python pandas数据框根据另一列的条件将列中的文本着色为红色、绿色或黑色

Question

I have a pandas dataframe which looks like this:

ID  CNTS    neg pos neu comp    Overall
1   Reliance Jio Infocomm has accused Bharti Airtel, Vodafone Idea and BSNL of 'cheating' by fraudulently masquerading landline numbers as mobile numbers to unfairly earn interconnect revenue.    0.081   0   0.919   -0.296  Negative
1   The accusation adds new twist to the ongoing telecom tussle.    0.182   0   0.818   -0.25   Negative
1   Here's what is making India's richest man angry.    0.26    0.268   0.472   0.0258  Neutral
2   Jio wants Trai to slap the heaviest penalties on both rivals & BSNL for flouting rules, which it claims cost the company hundreds of crores.    0   0.065   0.935   0.1531  Positive
2   It has also sought a refund of the termination charges it had paid the incumbents due to the alleged fraud. 0.258   0   0.742   -0.7096 Negative
2   Jio claims Airtel, Vodafone Idea and BSNL have implemented a process under which various enterprises are offered mobile numbers as their customer care or helpline numbers. 0   0.118   0.882   0.4939  Positive

Also I wrote a function which returns the specific color based on the values of the dataframe column name "Overall":

def cts(val):
    if (val == 'Negative'):
        color = 'red'
    elif (val == "Positive"):
        color = 'green'
    else: 
        color = 'black'

    return 'color: %s' % color

Now what I want to do that, using the color, the text in the column "CNTS" should get formatted accordingly.

I was trying something which I read on Pandas documentation site:

# Apply color
s = df.style.applymap(cts)
s

But it obviously threw an error. But I don't have any clue or idea how I could apply the function to achieve what I wanted to have as. Could someone help please?

Answer 1

Use custom function with Series.map for filling column by dictionary of colors:

df = pd.DataFrame({'Overall':['Negative','Positive','Another'],
                   'CNT':list('abc')})

def cts(x):
    c1 = 'color: red'
    c2 = 'color: green'
    d = {'Negative':c1, 'Positive':c2}

    df1 = pd.DataFrame('', index=x.index, columns=x.columns)


    df1['CNT'] = x['Overall'].map(d).fillna('color: black')
    return df1

df.style.apply(cts, axis=None)

Sample :