code: def remove_emoji(text):
      emoji_pattern = re.compile(
          "["
          "\U0001F600-\U0001F64F"  # emoticons
          "\U0001F300-\U0001F5FF"  # symbols & pictographs
          "\U0001F680-\U0001F6FF"  # transport & map symbols
          "\U0001F1E0-\U0001F1FF"  # flags (iOS)
          "\U00002702-\U000027B0"
          "\U000024C2-\U0001F251"
          "]+",
          flags=re.UNICODE,
      )
      return emoji_pattern.sub(r"", text)
  
imports: import pandas, numpy
  import pdb
  import nltk
  from nltk.sentiment.vader import SentimentIntensityAnalyzer
  from operator import itemgetter
  import copy
  from nltk import word_tokenize, pos_tag
  from collections import Counter
  from nltk.stem.wordnet import WordNetLemmatizer
  from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer
  import emoji
  import string
  import string
  from nltk.tokenize import word_tokenize
  import re
  import string
  import re
  from wordcloud import WordCloud, STOPWORDS
  import matplotlib.pyplot
  from textblob import TextBlob, Word
  from itertools import chain
label_desc: Use image node_id 14 for calling a global function with example usage: remove_emoji(text) and returns: emoji_pattern