diff --git a/aengelvi.ipynb b/aengelvi.ipynb new file mode 100644 index 0000000..7731e69 --- /dev/null +++ b/aengelvi.ipynb @@ -0,0 +1,296 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "IPython version: %6.6s 7.17.0\n" + ] + } + ], + "source": [ + "import IPython\n", + "import json\n", + "# Numpy is a library for working with Arrays\n", + "import numpy as np\n", + "# SciPy implements many different numerical algorithms\n", + "import scipy as sp\n", + "# Pandas is good with data tables\n", + "import pandas as pd\n", + "# Module for plotting\n", + "import matplotlib\n", + "#BeautifulSoup parses HTML documents (once you get them via requests)\n", + "import bs4\n", + "# Nltk helps with some natural language tasks, like stemming\n", + "import nltk\n", + "# Bson is a binary format of json to be stored in databases\n", + "import bson\n", + "# Mongo is one of common nosql databases \n", + "# it stores/searches json documents natively\n", + "import pymongo\n", + "print (\"IPython version: %6.6s\", IPython.__version__)" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Make a 2 row x 3 column array of random numbers\n", + "[[0.88356521 0.45521337 0.21061482]\n", + " [0.61092799 0.05047963 0.10748752]]\n", + "Add 5 to every element\n", + "[[5.88356521 5.45521337 5.21061482]\n", + " [5.61092799 5.05047963 5.10748752]]\n", + "Get the first row\n", + "[5.88356521 5.45521337 5.21061482]\n" + ] + } + ], + "source": [ + "#Here is what numpy can do\\n\",\n", + "print (\"Make a 2 row x 3 column array of random numbers\")\n", + "x = np.random.random((2, 3))\n", + "print (x)\n", + "\n", + "#array operation (as in R)\n", + "print (\"Add 5 to every element\")\n", + "x = x + 5\n", + "print (x)\n", + "\n", + "# get a slice (first row) (as in R)\n", + "print (\"Get the first row\")\n", + "print (x[0, :])" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# IPython is quite modern: just press at the end of the unfinished statement to see the documentation\n", + "# on possible completions.\n", + "# In the code cell below, type x., to find built-in operations for x\n", + "x.any" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "%matplotlib inline \n", + "import matplotlib.pyplot as plt\n", + "heads = np.random.binomial(500, .5, size=500)\n", + "histogram = plt.hist(heads, bins=10)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "collapsed": true + }, + "source": [ + "# Task 1\n", + "## write a program to produce Fibonacci numbers up to 1000000" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "How many numbers?30\n", + "0\n", + "1\n", + "1\n", + "2\n", + "3\n", + "5\n", + "8\n", + "13\n", + "21\n", + "34\n", + "55\n", + "89\n", + "144\n", + "233\n", + "377\n", + "610\n", + "987\n", + "1597\n", + "2584\n", + "4181\n", + "6765\n", + "10946\n", + "17711\n", + "28657\n", + "46368\n", + "75025\n", + "121393\n", + "196418\n", + "317811\n", + "514229\n" + ] + } + ], + "source": [ + "def fibonacci(num):\n", + " n1 = 0\n", + " n2 = 1\n", + " fib = 0\n", + " for i in range(num):\n", + " print(fib)\n", + " n1 = n2;\n", + " n2 = fib;\n", + " fib = n1 + n2;\n", + "\n", + "\n", + "num = int(input('How many numbers?'))\n", + "fibonacci(num)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Task 2\n", + "## write a program to simulate 1000 tosses of a fair coin (use np.random.binomial)\n", + "## Calculate the mean and standard deviation of that sample" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.472\n", + "0.4992153843783262\n" + ] + } + ], + "source": [ + "import numpy as np\n", + "np.random.seed(34)\n", + "s= np.random.binomial(1,.5,1000)\n", + "print(np.average(s))\n", + "print(np.std(s))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Task 3\n", + "## Produce a scatterplot of y = 0.5*x+e where x has gaussian (0, 5) and e has gaussian (0, 1) distributions \n", + "### use numpy.random.normal to generate gaussian distribution" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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