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Creating Tables with PrettyTable Library – Python
  • Last Updated : 18 Aug, 2020
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PrettyTable class inside the prettytable library is used to create relational tables in Python. For example, the table below has been created using this library, in Command Prompt on Windows.

Installing the Library:

pip install prettytable 

Let’s create the sample table using the prettytable library in Python.

Creating the Table: Row-Wise



Python3




from prettytable import PrettyTable
  
# Specify the Column Names while initializing the Table
myTable = PrettyTable(["Student Name", "Class", "Section", "Percentage"])
  
# Add rows
myTable.add_row(["Leanord", "X", "B", "91.2 %"])
myTable.add_row(["Penny", "X", "C", "63.5 %"])
myTable.add_row(["Howard", "X", "A", "90.23 %"])
myTable.add_row(["Bernadette", "X", "D", "92.7 %"])
myTable.add_row(["Sheldon", "X", "A", "98.2 %"])
myTable.add_row(["Raj", "X", "B", "88.1 %"])
myTable.add_row(["Amy", "X", "B", "95.0 %"])
  
print(myTable)

 
 

Output
+--------------+-------+---------+------------+
| Student Name | Class | Section | Percentage |
+--------------+-------+---------+------------+
|   Leanord    |   X   |    B    |   91.2%    |
|    Penny     |   X   |    C    |   63.5%    |
|    Howard    |   X   |    A    |   90.23%   |
|  Bernadette  |   X   |    D    |   92.7%    |
|   Sheldon    |   X   |    A    |   98.2%    |
|     Raj      |   X   |    B    |   88.1%    |
|     Amy      |   X   |    B    |   95.0%    |
+--------------+-------+---------+------------+

 

Creating the Table: Column-Wise

Python3




from prettytable import PrettyTable
  
columns = ["Student Name", "Class", "Section", "Percentage"]
  
myTable = PrettyTable()
  
# Add Columns
myTable.add_column(columns[0], ["Leanord", "Penny", "Howard",
                       "Bernadette", "Sheldon", "Raj", "Amy"])
myTable.add_column(columns[1], ["X", "X", "X", "X", "X", "X", "X"])
myTable.add_column(columns[2], ["B", "C", "A", "D", "A", "B", "B"])
myTable.add_column(columns[3], ["91.2 %", "63.5 %", "90.23 %", "92.7 %"
                                          "98.2 %", "88.1 %", "95.0 %"])
  
print(myTable)

 
 

Output
+--------------+-------+---------+------------+
| Student Name | Class | Section | Percentage |
+--------------+-------+---------+------------+
|   Leanord    |   X   |    B    |   91.2%    |
|    Penny     |   X   |    C    |   63.5%    |
|    Howard    |   X   |    A    |   90.23%   |
|  Bernadette  |   X   |    D    |   92.7%    |
|   Sheldon    |   X   |    A    |   98.2%    |
|     Raj      |   X   |    B    |   88.1%    |
|     Amy      |   X   |    B    |   95.0%    |
+--------------+-------+---------+------------+

Deleting Rows

myTable.del_row(0)

This will delete the first row from the table, i.e, the rows follow standard indexing starting from index 0. 

Clearing the Table

myTable.clear_rows()

This will clear the entire table (Only the Column Names would remain).

There are many advanced features associated with these tables, like converting these tables to HTML or converting a CSV to a PrettyTable. Those functions would be covered in a separate article.

Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course.

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