pandas-vs-d.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "34.3 s ± 145 ms per loop (mean ± std. dev. of 3 runs, 1 loop each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit -n1 -r3\n",
    "tab = pd.read_csv(\"./input_big.csv\")\n",
    "tab[\"field7\"] = \"London\"\n",
    "tab.to_csv(\"./output.csv\", index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Initial version (from the top)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1min 23s ± 134 ms per loop (mean ± std. dev. of 3 runs, 1 loop each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit -n1 -r3\n",
    "!./test.d input_big.csv field7 London output_d.csv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Optimized version (from the bottom)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "!ldc ./optimized.d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "29.7 s ± 203 ms per loop (mean ± std. dev. of 3 runs, 1 loop each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit -n1 -r3\n",
    "!./optimized input_big.csv field7 London output_d.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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