dropna {SparkR} | R Documentation |
dropna, na.omit - Returns a new SparkDataFrame omitting rows with null values.
fillna - Replace null values.
dropna(x, how = c("any", "all"), minNonNulls = NULL, cols = NULL) na.omit(object, ...) fillna(x, value, cols = NULL) ## S4 method for signature 'SparkDataFrame' dropna(x, how = c("any", "all"), minNonNulls = NULL, cols = NULL) ## S4 method for signature 'SparkDataFrame' na.omit(object, how = c("any", "all"), minNonNulls = NULL, cols = NULL) ## S4 method for signature 'SparkDataFrame' fillna(x, value, cols = NULL)
x |
a SparkDataFrame. |
how |
"any" or "all".
if "any", drop a row if it contains any nulls.
if "all", drop a row only if all its values are null.
if |
minNonNulls |
if specified, drop rows that have less than
|
cols |
optional list of column names to consider. In |
object |
a SparkDataFrame. |
... |
further arguments to be passed to or from other methods. |
value |
value to replace null values with. Should be an integer, numeric, character or named list. If the value is a named list, then cols is ignored and value must be a mapping from column name (character) to replacement value. The replacement value must be an integer, numeric or character. |
A SparkDataFrame.
dropna since 1.4.0
na.omit since 1.5.0
fillna since 1.4.0
Other SparkDataFrame functions: SparkDataFrame-class
,
agg
, alias
,
arrange
, as.data.frame
,
attach,SparkDataFrame-method
,
broadcast
, cache
,
checkpoint
, coalesce
,
collect
, colnames
,
coltypes
,
createOrReplaceTempView
,
crossJoin
, cube
,
dapplyCollect
, dapply
,
describe
, dim
,
distinct
, dropDuplicates
,
drop
, dtypes
,
except
, explain
,
filter
, first
,
gapplyCollect
, gapply
,
getNumPartitions
, group_by
,
head
, hint
,
histogram
, insertInto
,
intersect
, isLocal
,
isStreaming
, join
,
limit
, localCheckpoint
,
merge
, mutate
,
ncol
, nrow
,
persist
, printSchema
,
randomSplit
, rbind
,
registerTempTable
, rename
,
repartition
, rollup
,
sample
, saveAsTable
,
schema
, selectExpr
,
select
, showDF
,
show
, storageLevel
,
str
, subset
,
summary
, take
,
toJSON
, unionByName
,
union
, unpersist
,
withColumn
, withWatermark
,
with
, write.df
,
write.jdbc
, write.json
,
write.orc
, write.parquet
,
write.stream
, write.text
## Not run:
##D sparkR.session()
##D path <- "path/to/file.json"
##D df <- read.json(path)
##D dropna(df)
## End(Not run)
## Not run:
##D sparkR.session()
##D path <- "path/to/file.json"
##D df <- read.json(path)
##D fillna(df, 1)
##D fillna(df, list("age" = 20, "name" = "unknown"))
## End(Not run)