Skip to content

Instantly share code, notes, and snippets.

@themendozaline

themendozaline/PY0101EN-5.1_notebook_quizz_numpy1d.ipynb

Created July 2, 2019 21:15
Show Gist options

  • Select an option

    Learn more about clone URLs
  • Save themendozaline/94b95d0bde9cf09f5e426400a04787ef to your computer and use it in GitHub Desktop.

Select an option

Learn more about clone URLs
Save themendozaline/94b95d0bde9cf09f5e426400a04787ef to your computer and use it in GitHub Desktop.
Download ZIP
Created on Cognitive Class Labs
Display the source blob
Display the rendered blob
Raw
PY0101EN-5.1_notebook_quizz_numpy1d.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<h3> Get to Know a numpy Array </h3>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"cast the following list to a numpy array:"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"a=[1,2,3,4,5]\n",
"\n",
"A=np.array(a)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"1) type using the function type "
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([1, 2, 3, 4, 5])"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"A"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"2) the shape of the array "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"3) the type of data in the array "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"4) find the mean of the array "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<h3> Creating and Plotting Functions </h3>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"1) create the following functions using the numpy array <code> x </code>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$$y=sin(x)+2$$"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"x=np.linspace(0,2*np.pi,100)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"2) plot the function"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"%matplotlib inline \n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<hr>\n",
"<small>Copyright &copy; 2018 IBM Cognitive Class. This notebook and its source code are released under the terms of the [MIT License](https://cognitiveclass.ai/mit-license/).</small>"
]
}
],
"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": "3.6.8"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment