How can I sum up of all prices from tablewidget in python in terms of date column?

Question

I have problem with to do code to sum up prices in terms of date column.

For example:

31-12-2019

There we have :

39,0 and 62.0

I want sum up it and get 101.0 in other column or under last date in new row

All data in tablewidget i have thanks for excel spreedsheet reader procedure:

df = pd.read_excel('test_cod.xlsx')
self.tableWidget_25.setRowCount(len(df.index))
for i in range(len(df.index)):
    for j in range (len(df.columns)):

self.tableWidget_25.setItem(i,j,QTableWidgetItem(str(df.iat[i,j])))

test_cos.xlsx here: spreedsheet

Answer 1

I created a simple csv for this purpose, but you can easily apply this to your dataframe. The dataframe I used is this:

         Date  value  total
0  24-11-2019     10    NaN
1  24-11-2019     20    NaN
2  24-11-2019     50    NaN
3  26-11-2019     14    NaN
4  26-11-2019     23    NaN
5  02-12-2019     15    NaN
6  02-12-2019     15    NaN

This is the solution I came up with. It might not be most optimal, as I have barely ever used pandas, but it works. It doesn't loop within a loop which I think your draft is doing, which is better in terms of performance.

import pandas as pd

df = pd.read_csv('test.csv')

compareVal = df.Date[0]

total=0

print(df)

for x, date in enumerate(df.Date):
    if compareVal==date:
        total += df.value[x]

    else:
        df.at[x-1,'total'] = total
        total = df.value[x]
        compareVal = df.Date[x]

    if x == len(df)-1:
        df.at[x,'total'] = total

print(df)

This is the output:

         Date  value  total
0  24-11-2019     10    NaN
1  24-11-2019     20    NaN
2  24-11-2019     50   80.0
3  26-11-2019     14    NaN
4  26-11-2019     23   37.0
5  02-12-2019     15    NaN
6  02-12-2019     15   30.0