From 346c4f766539d813e957491e05603d47a76258fb Mon Sep 17 00:00:00 2001
From: Tommy <tommy.odland@gmail.com>
Date: Tue, 6 Mar 2018 22:32:24 +0100
Subject: [PATCH] Added a template for a cheat sheet

---
 cheat_sheet/Cheat Sheet.ipynb | 103 ++++++++++++++++++++++++++++++++++
 1 file changed, 103 insertions(+)
 create mode 100644 cheat_sheet/Cheat Sheet.ipynb

diff --git a/cheat_sheet/Cheat Sheet.ipynb b/cheat_sheet/Cheat Sheet.ipynb
new file mode 100644
index 0000000..ab64c47
--- /dev/null
+++ b/cheat_sheet/Cheat Sheet.ipynb	
@@ -0,0 +1,103 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Pandas Cheat Sheet"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Table of contents\n",
+    "\n",
+    "\n",
+    "- **The setup**: anaconda, Python, pandas, Jupyter\n",
+    "- **Importing data**: from csv (and options), from the web, creating from scratch, convering types, rename cols\n",
+    "- **Summarizing data**: len(df), shape, value_counts, head, tail, max(), min(), mean, dtype, info(), describe(), memory_usage(), scatter matrix, corr, isnull, notnull, unique(), nlargest\n",
+    "- **Selecting and computing**: select subset of row and cols, .loc, .iloc, drop columns, assign, apply/map/applymap, multiindex\n",
+    "- **Filtering and sorting**: >=, AND, OR, ==, ~, str.contains, str.startswith, sort_values, sort_index, filtering on sorted/unsorted, isin()\n",
+    "- **Split-apply-combine and pivots**: groupby, dt.month, dt.year, groupby.mean(), agg, stack, unstack, pivot, melt, merge\n",
+    "- **Time series manipulations**: downsampling, upsampling, rolling, mean, simple plotting\n",
+    "- **Plotting**: built-in plotting, advanced plotting, matplotlib, seaborn, styles, saving\n",
+    "- **Modeling and machine learning**: .value, feeding data, saving data\n",
+    "- **Misc tips and tricks**: pandas options, vectorization, timings with %%timeit, profiling with lprun\n",
+    "\n",
+    "**principles:** small examples, no more than 5 rows. one or two data sets, no more."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "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": "3.6.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}