{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "fbc41bf2-ad45-40fb-a3b4-750cf9c76263",
   "metadata": {},
   "source": [
    "# averager"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0e2f11b4-84d5-4266-b259-6351e2ae5d31",
   "metadata": {},
   "source": [
    "`averager()` allows the user to check well replicate reproducibility and remove outlier wells systematically. The function can be used independently but is also wrapped into other functions such as `deltact()`. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fb1a9bc9-37e3-45fb-a242-ef39e9b770bf",
   "metadata": {},
   "source": [
    "## Using averager"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b8992eb-a3d5-4117-b557-4cb786bd5809",
   "metadata": {},
   "source": [
    "The first input for `averager()` is the output of `namer()`. In this case, we will use the primer efficiency data used in the `namer()` documentation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b152de80-b87b-43af-8441-c0287d0673d5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pos</th>\n",
       "      <th>Cp</th>\n",
       "      <th>Primer</th>\n",
       "      <th>Name</th>\n",
       "      <th>NamePrim</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A1</td>\n",
       "      <td>17.51</td>\n",
       "      <td>Fus (112734868c1)</td>\n",
       "      <td>mESC total cDNA_20</td>\n",
       "      <td>mESC total cDNA_20Fus (112734868c1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A2</td>\n",
       "      <td>17.54</td>\n",
       "      <td>Fus (112734868c1)</td>\n",
       "      <td>mESC total cDNA_20</td>\n",
       "      <td>mESC total cDNA_20Fus (112734868c1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A3</td>\n",
       "      <td>17.55</td>\n",
       "      <td>Fus (112734868c1)</td>\n",
       "      <td>mESC total cDNA_20</td>\n",
       "      <td>mESC total cDNA_20Fus (112734868c1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A4</td>\n",
       "      <td>18.49</td>\n",
       "      <td>Fus (112734868c1)</td>\n",
       "      <td>mESC total cDNA_40</td>\n",
       "      <td>mESC total cDNA_40Fus (112734868c1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>A5</td>\n",
       "      <td>18.52</td>\n",
       "      <td>Fus (112734868c1)</td>\n",
       "      <td>mESC total cDNA_40</td>\n",
       "      <td>mESC total cDNA_40Fus (112734868c1)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Pos     Cp             Primer                Name  \\\n",
       "0  A1  17.51  Fus (112734868c1)  mESC total cDNA_20   \n",
       "1  A2  17.54  Fus (112734868c1)  mESC total cDNA_20   \n",
       "2  A3  17.55  Fus (112734868c1)  mESC total cDNA_20   \n",
       "3  A4  18.49  Fus (112734868c1)  mESC total cDNA_40   \n",
       "4  A5  18.52  Fus (112734868c1)  mESC total cDNA_40   \n",
       "\n",
       "                              NamePrim  \n",
       "0  mESC total cDNA_20Fus (112734868c1)  \n",
       "1  mESC total cDNA_20Fus (112734868c1)  \n",
       "2  mESC total cDNA_20Fus (112734868c1)  \n",
       "3  mESC total cDNA_40Fus (112734868c1)  \n",
       "4  mESC total cDNA_40Fus (112734868c1)  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import equipt\n",
    "\n",
    "primers = ['Fus (112734868c1)',\n",
    "         'Fus (15029724a1)',\n",
    "         'Ewsr1 (6679715a1)',\n",
    "         'Ewsr1 (88853580c2)',\n",
    "         'Taf15 (141803447c1)',\n",
    "         'Taf15 (141803447c2)',\n",
    "         'Tsix exon4']\n",
    "\n",
    "samples = ['mESC total cDNA']\n",
    "\n",
    "reps = 3\n",
    "\n",
    "config = 'line'\n",
    "\n",
    "kwargs = {'with_dil':samples,\n",
    "         'dil_series':[20,40,80,160],\n",
    "         'dil_rest':None} \n",
    "\n",
    "df = equipt.namer('data/22.11.22_PrimerCurve_Ct.csv',\n",
    "            primers,\n",
    "            samples,\n",
    "            reps,\n",
    "            config,\n",
    "            **kwargs)\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1d7cd514-bb67-4ffa-906a-be96b9c991e3",
   "metadata": {},
   "source": [
    "Notice that `namer()` has supplied the column 'NamePrim'. 'NamePrim' allows `averager()` to identify technical replicates by looking for wells with identical sample-primer pairs.\n",
    "\n",
    "`averager()` takes four parameters. Their documentation is reproduced below:\n",
    "\n",
    "    Params\n",
    "    ______\n",
    "    \n",
    "    ct_data : a dataframe\n",
    "        Output of namer().\n",
    "        \n",
    "    reps : int\n",
    "        The number of replicate wells in the sample. Used to flag sample-\n",
    "        primer pairs where more than half the wells have been removed. Is\n",
    "        not used if thresh == None.\n",
    "\n",
    "    thresh : float or None\n",
    "        Highest acceptable standard deviation for a set of sample-primer\n",
    "        replicate wells. If set to None no wells are removed. Default 0.1\n",
    "        \n",
    "    update_data : Bool\n",
    "        Whether to alter the input dataframe in place or to leave it unaffected.\n",
    "        \n",
    "The simplest use of `averager()` is to calculate the mean Ct values of replicates and their standard deviation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8132ebec-5695-46f3-a18f-b53ac03e6465",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Primer</th>\n",
       "      <th>Name</th>\n",
       "      <th>NamePrim</th>\n",
       "      <th>AvgCt</th>\n",
       "      <th>StdCt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ewsr1 (6679715a1)</td>\n",
       "      <td>mESC total cDNA_160</td>\n",
       "      <td>mESC total cDNA_160Ewsr1 (6679715a1)</td>\n",
       "      <td>21.996667</td>\n",
       "      <td>0.016997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ewsr1 (88853580c2)</td>\n",
       "      <td>mESC total cDNA_160</td>\n",
       "      <td>mESC total cDNA_160Ewsr1 (88853580c2)</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>0.043205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Fus (112734868c1)</td>\n",
       "      <td>mESC total cDNA_160</td>\n",
       "      <td>mESC total cDNA_160Fus (112734868c1)</td>\n",
       "      <td>21.040000</td>\n",
       "      <td>0.558629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Fus (15029724a1)</td>\n",
       "      <td>mESC total cDNA_160</td>\n",
       "      <td>mESC total cDNA_160Fus (15029724a1)</td>\n",
       "      <td>20.700000</td>\n",
       "      <td>0.029439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Taf15 (141803447c1)</td>\n",
       "      <td>mESC total cDNA_160</td>\n",
       "      <td>mESC total cDNA_160Taf15 (141803447c1)</td>\n",
       "      <td>22.020000</td>\n",
       "      <td>0.008165</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Primer                 Name  \\\n",
       "0    Ewsr1 (6679715a1)  mESC total cDNA_160   \n",
       "1   Ewsr1 (88853580c2)  mESC total cDNA_160   \n",
       "2    Fus (112734868c1)  mESC total cDNA_160   \n",
       "3     Fus (15029724a1)  mESC total cDNA_160   \n",
       "4  Taf15 (141803447c1)  mESC total cDNA_160   \n",
       "\n",
       "                                 NamePrim      AvgCt     StdCt  \n",
       "0    mESC total cDNA_160Ewsr1 (6679715a1)  21.996667  0.016997  \n",
       "1   mESC total cDNA_160Ewsr1 (88853580c2)  21.000000  0.043205  \n",
       "2    mESC total cDNA_160Fus (112734868c1)  21.040000  0.558629  \n",
       "3     mESC total cDNA_160Fus (15029724a1)  20.700000  0.029439  \n",
       "4  mESC total cDNA_160Taf15 (141803447c1)  22.020000  0.008165  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avg_df = equipt.averager(df,\n",
    "                        3,\n",
    "                        thresh=None)\n",
    "\n",
    "avg_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "31c86c2e-1e7d-4ead-a14a-3515ec2a1ce2",
   "metadata": {},
   "source": [
    "The head of avg_df shows that of the first five sample-primer pairs one had an unusually high standard deviation: Fus (112734868c1) paired with 1:160 dilute cDNA. If we look in the original dataframe, we can see the errant well:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c2583b9d-b969-48ff-8948-fbade33f218a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pos</th>\n",
       "      <th>Cp</th>\n",
       "      <th>Primer</th>\n",
       "      <th>Name</th>\n",
       "      <th>NamePrim</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>A10</td>\n",
       "      <td>20.64</td>\n",
       "      <td>Fus (112734868c1)</td>\n",
       "      <td>mESC total cDNA_160</td>\n",
       "      <td>mESC total cDNA_160Fus (112734868c1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>A11</td>\n",
       "      <td>20.65</td>\n",
       "      <td>Fus (112734868c1)</td>\n",
       "      <td>mESC total cDNA_160</td>\n",
       "      <td>mESC total cDNA_160Fus (112734868c1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>A12</td>\n",
       "      <td>21.83</td>\n",
       "      <td>Fus (112734868c1)</td>\n",
       "      <td>mESC total cDNA_160</td>\n",
       "      <td>mESC total cDNA_160Fus (112734868c1)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Pos     Cp             Primer                 Name  \\\n",
       "9   A10  20.64  Fus (112734868c1)  mESC total cDNA_160   \n",
       "10  A11  20.65  Fus (112734868c1)  mESC total cDNA_160   \n",
       "11  A12  21.83  Fus (112734868c1)  mESC total cDNA_160   \n",
       "\n",
       "                                NamePrim  \n",
       "9   mESC total cDNA_160Fus (112734868c1)  \n",
       "10  mESC total cDNA_160Fus (112734868c1)  \n",
       "11  mESC total cDNA_160Fus (112734868c1)  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['NamePrim'] == 'mESC total cDNA_160Fus (112734868c1)']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de44ccc4-9072-4c86-a5b8-8a2997eeed06",
   "metadata": {},
   "source": [
    "## Removing Outliers"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "75698041-54f4-453a-9dbf-a9722c4e1032",
   "metadata": {},
   "source": [
    "Two wells are within 0.01 cycles of one another while the third diverges by more than 1, presumably due to pipetting error. These samples could be removed manually, but `averager()` can also perform this automatically by searching for the replicate with the highest divergence from the others:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a00dd8fc-cf52-452e-8aa0-6bd598515071",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Primer</th>\n",
       "      <th>Name</th>\n",
       "      <th>NamePrim</th>\n",
       "      <th>AvgCt</th>\n",
       "      <th>StdCt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ewsr1 (6679715a1)</td>\n",
       "      <td>mESC total cDNA_160</td>\n",
       "      <td>mESC total cDNA_160Ewsr1 (6679715a1)</td>\n",
       "      <td>21.996667</td>\n",
       "      <td>0.016997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ewsr1 (88853580c2)</td>\n",
       "      <td>mESC total cDNA_160</td>\n",
       "      <td>mESC total cDNA_160Ewsr1 (88853580c2)</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>0.043205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Fus (112734868c1)</td>\n",
       "      <td>mESC total cDNA_160</td>\n",
       "      <td>mESC total cDNA_160Fus (112734868c1)</td>\n",
       "      <td>20.645000</td>\n",
       "      <td>0.005000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Fus (15029724a1)</td>\n",
       "      <td>mESC total cDNA_160</td>\n",
       "      <td>mESC total cDNA_160Fus (15029724a1)</td>\n",
       "      <td>20.700000</td>\n",
       "      <td>0.029439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Taf15 (141803447c1)</td>\n",
       "      <td>mESC total cDNA_160</td>\n",
       "      <td>mESC total cDNA_160Taf15 (141803447c1)</td>\n",
       "      <td>22.020000</td>\n",
       "      <td>0.008165</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Primer                 Name  \\\n",
       "0    Ewsr1 (6679715a1)  mESC total cDNA_160   \n",
       "1   Ewsr1 (88853580c2)  mESC total cDNA_160   \n",
       "2    Fus (112734868c1)  mESC total cDNA_160   \n",
       "3     Fus (15029724a1)  mESC total cDNA_160   \n",
       "4  Taf15 (141803447c1)  mESC total cDNA_160   \n",
       "\n",
       "                                 NamePrim      AvgCt     StdCt  \n",
       "0    mESC total cDNA_160Ewsr1 (6679715a1)  21.996667  0.016997  \n",
       "1   mESC total cDNA_160Ewsr1 (88853580c2)  21.000000  0.043205  \n",
       "2    mESC total cDNA_160Fus (112734868c1)  20.645000  0.005000  \n",
       "3     mESC total cDNA_160Fus (15029724a1)  20.700000  0.029439  \n",
       "4  mESC total cDNA_160Taf15 (141803447c1)  22.020000  0.008165  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avg_df = equipt.averager(df,\n",
    "                        3,\n",
    "                        thresh=0.1)\n",
    "\n",
    "avg_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df9a129b-4dd5-4b86-90e6-6b21ca0d9813",
   "metadata": {},
   "source": [
    "Now the standard deviation for that sample-primer pair has been reduced to 0.005. `averager()` records this removal in a log file:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3593e2fc-c2cc-46d2-8506-512419c33968",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Outlier Wells Dropped:\n",
      "mESC total cDNA_160Fus (112734868c1) - 1\n",
      "\n",
      "Samples Removed:\n",
      "\n"
     ]
    }
   ],
   "source": [
    "with open('droppedWells.txt','r') as f:\n",
    "    print(f.read())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9dd8651-4650-4d15-94b2-d5efaf2d74bb",
   "metadata": {},
   "source": [
    "In this case, only one well was removed. If more than half the replicate wells for a given sample-primer pair are removed, `averager()` removes them completely from the dataframe and records them in the log file under 'Samples Removed:'. Deciding the threshold standard deviation for exclusion is up to the user, but in no case should someone analyze a sample-primer pair where two of three replicate wells have been removed."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50d6a9a2-4ac1-495b-91bb-39a4269f1ea7",
   "metadata": {},
   "source": [
    "## Updating input dataframe"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce4a54ac-2b74-4a58-8d54-423a2fe5ff47",
   "metadata": {
    "tags": []
   },
   "source": [
    "Note that by default `averager()` does not remove wells in place, so the original dataframe remains unaffected:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "12c3323d-2329-46fa-86ce-bcf1dffe612f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pos</th>\n",
       "      <th>Cp</th>\n",
       "      <th>Primer</th>\n",
       "      <th>Name</th>\n",
       "      <th>NamePrim</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>A10</td>\n",
       "      <td>20.64</td>\n",
       "      <td>Fus (112734868c1)</td>\n",
       "      <td>mESC total cDNA_160</td>\n",
       "      <td>mESC total cDNA_160Fus (112734868c1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>A11</td>\n",
       "      <td>20.65</td>\n",
       "      <td>Fus (112734868c1)</td>\n",
       "      <td>mESC total cDNA_160</td>\n",
       "      <td>mESC total cDNA_160Fus (112734868c1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>A12</td>\n",
       "      <td>21.83</td>\n",
       "      <td>Fus (112734868c1)</td>\n",
       "      <td>mESC total cDNA_160</td>\n",
       "      <td>mESC total cDNA_160Fus (112734868c1)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Pos     Cp             Primer                 Name  \\\n",
       "9   A10  20.64  Fus (112734868c1)  mESC total cDNA_160   \n",
       "10  A11  20.65  Fus (112734868c1)  mESC total cDNA_160   \n",
       "11  A12  21.83  Fus (112734868c1)  mESC total cDNA_160   \n",
       "\n",
       "                                NamePrim  \n",
       "9   mESC total cDNA_160Fus (112734868c1)  \n",
       "10  mESC total cDNA_160Fus (112734868c1)  \n",
       "11  mESC total cDNA_160Fus (112734868c1)  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['NamePrim'] == 'mESC total cDNA_160Fus (112734868c1)']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d32dbf28-589f-4040-82bf-1123807dd9f5",
   "metadata": {},
   "source": [
    "In general, it is not advisable to remove replicates from the original dataframe. In some cases (such as the function `efficiency()`) it is convenient to modify a dataframe in place. For these rare cases, `averager()` gives the option to modify the input dataframe:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "35859399-b6f5-4fa4-838a-6849d0c48735",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pos</th>\n",
       "      <th>Cp</th>\n",
       "      <th>Primer</th>\n",
       "      <th>Name</th>\n",
       "      <th>NamePrim</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>A10</td>\n",
       "      <td>20.64</td>\n",
       "      <td>Fus (112734868c1)</td>\n",
       "      <td>mESC total cDNA_160</td>\n",
       "      <td>mESC total cDNA_160Fus (112734868c1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>A11</td>\n",
       "      <td>20.65</td>\n",
       "      <td>Fus (112734868c1)</td>\n",
       "      <td>mESC total cDNA_160</td>\n",
       "      <td>mESC total cDNA_160Fus (112734868c1)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Pos     Cp             Primer                 Name  \\\n",
       "9   A10  20.64  Fus (112734868c1)  mESC total cDNA_160   \n",
       "10  A11  20.65  Fus (112734868c1)  mESC total cDNA_160   \n",
       "\n",
       "                                NamePrim  \n",
       "9   mESC total cDNA_160Fus (112734868c1)  \n",
       "10  mESC total cDNA_160Fus (112734868c1)  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "equipt.averager(df,\n",
    "                3,\n",
    "                thresh=0.1,\n",
    "                update_data=True)\n",
    "\n",
    "df[df['NamePrim'] == 'mESC total cDNA_160Fus (112734868c1)']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "5aae24ab-cec8-47d9-a984-3db60fb5262d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Python implementation: CPython\n",
      "Python version       : 3.9.17\n",
      "IPython version      : 8.12.0\n",
      "\n",
      "equipt    : 1.0.0\n",
      "jupyterlab: 3.6.3\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%load_ext watermark\n",
    "%watermark -v -p equipt,jupyterlab"
   ]
  }
 ],
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   "display_name": "Python 3 (ipykernel)",
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