Mercurial > repos > jay > gaiac_windrose_plot

annotate gaiac_pm_data_pulling/Untitled.ipynb @ 3:eafdbea68dbf draft default tip

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planemo upload for repository https://github.com/jaidevjoshi83/gaiac commit e9587f93346c7b55e1be00bad5844bf2db3ed03d-dirty
author jay
date Thu, 10 Jul 2025 19:39:38 +0000
parents
children
Ignore whitespace changes - Everywhere: Within whitespace: At end of lines:
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3
eafdbea68dbf planemo upload for repository https://github.com/jaidevjoshi83/gaiac commit e9587f93346c7b55e1be00bad5844bf2db3ed03d-dirty
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1 {
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2 "cells": [
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3 {
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4 "cell_type": "code",
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5 "execution_count": 1,
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6 "id": "4707b84c-b2f9-4740-bd62-a159e2c7e123",
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7 "metadata": {},
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8 "outputs": [],
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9 "source": [
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10 "import pandas as pd"
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11 ]
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12 },
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13 {
eafdbea68dbf planemo upload for repository https://github.com/jaidevjoshi83/gaiac commit e9587f93346c7b55e1be00bad5844bf2db3ed03d-dirty
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14 "cell_type": "code",
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15 "execution_count": 6,
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16 "id": "c9870ed9-90cc-427b-b811-bd94c6b867c9",
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17 "metadata": {},
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18 "outputs": [],
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19 "source": [
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20 "a = [1,2,4,6]\n",
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21 "b = [4,5,6,7]\n",
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22 "\n",
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23 "df = pd.DataFrame([a,b])"
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24 ]
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25 },
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26 {
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27 "cell_type": "code",
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28 "execution_count": 8,
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29 "id": "502e66d5-022d-47af-a299-a918f0ebd887",
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30 "metadata": {},
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31 "outputs": [
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32 {
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33 "data": {
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34 "text/html": [
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35 "<div>\n",
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36 "<style scoped>\n",
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37 " .dataframe tbody tr th:only-of-type {\n",
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38 " vertical-align: middle;\n",
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39 " }\n",
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40 "\n",
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41 " .dataframe tbody tr th {\n",
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42 " vertical-align: top;\n",
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43 " }\n",
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44 "\n",
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45 " .dataframe thead th {\n",
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46 " text-align: right;\n",
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47 " }\n",
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48 "</style>\n",
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49 "<table border=\"1\" class=\"dataframe\">\n",
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50 " <thead>\n",
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51 " <tr style=\"text-align: right;\">\n",
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52 " <th></th>\n",
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53 " <th>0</th>\n",
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54 " <th>1</th>\n",
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55 " </tr>\n",
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56 " </thead>\n",
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57 " <tbody>\n",
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58 " <tr>\n",
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59 " <th>0</th>\n",
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60 " <td>1</td>\n",
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61 " <td>4</td>\n",
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62 " </tr>\n",
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63 " <tr>\n",
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64 " <th>1</th>\n",
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65 " <td>2</td>\n",
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66 " <td>5</td>\n",
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67 " </tr>\n",
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68 " <tr>\n",
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69 " <th>2</th>\n",
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70 " <td>4</td>\n",
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71 " <td>6</td>\n",
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72 " </tr>\n",
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73 " <tr>\n",
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74 " <th>3</th>\n",
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75 " <td>6</td>\n",
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76 " <td>7</td>\n",
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77 " </tr>\n",
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78 " </tbody>\n",
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79 "</table>\n",
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80 "</div>"
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81 ],
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82 "text/plain": [
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83 " 0 1\n",
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84 "0 1 4\n",
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85 "1 2 5\n",
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86 "2 4 6\n",
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87 "3 6 7"
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88 ]
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89 },
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90 "execution_count": 8,
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91 "metadata": {},
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92 "output_type": "execute_result"
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93 }
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94 ],
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95 "source": [
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96 "df.T"
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97 ]
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98 },
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99 {
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100 "cell_type": "code",
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101 "execution_count": null,
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102 "id": "f39e7015-3e8b-4123-8ec7-c05547ee28b1",
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103 "metadata": {},
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104 "outputs": [],
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105 "source": []
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106 }
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107 ],
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108 "metadata": {
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109 "kernelspec": {
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110 "display_name": "Python 3 (ipykernel)",
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111 "language": "python",
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112 "name": "python3"
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113 },
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114 "language_info": {
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115 "codemirror_mode": {
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116 "name": "ipython",
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117 "version": 3
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118 },
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119 "file_extension": ".py",
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120 "mimetype": "text/x-python",
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121 "name": "python",
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122 "nbconvert_exporter": "python",
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123 "pygments_lexer": "ipython3",
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124 "version": "3.10.14"
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125 },
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126 "widgets": {
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127 "application/vnd.jupyter.widget-state+json": {
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128 "state": {},
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129 "version_major": 2,
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130 "version_minor": 0
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131 }
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132 }
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133 },
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134 "nbformat": 4,
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135 "nbformat_minor": 5
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136 }