Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/8869#discussion_r41348491
--- Diff: R/pkg/R/stats.R ---
@@ -0,0 +1,102 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# DataFrameStatFunctions.R - Statistic functions for DataFrames.
+
+setOldClass("jobj")
+
+#' crosstab
+#'
+#' Computes a pair-wise frequency table of the given columns. Also known
as a contingency
+#' table. The number of distinct values for each column should be less
than 1e4. At most 1e6
+#' non-zero pair frequencies will be returned.
+#'
+#' @param col1 name of the first column. Distinct items will make the
first item of each row.
+#' @param col2 name of the second column. Distinct items will make the
column names of the output.
+#' @return a local R data.frame representing the contingency table. The
first column of each row
+#' will be the distinct values of `col1` and the column names will
be the distinct values
+#' of `col2`. The name of the first column will be `$col1_$col2`.
Pairs that have no
+#' occurrences will have zero as their counts.
+#'
+#' @rdname statfunctions
+#' @name crosstab
+#' @export
+#' @examples
+#' \dontrun{
+#' df <- jsonFile(sqlCtx, "/path/to/file.json")
+#' ct <- crosstab(df, "title", "gender")
+#' }
+setMethod("crosstab",
+ signature(x = "DataFrame", col1 = "character", col2 =
"character"),
+ function(x, col1, col2) {
+ statFunctions <- callJMethod(x@sdf, "stat")
+ sct <- callJMethod(statFunctions, "crosstab", col1, col2)
+ collect(dataFrame(sct))
+ })
+
+#' cov
+#'
+#' Calculate the sample covariance of two numerical columns of a DataFrame.
+#'
+#' @param x A SparkSQL DataFrame
+#' @param col1 the name of the first column
+#' @param col2 the name of the second column
+#' @return the covariance of the two columns.
+#'
+#' @rdname statfunctions
+#' @name cov
+#' @export
+#' @examples
+#'\dontrun{
+#' df <- jsonFile(sqlCtx, "/path/to/file.json")
+#' cov <- cov(df, "title", "gender")
+#' }
+setMethod("cov",
+ signature(x = "DataFrame", col1 = "character", col2 =
"character"),
+ function(x, col1, col2) {
+ statFunctions <- callJMethod(x@sdf, "stat")
+ callJMethod(statFunctions, "cov", col1, col2)
+ })
+
+#' corr
+#'
+#' Calculates the correlation of two columns of a DataFrame.
+#' Currently only supports the Pearson Correlation Coefficient.
+#' For Spearman Correlation, consider using RDD methods found in MLlib's
Statistics.
+#'
+#' @param x A SparkSQL DataFrame
+#' @param col1 the name of the first column
+#' @param col2 the name of the second column
+#' @param method Optional. A character specifying the method for
calculating the correlation.
+#' only "pearson" is allowed now.
+#' @return The Pearson Correlation Coefficient as a Double.
+#'
+#' @rdname statfunctions
+#' @name corr
+#' @export
+#' @examples
+#'\dontrun{
+#' df <- jsonFile(sqlCtx, "/path/to/file.json")
+#' corr <- corr(df, "title", "gender")
+#' corr <- corr(df, "title", "gender", "pearson")
--- End diff --
would it be better to say
`corr <- corr(df, "title", "gender", method = "pearson")`
?
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