{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "560f48cd",
   "metadata": {},
   "source": [
    "# Exercise: Have a look at the neural data using Pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f7777604",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# Set some Pandas options: maximum number of rows/columns it's going to display\n",
    "pd.set_option('display.max_rows', 1000)\n",
    "pd.set_option('display.max_columns', 100)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6494fb41",
   "metadata": {},
   "source": [
    "# Load electrophysiology data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9ca3bec6",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('../../data/QC_passed_2024-07-04_collected.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d78a63e",
   "metadata": {},
   "source": [
    "## 1. How many rows/columns does the data set have?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4b68e5a6",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "0fab635e",
   "metadata": {},
   "source": [
    "## 2. Display the first 5 rows of the DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4adcd5bf",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "deecdfa0",
   "metadata": {},
   "source": [
    "## 3. Display the names and dtypes of all the columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "64df567c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "411f4228",
   "metadata": {},
   "source": [
    "## 4. Display the unique values of the `high K concentration` and of the `treatment` columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b90ce541",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "1e395e8d",
   "metadata": {},
   "source": [
    "## 5. Display the main statistics of the `max_spikes` column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e2b86159",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "c8c9f6b2",
   "metadata": {},
   "source": [
    "## 6. Show all the rows where the max number of spikes is larger than 50"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c449e9ff",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "ce9ff32b",
   "metadata": {},
   "source": [
    "## 7. Display the main statistics of `'max_spikes'`, for the rows where `high K concentration` is `8 mM` and `15 mM` (separately)\n",
    "\n",
    "Are the distributions any different?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8b84faa2",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "8b2d1c2b",
   "metadata": {},
   "source": [
    "## 8. Display the statistics of `max_spikes` when `high K concentration` is `8 mM`, and the maximum number of spikes is <= 100\n",
    "\n",
    "Does that change your conclusion?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1201f7d1",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "6dbbf6c8",
   "metadata": {},
   "source": [
    "## 9. Transform the `high K concentration` column into a numerical column\n",
    "\n",
    "a) Discard the last three characters of the columns (`' mM'`)\n",
    "\n",
    "b) Use `.astype(float)` to convert to floating point numbers\n",
    "\n",
    "c) Save the result in a column `K (mM)`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1cf5c15d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ecc0cad1",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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