import pandas as pd
new_dogs = pd.read_csv(“new_dogs.csv”)
print(new_dogs)
import pandas as pd
airline_bumping = pd.read_csv("airline_bumping.csv") # Read CSV as DataFrame
print(airline_bumping.head())
airline_totals = airline_bumping.groupby("airline")[["nb_bumped", "total_passengers"]].sum() # For each airline, select nb_bumped and total_passengers and sum
airline_totals["bumps_per_10k"] = airline_totals["nb_bumped"] / airline_totals["total_passengers"] * 10000 # Create new column
print(airline_totals)
new_dogs[“bmi”] = new_dogs[“weight_kg”] / (new_dogs[“height_cm”] / 100) ** 2
print(new_dogs)
new_dogs.to_csv(“new_dogs_with_bmi.csv”)
import pandas as pd
airline_totals_sorted = airline_totals.sort_values("bumps_per_10k", ascending = False) # Create airline_totals_sorted
print(airline_totals_sorted)
airline_totals_sorted.to_csv("airline_totals_sorted.csv") # Save as airline_totals_sorted.csv