This is the HACK to highlight cells in pandas based on a condition

style_on_condition.py

# Wow way
df[(np.abs(df) > 2).any(1)].style.applymap(lambda x: "background: yellow" if np.abs(x) > 2 else "")
                                 # ↑ Here applymap is used which
                                 #   is eqivalent to the code below
        
# Verbose, but still more control way
df[(np.abs(df) > 2).any(1)].style.apply(lambda x: ["background: yellow" if np.abs(value) > 2 else "" for value in x])
                                # ↑ Only apply is used, so needed to itereate over all elements in this ↑ list comp way
    

# Best EVER! Style based on the positions! (BEST BEST BEST)
def styling_specific_cell(df, rows, cols):
    df_styler = pd.DataFrame('', index= df.index, columns= df.columns)
    df_styler.iloc[rows, cols] = 'background-color: red'
    return df_styler
    
left.style.apply(styling_specific_cell, rows= [0, 2], cols= [0, 2], axis= None)
                                                                   # ↑ This is required
    
'''
Need to remember this that, the styling works is such a way that YOU NEED TO PASS value for EACH CELL. 
No matter whether it meets a condition or not. IF NOT just pass "" or pass color

In the 3rd example, we are makeing one DF for style. That is the matrix by itself.
When it is being created, we filled it with '' and then only filled color in the cell
where we gave the positions.
Then it returned the DF and applied.
REMEMBER: THIS WILL ONLY WORK WHEN `axis= None` IS PASSED. (As it passes WHOLE DF - not Series by Series)
'''

From this site: https://thecodingbot.com/how-to-colour-a-specific-cell-in-pandas-dataframe-based-on-its-position/