plt
-
-   import pandas as pd
-
-   np.random.seed(123456)
-   np.set_printoptions(precision=4, suppress=True)
-   pd.options.display.max_rows = 15
-
-   plt.close('all')
-
 .. _computation:
 
+{{ header }}
+
 Computational tools
 ===================
 

doc/source/conf.py

@@ -301,25 +301,25 @@
 }
 
 
-common_imports = """\
+header = """\
 .. currentmodule:: pandas
 
 .. ipython:: python
    :suppress:
 
    import numpy as np
-   from pandas import *
    import pandas as pd
+
    randn = np.random.randn
+   np.random.seed(123456)
    np.set_printoptions(precision=4, suppress=True)
-   options.display.max_rows = 15
-   from pandas.compat import StringIO
+   pd.options.display.max_rows = 15
 """
 
 
 html_context = {
     'redirects': {old: new for old, new in moved_api_pages},
-    'common_imports': common_imports,
+    'header': header
 }
 
 # If false, no module index is generated.

doc/source/contributing.rst

@@ -672,6 +672,7 @@ Otherwise, you need to do it manually:
 
     import warnings
 
+
     def old_func():
         """Summary of the function.
 
@@ -681,6 +682,7 @@ Otherwise, you need to do it manually:
         warnings.warn('Use new_func instead.', FutureWarning, stacklevel=2)
         new_func()
 
+
     def new_func():
         pass
 
@@ -814,9 +816,8 @@ We would name this file ``test_cool_feature.py`` and put in an appropriate place
 .. code-block:: python
 
    import pytest
-   import numpy as np
-   import pandas as pd
-   from pandas.util import testing as tm
+   import numpy as np        # noqa: F811
+   import pandas as pd       # noqa: F811
 
 
    @pytest.mark.parametrize('dtype', ['int8', 'int16', 'int32', 'int64'])
@@ -938,8 +939,10 @@ If your change involves checking that a warning is actually emitted, use
 
 .. code-block:: python
 
-   df = pd.DataFrame()
+   import pandas.util.testing as tm
 
+
+   df = pd.DataFrame()
    with tm.assert_produces_warning(FutureWarning):
        df.some_operation()
 

doc/source/cookbook.rst

@@ -1,25 +1,6 @@
 .. _cookbook:
 
-.. currentmodule:: pandas
-
-.. ipython:: python
-   :suppress:
-
-   import datetime
-   import functools
-   import glob
-   import itertools
-   import os
-
-   import numpy as np
-   import pandas as pd
-   from pandas.compat import StringIO
-
-
-   np.random.seed(123456)
-   np.set_printoptions(precision=4, suppress=True)
-   pd.options.display.max_rows = 15
-
+{{ header }}
 
 ********
 Cookbook
@@ -186,6 +167,8 @@ One could hard code:
 
 .. ipython:: python
 
+   import functools
+
    CritList = [Crit1, Crit2, Crit3]
    AllCrit = functools.reduce(lambda x, y: x & y, CritList)
 
@@ -409,6 +392,8 @@ To take the cross section of the 1st level and 1st axis the index:
 
 .. ipython:: python
 
+   import itertools
+
    index = list(itertools.product(['Ada', 'Quinn', 'Violet'],
                                   ['Comp', 'Math', 'Sci']))
    headr = list(itertools.product(['Exams', 'Labs'], ['I', 'II']))
@@ -1022,6 +1007,9 @@ You can use the same approach to read all files matching a pattern.  Here is an
 
 .. ipython:: python
 
+    import glob
+    import os
+
     files = glob.glob('file_*.csv')
     result = pd.concat([pd.read_csv(f) for f in files], ignore_index=True)
 
@@ -1081,6 +1069,8 @@ Option 1: pass rows explicitly to skip rows
 
 .. ipython:: python
 
+    from pandas.compat import StringIO
+
     pd.read_csv(StringIO(data), sep=';', skiprows=[11, 12],
                 index_col=0, parse_dates=True, header=10)
 
@@ -1327,6 +1317,8 @@ The :ref:`Timedeltas <timedeltas.timedeltas>` docs.
 
 .. ipython:: python
 
+   import datetime
+
    s = pd.Series(pd.date_range('2012-1-1', periods=3, freq='D'))
 
    s - s.max()