Mercurial > repos > jay > gaiac_violin_plot
diff gaiac_pm_data_pulling/Untitled.ipynb @ 3:9de2b10ed246 draft default tip
planemo upload for repository https://github.com/jaidevjoshi83/gaiac commit e9587f93346c7b55e1be00bad5844bf2db3ed03d-dirty
author | jay |
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date | Thu, 10 Jul 2025 19:40:38 +0000 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/gaiac_pm_data_pulling/Untitled.ipynb Thu Jul 10 19:40:38 2025 +0000 @@ -0,0 +1,136 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "4707b84c-b2f9-4740-bd62-a159e2c7e123", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "c9870ed9-90cc-427b-b811-bd94c6b867c9", + "metadata": {}, + "outputs": [], + "source": [ + "a = [1,2,4,6]\n", + "b = [4,5,6,7]\n", + "\n", + "df = pd.DataFrame([a,b])" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "502e66d5-022d-47af-a299-a918f0ebd887", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>0</th>\n", + " <th>1</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>0</th>\n", + " <td>1</td>\n", + " <td>4</td>\n", + " </tr>\n", + " <tr>\n", + " <th>1</th>\n", + " <td>2</td>\n", + " <td>5</td>\n", + " </tr>\n", + " <tr>\n", + " <th>2</th>\n", + " <td>4</td>\n", + " <td>6</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3</th>\n", + " <td>6</td>\n", + " <td>7</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "</div>" + ], + "text/plain": [ + " 0 1\n", + "0 1 4\n", + "1 2 5\n", + "2 4 6\n", + "3 6 7" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.T" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f39e7015-3e8b-4123-8ec7-c05547ee28b1", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "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": "3.10.14" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}