{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook does not use Tatoeba data. Instead, it provides some functions that you may want to use in other notebooks. You can check how to:\n",
    "- [Save your data into a file you can download](#write_csv)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run the following cell to be able to run the examples."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='write_csv'></a>\n",
    "# Write a dataframe into a file that can be retrieved"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is very simple to write a dataframe to a CSV file. \n",
    "\n",
    "Suppose you have the following dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame({'name': ['Raphael', 'Donatello'],\n",
    "                    'mask': ['red', 'purple'],\n",
    "                    'weapon': ['sai', 'bo staff']})\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can use the `to_csv` function to write your dataframe to a CSV file. If you have some Python knowledge, you can check the [documentation](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_csv.html). Otherwise, the following examples are the most used. \n",
    "\n",
    "After running the `to_csv` function, go back to the `Home` page. All files in the current folder are displayed there, so you should see your `Data_export.csv` file. If you want to download it, simply check the box on its left and click the `Download` button at the top of the list."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Write everything"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Simply specify the name of the file you want to create."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('Data_export.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This will give you the following content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!cat 'Data_export.csv'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Do not write the index"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The index of a dataframe is the first column on the left (in bold). In some situations, it is a useless information so you can ignore it when you export your data to a file. To do so, add the `index=False` parameter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('Data_export.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This will give you the following content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!cat 'Data_export.csv'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. Do not write the headers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you don't need the column headers, add the `header=None` parameter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('Data_export.csv', index=False, header=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This will give you the following content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!cat 'Data_export.csv'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4. Change the separator"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The default separator is the comma `,` (hence, CSV :) ). If you want to change it, you can use `sep='<character>'`. Note: a tabulation is represented by `\\t`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('Data_export.csv', index=False, header=None, sep='\\t')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This will give you the following content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!cat 'Data_export.csv'"
   ]
  }
 ],
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