diff --git a/daqviewer/tables.py b/daqviewer/tables.py
index a952ba9..fc0fa10 100644
--- a/daqviewer/tables.py
+++ b/daqviewer/tables.py
@@ -5,15 +5,25 @@ import dash_table
 import dash_core_components as dcc
 import dash_html_components as html
 import pandas as pd
+import numpy as np
+
 
 csv_name = os.path.dirname(__file__) + '../statistics.csv'
-df = pd.read_csv(csv_name, index_col=0).T
+df = pd.read_csv(csv_name)
+
+# Round floats
+df.iloc[:, 1:] = np.round(df.iloc[:, 1:] * 100) / 100
+
+var_list = ['H_sig', 'H_1%', 'H_max', 'Hm0', 'Tp', 'Tp1']
+df = df[['location'] + var_list]
+
 # add an id column and set it as the index
 # in this case the unique ID is just the country name, so we could have just
 # renamed 'country' to 'id' (but given it the display name 'country'), but
 # here it's duplicated just to show the more general pattern.
 df['id'] = df.index
-# df.set_index('location', inplace=True, drop=False)
+# df.set_index('id', inplace=True, drop=False)
+
 
 app = dash.Dash(__name__)
 
@@ -21,7 +31,7 @@ app.layout = html.Div([
     dash_table.DataTable(
         id='datatable-row-ids',
         columns=[
-            {'name': i, 'id': i} for i in df.columns
+            {'name': i, 'id': i, 'deletable': True} for i in df.columns
             # omit the id column
             if i != 'id'
         ],
@@ -78,7 +88,7 @@ def update_graphs(row_ids, selected_row_ids, active_cell):
             figure={
                 'data': [
                     {
-                        'x': dff.index,
+                        'x': dff['id'],
                         'y': dff[column],
                         'type': 'bar',
                         'marker': {'color': colors},
@@ -98,7 +108,7 @@ def update_graphs(row_ids, selected_row_ids, active_cell):
         # check if column exists - user may have deleted it
         # If `column.deletable=False`, then you don't
         # need to do this check.
-        for column in dff.columns
+        for column in ['pop', 'lifeExp', 'gdpPercap'] if column in dff
     ]