import datetime
import pandas as pd
class MetaData:
"""
Meta Data Class for DAVE_data.
Parameters
----------
source_license
source_date
Attributes
----------
license : str
organisation : str
source_date : str
fetch_date : datetime.date
source meta : dict
"""
def __init__(self, source_license, source_date, organisation=None):
self.license = source_license
self.source_date = self._convert_date(source_date)
self.fetch_date = datetime.datetime.now(tz=datetime.timezone.utc)
self.source_url = None
self.organisation = organisation
self.source_meta = None
def _convert_date(self, value):
return ""
class Data:
"""
Attributes
----------
name
"""
def __init__(
self,
name,
description=None,
data=None,
meta=None,
polygon=None,
tags=None,
):
"""
Parameters
----------
data : geopandas.geoDataFrame
Data table with the original data.
organ
"""
self.name = name
self.description = description
self.data = data # geopandas.geoDataFrame
self.meta = meta # MetaData object
self.polygon = polygon # Searching polygon
self.tags = tags # list
def store(self):
pass
def restore(self):
pass
[docs]
def compute(args):
return max(args, key=len)
[docs]
def get_data(datatype):
"""
Parameters
----------
datatype :str
The category of your data.
Returns
-------
pandas.Series
Examples
--------
>>> get_data("building")
Here is your building data.
0 1
1 2
2 3
3 4
dtype: int64
"""
print(f"Here is your {datatype} data.")
return pd.Series([1, 2, 3, 4])