Let’s see various methods to Highlight the positive values red and negative values black in Pandas Dataframe.
First, Let’s make a Dataframe:
Python3
# Import Required Libraries import pandas as pd import numpy as np # Create a dictionary for the dataframe dict = { 'Name': ['Sukritin', 'Sumit Tyagi', 'Akriti Goel', 'Sanskriti', 'Abhishek Jain'], 'Age': [22, 20, 45, 21, 22], 'Marks': [90, 84, -33, -87, 82] } # Converting Dictionary to # Pandas Dataframe df = pd.DataFrame(dict) # Print Dataframe print(df) |
Output:
Now, come to the highlighting part. Our objective is to highlight negative values red and positive values black.
Method 1: Using Dataframe.style.apply().
Syntax: DataFrame.style.apply(self, func, axis=0, subset=None, **kwargs)
Parameters:
- func: It should take a pandas.Series or pandas.DataFrame based on the axis and should return an object with the same shape.
- axis: {0 or ‘index’, 1 or ‘columns’, None}, default 0. Apply to each column (axis=0 or ‘index’), to each row (axis=1 or ‘columns’), or to the entire DataFrame at once with axis=None.
- subset: Set of columns or rows on which you want to call the func.
- **kwargs: Pass along to func.
Returns: Styler object.
Example 1: Highlighting text.
Python3
# Define a function for colouring # negative values red and # positive values black def highlight_max(s): if s.dtype == np.object: is_neg = [False for _ in range(s.shape[0])] else: is_neg = s < 0 return ['color: red;' if cell else 'color:black' for cell in is_neg] # Using apply method of style # attribute of Pandas DataFrame df.style.apply(highlight_max) |
Output:
Example 2: Highlighting cells instead of text.
Python3
# Define a function which # returns the list for # df.style.apply() method def highlight_max(s): if s.dtype == np.object: is_neg = [False for _ in range(s.shape[0])] else: is_neg = s < 0 return ['background: red; color:white' if cell else 'background:black; color:white' for cell in is_neg] # Using apply method of style # attribute of Pandas DataFrame df.style.apply(highlight_max) |
Output:
Method 2: Using dataframe.style.applymap() method.
Syntax: DataFrame.style.applymap(self, func, subset=None, **kwargs)
Parameters:
- func: It takes a scalar value and return the scalar values
- subset: Set of columns or rows on which you want to call the func.
- **kwargs: Pass along to func.
Returns: Styler object.
Example 1: Highlighting text.
Python3
# Define a function for # colouring negative values # red and positive values black def highlight_max(cell): if type(cell) != str and cell < 0 : return 'color: red' else: return 'color: black' df.style.applymap(highlight_max) |
Output:
Example 2: Highlighting cells instead of text.
Python3
# Define a function which # returns string for # applymap() method def highlight_max(cell): if type(cell) != str and cell < 0 : return 'background: red; color:black' else: return 'background: black; color: white' df.style.applymap(highlight_max) |
Output:
Note: pandas.DataFrame.applymap() method passes only single cell into the callable function while the pandas.DataFrame.apply() passes the pandas.Series to the callable function.
Reference: Styling in Pandas
