Pandas Styling: Exercises, Practice, Solution
[An editor is available at the bottom of the page to write and execute the scripts.]
Styling: This is a new feature and still under development. The styling is accomplished using CSS. You can write "style functions" that take scalars, DataFrames or Series, and return like-indexed DataFrames or Series with CSS "attribute: value" pairs for the values.
Pandas Styling [15 exercises with solution]
1. 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. Go to the editor
Expected Output:
Click me to see the sample solution
2. 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. Go to the editor
Expected Output:
Click me to see the sample solution
3. Create a dataframe of ten rows, four columns with random values. Write a Pandas program to highlight the maximum value in each column. Go to the editor
Expected Output:
Click me to see the sample solution
4. Create a dataframe of ten rows, four columns with random values. Write a Pandas program to highlight the minimum value in each column. Go to the editor
Expected Output:
Click me to see the sample solution
5. Create a dataframe of ten rows, four columns with random values. Write a Pandas program to highlight the maximum value in last two columns. Go to the editor
Expected Output:
Click me to see the sample solution
6. Create a dataframe of ten rows, four columns with random values. Write a Pandas program to set dataframe background Color black and font color yellow. Go to the editor
Expected Output:
Click me to see the sample solution
7. Create a dataframe of ten rows, four columns with random values. Write a Pandas program to highlight dataframe's specific columns. Go to the editor
Expected Output:
Click me to see the sample solution
8. Create a dataframe of ten rows, four columns with random values. Write a Pandas program to highlight dataframe's specific columns with different colors. Go to the editor
Expected Output:
Click me to see the sample solution
9. Create a dataframe of ten rows, four columns with random values. Write a Pandas program to display the dataframe in table style. Go to the editor
Expected Output:
Click me to see the sample solution
10. Create a dataframe of ten rows, four columns with random values. Write a Pandas program to highlight the entire row in Yellow where a specific column value is greater than 0.5. Go to the editor
Expected Output:
Click me to see the sample solution
11. Create a dataframe of ten rows, four columns with random values. Write a Pandas program to display the dataframe in Heatmap style. Go to the editor
Expected Output:
Click me to see the sample solution
12. Create a dataframe of ten rows, four columns with random values. Write a Pandas program to make a gradient color mapping on a specified column. Go to the editor
Expected Output:
Click me to see the sample solution
13. Create a dataframe of ten rows, four columns with random values. Write a Pandas program to make a gradient color on all the values of the said dataframe. Go to the editor
Expected Output:
Click me to see the sample solution
14. Create a dataframe of ten rows, four columns with random values. Write a Pandas program to display the dataframe in table style and border around the table and not around the rows. Go to the editor
Expected Output:
Click me to see the sample solution
15. Create a dataframe of ten rows, four columns with random values. Write a Pandas program to display bar charts in dataframe on specified columns. Go to the editor
Expected Output:
Click me to see the sample solution
Python Code Editor:
More to Come !
Do not submit any solution of the above exercises at here, if you want to contribute go to the appropriate exercise page.
[ Want to contribute to Python Pandas exercises? Send your code (attached with a .zip file) to us at w3resource[at]yahoo[dot]com. Please avoid copyrighted materials.]
Test your Python skills with w3resource's quiz
Python: Tips of the Day
Find current directory and file's directory:
To get the full path to the directory a Python file is contained in, write this in that file:
import os dir_path = os.path.dirname(os.path.realpath(__file__))
(Note that the incantation above won't work if you've already used os.chdir() to change your current working directory, since the value of the __file__ constant is relative to the current working directory and is not changed by an os.chdir() call.)
To get the current working directory use
import os cwd = os.getcwd()
Documentation references for the modules, constants and functions used above:
- The os and os.path modules.
- The __file__ constant
- os.path.realpath(path) (returns "the canonical path of the specified filename, eliminating any symbolic links encountered in the path")
- os.path.dirname(path) (returns "the directory name of pathname path")
- os.getcwd() (returns "a string representing the current working directory")
- os.chdir(path) ("change the current working directory to path")
Ref: https://bit.ly/3fy0R6m
- New Content published on w3resource:
- HTML-CSS Practical: Exercises, Practice, Solution
- Java Regular Expression: Exercises, Practice, Solution
- Scala Programming Exercises, Practice, Solution
- Python Itertools exercises
- Python Numpy exercises
- Python GeoPy Package exercises
- Python Pandas exercises
- Python nltk exercises
- Python BeautifulSoup exercises
- Form Template
- Composer - PHP Package Manager
- PHPUnit - PHP Testing
- Laravel - PHP Framework
- Angular - JavaScript Framework
- Vue - JavaScript Framework
- Jest - JavaScript Testing Framework