#!/usr/bin/python3.8 import pandas as pd import os import glob def init(): global df #list_of_files = glob.glob('*.xlsx') # * means all if need specific format then *.csv latest_file = max(glob.iglob('*.xlsx'),key=os.path.getctime) if latest_file.startswith("~$"): latest_file=latest_file.replace("~$", "") print(latest_file) df = pd.read_excel(latest_file, engine="openpyxl", sheet_name="daily") if df.size > 0: createHtmlSummary(df) def createHtmlSummary(df): #df = self.totalall df=df.sort_values(by=['HUB']) unique_hub=df["HUB"].unique() SummaryString='

Processed SLO count: '+ str(len(df)) +'

' #Adding colum headers for ever hub for hub in unique_hub: SummaryString+="" SummaryString+="" #################################### ####### Between 99 and 100 ########## #################################### SummaryString+='' tmp99 = df[(df.evaluatedPercentage >=99) & (df.evaluatedPercentage <= 100)].groupby("HUB")["evaluatedPercentage"].count().reset_index() for hub in unique_hub: #for index, row in tmp99.iterrows(): SummaryString+=''.format(tmp99[(tmp99.HUB == hub)]["evaluatedPercentage"].values[0] if tmp99[(tmp99.HUB == hub)].size != 0 else 0) SummaryString+=''.format(len(df[(df.evaluatedPercentage >=99) & (df.evaluatedPercentage <= 100)])) #################################### ####### Between 98 and 99 ########## #################################### SummaryString+='' #if tmp98.size != 0: tmp98 = df[(df.evaluatedPercentage >=98) & (df.evaluatedPercentage < 99)].groupby("HUB")["evaluatedPercentage"].count().reset_index() for hub in unique_hub: SummaryString+=''.format(tmp98[(tmp98.HUB == hub)]["evaluatedPercentage"].values[0] if tmp98[(tmp98.HUB == hub)].size != 0 else 0) SummaryString+=''.format(len(df[(df.evaluatedPercentage >=98) & (df.evaluatedPercentage < 99)])) #################################### ####### Between 0 and 98 ########### #################################### SummaryString+='' tmp0 = df[(df.evaluatedPercentage >=0) & (df.evaluatedPercentage < 98)].groupby("HUB")["evaluatedPercentage"].count().reset_index() for hub in unique_hub: SummaryString+=''.format(tmp0[(tmp0.HUB == hub)]["evaluatedPercentage"].values[0] if tmp0[(tmp0.HUB == hub)].size != 0 else 0) SummaryString+=''.format(len(df[(df.evaluatedPercentage >=0) & (df.evaluatedPercentage < 98)])) #################################### ####### -1 --> N/A ########### #################################### SummaryString+='' tmpNA = df[(df.evaluatedPercentage == -1)].groupby("HUB")["evaluatedPercentage"].count().reset_index() for hub in unique_hub: SummaryString+=''.format(tmpNA[(tmpNA.HUB == hub)]["evaluatedPercentage"].values[0] if tmpNA[(tmpNA.HUB == hub)].size != 0 else 0) SummaryString+=''.format(len(df[(df.evaluatedPercentage == -1)])) SummaryString+="
"+hub+"total
>= 99{0}{0}
>= 98{0}{0}
< 98{0}{0}
-1{0}{0}
" with open('summary.txt', 'w') as f: f.write(SummaryString) if __name__ == "__main__": init()