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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:

Python Pandas: pandas style exercise-1 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:

Python Pandas: pandas style exercise-2 output
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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:

Python Pandas: pandas style exercise-3 output
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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:

Python Pandas: pandas style exercise-4 output
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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:

Python Pandas: pandas style exercise-5 output
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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:

Python Pandas: pandas style exercise-6 output
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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:

Python Pandas: pandas style exercise-7 output
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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:

Python Pandas: pandas style exercise-8 output
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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:

Python Pandas: pandas style exercise-9 output
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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:

Python Pandas: pandas style exercise-10 output
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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:

Python Pandas: pandas style exercise-11 output
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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:

Python Pandas: pandas style exercise-12 output
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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:

Python Pandas: pandas style exercise-13 output
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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:

Python Pandas: pandas style exercise-14 output
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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:

Python Pandas: pandas style exercise-15 output
Click me to see the sample solution

Python Code Editor:


[ 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.]



Python: Tips of the Day

Python: Inserting if statements using conditional list comprehensions

x = [1, 2, 3, 4, 5, 6]
result = []
for idx in range(len(x)):
    if x[idx] % 2 == 0:
        result.append(x[idx] * 2)
    else:
        result.append(x[idx])
result

Output:

[1, 4, 3, 8, 5, 12]

[(element * 2 if element % 2 == 0 else element) for element in x]

Output:

[1, 4, 3, 8, 5, 12]

[element * 2 for element in x if element % 2 == 0]

Output:

[4, 8, 12]