exercises/ex05_reading_error_messages.ipynb

{"cells": [{"cell_type": "markdown", "metadata": {"id": "Y2SZiOJLknDc"}, "source": ["# Exercise 05: Fixing Errors\n", "Try to understand the examples below and fix all errors that occure with the knowledge you gained in the last few days."]}, {"cell_type": "code", "execution_count": 0, "metadata": {}, "outputs": [], "source": ["some_random_numbers = [98, 98, 22, 49, 19, 38, 22, 28, 23, 70, 21, 97, 13, 56, 98, 2, 93, 41, 72, 56}\n", "    \n", "result = 0   \n", "for number in some_random_numbers\n", "    result += number\n", "    \n", "print(\"The sum of the random numbers is {result}')\n", "\n"]}, {"cell_type": "code", "execution_count": 0, "metadata": {}, "outputs": [], "source": ["students_and_points = {'Rolf': 24, 'Bob': 18, 'Anne' 42, 'Charlie': 37, 'Jen': 12, 'Jose': 24}\n", "for student, points in students_and_points:\n", "    print(student, student)"]}, {"cell_type": "code", "execution_count": 0, "metadata": {}, "outputs": [], "source": ["\n", "def is_palindrome(string)\n", "    string = \"\".join(string.lower().split()\n", "    return string = string[::-1]\n", "\n", "is_palindrome(\"Anna\")"]}, {"cell_type": "code", "execution_count": 0, "metadata": {}, "outputs": [], "source": ["employment_info = {\n", "\"Jhon\": {\n", "    \"employee_id\" 109231, \n", "    \"employment\": \"Carpenter\", \n", "    \"Yearly Net Income\": 49520},\n", "\"Anna\": {\n", "    \"employee_id\": 201201 \n", "    \"employment\": \"Graphic Designer\", \n", "    \"Yearly Net Income\": 5700}\n", "\"Bob': {\n", "    \"employee_id\": 302211, \n", "    \"employment\": \"Python Programmer\", \n", "    \"Yearly Net Income\": 2147483647,\n", "\n", "with open(\"employment_info.csv\"):\n", "    employment_info_file.write(\"Name,Employee-ID,Employment,Yearly-Net-Income\")\n", "    for name, info in employment_info:\n", "        some_file.write(f\"{name},{info[\"employee_id\"]},{info[\"employment\"]},{info[\"Yearly Net Income\"]}\")\n", "        "]}, {"cell_type": "code", "execution_count": 0, "metadata": {}, "outputs": [], "source": ["# Fix the example before first since you need the datafile from it ;)\n", "with open(\"C:/a/very/good/and/definitely/available/absolute/path/to/employment_info.csv\") as employment_info:\n", "    total_net_income = 0\n", "    for line in employment_info.readlines()[1:]: # skip header\n", "        total_net_income = line.strip().split(\",')[-1]\n", "    print(\"All employees together have a yearly net income of: {total_net_income}\")"]}], "metadata": {"interpreter": {"hash": "31f2aee4e71d21fbe5cf8b01ff0e069b9275f58929596ceb00d14d90e3e16cd6"}, "kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"}, "language_info": {"codemirror_mode": {"name": "ipython", "version": 3}, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.7"}}, "nbformat": 4, "nbformat_minor": 4}