From 35fc9665448b4213a8045c681231d3991a40315d Mon Sep 17 00:00:00 2001
From: danielon-5 <71201117+danielon-5@users.noreply.github.com>
Date: Thu, 18 Mar 2021 00:00:24 -0600
Subject: [PATCH 1/2] Update logreg usage example

Fix the usage example for logreg and style in first paragraph
---
 README.md | 28 +++++++++++++++++++---------
 1 file changed, 19 insertions(+), 9 deletions(-)

diff --git a/README.md b/README.md
index f58f1b1..3288e3f 100644
--- a/README.md
+++ b/README.md
@@ -6,7 +6,7 @@ DRY out your regression analysis!
 
 ## Python Package for Inferential Regression and EDA Analysis!
 
-As Data Scientists, being able to perform Exploratory Data Analysis as well as Regression Analysis are paramount to the process of analyzing trends in data. Moreover, following the DRY (Do Not Repeat Yourself) principle is regarded as a majority priority for maximizing code quality. Yet, often times Data Scientists facing these tasks will start the entire process from scratch, wasting both time and effort while compromising code quality. The aridanalysis package strives to remedy this problem by giving users an easy-to-implement EDA function alongside 3 robust statistical tests that will simplify these analytical processes and produce an easy to read interpretation of the input data. Users will no longer have to write many lines of code to explore their data effectively. 
+As Data Scientists, being able to perform Exploratory Data Analysis as well as Regression Analysis are paramount to the process of analyzing trends in data. Moreover, following the DRY (Do Not Repeat Yourself) principle is regarded as a majority priority for maximizing code quality. Yet, often times Data Scientists facing these tasks will start the entire process from scratch, wasting both time and effort while compromising code quality. The `aridanalysis` package strives to remedy this problem by giving users an easy-to-implement EDA function alongside 3 robust statistical tests that will simplify these analytical processes and produce an easy to read interpretation of the input data. Users will no longer have to write many lines of code to explore their data effectively. 
 
 ## Package Functions
 
@@ -50,16 +50,26 @@ tdf = pd.DataFrame(
 )
 >>> aa.arid_linreg(tdf, y) 
 
+data = [
+    [32, "male", 80, 0],
+    [26, "female", 65, 1],
+    [22, "female", 75, 1],
+    [36, "male", 85, 0],
+    [45, "male", 82, 1],
+    [18, "female", 57, 0],
+    [57, "male", 60, 1],
+]
+
 df = pd.DataFrame(
-    {
-        "x1": [1, 0, 0],
-        "x2": [0, 1.0, 0],
-        "x3": [0, 0, 1],
-        "x4": ["a", "a", "b"],
-        "y": [1, 0, 0],
-    }
+    data, 
+    columns=[
+        "x1", 
+        "x2", 
+        "x3", 
+        "y"
+    ]
 )
->>> aa.arid_logreg(df, y)
+>>> aa.arid_logreg(df, Target)
 
 df = pd.DataFrame(
     {

From 4e8d0685a182ee91026a03bd9d6170ee9bc61bbb Mon Sep 17 00:00:00 2001
From: danielon-5 <71201117+danielon-5@users.noreply.github.com>
Date: Thu, 18 Mar 2021 00:01:26 -0600
Subject: [PATCH 2/2] fix typo in logreg example parameters

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 3288e3f..e3d9869 100644
--- a/README.md
+++ b/README.md
@@ -69,7 +69,7 @@ df = pd.DataFrame(
         "y"
     ]
 )
->>> aa.arid_logreg(df, Target)
+>>> aa.arid_logreg(df, y)
 
 df = pd.DataFrame(
     {