Conditionally format Python pandas cell

Question

I am trying to color, highlight, or change fond of Python pandas DataFrame based on the value of the cell. e.g. if the cells on each rows are bigger than the cell in the first column of that row, then highlight the cell as red (or any other color), otherwise leave it as it is.

I wrote a for loop here:

for index in range(0, df.shape[0]):
    for column in range(1, df.shape[1]): # from 1 not from 0 because I only need # to compare the 2nd to the last cell of each row with the 1st cell in the row 

        if df.iloc[index][column] - df_BDE_n_months_avg_std_pct.iloc[index][0] > 0:
            then "PLEASE PUT YOUR HELP HERE, I NEED A PIECE OF CODE THAT CAN HIGHLIGHT THE CELL"
        else:
            "DO NOTHING"

So far I haven't found a way to do it. Any help will be great.

Answer 1

From the style docs:

You can apply conditional formatting, the visual styling of a DataFrame depending on the data within, by using the DataFrame.style property.

import pandas as pd
df = pd.DataFrame([[2,3,1], [3,2,2], [2,4,4]], columns=list("ABC"))

df.style.apply(lambda x: ["background: red" if v > x.iloc[0] else "" for v in x], axis = 1)

---

Edit: to format specific cells, you can add condition checkers to check the name of element with Series.iteritems() or check the index with enumerate(), e.g. if you want to format starting from column 3, you can use enumerate and check the index:

df = pd.DataFrame([[2,3,-3], [3,2,7], [2,4,4]], columns=list("ABC"))

df.style.apply(lambda x: ["background-color: #ff33aa" 
                          if (i >= 2 and (v > x.iloc[0] + x.iloc[1] 
                                          or v < x.iloc[0] - x.iloc[1])) 
                          else "" for i, v in enumerate(x)], axis = 1)

Answer 2

import numpy as np
import pandas as pd
df = pd.DataFrame(np.random.rand(4,3))
df.style.applymap(lambda x: 'background-color : yellow' if x>df.iloc[0,0] else '')