A Assignment

Please complete Exercises write your solutions in a single Python script named unit08_assigment.py.

Save all scripts in the same unit08_assigment folder, compress the folder into a .zip file, and upload it to ILIAS.

For more information, please visit the following link:
https://geomoer.github.io/moer-base-python/unit00/unit00-04_submission_guidelines.html

Make sure your code is clearly structured and includes comments where helpful.

Dataset World Bank – Total Population by Country and Year

import pandas as pd
import matplotlib.pyplot as plt

url = "https://raw.githubusercontent.com/datasets/population/master/data/population.csv"
df = pd.read_csv(url)

Analyze and compare population development of selected countries and visualize the results.

Task 1 – Data Exploration

  1. Print the column names.
  2. Display the first 5 rows of the dataset.
  3. Determine:
    • the minimum year in the dataset
    • the maximum year in the dataset

Task 2 - Line Plot: Population Over Time

  1. Create one line plot showing population development over time for the following five African countries:
    • Nigeria
    • Egypt
    • Ethiopia
    • South Africa
    • Kenya
  2. Each country must have its own line in the plot.
  3. Explicitly define the x-axis so that it starts at the minimum year and ends at the maximum year in the dataset.
    You can use the function plt.xlim() for this.
  4. Add:
    • a descriptive title
    • an x-axis label
    • a y-axis label
    • a legend

Task 3 - Population Comparison for One Year

  1. Select the year 2020.
  2. Filter the data so that it contains only the following five European countries:
    • Germany
    • France
    • United Kingdom
    • Italy
    • Spain

Hint: There is a pandas function that allows you to check whether values are contained in a list (2020).

  1. Create:
    • a bar chart comparing the population sizes of these countries in 2020
    • a pie chart with percentages showing each country’s share of the total population

Hint: Make sure that both charts are based on the same filtered dataset (year 2020 and the selected countries).

Titanic Data Visualization – Python Homework

Dataset (used for all tasks)

import pandas as pd
import matplotlib.pyplot as plt

url = "https://raw.githubusercontent.com/datasciencedojo/datasets/master/titanic.csv"
df = pd.read_csv(url)

Task 4 – Survivors vs. Non-Survivors

  1. Access the column Survived.
  2. Count survivors and non-survivors using value_counts().
  3. Create:
    • a bar chart
    • a pie chart with percentages
  4. Add titles and axis labels.

Task 5 – Gender Distribution

  1. Use the column Sex.
  2. Count male and female passengers.
  3. Create a pie chart with percentages.

Task 6 – Passenger Class Distribution

  1. Use the column Pclass.
  2. Count passengers per class.
  3. Create a bar chart or pie chart.

Bonus Task – Multiple Plots in One Figure

Create a figure with multiple subplots (e.g. 2x2) including:

  • Survivors
  • Gender distribution
  • Passenger class distribution

Each subplot must have its own title and one global figure title.

Updated: