https://github.com/mayasmess/pandas-oop
⚡️ Pandas dataframes with object oriented programming style (not maintained)
https://github.com/mayasmess/pandas-oop
pandas python sql
Last synced: 9 months ago
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⚡️ Pandas dataframes with object oriented programming style (not maintained)
- Host: GitHub
- URL: https://github.com/mayasmess/pandas-oop
- Owner: MayasMess
- License: mit
- Created: 2022-03-28T19:48:57.000Z (about 4 years ago)
- Default Branch: master
- Last Pushed: 2024-03-17T14:20:09.000Z (about 2 years ago)
- Last Synced: 2025-06-25T20:36:46.172Z (9 months ago)
- Topics: pandas, python, sql
- Language: Python
- Homepage:
- Size: 204 KB
- Stars: 11
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Pandas-Oop (not maintained, see https://github.com/MayasMess/panorma it's simpler)
(Also known as Poop), is a package that uses Pandas dataframes with object oriented programming style
Installation:
-
```shell script
pip install pandas-oop
```
Some examples
-
```python
from pandas_oop import models
from pandas_oop.fields import StringColumn, IntegerColumn, FloatColumn, DateColumn, BoolColumn
```
```python
DB_CONNECTION = models.Connection('sqlite:///pandas_oop.db') # this is the same con_string for sqlalchemy engine
```
```python
@models.sql(table='people', con=DB_CONNECTION) # Use this decorator if you want to connect your class to a database
@models.Data
class People(models.DataFrame):
name = StringColumn(unique=True)
age = IntegerColumn()
money = FloatColumn(target_name="coins") # target_name if the name in the csv or table is coins and you want to have a different variable name
insertion_date = DateColumn(format='%d-%m-%Y')
is_staff = 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
```python
people = People()
"""-----------------------------------------------------------"""
people = People(from_csv=DATA_FILE, delimiter=";")
"""-----------------------------------------------------------"""
people = People(from_sql_query='select * from people')
"""-----------------------------------------------------------"""
people = People(from_df=some_dataframe)
"""-----------------------------------------------------------"""
people = People(from_iterator=some_function_that_yield_values)
"""-----------------------------------------------------------"""
for people_chunk in People(from_csv=DATA_FILE, delimiter=";", chunksize=10):
...
```
example of function that yield values:
```python
def some_function_that_yield_values():
while something:
...
yield name, age, money, insertion_date, is_staff
```
You can also save it to the database with the save() method (if the dtypes of the columns change, this will raise a
ValidationError):
```python
people.save()
```
You can upsert to the database and this will automatically look at the unique fields that were declared in the class
```python
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:
```python
people.validate()
```
You can also validate from another class. For example, you can do something like this:
```python
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'
- 'loc' and dataframe slicing
I will add more and more methods on this list.
New features
-
Alembic Database migration support added:
- On your main application package, import Base (this is a declarative_base from sqlalchemy)
```python
from pandas_oop import Base
```
- Add this configuration on the env.py file of your alembic config
```python
from your_app import Base
target_metadata = Base.metadata
```
- And finaly, update your database url on your alembic.ini file