Merge pull request datacarpentry#318 from kleintom/tk_typos

Fix some typos

Author: bencomp

episodes/02-importing-data.md

@@ -83,7 +83,7 @@ and you can undo any changes too.
 
 - Use the Create Project option to import data
 - You can control how data imports using options on the import screen
-- Several files types may be imported into OpenRefine
+- Several file types may be imported into OpenRefine
 
 ::::::::::::::::::::::::::::::::::::::::::::::::::
 

episodes/04-transforming-data.md

@@ -42,7 +42,7 @@ clean leading and trailing white spaces from all data when importing the data in
 
 Look at the data in the column `coordinates` and split these values to obtain latitude and longitude. Make sure that the option for `Guess cell type` is checked and that `Remove this column` is not. Rename the new columns.
 
-What type of data does OpenRefine assign to the new colunms?
+What type of data does OpenRefine assign to the new columns?
 
 :::::::::::::::  solution
 
@@ -157,7 +157,7 @@ Once the new column is created, convert it to date using `Edit cells` > `Common
 Clustering allows you to find groups of entries that are not identical but are
 sufficiently similar that they may be alternative representations of the same thing (term or data value).
 For example, the two strings `New York` and `new york` are very likely to refer to the same concept and just have a
-capitalization differences. Likewise, `Björk` and `Bjork` probably refer to the same person. These kinds of variations
+capitalization difference. Likewise, `Björk` and `Bjork` probably refer to the same person. These kinds of variations
 occur a lot in scientific data. Clustering gives us a tool to resolve them.
 
 OpenRefine provides different clustering algorithms. The best way to understand how they work is to experiment with them.
@@ -172,7 +172,7 @@ The dataset has several near-identical entries in `scientificName`. For example,
 
 2. In the resulting pop-up window, you can change the `Method` and the `Keying Function`. Try different combinations to see what different mergers of values are suggested.
 
-3. If you select the `key collision` method and the `metaphone3` keying function. It should identify one cluster:
+3. If you select the `key collision` method and the `metaphone3` keying function, it should identify one cluster:
 
   ![](fig/or362-clustering.png){alt='OpenRefine window for clustering'}
 

episodes/05-filter-exclude-sort.md

@@ -34,7 +34,7 @@ If you still have your text facet for `scientificName`, you can use it. If you'v
   `exclude` will be presented. Note that in the top of the page, "33 matching rows" is now displayed instead of "790 rows".
 3. You can include other species in your current filter - e.g. click on *Chaetodipus baileyi* in the same way to include it in the filter.
 4. Alternatively, you can click the name of the species to include it in the filter instead of clicking the
-  `include`/`exclude` buttons. This will include the selected species and exclude all others options in a single step, which can be useful.
+  `include`/`exclude` buttons. This will include the selected species and exclude all other options in a single step, which can be useful.
 5. Click `include` and `exclude` on the other species and notice how the entries appear and
   disappear from the data table to the right.
 

episodes/06-reconciliation.md

@@ -110,7 +110,7 @@ If Wikidata does not appear in the list of reconciliation services, add the stan
 - In the `Expression` box, enter the following GREL: `cell.recon.best.name`
 - Click `OK`
 
-This will create a new column with the reconciled names for the countries. Create a text facet to see that there are a single name for each country.
+This will create a new column with the reconciled names for the countries. Create a text facet to see that there is a single name for each country.
 
 1. In the cases where OpenRefine did not select a match automatically, are the options relevant?
 2. Why do some cells in the `county` column have many options?