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ynrng/discord.ipynb

Last active May 30, 2024 06:32
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Draw a stacked bar chart of predicted discord gender. [Require data from Discord](https://support.discord.com/hc/en-us/articles/360004027692-Requesting-a-Copy-of-your-Data) and find json in /activity/analytics/events-*json.
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discord.ipynb
{"cells":[{"cell_type":"markdown","metadata":{},"source":["[Gist link](https://gist.github.com/ynrng/7c7db8cbd10d1ebd809d5d680873ce65).\n","\n","Draw a stacked bar chart of predicted discord gender. [Require data from Discord](https://support.discord.com/hc/en-us/articles/360004027692-Requesting-a-Copy-of-your-Data) and find json in /activity/analytics/events-*json."]},{"cell_type":"code","execution_count":97,"metadata":{},"outputs":[],"source":["# !pip install matplotlib\n","# !pip install numpy"]},{"cell_type":"code","execution_count":98,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["78 0.6282051282051282 0.3717948717948718 0.0\n"]}],"source":["import json\n","import numpy as np\n","\n","filter_gender_lines = []\n","# Request Discord Data and go to /activity/analytics/events-*json. Put the json file in the same directory as this script.\n","with open('events-2024-00000-of-00001.json', 'r') as f:\n"," for line in f:\n"," obj = json.loads(line.strip('\\n'))\n"," if obj.get('predicted_gender') is not None :\n"," filter_gender_lines.append(obj)\n","\n","filter_gender_lines.sort(key=lambda x: x['day_pt'])\n","\n","pred_list = np.empty([0, 3])\n","day_list = np.empty([0, 2])\n","for obj in filter_gender_lines:\n"," pred_list = np.append(pred_list, [[obj['prob_male']*100, obj['prob_female']*100, obj['prob_non_binary_gender_expansive']*100,]], axis=0)\n"," day_list = np.append(day_list, [[obj['predicted_gender'], obj['day_pt'][0:10]]], axis=0)\n","\n","\n","len_filter_gender_lines = len(filter_gender_lines)\n","pred_male = np.count_nonzero(day_list[:,0] == 'male') / len_filter_gender_lines\n","pred_female = np.count_nonzero(day_list[:,0] == 'female') / len_filter_gender_lines\n","pred_nonbinary = np.count_nonzero(day_list[:,0] == 'non_binary_gender_expansive') / len_filter_gender_lines\n","\n","print(len_filter_gender_lines, pred_male, pred_female, pred_nonbinary)\n"]},{"cell_type":"code","execution_count":99,"metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 1500x700 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["import matplotlib.pyplot as plt\n","import numpy as np\n","\n","width = 0.3 # the width of the bars: can also be len(x) sequence\n","\n","# Plotting\n","plt.figure(figsize=(15, 7))\n","\n","p1 = plt.bar(day_list[:, -1], pred_list[:, 0], width)\n","p2 = plt.bar(day_list[:, -1], pred_list[:, 1], width, bottom=pred_list[:, 0])\n","p3 = plt.bar(day_list[:, -1], pred_list[:, 2], width, bottom=(pred_list[:, 0]+pred_list[:, 1]))\n","\n","plt.ylabel('Certainty (%)')\n","plt.title('What gender Discord thinks I am.')\n","plt.xticks(day_list[:, -1], rotation=90, fontsize=10)\n","plt.yticks(range(0,100,10))\n","\n","plt.legend((p1[0], p2[0], p3[0]), (f'male: {pred_male * 100:.2f} %', f'female: {pred_female * 100:.2f} %', f'non_binary: {pred_nonbinary * 100:.2f} %'))\n","\n","plt.show()"]},{"cell_type":"code","execution_count":null,"metadata":{},"outputs":[],"source":[]}],"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":"3.9.16"}},"nbformat":4,"nbformat_minor":2}
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