diff --git a/front/front_pages/2_Analytics.py b/front/front_pages/2_Analytics.py
index ff84ca4..c29ff84 100644
--- a/front/front_pages/2_Analytics.py
+++ b/front/front_pages/2_Analytics.py
@@ -41,7 +41,7 @@
             lambda td:
                 f"{int(td.total_seconds() // 3600):02}:{int((td.total_seconds() % 3600) // 60):02}:{int(td.total_seconds() % 60):02}"
         )
-        st.write(shown_df, hide_index=True)
+        st.write(shown_df)
 
     with col2:
         st.markdown("""
diff --git a/front/metrics.py b/front/metrics.py
index 5c46cad..544a9cf 100644
--- a/front/metrics.py
+++ b/front/metrics.py
@@ -13,14 +13,14 @@ def calculate_metric(df: pd.DataFrame, col: str, days: int) -> pd.DataFrame:
 
 def calculate_ctl(df: pd.DataFrame) -> pd.DataFrame:
     ctl_days = 42
-    df['ctl'] = 0
+    df['ctl'] = 0.
 
     return calculate_metric(df, 'ctl', ctl_days)
 
 
 def calculate_atl(df: pd.DataFrame) -> pd.DataFrame:
     atl_days = 7
-    df['atl'] = 0
+    df['atl'] = 0.
 
     return calculate_metric(df, 'atl', atl_days)
 
@@ -28,7 +28,7 @@ def calculate_atl(df: pd.DataFrame) -> pd.DataFrame:
 def calculate_form(df: pd.DataFrame) -> pd.DataFrame:
     for i in range(len(df)):
         if i == 0:
-            df['form'] = 0
+            df['form'] = 0.
         else:
             df.loc[i, 'form'] = df.loc[i - 1, 'ctl'] - df.loc[i - 1, 'atl']
 
diff --git a/front/user/user.py b/front/user/user.py
index 1ea9e9e..36d5c36 100644
--- a/front/user/user.py
+++ b/front/user/user.py
@@ -133,9 +133,9 @@ def _get_query(self, table: str, select: str = "*", wkt_id: int = None, order_by
 
     def _prep_calendar(self, data: pd.DataFrame, sport: str) -> pd.DataFrame:
         cols = ['activity_id', 'date', 'duration']
-        data = data[cols]
-        data['title'] = sport
-        data['end'] = data.apply(lambda row: row['date'] + time_to_timedelta(row['duration']), axis=1)
+        data = data[cols].copy()
+        data.loc[:, 'title'] = sport
+        data.loc[:, 'end'] = data.apply(lambda row: row['date'] + time_to_timedelta(row['duration']), axis=1)
         return data
 
     def _process_duration(self, total: pd.DataFrame) -> pd.DataFrame: