import redivis
​
# Perform a query on the Demo CMS Medicare data. Table at https://redivis.com/demo/datasets/1754/tables
query = redivis.query("""
    SELECT * FROM demo.cms_2014_medicare_data.home_health_agencies 
    WHERE state = 'CA'
""")
​
for row in query.list_rows():
    print(row['agency_name'])
​
# We can also use data frames
df = query.to_dataframe();
print(df)

import redivis
​
# Perform a query on the Demo CMS Medicare data. Table at https://redivis.com/demo/datasets/1754/tablesd
​
# We don't need to include fully-qualified table names if we scope our query to the appropriate dataset or project
​
query = (
    redivis
    .organization("Demo")
    .dataset("CMS 2014 Medicare Data")
    .query("""
        SELECT provider_name, average_total_payments 
        FROM nursing_facilities
        INNER JOIN outpatient_charges USING (provider_id)
        WHERE state = 'CA'
    """)
)
​
for row in query.list_rows():
    print(row.agency_name)
​
# We can also use data frames
df = query.to_dataframe();
print(df)

table = (
    redivis
    .organization("Demo")
    .dataset("CMS 2014 Medicare Data")
    .table("Hospice providers")
​
# We can specify an optional limit argument to only load some of the records
for row in table.list_rows(limit=100):
    print(row)
​
df = table.to_dataframe(limit=100)
print(df)

import redivis
​
dataset = redivis.user("your-username").dataset("some dataset")
​
# Could also create a dataset under an organization:
# dataset = redivis.organization("Demo organization").dataset("some dataset")
​
​
# public_access_level can be one of ('none', 'overview', 'metadata', 'sample', 'data')
dataset.create(public_access_level="overview")

import redivis
​
dataset = redivis.user("your-username").dataset("some dataset")
​
# Create a table on the dataset. Datasets may have multiple tables
# Merge strategy (append or replace) will affect whether future updates
#    are appended to or replace the existing table. This can also be modified at a later point.
​
table = (
    dataset
    .table("Table name")
    .create(description="Some description", upload_merge_strategy="replace")
)
​
# Upload a file to the table. You can upload multiple files to any table, and they'll be appended together
​
with open("path/to/file", "rb") as f:
    table.create_upload(name="tiny.csv", type="delimited", data=f)

import redivis
​
dataset = redivis.organization("Demo").dataset("some dataset")
dataset.release()

import redivis
​
dataset = redivis.user("your-username").dataset("some dataset")
​
# dataset.create_next_version will throw an error if a "next" version already exists,
# unless the ignore_if_exists argument is provided
dataset = dataset.create_next_version(ignore_if_exists=True)
​
# Upload new data to your table
with open("tiny.csv", "rb") as f:
    dataset.table("Table name").upload(name="tiny.csv", type="delimited", data=f)
​
dataset.release()