w3resource

Pandas styling Exercises: Write a Pandas program to highlight the negative numbers red and positive numbers black

Pandas styling: Exercise-1 with Solution

Create a dataframe of ten rows, four columns with random values. Write a Pandas program to highlight the negative numbers red and positive numbers black.

Sample Solution :

Python Code :

import pandas as pd
import numpy as np
np.random.seed(24)
df = pd.DataFrame({'A': np.linspace(1, 10, 10)})
df = pd.concat([df, pd.DataFrame(np.random.randn(10, 4), columns=list('BCDE'))],
               axis=1)
print("Original array:")
print(df)
def color_negative_red(val):
    color = 'red' if val < 0 else 'black'
    return 'color: %s' % color
print("\nNegative numbers red and positive numbers black:")
df.style.applymap(color_negative_red)

Original array:

Original array:
      A         B         C         D         E
0   1.0  1.329212 -0.770033 -0.316280 -0.990810
1   2.0 -1.070816 -1.438713  0.564417  0.295722
2   3.0 -1.626404  0.219565  0.678805  1.889273
3   4.0  0.961538  0.104011 -0.481165  0.850229
4   5.0  1.453425  1.057737  0.165562  0.515018
5   6.0 -1.336936  0.562861  1.392855 -0.063328
6   7.0  0.121668  1.207603 -0.002040  1.627796
7   8.0  0.354493  1.037528 -0.385684  0.519818
8   9.0  1.686583 -1.325963  1.428984 -2.089354
9  10.0 -0.129820  0.631523 -0.586538  0.290720

Negative numbers red and positive numbers black:

Sample Output:

Python Pandas: pandas styling exercise-1 output

Download the Jupyter Notebook from here.

Python Code Editor:

Have another way to solve this solution? Contribute your code (and comments) through Disqus.

Previous: Python Pandas Style Home.
Next: Create a dataframe of ten rows, four columns with random values. Convert some values to nan values. Write a Pandas program which will highlight the nan values.

What is the difficulty level of this exercise?



Become a Patron!

Follow us on Facebook and Twitter for latest update.

It will be nice if you may share this link in any developer community or anywhere else, from where other developers may find this content. Thanks.

https://198.211.115.131/python-exercises/pandas/style/pandas-style-exercise-1.php