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tap1012
Commit f437f599 authored by Mario Chirinos Colunga's avatar Mario Chirinos Colunga 💬
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numpy

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Showing with 269 additions and 8 deletions
05-NumPy&Pandas.ipynb
View file @ f437f599
......@@ -850,27 +850,28 @@
},
{
"cell_type": "code",
"execution_count": 45,
"execution_count": 51,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"a -1.144505\n",
"b 0.483479\n",
"c -0.633879\n",
"d -1.152392\n",
"e 1.992141\n",
"a 0.994272\n",
"b 0.530519\n",
"c 1.162452\n",
"d -0.981436\n",
"e -1.283798\n",
"dtype: float64"
]
},
"execution_count": 45,
"execution_count": 51,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pd.Series(np.random.randn(5), index=['a', 'b', 'c', 'd', 'e'])"
"s = pd.Series(np.random.randn(5), index=['a', 'b', 'c', 'd', 'e'])\n",
"s"
]
},
{
......@@ -947,6 +948,266 @@
"pd.Series(d, index=['b', 'c', 'd', 'a'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Las Series son compatibles con *numpy.array* y *dict*"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.9942721192063438"
]
},
"execution_count": 53,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"s[0]"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"a 0.994272\n",
"b 0.530519\n",
"c 1.162452\n",
"dtype: float64"
]
},
"execution_count": 54,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"s[:3]"
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"a 0.994272\n",
"b 0.530519\n",
"c 1.162452\n",
"dtype: float64"
]
},
"execution_count": 55,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"s[s>s.mean()]"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"a 1.988544\n",
"b 1.061037\n",
"c 2.324904\n",
"d -1.962872\n",
"e -2.567597\n",
"dtype: float64"
]
},
"execution_count": 56,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"s*2"
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"a True\n",
"b False\n",
"c True\n",
"d False\n",
"e False\n",
"dtype: bool"
]
},
"execution_count": 57,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"s>s.median()"
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.9942721192063438"
]
},
"execution_count": 58,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"s[\"a\"]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Alieneacion Automatica"
]
},
{
"cell_type": "code",
"execution_count": 59,
"metadata": {},
"outputs": [],
"source": [
"a = np.array(range(10))\n",
"s = pd.Series(a)"
]
},
{
"cell_type": "code",
"execution_count": 60,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"
]
},
"execution_count": 60,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"a"
]
},
{
"cell_type": "code",
"execution_count": 62,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0 0\n",
"1 1\n",
"2 2\n",
"3 3\n",
"4 4\n",
"5 5\n",
"6 6\n",
"7 7\n",
"8 8\n",
"9 9\n",
"dtype: int64"
]
},
"execution_count": 62,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"s"
]
},
{
"cell_type": "code",
"execution_count": 75,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([ 4, 6, 8, 10, 12, 14])"
]
},
"execution_count": 75,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"(a[:6]+a[4:])"
]
},
{
"cell_type": "code",
"execution_count": 76,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0 NaN\n",
"1 NaN\n",
"2 NaN\n",
"3 NaN\n",
"4 8.0\n",
"5 10.0\n",
"6 NaN\n",
"7 NaN\n",
"8 NaN\n",
"9 NaN\n",
"dtype: float64"
]
},
"execution_count": 76,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"(s[:6]+s[4:])"
]
},
{
"cell_type": "code",
"execution_count": null,
......
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