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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

Understanding slice notation:

It's pretty simple really:

a[start:stop]  # items start through stop-1
a[start:]      # items start through the rest of the array
a[:stop]       # items from the beginning through stop-1
a[:]           # a copy of the whole array

There is also the step value, which can be used with any of the above:

a[start:stop:step] # start through not past stop, by step

The key point to remember is that the :stop value represents the first value that is not in the selected slice. So, the difference between stop and start is the number of elements selected (if step is 1, the default).

The other feature is that start or stop may be a negative number, which means it counts from the end of the array instead of the beginning. So:

a[-1]    # last item in the array
a[-2:]   # last two items in the array
a[:-2]   # everything except the last two items

Similarly, step may be a negative number:

a[::-1]    # all items in the array, reversed
a[1::-1]   # the first two items, reversed
a[:-3:-1]  # the last two items, reversed
a[-3::-1]  # everything except the last two items, reversed

Python is kind to the programmer if there are fewer items than you ask for. For example, if you ask for a[:-2] and a only contains one element, you get an empty list instead of an error. Sometimes you would prefer the error, so you have to be aware that this may happen.

Relation to slice() object

The slicing operator [] is actually being used in the above code with a slice() object using the : notation (which is only valid within []), i.e.:

a[start:stop:step]

is equivalent to:

a[slice(start, stop, step)]

Slice objects also behave slightly differently depending on the number of arguments, similarly to range(), i.e. both slice(stop) and slice(start, stop[, step]) are supported. To skip specifying a given argument, one might use None, so that e.g. a[start:] is equivalent to a[slice(start, None)] or a[::-1] is equivalent to a[slice(None, None, -1)].

While the : -based notation is very helpful for simple slicing, the explicit use of slice() objects simplifies the programmatic generation of slicing.

Ref: https://bit.ly/2MHaTp7