Update project

backend/api/main.py

@@ -16,12 +16,12 @@ def display_data():
 @app.get("/ShowAllContinents")
 def display_continents():
     continents = home_page.display_continents(df)
-    return continents.tolist()
+    return continents
 
 @app.get("/ShowAllCountries")
 def display_countries():
     countries = home_page.display_countries(df)
-    return countries.tolist()
+    return countries
 
 @app.get("/ShowContinentStats/{attribute}/{stat_type}")
 def display_continent_stats(attribute:str, stat_type:str):
@@ -31,4 +31,14 @@ def display_continent_stats(attribute:str, stat_type:str):
 @app.get("/ShowCountryStats/{attribute}/{stat_type}")
 def display_country_stats(attribute : str, stat_type : str):
     country_stats = home_page.country_stat(df, attribute,stat_type)
-    return country_stats
+    return country_stats
+
+@app.get("/ShowContinentWiseData/{attribute}")
+def display_cont_wise_stats(attribute : str):
+    conts_stats = home_page.get_continent_wise_stat(df,attribute)
+    return conts_stats
+
+@app.get("/ShowCountryData/{country}/{attribute}")
+def display_country_wise_stats(country : str, attribute : str):
+    conts_stats = home_page.get_country_wise_stat(df, country, attribute)
+    return conts_stats

backend/modules/home_page.py

@@ -7,9 +7,6 @@ from utils import logger
 
 file_path =  "./world_population.csv"
 
-# file_path =  "C:/Users/Vijay/Downloads/world_population.csv"
-# data_frame = pd.read_csv(file_path)
-
 def process_data():
     try:
         logger.log("I'm going to read the csv")
@@ -23,12 +20,14 @@ def process_data():
 def display_continents(dataframe):
     continents = dataframe['Continent'].unique()
     logger.log("Displaying the list of continents in the data")
-    return continents
+    continents_df = pd.DataFrame(continents, columns=["Continent"])
+    return continents_df
 
 def display_countries(dataframe):
     countries = dataframe['Country'].values
+    countries_df = pd.DataFrame(countries, columns=["Country"])
     logger.log("Displaying the list of countries in the data")
-    return countries
+    return countries_df
 
 def continent_stat(dataframe, attribute="Population", stat_type="highest"):
     try:
@@ -49,8 +48,8 @@ def continent_stat(dataframe, attribute="Population", stat_type="highest"):
 
         else:
             raise ValueError("Invalid stat_type. Use 'highest' or 'lowest'.")
-        
-        return {continent: value}
+        result = {attribute : {continent: value}}
+        return result
     
     except Exception as e:
         logger.log(f"Error in continent_stat: {str(e)}")
@@ -65,66 +64,19 @@ def country_stat(dataframe, attribute : str = "Population", stat_type :str = "hi
 
         country = dataframe['Country'][index]
         requested_attribute = dataframe[attribute][index]
-        result = {country:requested_attribute.item()}
+        result = {attribute:{country:requested_attribute.item()}}
         logger.log(f"Displaying the country with {stat_type} {attribute} in the data")
         return result
     except Exception as e:
         return f"Unable to fetch the data. Error {e}"
-
-    
-
-# def list_country_by_continent(dataframe,continent):
-#     try:
-#         df_countries = dataframe[dataframe['Continent'] == continent]
-#         countries= df_countries['Country'].to_list()
-#         logger.log("Separated data by continent")
-#         return countries
-#     except Exception as e:
-#         return f"{e}"
-
-# def get_stat_by_continent(df ,continent: str, data_type: str, stat: str , ):
-
-#     if continent.lower() == "NorthAmerica".lower():
-#         continent = "North America"
-#     if continent.lower() == "SouthAmerica".lower():
-#         continent = "South America"
-
-#     valid_stats = ['max', 'min', 'mean' , 'sum' , 'count']
-#     if stat not in valid_stats:
-#         return f"Invalid stat. Please use one of the following: {valid_stats}."
-    
-#     continent_population_stats = df.groupby('Continent')[data_type].agg(
-#         Maximum='max', Minimum='min', Average = 'mean',Total='sum' , Number_of_Countries = 'count')
-    
-#     continent_countries = df[df['Continent'] == continent]
-
-#     if continent not in continent_population_stats.index:
-#         return f"Continent '{continent}' not found in the data."
     
-#     if stat == 'max':
-#         population_result = continent_population_stats.loc[continent]['Maximum']
-#         country_id = continent_countries.loc[continent_countries[data_type].idxmax()]
-#         country_name = country_id['Country']
-#         population_value = country_id[data_type]
-#         return f"{continent}'s {stat} {data_type} is {int(population_result)}. Country: {country_name} , {data_type} :{population_value}"
-#     if stat == 'min':  
-#         population_result = continent_population_stats.loc[continent]['Minimum']
-#         country_id = continent_countries.loc[continent_countries[data_type].idxmin()]
-#         country_name = country_id['Country']
-#         population_value = country_id[data_type]
-#         return f"{continent}'s {stat} {data_type} is {int(population_result)}. Country: {country_name} , {data_type} :{population_value}"
-#     if stat == 'mean':
-#         population_result = continent_population_stats.loc[continent]['Average']
-#         return f"{continent}'s average {data_type} is {int(population_result)}"
-#     if stat == 'sum':
-#         population_result = continent_population_stats.loc[continent]['Total']
-#         return f"{continent}'s total {data_type} is {int(population_result)}"
-#     if stat == 'count' :
-#         population_result = continent_population_stats.loc[continent]['Number_of_Countries']
-#         return f"Total countries in {continent} is {int(population_result)}"
+def get_continent_wise_stat(data_frame, attribute):
+    if "Continent" in data_frame.columns and "Population" in data_frame.columns:
+        continent_data = data_frame.groupby("Continent")[attribute].sum().reset_index()
+        return continent_data.to_dict()
     
-# def get_continent_with_max_value(dataframe, key, value):
-#     max_id = dataframe[value].idxmax()
-#     value_num = dataframe[value][max_id]
-#     value_country = dataframe[key][max_id]
-#     return f"{value_country}'s max {value} is {value_num}"
+def get_country_wise_stat(data_frame, country, attribute):
+    country_df = data_frame[data_frame["Country"]== country]
+    data = country_df[attribute].item()
+    result = {country:{attribute:data}}
+    return result