From 12cf313f286f0a008d25d14d6d7de9a88d867126 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Sa=C3=BAl=20Oviedo?= Date: Tue, 24 Aug 2021 18:19:46 -0400 Subject: [PATCH] lab 1 completado --- .../challenge-1-checkpoint.ipynb | 378 +++++++++++++ .../challenge-2-checkpoint.ipynb | 481 ++++++++++++++++ .../challenge-3-checkpoint.ipynb | 521 ++++++++++++++++++ your-code/challenge-1.ipynb | 211 ++++++- your-code/challenge-2.ipynb | 270 +++++++-- your-code/challenge-3.ipynb | 359 +++++++++++- 6 files changed, 2120 insertions(+), 100 deletions(-) create mode 100644 your-code/.ipynb_checkpoints/challenge-1-checkpoint.ipynb create mode 100644 your-code/.ipynb_checkpoints/challenge-2-checkpoint.ipynb create mode 100644 your-code/.ipynb_checkpoints/challenge-3-checkpoint.ipynb diff --git a/your-code/.ipynb_checkpoints/challenge-1-checkpoint.ipynb b/your-code/.ipynb_checkpoints/challenge-1-checkpoint.ipynb new file mode 100644 index 0000000..3849db7 --- /dev/null +++ b/your-code/.ipynb_checkpoints/challenge-1-checkpoint.ipynb @@ -0,0 +1,378 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Challenge 1: Tuples\n", + "\n", + "#### Do you know you can create tuples with only one element?\n", + "\n", + "**In the cell below, define a variable `tup` with a single element `\"I\"`.**\n", + "\n", + "*Hint: you need to add a comma (`,`) after the single element.*" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "# Your code here\n", + "tup = \"I\"," + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Print the type of `tup`. \n", + "\n", + "Make sure its type is correct (i.e. *tuple* instead of *str*)." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "# Your code here\n", + "print(type(tup))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Now try to append the following elements to `tup`. \n", + "\n", + "Are you able to do it? Explain.\n", + "\n", + "```\n", + "\"r\", \"o\", \"n\", \"h\", \"a\", \"c\", \"k',\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "ename": "AttributeError", + "evalue": "'tuple' object has no attribute 'append'", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[1;31m# Your code here\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mtup\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"r\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"o\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"n\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"h\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"a\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"c\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"k\"\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 3\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 4\u001b[0m \u001b[1;31m# Your explanation here\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;31mAttributeError\u001b[0m: 'tuple' object has no attribute 'append'" + ] + } + ], + "source": [ + "# Your code here\n", + "tup.append([\"r\", \"o\", \"n\", \"h\", \"a\", \"c\", \"k\"])\n", + "\n", + "# Your explanation here\n", + "# Tuples son tipos de variables inmutables" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### How about re-assign a new value to an existing tuple?\n", + "\n", + "Re-assign the following elements to `tup`. Are you able to do it? Explain.\n", + "\n", + "```\n", + "\"I\", \"r\", \"o\", \"n\", \"h\", \"a\", \"c\", \"k\"\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('I', 'r', 'o', 'n', 'h', 'a', 'c', 'k')\n" + ] + } + ], + "source": [ + "# Your code here\n", + "tup = (\"I\", \"r\", \"o\", \"n\", \"h\", \"a\", \"c\", \"k\")\n", + "print(tup)\n", + "\n", + "# Your explanation here\n", + "# ya que los tuples son inmitables, lo mejor forma para hacer una modificacion es l reasignacion" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Split `tup` into `tup1` and `tup2` with 4 elements in each. \n", + "\n", + "`tup1` should be `(\"I\", \"r\", \"o\", \"n\")` and `tup2` should be `(\"h\", \"a\", \"c\", \"k\")`.\n", + "\n", + "*Hint: use positive index numbers for `tup1` assignment and use negative index numbers for `tup2` assignment. Positive index numbers count from the beginning whereas negative index numbers count from the end of the sequence.*\n", + "\n", + "Also print `tup1` and `tup2`." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('I', 'r', 'o', 'n')\n", + "('h', 'a', 'c', 'k')\n" + ] + } + ], + "source": [ + "# Your code here\n", + "tup1 = tup[:4]\n", + "tup2 = tup[-4:]\n", + "\n", + "print(tup1)\n", + "print(tup2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Add `tup1` and `tup2` into `tup3` using the `+` operator.\n", + "\n", + "Then print `tup3` and check if `tup3` equals to `tup`." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('I', 'r', 'o', 'n', 'h', 'a', 'c', 'k')\n", + "True\n" + ] + } + ], + "source": [ + "# Your code here\n", + "tup3 = tup1 + tup2\n", + "\n", + "# chechk if tup3 == tup\n", + "print(tup3 == tup)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Count the number of elements in `tup1` and `tup2`. Then add the two counts together and check if the sum is the same as the number of elements in `tup3`" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "True\n" + ] + } + ], + "source": [ + "# Your code here\n", + "tup1_len = len(tup1)\n", + "tup2_len = len(tup2)\n", + "\n", + "print( tup1_len + tup2_len == len(tup))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### What is the index number of `\"h\"` in `tup3`?" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "h\n" + ] + } + ], + "source": [ + "# Your code here\n", + "# Index 4\n", + "\n", + "print(tup3[4])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Now, use a FOR loop to check whether each letter in the following list is present in `tup3`:\n", + "\n", + "```\n", + "letters = [\"a\", \"b\", \"c\", \"d\", \"e\"]\n", + "```\n", + "\n", + "For each letter you check, print `True` if it is present in `tup3` otherwise print `False`.\n", + "\n", + "*Hint: you only need to loop `letters`. You don't need to loop `tup3` because there is a Python operator `in` you can use. See [reference](https://stackoverflow.com/questions/17920147/how-to-check-if-a-tuple-contains-an-element-in-python).*" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "a --> True\n", + "b --> False\n", + "c --> True\n", + "d --> False\n", + "e --> False\n" + ] + } + ], + "source": [ + "# Your code here\n", + "letters = [\"a\", \"b\", \"c\", \"d\", \"e\"]\n", + "\n", + "for letter in letters:\n", + " print(letter, '-->', letter in tup3)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### How many times does each letter in `letters` appear in `tup3`?\n", + "\n", + "Print out the number of occurrence of each letter." + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "------------\n", + "a --> 1\n", + "b --> 0\n", + "c --> 1\n", + "d --> 0\n", + "e --> 0\n", + "------------\n", + "a --> 1\n", + "b --> 0\n", + "c --> 1\n", + "d --> 0\n", + "e --> 0\n", + "------------\n", + "a --> 1\n", + "b --> 0\n", + "c --> 1\n", + "d --> 0\n", + "e --> 0\n" + ] + } + ], + "source": [ + "# Your code here\n", + "\n", + "print('------------')\n", + "\n", + "for letter in letters:\n", + " print(letter, '-->', sum([letter == l for l in tup]))\n", + " \n", + "print('------------')\n", + "\n", + "for letter in letters:\n", + " c = 0\n", + " for l in tup:\n", + " if letter == l:\n", + " c += 1\n", + " print(letter, '-->', c)\n", + " \n", + "print('------------')\n", + "for letter in letters:\n", + " print(letter, '-->', tup.count(letter))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "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": "3.8.8" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/your-code/.ipynb_checkpoints/challenge-2-checkpoint.ipynb b/your-code/.ipynb_checkpoints/challenge-2-checkpoint.ipynb new file mode 100644 index 0000000..4d7b3ba --- /dev/null +++ b/your-code/.ipynb_checkpoints/challenge-2-checkpoint.ipynb @@ -0,0 +1,481 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Challenge 2: Sets\n", + "\n", + "There are a lot to learn about Python Sets and the information presented in the lesson is limited due to its length. To learn Python Sets in depth you are strongly encouraged to review the W3Schools tutorial on [Python Sets Examples and Methods](https://www.w3schools.com/python/python_sets.asp) before you work on this lab. Some difficult questions in this lab have their solutions in the W3Schools tutorial.\n", + "\n", + "#### First, import the Python `random` libary" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import random" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### In the cell below, create a list named `sample_list_1` with 80 random values. \n", + "\n", + "Requirements:\n", + "\n", + "* Each value is an integer falling between 0 and 100.\n", + "* Each value in the list is unique.\n", + "\n", + "Print `sample_list_1` to review its values\n", + "\n", + "*Hint: use `random.sample` ([reference](https://docs.python.org/3/library/random.html#random.sample)).*" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[40, 59, 19, 20, 18, 97, 86, 52, 46, 44, 90, 24, 35, 77, 68, 0, 39, 76, 99, 88, 23, 4, 16, 54, 96, 72, 22, 37, 82, 17, 66, 61, 21, 55, 58, 70, 50, 3, 13, 42, 84, 25, 89, 15, 69, 51, 64, 67, 2, 87, 8, 12, 83, 63, 45, 43, 81, 30, 47, 5, 7, 71, 74, 78, 57, 48, 65, 56, 14, 31, 73, 94, 10, 27, 26, 32, 80, 11, 9, 79]\n" + ] + } + ], + "source": [ + "# Your code here\n", + "sample_list_1 = random.sample(range(101), k=80)\n", + "\n", + "print(sample_list_1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Convert `sample_list_1` to a set called `set1`. Print the length of the set. Is its length still 80?" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "80\n" + ] + } + ], + "source": [ + "set_1 = set(sample_list_1)\n", + "print(len(set_1))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Create another list named `sample_list_2` with 80 random values.\n", + "\n", + "Requirements:\n", + "\n", + "* Each value is an integer falling between 0 and 100.\n", + "* The values in the list don't have to be unique.\n", + "\n", + "*Hint: Use a FOR loop.*" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[29, 78, 43, 70, 11, 19, 5, 44, 85, 20, 88, 28, 66, 42, 96, 60, 93, 45, 65, 53, 73, 89, 1, 79, 58, 77, 86, 12, 41, 74, 17, 50, 51, 80, 37, 83, 62, 100, 7, 8, 16, 27, 69, 82, 87, 95, 49, 72, 54, 56, 13, 67, 3, 10, 64, 24, 31, 71, 36, 81, 40, 98, 0, 59, 23, 35, 34, 6, 21, 33, 18, 47, 9, 32, 84, 75, 68, 61, 2, 4]\n" + ] + } + ], + "source": [ + "# Your code here\n", + "sample_list_2 = random.sample(range(101), k=80)\n", + "print(sample_list_2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Convert `sample_list_2` to a set called `set2`. Print the length of the set. Is its length still 80?" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "80\n" + ] + } + ], + "source": [ + "# Your code here\n", + "set_2 = set(sample_list_2)\n", + "print(len(set_2))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Identify the elements present in `set1` but not in `set2`. Assign the elements to a new set named `set3`." + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{97, 99, 90, 39, 76, 14, 15, 46, 48, 52, 94, 22, 55, 25, 26, 63, 30, 57}\n" + ] + } + ], + "source": [ + "# Your code here\n", + "set_3 = set_1 - set_2\n", + "print(set_3)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Identify the elements present in `set2` but not in `set1`. Assign the elements to a new set named `set4`." + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{1, 33, 34, 36, 98, 6, 100, 41, 75, 60, 49, 93, 53, 85, 28, 29, 62, 95}\n" + ] + } + ], + "source": [ + "# Your code here\n", + "set_4 = set_2 - set_1\n", + "print(set_4)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Now Identify the elements shared between `set1` and `set2`. Assign the elements to a new set named `set5`." + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{0, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 13, 16, 17, 18, 19, 20, 21, 23, 24, 27, 31, 32, 35, 37, 40, 42, 43, 44, 45, 47, 50, 51, 54, 56, 58, 59, 61, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 77, 78, 79, 80, 81, 82, 83, 84, 86, 87, 88, 89, 96}\n" + ] + } + ], + "source": [ + "# Your code here\n", + "set_5 = set_1.intersection(set_2)\n", + "print(set_5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### What is the relationship among the following values:\n", + "\n", + "* len(set1)\n", + "* len(set2)\n", + "* len(set3)\n", + "* len(set4)\n", + "* len(set5)\n", + "\n", + "Use a math formular to represent that relationship. Test your formular with Python code." + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 44, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Your code here\n", + "len(set_1) + len(set_2) == len(set_3) + len(set_4) + 2*len(set_5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Create an empty set called `set6`." + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [], + "source": [ + "# Your code here\n", + "\n", + "set_6 = set()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Add `set3` and `set5` to `set6` using the Python Set `update` method." + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{0, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 30, 31, 32, 35, 37, 39, 40, 42, 43, 44, 45, 46, 47, 48, 50, 51, 52, 54, 55, 56, 57, 58, 59, 61, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 76, 77, 78, 79, 80, 81, 82, 83, 84, 86, 87, 88, 89, 90, 94, 96, 97, 99}\n" + ] + } + ], + "source": [ + "# Your code here\n", + "set_6.update(set_3, set_5)\n", + "print(set_6)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Check if `set1` and `set6` are equal." + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 52, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Your code here\n", + "set_1 == set_6" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Check if `set1` contains `set2` using the Python Set `issubset` method. Then check if `set1` contains `set3`.*" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "False\n", + "True\n" + ] + } + ], + "source": [ + "# Your code here\n", + "print(set_2.issubset(set_1))\n", + "\n", + "print(set_3.issubset(set_1))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Using the Python Set `union` method, aggregate `set3`, `set4`, and `set5`. Then aggregate `set1` and `set2`. \n", + "\n", + "#### Check if the aggregated values are equal." + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Union de set 3, set 4 y set 5\n", + "{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 93, 94, 95, 96, 97, 98, 99, 100} \n", + "\n", + "Union de set 1 y set 2\n", + "{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 93, 94, 95, 96, 97, 98, 99, 100}\n" + ] + } + ], + "source": [ + "# Your code here\n", + "print(\"Union de set 3, set 4 y set 5\")\n", + "print(set_3.union(set_4, set_5), '\\n')\n", + "\n", + "\n", + "print(\"Union de set 1 y set 2\")\n", + "print(set_3.union(set_4, set_5))\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Using the `pop` method, remove the first element from `set1`." + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0" + ] + }, + "execution_count": 67, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Your code here\n", + "set_1.pop()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Remove every element in the following list from `set1` if they are present in the set. Print the remaining elements.\n", + "\n", + "```\n", + "list_to_remove = [1, 9, 11, 19, 21, 29, 31, 39, 41, 49, 51, 59, 61, 69, 71, 79, 81, 89, 91, 99]\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{2, 3, 4, 5, 7, 8, 10, 12, 13, 14, 15, 16, 17, 18, 20, 22, 23, 24, 25, 26, 27, 30, 32, 35, 37, 40, 42, 43, 44, 45, 46, 47, 48, 50, 52, 54, 55, 56, 57, 58, 63, 64, 65, 66, 67, 68, 70, 72, 73, 74, 76, 77, 78, 80, 82, 83, 84, 86, 87, 88, 90, 94, 96, 97}\n" + ] + } + ], + "source": [ + "# Your code here\n", + "list_to_remove = [1, 9, 11, 19, 21, 29, 31, 39, 41, 49, 51, 59, 61, 69, 71, 79, 81, 89, 91, 99]\n", + "remaining = set_1 - set(list_to_remove)\n", + "print(remaining)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "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": "3.8.8" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/your-code/.ipynb_checkpoints/challenge-3-checkpoint.ipynb b/your-code/.ipynb_checkpoints/challenge-3-checkpoint.ipynb new file mode 100644 index 0000000..733435b --- /dev/null +++ b/your-code/.ipynb_checkpoints/challenge-3-checkpoint.ipynb @@ -0,0 +1,521 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Challenge 3: Dictionaries\n", + "\n", + "In this challenge you will practice how to manipulate Python dictionaries. Before starting on this challenge, you are encouraged to review W3School's [Python Dictionary Examples and Methods](https://www.w3schools.com/python/python_dictionaries.asp).\n", + "\n", + "First thing you will practice is how to sort the keys in a dictionary. Unlike the list object, Python dictionary does not have a built-in *sort* method. You'll need to use FOR loops to to sort dictionaries either by key or by value.\n", + "\n", + "The dictionary below is a summary of the word frequency of Ed Sheeran's song *Shape of You*. Each key is a word in the lyrics and the value is the number of times that word appears in the lyrics." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "word_freq = {'love': 25, 'conversation': 1, 'every': 6, \"we're\": 1, 'plate': 1, 'sour': 1, 'jukebox': 1, 'now': 11, 'taxi': 1, 'fast': 1, 'bag': 1, 'man': 1, 'push': 3, 'baby': 14, 'going': 1, 'you': 16, \"don't\": 2, 'one': 1, 'mind': 2, 'backseat': 1, 'friends': 1, 'then': 3, 'know': 2, 'take': 1, 'play': 1, 'okay': 1, 'so': 2, 'begin': 1, 'start': 2, 'over': 1, 'body': 17, 'boy': 2, 'just': 1, 'we': 7, 'are': 1, 'girl': 2, 'tell': 1, 'singing': 2, 'drinking': 1, 'put': 3, 'our': 1, 'where': 1, \"i'll\": 1, 'all': 1, \"isn't\": 1, 'make': 1, 'lover': 1, 'get': 1, 'radio': 1, 'give': 1, \"i'm\": 23, 'like': 10, 'can': 1, 'doing': 2, 'with': 22, 'club': 1, 'come': 37, 'it': 1, 'somebody': 2, 'handmade': 2, 'out': 1, 'new': 6, 'room': 3, 'chance': 1, 'follow': 6, 'in': 27, 'may': 2, 'brand': 6, 'that': 2, 'magnet': 3, 'up': 3, 'first': 1, 'and': 23, 'pull': 3, 'of': 6, 'table': 1, 'much': 2, 'last': 3, 'i': 6, 'thrifty': 1, 'grab': 2, 'was': 2, 'driver': 1, 'slow': 1, 'dance': 1, 'the': 18, 'say': 2, 'trust': 1, 'family': 1, 'week': 1, 'date': 1, 'me': 10, 'do': 3, 'waist': 2, 'smell': 3, 'day': 6, 'although': 3, 'your': 21, 'leave': 1, 'want': 2, \"let's\": 2, 'lead': 6, 'at': 1, 'hand': 1, 'how': 1, 'talk': 4, 'not': 2, 'eat': 1, 'falling': 3, 'about': 1, 'story': 1, 'sweet': 1, 'best': 1, 'crazy': 2, 'let': 1, 'too': 5, 'van': 1, 'shots': 1, 'go': 2, 'to': 2, 'a': 8, 'my': 33, 'is': 5, 'place': 1, 'find': 1, 'shape': 6, 'on': 40, 'kiss': 1, 'were': 3, 'night': 3, 'heart': 3, 'for': 3, 'discovering': 6, 'something': 6, 'be': 16, 'bedsheets': 3, 'fill': 2, 'hours': 2, 'stop': 1, 'bar': 1}" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Sort the keys of `word_freq` ascendingly.\n", + "\n", + "Please create a new dictionary called `word_freq2` based on `word_freq` with the keys sorted ascedingly.\n", + "\n", + "There are several ways to achieve that goal but many of the ways are beyond what we have covered so far in the course. There is one way that we'll describe employing what you have learned. Please feel free to use this way or any other way you want.\n", + "\n", + "1. First extract the keys of `word_freq` and convert it to a list called `keys`.\n", + "\n", + "1. Sort the `keys` list.\n", + "\n", + "1. Create an empty dictionary `word_freq2`.\n", + "\n", + "1. Use a FOR loop to iterate each value in `keys`. For each key iterated, find the corresponding value in `word_freq` and insert the key-value pair to `word_freq2`.\n", + "\n", + "Print out `word_freq2` to examine its keys and values. Your output should be:\n", + "\n", + "```python\n", + "{'a': 8, 'about': 1, 'all': 1, 'although': 3, 'and': 23, 'are': 1, 'at': 1, 'baby': 14, 'backseat': 1, 'bag': 1, 'bar': 1, 'be': 16, 'bedsheets': 3, 'begin': 1, 'best': 1, 'body': 17, 'boy': 2, 'brand': 6, 'can': 1, 'chance': 1, 'club': 1, 'come': 37, 'conversation': 1, 'crazy': 2, 'dance': 1, 'date': 1, 'day': 6, 'discovering': 6, 'do': 3, 'doing': 2, \"don't\": 2, 'drinking': 1, 'driver': 1, 'eat': 1, 'every': 6, 'falling': 3, 'family': 1, 'fast': 1, 'fill': 2, 'find': 1, 'first': 1, 'follow': 6, 'for': 3, 'friends': 1, 'get': 1, 'girl': 2, 'give': 1, 'go': 2, 'going': 1, 'grab': 2, 'hand': 1, 'handmade': 2, 'heart': 3, 'hours': 2, 'how': 1, 'i': 6, \"i'll\": 1, \"i'm\": 23, 'in': 27, 'is': 5, \"isn't\": 1, 'it': 1, 'jukebox': 1, 'just': 1, 'kiss': 1, 'know': 2, 'last': 3, 'lead': 6, 'leave': 1, 'let': 1, \"let's\": 2, 'like': 10, 'love': 25, 'lover': 1, 'magnet': 3, 'make': 1, 'man': 1, 'may': 2, 'me': 10, 'mind': 2, 'much': 2, 'my': 33, 'new': 6, 'night': 3, 'not': 2, 'now': 11, 'of': 6, 'okay': 1, 'on': 40, 'one': 1, 'our': 1, 'out': 1, 'over': 1, 'place': 1, 'plate': 1, 'play': 1, 'pull': 3, 'push': 3, 'put': 3, 'radio': 1, 'room': 3, 'say': 2, 'shape': 6, 'shots': 1, 'singing': 2, 'slow': 1, 'smell': 3, 'so': 2, 'somebody': 2, 'something': 6, 'sour': 1, 'start': 2, 'stop': 1, 'story': 1, 'sweet': 1, 'table': 1, 'take': 1, 'talk': 4, 'taxi': 1, 'tell': 1, 'that': 2, 'the': 18, 'then': 3, 'thrifty': 1, 'to': 2, 'too': 5, 'trust': 1, 'up': 3, 'van': 1, 'waist': 2, 'want': 2, 'was': 2, 'we': 7, \"we're\": 1, 'week': 1, 'were': 3, 'where': 1, 'with': 22, 'you': 16, 'your': 21}\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'a': 8, 'about': 1, 'all': 1, 'although': 3, 'and': 23, 'are': 1, 'at': 1, 'baby': 14, 'backseat': 1, 'bag': 1, 'bar': 1, 'be': 16, 'bedsheets': 3, 'begin': 1, 'best': 1, 'body': 17, 'boy': 2, 'brand': 6, 'can': 1, 'chance': 1, 'club': 1, 'come': 37, 'conversation': 1, 'crazy': 2, 'dance': 1, 'date': 1, 'day': 6, 'discovering': 6, 'do': 3, 'doing': 2, \"don't\": 2, 'drinking': 1, 'driver': 1, 'eat': 1, 'every': 6, 'falling': 3, 'family': 1, 'fast': 1, 'fill': 2, 'find': 1, 'first': 1, 'follow': 6, 'for': 3, 'friends': 1, 'get': 1, 'girl': 2, 'give': 1, 'go': 2, 'going': 1, 'grab': 2, 'hand': 1, 'handmade': 2, 'heart': 3, 'hours': 2, 'how': 1, 'i': 6, \"i'll\": 1, \"i'm\": 23, 'in': 27, 'is': 5, \"isn't\": 1, 'it': 1, 'jukebox': 1, 'just': 1, 'kiss': 1, 'know': 2, 'last': 3, 'lead': 6, 'leave': 1, 'let': 1, \"let's\": 2, 'like': 10, 'love': 25, 'lover': 1, 'magnet': 3, 'make': 1, 'man': 1, 'may': 2, 'me': 10, 'mind': 2, 'much': 2, 'my': 33, 'new': 6, 'night': 3, 'not': 2, 'now': 11, 'of': 6, 'okay': 1, 'on': 40, 'one': 1, 'our': 1, 'out': 1, 'over': 1, 'place': 1, 'plate': 1, 'play': 1, 'pull': 3, 'push': 3, 'put': 3, 'radio': 1, 'room': 3, 'say': 2, 'shape': 6, 'shots': 1, 'singing': 2, 'slow': 1, 'smell': 3, 'so': 2, 'somebody': 2, 'something': 6, 'sour': 1, 'start': 2, 'stop': 1, 'story': 1, 'sweet': 1, 'table': 1, 'take': 1, 'talk': 4, 'taxi': 1, 'tell': 1, 'that': 2, 'the': 18, 'then': 3, 'thrifty': 1, 'to': 2, 'too': 5, 'trust': 1, 'up': 3, 'van': 1, 'waist': 2, 'want': 2, 'was': 2, 'we': 7, \"we're\": 1, 'week': 1, 'were': 3, 'where': 1, 'with': 22, 'you': 16, 'your': 21}\n" + ] + } + ], + "source": [ + "# Your code here\n", + "\n", + "word_freq2 = {}\n", + "\n", + "for w in sorted(word_freq.keys()):\n", + " word_freq2[w] = word_freq[w]\n", + "\n", + "print(word_freq2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Sort the values of `word_freq` ascendingly.\n", + "\n", + "Sorting the values of a dictionary is more tricky than sorting the keys because a dictionary's values are not unique. Therefore you cannot use the same way you sorted dict keys to sort dict values.\n", + "\n", + "The way to sort a dict by value is to utilize the `sorted` and `operator.itemgetter` functions. The following code snippet is provided to you to try. It will give you a list of tuples in which each tuple contains the key and value of a dict item. And the list is sorted based on the dict value ([reference](http://thomas-cokelaer.info/blog/2017/12/how-to-sort-a-dictionary-by-values-in-python/)\n", + ").\n", + "\n", + "```python\n", + "import operator\n", + "sorted_tups = sorted(word_freq.items(), key=operator.itemgetter(1))\n", + "print(sorted_tups)\n", + "```\n", + "\n", + "Therefore, the steps to sort `word_freq` by value are:\n", + "\n", + "* Using `sorted` and `operator.itemgetter`, obtain a list of tuples of the dict key-value pairs which is sorted on the value.\n", + "\n", + "* Create an empty dictionary named `word_freq2`.\n", + "\n", + "* Iterate the list of tuples. Insert each key-value pair into `word_freq2` as an object.\n", + "\n", + "Print `word_freq2` to confirm your dictionary has its values sorted. Your output should be:\n", + "\n", + "```python\n", + "{'conversation': 1, \"we're\": 1, 'plate': 1, 'sour': 1, 'jukebox': 1, 'taxi': 1, 'fast': 1, 'bag': 1, 'man': 1, 'going': 1, 'one': 1, 'backseat': 1, 'friends': 1, 'take': 1, 'play': 1, 'okay': 1, 'begin': 1, 'over': 1, 'just': 1, 'are': 1, 'tell': 1, 'drinking': 1, 'our': 1, 'where': 1, \"i'll\": 1, 'all': 1, \"isn't\": 1, 'make': 1, 'lover': 1, 'get': 1, 'radio': 1, 'give': 1, 'can': 1, 'club': 1, 'it': 1, 'out': 1, 'chance': 1, 'first': 1, 'table': 1, 'thrifty': 1, 'driver': 1, 'slow': 1, 'dance': 1, 'trust': 1, 'family': 1, 'week': 1, 'date': 1, 'leave': 1, 'at': 1, 'hand': 1, 'how': 1, 'eat': 1, 'about': 1, 'story': 1, 'sweet': 1, 'best': 1, 'let': 1, 'van': 1, 'shots': 1, 'place': 1, 'find': 1, 'kiss': 1, 'stop': 1, 'bar': 1, \"don't\": 2, 'mind': 2, 'know': 2, 'so': 2, 'start': 2, 'boy': 2, 'girl': 2, 'singing': 2, 'doing': 2, 'somebody': 2, 'handmade': 2, 'may': 2, 'that': 2, 'much': 2, 'grab': 2, 'was': 2, 'say': 2, 'waist': 2, 'want': 2, \"let's\": 2, 'not': 2, 'crazy': 2, 'go': 2, 'to': 2, 'fill': 2, 'hours': 2, 'push': 3, 'then': 3, 'put': 3, 'room': 3, 'magnet': 3, 'up': 3, 'pull': 3, 'last': 3, 'do': 3, 'smell': 3, 'although': 3, 'falling': 3, 'were': 3, 'night': 3, 'heart': 3, 'for': 3, 'bedsheets': 3, 'talk': 4, 'too': 5, 'is': 5, 'every': 6, 'new': 6, 'follow': 6, 'brand': 6, 'of': 6, 'i': 6, 'day': 6, 'lead': 6, 'shape': 6, 'discovering': 6, 'something': 6, 'we': 7, 'a': 8, 'like': 10, 'me': 10, 'now': 11, 'baby': 14, 'you': 16, 'be': 16, 'body': 17, 'the': 18, 'your': 21, 'with': 22, \"i'm\": 23, 'and': 23, 'love': 25, 'in': 27, 'my': 33, 'come': 37, 'on': 40}\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'conversation': 1, \"we're\": 1, 'plate': 1, 'sour': 1, 'jukebox': 1, 'taxi': 1, 'fast': 1, 'bag': 1, 'man': 1, 'going': 1, 'one': 1, 'backseat': 1, 'friends': 1, 'take': 1, 'play': 1, 'okay': 1, 'begin': 1, 'over': 1, 'just': 1, 'are': 1, 'tell': 1, 'drinking': 1, 'our': 1, 'where': 1, \"i'll\": 1, 'all': 1, \"isn't\": 1, 'make': 1, 'lover': 1, 'get': 1, 'radio': 1, 'give': 1, 'can': 1, 'club': 1, 'it': 1, 'out': 1, 'chance': 1, 'first': 1, 'table': 1, 'thrifty': 1, 'driver': 1, 'slow': 1, 'dance': 1, 'trust': 1, 'family': 1, 'week': 1, 'date': 1, 'leave': 1, 'at': 1, 'hand': 1, 'how': 1, 'eat': 1, 'about': 1, 'story': 1, 'sweet': 1, 'best': 1, 'let': 1, 'van': 1, 'shots': 1, 'place': 1, 'find': 1, 'kiss': 1, 'stop': 1, 'bar': 1, \"don't\": 2, 'mind': 2, 'know': 2, 'so': 2, 'start': 2, 'boy': 2, 'girl': 2, 'singing': 2, 'doing': 2, 'somebody': 2, 'handmade': 2, 'may': 2, 'that': 2, 'much': 2, 'grab': 2, 'was': 2, 'say': 2, 'waist': 2, 'want': 2, \"let's\": 2, 'not': 2, 'crazy': 2, 'go': 2, 'to': 2, 'fill': 2, 'hours': 2, 'push': 3, 'then': 3, 'put': 3, 'room': 3, 'magnet': 3, 'up': 3, 'pull': 3, 'last': 3, 'do': 3, 'smell': 3, 'although': 3, 'falling': 3, 'were': 3, 'night': 3, 'heart': 3, 'for': 3, 'bedsheets': 3, 'talk': 4, 'too': 5, 'is': 5, 'every': 6, 'new': 6, 'follow': 6, 'brand': 6, 'of': 6, 'i': 6, 'day': 6, 'lead': 6, 'shape': 6, 'discovering': 6, 'something': 6, 'we': 7, 'a': 8, 'like': 10, 'me': 10, 'now': 11, 'baby': 14, 'you': 16, 'be': 16, 'body': 17, 'the': 18, 'your': 21, 'with': 22, \"i'm\": 23, 'and': 23, 'love': 25, 'in': 27, 'my': 33, 'come': 37, 'on': 40}\n" + ] + } + ], + "source": [ + "import operator\n", + "sorted_tups = sorted(word_freq.items(), key=operator.itemgetter(1))\n", + "word_freq2 = {k:v for k,v in sorted_tups}\n", + "print(word_freq2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Convert `word_freq` into Pandas dataframes\n", + "\n", + "In your future work, you may need to convert Python dictionaries to Pandas dataframes. So let's practice this by converting `word_freq`.\n", + "\n", + "**First, import the `pandas` library.**" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Then, use the `pd.DataFrame()` constructor to convert `word_freq` into a dataframe.**\n", + "\n", + "Here's a [reference](https://stackoverflow.com/questions/18837262/convert-python-dict-into-a-dataframe) to show you how to accomplish this. Also name the two columns of the dataframe as `word` and `freq`.\n", + "\n", + "Assign the converted value to a variable called `df`. The first few rows of `df` should look like this:\n", + "\n", + "![df](df.png)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " word freq\n", + "0 love 25\n", + "1 conversation 1\n", + "2 every 6\n", + "3 we're 1\n", + "4 plate 1" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Your code here\n", + "df = pd.DataFrame(word_freq.items(), columns=['word', 'freq'])\n", + "\n", + "df.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "With the Pandas DataFrame, you can sort the values easily with the built-in method `sort_values` ([reference](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.sort_values.html)).\n", + "\n", + "#### Sort `df` ascendingly based on column `word`." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " word freq\n", + "120 a 8\n", + "109 about 1\n", + "43 all 1\n", + "96 although 3\n", + "72 and 23\n", + ".. ... ...\n", + "128 were 3\n", + "41 where 1\n", + "54 with 22\n", + "15 you 16\n", + "97 your 21\n", + "\n", + "[140 rows x 2 columns]" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Your code here\n", + "df.sort_values('word', ascending=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Sort `df` ascendingly based on column `freq`." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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wordfreq
139bar1
114let1
116van1
60out1
57it1
.........
0love25
65in27
121my33
56come37
126on40
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140 rows × 2 columns

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" + ], + "text/plain": [ + " word freq\n", + "139 bar 1\n", + "114 let 1\n", + "116 van 1\n", + "60 out 1\n", + "57 it 1\n", + ".. ... ...\n", + "0 love 25\n", + "65 in 27\n", + "121 my 33\n", + "56 come 37\n", + "126 on 40\n", + "\n", + "[140 rows x 2 columns]" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Your code here\n", + "df.sort_values('freq', ascending=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "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": "3.8.8" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/your-code/challenge-1.ipynb b/your-code/challenge-1.ipynb index 2e59d77..3849db7 100755 --- a/your-code/challenge-1.ipynb +++ b/your-code/challenge-1.ipynb @@ -15,11 +15,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ - "# Your code here\n" + "# Your code here\n", + "tup = \"I\"," ] }, { @@ -33,11 +34,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "print(type(tup))" ] }, { @@ -55,13 +65,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "ename": "AttributeError", + "evalue": "'tuple' object has no attribute 'append'", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[1;31m# Your code here\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mtup\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"r\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"o\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"n\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"h\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"a\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"c\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"k\"\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 3\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 4\u001b[0m \u001b[1;31m# Your explanation here\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;31mAttributeError\u001b[0m: 'tuple' object has no attribute 'append'" + ] + } + ], "source": [ "# Your code here\n", + "tup.append([\"r\", \"o\", \"n\", \"h\", \"a\", \"c\", \"k\"])\n", "\n", - "# Your explanation here\n" + "# Your explanation here\n", + "# Tuples son tipos de variables inmutables" ] }, { @@ -79,13 +103,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('I', 'r', 'o', 'n', 'h', 'a', 'c', 'k')\n" + ] + } + ], "source": [ "# Your code here\n", + "tup = (\"I\", \"r\", \"o\", \"n\", \"h\", \"a\", \"c\", \"k\")\n", + "print(tup)\n", "\n", - "# Your explanation here\n" + "# Your explanation here\n", + "# ya que los tuples son inmitables, lo mejor forma para hacer una modificacion es l reasignacion" ] }, { @@ -103,11 +138,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('I', 'r', 'o', 'n')\n", + "('h', 'a', 'c', 'k')\n" + ] + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "tup1 = tup[:4]\n", + "tup2 = tup[-4:]\n", + "\n", + "print(tup1)\n", + "print(tup2)" ] }, { @@ -121,11 +170,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('I', 'r', 'o', 'n', 'h', 'a', 'c', 'k')\n", + "True\n" + ] + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "tup3 = tup1 + tup2\n", + "\n", + "# chechk if tup3 == tup\n", + "print(tup3 == tup)" ] }, { @@ -137,11 +199,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "True\n" + ] + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "tup1_len = len(tup1)\n", + "tup2_len = len(tup2)\n", + "\n", + "print( tup1_len + tup2_len == len(tup))" ] }, { @@ -153,11 +227,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "h\n" + ] + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "# Index 4\n", + "\n", + "print(tup3[4])" ] }, { @@ -177,11 +262,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "a --> True\n", + "b --> False\n", + "c --> True\n", + "d --> False\n", + "e --> False\n" + ] + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "letters = [\"a\", \"b\", \"c\", \"d\", \"e\"]\n", + "\n", + "for letter in letters:\n", + " print(letter, '-->', letter in tup3)" ] }, { @@ -195,12 +296,62 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 27, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "------------\n", + "a --> 1\n", + "b --> 0\n", + "c --> 1\n", + "d --> 0\n", + "e --> 0\n", + "------------\n", + "a --> 1\n", + "b --> 0\n", + "c --> 1\n", + "d --> 0\n", + "e --> 0\n", + "------------\n", + "a --> 1\n", + "b --> 0\n", + "c --> 1\n", + "d --> 0\n", + "e --> 0\n" + ] + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "\n", + "print('------------')\n", + "\n", + "for letter in letters:\n", + " print(letter, '-->', sum([letter == l for l in tup]))\n", + " \n", + "print('------------')\n", + "\n", + "for letter in letters:\n", + " c = 0\n", + " for l in tup:\n", + " if letter == l:\n", + " c += 1\n", + " print(letter, '-->', c)\n", + " \n", + "print('------------')\n", + "for letter in letters:\n", + " print(letter, '-->', tup.count(letter))" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { @@ -219,7 +370,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.2" + "version": "3.8.8" } }, "nbformat": 4, diff --git a/your-code/challenge-2.ipynb b/your-code/challenge-2.ipynb index 41d6911..4d7b3ba 100755 --- a/your-code/challenge-2.ipynb +++ b/your-code/challenge-2.ipynb @@ -13,7 +13,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -38,11 +38,22 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Your code here\n" + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[40, 59, 19, 20, 18, 97, 86, 52, 46, 44, 90, 24, 35, 77, 68, 0, 39, 76, 99, 88, 23, 4, 16, 54, 96, 72, 22, 37, 82, 17, 66, 61, 21, 55, 58, 70, 50, 3, 13, 42, 84, 25, 89, 15, 69, 51, 64, 67, 2, 87, 8, 12, 83, 63, 45, 43, 81, 30, 47, 5, 7, 71, 74, 78, 57, 48, 65, 56, 14, 31, 73, 94, 10, 27, 26, 32, 80, 11, 9, 79]\n" + ] + } + ], + "source": [ + "# Your code here\n", + "sample_list_1 = random.sample(range(101), k=80)\n", + "\n", + "print(sample_list_1)" ] }, { @@ -54,11 +65,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 32, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "80\n" + ] + } + ], "source": [ - "# Your code here\n" + "set_1 = set(sample_list_1)\n", + "print(len(set_1))" ] }, { @@ -77,11 +97,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 38, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[29, 78, 43, 70, 11, 19, 5, 44, 85, 20, 88, 28, 66, 42, 96, 60, 93, 45, 65, 53, 73, 89, 1, 79, 58, 77, 86, 12, 41, 74, 17, 50, 51, 80, 37, 83, 62, 100, 7, 8, 16, 27, 69, 82, 87, 95, 49, 72, 54, 56, 13, 67, 3, 10, 64, 24, 31, 71, 36, 81, 40, 98, 0, 59, 23, 35, 34, 6, 21, 33, 18, 47, 9, 32, 84, 75, 68, 61, 2, 4]\n" + ] + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "sample_list_2 = random.sample(range(101), k=80)\n", + "print(sample_list_2)" ] }, { @@ -93,11 +123,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 39, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "80\n" + ] + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "set_2 = set(sample_list_2)\n", + "print(len(set_2))" ] }, { @@ -109,11 +149,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 41, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{97, 99, 90, 39, 76, 14, 15, 46, 48, 52, 94, 22, 55, 25, 26, 63, 30, 57}\n" + ] + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "set_3 = set_1 - set_2\n", + "print(set_3)" ] }, { @@ -125,11 +175,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 42, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{1, 33, 34, 36, 98, 6, 100, 41, 75, 60, 49, 93, 53, 85, 28, 29, 62, 95}\n" + ] + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "set_4 = set_2 - set_1\n", + "print(set_4)" ] }, { @@ -141,11 +201,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 43, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{0, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 13, 16, 17, 18, 19, 20, 21, 23, 24, 27, 31, 32, 35, 37, 40, 42, 43, 44, 45, 47, 50, 51, 54, 56, 58, 59, 61, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 77, 78, 79, 80, 81, 82, 83, 84, 86, 87, 88, 89, 96}\n" + ] + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "set_5 = set_1.intersection(set_2)\n", + "print(set_5)" ] }, { @@ -165,11 +235,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 44, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 44, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "len(set_1) + len(set_2) == len(set_3) + len(set_4) + 2*len(set_5)" ] }, { @@ -181,11 +263,13 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 50, "metadata": {}, "outputs": [], "source": [ - "# Your code here\n" + "# Your code here\n", + "\n", + "set_6 = set()" ] }, { @@ -197,11 +281,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 51, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{0, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 30, 31, 32, 35, 37, 39, 40, 42, 43, 44, 45, 46, 47, 48, 50, 51, 52, 54, 55, 56, 57, 58, 59, 61, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 76, 77, 78, 79, 80, 81, 82, 83, 84, 86, 87, 88, 89, 90, 94, 96, 97, 99}\n" + ] + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "set_6.update(set_3, set_5)\n", + "print(set_6)" ] }, { @@ -213,11 +307,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 52, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 52, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "set_1 == set_6" ] }, { @@ -229,11 +335,23 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Your code here\n" + "execution_count": 55, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "False\n", + "True\n" + ] + } + ], + "source": [ + "# Your code here\n", + "print(set_2.issubset(set_1))\n", + "\n", + "print(set_3.issubset(set_1))" ] }, { @@ -247,11 +365,29 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Your code here\n" + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Union de set 3, set 4 y set 5\n", + "{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 93, 94, 95, 96, 97, 98, 99, 100} \n", + "\n", + "Union de set 1 y set 2\n", + "{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 93, 94, 95, 96, 97, 98, 99, 100}\n" + ] + } + ], + "source": [ + "# Your code here\n", + "print(\"Union de set 3, set 4 y set 5\")\n", + "print(set_3.union(set_4, set_5), '\\n')\n", + "\n", + "\n", + "print(\"Union de set 1 y set 2\")\n", + "print(set_3.union(set_4, set_5))\n" ] }, { @@ -263,11 +399,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 67, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "0" + ] + }, + "execution_count": 67, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "set_1.pop()" ] }, { @@ -281,14 +429,32 @@ "```" ] }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{2, 3, 4, 5, 7, 8, 10, 12, 13, 14, 15, 16, 17, 18, 20, 22, 23, 24, 25, 26, 27, 30, 32, 35, 37, 40, 42, 43, 44, 45, 46, 47, 48, 50, 52, 54, 55, 56, 57, 58, 63, 64, 65, 66, 67, 68, 70, 72, 73, 74, 76, 77, 78, 80, 82, 83, 84, 86, 87, 88, 90, 94, 96, 97}\n" + ] + } + ], + "source": [ + "# Your code here\n", + "list_to_remove = [1, 9, 11, 19, 21, 29, 31, 39, 41, 49, 51, 59, 61, 69, 71, 79, 81, 89, 91, 99]\n", + "remaining = set_1 - set(list_to_remove)\n", + "print(remaining)" + ] + }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], - "source": [ - "# Your code here\n" - ] + "source": [] } ], "metadata": { @@ -307,7 +473,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.2" + "version": "3.8.8" } }, "nbformat": 4, diff --git a/your-code/challenge-3.ipynb b/your-code/challenge-3.ipynb index 7ab8ea5..733435b 100755 --- a/your-code/challenge-3.ipynb +++ b/your-code/challenge-3.ipynb @@ -15,7 +15,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -49,11 +49,26 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'a': 8, 'about': 1, 'all': 1, 'although': 3, 'and': 23, 'are': 1, 'at': 1, 'baby': 14, 'backseat': 1, 'bag': 1, 'bar': 1, 'be': 16, 'bedsheets': 3, 'begin': 1, 'best': 1, 'body': 17, 'boy': 2, 'brand': 6, 'can': 1, 'chance': 1, 'club': 1, 'come': 37, 'conversation': 1, 'crazy': 2, 'dance': 1, 'date': 1, 'day': 6, 'discovering': 6, 'do': 3, 'doing': 2, \"don't\": 2, 'drinking': 1, 'driver': 1, 'eat': 1, 'every': 6, 'falling': 3, 'family': 1, 'fast': 1, 'fill': 2, 'find': 1, 'first': 1, 'follow': 6, 'for': 3, 'friends': 1, 'get': 1, 'girl': 2, 'give': 1, 'go': 2, 'going': 1, 'grab': 2, 'hand': 1, 'handmade': 2, 'heart': 3, 'hours': 2, 'how': 1, 'i': 6, \"i'll\": 1, \"i'm\": 23, 'in': 27, 'is': 5, \"isn't\": 1, 'it': 1, 'jukebox': 1, 'just': 1, 'kiss': 1, 'know': 2, 'last': 3, 'lead': 6, 'leave': 1, 'let': 1, \"let's\": 2, 'like': 10, 'love': 25, 'lover': 1, 'magnet': 3, 'make': 1, 'man': 1, 'may': 2, 'me': 10, 'mind': 2, 'much': 2, 'my': 33, 'new': 6, 'night': 3, 'not': 2, 'now': 11, 'of': 6, 'okay': 1, 'on': 40, 'one': 1, 'our': 1, 'out': 1, 'over': 1, 'place': 1, 'plate': 1, 'play': 1, 'pull': 3, 'push': 3, 'put': 3, 'radio': 1, 'room': 3, 'say': 2, 'shape': 6, 'shots': 1, 'singing': 2, 'slow': 1, 'smell': 3, 'so': 2, 'somebody': 2, 'something': 6, 'sour': 1, 'start': 2, 'stop': 1, 'story': 1, 'sweet': 1, 'table': 1, 'take': 1, 'talk': 4, 'taxi': 1, 'tell': 1, 'that': 2, 'the': 18, 'then': 3, 'thrifty': 1, 'to': 2, 'too': 5, 'trust': 1, 'up': 3, 'van': 1, 'waist': 2, 'want': 2, 'was': 2, 'we': 7, \"we're\": 1, 'week': 1, 'were': 3, 'where': 1, 'with': 22, 'you': 16, 'your': 21}\n" + ] + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "\n", + "word_freq2 = {}\n", + "\n", + "for w in sorted(word_freq.keys()):\n", + " word_freq2[w] = word_freq[w]\n", + "\n", + "print(word_freq2)" ] }, { @@ -90,11 +105,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'conversation': 1, \"we're\": 1, 'plate': 1, 'sour': 1, 'jukebox': 1, 'taxi': 1, 'fast': 1, 'bag': 1, 'man': 1, 'going': 1, 'one': 1, 'backseat': 1, 'friends': 1, 'take': 1, 'play': 1, 'okay': 1, 'begin': 1, 'over': 1, 'just': 1, 'are': 1, 'tell': 1, 'drinking': 1, 'our': 1, 'where': 1, \"i'll\": 1, 'all': 1, \"isn't\": 1, 'make': 1, 'lover': 1, 'get': 1, 'radio': 1, 'give': 1, 'can': 1, 'club': 1, 'it': 1, 'out': 1, 'chance': 1, 'first': 1, 'table': 1, 'thrifty': 1, 'driver': 1, 'slow': 1, 'dance': 1, 'trust': 1, 'family': 1, 'week': 1, 'date': 1, 'leave': 1, 'at': 1, 'hand': 1, 'how': 1, 'eat': 1, 'about': 1, 'story': 1, 'sweet': 1, 'best': 1, 'let': 1, 'van': 1, 'shots': 1, 'place': 1, 'find': 1, 'kiss': 1, 'stop': 1, 'bar': 1, \"don't\": 2, 'mind': 2, 'know': 2, 'so': 2, 'start': 2, 'boy': 2, 'girl': 2, 'singing': 2, 'doing': 2, 'somebody': 2, 'handmade': 2, 'may': 2, 'that': 2, 'much': 2, 'grab': 2, 'was': 2, 'say': 2, 'waist': 2, 'want': 2, \"let's\": 2, 'not': 2, 'crazy': 2, 'go': 2, 'to': 2, 'fill': 2, 'hours': 2, 'push': 3, 'then': 3, 'put': 3, 'room': 3, 'magnet': 3, 'up': 3, 'pull': 3, 'last': 3, 'do': 3, 'smell': 3, 'although': 3, 'falling': 3, 'were': 3, 'night': 3, 'heart': 3, 'for': 3, 'bedsheets': 3, 'talk': 4, 'too': 5, 'is': 5, 'every': 6, 'new': 6, 'follow': 6, 'brand': 6, 'of': 6, 'i': 6, 'day': 6, 'lead': 6, 'shape': 6, 'discovering': 6, 'something': 6, 'we': 7, 'a': 8, 'like': 10, 'me': 10, 'now': 11, 'baby': 14, 'you': 16, 'be': 16, 'body': 17, 'the': 18, 'your': 21, 'with': 22, \"i'm\": 23, 'and': 23, 'love': 25, 'in': 27, 'my': 33, 'come': 37, 'on': 40}\n" + ] + } + ], "source": [ - "# Your code here\n" + "import operator\n", + "sorted_tups = sorted(word_freq.items(), key=operator.itemgetter(1))\n", + "word_freq2 = {k:v for k,v in sorted_tups}\n", + "print(word_freq2)" ] }, { @@ -110,7 +136,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -132,11 +158,83 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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wordfreq
0love25
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2every6
3we're1
4plate1
\n", + "
" + ], + "text/plain": [ + " word freq\n", + "0 love 25\n", + "1 conversation 1\n", + "2 every 6\n", + "3 we're 1\n", + "4 plate 1" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "df = pd.DataFrame(word_freq.items(), columns=['word', 'freq'])\n", + "\n", + "df.head()" ] }, { @@ -150,11 +248,120 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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wordfreq
120a8
109about1
43all1
96although3
72and23
.........
128were3
41where1
54with22
15you16
97your21
\n", + "

140 rows × 2 columns

\n", + "
" + ], + "text/plain": [ + " word freq\n", + "120 a 8\n", + "109 about 1\n", + "43 all 1\n", + "96 although 3\n", + "72 and 23\n", + ".. ... ...\n", + "128 were 3\n", + "41 where 1\n", + "54 with 22\n", + "15 you 16\n", + "97 your 21\n", + "\n", + "[140 rows x 2 columns]" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "df.sort_values('word', ascending=True)" ] }, { @@ -166,12 +373,128 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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wordfreq
139bar1
114let1
116van1
60out1
57it1
.........
0love25
65in27
121my33
56come37
126on40
\n", + "

140 rows × 2 columns

\n", + "
" + ], + "text/plain": [ + " word freq\n", + "139 bar 1\n", + "114 let 1\n", + "116 van 1\n", + "60 out 1\n", + "57 it 1\n", + ".. ... ...\n", + "0 love 25\n", + "65 in 27\n", + "121 my 33\n", + "56 come 37\n", + "126 on 40\n", + "\n", + "[140 rows x 2 columns]" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "df.sort_values('freq', ascending=True)" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { @@ -190,7 +513,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.2" + "version": "3.8.8" } }, "nbformat": 4,