{ "nbformat": 4, "nbformat_minor": 0, "metadata": { "colab": { "name": "python-novice-notebook.ipynb", "provenance": [] }, "kernelspec": { "name": "python3", "display_name": "Python 3" } }, "cells": [ { "cell_type": "markdown", "metadata": { "id": "LqLqhxd58VvR" }, "source": [ "# Python for novice : recommended for beginners before using jarvis-tools, designed for educational purposes only" ] }, { "cell_type": "markdown", "metadata": { "id": "l8a2A41CBGUZ" }, "source": [ "## Contents:\n", "- Hello world, python 2 vs python 3\n", "- Variable types\n", "- Mathematical operations\n", "- Arrays, for-loops, if-statement\n", "- Importing and using python libraries, numpy example\n", "- Python dictionaries, JSON files\n", "- Visualizing data\n", "- Writing simple modules/functions, docstrings\n", "- Pandas library" ] }, { "cell_type": "markdown", "metadata": { "id": "9Y6SAXk08Iff" }, "source": [ "###Hello world! Note that parenthesis is needed for python 3" ] }, { "cell_type": "code", "metadata": { "id": "8_JHiq4q8STo", "outputId": "ee8f4d04-4289-404f-c68b-2120ef4e08df", "colab": { "base_uri": "https://localhost:8080/", "height": 34 } }, "source": [ "print ('Hello world')" ], "execution_count": null, "outputs": [ { "output_type": "stream", "text": [ "Hello world\n" ], "name": "stdout" } ] }, { "cell_type": "markdown", "metadata": { "id": "ixswQv_rBWEN" }, "source": [ "### Common variable types: digits (int), fractional numbers (float), characters (str)" ] }, { "cell_type": "code", "metadata": { "id": "mhI3kAO7BZn-", "outputId": "5e301bcc-f967-426b-f87f-2d7158ccceaa", "colab": { "base_uri": "https://localhost:8080/", "height": 68 } }, "source": [ "a = 2\n", "b = 1.5\n", "c = 'Coding'\n", "print (type(a))\n", "print (type(b))\n", "print (type(c))" ], "execution_count": null, "outputs": [ { "output_type": "stream", "text": [ "\n", "\n", "\n" ], "name": "stdout" } ] }, { "cell_type": "markdown", "metadata": { "id": "OTAyWELE8eIp" }, "source": [ "### Add/substract/multiply/divide two variables" ] }, { "cell_type": "code", "metadata": { "id": "OntW110l8UgT", "outputId": "5e3d9b38-1db2-4994-f263-99b645678c9b", "colab": { "base_uri": "https://localhost:8080/", "height": 85 } }, "source": [ "a = 2\n", "b = 4\n", "print (a+b)\n", "print (a-b)\n", "print (a*b)\n", "print (a/b)" ], "execution_count": null, "outputs": [ { "output_type": "stream", "text": [ "6\n", "-2\n", "8\n", "0.5\n" ], "name": "stdout" } ] }, { "cell_type": "markdown", "metadata": { "id": "j-ZjpkGUna5G" }, "source": [ "### Exercise 1: Round off (1/3) to 3 digits\n", "\n" ] }, { "cell_type": "code", "metadata": { "id": "YiZm68PXnneT", "outputId": "8e7932b2-8191-4dc7-87e2-aed7cfdf691e", "colab": { "base_uri": "https://localhost:8080/", "height": 34 } }, "source": [ "\"\"\"\n", "print (round(1/3,__))\n", "\"\"\"\n" ], "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "'\\nprint (round(1/3,__))\\n'" ] }, "metadata": { "tags": [] }, "execution_count": 17 } ] }, { "cell_type": "markdown", "metadata": { "id": "hxnXQNha9FkY" }, "source": [ "### Does addition work with strings?\n", "\n", "\n" ] }, { "cell_type": "code", "metadata": { "id": "YigiyUFX8_h3", "outputId": "c590ecf8-3fc0-498e-8c81-110958cd638b", "colab": { "base_uri": "https://localhost:8080/", "height": 34 } }, "source": [ "a = 'My'\n", "b = 'Awesome'\n", "c = 'Code'\n", "\n", "print (a+' '+b+' '+c)\n" ], "execution_count": null, "outputs": [ { "output_type": "stream", "text": [ "My Awesome Code\n" ], "name": "stdout" } ] }, { "cell_type": "markdown", "metadata": { "id": "2fCJLhXPn2Ch" }, "source": [ "### Exercise 2: replace character in a string: 'e with 'ing' i.e. make 'Code' to 'Coding' using 'replace' function\n", "\n", "\n" ] }, { "cell_type": "code", "metadata": { "id": "3ZDDBkGFn46z", "outputId": "f75b0bc3-8a13-4e41-8ef0-067c6b68211a", "colab": { "base_uri": "https://localhost:8080/", "height": 34 } }, "source": [ "\"\"\"\n", "'Code'.replace('e',__)\n", "\"\"\"" ], "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "\"\\n'Code'.replace('e',__)\\n\"" ] }, "metadata": { "tags": [] }, "execution_count": 19 } ] }, { "cell_type": "markdown", "metadata": { "id": "06LHAFt0AwGw" }, "source": [ " ### Strings cannot be added to float/int" ] }, { "cell_type": "code", "metadata": { "id": "cx7ilJsS9Pmn" }, "source": [ "a = 'Code'\n", "b = 2\n", "## print (a+b)" ], "execution_count": null, "outputs": [] }, { "cell_type": "markdown", "metadata": { "id": "dqpUpFJ8BQ92" }, "source": [ "### but string casting is possible." ] }, { "cell_type": "code", "metadata": { "id": "qlmAVTkCBC3S", "outputId": "b5557647-2109-41ef-d996-0cc5ea10f06e", "colab": { "base_uri": "https://localhost:8080/", "height": 34 } }, "source": [ "a = 'Code'\n", "b = str(2)\n", "print (a+' '+b)" ], "execution_count": null, "outputs": [ { "output_type": "stream", "text": [ "Code 2\n" ], "name": "stdout" } ] }, { "cell_type": "markdown", "metadata": { "id": "L1h13Cwe9kmh" }, "source": [ "### Python array and \"for\" loops" ] }, { "cell_type": "code", "metadata": { "id": "MPdF-YIY9hG-", "outputId": "7825a6c6-7fb2-4ed2-daae-e7d31c408c41", "colab": { "base_uri": "https://localhost:8080/", "height": 102 } }, "source": [ "a = [1,2,3,4,5] # example array\n", "for i in a: # i is a temporary variable\n", " print (i, i*2) # printing the array element, array element multiplied by 2 simultaneously" ], "execution_count": null, "outputs": [ { "output_type": "stream", "text": [ "1 2\n", "2 4\n", "3 6\n", "4 8\n", "5 10\n" ], "name": "stdout" } ] }, { "cell_type": "markdown", "metadata": { "id": "59UoTCY6CvA6" }, "source": [ "### If statement : generally used when applying conditions for filtering options: example print even numbers only" ] }, { "cell_type": "code", "metadata": { "id": "KZua636oC9SZ", "outputId": "7f838cab-26a8-42f6-fb8d-41bbf6f6e6e9", "colab": { "base_uri": "https://localhost:8080/", "height": 51 } }, "source": [ "a = [1,2,3,4,5]\n", "for i in a:\n", " if i%2 == 0: # print even number only, % gets remainder after divison\n", " print (i)" ], "execution_count": null, "outputs": [ { "output_type": "stream", "text": [ "2\n", "4\n" ], "name": "stdout" } ] }, { "cell_type": "markdown", "metadata": { "id": "lGxm8GaS97XD" }, "source": [ "### Numpy arrays, first need to import numpy and give it a shorter name say, 'np'. There are numerous array operations, such as average, maximum, minimum etc that can be done easily done using numpy. You can find details at https://numpy.org/" ] }, { "cell_type": "code", "metadata": { "id": "Qlug_wxg9zhR", "outputId": "a9607313-4d52-429a-e472-7e022c8ce3f2", "colab": { "base_uri": "https://localhost:8080/", "height": 68 } }, "source": [ "import numpy as np # importing numpy\n", "a = np.array([1,2,3,4,5])\n", "print ('Avegage', np.mean(a))\n", "print ('Maximum',np.max(a))\n", "print ('Minimum',np.min(a))" ], "execution_count": null, "outputs": [ { "output_type": "stream", "text": [ "Avegage 3.0\n", "Maximum 5\n", "Minimum 1\n" ], "name": "stdout" } ] }, { "cell_type": "markdown", "metadata": { "id": "N5RrwBmQ-fcY" }, "source": [ "### Python dictionaries and key-value pairs: generally used for storing data and making databases\n", "### \"key : value\" format. Key is generally a variable (string mostly), value can be a single variable or array or another dictionary " ] }, { "cell_type": "code", "metadata": { "id": "foMd5Dh--LDv" }, "source": [ "a = {'marvel_movies':['iron_man','spider-man','captain-marvel','thor'],\n", " 'other_fav_movies':['the godfather','the lord of the rings']}\n" ], "execution_count": null, "outputs": [] }, { "cell_type": "code", "metadata": { "id": "ZCSeVlE-El5d", "outputId": "aea9199d-c901-4adc-ea1f-f258c3f07b84", "colab": { "base_uri": "https://localhost:8080/", "height": 34 } }, "source": [ "a.keys()" ], "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "dict_keys(['marvel_movies', 'other_fav_movies'])" ] }, "metadata": { "tags": [] }, "execution_count": 11 } ] }, { "cell_type": "code", "metadata": { "id": "KzEsJfRkEqW4", "outputId": "91e08975-f82a-4aa4-9459-ff55d55a739e", "colab": { "base_uri": "https://localhost:8080/", "height": 34 } }, "source": [ "a.values()" ], "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "dict_values([['iron_man', 'spider-man', 'captain-marvel', 'thor'], ['the godfather', 'the lord of the rings']])" ] }, "metadata": { "tags": [] }, "execution_count": 12 } ] }, { "cell_type": "markdown", "metadata": { "id": "xtGLIJXJALhf" }, "source": [ "### We can query the disctionary based on the key" ] }, { "cell_type": "code", "metadata": { "id": "VMfzNZYtAEP3", "outputId": "3b4e038e-b2e8-45e5-96d9-4eee228edaad", "colab": { "base_uri": "https://localhost:8080/", "height": 34 } }, "source": [ "a['other_fav_movies']" ], "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "['the godfather', 'the lord of the rings']" ] }, "metadata": { "tags": [] }, "execution_count": 13 } ] }, { "cell_type": "markdown", "metadata": { "id": "Yc2TVnP4p2It" }, "source": [ "###Exercise 3: Update the dictionary with a new key-value pairt:\n", "{'thrillers':['silecence_of_the_lambs','bourne_identity','inception']}" ] }, { "cell_type": "code", "metadata": { "id": "8D9Xp0XarQ6F", "outputId": "175c0323-2d56-4fbc-857a-291c4e591d1d", "colab": { "base_uri": "https://localhost:8080/", "height": 34 } }, "source": [ "\"\"\"\n", "tmp = {'thrillers':['silecence_of_the_lambs','bourne_identity','inception']}\n", "a.update(__)\n", "print (a)\n", "\"\"\"" ], "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "\"\\ntmp = {'thrillers':['silecence_of_the_lambs','bourne_identity','inception']}\\na.update(__)\\nprint (a)\\n\"" ] }, "metadata": { "tags": [] }, "execution_count": 22 } ] }, { "cell_type": "markdown", "metadata": { "id": "ztX_qdwcIrB8" }, "source": [ "## Read-write a JSON file" ] }, { "cell_type": "markdown", "metadata": { "id": "KbY16aDzFnVK" }, "source": [ "### Saving data in a JSON file" ] }, { "cell_type": "code", "metadata": { "id": "1MswAS17Fmyi" }, "source": [ "import json\n", "f=open('test.json','w')\n", "f.write(json.dumps(a))\n", "f.close()" ], "execution_count": null, "outputs": [] }, { "cell_type": "markdown", "metadata": { "id": "gh9b1OVjG_jv" }, "source": [ "### Reading a JSON file" ] }, { "cell_type": "code", "metadata": { "id": "olnl4P8ZARfj" }, "source": [ "import json\n", "f=open('test.json','r')\n", "data = json.load(f)\n", "f.close()" ], "execution_count": null, "outputs": [] }, { "cell_type": "code", "metadata": { "id": "dAAUwoqHG9Gz", "outputId": "6610a3b4-3756-4da2-993c-74146a5ef0ed", "colab": { "base_uri": "https://localhost:8080/", "height": 51 } }, "source": [ "data" ], "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "{'marvel_movies': ['iron_man', 'spider-man', 'captain-marvel', 'thor'],\n", " 'other_fav_movies': ['the godfather', 'the lord of the rings']}" ] }, "metadata": { "tags": [] }, "execution_count": 16 } ] }, { "cell_type": "markdown", "metadata": { "id": "u679bBT-Ixul" }, "source": [ "# Plotting data using matplotlib library in python" ] }, { "cell_type": "code", "metadata": { "id": "MHKKSDohIxQ0", "outputId": "8041d1c1-320e-43b7-92e9-2fec181fadd0", "colab": { "base_uri": "https://localhost:8080/", "height": 300 } }, "source": [ "x = [1,2,3,4,5]\n", "y = [2,4,6,8,10]\n", "import matplotlib\n", "# % is a magic command for notebooks\n", "% matplotlib inline\n", "# pyplot is a long name so let's call it plt using 'as'\n", "import matplotlib.pyplot as plt\n", "plt.plot(x,y,'o') #o is a marker, you can use 's', '^ etc.\n", "plt.xlabel('X')\n", "plt.ylabel('Y')" ], "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "Text(0, 0.5, 'Y')" ] }, "metadata": { "tags": [] }, "execution_count": 6 }, { "output_type": "display_data", "data": { "image/png": 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" ] }, "metadata": { "tags": [] } } ] }, { "cell_type": "markdown", "metadata": { "id": "Hb75zoiLPjDX" }, "source": [ "### Python-functions: \"def\"" ] }, { "cell_type": "code", "metadata": { "id": "V3bKowQPPnYj" }, "source": [ "def add_two_numbers(a='',b=''):\n", " \"\"\"\n", " Args:\n", " a,b: input value, integer/float\n", " Returns:\n", " sum: sum of a and b , integer/float\n", " \"\"\"\n", " sum = a+b\n", " return sum" ], "execution_count": null, "outputs": [] }, { "cell_type": "code", "metadata": { "id": "OLbS0dwaPzRt", "outputId": "0ecaaae3-0d81-4e1c-e4af-cb76851b3fb2", "colab": { "base_uri": "https://localhost:8080/", "height": 34 } }, "source": [ "add_two_numbers(a=2,b=3)" ], "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "5" ] }, "metadata": { "tags": [] }, "execution_count": 31 } ] }, { "cell_type": "markdown", "metadata": { "id": "ItsSpBuR2BLO" }, "source": [ "###Pandas library" ] }, { "cell_type": "code", "metadata": { "id": "UAEB8VdyMwWk", "outputId": "0c1fa1cc-4d5c-44a8-bea4-a1dbfd6ffa30", "colab": { "base_uri": "https://localhost:8080/", "height": 204 } }, "source": [ "import pandas as pd\n", "data = pd.read_csv('https://vincentarelbundock.github.io/Rdatasets/csv/datasets/OrchardSprays.csv', index_col=0)\n", "data.head()" ], "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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decreaserowposcolpostreatment
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3831B
46941H
59251G
\n", "
" ], "text/plain": [ " decrease rowpos colpos treatment\n", "1 57 1 1 D\n", "2 95 2 1 E\n", "3 8 3 1 B\n", "4 69 4 1 H\n", "5 92 5 1 G" ] }, "metadata": { "tags": [] }, "execution_count": 7 } ] }, { "cell_type": "code", "metadata": { "id": "dgRUr0IZ2JSB", "outputId": "9e9356ba-eae3-48d6-f475-477da81f70b0", "colab": { "base_uri": "https://localhost:8080/", "height": 297 } }, "source": [ "data.describe()" ], "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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decreaserowposcolpos
count64.00000064.00000064.000000
mean45.4218754.5000004.500000
std35.5745612.3094012.309401
min2.0000001.0000001.000000
25%12.7500002.7500002.750000
50%41.0000004.5000004.500000
75%72.0000006.2500006.250000
max130.0000008.0000008.000000
\n", "
" ], "text/plain": [ " decrease rowpos colpos\n", "count 64.000000 64.000000 64.000000\n", "mean 45.421875 4.500000 4.500000\n", "std 35.574561 2.309401 2.309401\n", "min 2.000000 1.000000 1.000000\n", "25% 12.750000 2.750000 2.750000\n", "50% 41.000000 4.500000 4.500000\n", "75% 72.000000 6.250000 6.250000\n", "max 130.000000 8.000000 8.000000" ] }, "metadata": { "tags": [] }, "execution_count": 8 } ] }, { "cell_type": "code", "metadata": { "id": "-RGUdPEC3e45", "outputId": "b20a42ae-bd2e-465f-b124-096e820f4424", "colab": { "base_uri": "https://localhost:8080/", "height": 34 } }, "source": [ "data.columns" ], "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "Index(['decrease', 'rowpos', 'colpos', 'treatment'], dtype='object')" ] }, "metadata": { "tags": [] }, "execution_count": 9 } ] }, { "cell_type": "markdown", "metadata": { "id": "PK5GpY7HpuDD" }, "source": [ "### Plotting data in pandas" ] }, { "cell_type": "code", "metadata": { "id": "KORTbJQe3l6z", "outputId": "910f33cb-bb6a-4a3d-e7e9-f02a80d51c95", "colab": { "base_uri": "https://localhost:8080/", "height": 300 } }, "source": [ "data.plot(kind='scatter',x='rowpos',y='decrease',color='red')" ], "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "" ] }, "metadata": { "tags": [] }, "execution_count": 23 }, { "output_type": "display_data", "data": { "image/png": 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iW0n19vzHXyG7id8XET+U9DivXOL8uHxV0xfJkgtkq51+StJvkSWCq/LzH5O0\nPP+ce4BvFvX3MpuJV3M1K1C+IdFgRDxZdixms+UmJjMza8k1CDMza8k1CDMza8kJwszMWnKCMDOz\nlpwgzMysJScIMzNryQnCzMxa+icfu2RS4jA8LwAAAABJRU5ErkJggg==\n", "text/plain": [ "
" ] }, "metadata": { "tags": [] } } ] }, { "cell_type": "markdown", "metadata": { "id": "0hstGp8Yssep" }, "source": [ "### Exercise 4: Plot descrese vs colpos" ] }, { "cell_type": "code", "metadata": { "id": "ZjD9W7_Jppb2", "outputId": "cb306c38-a0c7-4cbe-9c02-4611b649395a", "colab": { "base_uri": "https://localhost:8080/", "height": 34 } }, "source": [ "\"\"\"\n", "data.plot(kind='scatter',x=__,y='decrease',color='red')\n", "\"\"\"" ], "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "\"\\ndata.plot(kind='scatter',x=__,y='decrease',color='red')\\n\"" ] }, "metadata": { "tags": [] }, "execution_count": 25 } ] }, { "cell_type": "code", "metadata": { "id": "IH04YdpOt3yz" }, "source": [], "execution_count": null, "outputs": [] } ] }