MergeCPTables.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This script will annotate CellProfiler object datasheets with image information"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Provide paths to the objects and images CSV files.\n",
    "object_csv = \"/example/path/to/nuclei.csv\"\n",
    "image_csv = \"/example/path/to/images.csv\"\n",
    "\n",
    "# Specify column names from the images sheet that you want to annotate the objects with, examples provided.\n",
    "# ImageNumber is required for merging, please don't remove this.\n",
    "columns_to_merge = ['ImageNumber', 'Image_Metadata_ColNameHere', 'Image_Metadata_AnotherColNameHere']\n",
    "\n",
    "# Provide an export file name and directory.\n",
    "target_file = \"/example/results/output.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This will construct the data frames we want to merge.\n",
    "main_df = pd.read_csv(object_csv, engine='python')\n",
    "\n",
    "image_df = pd.read_csv(image_csv, engine='python')\n",
    "\n",
    "meta_df = image_df[columns_to_merge]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Perform merging and display a preview of the resulting table.\n",
    "main_df = main_df.merge(meta_df, on=\"ImageNumber\")\n",
    "main_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save the resulting table\n",
    "main_df.to_csv(target_file)"
   ]
  }
 ],
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