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beppe.vanrolleghem
2019-03-15 14:51:38 +01:00
parent 209fee95e3
commit 24cd306c29
2 changed files with 284 additions and 9 deletions
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98
4/Labo4.ipynb
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@@ -35,10 +35,57 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 60,
"metadata": {},
"outputs": [],
"source": []
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r', 's', 't', 'u', 'v', 'w', 'x', 'y', 'z']\n",
"[ 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24\n",
" 25 26]\n",
"{'a': 1, 'b': 2, 'c': 3, 'd': 4, 'e': 5, 'f': 6, 'g': 7, 'h': 8, 'i': 9, 'j': 10, 'k': 11, 'l': 12, 'm': 13, 'n': 14, 'o': 15, 'p': 16, 'q': 17, 'r': 18, 's': 19, 't': 20, 'u': 21, 'v': 22, 'w': 23, 'x': 24, 'y': 25, 'z': 26}\n",
"a,e,i,o,u\n",
"[]\n",
"[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]\n",
"[ 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48\n",
" 50 52]\n"
]
}
],
"source": [
"import numpy as np\n",
"\n",
"alfabet = list(\"abcdefghijklmnopqrstuvwxyz\")\n",
"print(alfabet)\n",
"f = np.array(range(1,27))\n",
"print(f)\n",
"dic = {}\n",
"for i in alfabet:\n",
" dic[alfabet.index(i)+1] = i\n",
"\n",
"dic = dict(zip(alfabet,f)) # korte manier zelfde shit\n",
"print(dic)\n",
"\n",
"\n",
"print(\"{},{},{},{},{}\".format(alfabet[0],alfabet[4],alfabet[8],alfabet[14],alfabet[20]))\n",
"\n",
"\n",
"print([a for a in alfabet if a in dic.values()])\n",
"\n",
"\n",
"print([a for a in f if a not in dic.keys()])\n",
"\n",
"\n",
"\n",
"print(f * 2)\n",
"\n",
"\n",
"\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
@@ -56,10 +103,31 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 59,
"metadata": {},
"outputs": [],
"source": []
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" gewicht\n",
"fruit \n",
"apple 0.650914\n",
"banana 0.241583\n",
"kiwi 0.493209\n",
"lemon 0.564981\n"
]
}
],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"s1 = pd.Series(np.random.choice(['apple','lemon', 'banana','kiwi'], 10))\n",
"s2 = pd.Series(np.random.rand(10))\n",
"f = pd.concat([s1, s2], keys=['fruit','gewicht'], axis=1)\n",
"print(f.groupby(['fruit']).mean())\n",
"\n"
]
},
{
"cell_type": "markdown",
@@ -70,9 +138,21 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 34,
"metadata": {},
"outputs": [],
"outputs": [
{
"ename": "NameError",
"evalue": "name 'ser2' is not defined",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m<ipython-input-34-97a3c6f78260>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mdf1\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconcat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mser2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mser3\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 2\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdf1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 3\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 5\u001b[0m \u001b[0mdf2\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mDataFrame\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m{\u001b[0m\u001b[1;34m'col1'\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mser1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'col2'\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mser2\u001b[0m\u001b[1;33m}\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mNameError\u001b[0m: name 'ser2' is not defined"
]
}
],
"source": [
"df1 = pd.concat([ser2, ser3], axis=0)\n",
"print(df1)\n",
@@ -187,7 +267,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.4"
"version": "3.6.5"
}
},
"nbformat": 4,