Add a prototyping document for temporal hierarchical forecasting #127

Some experiments with pandas datetime functions
antoinecarme · May 2, 2020 · 6882c73 · 6882c73
1 parent 4c25e80
commit 6882c73
Showing 1 changed file with 189 additions and 0 deletions.
diff --git a/notebooks_sandbox/temporal_hierarchy/pandas_datetime_periods.ipynb b/notebooks_sandbox/temporal_hierarchy/pandas_datetime_periods.ipynb
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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "range1 = pd.date_range('1/1/2011', periods=2, freq='H')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "DatetimeIndex(['2011-01-01 00:00:00', '2011-01-01 01:00:00'], dtype='datetime64[ns]', freq='H')"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "range1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "delta_t = range1[1] - range1[0]\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3600.0"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "delta_t.total_seconds()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_nb_seconds(iFreq):\n",
+    "    lRange = pd.date_range('1/1/1970', periods=2, freq=iFreq)\n",
+    "    delta_t = lRange[1] - lRange[0]\n",
+    "    return delta_t.total_seconds()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "FREQ_IN_SECONDS S 1.0 1.0\n",
+      "FREQ_IN_SECONDS T 60.0 60.0\n",
+      "FREQ_IN_SECONDS 30T 1800.0 30.0\n",
+      "FREQ_IN_SECONDS H 3600.0 2.0\n",
+      "FREQ_IN_SECONDS 12H 43200.0 12.0\n",
+      "FREQ_IN_SECONDS D 86400.0 2.0\n",
+      "FREQ_IN_SECONDS W 604800.0 7.0\n",
+      "FREQ_IN_SECONDS M 2419200.0 4.0\n",
+      "FREQ_IN_SECONDS 2M 5097600.0 2.107142857142857\n",
+      "FREQ_IN_SECONDS Q 7862400.0 1.5423728813559323\n",
+      "FREQ_IN_SECONDS 2Q 15811200.0 2.010989010989011\n"
+     ]
+    }
+   ],
+   "source": [
+    "lSeconds = [1]\n",
+    "for lFreq in [\"S\" , \"T\" , \"30T\" , \"H\", \"12H\", \"D\", \"W\" , \"M\" , \"2M\", \"Q\" , \"2Q\"]:\n",
+    "    lSeconds = lSeconds + [get_nb_seconds(lFreq)]\n",
+    "    print(\"FREQ_IN_SECONDS\", lFreq , lSeconds[-1] , lSeconds[-1] / lSeconds[-2])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "10.5"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "7*1.5"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Timedelta('0 days 01:00:00')"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "delta_t"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "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": "3.8.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}