Python Question
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Suppose we are data scientists working for an environmental organisation. Our task is to analyse data related to forest areas across different regions to help formulate conservation strategies. The dataset includes forest areas (in square kilometres) from over 1,000 regions worldwide.
Exercise 1
We are working with a dataset that contains information about different species found in national parks around the world. The dataset includes data on the number of individual animals of each species found in these parks.
Task: Calculate the population mean (population_mean) and variance (population_variance) of the species count.
In [ ]:
import pandas as pd import numpy as np # Generating random data. Fixed seed for reproducibility np.random.seed(0) forest_areas = np.random.randint(500, 10000, size=1000) # Forest areas in sq km regions = ['Region' + str(i) for i in range(1, 1001)] # Creating a dictionary data = {'Region': regions, 'Forest_Area': forest_areas} # Converting to a pandas DataFrame df = pd.DataFrame(data) # insert code here
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