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Pandas Pivot Table: Exercises, Practice, Solution

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Table of Contain

Pandas Pivot Table [13 exercises with solution]

[ The purpose of the following exercises to show various tasks of a pivot table. We have executed Python code in Jupyter QtConsole and used Salesdata.xlsx as reference data. To get Jupyter QtConsole download Anaconda from here.

A pivot table is a table of statistics that summarizes the data of a more extensive table (such as from a database, spreadsheet, or business intelligence program). This summary might include sums, averages, or other statistics, which the pivot table groups together in a meaningful way.

1. Write a Pandas program to create a Pivot table with multiple indexes from a given excel sheet (Salesdata.xlsx). Go to Excel data
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2. Write a Pandas program to create a Pivot table and find the total sale amount region wise, manager wise. Go to Excel data
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3. Write a Pandas program to create a Pivot table and find the total sale amount region wise, manager wise, sales man wise. Go to Excel data
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4. Write a Pandas program to create a Pivot table and find the item wise unit sold. Go to Excel data
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5. Write a Pandas program to create a Pivot table and find the region wise total sale. Go to Excel data
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6. Write a Pandas program to create a Pivot table and find the region wise, item wise unit sold. Go to Excel data
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7. Write a Pandas program to create a Pivot table and count the manager wise sale and mean value of sale amount. Go to Excel data
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8. Write a Pandas program to create a Pivot table and find manager wise, salesman wise total sale and also display the sum of all sale amount at the bottom. Go to Excel data
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9. Write a Pandas program to create a Pivot table and find the total sale amount region wise, manager wise, sales man wise where Manager = "Douglas". Go to Excel data
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10. Write a Pandas program to create a Pivot table and find the region wise Television and Home Theater sold. Go to Excel data
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11. Write a Pandas program to create a Pivot table and find the maximum sale value of the items. Go to Excel data
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12. Write a Pandas program to create a Pivot table and find the minimum sale value of the items. Go to Excel data
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13.Write a Pandas program to create a Pivot table and find the maximum and minimum sale value of the items. Go to Excel data
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Pandas Pivot on Titanic Passengers csv [19 exercises with solution]

1. Write a Pandas program to print a concise summary of the dataset (titanic.csv). Go to Editor
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2. Write a Pandas program to extract the column labels, shape and data types of the dataset (titanic.csv). Go to Editor
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3. Write a Pandas program to create a Pivot table with multiple indexes from the data set of titanic.csv. Go to Editor
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4. Write a Pandas program to create a Pivot table and find survival rate by gender on various classes. Go to Editor
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5. Write a Pandas program to create a Pivot table and find survival rate by gender. Go to Editor
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6. Write a Pandas program to create a Pivot table and find survival rate by gender, age wise of various classes. Go to Editor
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7. Write a Pandas program to partition each of the passengers into four categories based on their age. Go to Editor
Note: Age categories (0, 10), (10, 30), (30, 60), (60, 80)
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8. Write a Pandas program to create a Pivot table and count survival by gender, categories wise age of various classes. Go to Editor
Note: Age categories (0, 10), (10, 30), (30, 60), (60, 80)
Click me to see the sample solution

9. Write a Pandas program to create a Pivot table and find survival rate by gender, age of the different categories of various classes. Go to Editor
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10. Write a Pandas program to create a Pivot table and find survival rate by gender, age of the different categories of various classes. Add the fare as a dimension of columns and partition fare column into 2 categories based on the values present in fare columns. Go to Editor
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11. Write a Pandas program to create a Pivot table and calculate number of women and men were in a particular cabin class. Go to Editor
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12. Write a Pandas program to create a Pivot table and find survival of both gender and class affected. Go to Editor
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13. Write a Pandas program to create a Pivot table and compute survival totals of all classes along each group. Go to Editor
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14. Write a Pandas program to create a Pivot table and calculate how many women and men were in a particular cabin class. Go to Editor
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15. Write a Pandas program to create a Pivot table and find number of survivors and average rate grouped by gender and class. Go to Editor
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16. Write a Pandas program to create a Pivot table and find number of adult male, adult female and children. Go to Editor
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17. Write a Pandas program to create a Pivot table and check missing values of children. Go to Editor
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18. Write a Pandas program to create a Pivot table and separate the gender according to whether they traveled alone or not to get the probability of survival. Go to Editor
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19. Write a Pandas program to create a Pivot table and find the probability of survival by class, gender, solo boarding and port of embarkation. Go to Editor
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Salesdata.xlsx:


Download (Salesdata.xlsx) from here

Titanic.csv:


Source: OpenDataSoft

Download (Titanic.csv) from here

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.

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Python: Tips of the Day

Calling an external command from Python:

The subprocess module in the standard library:

Example:

import subprocess
subprocess.run(["ls", "-l"])

The advantage of subprocess vs. system is that it is more flexible (you can get the stdout, stderr, the "real" status code, better error handling, etc...).

The official documentation recommends the subprocess module over the alternative os.system():

The subprocess module provides more powerful facilities for spawning new processes and retrieving their results; using that module is preferable to using this function [os.system()].

The Replacing Older Functions with the subprocess Module section in the subprocess documentation may have some helpful recipes.

For versions of Python before 3.5, use call:

import subprocess
subprocess.call(["ls", "-l"])

Ref: https://bit.ly/2ANeuPR