pandas-oop 0.0.4

Pandas dataframes with object oriented programming style

Pandas-Oop

(Also known as Poop), is a package that uses Pandas dataframes with object oriented programming style

Installation:

  pip install pandas-oop

Some examples

from pandas_oop import models

DB_CONNECTION = models.Connection('sqlite:///pandas_oop.db')

@models.sql(table='people', con=DB_CONNECTION)
@models.Data
class People(models.DataFrame):
    name = models.StringColumn(unique=True)
    age = models.IntegerColumn()
    money = models.FloatColumn()
    insertion_date = models.DateColumn(format='%d-%m-%Y')
    is_staff = models.BoolColumn(true='yes', false='no')

Now when instantiating this class, it will return a custom dataframe with all the functionalities of a Pandas dataframe and some others

people = People()
or
people = People(from_csv=DATA_FILE, delimiter=";")
or
people = People(from_sql_query='select * from people')
or
people = People(from_df=some_dataframe)

You can also save it to the database with the save() method (if the dtypes of the columns change, this will raise a ValidationError):

people.save()

You can upsert to the database and this will automatically look at the unique fields that were declared in the class

people.save(if_row_exists='update')
or
people.save(if_row_exists='ignore')

If you want to revalidate your dataframe (convert the columns dtypes to the type that was declared in the class), you can call the validate() method:

people.validate()

You can also validate from another class. For example, you can do something like this:

people = People(from_csv=DATA_FILE)
jobs = Jobs(from_sql_query='select * from jobs')
people_with_jobs = people.merge(jobs, on='name').validate(from_class=PeopleWithJobs)

This is the list of the overriten methods that return a pandas_oop custom dataframe

• 'isnull'
• 'head'
• 'abs'
• 'merge'

I will add more and more methods on this list.