accudata 1.0.1

Do you collect a heterogeneous data step by step?

Here you find a convinient solution of this problem. class AccumulativeData provides a simple interface to store data step by step. The data can be consisted of:

1. Numbers
2. Lists / arrays
3. Objects

You can store it as pickled object or Pandas Dataframe.

Installation

The module can be installed from pip

pip install accudata

For example

You have a social data collecting process. You must collect on every step heterogeneous data:

1. Name of a person
2. Age
3. Interests
4. Preferences by categories: food, pets, sport, politics

You can make a class:

from accudata import AccumulativeData

class PeopleAccData(AccumulativeData):
	def __init__(self):
		lists = ['name', 'age', 'interests']
		dicts = {'pref': ['food', 'pets', 'sport', 'politics]}
		super().__init__(lists=lists, dicts=dicts)

After that you can make an iterative collecting process as follows:

Data = PeopleAccData()
for item in raw_data:
	Data.next()
	# \\\ A complicated code to extract data
	name, age, interests, food, pets, sport, politics, _ = extract_data(item)
	Data.append(name, age, interests,
		    pref=[food, pets, sport, politics])
	

It is simple to get data:

names = Data.name
# Make the dataframe
dataframe = Data.todf()
print(dataframe.name)