Reputation: 83
I have two DataFrames:
d1 = {"col1" : ['A', 'B', 'C'],
"Col2": ["home", "car","banana" ]}
d2 = {"col1" : ['D', 'F','C'],
"Col2": ["garden", "boat","banana" ]}
df1 = pd.DataFrame(data=d1)
df2 = pd.DataFrame(data=d2)
new_df = pd.merge(df1, df2, on ='col1', how='outer')
new_df
What I am trying to do is highlight the third row "banana" that was found in the two DataFrames. I was using the Styling documentation to find a solution but no luck. I was able to highlight only a single row, but when I have multiple rows it doesn't work.
Upvotes: 8
Views: 15066
Reputation: 21
Lots of questions link here regarding styling a DataFrame row, so I kept coming here despite the accepted answer not working for me, and no useful error message from pandas. I just came to point out that while the accepted answer may work fine for html, or Jupyter or whatever they're using. It does not work when applied to Excel. For Excel you'll need the following:
new_df.style.apply(
lambda x: ['background-color: <color>' if x.name in [2,4] else '' for i in x],
axis=1
)
Note the use of "backgound-color". Excel will not render "background" as you might expect
In addition, when working with Excel, you'll need to use a color name From Excel's list of recognized colors, Fiddling around with the above answer using "lightgreen" may give you black-on-black... probably not what anyone is looking for.
Upvotes: 2
Reputation: 13437
In case you want to highlight two rows (say index 2 and 4) it is a almost a duplicate of this answer
new_df.style.apply(lambda x: ['background: lightgreen' if x.name in [2,4]
else '' for i in x],
axis=1)
If instead you are looking to highlight every row that contain a given name in a list (i.e. lst = ['car', 'boat']
) you can use
new_df.style.apply(lambda x: ['background: lightgreen' if (set(lst).intersection(x.values))
else '' for i in x],
axis=1)
Upvotes: 8