Lesson_2_Exercises.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "dWboQTMeJ1mS"
   },
   "source": [
    "# Exercises\n",
    "\n",
    "Choose and try to provide a working solution for as many problems as you want/can. You can use everything we learned so far and even (I encourange you to do so) check on Google for possible solutions. Just be sure to understand the solution!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "GU4gL1kkK1sF"
   },
   "source": [
    "### Ex #1\n",
    "Consider the following text in the `s` multiline string (don't be scared is just a normal string)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "id": "-2JVN5An0mcp"
   },
   "outputs": [],
   "source": [
    "s = '''>id_sequence_10188\n",
    "TGCAAATGGGTGGGTCAATGTTCCAAGGCCACCCCAAAGGGGCCCATGAGGAAAGGGCAAAACTAATGTGCTATAGCCTTAGGCCCTAAGGCCCGAGGGGAGTTGAGTTTTTCTACCCTGGGAAATTCATTGAGGCAGTAAGAGTGCCAGCCAAGCGGTGCCTCACCGCCACCAGAAGGCTCTAATAGTTTTTTGGGAATTTATTCCAAAATTAGGCCTAAAATTTTGATTT\n",
    ">id_sequence_17\n",
    "CATTGTGAGTTTTTAATTTAATTGCATTGTGTGTTTTTCATGTTGGATTTTAGAATTAATTTGTGTGCGGGGTTGAAATGGTTGTAGATTTGAATTGTGTTTTTTTAAATTTAAGGAAAAATGACACAGAGACCCCCAACGTTTGAATAAAGGACACAAAACCCCCTAAGGTTTCAAAAAAGACACTCAGACCCTCATTTGTTAACAGTAAATTATAAT\n",
    ">id_sequence_451\n",
    "AAACTTGGTCTTTCTGAAAATACTGAAAGAGGCATCGGTCTGTTATGGGGTCCTGATAGCACCGAGGAGTTCTTAAAAAAGTTTAGTCTAAAGGTGATATCATGATCCTACATTTTATCTTTTAAACCAATGGATTCATATTTATCTCTGTAAGTAGTGTTAAAACTTACTGAAGTTTAAAGTGGCAGTGGCAACCTCGTAGTTC\n",
    ">id_sequence_41\n",
    "TTGATTTTTGCTGCGTTAAGAGTTTTTAAAAAAATAATAATAATAATAACGAAAGAGATTGAACTGATCATTATGTACCCATTGATTACCGTTACGGCCAGCACAAATTTTAAGTCGAAGAGATTAACTAGACAAGCTCAAGATGTAACAGTTTGGCTTGATTTTAGAAGGTTTTATTTTTAAGAATACTCTAGAGTGATAAAATGTGAGTTCTTTAACAATTTCGTACTCTAGCGAGTAATAAAATGTGAGTTCTTTAACAATTTCGTATATAGAAGTCTCTAGCATATTGTAGATAGTAATCGGTCTAAAATATTCTAGGTATTACTAAAAATGAGATTTCTTTAAACCATGAAAATTCTCTAGATTAGAAAAGCCAGGCCCTCCCTATAGGCTTGGTTACTTGACATTTTATTCAAGCAATTCAAATTAAGCAATGCCAAGTATCAAATACCAAGCATCAAATACCAAGCATCAAGT\n",
    ">id_sequence_101\n",
    "TTGCCAAACAAGTTACCAAATATGTTACTAGAGAGAAATCTAGTACATGGTACCTACAAAATTAAATATCAAAGCGGACTGACACCAAACTGTAGCTAACATCTTCATTTCCATGGATAGCTGATATATTTCTCAATATGAACTCTCTTTCATATATCTCATACTTTCTAAATAGATGTTCTGTCTCAAATTGAATT\n",
    ">id_sequence_201\n",
    "ACAGAAAATATTCAAAAGTTTTGGAGGAAAGTTGGTCTGGTTGTTTGCTAGGTCATTCTGATTGTGCAACTTCAATAAGCACAAATGGTATGTCATTAACTTAGAAGAAATATACTTTAGATATCAACTACTTCACATATCCTCTCTTGCATCAATATAAGAGCAGGAATCATGCCAAGCCATAAGAGCCCAGATAACCTGACTC\n",
    ">id_sequence_131\n",
    "GGCTTAAATTCCATGCTCCTATCTCTAAAGAAGTTTTCAAGTTCCTCCATGAATGATGATTGCTCCTCTTCCGTTCCAGATTCACTGCCCTCGTCACTTCCATCCAAAAGAAATAACTGTGCTGAGTTGGACTTCTCATTCATTGGTAGTGTAGGTAACTCCGATTTGTTAACCTTATCTTTGATTTCTGTGTCATTTACATTCTTAAGCTCTGTGTCAGAAGGAGCTGCATTACG\n",
    ">id_sequence_21\n",
    "TTATTTTGTCTTTGTCGACGATCTGATTCCTTCCGATAAAAGATAAACCCTAACTTATTTCTTAACGATATCGATCTAATATCACCCCTTTTCCTTTCCGCAGCACTCTGCTTCTTTTTATTTATGTTTTTCCTTTTCCCGTCTTCTTTTTTTTAATAATTAAGAGGATTCTCTAATTCATTCTTGATAACGGGACGGTACAGGCACAAAAGCCAGGCGGACAGCTTCCGTATTGAACACGTGTTTTATTACT\n",
    ">id_sequence_10\n",
    "ACTGTAAAAATCCGAGGAATAGCTTTTTAGAATTTAATTTTAAAAATCAGTTTTATATTTAATACAATTTCACATATATTCTTACATACTTTACATAAACCCAAAGTTTTACTTAGTCAATTTAAAAATAAACTCAGAAAAGTTTAGATAATTATTCTTTTAATTTATTTTTTCTTCATGCACACTCTTCACCCCAAAACCTCTTCTTCTTCCTATTTTCCATTCCATCCAAACTTATCTAATCGTATAAAAATCATTA\n",
    ">id_sequence_112\n",
    "TGGTAGTATAACTCTCAAATATCAAGAGATAAGCCCCTTGAAGAAAATATAGCTTTTGTAAATATGTCTGGTATCAAAGGGTATTATCAGAACTCAAATTTTGTTGATTAGAGACAGCACGTGAATAGTGCACGCTATCATGAGAAAAAATAAAATATCTTCTTTTTTGGCTAAGAATAAGAAGCCAATAAAAATAAAAGTTCTTTAAACAAATCAATAGGAGTGGACCACGTCAGTTGTCCTTT\n",
    "'''"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "kLWKr0oHLWiH"
   },
   "source": [
    "If you are used to FASTA format that is a set of DNA sequences in a FASTA-formatted string. If you never saw a FASTA formatted file before don't worry they are composed as follow:\n",
    "everything that starts with a  `>` till the end of line is considered an `ID` and everything from the following line up until the next end of line is considered a `sequence`.\n",
    "\n",
    "1) Write a program to read the FASTA format and put the result in a dictionary in the form `{'ID1': 'sequence1', 'ID2': 'sequence2', ... }`\n",
    "\n",
    "2) How many sequences are there? Which is the longest and the shortest? What is the average length?\n",
    "\n",
    "3) Which sequence contains the following 'CCATTCCATCCAAACTTATCT`?\n",
    "\n",
    "4) Extract the pieces from the nucleotide (aka letter) 30 to 40 and from 65 to 85 from each sequence, printing a valid FASTA formatted string\n",
    "\n",
    "5) Since every nucleotide (aka A, C, T, G) has a complementary nucleotide (T, G, A, C respectively). Write the reverse complement of each sequence."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'>id_sequence_10188': 'TGCAAATGGGTGGGTCAATGTTCCAAGGCCACCCCAAAGGGGCCCATGAGGAAAGGGCAAAACTAATGTGCTATAGCCTTAGGCCCTAAGGCCCGAGGGGAGTTGAGTTTTTCTACCCTGGGAAATTCATTGAGGCAGTAAGAGTGCCAGCCAAGCGGTGCCTCACCGCCACCAGAAGGCTCTAATAGTTTTTTGGGAATTTATTCCAAAATTAGGCCTAAAATTTTGATTT',\n",
       " '>id_sequence_17': 'CATTGTGAGTTTTTAATTTAATTGCATTGTGTGTTTTTCATGTTGGATTTTAGAATTAATTTGTGTGCGGGGTTGAAATGGTTGTAGATTTGAATTGTGTTTTTTTAAATTTAAGGAAAAATGACACAGAGACCCCCAACGTTTGAATAAAGGACACAAAACCCCCTAAGGTTTCAAAAAAGACACTCAGACCCTCATTTGTTAACAGTAAATTATAAT',\n",
       " '>id_sequence_451': 'AAACTTGGTCTTTCTGAAAATACTGAAAGAGGCATCGGTCTGTTATGGGGTCCTGATAGCACCGAGGAGTTCTTAAAAAAGTTTAGTCTAAAGGTGATATCATGATCCTACATTTTATCTTTTAAACCAATGGATTCATATTTATCTCTGTAAGTAGTGTTAAAACTTACTGAAGTTTAAAGTGGCAGTGGCAACCTCGTAGTTC',\n",
       " '>id_sequence_41': 'TTGATTTTTGCTGCGTTAAGAGTTTTTAAAAAAATAATAATAATAATAACGAAAGAGATTGAACTGATCATTATGTACCCATTGATTACCGTTACGGCCAGCACAAATTTTAAGTCGAAGAGATTAACTAGACAAGCTCAAGATGTAACAGTTTGGCTTGATTTTAGAAGGTTTTATTTTTAAGAATACTCTAGAGTGATAAAATGTGAGTTCTTTAACAATTTCGTACTCTAGCGAGTAATAAAATGTGAGTTCTTTAACAATTTCGTATATAGAAGTCTCTAGCATATTGTAGATAGTAATCGGTCTAAAATATTCTAGGTATTACTAAAAATGAGATTTCTTTAAACCATGAAAATTCTCTAGATTAGAAAAGCCAGGCCCTCCCTATAGGCTTGGTTACTTGACATTTTATTCAAGCAATTCAAATTAAGCAATGCCAAGTATCAAATACCAAGCATCAAATACCAAGCATCAAGT',\n",
       " '>id_sequence_101': 'TTGCCAAACAAGTTACCAAATATGTTACTAGAGAGAAATCTAGTACATGGTACCTACAAAATTAAATATCAAAGCGGACTGACACCAAACTGTAGCTAACATCTTCATTTCCATGGATAGCTGATATATTTCTCAATATGAACTCTCTTTCATATATCTCATACTTTCTAAATAGATGTTCTGTCTCAAATTGAATT',\n",
       " '>id_sequence_201': 'ACAGAAAATATTCAAAAGTTTTGGAGGAAAGTTGGTCTGGTTGTTTGCTAGGTCATTCTGATTGTGCAACTTCAATAAGCACAAATGGTATGTCATTAACTTAGAAGAAATATACTTTAGATATCAACTACTTCACATATCCTCTCTTGCATCAATATAAGAGCAGGAATCATGCCAAGCCATAAGAGCCCAGATAACCTGACTC',\n",
       " '>id_sequence_131': 'GGCTTAAATTCCATGCTCCTATCTCTAAAGAAGTTTTCAAGTTCCTCCATGAATGATGATTGCTCCTCTTCCGTTCCAGATTCACTGCCCTCGTCACTTCCATCCAAAAGAAATAACTGTGCTGAGTTGGACTTCTCATTCATTGGTAGTGTAGGTAACTCCGATTTGTTAACCTTATCTTTGATTTCTGTGTCATTTACATTCTTAAGCTCTGTGTCAGAAGGAGCTGCATTACG',\n",
       " '>id_sequence_21': 'TTATTTTGTCTTTGTCGACGATCTGATTCCTTCCGATAAAAGATAAACCCTAACTTATTTCTTAACGATATCGATCTAATATCACCCCTTTTCCTTTCCGCAGCACTCTGCTTCTTTTTATTTATGTTTTTCCTTTTCCCGTCTTCTTTTTTTTAATAATTAAGAGGATTCTCTAATTCATTCTTGATAACGGGACGGTACAGGCACAAAAGCCAGGCGGACAGCTTCCGTATTGAACACGTGTTTTATTACT',\n",
       " '>id_sequence_10': 'ACTGTAAAAATCCGAGGAATAGCTTTTTAGAATTTAATTTTAAAAATCAGTTTTATATTTAATACAATTTCACATATATTCTTACATACTTTACATAAACCCAAAGTTTTACTTAGTCAATTTAAAAATAAACTCAGAAAAGTTTAGATAATTATTCTTTTAATTTATTTTTTCTTCATGCACACTCTTCACCCCAAAACCTCTTCTTCTTCCTATTTTCCATTCCATCCAAACTTATCTAATCGTATAAAAATCATTA',\n",
       " '>id_sequence_112': 'TGGTAGTATAACTCTCAAATATCAAGAGATAAGCCCCTTGAAGAAAATATAGCTTTTGTAAATATGTCTGGTATCAAAGGGTATTATCAGAACTCAAATTTTGTTGATTAGAGACAGCACGTGAATAGTGCACGCTATCATGAGAAAAAATAAAATATCTTCTTTTTTGGCTAAGAATAAGAAGCCAATAAAAATAAAAGTTCTTTAAACAAATCAATAGGAGTGGACCACGTCAGTTGTCCTTT'}"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "separator='\\n'\n",
    "dna=s.split(separator)\n",
    "key=[dna[i] for i in range(len(dna)) if i%2==0]\n",
    "value=[dna[i] for i in range(len(dna)) if i%2==1]\n",
    "dd=dict(zip(key,value))\n",
    "dd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(dd)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'id_sequence_10188': 'TGCAAATGGGTGGGTCAATGTTCCAAGGCCACCCCAAAGGGGCCCATGAGGAAAGGGCAAAACTAATGTGCTATAGCCTTAGGCCCTAAGGCCCGAGGGGAGTTGAGTTTTTCTACCCTGGGAAATTCATTGAGGCAGTAAGAGTGCCAGCCAAGCGGTGCCTCACCGCCACCAGAAGGCTCTAATAGTTTTTTGGGAATTTATTCCAAAATTAGGCCTAAAATTTTGATTT',\n",
       " 'id_sequence_17': 'CATTGTGAGTTTTTAATTTAATTGCATTGTGTGTTTTTCATGTTGGATTTTAGAATTAATTTGTGTGCGGGGTTGAAATGGTTGTAGATTTGAATTGTGTTTTTTTAAATTTAAGGAAAAATGACACAGAGACCCCCAACGTTTGAATAAAGGACACAAAACCCCCTAAGGTTTCAAAAAAGACACTCAGACCCTCATTTGTTAACAGTAAATTATAAT',\n",
       " 'id_sequence_451': 'AAACTTGGTCTTTCTGAAAATACTGAAAGAGGCATCGGTCTGTTATGGGGTCCTGATAGCACCGAGGAGTTCTTAAAAAAGTTTAGTCTAAAGGTGATATCATGATCCTACATTTTATCTTTTAAACCAATGGATTCATATTTATCTCTGTAAGTAGTGTTAAAACTTACTGAAGTTTAAAGTGGCAGTGGCAACCTCGTAGTTC',\n",
       " 'id_sequence_41': 'TTGATTTTTGCTGCGTTAAGAGTTTTTAAAAAAATAATAATAATAATAACGAAAGAGATTGAACTGATCATTATGTACCCATTGATTACCGTTACGGCCAGCACAAATTTTAAGTCGAAGAGATTAACTAGACAAGCTCAAGATGTAACAGTTTGGCTTGATTTTAGAAGGTTTTATTTTTAAGAATACTCTAGAGTGATAAAATGTGAGTTCTTTAACAATTTCGTACTCTAGCGAGTAATAAAATGTGAGTTCTTTAACAATTTCGTATATAGAAGTCTCTAGCATATTGTAGATAGTAATCGGTCTAAAATATTCTAGGTATTACTAAAAATGAGATTTCTTTAAACCATGAAAATTCTCTAGATTAGAAAAGCCAGGCCCTCCCTATAGGCTTGGTTACTTGACATTTTATTCAAGCAATTCAAATTAAGCAATGCCAAGTATCAAATACCAAGCATCAAATACCAAGCATCAAGT',\n",
       " 'id_sequence_101': 'TTGCCAAACAAGTTACCAAATATGTTACTAGAGAGAAATCTAGTACATGGTACCTACAAAATTAAATATCAAAGCGGACTGACACCAAACTGTAGCTAACATCTTCATTTCCATGGATAGCTGATATATTTCTCAATATGAACTCTCTTTCATATATCTCATACTTTCTAAATAGATGTTCTGTCTCAAATTGAATT',\n",
       " 'id_sequence_201': 'ACAGAAAATATTCAAAAGTTTTGGAGGAAAGTTGGTCTGGTTGTTTGCTAGGTCATTCTGATTGTGCAACTTCAATAAGCACAAATGGTATGTCATTAACTTAGAAGAAATATACTTTAGATATCAACTACTTCACATATCCTCTCTTGCATCAATATAAGAGCAGGAATCATGCCAAGCCATAAGAGCCCAGATAACCTGACTC',\n",
       " 'id_sequence_131': 'GGCTTAAATTCCATGCTCCTATCTCTAAAGAAGTTTTCAAGTTCCTCCATGAATGATGATTGCTCCTCTTCCGTTCCAGATTCACTGCCCTCGTCACTTCCATCCAAAAGAAATAACTGTGCTGAGTTGGACTTCTCATTCATTGGTAGTGTAGGTAACTCCGATTTGTTAACCTTATCTTTGATTTCTGTGTCATTTACATTCTTAAGCTCTGTGTCAGAAGGAGCTGCATTACG',\n",
       " 'id_sequence_21': 'TTATTTTGTCTTTGTCGACGATCTGATTCCTTCCGATAAAAGATAAACCCTAACTTATTTCTTAACGATATCGATCTAATATCACCCCTTTTCCTTTCCGCAGCACTCTGCTTCTTTTTATTTATGTTTTTCCTTTTCCCGTCTTCTTTTTTTTAATAATTAAGAGGATTCTCTAATTCATTCTTGATAACGGGACGGTACAGGCACAAAAGCCAGGCGGACAGCTTCCGTATTGAACACGTGTTTTATTACT',\n",
       " 'id_sequence_10': 'ACTGTAAAAATCCGAGGAATAGCTTTTTAGAATTTAATTTTAAAAATCAGTTTTATATTTAATACAATTTCACATATATTCTTACATACTTTACATAAACCCAAAGTTTTACTTAGTCAATTTAAAAATAAACTCAGAAAAGTTTAGATAATTATTCTTTTAATTTATTTTTTCTTCATGCACACTCTTCACCCCAAAACCTCTTCTTCTTCCTATTTTCCATTCCATCCAAACTTATCTAATCGTATAAAAATCATTA',\n",
       " 'id_sequence_112': 'TGGTAGTATAACTCTCAAATATCAAGAGATAAGCCCCTTGAAGAAAATATAGCTTTTGTAAATATGTCTGGTATCAAAGGGTATTATCAGAACTCAAATTTTGTTGATTAGAGACAGCACGTGAATAGTGCACGCTATCATGAGAAAAAATAAAATATCTTCTTTTTTGGCTAAGAATAAGAAGCCAATAAAAATAAAAGTTCTTTAAACAAATCAATAGGAGTGGACCACGTCAGTTGTCCTTT'}"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d_fasta = {}\n",
    "\n",
    "for l in s.split('\\n'):\n",
    "  if len(l) and l[0] == '>':\n",
    "    id = l[1:].strip()\n",
    "    d_fasta[id] = ''\n",
    "  else:\n",
    "    d_fasta[id] += l.strip()\n",
    "\n",
    "d_fasta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(d_fasta)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "string = '\\nciaociao\\n\\nciao\\n\\n\\n'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "ciaociao\n",
      "\n",
      "ciao\n",
      "\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(string)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ciaociao\n",
      "\n",
      "ciao\n"
     ]
    }
   ],
   "source": [
    "print(string.strip())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "VZ0G0kPbTO7n"
   },
   "source": [
    "# Ex # 2\n",
    "Consider the following 3 `dict` as 3 samples containing the measurements for 18 variables each"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "UU_YPumsTAIg"
   },
   "outputs": [],
   "source": [
    "sample_a = {'var_1': 30, 'var_2': 60, 'var_3': 56, 'var_4': 97, 'var_5': 66, 'var_6': 40, 'var_7': 23, 'var_8': 16, 'var_9': 90, 'var_10': 22, 'var_11': 40, 'var_12': 10, 'var_13': 18, 'var_14': 37, 'var_15': 5, 'var_16': 66, 'var_17': 60, 'var_18': 36}\n",
    "sample_b = {'var_1': 96, 'var_2': 91, 'var_3': 9, 'var_4': 34, 'var_5': 19, 'var_6': 61, 'var_7': 11, 'var_8': 52, 'var_9': 72, 'var_10': 44, 'var_11': 57, 'var_12': 21, 'var_13': 95, 'var_14': 34, 'var_15': 4, 'var_16': 80, 'var_17': 83, 'var_18': 75}\n",
    "sample_c = {'var_1': 85, 'var_2': 61, 'var_3': 99, 'var_4': 98, 'var_5': 99, 'var_6': 51, 'var_7': 34, 'var_8': 76, 'var_9': 87, 'var_10': 94, 'var_11': 66, 'var_12': 64, 'var_13': 69, 'var_14': 68, 'var_15': 4, 'var_16': 74, 'var_17': 57, 'var_18': 31}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "9li9ARRKkHnS"
   },
   "source": [
    "1. Calculate the average value of each variable between samples;\n",
    "2. Calculate the standard deviation of each variable between samples (check on Google if you don't remember how to calculate standard deviation). You can use `import math` and `math.sqrt` or power of 0.5 to get the square root of a number.\n",
    "3. Compare all the possible couples calculating the difference between variables, i.e. sample_a - sample_b, sample_a - sample_c, etc.\n",
    "4. Starting from the previous point consider only the couples in which variable difference has an absolute value of at least 20. How many of these variables are in common between all couples? How many there are in total? How many are common to just 2 of the couples? Hint: think about that as a Venn diagram. You might want to use the functions set.union(a, b), set.intersection(a, b) and set.difference(a, b) calculate union, intersection and difference between sets.\n",
    "The absolute value can be calculated using the `abs(n)` function where `n` is the number for which we want the absolute value, so `abs(-5)` will return `5`.\n",
    "5. Normalize each variable value by substracting the mean value for that variable and dividing it by its standard deviation.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import math\n",
    "\n",
    "4**0.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "abs(-5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1, 2, 3, 4}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = set([1, 2, 3])\n",
    "b = set([1, 2, 4])\n",
    "\n",
    "set.union(a, b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1, 2}"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "set.intersection(a, b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{3}"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a - b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{3}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "set.difference(a, b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{4}"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "set.difference(b, a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'>id_sequence_101': 'TTGCCAAACAAGTTACCAAATATGTTACTAGAGAGAAATCTAGTACATGGTACCTACAAAATTAAATATCAAAGCGGACTGACACCAAACTGTAGCTAACATCTTCATTTCCATGGATAGCTGATATATTTCTCAATATGAACTCTCTTTCATATATCTCATACTTTCTAAATAGATGTTCTGTCTCAAATTGAATT',\n",
       " '>id_sequence_17': 'CATTGTGAGTTTTTAATTTAATTGCATTGTGTGTTTTTCATGTTGGATTTTAGAATTAATTTGTGTGCGGGGTTGAAATGGTTGTAGATTTGAATTGTGTTTTTTTAAATTTAAGGAAAAATGACACAGAGACCCCCAACGTTTGAATAAAGGACACAAAACCCCCTAAGGTTTCAAAAAAGACACTCAGACCCTCATTTGTTAACAGTAAATTATAAT',\n",
       " '>id_sequence_451': 'AAACTTGGTCTTTCTGAAAATACTGAAAGAGGCATCGGTCTGTTATGGGGTCCTGATAGCACCGAGGAGTTCTTAAAAAAGTTTAGTCTAAAGGTGATATCATGATCCTACATTTTATCTTTTAAACCAATGGATTCATATTTATCTCTGTAAGTAGTGTTAAAACTTACTGAAGTTTAAAGTGGCAGTGGCAACCTCGTAGTTC',\n",
       " '>id_sequence_41': 'TTGATTTTTGCTGCGTTAAGAGTTTTTAAAAAAATAATAATAATAATAACGAAAGAGATTGAACTGATCATTATGTACCCATTGATTACCGTTACGGCCAGCACAAATTTTAAGTCGAAGAGATTAACTAGACAAGCTCAAGATGTAACAGTTTGGCTTGATTTTAGAAGGTTTTATTTTTAAGAATACTCTAGAGTGATAAAATGTGAGTTCTTTAACAATTTCGTACTCTAGCGAGTAATAAAATGTGAGTTCTTTAACAATTTCGTATATAGAAGTCTCTAGCATATTGTAGATAGTAATCGGTCTAAAATATTCTAGGTATTACTAAAAATGAGATTTCTTTAAACCATGAAAATTCTCTAGATTAGAAAAGCCAGGCCCTCCCTATAGGCTTGGTTACTTGACATTTTATTCAAGCAATTCAAATTAAGCAATGCCAAGTATCAAATACCAAGCATCAAATACCAAGCATCAAGT',\n",
       " '>id_sequence_201': 'ACAGAAAATATTCAAAAGTTTTGGAGGAAAGTTGGTCTGGTTGTTTGCTAGGTCATTCTGATTGTGCAACTTCAATAAGCACAAATGGTATGTCATTAACTTAGAAGAAATATACTTTAGATATCAACTACTTCACATATCCTCTCTTGCATCAATATAAGAGCAGGAATCATGCCAAGCCATAAGAGCCCAGATAACCTGACTC',\n",
       " '>id_sequence_131': 'GGCTTAAATTCCATGCTCCTATCTCTAAAGAAGTTTTCAAGTTCCTCCATGAATGATGATTGCTCCTCTTCCGTTCCAGATTCACTGCCCTCGTCACTTCCATCCAAAAGAAATAACTGTGCTGAGTTGGACTTCTCATTCATTGGTAGTGTAGGTAACTCCGATTTGTTAACCTTATCTTTGATTTCTGTGTCATTTACATTCTTAAGCTCTGTGTCAGAAGGAGCTGCATTACG',\n",
       " '>id_sequence_21': 'TTATTTTGTCTTTGTCGACGATCTGATTCCTTCCGATAAAAGATAAACCCTAACTTATTTCTTAACGATATCGATCTAATATCACCCCTTTTCCTTTCCGCAGCACTCTGCTTCTTTTTATTTATGTTTTTCCTTTTCCCGTCTTCTTTTTTTTAATAATTAAGAGGATTCTCTAATTCATTCTTGATAACGGGACGGTACAGGCACAAAAGCCAGGCGGACAGCTTCCGTATTGAACACGTGTTTTATTACT',\n",
       " '>id_sequence_10': 'ACTGTAAAAATCCGAGGAATAGCTTTTTAGAATTTAATTTTAAAAATCAGTTTTATATTTAATACAATTTCACATATATTCTTACATACTTTACATAAACCCAAAGTTTTACTTAGTCAATTTAAAAATAAACTCAGAAAAGTTTAGATAATTATTCTTTTAATTTATTTTTTCTTCATGCACACTCTTCACCCCAAAACCTCTTCTTCTTCCTATTTTCCATTCCATCCAAACTTATCTAATCGTATAAAAATCATTA',\n",
       " '>id_sequence_112': 'TGGTAGTATAACTCTCAAATATCAAGAGATAAGCCCCTTGAAGAAAATATAGCTTTTGTAAATATGTCTGGTATCAAAGGGTATTATCAGAACTCAAATTTTGTTGATTAGAGACAGCACGTGAATAGTGCACGCTATCATGAGAAAAAATAAAATATCTTCTTTTTTGGCTAAGAATAAGAAGCCAATAAAAATAAAAGTTCTTTAAACAAATCAATAGGAGTGGACCACGTCAGTTGTCCTTT'}"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "separator='\\n'\n",
    "dna=s.split(separator)\n",
    "key=[dna[i] for i in range(len(dna)) if i%2==0]\n",
    "value=[dna[i] for i in range(len(dna)) if i%2==1]\n",
    "dd=dict(zip(key,value))\n",
    "dd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'>id_sequence_101': 'TTGCCAAACAAGTTACCAAATATGTTACTAGAGAGAAATCTAGTACATGGTACCTACAAAATTAAATATCAAAGCGGACTGACACCAAACTGTAGCTAACATCTTCATTTCCATGGATAGCTGATATATTTCTCAATATGAACTCTCTTTCATATATCTCATACTTTCTAAATAGATGTTCTGTCTCAAATTGAATT', '>id_sequence_17': 'CATTGTGAGTTTTTAATTTAATTGCATTGTGTGTTTTTCATGTTGGATTTTAGAATTAATTTGTGTGCGGGGTTGAAATGGTTGTAGATTTGAATTGTGTTTTTTTAAATTTAAGGAAAAATGACACAGAGACCCCCAACGTTTGAATAAAGGACACAAAACCCCCTAAGGTTTCAAAAAAGACACTCAGACCCTCATTTGTTAACAGTAAATTATAAT', '>id_sequence_451': 'AAACTTGGTCTTTCTGAAAATACTGAAAGAGGCATCGGTCTGTTATGGGGTCCTGATAGCACCGAGGAGTTCTTAAAAAAGTTTAGTCTAAAGGTGATATCATGATCCTACATTTTATCTTTTAAACCAATGGATTCATATTTATCTCTGTAAGTAGTGTTAAAACTTACTGAAGTTTAAAGTGGCAGTGGCAACCTCGTAGTTC', '>id_sequence_41': 'TTGATTTTTGCTGCGTTAAGAGTTTTTAAAAAAATAATAATAATAATAACGAAAGAGATTGAACTGATCATTATGTACCCATTGATTACCGTTACGGCCAGCACAAATTTTAAGTCGAAGAGATTAACTAGACAAGCTCAAGATGTAACAGTTTGGCTTGATTTTAGAAGGTTTTATTTTTAAGAATACTCTAGAGTGATAAAATGTGAGTTCTTTAACAATTTCGTACTCTAGCGAGTAATAAAATGTGAGTTCTTTAACAATTTCGTATATAGAAGTCTCTAGCATATTGTAGATAGTAATCGGTCTAAAATATTCTAGGTATTACTAAAAATGAGATTTCTTTAAACCATGAAAATTCTCTAGATTAGAAAAGCCAGGCCCTCCCTATAGGCTTGGTTACTTGACATTTTATTCAAGCAATTCAAATTAAGCAATGCCAAGTATCAAATACCAAGCATCAAATACCAAGCATCAAGT', '>id_sequence_201': 'ACAGAAAATATTCAAAAGTTTTGGAGGAAAGTTGGTCTGGTTGTTTGCTAGGTCATTCTGATTGTGCAACTTCAATAAGCACAAATGGTATGTCATTAACTTAGAAGAAATATACTTTAGATATCAACTACTTCACATATCCTCTCTTGCATCAATATAAGAGCAGGAATCATGCCAAGCCATAAGAGCCCAGATAACCTGACTC', '>id_sequence_131': 'GGCTTAAATTCCATGCTCCTATCTCTAAAGAAGTTTTCAAGTTCCTCCATGAATGATGATTGCTCCTCTTCCGTTCCAGATTCACTGCCCTCGTCACTTCCATCCAAAAGAAATAACTGTGCTGAGTTGGACTTCTCATTCATTGGTAGTGTAGGTAACTCCGATTTGTTAACCTTATCTTTGATTTCTGTGTCATTTACATTCTTAAGCTCTGTGTCAGAAGGAGCTGCATTACG', '>id_sequence_21': 'TTATTTTGTCTTTGTCGACGATCTGATTCCTTCCGATAAAAGATAAACCCTAACTTATTTCTTAACGATATCGATCTAATATCACCCCTTTTCCTTTCCGCAGCACTCTGCTTCTTTTTATTTATGTTTTTCCTTTTCCCGTCTTCTTTTTTTTAATAATTAAGAGGATTCTCTAATTCATTCTTGATAACGGGACGGTACAGGCACAAAAGCCAGGCGGACAGCTTCCGTATTGAACACGTGTTTTATTACT', '>id_sequence_10': 'ACTGTAAAAATCCGAGGAATAGCTTTTTAGAATTTAATTTTAAAAATCAGTTTTATATTTAATACAATTTCACATATATTCTTACATACTTTACATAAACCCAAAGTTTTACTTAGTCAATTTAAAAATAAACTCAGAAAAGTTTAGATAATTATTCTTTTAATTTATTTTTTCTTCATGCACACTCTTCACCCCAAAACCTCTTCTTCTTCCTATTTTCCATTCCATCCAAACTTATCTAATCGTATAAAAATCATTA', '>id_sequence_112': 'TGGTAGTATAACTCTCAAATATCAAGAGATAAGCCCCTTGAAGAAAATATAGCTTTTGTAAATATGTCTGGTATCAAAGGGTATTATCAGAACTCAAATTTTGTTGATTAGAGACAGCACGTGAATAGTGCACGCTATCATGAGAAAAAATAAAATATCTTCTTTTTTGGCTAAGAATAAGAAGCCAATAAAAATAAAAGTTCTTTAAACAAATCAATAGGAGTGGACCACGTCAGTTGTCCTTT'}\n"
     ]
    }
   ],
   "source": [
    "lines = s.split(\"\\n\")\n",
    "headers = []\n",
    "sequences = []\n",
    "for l in lines:\n",
    "    if l.startswith(\">\"):\n",
    "        headers.append(l)\n",
    "    else:\n",
    "        sequences.append(l)\n",
    "data = dict(zip(headers, sequences))\n",
    "print(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [],
   "name": "Lesson 2: Exercises",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}