[docs] - Improve Pandera guide

Summary

Describe the supported schema definition options (SchemaModel and DataFrameSchema)
Include info about column names containing spaces + using the DataFrameSchema approach
Include a link to the Pandera docs about DataFrameSchema: https://pandera.readthedocs.io/en/stable/

Issue from the Dagster Slack

This issue was generated from the slack conversation at: https://dagster.slack.com/archives/C01U954MEER/p1654667850385989?thread_ts=1654667850.385989&cid=C01U954MEER

Conversation excerpt

U03G3ND6C03: Hi all, I'm looking to use pandera to validate my SDA's. I'm looking to validate my raw data assets, which are straight dumps of the source data. However, there are spaces in the raw data field names, and I'm looking to use the dagster-pandera API which looks like below. Is there a way to overcome the spaces, preferably without changing the raw column names?

class Member_Schema(pa.SchemaModel):
  # col_name: Series[expected data type] - pa.Field()
  client number: Series[float64] = pa.Field()
  account number: Series[object] = pa.Field()

U015C9U9RLK: <@U018K0G2Y85> issue dagster-pandera doesn’t handle spaces in col names

U01GTMVMGQH: Hi Barry, dagster-pandera supports either of pandera’s formats for defining a dataframe schema-- the SchemaModel approach (which is illustrated in your snippet) and the pa.DataFrameSchema approach. For columns with spaces, you should use the pa.DataFrameSchema approach:

from dagster_pandera import pandera_schema_to_dagster_type
import pandera as pa
member_schema = pa.DataFrameSchema(
    {
        "client number": pa.Column(float),
        "account number": pa.Column(object)
    }
)

df_type = pandera_schema_to_dagster_type(member_schema)

See Pandera docs for more on the DataFrameSchema object.

U03G3ND6C03: Ok sweet! So am I able to pass in the member_schema to my asset like so? It should work for either format of the schema?

@asset(dagster_type=pandera_schema_to_dagster_type(Member_Schema))

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