How can I use df.style for subsets of a DataFrame based on this given condition? I want to highlight the cells in which it is False. But make changes to df, not just df1 Have edited the question. It is different from the previous questions because they are only dealing with element-wise coloring. But I want to color based the
Tag: pandas-styles
Highlight rows from a DataFrame based on values in a column in Python Pandas
I have been trying to highlight some rows in a pandas dataframe based on multiple conditions. I’m expecting that when a string in the target column match the criteria defined in the function, the entire row will be highlighted. I tried different combinations of the .style.apply method, but it kept giving me the following error: ValueError: style is not supported
pandas DataFrame style, highlight nan’s
Say with this DataFrame How can I check which element is nan inside df.applymap? (ie, not using df.isnull) The problem comes from where I want to use the pandas html styling. We have the built-in nan highlighting but it changes the background colour, instead I want “nan” to be displayed in red. So I need to do it myself with