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import pandas as pd
import os
import sys
src_directory = os.path.abspath(os.path.join(os.path.dirname(__file__), "../..", "backend"))
sys.path.append(src_directory)
from utils import logger
file_path = "./world_population.csv"
def process_data():
try:
logger.log("I'm going to read the csv")
data_frame = pd.read_csv(file_path)
logger.log("I'm reading the csv")
return data_frame
except Exception as e :
logger.log("I couldn't read the file")
return f"Unable to read the file {e}"
def display_continents(dataframe):
continents = dataframe['Continent'].unique()
logger.log("Displaying the list of continents in the data")
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_df
def continent_stat(dataframe, attribute="Population", stat_type="highest"):
try:
if 'Continent' not in dataframe.columns or attribute not in dataframe.columns:
return ValueError(f"Dataframe must contain 'Continent' and '{attribute}' columns.")
continent_stats = dataframe.groupby('Continent')[attribute].agg(total_attribute='sum')
if stat_type == "highest":
continent = continent_stats.idxmax().item()
value = continent_stats.max().item()
logger.log(f"Displaying the continent with the highest {attribute}: {continent} with {attribute} {value}")
elif stat_type == "lowest":
continent = continent_stats.idxmin().item()
value = continent_stats.min().item()
logger.log(f"Displaying the continent with the lowest {attribute}: {continent} with {attribute} {value}")
else:
raise ValueError("Invalid stat_type. Use 'highest' or 'lowest'.")
result = {attribute : {continent: value}}
return result
except Exception as e:
logger.log(f"Error in continent_stat: {str(e)}")
return {"error": str(e)}
def country_stat(dataframe, attribute : str = "Population", stat_type :str = "highest"):
try :
if stat_type.lower() == "highest":
index= dataframe[attribute].idxmax()
elif stat_type.lower() == "lowest":
index= dataframe[attribute].idxmin()
country = dataframe['Country'][index]
requested_attribute = dataframe[attribute][index]
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 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_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 |