Merge branch 'dev' into feature/structure

Author: gauthampughazhendhi

README.md

@@ -2,7 +2,7 @@
 
 ## Accessing the App via Heroku
 
-Link to Heroku app: [tsunami-events-dashboard](https://dashboard.heroku.com/apps/tsunami-events-dashboard)
+Link to Live App: [Tsunami Events Dashboard](https://tsunami-events-dashboard.herokuapp.com/)
 
 ## Description of the App Interface
 

docs/reflections-milestone2.md

@@ -0,0 +1,23 @@
+# Reflections for Milestone 2
+
+*By **DSCI 532 Group 11***
+
+## What we have implemented
+In this milestone, we have attempted to create three plots. 
+First, a map plot highlighting the intensity of earthquakes and the countries that were affected by the tsunami (underwater earthquakes).
+Second, a scatter plot to plot the trend of the earthquakes according to its intensity on the Richter Scale.
+Third, a bar chart to highlight the top 10 tsunamis with the highest tsunami intensity of a given time period. (This is different from the earthquake intensity on the Richter Scale).
+
+To use this dashboard, the user will be able to toggle the specific years and countries that they will like to examine on the left sidebar. 
+The default argument for the time period for all three plots will from 1802 to 2022. 
+The default argument for the countries for the map plot and scatter plot will be all countries. 
+The scatter plot will highlight the top 10 countries from 1802 to 2022.
+
+The bar chart will only take in the values for the years, and not the countries as it 
+will display the top 10 most intense tsunamis across the world based on time period specified. 
+
+## What could be improved
+The structure of the dashboard needs to be improved greatly to make it more streamlined. Moreover, we would like to increase the functionality of the sidebar where users can collapse it,
+such that the plot is rendered larger. Moreover, we would like to add a buttom besides the scatter plot and bar chart, to inform readers about how to interpret the 'Richter Scale' and 'Tsunami Intensity'.
+
+The convention of the naming of the functions within each component can also be improved, to allow future collaborators to understand our code with ease.

src/components/dropdown.py

@@ -6,6 +6,22 @@
 PROCESSED_DATA_PATH = "data/processed/tsunami-events.csv"
 
 def preprocess(year_start, year_end):
+        """The function to return the processed dataframe with a new index column
+        and combination column of the country and year. Also filters the df
+        based on the callback year slider for tsunamis occurring between
+        specific dates, then reorders by tsunami intensity.
+    Parameters
+    ----------
+    year_start : int
+        the lower bound of the range of years selected by user
+    year_end : int
+        the upper bound of the range of years selected by user
+    Returns
+    -------
+    df:
+        a processed dataframe with additional columns and filtered
+        data
+    """
     df = pd.read_csv(PROCESSED_DATA_PATH)
     df['tsunami_instance'] = range(1, len(df) + 1)
     df['tsunami_instance'] = df.index
@@ -17,6 +33,20 @@ def preprocess(year_start, year_end):
     return df
 
 def create_bar_plot(year_start, year_end):
+        """The function to create a bar graph of the highest intensity
+        tsunamis between the year_start and year_end.
+    Parameters
+    ----------
+    year_start : int
+        the lower bound of the range of years selected by user
+    year_end : int
+        the upper bound of the range of years selected by user
+    Returns
+    -------
+    bar plot object
+        horizontal bar graph of greatest intensity tsunamis with tooltip
+        to glean further information when hovering over each bar.
+    """
     df = preprocess(year_start, year_end)
     chart = alt.Chart(df).mark_bar().encode(
         x=alt.X('tsunami_intensity:Q', title = 'Tsunami Intensity', scale=alt.Scale(domain=(0, 12))),