Fix some capitalization (#392)

pola-rs · Aug 30, 2023 · 1e0beaf · 1e0beaf
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diff --git a/docs/getting-started/reading-writing.md b/docs/getting-started/reading-writing.md
@@ -1,6 +1,6 @@
-# Reading & Writing
+# Reading & writing
 
-Polars supports reading & writing to all common files (e.g. csv, json, parquet), cloud storage (S3, Azure Blob, BigQuery) and databases (e.g. postgres, mysql). In the following examples we will show how to operate on most common file formats. For the following dataframe
+Polars supports reading and writing to all common files (e.g. csv, json, parquet), cloud storage (S3, Azure Blob, BigQuery) and databases (e.g. postgres, mysql). In the following examples we will show how to operate on most common file formats. For the following dataframe
 
 {{code_block('getting-started/reading-writing','dataframe',['DataFrame'])}}
 

diff --git a/docs/user-guide/concepts/contexts.md b/docs/user-guide/concepts/contexts.md
@@ -49,7 +49,7 @@ In the `filter` context you filter the existing dataframe based on arbitrary exp
 --8<-- "python/user-guide/concepts/contexts.py:filter"
 ```
 
-## Group by / Aggregation
+## Group by / aggregation
 
 In the `group_by` context, expressions work on groups and thus may yield results of any length (a group may have many members).
 

diff --git a/docs/user-guide/concepts/data-structures.md b/docs/user-guide/concepts/data-structures.md
@@ -1,4 +1,4 @@
-# Data Structures
+# Data structures
 
 The core base data structures provided by Polars are `Series` and `DataFrames`.
 

diff --git a/docs/user-guide/concepts/lazy-vs-eager.md b/docs/user-guide/concepts/lazy-vs-eager.md
@@ -1,4 +1,4 @@
-# Lazy / Eager API
+# Lazy / eager API
 
 `Polars` supports two modes of operation: lazy and eager. In the eager API the query is executed immediately while in the lazy API the query is only evaluated once it is 'needed'. Deferring the execution to the last minute can have significant performance advantages that is why the Lazy API is preferred in most cases. Let us demonstrate this with an example:
 

diff --git a/docs/user-guide/expressions/column-selections.md b/docs/user-guide/expressions/column-selections.md
@@ -1,4 +1,4 @@
-# Column Selections
+# Column selections
 
 Let's create a dataset to use in this section:
 
@@ -9,7 +9,7 @@ Let's create a dataset to use in this section:
 --8<-- "python/user-guide/expressions/column-selections.py:selectors_df"
 ```
 
-## Expression Expansion
+## Expression expansion
 
 As we've seen in the previous section, we can select specific columns using the `pl.col` method. It can also select multiple columns - both as a means of convenience, and to _expand_ the expression.
 

diff --git a/docs/user-guide/expressions/folds.md b/docs/user-guide/expressions/folds.md
@@ -5,7 +5,7 @@ etc. However, when you need a more complex aggregation the default methods `Pola
 
 The `fold` expression operates on columns for maximum speed. It utilizes the data layout very efficiently and often has vectorized execution.
 
-### Manual Sum
+### Manual sum
 
 Let's start with an example by implementing the `sum` operation ourselves, with a `fold`.
 

diff --git a/docs/user-guide/expressions/functions.md b/docs/user-guide/expressions/functions.md
@@ -11,7 +11,7 @@ In the examples below we will use the following `DataFrame`:
 --8<-- "python/user-guide/expressions/functions.py:dataframe"
 ```
 
-## Column Naming
+## Column naming
 
 By default if you perform an expression it will keep the same name as the original column. In the example below we perform an expression on the `nrs` column. Note that the output `DataFrame` still has the same name.
 
@@ -50,7 +50,7 @@ In case of multiple columns for example when using `all()` or `col(*)` you can a
 [:material-api: `suffix`](https://pola-rs.github.io/polars/py-polars/html/reference/expressions/api/polars.Expr.suffix.html)
 [:material-api: `map_alias`](https://pola-rs.github.io/polars/py-polars/html/reference/expressions/api/polars.Expr.map_alias.html)
 
-## Count Unique Values
+## Count unique values
 
 There are two ways to count unique values in `Polars`: an exact methodology and an approximation. The approximation uses the [HyperLogLog++](https://en.wikipedia.org/wiki/HyperLogLog) algorithm to approximate the cardinality and is especially useful for very large datasets where an approximation is good enough.
 

diff --git a/docs/user-guide/expressions/operators.md b/docs/user-guide/expressions/operators.md
@@ -1,4 +1,4 @@
-# Basic Operators
+# Basic operators
 
 This section describes how to use basic operators (e.g. addition, subtraction) in conjunction with Expressions. We will provide various examples using different themes in the context of the following dataframe.
 

diff --git a/docs/user-guide/expressions/strings.md b/docs/user-guide/expressions/strings.md
@@ -15,7 +15,7 @@ The `str` namespace can be accessed through the `.str` attribute of a column wit
 --8<-- "python/user-guide/expressions/strings.py:df"
 ```
 
-#### String Parsing
+#### String parsing
 
 `Polars` offers multiple methods for checking and parsing elements of a string. Firstly, we can use the `contains` method to check whether a given pattern exists within a substring. Subsequently, we can extract these patterns and replace them using other methods, which will be demonstrated in upcoming examples.
 
@@ -57,6 +57,6 @@ We have discussed two methods for pattern matching and extraction thus far, and
 --8<-- "python/user-guide/expressions/strings.py:replace"
 ```
 
-#### API Documentation
+#### API documentation
 
 In addition to the examples covered above, Polars offers various other string manipulation methods for tasks such as formatting, stripping, splitting, and more. To explore these additional methods, you can go to the API documentation of your chosen programming language for Polars.
diff --git a/docs/user-guide/expressions/user-defined-functions.md b/docs/user-guide/expressions/user-defined-functions.md
@@ -1,4 +1,4 @@
-# User Defined functions
+# User-defined functions
 
 !!! warning "Not updated for Python Polars `0.19.0`"
 

diff --git a/docs/user-guide/io/csv.md b/docs/user-guide/io/csv.md
@@ -1,6 +1,6 @@
 # CSV
 
-## Read & Write
+## Read & write
 
 Reading a CSV file should look familiar:
 

diff --git a/docs/user-guide/io/json_file.md b/docs/user-guide/io/json_file.md
@@ -1,6 +1,6 @@
 # JSON files
 
-## Read & Write
+## Read & write
 
 ### JSON
 

diff --git a/docs/user-guide/io/multiple.md b/docs/user-guide/io/multiple.md
@@ -1,6 +1,6 @@
 ## Dealing with multiple files.
 
-`Polars` can deal with multiple files differently depending on your needs and memory strain.
+Polars can deal with multiple files differently depending on your needs and memory strain.
 
 Let's create some files to give us some context:
 

diff --git a/docs/user-guide/lazy/query_plan.md b/docs/user-guide/lazy/query_plan.md
@@ -1,4 +1,4 @@
-# Query Plan
+# Query plan
 
 For any lazy query `Polars` has both:
 

diff --git a/docs/user-guide/misc/reference-guides.md b/docs/user-guide/misc/reference-guides.md
@@ -1,4 +1,4 @@
-# Reference Guides
+# Reference guides
 
 The api documentations with details on function / object signatures can be found here:
 

diff --git a/docs/user-guide/transformations/melt.md b/docs/user-guide/transformations/melt.md
@@ -10,7 +10,7 @@ Melt operations unpivot a DataFrame from wide format to long format
 --8<-- "python/user-guide/transformations/melt.py:df"
 ```
 
-## Eager + Lazy
+## Eager + lazy
 
 `Eager` and `lazy` have the same API.
 

diff --git a/mkdocs.yml b/mkdocs.yml
@@ -9,14 +9,14 @@ repo_name: pola-rs/polars
 # Documentation layout
 nav:
   - Home: index.md
-  - Getting Started:
+  - Getting started:
     - getting-started/intro.md
     - getting-started/installation.md
     - getting-started/series-dataframes.md
     - getting-started/reading-writing.md
     - getting-started/expressions.md
     - getting-started/joins.md
-  - User Guide:
+  - User guide:
     - user-guide/index.md
     - user-guide/installation.md
     - Concepts:
@@ -45,7 +45,7 @@ nav:
       - user-guide/transformations/concatenation.md
       - user-guide/transformations/pivot.md
       - user-guide/transformations/melt.md
-      - Time Series:
+      - Time series:
         - user-guide/transformations/time-series/parsing.md
         - user-guide/transformations/time-series/filter.md
         - user-guide/transformations/time-series/rolling.md