如果该行也出现在另一个 df 中，则突出显示 pandas df 中的一行

Question

I have two dataframes df1 and df2. I would like to highlight in yellow all the rows in df1 that are also present in df2.

df1

df2

What I want to achive

So far I have only found solutions in which I insert another row and use a variable there to identify which row I have to colour.

My question is whether it is possible to compare these two df directly in the function presented below.

So these are the two df's:

df1 = pd.DataFrame([['AA',3,'hgend',1], ['BB','frdf',7,2], ['C1',4,'asef',4], ['C2',4,'asef',4], ['C3',4,'asef',4]], columns=list("ABCD"))
df2 = pd.DataFrame([['C1',4,'asef',4], ['C2',4,'asef',4], ['C3',4,'asef',4]], columns=list("XYZQ"))

This is my code to colour the rows:

def highlight_rows(row):
    value = row.loc['A']
    if value == 'C1':
        color = 'yellow'
    else:
        color = ''
    return ['background-color: {}'.format(color) for r in row]

df1.style.apply(highlight_rows, axis=1)

As I said, if I do the comparison beforehand, insert another column and put a variable there, I can then search for this variable and highlight the row. My question is whether I can also do this directly in the function. To do this, I would have to be able to compare both df's in the function. Is this possible at all? It would be enough to be able to compare a single row, eg with.isin

Answer 1

Comparing to df2 inside the function would be inefficient.

You could define a temporary column to identify matches using a merge (the indicator column in_1 becomes left_only or both depending on whether or not the row is present in df2 ). It is then ignored by the styler:

def highlight_rows(row):
    highlight = 'yellow' if row['in_1'] == "both" else ""
    return ['background-color: {}'.format(highlight) for r in row]

(pd.merge(df1, df2.set_axis(df1.columns.tolist(), axis=1), 
          how="left", indicator="in_1")
    .style
    .hide_columns(['in_1'])
    .apply(highlight_rows, axis=1))

---

Alternatively, to actually do the comparison inside the function, define a set of tuples of df2 rows beforehand:

set_df2 = set(df2.apply(tuple, axis=1))

def highlight_rows(row):
    color = 'yellow' if tuple(row) in set_df2 else ""
    return [f'background-color: {color}'] * len(row)

df1.style.apply(highlight_rows, axis=1)