“How to consolidate Values present in Unique Rownames” and add a row containing their Sum

I want to append 2 Rows (Yes/No) for Each Unique Session name.

Eg: Take 1st Session
I want to Add 2 Rows Yes and No which comprises of values as stated below

Yes -> “On Duty + Attended + Online Prescence” => 25+30+40 = 95
No -> “Did Not Attend => 10.

Is there any way to do it in Python.

My input is given below

`

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My Final output Should Look like this

Answer

Here is an idea via dplyr with only fault that the Yes and No appear at the top of each group,

library(dplyr)

df %>% 
 group_by(Name, grp = cumsum(Status == 'Did not attend')) %>% 
 summarise(count = sum(count)) %>% 
 ungroup() %>% 
 select(-grp) %>% 
 mutate(Status = rep(c('Yes', 'No'), length(unique(Name)))) %>% 
 bind_rows(df) %>% 
 arrange(Name)

which gives,

# A tibble: 17 x 3
    Name count Status         
   <dbl> <dbl> <chr>          
 1     1    95 Yes            
 2     1    10 No             
 3     1    25 On Duty        
 4     1    30 Attended       
 5     1    40 Online Presence
 6     1    10 Did not attend 
 7     2   110 Yes            
 8     2    20 No             
 9     2    20 On Duty        
10     2    50 Attended       
11     2    40 Online Presence
12     2    20 Did not attend 
13     3    26 Yes            
14     3    11 No             
15     3    11 On Duty        
16     3    15 Attended       
17     3    11 Did not attend

DATA:

dput(df)
structure(list(Name = c(1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3), Status = c("On Duty", 
"Attended", "Online Presence", "Did not attend", "On Duty", "Attended", 
"Online Presence", "Did not attend", "On Duty", "Attended", "Did not attend"
), count = c(25, 30, 40, 10, 20, 50, 40, 20, 11, 15, 11)), class = "data.frame", row.names = c(NA, 
-11L))