kshirsagarsiddharth

Login email;Identifier;First name;Last name
laura@example.com;2070;Laura;Grey
craig@example.com;4081;Craig;Johnson
mary@example.com;9346;Mary;Jenkins
jamie@example.com;5079;Jamie;Smith

kshirsagarsiddharth

import spacy

# Load the English model
nlp = spacy.load("en_core_web_sm")

def clean_social_media_data(text):
    # Process the text
    doc = nlp(text)

    # Extract the lemmas and remove stop words

kshirsagarsiddharth

import re

def clean_social_media_data(text):
    # Remove hashtags and mentions
    text = re.sub(r'#\w+', '', text)
    text = re.sub(r'@\w+', '', text)

    # Remove emojis
    text = re.sub(r'[^\x00-\x7F]+', '', text)

kshirsagarsiddharth

import spacy

# Load the English model
nlp = spacy.load("en_core_web_sm")

def lemmatize_text(text):
    # Process the text
    doc = nlp(text)

    # Extract the lemmas

kshirsagarsiddharth

import nltk
from nltk.stem import WordNetLemmatizer

# Initialize the lemmatizer
lemmatizer = WordNetLemmatizer()

def lemmatize_text(text):
    # Tokenize the text
    tokens = nltk.word_tokenize(text)

kshirsagarsiddharth

import nltk
from nltk.corpus import stopwords

# Load the stop words
stop_words = set(stopwords.words('english'))

def remove_stop_words(text):
    # Tokenize the text
    tokens = nltk.word_tokenize(text)

kshirsagarsiddharth

def remove_stop_words(text):
    # Split the text into words
    words = text.split()

    # Define the stop words
    stop_words = ['a', 'an', 'and', 'the', 'in', 'of']

    # Remove stop words
    clean_words = [word for word in words if word not in stop_words]

kshirsagarsiddharth

import re

def clean_text(text):
    # Use a regular expression to remove punctuation and special characters
    clean_text = re.sub(r'[^\w\s]', '', text)

    # Remove leading and trailing whitespace
    clean_text = clean_text.strip()

    return clean_text

kshirsagarsiddharth

import string


def clean_text(text):
    # Create a translation table to remove punctuation and special characters we are replacing space.
    translator = str.maketrans('', '', string.punctuation + string.printable.replace(' ','')[62:])

    # Use the translate method to remove the characters
    clean_text = text.translate(translator)

kshirsagarsiddharth

@app.callback(Output('km-travelled-gauge', 'value'), Input('km-travelled-slider', 'value'))
def km_travelled_update(km_travelled):
    return km_travelled

@app.callback(Output('km-per-liters-slider-output', 'value'), Input('km-per-liters-slider', 'value'))
def km_travelled_update(km_per_lit):
    return km_per_lit

@app.callback(Output('engine-size-slider-output', 'value'), Input('engine-size-slider', 'value'))
def km_travelled_update(engine_slider):