Fine tuning

app.py

@@ -16,6 +16,9 @@ import graphviz as graphviz
 # load data
 data = pd.read_csv('german_credit_from_r.csv')
 
+# remove vars
+data.drop(['Foreign_worker', 'Gender'], axis=1, inplace=True)
+
 # recode credit risk
 data['Credit_risk'] = data['Credit_risk'].map({'GOOD': 0, 'BAD': 1})
 
@@ -55,15 +58,20 @@ The dataset contains the following variables:
 - Job
 - Number of people being liable to provide maintenance for
 - Telephone
-- Foreign worker
-- Gender
+- Credit risk (1 = bad, 0 = good)
 """
 )
 #st.divider()
 
 # header: data
 st.header('Data')
-data
+# move Credit_risk to the end
+cols = data.columns.tolist()
+cols.remove('Credit_risk')
+cols.append('Credit_risk')
+data = data[cols]
+st.write('First 20 rows of the dataset:')
+data.loc[1:20, :]
 #st.divider()
 
 # header: predictors