diff --git a/README.md b/README.md
new file mode 100644
index 000000000..e69de29bb
diff --git a/base/templates/base/home.html b/base/templates/base/home.html
index a354839a5..192f806e5 100644
--- a/base/templates/base/home.html
+++ b/base/templates/base/home.html
@@ -13,18 +13,17 @@
 
     <br>
     <br>
-    
-    <div class="row">
-        <div class="col d-flex justify-content-center">
-            <h3>
-                <i class="fas fa-upload"></i> Import a file
-            </h3>
-        </div>
-    </div>
 
     <div class="row">
-        <div class = "mx-auto p-4 text-center">
+        <div class="col d-flex justify-content-center">
             <form action="{% url 'home' %}" id="csv" method="post" enctype="multipart/form-data">
+                <label style="display:flex;
+                flex-direction:column;
+                align-items: center;">
+                    <h3>
+                        <i class="fas fa-upload"></i> Import a file
+                    </h3>
+                </label>
                 {% csrf_token %}
                 <input type="file"
                     title="Upload excel file"
@@ -37,19 +36,6 @@
                     style="border: 1px solid green; padding:5px; border-radius: 2px; cursor: pointer;">
             </form>
         </div>
-    </div>
-
-    <br>
-    <div class="row">
-        <div class="col">
-            <div class="scrollit">
-                {{ data_to_display|safe }}
-            </div>
-        </div>
-    </div>
-    <br>
-    
-    <div class="row justify-content-center">
         <div class="col d-flex justify-content-center">
             <form action="{% url 'home' %}" name="plot" method="POST" id="stats">
                 <label style="display:flex;
@@ -79,30 +65,22 @@
                 <input type="submit" value="Plot" name="plot">
             </form>
         </div>
-
-        <div class="col d-flex justify-content-center multi-button">
-            <form action="{% url 'home' %}" method="POST">
-                {% csrf_token %}
-                <label style="display:flex;
-                flex-direction:column;
-                align-items: center;">
-                    <h3>
-                        <i class="fas fa-cog"></i> Preprocessing
-                    </h3>
-                </label>
-                <div class="multi-button">
-                    <button type="submit" name="std" class="button-6" role="button" >Standardization</button>
-                    <button type="submit" name="onehot" style="margin:0;margin-left:16px;" class="button-6" role="button" >One Hot Encoding</button>
-                    <button type="submit" name="imp" style="margin:0;margin-left:16px;" class="button-6" role="button" >Imputations</button>
-                </div>
-            </form>
-        </div>
     </div>
+
     <br>
-    <div class="row justify-content-center">
+    <div class="row">
+        <div class="col d-flex justify-content-center">
+            <div class="scrollit">
+                {{ data_to_display|safe }}
+            </div>
+        </div>
         <div class="col d-flex justify-content-center">
             {{ fig|safe }}
         </div>
+    </div>
+    <br>
+    <br>
+    <div class="row justify-content-center">
         <div class="col d-flex justify-content-center">
             <form action="{% url 'home' %}" method="POST">
                 <label style="display:flex;
@@ -125,6 +103,25 @@
                 </div>
             </form>
         </div>
+        <div class="col d-flex justify-content-center"> 
+            <div class="col d-flex justify-content-center multi-button">
+                <form action="{% url 'home' %}" method="POST">
+                    {% csrf_token %}
+                    <label style="display:flex;
+                    flex-direction:column;
+                    align-items: center;">
+                        <h3>
+                            <i class="fas fa-cog"></i> Preprocessing
+                        </h3>
+                    </label>
+                    <div class="multi-button">
+                        <button type="submit" name="std" class="button-6" role="button" >Standardization</button>
+                        <button type="submit" name="onehot" style="margin:0;margin-left:16px;" class="button-6" role="button" >One Hot Encoding</button>
+                        <button type="submit" name="imp" style="margin:0;margin-left:16px;" class="button-6" role="button" >Imputations</button>
+                    </div>
+                </form>
+            </div>
+        </div>
     </div>
 </div>
 {% endblock content%}
diff --git a/base/views.py b/base/views.py
index 645ce1820..829ba7576 100644
--- a/base/views.py
+++ b/base/views.py
@@ -6,6 +6,8 @@ from sklearn.preprocessing import OneHotEncoder
 from sklearn.impute import SimpleImputer
 from sklearn.preprocessing import StandardScaler
 import numpy as np
+from pandas.api.types import is_string_dtype
+from pandas.api.types import is_numeric_dtype
 from . import utils
 
 
@@ -18,19 +20,15 @@ def home(request):
     global excel_file_name
     global excel_file_name_preprocessed
     
-    # if file for preprocessing does not exist create it
-    if os.path.exists(excel_file_name_preprocessed) == False:
-        df = pd.read_csv(excel_file_name) 
-        df.to_csv(excel_file_name_preprocessed)
-    
     if request.method == 'POST':
-        print("HEYEYEYEYEYE")
-        feature1 = request.POST.get('feature1')
-        feature2 = request.POST.get('feature2')
         if 'csv' in request.POST:
             excel_file = request.FILES["excel_file"]
             excel_file_name = request.FILES["excel_file"].name
-            df = pd.read_csv(excel_file)
+            
+            # here we dont use the name of the file since the 
+            # uploaded file is not yet saved
+            # In every other case we just need the name
+            df = pd.read_csv(excel_file) 
             
             fs = FileSystemStorage() #defaults to MEDIA_ROOT
             request.session['excel_file_name'] = excel_file_name
@@ -41,29 +39,49 @@ def home(request):
             fs = FileSystemStorage() #defaults to MEDIA_ROOT
             request.session['excel_file_name_preprocess'] = excel_file_name_preprocessed
             fs.save(excel_file_name_preprocessed, excel_file)
-        
-        if 'std' in request.POST:
-            preprocess(excel_file_name_preprocessed, 'std')
-        if 'onehot' in request.POST:
-            preprocess(excel_file_name_preprocessed, 'onehot')  
-        if 'imp' in request.POST:
-            preprocess(excel_file_name_preprocessed, 'imp')
-        
-        if 'plot' in request.POST:
-            fig = stats(excel_file_name, feature1, feature2)
+                    # if file for preprocessing does not exist create it
+            if os.path.exists(excel_file_name_preprocessed) == False:
+                df.to_csv(excel_file_name_preprocessed)
+                
+            feature1 = df.columns[0]
+            feature2 = df.columns[1]
+            request.session['feature1'] = feature1
+            request.session['feature2'] = feature2
             
-        if 'logit' in request.POST:
-            training(excel_file_name_preprocessed, 'logit')
-        if 'xgb' in request.POST:
-            training(excel_file_name_preprocessed, 'xgb')
+        elif 'plot' in request.POST:
+            df = pd.read_csv(excel_file_name)
+            feature1 = request.POST.get('feature1')
+            feature2 = request.POST.get('feature2')
+            print(feature1)
+            request.session['feature1'] = feature1
+            request.session['feature2'] = feature2
+        else:
+            df = pd.read_csv(excel_file_name)
+            
+            if 'std' in request.POST:
+                preprocess(excel_file_name_preprocessed, 'std')
+            if 'onehot' in request.POST:
+                preprocess(excel_file_name_preprocessed, 'onehot')  
+            if 'imp' in request.POST:
+                preprocess(excel_file_name_preprocessed, 'imp')
+                
+            if 'logit' in request.POST:
+                training(excel_file_name_preprocessed, 'logit')
+            if 'xgb' in request.POST:
+                training(excel_file_name_preprocessed, 'xgb')
     else:
-        # if not post, meaning either a lanch of the page or a refresh
-        feature1 = 'MonthlyCharges'
-        feature2 = 'tenure'
-        fig = stats(excel_file_name, feature1, feature2)
-    
-    # collect the data to render
-    df = pd.read_csv(excel_file_name)
+        df = pd.read_csv(excel_file_name)
+            # if file for preprocessing does not exist create it
+        if os.path.exists(excel_file_name_preprocessed) == False:
+            df.to_csv(excel_file_name_preprocessed)     
+        
+        feature1 = df.columns[0]
+        feature2 = df.columns[1]
+        request.session['feature1'] = feature1
+        request.session['feature2'] = feature2
+        
+    fig = stats(excel_file_name, request.session['feature1'], request.session['feature2'])
+        
     data_to_display = df[:5].to_html()
 
     request.session['data_to_display'] = data_to_display
@@ -71,14 +89,23 @@ def home(request):
     request.session['excel_file_name_preprocessed'] = excel_file_name_preprocessed
     labels = df.columns
     
-    context = {'data_to_display': data_to_display, 'excel_file': excel_file_name, 'labels': labels, 'fig': fig, 'feature1': feature1, 'feature2': feature2}
+    context = {'data_to_display': data_to_display, 'excel_file': excel_file_name, 'labels': labels, 'fig': fig, 'feature1': request.session['feature1'], 'feature2': request.session['feature2']}
     return render(request,'base/home.html', context)
 
 def stats(name, feature1, feature2):
     global fig
     df = pd.read_csv(name)
     import plotly.express as px
-    fig = px.scatter(df, x=feature1, y=feature2, color='Churn')
+    if is_numeric_dtype(df[feature1]) and is_numeric_dtype(df[feature2]):
+        print("if")
+        fig = px.scatter(df, feature1, feature2, color='DEATH_EVENT')
+    elif is_string_dtype(df[feature1]) and is_string_dtype(df[feature2]):
+        print("elseif")
+        fig = px.histogram(df, feature1)
+    else:
+        print("else")
+        fig = px.strip(df, feature1, feature2)
+    
     fig = fig.to_html(full_html=False)
     return fig
 
diff --git a/db.sqlite3 b/db.sqlite3
index e45d1517d..d91c9b6fc 100644
Binary files a/db.sqlite3 and b/db.sqlite3 differ
diff --git a/templates/main.html b/templates/main.html
index b603b0d62..9e765e7b3 100644
--- a/templates/main.html
+++ b/templates/main.html
@@ -16,8 +16,10 @@
 
     .scrollit {
       overflow: auto;
+      position: fixed; 
+      float: left;
       height: auto;
-      width: 60%;
+      width: 40%;
       max-width: fit-content;
       margin: 0px auto;
     }