import numpy as np
import pandas as pd

# Without using loops, add 1 to each of the values in the following numpy array
nums = np.array([0, 1, 4, 9, 16, 25, 36, 49, 64, 81, 100])
nums_plus_one =

# Calculate the square root of the values in nums stored in a NumPy array
nums_sqrt = ...

# Create a NumPy array of all multiples of 5 from 0 to 100.
...

# Run this cell to see COVID-19 cases by country
covid_cases = pd.read_csv('covid.csv')
covid_cases

# Create a new dataframe with only the countries with more than 300,000 total confirmed cases (replace ...)
new_df = covid_cases[covid_cases['...'] > ...]
new_df

# Display only the Country/Region and the total number confirmed cases
new_df[['...', '...']]

# Calculate the average number of confirmed cases between these countries
...

# What is the country with the least number of confirmed cases out of all the countries?
...

restuarants = ...

# How many restaurants have "$$$$$" as the price? What about "$"?
...

# Select only rows where restaurants fall under "modern cuisine". What country has the most of these restaurants? (Try not to use loops!)
...

# Sort the restaurants alphabetically from A-Z and display the top 5 restaurants. What is the name of the first restaurant?
first_restaurant = '...'
first_restaurant