Update README.md

README.md

@@ -32,32 +32,32 @@ its way towards this goal.
 Here are just a few of the things that pandas does well:
 
   - Easy handling of [**missing data**][missing-data] (represented as
-    `NaN`, `NA`, or `NaT`) in floating point as well as non-floating point data
+    `NaN`, `NA`, or `NaT`) in floating point as well as non-floating point data;
   - Size mutability: columns can be [**inserted and
     deleted**][insertion-deletion] from DataFrame and higher dimensional
-    objects
+    objects;
   - Automatic and explicit [**data alignment**][alignment]: objects can
     be explicitly aligned to a set of labels, or the user can simply
     ignore the labels and let `Series`, `DataFrame`, etc. automatically
-    align the data for you in computations
+    align the data for you in computations;
   - Powerful, flexible [**group by**][groupby] functionality to perform
     split-apply-combine operations on data sets, for both aggregating
-    and transforming data
+    and transforming data;
   - Make it [**easy to convert**][conversion] ragged,
     differently-indexed data in other Python and NumPy data structures
-    into DataFrame objects
+    into DataFrame objects;
   - Intelligent label-based [**slicing**][slicing], [**fancy
     indexing**][fancy-indexing], and [**subsetting**][subsetting] of
-    large data sets
+    large data sets;
   - Intuitive [**merging**][merging] and [**joining**][joining] data
-    sets
+    sets;
   - Flexible [**reshaping**][reshape] and [**pivoting**][pivot-table] of
-    data sets
+    data sets;
   - [**Hierarchical**][mi] labeling of axes (possible to have multiple
-    labels per tick)
+    labels per tick);
   - Robust IO tools for loading data from [**flat files**][flat-files]
     (CSV and delimited), [**Excel files**][excel], [**databases**][db],
-    and saving/loading data from the ultrafast [**HDF5 format**][hdfstore]
+    and saving/loading data from the ultrafast [**HDF5 format**][hdfstore];
   - [**Time series**][timeseries]-specific functionality: date range
     generation and frequency conversion, moving window statistics,
     date shifting and lagging.