CODEWITHSUNDEEP
pythonpandascolorsapply
Oam
Oam

Reputation: 345

Highlight pandas dataframe columns based on two different conditions

I have the following dataframe comp:

    time        first_max   name             second_max name.1      Perceived OoM.1 Perceived OoM.2
0   0.000000    18          shoulder_center  9          right_hip   shoulder_center shoulder_center
1   0.010000    18          shoulder_center  9          right_hip   shoulder_center shoulder_center
2   0.020000    18          right_hip        9          right_hip   shoulder_center right_hip
3   0.030000    18          shoulder_center  9          right_hip   shoulder_center right_hip

And I have this function that highlights a whole row based on whether name == Perceived OoM.1:

def highlight_col(x):
    df = x.copy()
    mask = df['name'] == df['Perceived OoM.1']
    df.loc[mask, :] = 'background-color: yellow'
    df.loc[~mask,:] = 'background-color: ""'
    return df

comp.style.apply(highlight_col, axis=None)

But, I want to figure out a way to colour a whole row another colour if name == Perceived OoM.2. Basically, I want the row to be yellow if name == Perceived OoM.1 otherwise the row to be blue if name == Perceived OoM.2.

But I can't seem to work that condition into my function.

Any help?

Upvotes: 1

Views: 1835

Answers (2)

Quang Hoang
Quang Hoang

Reputation: 150735

Another way is to define a function so you can apply on rows:

def highlight(x):
    color = 'background-color:yellow' if  x['name']==x['Perceived OoM.1']\
            else 'background-color: green' if x['name']==x['Perceived OoM.2']\
            else ''
    return [color]*len(x)

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

Output:

enter image description here

Upvotes: 1

jezrael
jezrael

Reputation: 862641

Create another mask and pass same way, also for default empty values is used DataFrame constructor:

def highlight_col(x):
    df = pd.DataFrame('', index=x.index, columns=x.columns)
    mask1 = x['name'] == x['Perceived OoM.1']
    mask2 = x['name'] == x['Perceived OoM.2']
    df.loc[mask1, :] = 'background-color: yellow'
    df.loc[mask2, :] = 'background-color: blue'
    return df

Upvotes: 3

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