How to avoid the assigned value being re-written?-CodePudding

The assignment happens appropriately for each category, but if the blocks get full and there are IDs pending in the category and we assign them to a new block, the old assignments get rewritten. Also how do I print the whole new dataframe at the end, because when I am trying it only shows the D block assignment...

import pandas as pd
data = pd.read_csv("database.csv")

blocks = {"A": 5, "B": 30, "C": 50, "D": 100}
for key, value in blocks.items():
    print("For block "   key   " capacity is "   str(value))
    while True:
        s = input("Which category to be allocated? ")
        dataFrame = data[data['Category'].str.contains(s)]
        if not dataFrame.empty:
            dataFrame['Block'] = key

            # for loop for Sr. Number
            spc = blocks[key]
            i = 1
            for index, row in dataFrame.iterrows():
                if i > spc:
                    break
                dataFrame.loc[index, 'Sr.'] = str(i)
                i  = 1
            print(dataFrame)
            break

print(dataFrame)


This is the input 
Name,ID,Category 
ABC,2020,G 
WER,2021,M 
XCV,2022,T 
GFV,2034,M 
WEQ,2021,M 
WEW,2021,M 
WET,2021,M 
WEY,2021,M 
WLK,2021,M 
WYH,2021,M 

expected output 
Name,ID,Category,Block, Sr. 
1 WER 2021 M A 1 
3 GFV 2034 M A 2 
4 WEQ 2021 M A 3 
5 WEW 2021 M A 4 
6 WET 2021 M A 5 

7 WEY 2021 M B 1
8 WLK 2021 M B 2
9 WYH 2021 M B 3

CodePudding user response：

IIUC, use:

s = pd.Series(blocks)
m = df['Category'].eq('M')

(df
 .loc[m]
 .assign(**{'block': s.index.repeat(s)[:m.sum()],
            'Sr.': lambda d: d.groupby('block')
                              .cumcount().add(1)
           })
)

output:

  Name    ID Category block  Sr.
1  WER  2021        M     A    1
3  GFV  2034        M     A    2
4  WEQ  2021        M     A    3
5  WEW  2021        M     A    4
6  WET  2021        M     A    5
7  WEY  2021        M     B    1
8  WLK  2021        M     B    2
9  WYH  2021        M     B    3