Assorted typos

episodes/00-before-we-start.md

@@ -102,7 +102,7 @@ when you have multiple projects. In general, you may wish to create separate dir
 your scripts, data, and documents.
 
 - **`data/`**: Use this folder to store your raw data. For the sake of transparency and provenance,
-  you should always keep a copy of your **raw data**. If you need to cleanup data, do it
+  you should always keep a copy of your **raw data**. If you need to clean up data, do it
   programmatically (*i.e.* with scripts) and make sure to separate cleaned up data from the raw data.
   For example, you can store raw data in files `./data/raw/` and clean data in `./data/clean/`.
 

episodes/04-data-types-and-format.md

@@ -348,14 +348,14 @@ df1['weight'].mean()
 38.751976145601844
 ```
 
-We can fill `NaN` values with any value that we chose. The code below fills all
+We can fill `NaN` values with any value that we choose. The code below fills all
 `NaN` values with a mean for all weight values.
 
 ```python
 df1['weight'] = surveys_df['weight'].fillna(surveys_df['weight'].mean())
 ```
 
-We could also chose to create a subset of our data, only keeping rows that do
+We could also choose to create a subset of our data, only keeping rows that do
 not contain `NaN` values.
 
 The point is to make conscious decisions about how to manage missing data. This

episodes/06-loops-and-functions.md

@@ -325,7 +325,7 @@ AND the file name itself.
 
 2. Let's say you only want to look at data from a given multiple of years. How would you modify your loop in order to generate a data file for only every 5th year, starting from 1977?
 
-3. Instead of splitting out the data by years, a colleague wants to do analyses each species separately. How would you write a unique CSV file for each species?
+3. Instead of splitting out the data by years, a colleague wants to do analyses of each species separately. How would you write a unique CSV file for each species?
 
 ::::::::::::::::::::::: solution
 

episodes/09-working-with-sql.md

@@ -23,7 +23,7 @@ exercises: 25
 ## Python and SQL
 
 When you open a CSV in python, and assign it to a variable name, you are using
-your computers memory to save that variable. Accessing data from a database like
+your computer's memory to save that variable. Accessing data from a database like
 SQL is not only more efficient, but also it allows you to subset and import only
 the parts of the data that you need.
 
@@ -225,7 +225,7 @@ con.close()
   results to their own tables in the portal database.
 
 2. What are some of the reasons you might want to save the results of your queries back into the
-  database? What are some of the reasons you might avoid doing this.
+  database? What are some of the reasons you might avoid doing this?
 
 ::::::::::::::::::::::: solution