Import Dataset with H2O Drive Connector¶

First, we'll initialize a client with our server credentials and store it in the variable dai.

In [22]:

import driverlessai
dai = driverlessai.Client(address='http://localhost:12345', username="py", password="py")

import driverlessai dai = driverlessai.Client(address='http://localhost:12345', username="py", password="py")

We can check that the H2O Drive connector has been enabled on the Driverless AI server.

In [23]:

dai.connectors.list()

dai.connectors.list()

Out[23]:

['upload', 'file', 'hdfs', 's3', 'recipe_file', 'recipe_url', 'h2o_drive']

In the following example, the data source, dataset CSV file, and name are specified.

In [24]:

dai.datasets.create(
    data_source="h2o_drive",
    name="dai_dataset_name",
    data="dataset_name_in_h2o_drive",
)

dataset_from_drive.head()

dai.datasets.create( data_source="h2o_drive", name="dai_dataset_name", data="dataset_name_in_h2o_drive", ) dataset_from_drive.head()

Complete 100.00% - [4/4] Computed stats for column isdepdelayed_rec

Out[24]:

fyear	fmonth	fdayofmonth	fdayofweek	deptime	arrtime	uniquecarrier	origin	dest	distance	isdepdelayed	isdepdelayed_rec
"f1987"	"f10"	"f15"	"f4"	729	903	"PS"	"SAN"	"SFO"	447	"NO"	-1
"f1987"	"f10"	"f17"	"f6"	741	918	"PS"	"SAN"	"SFO"	447	"YES"	1
"f1987"	"f10"	"f22"	"f4"	728	852	"PS"	"SAN"	"SFO"	447	"NO"	-1
"f1987"	"f10"	"f24"	"f6"	929	1052	"PS"	"SFO"	"RNO"	192	"YES"	1
"f1987"	"f10"	"f6"	"f2"	1505	1607	"PS"	"BUR"	"OAK"	325	"NO"	-1