Added World Map and organized app.py

app.py

@@ -9,43 +9,78 @@
 import streamlit as st
 import altair as alt
 import pandas as pd
+import pycountry
+import geopandas as gpd
 from vega_datasets import data
  
-st.title('Vizualization for Experts')
-
-st.subheader('This page will contain the entire dashboard.')
-
-st.text("*Dashboard Introduction*")
-
-
-st.text("*Brief description of Narrative*")
-
-
-st.text("*World map viz here*")
-
-
-st.text("*Interactive viz here*")
-
-
-'''
-####### Loading Data #######
-
-# 1. Contracts data
-data = pd.read_csv("/Users/sharanya/Documents/SEMESTERS/7- FALL 2024/IS445/FinalProject/IS445_VizForExperts/contract_awards_in_investment_project_financing.csv")
-# 2. World Map dataset
-world_map = alt.topo_feature(data.world_110m.url, feature='countries')
+ 
+st.title('World Bank Contracts Analysis')
 
-####### Loading Data #######
-from iso3166 import countries_by_name
-'''
 
-import streamlit as st
-import pandas as pd
-import altair as alt
+# Reading Main Data
 
 url = "contract_awards_in_investment_project_financing_22-11-2024.csv"
 df = pd.read_csv(url)
 
+
+############################################################################################################
+##################################### WORLD MAP - SHARANYA #####################################
+
+st.header("World Map")
+
+# Prompt for selecting country
+st.write("Click a country to see its contract data over time")
+
+###### 
+@st.cache_data
+def get_country_data():
+    # Mapping numeric codes to country names
+    country_data = []
+    for country in pycountry.countries:
+        try:
+            country_data.append({
+                'id': int(country.numeric),
+                'name': country.name
+            })
+        except:
+            continue
+    return pd.DataFrame(country_data)
+
+countries = alt.topo_feature(data.world_110m.url, 'countries')
+country_df = get_country_data()
+
+# Interactive selection tool initialization
+selection = alt.selection_single(fields=['name'])
+
+# World Map with Interactions
+map_chart = alt.Chart(countries).mark_geoshape(
+    stroke='white'
+).transform_lookup(
+    lookup='id',
+    from_=alt.LookupData(country_df, 'id', ['name'])
+).encode(
+    tooltip='name:N',
+    # Color changes when country is selected
+    color=alt.condition(selection, 
+                       alt.value('green'), 
+                       alt.value('lightgray')),
+).properties(
+    width=900,
+    height=400
+).project('naturalEarth1').add_selection(selection)
+
+# Displaying the map
+st.altair_chart(map_chart, use_container_width=True)
+
+
+############################################################################################################
+##################################### TIME SERIES PLOT - JEENAL #####################################
+
+# Code to be added 
+
+############################################################################################################
+##################################### CORRELATION PLOT - HARSHI #####################################
+
 numeric_columns = df.select_dtypes(include=['float64', 'int64']).columns
 st.header("Correlation Analysis")
 
@@ -71,3 +106,7 @@ correlation_plot = (
     )
 )
 st.altair_chart(correlation_plot, use_container_width=True)
+
+
+
+