How to delete CELLS and shift to right in Pandas Dataframe

Question

So I have a below table

      P         Q          R      
| -------- | --------| --------
| Performan| Dispite | Cammmr
| Dispo    | camera  | battery
| Perfumo  | Displu  | Cammmmt
| Disper   | camera  | battery
| Dispite  | camera  | battery

so I want the above table to appear like below :

|     P    |     Q    |     R   |    S
| -------- | -------- | --------
| Performan| Dispite  | Cammmr  | blank
| blank    | Dispo    | camera  | battery
| Perfumo  | Displu   | Cammmmt | blank
| blank    | Disper   | camera  | battery
| blank    | Dispite  | camera  | battery

so basically I wan to CUT values in column "P" which starts with "Dis" and then replace them by "blank" and then paste them in the adjacent column shifting thier values to right.

Answer 1

Code

1. adds S column (value is 'blank')
2. make condition (starting with 'Dis' in P column) -> variable cond,
3. filters rows and shift and concatenate and so on.

df['S'] = 'blank'
cond = df['P'].str.startswith('Dis')
out = pd.concat([df[~cond], df[cond].shift(axis=1)]).fillna('blank').sort_index()

out:

           P        Q        R        S
0  Performan  Dispite   Cammmr    blank
1      blank    Dispo   camera  battery
2    Perfumo   Displu  Cammmmt    blank
3      blank   Disper   camera  battery
4      blank  Dispite   camera  battery

---

Example Code

import pandas as pd
data1 = {'P': ['Performan', 'Dispo', 'Perfumo', 'Disper', 'Dispite'], 
         'Q': ['Dispite', 'camera', 'Displu', 'camera', 'camera'], 
         'R': ['Cammmr', 'battery', 'Cammmmt', 'battery', 'battery']}
df = pd.DataFrame(data1)

Answer 2

You can use pandas shift with a condition(where column P has cells that starts with "Dis")

df['S'] = 'blank'
df[df['P'].str.startswith('Dis')] = df[df['P'].str.startswith('Dis')].shift(axis=1, fill_value='blank')

end result

P	Q	R	S
Performan	Dispite	Cammmr	None
None	Dispo	camera	battery
Perfumo	Displu	Cammmmt	None
None	Disper	camera	battery
None	Dispite	camera	battery

Answer 3

# For your case you can do the following:
# Add extra Column
df["S"] = "" 

# Filter rows with dis
dis_indices = df['P'].str.startswith("Dis")

# shift the rows
shifted_df = df.loc[dis_indices].shift(1, axis=1) 

# replace the rows
df[dis_indices] = shifted_df[dis_indices] 

# replace nan values
df.fillna("")