diff --git a/README.md b/README.md
index fa22337..f71fe22 100644
--- a/README.md
+++ b/README.md
@@ -66,7 +66,7 @@ Follow the steps below to contribute to this project.
 
 Install the required dependencies from the `requirements.txt` file.
 
-If using `pip` then `pip install requirements.txt`.
+If using `pip` then `pip install -r requirements.txt`.
 
 If using `conda` then follow these steps to create an environment with the right dependencies:
 
diff --git a/src/VPPMod.py b/src/VPPMod.py
index 1232d5b..4f66d95 100644
--- a/src/VPPMod.py
+++ b/src/VPPMod.py
@@ -19,6 +19,7 @@
 from src.HydroMod import HydroMod
 from src.UtilsMod import KNOTS_TO_MPS, json_write, polar_plot, sail_chart
 from src.YachtMod import Yacht as YachtClass
+from rich.progress import track  # For progress bar
 
 logger = logging.getLogger(__name__)
 debug_mode = logging.getLogger().getEffectiveLevel() == logging.DEBUG
@@ -202,7 +203,7 @@ def run(self, verbose=False):
         if not self.upToDate:
             raise "VPP run stop: no analysis set!"
 
-        for i, tws in enumerate(self.tws_range):
+        for i, tws in track(enumerate(self.tws_range), description="Analysing...", total=len(self.tws_range)):
             logging.debug("Sailing in TWS : %.1f" % (tws / KNOTS_TO_MPS))
 
             for n in range(self.Nsails):
@@ -329,6 +330,58 @@ def results(self):
 
     def write(self, fname):
         json_write(self.results(), fname)
+        
+    def write_csv(self, fname):
+        import csv
+        
+        # Init a counter for how many values have been used to average the boat speed for a given wind direction and speed:
+        avg_counter = np.zeros((37, 20))
+    
+        with open(fname, mode="w", newline="") as file:
+            writer = csv.writer(file, delimiter=";")
+            # Write header with TWS in knots
+            writer.writerow(["TWA\TWS", "2", "4", "6", "8", "10", "12", "14", "16", "18", "20", "22", "24", "26", "28", "30", "32", "34", "36", "38", "40"])
+            # Loop through every degree from 0°to 180° in 5° increments
+            for angle in range(0, 181, 5):
+                # Init row to write
+                row = [None] * 21
+                # Set angle
+                row[0] = angle
+                # Go through each TWS and get the corresponding boat speed for the current angle
+                for i, tws in enumerate(self.tws_range):
+                    # Change tws to knots
+                    tws = tws / KNOTS_TO_MPS
+                    for j, twa in enumerate(self.twa_range):
+                        # Get closest wind speed and find column in openCPN. Note we are stuck using these until this issue (https://github.com/rgleason/polar_pi/issues/34) gets dealt with
+                        closest_wind_speed_column = round(tws/2)
+                        # If closest wind speed column is zero, increment by one so we don't overwrite the angle column.
+                        if closest_wind_speed_column == 0:
+                            closest_wind_speed_column += 1
+                        # Get closest angle and find see if it matches the current angle we are looking for
+                        closest_angle = round(twa/5)*5
+                        # If the closest_angle matches the angle we're currently working with then get the speeds, otherwise, skip to next entry
+                        if closest_angle == angle:
+                            # Get boat speed for give wind angle and speed
+                            boat_speed = self.store[i, j, 0, 0]
+                            # Get row number
+                            row_number = int(angle/5)
+
+                            # Update the row with the boat speed for this angle and wind speed
+                            # If there has not been a value used yet, set the value to the boat speed, otherwise, average the current value with the new boat speed
+                            if row[closest_wind_speed_column] is None:
+                                row[closest_wind_speed_column] = boat_speed
+                            else:
+                                # Find out how many values have been used to make this average
+                                num_values = avg_counter[row_number, closest_wind_speed_column]
+                                # Average the current boat speed with the already logged average boat speed
+                                row[closest_wind_speed_column] = (row[closest_wind_speed_column] * num_values + boat_speed) / (num_values + 1)
+
+                            # Update the average counter for this angle and wind speed
+                            avg_counter[row_number, closest_wind_speed_column] += 1
+                            # Print out the speed of the vessel given the angle and wind speed
+
+                # Write the row to the csv file
+                writer.writerow(row)
 
     def polar(self, n=1, save=False, fname="Polars.png"):
         polar_plot([self], n, save, fname)