<jupyter_start><jupyter_text><jupyter_code>#authenticatiopn script in gcp
!apt-get install -y -qq software-properties-common python-software-properties module-init-tools

!apt-get install software-properties-common

!apt-get install -y -qq software-properties-common module-init-tools

!apt-get install -y -qq python-software-properties module-init-tools

!add-apt-repository -y ppa:alessandro-strada/ppa 2>&1 > /dev/null

!apt-get update -qq 2>&1 > /dev/null
!apt-get -y install -qq google-drive-ocamlfuse fuse
from google.colab import auth
auth.authenticate_user()
from oauth2client.client import GoogleCredentials
creds = GoogleCredentials.get_application_default()
import getpass
!google-drive-ocamlfuse -headless -id={creds.client_id} -secret={creds.client_secret} < /dev/null 2>&1 | grep URL
vcode = getpass.getpass()
!echo {vcode} | google-drive-ocamlfuse -headless -id={creds.client_id} -secret={creds.client_secret}




#script for reading data from google drive
!mkdir -p drive
!google-drive-ocamlfuse drive
#important libraries in this exercise
import pandas as pd
import xlrd

data = pd.ExcelFile("drive//app//data.xlsx") 

wbook = xlrd.open_workbook("drive//app//data.xlsx")

for excel_sheet in wbook.sheets():
  print(excel_sheet.name)
 #reading all the sheets in the excel workbook
 sheet1 = pd.read_excel(data, sheet_name='Sheet1')
 sheet2 = pd.read_excel(data, sheet_name='Sheet2')
 sheet3 = pd.read_excel(data, sheet_name='Sheet3')
 sheet4 = pd.read_excel(data, sheet_name='Sheet4')
 sheet5 = pd.read_excel(data, sheet_name='Sheet5')
 sheet6 = pd.read_excel(data, sheet_name='Sheet6')
 sheet7 = pd.read_excel(data, sheet_name='Sheet7')
 sheet8 = pd.read_excel(data, sheet_name='Sheet8')
 sheet9 = pd.read_excel(data, sheet_name='Sheet9')
 sheet10 = pd.read_excel(data, sheet_name='Sheet10')
  
#exporting all read sheets to csv file
sheet1.to_csv('drive//app//sheet1.csv')
sheet2.to_csv('drive//app//sheet2.csv')
sheet3.to_csv('drive//app//sheet3.csv')
sheet4.to_csv('drive//app//sheet4.csv')
sheet5.to_csv('drive//app//sheet5.csv')
sheet6.to_csv('drive//app//sheet6.csv')
sheet7.to_csv('drive//app//sheet7.csv')
sheet8.to_csv('drive//app//sheet8.csv')
sheet9.to_csv('drive//app//sheet9.csv')
sheet10.to_csv('drive//app//sheet10.csv')<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.14680105170902716, 'fraction_numerical': 0.022348816827344433, 'mean_word_length': 5.412921348314606, 'pattern_counts': {'":': 0, '<': 6, '<?xml version=': 0, '>': 10, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '666998', 'license': 'MIT', 'n_tokens_mistral': 854, 'n_tokens_neox': 830, 'n_words': 158, 'path': 'FileOperations.ipynb', 'repo_name': 'DannyML-DSC/Hash-analytics', 'size': '2282'}