258 lines
7.1 KiB
Text
258 lines
7.1 KiB
Text
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/07_sequences/02_exercises.ipynb)."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Chapter 7: Sequential Data (Coding Exercises)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"The exercises below assume that you have read the [second part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/01_content.ipynb) of Chapter 7.\n",
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"\n",
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"The `...`'s in the code cells indicate where you need to fill in code snippets. The number of `...`'s within a code cell give you a rough idea of how many lines of code are needed to solve the task. You should not need to create any additional code cells for your final solution. However, you may want to use temporary code cells to try out some ideas."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Working with Lists"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Q1**: Write a function `nested_sum()` that takes a `list` object as its argument, which contains other `list` objects with numbers, and adds up the numbers! Use `nested_numbers` below to test your function!\n",
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"\n",
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"Hint: You need at least one `for`-loop."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"nested_numbers = [[1, 2, 3], [4], [5], [6, 7], [8], [9]]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"def nested_sum(list_of_lists):\n",
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" \"\"\"Add up numbers in nested lists.\n",
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" \n",
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" Args:\n",
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" list_of_lists (list): A list containing the lists with the numbers\n",
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" \n",
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" Returns:\n",
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" sum (int or float)\n",
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" \"\"\"\n",
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" ...\n",
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" ...\n",
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" ...\n",
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"\n",
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" return ..."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"nested_sum(nested_numbers)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Q2**: Generalize `nested_sum()` into a function `mixed_sum()` that can process a \"mixed\" `list` object, which contains numbers and other `list` objects with numbers! Use `mixed_numbers` below for testing!\n",
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"\n",
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"Hints: Use the built-in [isinstance() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#isinstance) function to check how an element is to be processed."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"mixed_numbers = [[1, 2, 3], 4, 5, [6, 7], 8, [9]]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import collections.abc as abc"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"def mixed_sum(list_of_lists_or_numbers):\n",
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" \"\"\"Add up numbers in nested lists.\n",
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" \n",
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" Args:\n",
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" list_of_lists_or_numbers (list): A list containing both numbers and\n",
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" lists with numbers\n",
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" \n",
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" Returns:\n",
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" sum (int or float)\n",
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" \"\"\"\n",
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" ...\n",
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" ...\n",
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" ...\n",
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" ...\n",
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" ...\n",
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" ...\n",
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"\n",
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" return ..."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"mixed_sum(mixed_numbers)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Q3.1**: Write a function `cum_sum()` that takes a `list` object with numbers as its argument and returns a *new* `list` object with the **cumulative sums** of these numbers! So, `sum_up` below, `[1, 2, 3, 4, 5]`, should return `[1, 3, 6, 10, 15]`.\n",
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"\n",
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"Hint: The idea behind is similar to the [cumulative distribution function <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Cumulative_distribution_function) from statistics."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"sum_up = [1, 2, 3, 4, 5]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"def cum_sum(numbers):\n",
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" \"\"\"Create the cumulative sums for some numbers.\n",
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"\n",
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" Args:\n",
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" numbers (list): A list with numbers for that the cumulative sums\n",
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" are calculated\n",
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" \n",
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" Returns:\n",
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" cum_sums (list): A list with all the cumulative sums\n",
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" \"\"\"\n",
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" ...\n",
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" ...\n",
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"\n",
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" ...\n",
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" ...\n",
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" ...\n",
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"\n",
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" return ..."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"cum_sum(sum_up)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Q3.2**: We should always make sure that our functions also work in corner cases. What happens if your implementation of `cum_sum()` is called with an empty list `[]`? Make sure it handles that case *without* crashing! What would be a good return value in this corner case?\n",
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"\n",
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"Hint: It is possible to write this without any extra input validation."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"cum_sum([])"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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" < your answer >"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.6"
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},
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"toc": {
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"base_numbering": 1,
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"nav_menu": {},
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"number_sections": false,
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"sideBar": true,
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"skip_h1_title": true,
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"title_cell": "Table of Contents",
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"title_sidebar": "Contents",
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"toc_cell": false,
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"toc_position": {},
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"toc_section_display": false,
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"toc_window_display": false
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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