Another refactoring

bigbio · Sep 23, 2024 · 5e56b21 · 5e56b21
1 parent 7a08e82
commit 5e56b21
Show file tree

Hide file tree

Showing 2 changed files with 8 additions and 8 deletions.
diff --git a/docs/README.data.md b/docs/README.data.md
@@ -1,9 +1,9 @@
-## fsspark - data structures
+## fslite - data structures
 
 --- 
 
-`fsspark` is a Python package that provides a set of tools for feature selection in Spark. 
-Here we describe the main data structures used in `fsspark` and how to use them.
+`fslite` is a Python package that provides a set of tools for feature selection in Spark. 
+Here we describe the main data structures used in `fslite` and how to use them.
 
 ### Input data
 
@@ -32,7 +32,7 @@ The following is an example of a TSV file with a binary response variable:
 
 ### Import functions
 
-`fsspark` provides two main functions to import data from a TSV file.
+`fslite` provides two main functions to import data from a TSV file.
 
 - `import_table` - Import data from a TSV file into a Spark Data Frame (sdf).
 
@@ -57,7 +57,7 @@ psdf = import_table_as_psdf('data.tsv.bgz',
 
 ### The Feature Selection Spark Data Frame (FSDataFrame)
 
-The `FSDataFrame` (**Figure 1**) is a core functionality of `fsspark`. It is a wrapper around a Spark Data Frame (sdf) 
+The `FSDataFrame` (**Figure 1**) is a core functionality of `fslite`. It is a wrapper around a Spark Data Frame (sdf) 
 that provides a set of methods to facilitate feature selection tasks. The `FSDataFrame` is initialized 
 with a Spark Data Frame (sdf) or a Pandas on Spark Data Frame (psdf) and two mandatory arguments: 
 `sample_col` and `label_col`. The `sample_col` argument is the name of the column in the sdf that 

diff --git a/docs/README.methods.md b/docs/README.methods.md
@@ -1,10 +1,10 @@
 
-# fsspark - features selection methods 
+# fslite - features selection methods 
 
 ---
 
-`fsspark `includes a set of methods to perform feature selection and machine learning based on spark.
-A typical workflow written using `fsspark` can be divided roughly in four major stages:
+`fslite `includes a set of methods to perform feature selection and machine learning based on spark.
+A typical workflow written using `fslite` can be divided roughly in four major stages:
 
 1) data pre-processing. 
 2) univariate filters.