Powerful package to prettify DataFrame into table.
Project description
What is it ?
Pandaspretty is a python package which provides you feature to convert your DataFrame in a good looking table, just in few steps. It aims to make everything simple.
What's new ?
- More customizable options
- New methods to create
Main features
- Custom styles
- Attractive tables
- Fast
- Automatically resizable cells
Where to get it
The source code is currently available on github
Installation from sources
To install it using PIP use the following command
pip install Pandaspretty
Usage
here is an example :
Let's suppose you have a DataFrame named df having value
Name | Class | Roll_no | Section | |
---|---|---|---|---|
0 | Ayush kumar | 12 | 8 | A |
1 | Prince kumar | 12 | 23 | A |
2 | Khushi singh | 12 | 18 | B |
3 | Prathisha | 12 | 23 | B |
Code to prettify your DataFrame (df)
import Pandaspretty as pp
[...]
prettyfied = pp.pretty(df)
print(prettyfied)
Output :
+----------------+---------+-----------+-----------+
| Name | Class | Roll_no | Section |
+----------------+---------+-----------+-----------+
| Ayush kumar | 12 | 8 | A |
+----------------+---------+-----------+-----------+
| Prince kumar | 12 | 23 | A |
+----------------+---------+-----------+-----------+
| Khushi singh | 12 | 18 | B |
+----------------+---------+-----------+-----------+
| Prathisha | 12 | 23 | B |
+----------------+---------+-----------+-----------+
More About it
Importing
import Pandaspretty as pp
Methods :
-
pretty(data = df, corner='%', separator=';', joins='=')
-
to_sql(data, index = True)
-
tabulate(data,index = True ,corner = '+', separator='|', joins='-')
Parameters :
-
data : Accepts a dataframe object.
-
index : Set index True/False to see the index of dataframe in table (default value is "True").
-
corner : Accepts character to be shown on corner points (default value is "+").
-
separator : Accepts character to be shown in place to the line separating two values (default value is "|").
-
joins : Accepts character to be shown in place to the line joining two rows (default value is "-").
Passing parameter
[...]
prettyfied = pp.pretty(data = df, index = True ,corner='%', separator=';', joins='=')
print(prettyfied)
Output :
%=====%================%=========%===========%===========%
; ; Name ; Class ; Roll_no ; Section ;
%=====%================%=========%===========%===========%
; 0 ; Ayush kumar ; 12 ; 8 ; A ;
%=====%================%=========%===========%===========%
; 1 ; Prince kumar ; 12 ; 23 ; A ;
%=====%================%=========%===========%===========%
; 2 ; Khushi singh ; 12 ; 18 ; B ;
%=====%================%=========%===========%===========%
; 3 ; Prathisha ; 12 ; 23 ; B ;
%=====%================%=========%===========%===========%
More examples
Example 1 :
Code
[...]
prettyfied = pp.pretty(data = df, corner='#')
print(prettyfied)
Output
#-----#----------------#---------#-----------#-----------#
| | Name | Class | Roll_no | Section |
#-----#----------------#---------#-----------#-----------#
| 0 | Ayush kumar | 12 | 8 | A |
#-----#----------------#---------#-----------#-----------#
| 1 | Prince kumar | 12 | 23 | A |
#-----#----------------#---------#-----------#-----------#
| 2 | Khushi singh | 12 | 18 | B |
#-----#----------------#---------#-----------#-----------#
| 3 | Prathisha | 12 | 23 | B |
#-----#----------------#---------#-----------#-----------#
Example 2:
Code
[...]
prettyfied = pp.pretty(data = df, index = False, separator='!')
print(prettyfied)
Output
+----------------+---------+-----------+-----------+
! Name ! Class ! Roll_no ! Section !
+----------------+---------+-----------+-----------+
! Ayush kumar ! 12 ! 8 ! A !
+----------------+---------+-----------+-----------+
! Prince kumar ! 12 ! 23 ! A !
+----------------+---------+-----------+-----------+
! Khushi singh ! 12 ! 18 ! B !
+----------------+---------+-----------+-----------+
! Prathisha ! 12 ! 23 ! B !
+----------------+---------+-----------+-----------+
Example 3 :
Code
[...]
prettyfied = pp.to_sql(data = df, index = False)
print(prettyfied)
Output
+----------------+---------+-----------+-----------+
| Name | Class | Roll_no | Section |
+----------------+---------+-----------+-----------+
| Ayush kumar | 12 | 8 | A |
| Prince kumar | 12 | 23 | A |
| Khushi singh | 12 | 18 | B |
| Prathisha | 12 | 23 | B |
+----------------+---------+-----------+-----------+
Example 4 :
Code
[...]
prettyfied = pp.to_sql(data = df, index = True)
print(prettyfied)
Output
+-----+----------------+---------+-----------+-----------+
| | Name | Class | Roll_no | Section |
+-----+----------------+---------+-----------+-----------+
| 0 | Ayush kumar | 12 | 8 | A |
| 1 | Prince kumar | 12 | 23 | A |
| 2 | Khushi singh | 12 | 18 | B |
| 3 | Prathisha | 12 | 23 | B |
+-----+----------------+---------+-----------+-----------+
Example 5 :
Code
[...]
prettyfied = pp.tabulate(data = df, separator=':')
print(prettyfied)
Output
+-----+----------------+---------+-----------+-----------+
: : Name : Class : Roll_no : Section :
+-----+----------------+---------+-----------+-----------+
: 0 : Ayush kumar : 12 : 8 : A :
: 1 : Prince kumar : 12 : 23 : A :
: 2 : Khushi singh : 12 : 18 : B :
: 3 : Prathisha : 12 : 23 : B :
+-----+----------------+---------+-----------+-----------+
Example 6 :
Code
[...]
prettyfied = pp.tabulate(data = df, separator=':', index = False, joins = '—', corner='#')
print(prettyfied)
Output
#————————————————#—————————#———————————#———————————#
: Name : Class : Roll_no : Section :
#————————————————#—————————#———————————#———————————#
: Ayush kumar : 12 : 8 : A :
: Prince kumar : 12 : 23 : A :
: Khushi singh : 12 : 18 : B :
: Prathisha : 12 : 23 : B :
#————————————————#—————————#———————————#———————————#
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