CODEWITHSUNDEEP
pythonpandaspandas-applypandas-styles
Mega_Noob
Mega_Noob

Reputation: 214

Conditionally color pandas column

My dataframe looks like this: 

Week    Item    Buyer   11  12  13  
0   clothes buyerID1    2   3   4   
1   food    buyerID2    2   1   1   
2   water   buyerID     7   5   1

11, 12, 13 are the weeks. I am trying to conditionally color the rows of the last column to depict a change in items purchased week over week. I am using an adaptation of another answer here to do so, but I am running into an IndexingError: Too many indexers error.

Below is my modified code:

def highlight3(x):
#if increase
c1 = 'background-color: green'

#if decrease
c2 = 'background-color: red'

c3 = ''

#last row greater than value in second to last row
m1 = x.iloc[:, -1] > x.iloc[:, -2]

#last row lesser than value in second to last row
m2 = x.iloc[:, -1] < x.iloc[:, -2]

out = np.select([m1, m2], [c1, c2], default=c3)
return pd.DataFrame(out, index=x.index, columns=x.columns)

And then I apply it to my df using: df.apply(highlight3, axis=None)

Upvotes: 0

Views: 214

Answers (1)

Roy2012
Roy2012

Reputation: 12493

Here's a solution: 

data = """Week    Item    Buyer   11  12  13  
0   clothes buyerID1    2   3   4   
1   food    buyerID2    2   1   1   
2   water   buyerID     7   5   1   """
df = pd.read_csv(StringIO(data), sep="\s+")

green = 'background-color: green'
red = 'background-color: red'

def style_last_week(x):
    s = pd.Series([""] * x.size)
    if x[-1] > x[-2]:
        s[x.size -1 ] = green

    if x[-2] > x[-1]:
        s[x.size -1 ] = red

    return s

df.style.apply(style_last_week, axis=1)

The result is:

enter image description here

Upvotes: 1

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