Several minor doc updates/changes.

doc/source/basics.rst

@@ -902,14 +902,14 @@ For instance:
 
 .. ipython:: python
 
-   set_eng_float_format(precision=3, use_eng_prefix=True)
+   set_eng_float_format(accuracy=3, use_eng_prefix=True)
    df['a']/1.e3
    df['a']/1.e6
 
 .. ipython:: python
    :suppress:
 
-   set_printoptions(precision=4)
+   reset_printoptions()
 
 
 The ``set_printoptions`` function has a number of options for controlling how

doc/source/dsintro.rst

@@ -558,11 +558,24 @@ For very large DataFrame objects, only a summary will be printed to the console
 (here I am reading a CSV version of the **baseball** dataset from the **plyr**
 R package):
 
+.. ipython:: python
+   :suppress:
+
+   # force a summary to be printed
+   print_config = core.common.GlobalPrintConfig
+   core.common.GlobalPrintConfig.max_rows = 5
+
 .. ipython:: python
 
    baseball = read_csv('data/baseball.csv')
    print baseball
 
+.. ipython:: python
+   :suppress:
+
+   # restore GlobalPrintConfig
+   core.common.GlobalPrintConfig = print_config
+
 However, using ``to_string`` will return a string representation of the
 DataFrame in tabular form, though it won't always fit the console width:
 

doc/source/io.rst

@@ -166,6 +166,11 @@ to do as before:
    df = read_csv('foo.csv', parse_dates=True)
    df.index
 
+.. ipython:: python
+   :suppress:
+
+   os.remove('foo.csv')
+
 
 Reading DataFrame objects with ``MultiIndex``
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -196,6 +201,12 @@ Automatically "sniffing" the delimiter
 comma-separated) files. YMMV, as pandas uses the Sniffer_ class of the csv
 module.
 
+.. ipython:: python
+   :suppress:
+
+   df[:7].to_csv('tmp.sv', sep='|')
+   df[:7].to_csv('tmp2.sv', sep=':')
+
 .. ipython:: python
 
     print open('tmp2.sv').read()
@@ -211,22 +222,13 @@ Iterating through files chunk by chunk
 Suppose you wish to iterate through a (potentially very large) file lazily
 rather than reading the entire file into memory, such as the following:
 
-.. ipython:: python
-   :suppress:
-
-   df[:7].to_csv('tmp.sv', sep='|')
-   df[:7].to_csv('tmp2.sv', sep=':')
 
 .. ipython:: python
 
    print open('tmp.sv').read()
    table = read_table('tmp.sv', sep='|')
    table
 
-.. ipython:: python
-   :suppress:
-
-   os.remove('tmp.csv')
 
 By specifiying a ``chunksize`` to ``read_csv`` or ``read_table``, the return
 value will be an iterable object of type ``TextParser``:
@@ -248,6 +250,12 @@ Specifying ``iterator=True`` will also return the ``TextParser`` object:
    reader = read_table('tmp.sv', sep='|', iterator=True)
    reader.get_chunk(5)
 
+.. ipython:: python
+   :suppress:
+
+   os.remove('tmp.sv')
+   os.remove('tmp2.sv')
+
 Writing to CSV format
 ~~~~~~~~~~~~~~~~~~~~~