From fffb22943835c85c2f431e1655d5960f91828835 Mon Sep 17 00:00:00 2001 From: JeniferVargas <88690404+JeniferVargas@users.noreply.github.com> Date: Sun, 29 Aug 2021 11:05:09 -0400 Subject: [PATCH] Add files via upload --- your-code/challange2.ipynb | 443 +++++++++++++++++++++++++++++ your-code/challenge-1.ipynb | 211 ++++++++++++-- your-code/challenge3.ipynb | 550 ++++++++++++++++++++++++++++++++++++ 3 files changed, 1175 insertions(+), 29 deletions(-) create mode 100644 your-code/challange2.ipynb create mode 100644 your-code/challenge3.ipynb diff --git a/your-code/challange2.ipynb b/your-code/challange2.ipynb new file mode 100644 index 0000000..104b60b --- /dev/null +++ b/your-code/challange2.ipynb @@ -0,0 +1,443 @@ +{ + "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": 28, + "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": 29, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[85, 51, 76, 11, 78, 42, 66, 5, 15, 94, 71, 22, 69, 98, 7, 61, 77, 70, 99, 1, 83, 38, 9, 43, 87, 60, 95, 25, 28, 36, 21, 49, 55, 65, 39, 93, 58, 19, 90, 32, 12, 8, 20, 89, 6, 2, 86, 54, 35, 0, 31, 80, 48, 74, 64, 14, 41, 29, 46, 3, 67, 91, 33, 57, 47, 34, 30, 82, 53, 24, 23, 62, 16, 27, 52, 56, 4, 44, 92, 10]\n" + ] + } + ], + "source": [ + "# Your code here\n", + "sample_list_1=random.sample(range(100), 80)\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": 30, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "80\n", + "Es la misma longitud\n" + ] + } + ], + "source": [ + "# Your code here\n", + "set1=set(sample_list_1)\n", + "print(len(set1))\n", + "if len(set1)==len(sample_list_1):\n", + " print(\"Es la misma longitud\")\n", + "else:\n", + " print(\"No es la misma longitud\")" + ] + }, + { + "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": 31, + "metadata": {}, + "outputs": [], + "source": [ + "# Your code here\n", + "sample_list_2=[]\n", + "for i in range(80):\n", + " sample_list_2.append(random.choice(range(100)))" + ] + }, + { + "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": 32, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "52\n", + "No es la misma longitud\n" + ] + } + ], + "source": [ + "# Your code here\n", + "set2=set(sample_list_2)\n", + "print(len(set2))\n", + "if len(set2)==len(sample_list_2):\n", + " print(\"Es la misma longitud\")\n", + "else:\n", + " print(\"No es la misma longitud\")" + ] + }, + { + "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": 33, + "metadata": {}, + "outputs": [], + "source": [ + "# Your code here\n", + "set3=set1-set2" + ] + }, + { + "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": 34, + "metadata": {}, + "outputs": [], + "source": [ + "# Your code here\n", + "set4=set2-set1" + ] + }, + { + "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": 35, + "metadata": {}, + "outputs": [], + "source": [ + "# Your code here\n", + "set5=set1.intersection(set2)" + ] + }, + { + "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": 36, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "80\n", + "52\n", + "36\n", + "8\n", + "44\n", + "Math worked\n" + ] + } + ], + "source": [ + "# Your code here\n", + "print(len(set1))\n", + "print(len(set2))\n", + "print(len(set3))\n", + "print(len(set4))\n", + "print(len(set5))\n", + "if set3.union(set4,set5)==set1.union(set2):\n", + " print(\"Math worked\")\n", + "else:\n", + " print(\"Mathn't\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Create an empty set called `set6`." + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [], + "source": [ + "# Your code here\n", + "set6=set()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Add `set3` and `set5` to `set6` using the Python Set `update` method." + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [], + "source": [ + "# Your code here\n", + "set6.update(set3,set5,set6)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Check if `set1` and `set6` are equal." + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Math worked\n" + ] + } + ], + "source": [ + "# Your code here\n", + "if set1==set6:\n", + " print(\"Math worked\")\n", + "else:\n", + " print(\"Mathn't\")" + ] + }, + { + "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": 40, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "False\n", + "False\n" + ] + } + ], + "source": [ + "# Your code here\n", + "print(set2.issubset(set1))\n", + "print(set1.issubset(set2))" + ] + }, + { + "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": 41, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Math worked\n" + ] + } + ], + "source": [ + "# Your code here\n", + "if set3.union(set4,set5)==set1.union(set2):\n", + " print(\"Math worked\")\n", + "else:\n", + " print(\"Mathn't\") " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Using the `pop` method, remove the first element from `set1`." + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Your code here\n", + "set1.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": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{2, 3, 4, 5, 6, 7, 10, 12, 13, 15, 16, 17, 18, 20, 23, 24, 25, 26, 27, 28, 30, 32, 33, 34, 35, 36, 37, 40, 42, 44, 45, 46, 47, 48, 54, 55, 56, 57, 62, 64, 65, 67, 70, 72, 76, 77, 78, 80, 82, 85, 86, 87, 90, 92, 93, 94, 95, 96, 97, 98}\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", + "list_to_remove = set(list_to_remove)\n", + "print(set1-list_to_remove)" + ] + } + ], + "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..192eb76 100755 --- a/your-code/challenge-1.ipynb +++ b/your-code/challenge-1.ipynb @@ -15,11 +15,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('I',)\n" + ] + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "tup=(\"I\",)\n", + "print(tup)" ] }, { @@ -33,11 +43,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "print(type(tup))" ] }, { @@ -55,13 +74,49 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "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[0;32m 2\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0ma\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\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[0m\n\u001b[0m\u001b[0;32m 4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 5\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", "\n", - "# Your explanation here\n" + "##No se puede añadir un nuevo elemento ya que las tuplas son inmutables\n", + "\n", + "\n", + "# Your explanation here\n", + "#Tuples dont admit new items because they are inmmutable" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('r', 'o', 'n', 'h', 'a', 'c', 'k')\n", + "\n" + ] + } + ], + "source": [ + "tup_ej= (\"r\", \"o\", \"n\", \"h\", \"a\", \"c\", \"k\")\n", + "print(tup_ej)\n", + "print(type(tup_ej))" ] }, { @@ -79,12 +134,14 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "# Your code here\n", "\n", + "tup= (\"I\", \"r\", \"o\", \"n\", \"h\", \"a\", \"c\", \"k\")\n", + "\n", "# Your explanation here\n" ] }, @@ -103,11 +160,26 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 26, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('I', 'r', 'o', 'n')\n", + "('h', 'a', 'c', 'k')\n", + "\n" + ] + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "tup1=tup[0:4]\n", + "print(tup1)\n", + "tup2=tup[4:]\n", + "print(tup2)\n", + "print(type(tup1))" ] }, { @@ -121,11 +193,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('I', 'r', 'o', 'n', 'h', 'a', 'c', 'k')\n" + ] + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "\n", + "tup3=tup1+tup2\n", + "print(tup3)" ] }, { @@ -137,11 +220,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "4\n", + "('I', 'r', 'o', 'n')\n", + "('h', 'a', 'c', 'k')\n" + ] + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "print(len(tup1))\n", + "print(tup1)\n", + "len(tup2)\n", + "print(tup2)\n" ] }, { @@ -153,11 +250,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "4" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "tup3.index('h')" ] }, { @@ -177,11 +286,31 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "true\n", + "false\n", + "true\n", + "false\n", + "false\n" + ] + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "letters = [\"a\", \"b\", \"c\", \"d\", \"e\"]\n", + "tup3=('I', 'r', 'o', 'n', 'h', 'a', 'c', 'k')\n", + "\n", + "for i in letters:\n", + " if i in tup3: \n", + " print(\"true\")\n", + " else:\n", + " print(\"false\")" ] }, { @@ -195,12 +324,36 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The letter a has a number of ocurrence of 1\n", + "The letter b has a number of ocurrence of 0\n", + "The letter c has a number of ocurrence of 1\n", + "The letter d has a number of ocurrence of 0\n", + "The letter e has a number of ocurrence of 0\n" + ] + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "letters=[\"a\", \"b\", \"c\", \"d\", \"e\"]\n", + "tup3=('I', 'r', 'o', 'n', 'h', 'a', 'c', 'k')\n", + "\n", + "for i in letters:\n", + " print(\"The letter\",i,\"has a number of ocurrence of\", tup3.count(i))" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { @@ -219,7 +372,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.2" + "version": "3.8.8" } }, "nbformat": 4, diff --git a/your-code/challenge3.ipynb b/your-code/challenge3.ipynb new file mode 100644 index 0000000..95dfd04 --- /dev/null +++ b/your-code/challenge3.ipynb @@ -0,0 +1,550 @@ +{ + "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": 2, + "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", + "import operator\n", + "word_freq2=sorted(word_freq.items(),key=operator.itemgetter(0))\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": 22, + "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": [ + "# Your code here\n", + "sorted_tups=sorted(word_freq.items(),key=operator.itemgetter(1))\n", + "word_freq2={}\n", + "for i in sorted_tups:\n", + " word_freq2[i[0]]=i[1]\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": 26, + "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": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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wordfreq
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139bar1
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140 rows × 2 columns

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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\n", + ".. ... ...\n", + "135 bedsheets 3\n", + "136 fill 2\n", + "137 hours 2\n", + "138 stop 1\n", + "139 bar 1\n", + "\n", + "[140 rows x 2 columns]" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Your code here\n", + "df=pd.DataFrame(word_freq.items(), columns=['word', 'freq'])\n", + "df" + ] + }, + { + "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": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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wordfreq
120a8
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43all1
96although3
72and23
.........
128were3
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54with22
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97your21
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140 rows × 2 columns

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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": 33, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Your code here\n", + "df.sort_values(by=['word'])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Sort `df` ascendingly based on column `freq`." + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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wordfreq
139bar1
114let1
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60out1
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.........
0love25
65in27
121my33
56come37
126on40
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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": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Your code here\n", + "df.sort_values(by=['freq'])" + ] + } + ], + "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 +}