12_sheet_prediction_general.py

#https://github.com/nithinmurali/pygsheets
import collections
import pygsheets, os, gspread
import numpy as np
import pandas as pd
from dotenv import load_dotenv
load_dotenv()


json_authentication_file = os.environ.get("json_authentication_file")
python_customer_metrics_1 = os.environ.get("python_customer_metrics_1")
path = 'output_data/'
current_file = f'{path}11_zz_finish_0_100.csv'


#
#
# CURRENT FILE
#
#
#creazione dataframe
df = pd.read_csv(current_file, sep='\t', encoding='UTF-8', decimal=',')
print(df)
#conteggio righe df

#scrittura con rige dataframe
#df_row = pd.read_csv (current_file, sep='\t',header=None, low_memory=False)
df_row = pd.read_csv (current_file, sep='\t', low_memory=False, decimal=',')
print(df_row)
df_row = df_row.replace(np.nan, 'Unknown')

df_row2 = df_row.append(df_row.sum(numeric_only=True), ignore_index=True)

df_row2 = df_row2.tail(1)
df_row2['Week'].fillna('Generale', inplace=True)
#print(df_row2)
#print(type(df_row2))
#print(df_row2.info())



numbers_of_rows = len(df_row2)
#print(numbers_of_rows)
row_sheet = numbers_of_rows +1
#print(row_sheet)
#conteggio colonne df
numbers_of_columns = len(df_row2.columns)
column_sheet = numbers_of_columns
#print(column_sheet)

#apertura Google Sheet
gc = pygsheets.authorize(service_file=json_authentication_file)
# Open spreadsheet and then worksheet
sh = gc.open_by_key(python_customer_metrics_1)
wks = sh.worksheet_by_title('row_predict_general')

#Creazione riche da csv ecommerce
rows = row_sheet
wks.rows=rows
cols = column_sheet
wks.cols=cols #colonna O
wks.clear()

total_rows = row_sheet -1
#print(total_rows)
total_rows = total_rows // 1000
#print(total_rows)

cell_list = wks.range('A:A')
#print(cell_list)
i = 1
for cell in cell_list:
    #print(cell)
    #print(len(cell_list))
    cell_str = str(cell)
    #print(type(cell))
    in_list = "''" in cell_str
    #print(in_list)
    if in_list == False:
        i += 1

wks.insert_rows(row=i, number=1)


print(type(df_row2))
df_row2 = df_row2.astype(str)

#df_row2 = df_row2.str[:-1]
df_row2 = df_row2.replace('\.',',', regex=True)

print(df_row2)

#print(i)
wks.set_dataframe(df_row2,(i, 1))