Fix doc typos and minor clarification (#207)

* wip * wip * wip
databrickslabs · Apr 18, 2023 · 54d7948 · 54d7948
1 parent b464bd9
commit 54d7948
Show file tree

Hide file tree

Showing 2 changed files with 9 additions and 3 deletions.
diff --git a/docs/source/DISTRIBUTIONS.md b/docs/source/DISTRIBUTIONS.md
@@ -22,7 +22,13 @@ The following distributions are supported:
 - Exponential distribution
 
 > Note the `distribution` option will have no effect for values that are not randomly generated as
-> per use of the `random` option
+> per use of the `random` option.
+> 
+> For values generated randomly, continuous distributions can still be used with discrete values such as strings
+> as the underlying random numbers used to select the appropriate discrete values will be drawn from the specified
+> distribution. So, for discrete values, the frequency of occurrence of particular values should conform approximately
+> to the underlying distribution.
+
 
 ### Examples 
 

diff --git a/docs/source/generating_from_existing_data.rst b/docs/source/generating_from_existing_data.rst
@@ -20,7 +20,7 @@ For more information, see :data:`~dbldatagen.data_analyzer.DataAnalyzer`
 Analyzing the data to be synthesized
 ------------------------------------
 
-You can use the ``summarizeToDf()`` method to generate a summary analysis of a dataframe.
+You can use the ``summarizeToDF()`` method to generate a summary analysis of a dataframe.
 
 Example:
 
@@ -32,7 +32,7 @@ Example:
 
    analyzer = dg.DataAnalyzer(sparkSession=spark, df=dfSource)
 
-   display(analyzer.summarizeToDf())
+   display(analyzer.summarizeToDF())
 
 Generating code to produce the synthetic data set
 -------------------------------------------------