NLP_Dataset_Preparation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "33826ec8",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8008f346",
   "metadata": {},
   "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>participant</th>\n",
       "      <th>sentence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MOT</td>\n",
       "      <td>what animal's on there Tracy ?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CHI</td>\n",
       "      <td>hm: horsie ?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MOT</td>\n",
       "      <td>horsie ?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MOT</td>\n",
       "      <td>it's a horsie phone ?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>MOT</td>\n",
       "      <td>that's pretty neat .</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  participant                        sentence\n",
       "0         MOT  what animal's on there Tracy ?\n",
       "1         CHI                    hm: horsie ?\n",
       "2         MOT                        horsie ?\n",
       "3         MOT           it's a horsie phone ?\n",
       "4         MOT            that's pretty neat ."
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Importing the csv file\n",
    "\n",
    "df = pd.read_csv('101.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e8cc07de",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "what animal's on there Tracy ?hm: horsie ?horsie ?it's a horsie phone ?that's pretty neat .can you call someone on that ?&-uh I wanna find another thing .you wanna find something else ?let's see what we have in here .oh we have a baby brush .you wanna brush her hair ?hm: no .no ?&=laughs we'll leave that with her .baby bottle ?do you wanna give her baby bottle ?no !no ?you sure ?look it fits right in there .look oh .no .no ?okay we'll leave the baby stuff over there .play with this !oh you wanna play with the blocks .alright let's take them out .you gonna help me take them out sweetie ?we'll make a tower ?what do you wanna make with it ?xxx .you're not sure ?alright .what we gonna make .you wanna put your phone down ?let's see we wanna make a +/.xxx .what's that ?spoon !I guess that's to feed the baby too .you don't wanna play with her right ?nah !no ?okay .too babyish !too babyish &=laughs ?alright .so teacups ?would you like to have a tea_party ?hm: ye(a)h .ye(a)h alright what would you prefer to do .you wanna &m build a tower now ?or do you wanna have tea first ?hm: tea .tea first ?okay aw at least you have a teacup .the boil, you hafta make sure the tea's all ready and then I, you needta pour some in our cups for us, so that we have enough tea .mm: that looks good .what kind of tea is it ?hm: 0 .you don't know &=laughs +!?what kind of tea do you like ?hm: watermelon tea .watermelon tea +!?what about what Pierre gets at bedtime ?you like that tea .what does he get ?hm: I don't get xxx .chamomile .oh chamomile tea !chamomile tea .that's a nice tea to have with a little bit, what do you put inside of it usually ?hm: tea .something sweet .xxx tea ?ye(a)h tea and then to make it a little sweeter what do we put inside ?do you remember ?no !xxx honey ?honey and +...honey, ye(a)h I put a little honey in there .so are we gonna have our tea together ?are you gonna make a phone+call first ?who you gonna call ?call Daddy ?alright call Daddy and tell him what you're doing .tell him what you're doing .but I +...it's not really a real phone .it's not a real phone &=laughs ?that's why .you can pretend then .that's why <it's not> [x 2] super fun right now (be)cause it doesn't work .ye(a)h .you like the real thing &eh ?oh and are we gonna have something to eat too ?no xxx like babies .no look I think the cups go on there and then we can put something on there to eat .do you wanna make me something to eat ?hm: I don't know what I wanna do .you don't know what you wanna do .okay well that can be your saucer and this can be mine .ye(a)h .alright have we finished our tea ?not yet .are we still drinking it ?xxx .let me see if it's too hot .&oo it's a little hot !&=laughs .<we should wait> [x 2] .blow on it a bit .put it here .hey how about add some honey +!?oh you can add honey to mine .add some honey ?hm: this is honey .that's honey too ?okay put a little honey .&eh &eh .sweeten it .there we go .mm: you hafta stir it up (be)cause honey usually makes it pretty sweet at the bottom .here the stirrers .I'll stir mine .mm: it's gonna be sweet delicious tea !xxx +/.all finished now .all finished ?okay taste it .mm: that was delicious !oh that is so good you drank all your tea in one gulp &=laughs !I want some more !some more ?okay here we go .mm: delicious tea +/.xxx .+, the same kind of tea you're making me ?xxx ye(a)h .what was it again ?&-uh cranberry ?cranberry tea this time ?ye(a)h .okay that's good too .what a nice little teapot you have .you gonna call Daddy again &=laughs ?tell him what you're doing .tell him what you're doing .xxx .oh hi Daddy oh hi ye(a)h .ye(a)h we're having a tea_party here .Tracy made me cranberry and chamomile, tea and put honey in it .and now we're just sipping it .although Tracy already drank his really quickly &=laughs .and I think we're gonna make a block tower next I'm not sure if he wants to .oh he's drinking some more tea !&ah .alright well have a nice day at work .&eh .see you later &=laughs .bye .can you say bye Daddy ?bye .see you later .there we go .alright wanna make a &bl, a big huge tower now Tracy ?no we're doing our tea now &gulp .oh okay we're still drinking tea alright &=laughs .what do you wanna eat with your tea ?hm: I don't know .you're not sure ?what did you have yesterday that you liked so much that I bought you, remember ?remember carrot raisin something ?&-uh cheese stick !a cheese stick, you xxx a cheese stick with your tea ?&-uh no .no &=laughs ?I got so more tea !more tea ?xxx .oh_my_goodness I think you know what ?I think you better get some more water from the kettle .just pretend right here &=laughs .where ?just right, pretend right here you got a kettle it's boiling .and we need some more water for our teacup, <for our> [x 2] &-uh teapot here .xxx fill it up .filled it with some water .is it already warm ?ye(a)h .ye(a)h, okay now we can pour the tea more .water xxx .ye(a)h some more in mine thank_you so much .thank_you .can I have a little more honey in mine please now ?&gulp .oh_my goodness_gracious you like that don't you ?you like that tea .I'm gonna stir mine nicely .make it cool down a bit .xxx could you make me some muffins to go with my tea ?xxx .&-uh sure xxx get some water for you .you gonna get some muffins ?okay &=laughs .&eh .did you make my muffins already ?that was fast !&-uh not yet .not yet ?xxx open this ?oh ye(a)h no you just pretend .just pretend stir up the batter .I need a spoon !need a spoon ?okay stir up the batter .xxx .you put that in there .cheers !oh cheers now okay .cheers sweetie .cheers &=laughs !&gulps .&oo that's delicious .you made a great tea .so good are you all refreshed now ?yes .try those ?xxx see how high you can make those go .&oh &oh &ah &=laughs !&ah &heh &ah .&aw .start with the, square ones .&oh !&aw &da .hard on the blanket &eh ?ye(a)h xxx do it on the floor .oh that'll work better .ye(a)h just take your time .there you go !woah think you could put a blue block on top ?see if it'll stay ?if it'll stay up ?&oo .excellent look how high you're making it !no [x 2] .(a)nother one ?wow &=gasps .&eek .what is xxx oh &=laughs !&aw &=laughs .that was a high tower !&pu &ah .that was a really high tower .one two three .see how many we can stack up there .one two three .four, take your time Tracy .ah &=laughs !&da !can you help me ?yes I can .xxx +/.try to make the tallest tower ever ?can't be on the phone though we're building a tower now right ?xxx .you know what I think we should do maybe ?let's start with the blue blocks .you wanna help me with the blue blocks ?oh ye(a)h !okay let's start with the blue (be)cause they're the, look they're the most the most stable I think .here put the blue on top .and we'll put the yellow .can put them on top even Tracy .like this .okay try to put the next one on .put it right on top though .<right on top> [x 2] &th there .xxx .&oo .&oo, and &w we'll try these very very carefully .and oh we're almost did it !two .oh &=squeals we did it !&=squeals .okay let's put everything back in the box here .wow we did the tallest tower possible !ye(a)h .xxx .I think we're almost done .&psh .great !\n"
     ]
    }
   ],
   "source": [
    "# logic to concatenate all the rows in sentence column into one single string\n",
    "\n",
    "temp = ''.join(df['sentence'].astype(str))\n",
    "\n",
    "print(temp)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "7dcaea8a",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['101.csv',\n",
       " '102.csv',\n",
       " '103.csv',\n",
       " '104.csv',\n",
       " '108.csv',\n",
       " '109.csv',\n",
       " '110.csv',\n",
       " '111.csv',\n",
       " '115.csv',\n",
       " '117.csv',\n",
       " '119.csv',\n",
       " '120.csv',\n",
       " '121.csv',\n",
       " '122.csv',\n",
       " '123.csv',\n",
       " '124.csv',\n",
       " '125.csv',\n",
       " '126.csv',\n",
       " '127.csv',\n",
       " '128.csv',\n",
       " '132.csv',\n",
       " '133.csv',\n",
       " '134.csv',\n",
       " '135.csv',\n",
       " '138.csv',\n",
       " '139.csv',\n",
       " '140.csv',\n",
       " '141.csv',\n",
       " '143.csv',\n",
       " '145.csv',\n",
       " '149.csv',\n",
       " '157.csv',\n",
       " '159.csv',\n",
       " '161.csv',\n",
       " '163.csv',\n",
       " '165.csv',\n",
       " '167.csv',\n",
       " '169.csv']"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# storing the list of all csv filenames into a list\n",
    "\n",
    "files = [f for f in os.listdir() if f.endswith('.csv')]\n",
    "files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "efa23632",
   "metadata": {
    "scrolled": true
   },
   "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>Subject</th>\n",
       "      <th>speech</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>101</td>\n",
       "      <td>what animal's on there Tracy ?hm: horsie ?hors...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>102</td>\n",
       "      <td>wow Harry .xxx the babies &amp;=gasps !&amp;ah Harry !...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>103</td>\n",
       "      <td>but &amp;the, the horsie on the phone .there's a h...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>104</td>\n",
       "      <td>wow okay .www .block .okay alright &lt;fix it&gt; [x...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>108</td>\n",
       "      <td>will we have these ?could this be his hair ?no...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>109</td>\n",
       "      <td>can I see this teapot ?hey look at &amp;nat .what ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>110</td>\n",
       "      <td>xxx .truck is gonna pick up the blocks .is the...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>111</td>\n",
       "      <td>okay so what do you wanna do ?&amp;-um make [x 3] ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>115</td>\n",
       "      <td>nice .oh !nice .oh &amp;=laughs fell over .that's ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>117</td>\n",
       "      <td>should we have some tea ?let's see what else w...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>119</td>\n",
       "      <td>no .no so why you xxx it up then ?xxx .xxx .ho...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>120</td>\n",
       "      <td>beep@o beep@o .what's that ?what's that ?hey ....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>121</td>\n",
       "      <td>Laura !oh no .oh no the cup broke we broke the...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>122</td>\n",
       "      <td>look .oh look she has a baby .look .she has a ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>123</td>\n",
       "      <td>are you gonna call the horses ?what are you go...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>124</td>\n",
       "      <td>we need an xxx .we need an airplane .hm: there...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>125</td>\n",
       "      <td>www .come .Mama .come sit here .&lt;thank you&gt; [x...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>126</td>\n",
       "      <td>okay wow look at that .what's that ?&amp;=grunts ....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>127</td>\n",
       "      <td>where do you wanna put that ?&amp;e .wanna make a ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>128</td>\n",
       "      <td>it's Aneesh .here .hi Aneesh .&amp;bu Aneesh can't...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>132</td>\n",
       "      <td>xxx right now we'll play tea, tea_party ?you d...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>133</td>\n",
       "      <td>can you see the &amp;-uh, what is it ?xxx toes .ti...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>134</td>\n",
       "      <td>Ginny .Look at the baby !let's feed the baby G...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>135</td>\n",
       "      <td>xxx what the phone .on Mommy's knee and on Mom...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>138</td>\n",
       "      <td>xxx .xxx dolly .www .let's build a little towe...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>139</td>\n",
       "      <td>no [x 2] she doesn't wanna sit up maybe we can...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>140</td>\n",
       "      <td>who's on the phone ?can you say hello ?say hel...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>141</td>\n",
       "      <td>okay can I have some tea please ?do you have a...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>143</td>\n",
       "      <td>www .(o)kay Miss Lu .what are we doing here ?w...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>145</td>\n",
       "      <td>what's that ?that's a car, oh we can have a te...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>149</td>\n",
       "      <td>can you give the babies &lt;a cup of&gt; [x 2] water...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>157</td>\n",
       "      <td>xxx .oh !oh no !&amp;=laughs oh no .do it again .p...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>159</td>\n",
       "      <td>hello ?oh hi Frank .hi I'm playing with Minerv...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>161</td>\n",
       "      <td>here gonna have some tea ?here's some for you ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>163</td>\n",
       "      <td>Seeley look .hello .hello .&amp;na call Grandma ?c...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>165</td>\n",
       "      <td>hi &amp;=laughs .oh you wanna talk to Lance, okay ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>167</td>\n",
       "      <td>would you open it please ?I can .and they doll...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>169</td>\n",
       "      <td>call somebody xxx .who are you calling ?you're...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Subject                                             speech\n",
       "0     101  what animal's on there Tracy ?hm: horsie ?hors...\n",
       "0     102  wow Harry .xxx the babies &=gasps !&ah Harry !...\n",
       "0     103  but &the, the horsie on the phone .there's a h...\n",
       "0     104  wow okay .www .block .okay alright <fix it> [x...\n",
       "0     108  will we have these ?could this be his hair ?no...\n",
       "0     109  can I see this teapot ?hey look at &nat .what ...\n",
       "0     110  xxx .truck is gonna pick up the blocks .is the...\n",
       "0     111  okay so what do you wanna do ?&-um make [x 3] ...\n",
       "0     115  nice .oh !nice .oh &=laughs fell over .that's ...\n",
       "0     117  should we have some tea ?let's see what else w...\n",
       "0     119  no .no so why you xxx it up then ?xxx .xxx .ho...\n",
       "0     120  beep@o beep@o .what's that ?what's that ?hey ....\n",
       "0     121  Laura !oh no .oh no the cup broke we broke the...\n",
       "0     122  look .oh look she has a baby .look .she has a ...\n",
       "0     123  are you gonna call the horses ?what are you go...\n",
       "0     124  we need an xxx .we need an airplane .hm: there...\n",
       "0     125  www .come .Mama .come sit here .<thank you> [x...\n",
       "0     126  okay wow look at that .what's that ?&=grunts ....\n",
       "0     127  where do you wanna put that ?&e .wanna make a ...\n",
       "0     128  it's Aneesh .here .hi Aneesh .&bu Aneesh can't...\n",
       "0     132  xxx right now we'll play tea, tea_party ?you d...\n",
       "0     133  can you see the &-uh, what is it ?xxx toes .ti...\n",
       "0     134  Ginny .Look at the baby !let's feed the baby G...\n",
       "0     135  xxx what the phone .on Mommy's knee and on Mom...\n",
       "0     138  xxx .xxx dolly .www .let's build a little towe...\n",
       "0     139  no [x 2] she doesn't wanna sit up maybe we can...\n",
       "0     140  who's on the phone ?can you say hello ?say hel...\n",
       "0     141  okay can I have some tea please ?do you have a...\n",
       "0     143  www .(o)kay Miss Lu .what are we doing here ?w...\n",
       "0     145  what's that ?that's a car, oh we can have a te...\n",
       "0     149  can you give the babies <a cup of> [x 2] water...\n",
       "0     157  xxx .oh !oh no !&=laughs oh no .do it again .p...\n",
       "0     159  hello ?oh hi Frank .hi I'm playing with Minerv...\n",
       "0     161  here gonna have some tea ?here's some for you ...\n",
       "0     163  Seeley look .hello .hello .&na call Grandma ?c...\n",
       "0     165  hi &=laughs .oh you wanna talk to Lance, okay ...\n",
       "0     167  would you open it please ?I can .and they doll...\n",
       "0     169  call somebody xxx .who are you calling ?you're..."
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Initialising the dataframe\n",
    "# result dataframe will store the entire conversation of each csv file in one row against its file name\n",
    "\n",
    "result = pd.DataFrame(columns=['Subject','speech'])\n",
    "    \n",
    "\n",
    "# Step 1: Iterate through a csv file\n",
    "for file in files:\n",
    "    temp=[] #temp is used to store the concatenated speech data\n",
    "    df = pd.read_csv(file) #reading the csv file and storing it in a dataframe\n",
    "    temp = ''.join(df['sentence'].astype(str)) # concatenate the entire speech column into one single string\n",
    "    temp_df = pd.DataFrame({'Subject': [file.split('.')[0]],'speech' : [temp]}) # storing the result in another dataframe temporarily\n",
    "    result = pd.concat([result, temp_df]) # concatenating the temporary dataframe with our initialised result dataframe\n",
    "    \n",
    "\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "f50b474b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 38 entries, 0 to 0\n",
      "Data columns (total 2 columns):\n",
      " #   Column   Non-Null Count  Dtype \n",
      "---  ------   --------------  ----- \n",
      " 0   Subject  38 non-null     object\n",
      " 1   speech   38 non-null     object\n",
      "dtypes: object(2)\n",
      "memory usage: 912.0+ bytes\n"
     ]
    }
   ],
   "source": [
    "result.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "da8a6199",
   "metadata": {},
   "outputs": [],
   "source": [
    "# converting the subject column into integer data type so that it will be easy to merge\n",
    "\n",
    "result['Subject'] = result['Subject'].astype('int')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "d6279673",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 38 entries, 0 to 0\n",
      "Data columns (total 2 columns):\n",
      " #   Column   Non-Null Count  Dtype \n",
      "---  ------   --------------  ----- \n",
      " 0   Subject  38 non-null     int32 \n",
      " 1   speech   38 non-null     object\n",
      "dtypes: int32(1), object(1)\n",
      "memory usage: 760.0+ bytes\n"
     ]
    }
   ],
   "source": [
    "result.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "ee8dd834",
   "metadata": {
    "scrolled": true
   },
   "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>Subject</th>\n",
       "      <th>Group</th>\n",
       "      <th>Child_Gender</th>\n",
       "      <th>Child_Types</th>\n",
       "      <th>Child_Age_Months</th>\n",
       "      <th>Language</th>\n",
       "      <th>Parent_Gender</th>\n",
       "      <th>Parent_Education</th>\n",
       "      <th>Parent_Token</th>\n",
       "      <th>Parent_Types</th>\n",
       "      <th>Parent_D_optimum_average</th>\n",
       "      <th>Parent_MLU</th>\n",
       "      <th>Parent_NumUtt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>102</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Boy</td>\n",
       "      <td>1</td>\n",
       "      <td>50.14</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>1059</td>\n",
       "      <td>171</td>\n",
       "      <td>52.50</td>\n",
       "      <td>4.224</td>\n",
       "      <td>259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>103</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Boy</td>\n",
       "      <td>45</td>\n",
       "      <td>31.70</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>719</td>\n",
       "      <td>183</td>\n",
       "      <td>50.07</td>\n",
       "      <td>6.344</td>\n",
       "      <td>122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>104</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Girl</td>\n",
       "      <td>33</td>\n",
       "      <td>43.07</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>635</td>\n",
       "      <td>150</td>\n",
       "      <td>42.13</td>\n",
       "      <td>4.762</td>\n",
       "      <td>143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>108</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Boy</td>\n",
       "      <td>115</td>\n",
       "      <td>78.92</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>412</td>\n",
       "      <td>138</td>\n",
       "      <td>46.50</td>\n",
       "      <td>6.027</td>\n",
       "      <td>73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>109</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Boy</td>\n",
       "      <td>86</td>\n",
       "      <td>36.70</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>746</td>\n",
       "      <td>187</td>\n",
       "      <td>50.06</td>\n",
       "      <td>6.194</td>\n",
       "      <td>124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>110</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Boy</td>\n",
       "      <td>50</td>\n",
       "      <td>72.84</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>630</td>\n",
       "      <td>142</td>\n",
       "      <td>53.58</td>\n",
       "      <td>4.985</td>\n",
       "      <td>133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>111</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Boy</td>\n",
       "      <td>82</td>\n",
       "      <td>34.43</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>372</td>\n",
       "      <td>131</td>\n",
       "      <td>57.07</td>\n",
       "      <td>5.937</td>\n",
       "      <td>63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>115</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Girl</td>\n",
       "      <td>88</td>\n",
       "      <td>52.70</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>393</td>\n",
       "      <td>135</td>\n",
       "      <td>43.69</td>\n",
       "      <td>4.494</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>119</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Girl</td>\n",
       "      <td>83</td>\n",
       "      <td>32.00</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>259</td>\n",
       "      <td>89</td>\n",
       "      <td>34.96</td>\n",
       "      <td>5.745</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>122</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Boy</td>\n",
       "      <td>117</td>\n",
       "      <td>58.58</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>above university</td>\n",
       "      <td>736</td>\n",
       "      <td>178</td>\n",
       "      <td>46.36</td>\n",
       "      <td>6.803</td>\n",
       "      <td>117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>123</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Boy</td>\n",
       "      <td>98</td>\n",
       "      <td>34.20</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>above university</td>\n",
       "      <td>1033</td>\n",
       "      <td>216</td>\n",
       "      <td>53.46</td>\n",
       "      <td>6.550</td>\n",
       "      <td>169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>124</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Boy</td>\n",
       "      <td>55</td>\n",
       "      <td>61.70</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>661</td>\n",
       "      <td>138</td>\n",
       "      <td>39.18</td>\n",
       "      <td>4.223</td>\n",
       "      <td>166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>128</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Boy</td>\n",
       "      <td>31</td>\n",
       "      <td>52.44</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>647</td>\n",
       "      <td>140</td>\n",
       "      <td>43.74</td>\n",
       "      <td>3.935</td>\n",
       "      <td>186</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>132</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Boy</td>\n",
       "      <td>93</td>\n",
       "      <td>75.33</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>698</td>\n",
       "      <td>170</td>\n",
       "      <td>42.43</td>\n",
       "      <td>5.631</td>\n",
       "      <td>130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>134</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Girl</td>\n",
       "      <td>17</td>\n",
       "      <td>63.24</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>896</td>\n",
       "      <td>124</td>\n",
       "      <td>34.64</td>\n",
       "      <td>4.650</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>135</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Boy</td>\n",
       "      <td>79</td>\n",
       "      <td>31.67</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>610</td>\n",
       "      <td>120</td>\n",
       "      <td>29.11</td>\n",
       "      <td>5.134</td>\n",
       "      <td>127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>138</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Boy</td>\n",
       "      <td>21</td>\n",
       "      <td>65.54</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>729</td>\n",
       "      <td>150</td>\n",
       "      <td>45.78</td>\n",
       "      <td>5.969</td>\n",
       "      <td>128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>139</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Boy</td>\n",
       "      <td>49</td>\n",
       "      <td>32.30</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>783</td>\n",
       "      <td>150</td>\n",
       "      <td>46.18</td>\n",
       "      <td>6.370</td>\n",
       "      <td>127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>140</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Boy</td>\n",
       "      <td>0</td>\n",
       "      <td>58.94</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>208</td>\n",
       "      <td>68</td>\n",
       "      <td>31.07</td>\n",
       "      <td>4.447</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>145</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Boy</td>\n",
       "      <td>32</td>\n",
       "      <td>26.18</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>552</td>\n",
       "      <td>122</td>\n",
       "      <td>30.61</td>\n",
       "      <td>5.910</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>161</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Girl</td>\n",
       "      <td>0</td>\n",
       "      <td>22.93</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>503</td>\n",
       "      <td>103</td>\n",
       "      <td>27.98</td>\n",
       "      <td>5.010</td>\n",
       "      <td>104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>165</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Boy</td>\n",
       "      <td>7</td>\n",
       "      <td>20.47</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>697</td>\n",
       "      <td>175</td>\n",
       "      <td>50.54</td>\n",
       "      <td>4.555</td>\n",
       "      <td>164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>202</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Girl</td>\n",
       "      <td>24</td>\n",
       "      <td>60.68</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>888</td>\n",
       "      <td>181</td>\n",
       "      <td>61.21</td>\n",
       "      <td>6.029</td>\n",
       "      <td>171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>205</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Girl</td>\n",
       "      <td>98</td>\n",
       "      <td>36.27</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>above university</td>\n",
       "      <td>572</td>\n",
       "      <td>156</td>\n",
       "      <td>58.45</td>\n",
       "      <td>5.953</td>\n",
       "      <td>106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>206</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Girl</td>\n",
       "      <td>52</td>\n",
       "      <td>61.27</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>519</td>\n",
       "      <td>150</td>\n",
       "      <td>64.03</td>\n",
       "      <td>4.841</td>\n",
       "      <td>113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>207</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Boy</td>\n",
       "      <td>73</td>\n",
       "      <td>34.53</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>797</td>\n",
       "      <td>190</td>\n",
       "      <td>62.84</td>\n",
       "      <td>5.466</td>\n",
       "      <td>161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>214</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Boy</td>\n",
       "      <td>20</td>\n",
       "      <td>62.62</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>301</td>\n",
       "      <td>105</td>\n",
       "      <td>57.18</td>\n",
       "      <td>3.040</td>\n",
       "      <td>101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>216</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Boy</td>\n",
       "      <td>87</td>\n",
       "      <td>62.36</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>639</td>\n",
       "      <td>196</td>\n",
       "      <td>65.61</td>\n",
       "      <td>5.711</td>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>218</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Girl</td>\n",
       "      <td>31</td>\n",
       "      <td>47.01</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>above university</td>\n",
       "      <td>325</td>\n",
       "      <td>108</td>\n",
       "      <td>41.25</td>\n",
       "      <td>4.274</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>221</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Boy</td>\n",
       "      <td>35</td>\n",
       "      <td>26.12</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>568</td>\n",
       "      <td>143</td>\n",
       "      <td>52.16</td>\n",
       "      <td>5.847</td>\n",
       "      <td>111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>222</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Girl</td>\n",
       "      <td>11</td>\n",
       "      <td>58.97</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>680</td>\n",
       "      <td>132</td>\n",
       "      <td>33.90</td>\n",
       "      <td>5.687</td>\n",
       "      <td>134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>224</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Boy</td>\n",
       "      <td>125</td>\n",
       "      <td>67.68</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>above university</td>\n",
       "      <td>693</td>\n",
       "      <td>169</td>\n",
       "      <td>51.97</td>\n",
       "      <td>5.839</td>\n",
       "      <td>137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>226</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Boy</td>\n",
       "      <td>61</td>\n",
       "      <td>53.95</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>676</td>\n",
       "      <td>173</td>\n",
       "      <td>63.53</td>\n",
       "      <td>5.319</td>\n",
       "      <td>141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>227</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Boy</td>\n",
       "      <td>71</td>\n",
       "      <td>26.45</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>362</td>\n",
       "      <td>114</td>\n",
       "      <td>60.81</td>\n",
       "      <td>4.061</td>\n",
       "      <td>98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>229</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Girl</td>\n",
       "      <td>87</td>\n",
       "      <td>29.70</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>958</td>\n",
       "      <td>226</td>\n",
       "      <td>70.01</td>\n",
       "      <td>5.908</td>\n",
       "      <td>174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>233</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Boy</td>\n",
       "      <td>55</td>\n",
       "      <td>26.35</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>586</td>\n",
       "      <td>140</td>\n",
       "      <td>52.88</td>\n",
       "      <td>4.043</td>\n",
       "      <td>164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>241</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Boy</td>\n",
       "      <td>70</td>\n",
       "      <td>46.49</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>above university</td>\n",
       "      <td>630</td>\n",
       "      <td>176</td>\n",
       "      <td>50.66</td>\n",
       "      <td>5.949</td>\n",
       "      <td>118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>247</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Girl</td>\n",
       "      <td>17</td>\n",
       "      <td>20.01</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>760</td>\n",
       "      <td>175</td>\n",
       "      <td>52.10</td>\n",
       "      <td>6.118</td>\n",
       "      <td>136</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Subject Group Child_Gender  Child_Types  Child_Age_Months Language  \\\n",
       "0       102   ASD          Boy            1             50.14  English   \n",
       "1       103   TYP          Boy           45             31.70  English   \n",
       "2       104   ASD         Girl           33             43.07  English   \n",
       "3       108   ASD          Boy          115             78.92  English   \n",
       "4       109   TYP          Boy           86             36.70  English   \n",
       "5       110   ASD          Boy           50             72.84  English   \n",
       "6       111   TYP          Boy           82             34.43  English   \n",
       "7       115   TYP         Girl           88             52.70  English   \n",
       "8       119   TYP         Girl           83             32.00  English   \n",
       "9       122   ASD          Boy          117             58.58  English   \n",
       "10      123   TYP          Boy           98             34.20  English   \n",
       "11      124   ASD          Boy           55             61.70  English   \n",
       "12      128   ASD          Boy           31             52.44  English   \n",
       "13      132   ASD          Boy           93             75.33  English   \n",
       "14      134   ASD         Girl           17             63.24  English   \n",
       "15      135   TYP          Boy           79             31.67  English   \n",
       "16      138   ASD          Boy           21             65.54  English   \n",
       "17      139   TYP          Boy           49             32.30  English   \n",
       "18      140   ASD          Boy            0             58.94  English   \n",
       "19      145   TYP          Boy           32             26.18  English   \n",
       "20      161   TYP         Girl            0             22.93  English   \n",
       "21      165   TYP          Boy            7             20.47  English   \n",
       "22      202   ASD         Girl           24             60.68   French   \n",
       "23      205   TYP         Girl           98             36.27   French   \n",
       "24      206   ASD         Girl           52             61.27   French   \n",
       "25      207   TYP          Boy           73             34.53   French   \n",
       "26      214   ASD          Boy           20             62.62   French   \n",
       "27      216   ASD          Boy           87             62.36   French   \n",
       "28      218   ASD         Girl           31             47.01   French   \n",
       "29      221   TYP          Boy           35             26.12   French   \n",
       "30      222   ASD         Girl           11             58.97   French   \n",
       "31      224   ASD          Boy          125             67.68   French   \n",
       "32      226   ASD          Boy           61             53.95   French   \n",
       "33      227   TYP          Boy           71             26.45   French   \n",
       "34      229   TYP         Girl           87             29.70   French   \n",
       "35      233   TYP          Boy           55             26.35   French   \n",
       "36      241   TYP          Boy           70             46.49   French   \n",
       "37      247   TYP         Girl           17             20.01   French   \n",
       "\n",
       "   Parent_Gender  Parent_Education  Parent_Token  Parent_Types  \\\n",
       "0         Female        university          1059           171   \n",
       "1         Female  below university           719           183   \n",
       "2         Female        university           635           150   \n",
       "3         Female  below university           412           138   \n",
       "4         Female        university           746           187   \n",
       "5         Female        university           630           142   \n",
       "6         Female  below university           372           131   \n",
       "7         Female  below university           393           135   \n",
       "8         Female  below university           259            89   \n",
       "9         Female  above university           736           178   \n",
       "10        Female  above university          1033           216   \n",
       "11        Female  below university           661           138   \n",
       "12        Female  below university           647           140   \n",
       "13        Female  below university           698           170   \n",
       "14        Female  below university           896           124   \n",
       "15        Female        university           610           120   \n",
       "16        Female        university           729           150   \n",
       "17        Female        university           783           150   \n",
       "18        Female        university           208            68   \n",
       "19        Female        university           552           122   \n",
       "20        Female  below university           503           103   \n",
       "21        Female        university           697           175   \n",
       "22        Female        university           888           181   \n",
       "23        Female  above university           572           156   \n",
       "24        Female        university           519           150   \n",
       "25        Female  below university           797           190   \n",
       "26        Female  below university           301           105   \n",
       "27        Female        university           639           196   \n",
       "28        Female  above university           325           108   \n",
       "29        Female        university           568           143   \n",
       "30        Female  below university           680           132   \n",
       "31        Female  above university           693           169   \n",
       "32        Female  below university           676           173   \n",
       "33        Female        university           362           114   \n",
       "34        Female  below university           958           226   \n",
       "35        Female        university           586           140   \n",
       "36        Female  above university           630           176   \n",
       "37        Female  below university           760           175   \n",
       "\n",
       "    Parent_D_optimum_average  Parent_MLU  Parent_NumUtt  \n",
       "0                      52.50       4.224            259  \n",
       "1                      50.07       6.344            122  \n",
       "2                      42.13       4.762            143  \n",
       "3                      46.50       6.027             73  \n",
       "4                      50.06       6.194            124  \n",
       "5                      53.58       4.985            133  \n",
       "6                      57.07       5.937             63  \n",
       "7                      43.69       4.494             89  \n",
       "8                      34.96       5.745             47  \n",
       "9                      46.36       6.803            117  \n",
       "10                     53.46       6.550            169  \n",
       "11                     39.18       4.223            166  \n",
       "12                     43.74       3.935            186  \n",
       "13                     42.43       5.631            130  \n",
       "14                     34.64       4.650            200  \n",
       "15                     29.11       5.134            127  \n",
       "16                     45.78       5.969            128  \n",
       "17                     46.18       6.370            127  \n",
       "18                     31.07       4.447             47  \n",
       "19                     30.61       5.910            100  \n",
       "20                     27.98       5.010            104  \n",
       "21                     50.54       4.555            164  \n",
       "22                     61.21       6.029            171  \n",
       "23                     58.45       5.953            106  \n",
       "24                     64.03       4.841            113  \n",
       "25                     62.84       5.466            161  \n",
       "26                     57.18       3.040            101  \n",
       "27                     65.61       5.711            114  \n",
       "28                     41.25       4.274             84  \n",
       "29                     52.16       5.847            111  \n",
       "30                     33.90       5.687            134  \n",
       "31                     51.97       5.839            137  \n",
       "32                     63.53       5.319            141  \n",
       "33                     60.81       4.061             98  \n",
       "34                     70.01       5.908            174  \n",
       "35                     52.88       4.043            164  \n",
       "36                     50.66       5.949            118  \n",
       "37                     52.10       6.118            136  "
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# importing the meta data \n",
    "\n",
    "\n",
    "meta = pd.read_excel('bang_nadig.xlsx')\n",
    "meta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "4bd8ade9",
   "metadata": {},
   "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>Subject</th>\n",
       "      <th>Group</th>\n",
       "      <th>Child_Gender</th>\n",
       "      <th>Child_Types</th>\n",
       "      <th>Child_Age_Months</th>\n",
       "      <th>Language</th>\n",
       "      <th>Parent_Gender</th>\n",
       "      <th>Parent_Education</th>\n",
       "      <th>Parent_Token</th>\n",
       "      <th>Parent_Types</th>\n",
       "      <th>Parent_D_optimum_average</th>\n",
       "      <th>Parent_MLU</th>\n",
       "      <th>Parent_NumUtt</th>\n",
       "      <th>speech</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>102</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Boy</td>\n",
       "      <td>1</td>\n",
       "      <td>50.14</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>1059</td>\n",
       "      <td>171</td>\n",
       "      <td>52.50</td>\n",
       "      <td>4.224</td>\n",
       "      <td>259</td>\n",
       "      <td>wow Harry .xxx the babies &amp;=gasps !&amp;ah Harry !...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>103</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Boy</td>\n",
       "      <td>45</td>\n",
       "      <td>31.70</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>719</td>\n",
       "      <td>183</td>\n",
       "      <td>50.07</td>\n",
       "      <td>6.344</td>\n",
       "      <td>122</td>\n",
       "      <td>but &amp;the, the horsie on the phone .there's a h...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>104</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Girl</td>\n",
       "      <td>33</td>\n",
       "      <td>43.07</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>635</td>\n",
       "      <td>150</td>\n",
       "      <td>42.13</td>\n",
       "      <td>4.762</td>\n",
       "      <td>143</td>\n",
       "      <td>wow okay .www .block .okay alright &lt;fix it&gt; [x...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>108</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Boy</td>\n",
       "      <td>115</td>\n",
       "      <td>78.92</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>412</td>\n",
       "      <td>138</td>\n",
       "      <td>46.50</td>\n",
       "      <td>6.027</td>\n",
       "      <td>73</td>\n",
       "      <td>will we have these ?could this be his hair ?no...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>109</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Boy</td>\n",
       "      <td>86</td>\n",
       "      <td>36.70</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>746</td>\n",
       "      <td>187</td>\n",
       "      <td>50.06</td>\n",
       "      <td>6.194</td>\n",
       "      <td>124</td>\n",
       "      <td>can I see this teapot ?hey look at &amp;nat .what ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>110</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Boy</td>\n",
       "      <td>50</td>\n",
       "      <td>72.84</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>630</td>\n",
       "      <td>142</td>\n",
       "      <td>53.58</td>\n",
       "      <td>4.985</td>\n",
       "      <td>133</td>\n",
       "      <td>xxx .truck is gonna pick up the blocks .is the...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>111</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Boy</td>\n",
       "      <td>82</td>\n",
       "      <td>34.43</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>372</td>\n",
       "      <td>131</td>\n",
       "      <td>57.07</td>\n",
       "      <td>5.937</td>\n",
       "      <td>63</td>\n",
       "      <td>okay so what do you wanna do ?&amp;-um make [x 3] ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>115</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Girl</td>\n",
       "      <td>88</td>\n",
       "      <td>52.70</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>393</td>\n",
       "      <td>135</td>\n",
       "      <td>43.69</td>\n",
       "      <td>4.494</td>\n",
       "      <td>89</td>\n",
       "      <td>nice .oh !nice .oh &amp;=laughs fell over .that's ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>119</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Girl</td>\n",
       "      <td>83</td>\n",
       "      <td>32.00</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>259</td>\n",
       "      <td>89</td>\n",
       "      <td>34.96</td>\n",
       "      <td>5.745</td>\n",
       "      <td>47</td>\n",
       "      <td>no .no so why you xxx it up then ?xxx .xxx .ho...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>122</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Boy</td>\n",
       "      <td>117</td>\n",
       "      <td>58.58</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>above university</td>\n",
       "      <td>736</td>\n",
       "      <td>178</td>\n",
       "      <td>46.36</td>\n",
       "      <td>6.803</td>\n",
       "      <td>117</td>\n",
       "      <td>look .oh look she has a baby .look .she has a ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>123</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Boy</td>\n",
       "      <td>98</td>\n",
       "      <td>34.20</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>above university</td>\n",
       "      <td>1033</td>\n",
       "      <td>216</td>\n",
       "      <td>53.46</td>\n",
       "      <td>6.550</td>\n",
       "      <td>169</td>\n",
       "      <td>are you gonna call the horses ?what are you go...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>124</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Boy</td>\n",
       "      <td>55</td>\n",
       "      <td>61.70</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>661</td>\n",
       "      <td>138</td>\n",
       "      <td>39.18</td>\n",
       "      <td>4.223</td>\n",
       "      <td>166</td>\n",
       "      <td>we need an xxx .we need an airplane .hm: there...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>128</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Boy</td>\n",
       "      <td>31</td>\n",
       "      <td>52.44</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>647</td>\n",
       "      <td>140</td>\n",
       "      <td>43.74</td>\n",
       "      <td>3.935</td>\n",
       "      <td>186</td>\n",
       "      <td>it's Aneesh .here .hi Aneesh .&amp;bu Aneesh can't...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>132</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Boy</td>\n",
       "      <td>93</td>\n",
       "      <td>75.33</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>698</td>\n",
       "      <td>170</td>\n",
       "      <td>42.43</td>\n",
       "      <td>5.631</td>\n",
       "      <td>130</td>\n",
       "      <td>xxx right now we'll play tea, tea_party ?you d...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>134</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Girl</td>\n",
       "      <td>17</td>\n",
       "      <td>63.24</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>896</td>\n",
       "      <td>124</td>\n",
       "      <td>34.64</td>\n",
       "      <td>4.650</td>\n",
       "      <td>200</td>\n",
       "      <td>Ginny .Look at the baby !let's feed the baby G...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>135</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Boy</td>\n",
       "      <td>79</td>\n",
       "      <td>31.67</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>610</td>\n",
       "      <td>120</td>\n",
       "      <td>29.11</td>\n",
       "      <td>5.134</td>\n",
       "      <td>127</td>\n",
       "      <td>xxx what the phone .on Mommy's knee and on Mom...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>138</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Boy</td>\n",
       "      <td>21</td>\n",
       "      <td>65.54</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>729</td>\n",
       "      <td>150</td>\n",
       "      <td>45.78</td>\n",
       "      <td>5.969</td>\n",
       "      <td>128</td>\n",
       "      <td>xxx .xxx dolly .www .let's build a little towe...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>139</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Boy</td>\n",
       "      <td>49</td>\n",
       "      <td>32.30</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>783</td>\n",
       "      <td>150</td>\n",
       "      <td>46.18</td>\n",
       "      <td>6.370</td>\n",
       "      <td>127</td>\n",
       "      <td>no [x 2] she doesn't wanna sit up maybe we can...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>140</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Boy</td>\n",
       "      <td>0</td>\n",
       "      <td>58.94</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>208</td>\n",
       "      <td>68</td>\n",
       "      <td>31.07</td>\n",
       "      <td>4.447</td>\n",
       "      <td>47</td>\n",
       "      <td>who's on the phone ?can you say hello ?say hel...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>145</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Boy</td>\n",
       "      <td>32</td>\n",
       "      <td>26.18</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>552</td>\n",
       "      <td>122</td>\n",
       "      <td>30.61</td>\n",
       "      <td>5.910</td>\n",
       "      <td>100</td>\n",
       "      <td>what's that ?that's a car, oh we can have a te...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>161</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Girl</td>\n",
       "      <td>0</td>\n",
       "      <td>22.93</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>503</td>\n",
       "      <td>103</td>\n",
       "      <td>27.98</td>\n",
       "      <td>5.010</td>\n",
       "      <td>104</td>\n",
       "      <td>here gonna have some tea ?here's some for you ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>165</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Boy</td>\n",
       "      <td>7</td>\n",
       "      <td>20.47</td>\n",
       "      <td>English</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>697</td>\n",
       "      <td>175</td>\n",
       "      <td>50.54</td>\n",
       "      <td>4.555</td>\n",
       "      <td>164</td>\n",
       "      <td>hi &amp;=laughs .oh you wanna talk to Lance, okay ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>202</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Girl</td>\n",
       "      <td>24</td>\n",
       "      <td>60.68</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>888</td>\n",
       "      <td>181</td>\n",
       "      <td>61.21</td>\n",
       "      <td>6.029</td>\n",
       "      <td>171</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>205</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Girl</td>\n",
       "      <td>98</td>\n",
       "      <td>36.27</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>above university</td>\n",
       "      <td>572</td>\n",
       "      <td>156</td>\n",
       "      <td>58.45</td>\n",
       "      <td>5.953</td>\n",
       "      <td>106</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>206</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Girl</td>\n",
       "      <td>52</td>\n",
       "      <td>61.27</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>519</td>\n",
       "      <td>150</td>\n",
       "      <td>64.03</td>\n",
       "      <td>4.841</td>\n",
       "      <td>113</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>207</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Boy</td>\n",
       "      <td>73</td>\n",
       "      <td>34.53</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>797</td>\n",
       "      <td>190</td>\n",
       "      <td>62.84</td>\n",
       "      <td>5.466</td>\n",
       "      <td>161</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>214</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Boy</td>\n",
       "      <td>20</td>\n",
       "      <td>62.62</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>301</td>\n",
       "      <td>105</td>\n",
       "      <td>57.18</td>\n",
       "      <td>3.040</td>\n",
       "      <td>101</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>216</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Boy</td>\n",
       "      <td>87</td>\n",
       "      <td>62.36</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>639</td>\n",
       "      <td>196</td>\n",
       "      <td>65.61</td>\n",
       "      <td>5.711</td>\n",
       "      <td>114</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>218</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Girl</td>\n",
       "      <td>31</td>\n",
       "      <td>47.01</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>above university</td>\n",
       "      <td>325</td>\n",
       "      <td>108</td>\n",
       "      <td>41.25</td>\n",
       "      <td>4.274</td>\n",
       "      <td>84</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>221</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Boy</td>\n",
       "      <td>35</td>\n",
       "      <td>26.12</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>568</td>\n",
       "      <td>143</td>\n",
       "      <td>52.16</td>\n",
       "      <td>5.847</td>\n",
       "      <td>111</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>222</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Girl</td>\n",
       "      <td>11</td>\n",
       "      <td>58.97</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>680</td>\n",
       "      <td>132</td>\n",
       "      <td>33.90</td>\n",
       "      <td>5.687</td>\n",
       "      <td>134</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>224</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Boy</td>\n",
       "      <td>125</td>\n",
       "      <td>67.68</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>above university</td>\n",
       "      <td>693</td>\n",
       "      <td>169</td>\n",
       "      <td>51.97</td>\n",
       "      <td>5.839</td>\n",
       "      <td>137</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>226</td>\n",
       "      <td>ASD</td>\n",
       "      <td>Boy</td>\n",
       "      <td>61</td>\n",
       "      <td>53.95</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>676</td>\n",
       "      <td>173</td>\n",
       "      <td>63.53</td>\n",
       "      <td>5.319</td>\n",
       "      <td>141</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>227</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Boy</td>\n",
       "      <td>71</td>\n",
       "      <td>26.45</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>362</td>\n",
       "      <td>114</td>\n",
       "      <td>60.81</td>\n",
       "      <td>4.061</td>\n",
       "      <td>98</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>229</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Girl</td>\n",
       "      <td>87</td>\n",
       "      <td>29.70</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>958</td>\n",
       "      <td>226</td>\n",
       "      <td>70.01</td>\n",
       "      <td>5.908</td>\n",
       "      <td>174</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>233</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Boy</td>\n",
       "      <td>55</td>\n",
       "      <td>26.35</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>university</td>\n",
       "      <td>586</td>\n",
       "      <td>140</td>\n",
       "      <td>52.88</td>\n",
       "      <td>4.043</td>\n",
       "      <td>164</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>241</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Boy</td>\n",
       "      <td>70</td>\n",
       "      <td>46.49</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>above university</td>\n",
       "      <td>630</td>\n",
       "      <td>176</td>\n",
       "      <td>50.66</td>\n",
       "      <td>5.949</td>\n",
       "      <td>118</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>247</td>\n",
       "      <td>TYP</td>\n",
       "      <td>Girl</td>\n",
       "      <td>17</td>\n",
       "      <td>20.01</td>\n",
       "      <td>French</td>\n",
       "      <td>Female</td>\n",
       "      <td>below university</td>\n",
       "      <td>760</td>\n",
       "      <td>175</td>\n",
       "      <td>52.10</td>\n",
       "      <td>6.118</td>\n",
       "      <td>136</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Subject Group Child_Gender  Child_Types  Child_Age_Months Language  \\\n",
       "0       102   ASD          Boy            1             50.14  English   \n",
       "1       103   TYP          Boy           45             31.70  English   \n",
       "2       104   ASD         Girl           33             43.07  English   \n",
       "3       108   ASD          Boy          115             78.92  English   \n",
       "4       109   TYP          Boy           86             36.70  English   \n",
       "5       110   ASD          Boy           50             72.84  English   \n",
       "6       111   TYP          Boy           82             34.43  English   \n",
       "7       115   TYP         Girl           88             52.70  English   \n",
       "8       119   TYP         Girl           83             32.00  English   \n",
       "9       122   ASD          Boy          117             58.58  English   \n",
       "10      123   TYP          Boy           98             34.20  English   \n",
       "11      124   ASD          Boy           55             61.70  English   \n",
       "12      128   ASD          Boy           31             52.44  English   \n",
       "13      132   ASD          Boy           93             75.33  English   \n",
       "14      134   ASD         Girl           17             63.24  English   \n",
       "15      135   TYP          Boy           79             31.67  English   \n",
       "16      138   ASD          Boy           21             65.54  English   \n",
       "17      139   TYP          Boy           49             32.30  English   \n",
       "18      140   ASD          Boy            0             58.94  English   \n",
       "19      145   TYP          Boy           32             26.18  English   \n",
       "20      161   TYP         Girl            0             22.93  English   \n",
       "21      165   TYP          Boy            7             20.47  English   \n",
       "22      202   ASD         Girl           24             60.68   French   \n",
       "23      205   TYP         Girl           98             36.27   French   \n",
       "24      206   ASD         Girl           52             61.27   French   \n",
       "25      207   TYP          Boy           73             34.53   French   \n",
       "26      214   ASD          Boy           20             62.62   French   \n",
       "27      216   ASD          Boy           87             62.36   French   \n",
       "28      218   ASD         Girl           31             47.01   French   \n",
       "29      221   TYP          Boy           35             26.12   French   \n",
       "30      222   ASD         Girl           11             58.97   French   \n",
       "31      224   ASD          Boy          125             67.68   French   \n",
       "32      226   ASD          Boy           61             53.95   French   \n",
       "33      227   TYP          Boy           71             26.45   French   \n",
       "34      229   TYP         Girl           87             29.70   French   \n",
       "35      233   TYP          Boy           55             26.35   French   \n",
       "36      241   TYP          Boy           70             46.49   French   \n",
       "37      247   TYP         Girl           17             20.01   French   \n",
       "\n",
       "   Parent_Gender  Parent_Education  Parent_Token  Parent_Types  \\\n",
       "0         Female        university          1059           171   \n",
       "1         Female  below university           719           183   \n",
       "2         Female        university           635           150   \n",
       "3         Female  below university           412           138   \n",
       "4         Female        university           746           187   \n",
       "5         Female        university           630           142   \n",
       "6         Female  below university           372           131   \n",
       "7         Female  below university           393           135   \n",
       "8         Female  below university           259            89   \n",
       "9         Female  above university           736           178   \n",
       "10        Female  above university          1033           216   \n",
       "11        Female  below university           661           138   \n",
       "12        Female  below university           647           140   \n",
       "13        Female  below university           698           170   \n",
       "14        Female  below university           896           124   \n",
       "15        Female        university           610           120   \n",
       "16        Female        university           729           150   \n",
       "17        Female        university           783           150   \n",
       "18        Female        university           208            68   \n",
       "19        Female        university           552           122   \n",
       "20        Female  below university           503           103   \n",
       "21        Female        university           697           175   \n",
       "22        Female        university           888           181   \n",
       "23        Female  above university           572           156   \n",
       "24        Female        university           519           150   \n",
       "25        Female  below university           797           190   \n",
       "26        Female  below university           301           105   \n",
       "27        Female        university           639           196   \n",
       "28        Female  above university           325           108   \n",
       "29        Female        university           568           143   \n",
       "30        Female  below university           680           132   \n",
       "31        Female  above university           693           169   \n",
       "32        Female  below university           676           173   \n",
       "33        Female        university           362           114   \n",
       "34        Female  below university           958           226   \n",
       "35        Female        university           586           140   \n",
       "36        Female  above university           630           176   \n",
       "37        Female  below university           760           175   \n",
       "\n",
       "    Parent_D_optimum_average  Parent_MLU  Parent_NumUtt  \\\n",
       "0                      52.50       4.224            259   \n",
       "1                      50.07       6.344            122   \n",
       "2                      42.13       4.762            143   \n",
       "3                      46.50       6.027             73   \n",
       "4                      50.06       6.194            124   \n",
       "5                      53.58       4.985            133   \n",
       "6                      57.07       5.937             63   \n",
       "7                      43.69       4.494             89   \n",
       "8                      34.96       5.745             47   \n",
       "9                      46.36       6.803            117   \n",
       "10                     53.46       6.550            169   \n",
       "11                     39.18       4.223            166   \n",
       "12                     43.74       3.935            186   \n",
       "13                     42.43       5.631            130   \n",
       "14                     34.64       4.650            200   \n",
       "15                     29.11       5.134            127   \n",
       "16                     45.78       5.969            128   \n",
       "17                     46.18       6.370            127   \n",
       "18                     31.07       4.447             47   \n",
       "19                     30.61       5.910            100   \n",
       "20                     27.98       5.010            104   \n",
       "21                     50.54       4.555            164   \n",
       "22                     61.21       6.029            171   \n",
       "23                     58.45       5.953            106   \n",
       "24                     64.03       4.841            113   \n",
       "25                     62.84       5.466            161   \n",
       "26                     57.18       3.040            101   \n",
       "27                     65.61       5.711            114   \n",
       "28                     41.25       4.274             84   \n",
       "29                     52.16       5.847            111   \n",
       "30                     33.90       5.687            134   \n",
       "31                     51.97       5.839            137   \n",
       "32                     63.53       5.319            141   \n",
       "33                     60.81       4.061             98   \n",
       "34                     70.01       5.908            174   \n",
       "35                     52.88       4.043            164   \n",
       "36                     50.66       5.949            118   \n",
       "37                     52.10       6.118            136   \n",
       "\n",
       "                                               speech  \n",
       "0   wow Harry .xxx the babies &=gasps !&ah Harry !...  \n",
       "1   but &the, the horsie on the phone .there's a h...  \n",
       "2   wow okay .www .block .okay alright <fix it> [x...  \n",
       "3   will we have these ?could this be his hair ?no...  \n",
       "4   can I see this teapot ?hey look at &nat .what ...  \n",
       "5   xxx .truck is gonna pick up the blocks .is the...  \n",
       "6   okay so what do you wanna do ?&-um make [x 3] ...  \n",
       "7   nice .oh !nice .oh &=laughs fell over .that's ...  \n",
       "8   no .no so why you xxx it up then ?xxx .xxx .ho...  \n",
       "9   look .oh look she has a baby .look .she has a ...  \n",
       "10  are you gonna call the horses ?what are you go...  \n",
       "11  we need an xxx .we need an airplane .hm: there...  \n",
       "12  it's Aneesh .here .hi Aneesh .&bu Aneesh can't...  \n",
       "13  xxx right now we'll play tea, tea_party ?you d...  \n",
       "14  Ginny .Look at the baby !let's feed the baby G...  \n",
       "15  xxx what the phone .on Mommy's knee and on Mom...  \n",
       "16  xxx .xxx dolly .www .let's build a little towe...  \n",
       "17  no [x 2] she doesn't wanna sit up maybe we can...  \n",
       "18  who's on the phone ?can you say hello ?say hel...  \n",
       "19  what's that ?that's a car, oh we can have a te...  \n",
       "20  here gonna have some tea ?here's some for you ...  \n",
       "21  hi &=laughs .oh you wanna talk to Lance, okay ...  \n",
       "22                                                NaN  \n",
       "23                                                NaN  \n",
       "24                                                NaN  \n",
       "25                                                NaN  \n",
       "26                                                NaN  \n",
       "27                                                NaN  \n",
       "28                                                NaN  \n",
       "29                                                NaN  \n",
       "30                                                NaN  \n",
       "31                                                NaN  \n",
       "32                                                NaN  \n",
       "33                                                NaN  \n",
       "34                                                NaN  \n",
       "35                                                NaN  \n",
       "36                                                NaN  \n",
       "37                                                NaN  "
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# merging the meta data and result dataframe based on the Subject column\n",
    "merged_dataset = meta.merge(result, how='left', on='Subject')\n",
    "merged_dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "082c14b5",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Subject</th>\n",
       "      <th>speech</th>\n",
       "      <th>Group</th>\n",
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       "      <th>0</th>\n",
       "      <td>102</td>\n",
       "      <td>wow Harry .xxx the babies &amp;=gasps !&amp;ah Harry !...</td>\n",
       "      <td>ASD</td>\n",
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       "      <th>1</th>\n",
       "      <td>103</td>\n",
       "      <td>but &amp;the, the horsie on the phone .there's a h...</td>\n",
       "      <td>TYP</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>104</td>\n",
       "      <td>wow okay .www .block .okay alright &lt;fix it&gt; [x...</td>\n",
       "      <td>ASD</td>\n",
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       "      <th>3</th>\n",
       "      <td>108</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
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       "      <td>can I see this teapot ?hey look at &amp;nat .what ...</td>\n",
       "      <td>TYP</td>\n",
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       "      <th>5</th>\n",
       "      <td>110</td>\n",
       "      <td>xxx .truck is gonna pick up the blocks .is the...</td>\n",
       "      <td>ASD</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>111</td>\n",
       "      <td>okay so what do you wanna do ?&amp;-um make [x 3] ...</td>\n",
       "      <td>TYP</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>115</td>\n",
       "      <td>nice .oh !nice .oh &amp;=laughs fell over .that's ...</td>\n",
       "      <td>TYP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>119</td>\n",
       "      <td>no .no so why you xxx it up then ?xxx .xxx .ho...</td>\n",
       "      <td>TYP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>122</td>\n",
       "      <td>look .oh look she has a baby .look .she has a ...</td>\n",
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       "      <th>10</th>\n",
       "      <td>123</td>\n",
       "      <td>are you gonna call the horses ?what are you go...</td>\n",
       "      <td>TYP</td>\n",
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       "      <th>11</th>\n",
       "      <td>124</td>\n",
       "      <td>we need an xxx .we need an airplane .hm: there...</td>\n",
       "      <td>ASD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>128</td>\n",
       "      <td>it's Aneesh .here .hi Aneesh .&amp;bu Aneesh can't...</td>\n",
       "      <td>ASD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>132</td>\n",
       "      <td>xxx right now we'll play tea, tea_party ?you d...</td>\n",
       "      <td>ASD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>134</td>\n",
       "      <td>Ginny .Look at the baby !let's feed the baby G...</td>\n",
       "      <td>ASD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>135</td>\n",
       "      <td>xxx what the phone .on Mommy's knee and on Mom...</td>\n",
       "      <td>TYP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>138</td>\n",
       "      <td>xxx .xxx dolly .www .let's build a little towe...</td>\n",
       "      <td>ASD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>139</td>\n",
       "      <td>no [x 2] she doesn't wanna sit up maybe we can...</td>\n",
       "      <td>TYP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>140</td>\n",
       "      <td>who's on the phone ?can you say hello ?say hel...</td>\n",
       "      <td>ASD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>145</td>\n",
       "      <td>what's that ?that's a car, oh we can have a te...</td>\n",
       "      <td>TYP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>161</td>\n",
       "      <td>here gonna have some tea ?here's some for you ...</td>\n",
       "      <td>TYP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>165</td>\n",
       "      <td>hi &amp;=laughs .oh you wanna talk to Lance, okay ...</td>\n",
       "      <td>TYP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>202</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASD</td>\n",
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       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>205</td>\n",
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       "      <td>TYP</td>\n",
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       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>206</td>\n",
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       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>207</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TYP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>214</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>216</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>218</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>221</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TYP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>222</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>224</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>226</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>227</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TYP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>229</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TYP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>233</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TYP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>241</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TYP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>247</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TYP</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Subject                                             speech Group\n",
       "0       102  wow Harry .xxx the babies &=gasps !&ah Harry !...   ASD\n",
       "1       103  but &the, the horsie on the phone .there's a h...   TYP\n",
       "2       104  wow okay .www .block .okay alright <fix it> [x...   ASD\n",
       "3       108  will we have these ?could this be his hair ?no...   ASD\n",
       "4       109  can I see this teapot ?hey look at &nat .what ...   TYP\n",
       "5       110  xxx .truck is gonna pick up the blocks .is the...   ASD\n",
       "6       111  okay so what do you wanna do ?&-um make [x 3] ...   TYP\n",
       "7       115  nice .oh !nice .oh &=laughs fell over .that's ...   TYP\n",
       "8       119  no .no so why you xxx it up then ?xxx .xxx .ho...   TYP\n",
       "9       122  look .oh look she has a baby .look .she has a ...   ASD\n",
       "10      123  are you gonna call the horses ?what are you go...   TYP\n",
       "11      124  we need an xxx .we need an airplane .hm: there...   ASD\n",
       "12      128  it's Aneesh .here .hi Aneesh .&bu Aneesh can't...   ASD\n",
       "13      132  xxx right now we'll play tea, tea_party ?you d...   ASD\n",
       "14      134  Ginny .Look at the baby !let's feed the baby G...   ASD\n",
       "15      135  xxx what the phone .on Mommy's knee and on Mom...   TYP\n",
       "16      138  xxx .xxx dolly .www .let's build a little towe...   ASD\n",
       "17      139  no [x 2] she doesn't wanna sit up maybe we can...   TYP\n",
       "18      140  who's on the phone ?can you say hello ?say hel...   ASD\n",
       "19      145  what's that ?that's a car, oh we can have a te...   TYP\n",
       "20      161  here gonna have some tea ?here's some for you ...   TYP\n",
       "21      165  hi &=laughs .oh you wanna talk to Lance, okay ...   TYP\n",
       "22      202                                                NaN   ASD\n",
       "23      205                                                NaN   TYP\n",
       "24      206                                                NaN   ASD\n",
       "25      207                                                NaN   TYP\n",
       "26      214                                                NaN   ASD\n",
       "27      216                                                NaN   ASD\n",
       "28      218                                                NaN   ASD\n",
       "29      221                                                NaN   TYP\n",
       "30      222                                                NaN   ASD\n",
       "31      224                                                NaN   ASD\n",
       "32      226                                                NaN   ASD\n",
       "33      227                                                NaN   TYP\n",
       "34      229                                                NaN   TYP\n",
       "35      233                                                NaN   TYP\n",
       "36      241                                                NaN   TYP\n",
       "37      247                                                NaN   TYP"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_dataset[['Subject', 'speech', 'Group']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "9f51f642",
   "metadata": {},
   "outputs": [],
   "source": [
    "# We only have around 21 complete records with speech and metadata. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "9a073e78",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>unique</th>\n",
       "      <th>top</th>\n",
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       "      <th>Group</th>\n",
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       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ASD</th>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>ASD</td>\n",
       "      <td>11</td>\n",
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       "    <tr>\n",
       "      <th>TYP</th>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>TYP</td>\n",
       "      <td>11</td>\n",
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      "text/plain": [
       "      count unique  top freq\n",
       "Group                       \n",
       "ASD      11      1  ASD   11\n",
       "TYP      11      1  TYP   11"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_dataset.dropna().groupby(['Group'])['Group'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6ba1834f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# There is equal proportion of records for ASD and TYP"
   ]
  }
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