DOC: fix datetime-like Series ops in docs + some extra api docs

doc/source/api.rst

@@ -127,13 +127,15 @@ Data manipulations
    :toctree: generated/
 
    melt
+   pivot
    pivot_table
    crosstab
    cut
    qcut
    merge
    concat
    get_dummies
+   factorize
 
 Top-level missing data
 ~~~~~~~~~~~~~~~~~~~~~~
@@ -320,6 +322,7 @@ Computations / Descriptive Stats
    :toctree: generated/
 
    Series.abs
+   Series.all
    Series.any
    Series.autocorr
    Series.between
@@ -362,6 +365,7 @@ Reindexing / Selection / Label manipulation
 
    Series.align
    Series.drop
+   Series.equals
    Series.first
    Series.head
    Series.idxmax
@@ -422,22 +426,6 @@ Time series-related
    Series.resample
    Series.tz_convert
    Series.tz_localize
-   Series.year
-   Series.month
-   Series.day
-   Series.hour
-   Series.minute
-   Series.second
-   Series.microsecond
-   Series.nanosecond
-   Series.date
-   Series.time
-   Series.dayofyear
-   Series.weekofyear
-   Series.week
-   Series.dayofweek
-   Series.weekday
-   Series.quarter
 
 String handling
 ~~~~~~~~~~~~~~~~~~~
@@ -500,8 +488,12 @@ Serialization / IO / Conversion
    Series.to_dict
    Series.to_frame
    Series.to_hdf
+   Series.to_sql
+   Series.to_gbq
+   Series.to_msgpack
    Series.to_json
    Series.to_sparse
+   Series.to_dense
    Series.to_string
    Series.to_clipboard
 
@@ -624,6 +616,7 @@ Computations / Descriptive Stats
    :toctree: generated/
 
    DataFrame.abs
+   DataFrame.all
    DataFrame.any
    DataFrame.clip
    DataFrame.clip_lower
@@ -666,6 +659,7 @@ Reindexing / Selection / Label manipulation
    DataFrame.drop
    DataFrame.drop_duplicates
    DataFrame.duplicated
+   DataFrame.equals
    DataFrame.filter
    DataFrame.first
    DataFrame.head
@@ -759,14 +753,18 @@ Serialization / IO / Conversion
    DataFrame.to_pickle
    DataFrame.to_csv
    DataFrame.to_hdf
+   DataFrame.to_sql
    DataFrame.to_dict
    DataFrame.to_excel
    DataFrame.to_json
    DataFrame.to_html
    DataFrame.to_latex
    DataFrame.to_stata
+   DataFrame.to_msgpack
+   DataFrame.to_gbq
    DataFrame.to_records
    DataFrame.to_sparse
+   DataFrame.to_dense
    DataFrame.to_string
    DataFrame.to_clipboard
 
@@ -911,6 +909,7 @@ Reindexing / Selection / Label manipulation
    Panel.add_prefix
    Panel.add_suffix
    Panel.drop
+   Panel.equals
    Panel.filter
    Panel.first
    Panel.last
@@ -1039,6 +1038,7 @@ Modifying and Computations
    Index.copy
    Index.delete
    Index.diff
+   Index.sym_diff
    Index.drop
    Index.equals
    Index.factorize
@@ -1197,8 +1197,13 @@ Indexing, iteration
    GroupBy.groups
    GroupBy.indices
    GroupBy.get_group
+
+.. currentmodule:: pandas
+
    Grouper
 
+.. currentmodule:: pandas.core.groupby
+
 Function application
 ~~~~~~~~~~~~~~~~~~~~
 .. autosummary::
@@ -1219,6 +1224,20 @@ Computations / Descriptive Stats
    GroupBy.var
    GroupBy.ohlc
 
+.. currentmodule:: pandas
+
+Working with options
+--------------------
+
+.. autosummary::
+   :toctree: generated/
+
+   describe_option
+   reset_option
+   get_option
+   set_option
+   option_context
+
 ..
     HACK - see github issue #4539. To ensure old links remain valid, include
     here the autosummaries with previous currentmodules as a comment and add

doc/source/timeseries.rst

@@ -579,8 +579,7 @@ calendars which account for local holidays and local weekend conventions.
     bday_egypt = CustomBusinessDay(holidays=holidays, weekmask=weekmask_egypt)
     dt = datetime(2013, 4, 30)
     dt + 2 * bday_egypt
-    dts = date_range(dt, periods=5, freq=bday_egypt).to_series()
-    dts
+    dts = date_range(dt, periods=5, freq=bday_egypt)
     Series(dts.weekday, dts).map(Series('Mon Tue Wed Thu Fri Sat Sun'.split()))
 
 As of v0.14 holiday calendars can be used to provide the list of holidays.  See the

doc/source/v0.12.0.txt

@@ -380,7 +380,7 @@ Experimental Features
       bday_egypt = CustomBusinessDay(holidays=holidays, weekmask=weekmask_egypt)
       dt = datetime(2013, 4, 30)
       print(dt + 2 * bday_egypt)
-      dts = date_range(dt, periods=5, freq=bday_egypt).to_series()
+      dts = date_range(dt, periods=5, freq=bday_egypt)
       print(Series(dts.weekday, dts).map(Series('Mon Tue Wed Thu Fri Sat Sun'.split())))
 
 Bug Fixes