In this article, we will discuss how to highlight the NaN (Not a number) values in Pandas Dataframe. NaN values used to represent NULL values and sometimes it is the result of the mathematical overflow.
Lets first make a dataframe:
# Import Required Libraries import pandas as pd
import numpy as np
# Create a dictionary for the dataframe dict = { 'Name' : [ 'Sumit Tyagi' , 'Sukritin' , 'Akriti Goel' ,
'Sanskriti' , 'Abhishek Jain' ],
'Age' : [ 22 , 20 , np.nan, np.nan, 22 ],
'Marks' : [ 90 , 84 , 33 , 87 , 82 ]}
# Converting Dictionary to Pandas Dataframe df = pd.DataFrame( dict )
# Print Dataframe df |
Output:
Now, come to the highlighting part. Our objective is to highlight those cells which have Nan values.
Method 1: Highlighting Cell with nan values
We can do this by using the highlight_null() method of DataFrame.style property.This is a property that returns a Styler object, which has useful methods for formatting and displaying DataFrames. highlight_null() method requires one string parameter (the name of the colour with which you want to highlight the cell).
Example:
# Highlighting cell with nan values df.style.highlight_null( 'red' )
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Output:
Method 2: Highlighting text with nan values instead of background
We can do this by using applymap() method of the style property. applymap() method requires a function that takes a scalar and returns a scalar.
Example:
# Highlighting text instead of the # cell's background df.style.applymap( lambda cell: 'color:red' if pd.isnull(cell) else '')
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Output:
Method 3: Highlighting the text of the complete row with nan values
We can do this using the apply() method
Example:
# Highlighting text of the complete row df.style. apply ( lambda row: np.repeat( 'color: red' if row.isnull(). any () else '',
row.shape[ 0 ]), axis = 1 )
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Output:
Method 4: Highlighting the complete row with nan values
# Highlighting the complete row df.style. apply ( lambda row: np.repeat( 'background: red' if row.isnull(). any () else '', row.shape[ 0 ]), axis = 1 )
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Output:
Solution 5: Highlighting the whole column with nan values
# Highlighting column with nan values df.style. apply ( lambda row: np.repeat( 'background: red' if row.isnull(). any () else '',
row.shape[ 0 ]), axis = 0 )
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Output: