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  • Parameters
  • Return Object
  • Sample Usage
  • Best Practices / Tips

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  1. Rasgo Graveyard
  2. PyRasgo 0.3
  3. Collection Methods

read.collection_snapshot_data()

Load a snapshot of Rasgo Collection data into a pandas DataFrame

Parameters

id:int:ID of Rasgo Collection to return

snapshot_index:int:Index number referencing the snapshot to pull

filters:dict: (Optional)SQL filters to apply to model data

limit:int: (Optional)Number of records to return

Return Object

pandas DataFrame

Sample Usage

Return an entire collection snapshot without filters

rasgo = pyrasgo.connect(api_key)

df = pd.DataFrame
df = rasgo.read.collection_snapshot_data(7, 1)

Return a collection with filtered results

df = rasgo.read.collection_data(id=7,
                                snapshot_index=1, 
                                filters={"DATE":"2020-12-25"}
                                )
df = rasgo.read.collection_data(id=7, 
                                snapshot_index=1, 
                                filters={"DATE":">='2020-12-25'"}
                                )
df = rasgo.read.collection_data(id=7, 
                                snapshot_index=1, 
                                filters={"DATE":"2020-12-25",
                                         "FIPS":"BETWEEN '0000' AND '2000'"},
                                limit=100
                                )

Best Practices / Tips

NOTE: Filter syntax is a pyton dictionary: { k : v } Where: k= field to apply filter to v= valid ANSI sql logic

Supported SQL Filters are:

  • ">" Greater than

  • "<" Less than

  • ">=" Greater than or eqaul to

  • "<=" Less than or equal to

  • "<>" or "!=" Does not equal

  • "IN (x,y,z)" In (list)

  • "BETWEEN x AND y" Between 2 values

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Last updated 3 years ago

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