dplyr 0.1.2

New features

• select() is substantially more powerful. You can use named arguments to
  rename existing variables, and new functions starts_with(), ends_with(),
  contains(), matches() and num_range() to select variables based on
  their names. It now also makes a shallow copy, substantially reducing its
  memory impact (#158, #172, #192, #232).
• summarize() added as alias for summarise() for people from countries
  that don't don't spell things correctly ;) (#245)

Bug fixes

• filter() now fails when given anything other than a logical vector, and
  correctly handles missing values (#249). filter.numeric() proxies
  stats::filter() so you can continue to use filter() function with
  numeric inputs (#264).
• summarise() correctly uses newly created variables (#259).
• mutate() correctly propagates attributes (#265) and mutate.data.frame()
  correctly mutates the same variable repeatedly (#243).
• lead() and lag() preserve attributes, so they now work with
  dates, times and factors (#166).
• n() never accepts arguments (#223).
• row_number() gives correct results (#227).
• rbind_all() silently ignores data frames with 0 rows or 0 columns (#274).
• group_by() orders the result (#242). It also checks that columns
  are of supported types (#233, #276).
• The hybrid evaluator did not handle some expressions correctly, for
  example in if(n() > 5) 1 else 2 the subexpression n() was not
  substituted correctly. It also correctly processes $ (#278).
• arrange() checks that all columns are of supported types (#266).
• Working towards Solaris compatibility.
• Benchmarking vignette temporarily disabled due to microbenchmark
  problems reported by BDR.

dplyr 0.1.1

Improvements

• new location() and changes() functions which provide more information
  about how data frames are stored in memory so that you can see what
  gets copied.
• renamed explain_tbl() to explain() (#182).
• tally() gains sort argument to sort output so highest counts
  come first (#173).
• ungroup.grouped_df(), tbl_df(), as.data.frame.tbl_df() now only
  make shallow copies of their inputs (#191).
• The benchmark-baseball vignette now contains fairer (including grouping
  times) comparisons with data.table. (#222)

Bug fixes

• filter() (#221) and summarise() (#194) correctly propagate attributes.
• summarise() throws an error when asked to summarise an unknown variable
  instead of crashing (#208).
• group_by() handles factors with missing values (#183).
• filter() handles scalar results (#217) and better handles scoping, e.g.
  filter(., variable) where variable is defined in the function that calls
  filter. It also handles T and F as aliases to TRUE and FALSE
  if there are no T or F variables in the data or in the scope.
• select.grouped_df fails when the grouping variables are not included
  in the selected variables (#170)
• all.equal.data.frame() handles a corner case where the data frame has
  NULL names (#217)
• mutate() gives informative error message on unsupported types (#179)
• dplyr source package no longer includes pandas benchmark, reducing
  download size from 2.8 MB to 0.5 MB.

First release

v0.1

Update readme and notes for CRAN release