pandas.io.formats.style.Styler.applymap¶
- Styler.applymap(func, subset=None, **kwargs)[source]¶
- Apply a CSS-styling function elementwise. - Updates the HTML representation with the result. - Parameters
- funcfunction
- funcshould take a scalar and return a scalar.
- subsetlabel, array-like, IndexSlice, optional
- A valid 2d input to DataFrame.loc[<subset>], or, in the case of a 1d input or single key, to DataFrame.loc[:, <subset>] where the columns are prioritised, to limit - datato before applying the function.
- **kwargsdict
- Pass along to - func.
 
- Returns
- selfStyler
 
 - See also - Styler.apply
- Apply a CSS-styling function column-wise, row-wise, or table-wise. 
 - Notes - The elements of the output of - funcshould be CSS styles as strings, in the format ‘attribute: value; attribute2: value2; …’ or, if nothing is to be applied to that element, an empty string or- None.- Examples - >>> def color_negative(v, color): ... return f"color: {color};" if v < 0 else None >>> df = pd.DataFrame(np.random.randn(5, 2), columns=["A", "B"]) >>> df.style.applymap(color_negative, color='red') - Using - subsetto restrict application to a single column or multiple columns- >>> df.style.applymap(color_negative, color='red', subset="A") >>> df.style.applymap(color_negative, color='red', subset=["A", "B"]) - Using a 2d input to - subsetto select rows in addition to columns- >>> df.style.applymap(color_negative, color='red', subset=([0,1,2], slice(None)) >>> df.style.applymap(color_negative, color='red', subset=(slice(0,5,2), "A")