I want to introduce a new col in df based on other col values.
If c1-c3 cols have only 1 unique value then that unique value will go into c4 col.
If c1-c3 cols have two different values then "both" will go into c4 col.
NaN should not be considered as a valid value. Only c2 and c3 have a few NaNs.

Minimal example:

df = pd.DataFrame({
                     "c1": ["left", "right", "right", "left", "left","right"], 
                     "c2": ["left", "right", "right", "right", "NaN","right"], 
                     "c3": ["NaN", "NaN", "left", "NaN", "left","right"]})

Required df:

answerdf = pd.DataFrame({
                     "c1": ["left", "right", "right", "left", "left","right"], 
                     "c2": ["left", "right", "right", "right", "NaN","right"], 
                     "c3": ["NaN", "NaN", "left", "NaN", "left","right"], 
                        "c4":["left", "right", "both", "both", "left","right"] })

>Solution :

import pandas as pd
import numpy as np

df = pd.DataFrame({
    "c1": ["left", "right", "right", "left", "left", "right"],
    "c2": ["left", "right", "right", "right", np.nan, "right"],
    "c3": [np.nan, np.nan, "left", np.nan, "left", "right"]
})

def worker(row):
    if "left" in row.values and "right" in row.values:
        return "both"
    if "left" in row.values:
        return "left"
    if "right" in row.values:
        return "right"
    return np.nan

df["c4"] = df[["c1", "c2", "c3"]].apply(worker, axis=1)

This returns nan if neither left nor right is given and might be easier to understand

Output

    c1  c2  c3  c4
0   left    left    NaN     left
1   right   right   NaN     right
2   right   right   left    both
3   left    right   NaN     both
4   left    NaN     left    left
5   right   right   right   right