Merge pull request #1 from masterdatascience-UIMP-UC/master

06, 07 - Numpy y Pandas
joseney19 · Oct 11, 2018 · 666fc2f · 666fc2f
2 parents bf543c0 + 64c5838
commit 666fc2f
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Showing 7 changed files with 1,989 additions and 13 deletions.
diff --git a/03.2-ejercicio.ipynb b/03.2-ejercicio.ipynb
@@ -12,7 +12,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -102,7 +102,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -120,11 +120,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
-    "def words_to_frequencies(lyrics)\n",
+    "def words_to_frequencies(lyrics):\n",
     "    \"\"\"\n",
     "    Convert words into frequencies. Return a dictionarky whose keys are the\n",
     "    words with the frequency as the value\n",
@@ -145,38 +145,39 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
-    "def most_common_words(frequencies)\n",
+    "def most_common_words(frequencies):\n",
     "    \"\"\"\n",
     "    Return a tuple containing:\n",
     "    * The number of occurences of a word in the first tuple element\n",
     "    * A list containing the words with that frequency\n",
     "    \"\"\"\n",
     "    values = frequencies.values()\n",
-    "    max = max(values)\n",
+    "    best = max(values)\n",
     "    \n",
     "    words = []\n",
     "    for word, score in frequencies.items():\n",
-    "        if score == max(value):\n",
+    "        if score == best:\n",
     "            words.append(word)\n",
-    "    return (max, words)"
+    "    return (best, words)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
-    "def get_more_often_user_words(threshold=10, frequencies):\n",
+    "def get_more_often_user_words(frequencies, threshold=10):\n",
     "    \"\"\"\n",
     "    Return a list of the words that are used more often, above\n",
     "    the *optional* threshold. If no threshold is passed, use 10.\n",
     "    \"\"\"\n",
     "    \n",
+    "    result = []\n",
     "    while True:\n",
     "        score = most_common_words(frequencies)\n",
     "        if score[0] < threshold:\n",
@@ -190,9 +191,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Palabras más frecuentes con más de 10 apariciones.\n",
+      "[(22, ['que']), (15, ['tu', 'a']), (12, ['quiero']), (10, ['despacito', 'sube'])]\n",
+      "\n",
+      "\n",
+      "Palabras más frecuentes con más de 10 apariciones.\n",
+      "[(9, ['y', 'de', 'favoritos']), (8, ['te', 'tus', 'pasito', 'poquito']), (6, ['oh', 'el', 'mi']), (5, ['no', 'un', 'yo', 'vamos'])]\n"
+     ]
+    }
+   ],
    "source": [
     "words_clean = split_into_words(lyrics)\n",
     "\n",
@@ -204,6 +218,20 @@
     "print(\"Palabras más frecuentes con más de 10 apariciones.\")\n",
     "print(get_more_often_user_words(freqs, threshold=5))"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {