{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "f11a76bf",
   "metadata": {},
   "source": [
    "# Exercise: Add experiment information to electrophysiology data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b6f2742b",
   "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": "2967c84e",
   "metadata": {},
   "source": [
    "# Load electrophysiology data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ed626ee3",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('../../data/QC_passed_2024-07-04_collected.csv')\n",
    "info = pd.read_csv('../../data/op_info.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2fef4d37",
   "metadata": {},
   "source": [
    "# 1. Add experiment information to the electrophysiology results\n",
    "\n",
    "* Is there information for every experiment?\n",
    "* How many experiments did each patcher perform?  (i.e., individual OPs, or rows in `info`)\n",
    "* How many samples did each patcher analyze?  (i.e., individual rows in `df`)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1f3f57eb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "44031178",
   "metadata": {},
   "source": [
    "# 2. Remove outliers from the table\n",
    "\n",
    "1. Load the list of outliers in `outliers.csv`\n",
    "2. Use an anti-join to remove the outliers from the table\n",
    "3. How many samples (rows) are left in the data?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7fa953af",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "84270332",
   "metadata": {},
   "source": [
    "# 3. Save final result in `processed_QC_passed_2024-07-04_collected_v1.csv`\n",
    "\n",
    "1. Using the `.to_csv` method of Pandas DataFrames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c7bcff45",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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