Display data in tables with python and Prettytable

In this article we look at a library that displays tabular data into ASCII tables called Prettytable

installation

As always you can install this from pypi like this

pip install prettytable

Example

Lets see some examples of this library in action

Basic example

In this example we display some countries, capitals of them and the continent they are in

from prettytable import PrettyTable  
  
# Creating a new table   
newTable = PrettyTable(["Country", "Capital", "Continent"])  
  
# Add rows  
newTable.add_row(["France", "Paris", "Europe"])  
newTable.add_row(["Germany", "Berlin", "Europe"])  
newTable.add_row(["Japan", "Tokyo", "Asia"])  
newTable.add_row(["Peru", "Lima", "South America"])  
newTable.add_row(["Egypyt", "Cairo", "Africa"])  
newTable.add_row(["China", "Beijing", "Asia"])  
  
print(newTable) 

When run you should see something that looks a bit like this

>>> %Run pretttablebasic.py
+---------+---------+---------------+
| Country | Capital |   Continent   |
+---------+---------+---------------+
|  France |  Paris  |     Europe    |
| Germany |  Berlin |     Europe    |
|  Japan  |  Tokyo  |      Asia     |
|   Peru  |   Lima  | South America |
|  Egypyt |  Cairo  |     Africa    |
|  China  | Beijing |      Asia     |
+---------+---------+---------------+

Import from CSV

You can also import a csv file and display the data in a Prettytable, this data is from another example when we were creating csv files in python

The data we have in the csv file is

Entry,Country,Capital
1,France,Paris
2,Germany,Berlin
3,Spain,Madrid
4,Italy,Rome
5,UK,London

Lets now display it

from prettytable import from_csv
with open("countries.csv") as fp:
    mytable = from_csv(fp)
print(mytable)

When run this displayed the following

>>> %Run perttytablefromcsv.py
+-------+---------+---------+
| Entry | Country | Capital |
+-------+---------+---------+
|   1   |  France |  Paris  |
|   2   | Germany |  Berlin |
|   3   |  Spain  |  Madrid |
|   4   |  Italy  |   Rome  |
|   5   |    UK   |  London |
+-------+---------+---------+

Adding data by columns

The first example we added data by row, you can also add it by column if you desire, like this

from prettytable import PrettyTable  
  
columns = ["Country", "Capital", "Continent"]  
  
newTable = PrettyTable()  
  
# Add Columns  
newTable.add_column(columns[0], ["France", "Germany", "Japan",  
                    "Peru", "Egypt", "China"])  
newTable.add_column(columns[1], ["Paris", "Berlin", "Tokyo", "Lima", "Cairo", "Beijing"])  
newTable.add_column(columns[2], ["Europe", "Europe", "Asia", "South America", "Africa", "Asia"])  

  
print(newTable)

When run, as expected the results are like this

>>> %Run prettytablecolumns.py
+---------+---------+---------------+
| Country | Capital |   Continent   |
+---------+---------+---------------+
|  France |  Paris  |     Europe    |
| Germany |  Berlin |     Europe    |
|  Japan  |  Tokyo  |      Asia     |
|   Peru  |   Lima  | South America |
|  Egypt  |  Cairo  |     Africa    |
|  China  | Beijing |      Asia     |
+---------+---------+---------------+

Deleting rows

We can also delete rows, take this example where we add the rows, print the table and then we delete rows we do not want and print the table again.

from prettytable import PrettyTable  
  
# Creating a new table   
newTable = PrettyTable(["Country", "Capital", "Continent"])  
  
# Add rows  
newTable.add_row(["France", "Paris", "Europe"])  
newTable.add_row(["Germany", "Berlin", "Europe"])  
newTable.add_row(["Japan", "Tokyo", "Asia"])  
newTable.add_row(["Peru", "Lima", "South America"])  
newTable.add_row(["Egypt", "Cairo", "Africa"])  
newTable.add_row(["China", "Beijing", "Asia"])  

print(newTable) 
  
newTable.del_row(1)  
newTable.del_row(2)  
newTable.del_row(3)  
  
print(newTable) 

Running this and you will see the following

>>> %Run prettytabledeleterow.py
+---------+---------+---------------+
| Country | Capital |   Continent   |
+---------+---------+---------------+
|  France |  Paris  |     Europe    |
| Germany |  Berlin |     Europe    |
|  Japan  |  Tokyo  |      Asia     |
|   Peru  |   Lima  | South America |
|  Egypt |  Cairo  |     Africa    |
|  China  | Beijing |      Asia     |
+---------+---------+---------------+
+---------+---------+-----------+
| Country | Capital | Continent |
+---------+---------+-----------+
|  France |  Paris  |   Europe  |
|  Japan  |  Tokyo  |    Asia   |
|  Egypt |  Cairo  |   Africa  |
+---------+---------+-----------+

Clear the entire table

You can clear the entire table with the clear_rows() method

from prettytable import PrettyTable  
  
# Creating a new table   
newTable = PrettyTable(["Country", "Capital", "Continent"])  
  
# Add rows  
newTable.add_row(["France", "Paris", "Europe"])  
newTable.add_row(["Germany", "Berlin", "Europe"])  
newTable.add_row(["Japan", "Tokyo", "Asia"])  
newTable.add_row(["Peru", "Lima", "South America"])  
newTable.add_row(["Egypyt", "Cairo", "Africa"])  
newTable.add_row(["China", "Beijing", "Asia"])  

newTable.clear_rows() 
  
print(newTable)  

When run this displays the following

>>> %Run prettytableclear.py
+---------+---------+-----------+
| Country | Capital | Continent |
+---------+---------+-----------+
+---------+---------+-----------+

There are several ways to get data out of a PrettyTable

• The del_row method takes an integer index of a single row to delete.
• The del_column method takes a field name of a single column to delete.
• The clear_rows method takes no arguments and deletes all the rows in the table – but keeps the field names as they were so you that you can repopulate it with the same kind of data.
• The clear method takes no arguments and deletes all rows and all field names. It’s not quite the same as creating a fresh table instance, though – style related settings, discussed later, are maintained.

Links

Our github examples

the github page of the library