125 lines
2.7 KiB
Plaintext
125 lines
2.7 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "f11a76bf",
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"metadata": {},
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"source": [
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"# Exercise: Add experiment information to electrophysiology data"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "b6f2742b",
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"\n",
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"# Set some Pandas options: maximum number of rows/columns it's going to display\n",
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"pd.set_option('display.max_rows', 1000)\n",
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"pd.set_option('display.max_columns', 100)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "2967c84e",
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"metadata": {},
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"source": [
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"# Load electrophysiology data"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "ed626ee3",
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"metadata": {},
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"outputs": [],
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"source": [
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"df = pd.read_csv('../../data/QC_passed_2024-07-04_collected.csv')\n",
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"info = pd.read_csv('../../data/op_info.csv')"
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]
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},
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{
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"cell_type": "markdown",
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"id": "2fef4d37",
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"metadata": {},
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"source": [
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"# 1. Add experiment information to the electrophysiology results\n",
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"\n",
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"* Is there information for every experiment?\n",
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"* How many experiments did each patcher perform? (i.e., individual OPs, or rows in `info`)\n",
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"* How many samples did each patcher analyze? (i.e., individual rows in `df`)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "1f3f57eb",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"id": "44031178",
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"metadata": {},
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"source": [
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"# 2. Remove outliers from the table\n",
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"\n",
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"1. Load the list of outliers in `outliers.csv`\n",
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"2. Use an anti-join to remove the outliers from the table\n",
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"3. How many samples (rows) are left in the data?"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "7fa953af",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"id": "84270332",
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"metadata": {},
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"source": [
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"# 3. Save final result in `processed_QC_passed_2024-07-04_collected_v1.csv`\n",
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"\n",
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"1. Using the `.to_csv` method of Pandas DataFrames"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "c7bcff45",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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