Update column-selection.qmd

docs/get-started/column-selection.qmd

@@ -4,16 +4,13 @@ jupyter: python3
 html-table-processing: none
 ---
 
-The `columns=` argument for functions like `.tab_spanner()` and `.cols_move()` can accept a range of arguments.
-In the above examples, we just passed a list of strings with the exact column names.
+The `columns=` argument for methods like [`tab_spanner()`](`great_tables.GT.tab_spanner`) and [`cols_move()`](`great_tables.GT.cols_move`) can accept a range of arguments. In the previous examples, we just passed a list of strings with the exact column names. However, we can specify columns using any of the following:
 
-However, we can specify columns using any of the following:
-
-* A single string column name.
-* An integer for the column's position.
-* A list of strings or integers.
-* A polars selector.
-* A function that takes a string and returns True or False.
+* a single string column name.
+* an integer for the column's position.
+* a list of strings or integers.
+* a **Polars** selector.
+* a function that takes a string and returns `True` or `False`.
 
 ```{python}
 from great_tables import GT
@@ -26,50 +23,47 @@ gt_ex
 
 ## String and integer selectors
 
-Use a list of strings or integers to select columns by name or position, respectively.
+We can use a list of strings or integers to select columns by name or position, respectively.
 
 ```{python}
-gt_ex.cols_move_to_start(["date", 1, -1])
+gt_ex.cols_move_to_start(columns=["date", 1, -1])
 ```
 
 Note the code above moved the following columns:
 
 * The string `"date"` matched the column of the same name.
-* The integer `1` matched the second column (similar to list indexing).
+* The integer `1` matched the second column (this is similar to list indexing).
 * The integer `-1` matched the last column.
 
-Moreover, the order of the list defines the order of selected columns.
-In this case, `"data"` was the first entry, so it's the very first column in the new table.
+Moreover, the order of the list defines the order of selected columns. In this case, `"data"` was the first entry, so it's the very first column in the new table.
 
-## Function selectors
+## Using function selectors
 
-A function can be used to select columns. It should take a string and returns True or False.
+A function can be used to select columns. It should take a string and returns `True` or `False`.
 
 ```{python}
-gt_ex.cols_move_to_start(lambda x: "c" in x)
+gt_ex.cols_move_to_start(columns=lambda x: "c" in x)
 ```
 
-## Polars selectors
-
-When using a polars DataFrame, you can select columns using [polars selectors](https://pola-rs.github.io/polars/py-polars/html/reference/selectors.html).
+## **Polars** selectors
 
-The example below uses polars selectors to move all columns that start with `"c"` or `"f"` to the start of the table.
+When using a **Polars** DataFrame, you can select columns using [**Polars** selectors](https://pola-rs.github.io/polars/py-polars/html/reference/selectors.html). The example below uses **Polars** selectors to move all columns that start with `"c"` or `"f"` to the start of the table.
 
 ```{python}
 import polars as pl
 import polars.selectors as cs
 
 pl_df = pl.from_pandas(exibble)
 
-GT(pl_df).cols_move_to_start(cs.starts_with("c") | cs.starts_with("f"))
+GT(pl_df).cols_move_to_start(columns=cs.starts_with("c") | cs.starts_with("f"))
 ```
 
-In general, selection should match the behaviors of the polars `DataFrame.select()` method.
+In general, selection should match the behaviors of the **Polars** `DataFrame.select()` method.
 
 ```{python}
 pl_df.select(cs.starts_with("c") | cs.starts_with("f")).columns
 ```
 
-See the [Selectors page in the polars docs](https://pola-rs.github.io/polars/py-polars/html/reference/selectors.html) for more information.
+See the [Selectors page in the polars docs](https://pola-rs.github.io/polars/py-polars/html/reference/selectors.html) for more information on this.