Fill NAs -------- Use this function to fill in NA values in a sequential manner up to a specified limit. When using this function, you will specify whether the method to fill the NAs should go forward (default) or backward , whether the NAs should be filled along rows (default) or columns, and the maximum number of consecutive NAs to fill (defaults to 1). .. example-code:: .. code-block:: r library(h2o) h2o.init() # Create a random data frame with 6 rows and 2 columns. # Specify that no more than 70% of the values are NAs. fr.with.nas = h2o.createFrame(categorical_fraction=0.0, missing_fraction=0.7, rows=6, cols=2, seed=123) fr.with.nas C1 C2 1 NaN NaN 2 -77.10471 -93.64087 3 -13.65926 57.44389 4 NaN NaN 5 39.10130 NaN 6 NaN 55.43136 [6 rows x 2 columns] # Forward fill a row. In R, the values for axis are 1 (row-wise) and 2 (column-wise) fr <- h2o.fillna(fr.with.nas, "forward", axis=1, maxlen=1L) fr C1 C2 1 NaN NaN 2 -77.10471 -93.64087 3 -13.65926 57.44389 4 NaN NaN 5 39.10130 39.10130 6 NaN 55.43136 [6 rows x 2 columns] .. code-block:: python import h2o h2o.init() # Create a random data frame with 10 rows and 3 columns. # Specify that no more than 20% of the values are NAs. df = h2o.create_frame(rows=10, cols=3, real_fraction=1.0, real_range=100, missing_fraction=0.2, seed=123) df C1 C2 C3 -------- -------- -------- nan nan -77.1047 -93.6409 -13.6593 57.4439 -93.71 25.4342 39.1013 -95.8291 -92.4271 55.4314 84.6372 -43.4759 53.1715 -57.9583 27.4148 -26.9013 83.0921 -62.7819 -91.9426 -77.9814 64.3228 -93.954 nan -80.6142 nan 27.1672 60.5492 -13.2275 [10 rows x 3 columns] # Forward fill a row. In Python, the values for axis are 0 (row-wise) and 1 (column-wise) filled = df.fillna(method="forward",axis=0,maxlen=1) filled filled C1 C2 C3 -------- -------- -------- nan nan -77.1047 -93.6409 -13.6593 57.4439 -93.71 25.4342 39.1013 -95.8291 -92.4271 55.4314 84.6372 -43.4759 53.1715 -57.9583 27.4148 -26.9013 83.0921 -62.7819 -91.9426 -77.9814 64.3228 -93.954 -77.9814 -80.6142 -93.954 27.1672 60.5492 -13.2275 [10 rows x 3 columns]