docs(language): de-simple-fy prose in docs

Removing some usage of the word `simple` or `simply` where it doesn't
add anything to the prose.

My favorite (now removed) example:

```
... simply pass `auth_mechanism='GSSAPI'` or
`auth_mechanism='LDAP'` (and set `kerberos_service_name` if necessary along
with `user` and `password` if necessary) to the
`ibis.impala_connect(...)` method when instantiating an
`ImpalaConnection`.
```

docs/backends/impala.qmd

@@ -1300,7 +1300,7 @@ connection semantics are similar to the other access methods for working with
 secure clusters.
 
 Specifically, after authenticating yourself against Kerberos (e.g., by issuing
-the appropriate `kinit` command), simply pass `auth_mechanism='GSSAPI'` or
+the appropriate `kinit` command), pass `auth_mechanism='GSSAPI'` or
 `auth_mechanism='LDAP'` (and set `kerberos_service_name` if necessary along
 with `user` and `password` if necessary) to the
 `ibis.impala_connect(...)` method when instantiating an `ImpalaConnection`.

docs/how-to/extending/elementwise.qmd

@@ -2,13 +2,17 @@
 
 This notebook will show you how to add a new elementwise operation to an existing backend.
 
-We are going to add `julianday`, a function supported by the SQLite database, to the SQLite Ibis backend.
+We are going to add `julianday`, a function supported by the SQLite database, to
+the SQLite Ibis backend.
 
-The Julian day of a date, is the number of days since January 1st, 4713 BC. For more information check the [Julian day](https://en.wikipedia.org/wiki/Julian_day) Wikipedia page.
+The Julian day of a date, is the number of days since January 1st, 4713 BC. For
+more information check the [Julian
+day](https://en.wikipedia.org/wiki/Julian_day) Wikipedia page.
 
 ## Step 1: Define the Operation
 
-Let's define the `julianday` operation as a function that takes one string input argument and returns a float.
+Let's define the `julianday` operation as a function that takes one string input
+argument and returns a float.
 
 ```python
 def julianday(date: str) -> float:
@@ -31,15 +35,21 @@ class JulianDay(Value):
     shape = rlz.shape_like('arg')
 ```
 
-We just defined a `JulianDay` class that takes one argument of type string or binary, and returns a float.
+We just defined a `JulianDay` class that takes one argument of type string or
+binary, and returns a float.
 
 ## Step 2: Define the API
 
-Because we know the output type of the operation, to make an expression out of ``JulianDay`` we simply need to construct it and call its `ibis.expr.types.Node.to_expr` method.
+Because we know the output type of the operation, to make an expression out of
+``JulianDay`` we can construct it and call its `ibis.expr.types.Node.to_expr`
+method.
 
-We still need to add a method to `StringValue` (this needs to work on both scalars and columns).
+We still need to add a method to `StringValue` (this needs to work on both
+scalars and columns).
 
-When you add a method to any of the expression classes whose name matches `*Value` both the scalar and column child classes will pick it up, making it easy to define operations for both scalars and columns in one place.
+When you add a method to any of the expression classes whose name matches
+`*Value` both the scalar and column child classes will pick it up, making it
+easy to define operations for both scalars and columns in one place.
 
 We can do this by defining a function and assigning it to the appropriate class
 of expressions.
@@ -120,7 +130,9 @@ jday_expr
 ibis.to_sql(jday_expr)
 ```
 
-Because we've defined our operation on `StringValue`, and not just on `StringColumn` we get operations on both string scalars *and* string columns for free
+Because we've defined our operation on `StringValue`, and not just on
+`StringColumn` we get operations on both string scalars *and* string columns for
+free.
 
 
 ```{python}

docs/how-to/extending/reduction.qmd

@@ -1,12 +1,15 @@
 # Add a reduction operation
 
-This notebook will show you how to add a new *reduction* operation `last_date` to the existing backend SQLite.
+This notebook will show you how to add a new *reduction* operation `last_date`
+to the existing backend SQLite.
 
-A reduction operation is a function that maps $N$ rows to 1 row, for example the `sum` function.
+A reduction operation is a function that maps $N$ rows to 1 row, for example the
+`sum` function.
 
 ## Description
 
-We're going to add a **`last_date`** function to ibis. `last_date` simply returns the latest date of a list of dates.
+We're going to add a **`last_date`** function to ibis. `last_date` returns the
+latest date of a list of dates.
 
 ## Step 1: Define the Operation
 
@@ -41,15 +44,22 @@ class LastDate(Reduction):
     shape = ds.scalar
 ```
 
-We just defined a `LastDate` class that takes one date column as input, and returns a scalar output of the same type as the input. This matches both the requirements of a reduction and the specifics of the function that we want to implement.
+We just defined a `LastDate` class that takes one date column as input, and
+returns a scalar output of the same type as the input. This matches both the
+requirements of a reduction and the specifics of the function that we want to
+implement.
 
-**Note**: It is very important that you write the correct argument rules and output type here. The expression *will not work* otherwise.
+**Note**: It is very important that you write the correct argument rules and
+output type here. The expression *will not work* otherwise.
 
 ## Step 2: Define the API
 
-Because every reduction in ibis has the ability to filter out values during aggregation, to make an expression out of `LastDate` we need to pass an additional argument `where` to our `LastDate` constructor.
+Because every reduction in Ibis has the ability to filter out values during
+aggregation, to make an expression out of `LastDate` we need to pass an
+additional argument `where` to our `LastDate` constructor.
 
-Additionally, reductions should be defined on `Column` classes because reductions are not always well-defined for a scalar value.
+Additionally, reductions should be defined on `Column` classes because
+reductions are not always well-defined for a scalar value.
 
 
 ```{python}
@@ -143,7 +153,8 @@ expr
 ibis.to_sql(expr)
 ```
 
-Show the last country to gain independence from the Spanish Empire, using the `where` parameter:
+Show the last country to gain independence from the Spanish Empire, using the
+`where` parameter:
 
 
 ```{python}

docs/how-to/visualization/altair.qmd

@@ -16,7 +16,8 @@ t.head(3)
 
 ## Using Altair with Ibis
 
-Refer to the [Altair documentation](https://altair-viz.github.io/). Simply pass in Ibis tables or expressions:
+Refer to the [Altair documentation](https://altair-viz.github.io/). You can pass
+in Ibis tables or expressions:
 
 ```{python}
 import altair as alt

docs/how-to/visualization/plotly.qmd

@@ -16,7 +16,8 @@ t.head(3)
 
 ## Using Plotly with Ibis
 
-Refer to the [Plotly documentation](https://plotly.com/python/). Simply pass in Ibis tables or expressions:
+Refer to the [Plotly documentation](https://plotly.com/python/). You can pass in
+Ibis tables or expressions:
 
 ```{python}
 import plotly.express as px

docs/how-to/visualization/plotnine.qmd

@@ -16,7 +16,8 @@ t.head(3)
 
 ## Using plotnine with Ibis
 
-Refer to the [plotnine documentation](https://plotnine.readthedocs.io/). Simply pass in Ibis tables or expressions:
+Refer to the [plotnine documentation](https://plotnine.readthedocs.io/). You can
+pass in Ibis tables or expressions:
 
 ```{python}
 from plotnine import ggplot, aes, geom_bar, theme

docs/posts/campaign-finance/index.qmd

@@ -262,8 +262,8 @@ able to determine the election type.
 cleaned.election_type.topk(10)
 ```
 
-About 1/20 of transactions are negative. These could represent refunds, or they could be data
-entry errors. Let's simply drop them to keep it simple.
+About 1/20 of transactions are negative. These could represent refunds, or they
+could be data entry errors. Let's drop them to keep it simple.
 
 
 ```{python}

docs/posts/ffill-and-bfill-using-ibis/index.qmd

@@ -152,8 +152,9 @@ Under this design, we now have another partition.
 Our first partition is by `event_id`.
 Within each set in that partition, we have a partition by `grouper`, where each set has up to one non-null value.
 
-Since there less than or equal to one non-null value in each group of `['event_id', 'grouper']`,
-we can simply fill values by overwriting _all_ values within the group by the max value in the group.
+Since there less than or equal to one non-null value in each group of
+`['event_id', 'grouper']`, we can fill values by overwriting _all_ values within
+the group by the max value in the group.
 
 So:
 

docs/tutorials/ibis-for-pandas-users.qmd

@@ -225,8 +225,8 @@ subset.columns
 
 ### Modifying columns
 
-Replacing existing columns is done using the `mutate` method just like adding columns. You simply
-add a column of the same name to replace it.
+Replacing existing columns is done using the `mutate` method just like adding
+columns. You add a column of the same name to replace it.
 
 
 ```{python}
@@ -241,8 +241,8 @@ mutated
 
 ### Renaming columns
 
-In addition to replacing columns, you can simply rename them as well. This is done with the `relabel` method
-which takes a dictionary containing the name mappings.
+In addition to replacing columns, you can rename them as well. This is done with
+the `relabel` method which takes a dictionary containing the name mappings.
 
 
 ```{python}
@@ -257,9 +257,10 @@ relabeled
 
 ## Selecting rows
 
-There are several methods that can be used to select rows of data in various ways. These are described
-in the sections below. We'll use the Palmer Penguins$^1$ dataset to investigate!
-Ibis has several built-in example datasets that you can access using the `ibis.examples` module.
+There are several methods that can be used to select rows of data in various
+ways. These are described in the sections below. We'll use the Palmer
+Penguins$^1$ dataset to investigate!  Ibis has several built-in example datasets
+that you can access using the `ibis.examples` module.
 
 $^1$: Horst AM, Hill AP, Gorman KB (2020). palmerpenguins: Palmer Archipelago (Antarctica) penguin data. R package version 0.1.0. https://allisonhorst.github.io/palmerpenguins/. doi: 10.5281/zenodo.3960218.
 
@@ -299,10 +300,11 @@ penguins.limit(5)
 
 ### Filtering rows
 
-In addition to simply limiting the number of rows that are returned, it is possible to filter the
-rows using expressions. Expressions are constructed very similarly to the way they are in pandas.
-Ibis expressions are constructed from operations on columns in a table which return a boolean result.
-This result is then used to filter the table.
+In addition to limiting the number of rows that are returned, it is possible to
+filter the rows using expressions. Expressions are constructed very similarly to
+the way they are in pandas.  Ibis expressions are constructed from operations on
+columns in a table which return a boolean result.  This result is then used to
+filter the table.
 
 
 ```{python}
@@ -402,10 +404,11 @@ df.sort_values(
 ).head(5)
 ```
 
-The same operation in Ibis would look like the following. Note that the index values of the
-resulting `DataFrame` start from zero and count up, whereas in the example above, they retain
-their original index value. This is simply due to the fact that rows in tables don't necessarily
-have a stable index in database backends, so the index is just generated on the result.
+The same operation in Ibis would look like the following. Note that the index
+values of the resulting `DataFrame` start from zero and count up, whereas in the
+example above, they retain their original index value. This is because rows in
+tables don't necessarily have a stable index in database backends, so the index
+is generated on the result.
 
 
 ```{python}