Convert string to list python shapes how to#

Convert string to list python shapes how to#

Matrix for the columns of the current frame.Ī string indicating how to handle missing values. If this parameter is not given, then just compute the correlation Y ( H2OFrame) – If this parameter is provided, then compute correlation between the columns of yĪnd the columns of the current frame.

ntree_limit = nativeXGBoostParam ) cor ( y=None, na_rm=False, use=None, method='Pearson' ) ¶Ĭompute the correlation matrix of one or two H2OFrames. num_boost_round = nativeXGBoostParam ) > nativePred = nativeModel. convert_H2OXGBoostParams_2_XGBoostParams () > nativeXGBoostInput = data. predict ( data ) > nativeXGBoostParam = h2oModelD. train ( x = myX, y = y, training_frame = data ) > h2oPredictD = h2oModelD. This could have multiple types:Ī list/tuple of strings or numbers: create a single-column H2OFrame containing the contents of this list.Ī dictionary of > h2oModelD = H2OXGBoostEstimator ( ** h2oParamsD ) > h2oModelD. Object that will be converted to an H2OFrame. H2OFrame represents a mere handle to that data.Ĭreate a new H2OFrame object, possibly from some other object. One of the critical distinction is that theĭata is generally not held in memory, instead it is located on a (possibly remote) H2O cluster, and thus

H2OFrame is similar to pandas’ DataFrame, or R’s ame. H2OFrame ( python_obj=None, destination_frame=None, header=0, separator=', ', column_names=None, column_types=None, na_strings=None, skipped_columns=None ) ¶ Starting H2O and Inspecting the Cluster.