diff --git a/core/src/main/scala/doric/syntax/BinaryColumns.scala b/core/src/main/scala/doric/syntax/BinaryColumns.scala
index f6e64633d..bb5440c25 100644
--- a/core/src/main/scala/doric/syntax/BinaryColumns.scala
+++ b/core/src/main/scala/doric/syntax/BinaryColumns.scala
@@ -19,6 +19,7 @@ private[syntax] trait BinaryColumns {
       * as a 32 character hex string.
       *
       * @group Binary Type
+      * @see [[org.apache.spark.sql.functions.md5]]
       */
     def md5: StringColumn = column.elem.map(f.md5).toDC
 
@@ -27,6 +28,7 @@ private[syntax] trait BinaryColumns {
       * as a 40 character hex string.
       *
       * @group Binary Type
+      * @see [[org.apache.spark.sql.functions.sha1]]
       */
     def sha1: StringColumn = column.elem.map(f.sha1).toDC
 
@@ -36,6 +38,7 @@ private[syntax] trait BinaryColumns {
       *
       * @throws java.lang.IllegalArgumentException if numBits is not in the permitted values
       * @group Binary Type
+      * @see [[org.apache.spark.sql.functions.sha2]]
       */
     def sha2(numBits: Int): StringColumn =
       column.elem.map(x => f.sha2(x, numBits)).toDC
@@ -45,6 +48,7 @@ private[syntax] trait BinaryColumns {
       * returns the value as a long column.
       *
       * @group Binary Type
+      * @see [[org.apache.spark.sql.functions.crc32]]
       */
     def crc32: LongColumn = column.elem.map(f.crc32).toDC
 
@@ -53,6 +57,7 @@ private[syntax] trait BinaryColumns {
       * This is the reverse of unbase64.
       *
       * @group Binary Type
+      * @see [[org.apache.spark.sql.functions.base64]]
       */
     def base64: StringColumn = column.elem.map(f.base64).toDC
 
@@ -62,6 +67,7 @@ private[syntax] trait BinaryColumns {
       * If either argument is null, the result will also be null.
       *
       * @group Binary Type
+      * @see [[org.apache.spark.sql.functions.decode]]
       */
     def decode(charset: StringColumn): StringColumn =
       (column.elem, charset.elem)
diff --git a/core/src/main/scala/doric/syntax/BooleanColumns.scala b/core/src/main/scala/doric/syntax/BooleanColumns.scala
index 51c0814b9..e9c683661 100644
--- a/core/src/main/scala/doric/syntax/BooleanColumns.scala
+++ b/core/src/main/scala/doric/syntax/BooleanColumns.scala
@@ -67,6 +67,7 @@ private[syntax] trait BooleanColumns {
       *
       * @throws java.lang.RuntimeException if the condition is false
       * @group Boolean Type
+      * @see [[org.apache.spark.sql.functions.assert_true(c:org\.apache\.spark\.sql\.Column):* org.apache.spark.sql.functions.assert_true]]
       */
     def assertTrue: NullColumn = column.elem.map(f.assert_true).toDC
 
@@ -75,6 +76,7 @@ private[syntax] trait BooleanColumns {
       *
       * @throws java.lang.RuntimeException if the condition is false
       * @group Boolean Type
+      * @see [[org.apache.spark.sql.functions.assert_true(c:org\.apache\.spark\.sql\.Column,e:* org.apache.spark.sql.functions.assert_true]]
       */
     def assertTrue(msg: StringColumn): NullColumn =
       (column.elem, msg.elem).mapN(f.assert_true).toDC
diff --git a/core/src/main/scala/doric/syntax/CommonColumns.scala b/core/src/main/scala/doric/syntax/CommonColumns.scala
index 887e2a266..89fa1b824 100644
--- a/core/src/main/scala/doric/syntax/CommonColumns.scala
+++ b/core/src/main/scala/doric/syntax/CommonColumns.scala
@@ -31,6 +31,7 @@ private[syntax] trait CommonColumns extends ColGetters[NamedDoricColumn] {
     *   the DoricColumns to coalesce
     * @return
     *   the first column that is not null, or null if all inputs are null.
+    * @see [[org.apache.spark.sql.functions.coalesce]]
     */
   def coalesce[T](cols: DoricColumn[T]*): DoricColumn[T] =
     cols.map(_.elem).toList.sequence.map(f.coalesce(_: _*)).toDC
@@ -39,6 +40,7 @@ private[syntax] trait CommonColumns extends ColGetters[NamedDoricColumn] {
     * Calculates the hash code of given columns, and returns the result as an integer column.
     *
     * @group All Types
+    * @see [[org.apache.spark.sql.functions.hash]]
     */
   def hash(cols: DoricColumn[_]*): IntegerColumn =
     cols.map(_.elem).toList.sequence.map(f.hash(_: _*)).toDC
@@ -48,6 +50,7 @@ private[syntax] trait CommonColumns extends ColGetters[NamedDoricColumn] {
     * variant of the xxHash algorithm, and returns the result as a long column.
     *
     * @group All Types
+    * @see [[org.apache.spark.sql.functions.xxhash64]]
     */
   def xxhash64(cols: DoricColumn[_]*): LongColumn =
     cols.map(_.elem).toList.sequence.map(f.xxhash64(_: _*)).toDC
@@ -181,6 +184,7 @@ private[syntax] trait CommonColumns extends ColGetters[NamedDoricColumn] {
       *   literals to compare to
       * @return
       *   Boolean DoricColumn with the comparation logic.
+      * @see [[org.apache.spark.sql.Column.isin]]
       */
     def isIn(elems: T*): BooleanColumn = column.elem.map(_.isin(elems: _*)).toDC
 
@@ -189,6 +193,7 @@ private[syntax] trait CommonColumns extends ColGetters[NamedDoricColumn] {
       * @group All Types
       * @return
       *   Boolean DoricColumn
+      * @see [[org.apache.spark.sql.Column.isNull]]
       */
     def isNull: BooleanColumn = column.elem.map(_.isNull).toDC
 
@@ -197,6 +202,7 @@ private[syntax] trait CommonColumns extends ColGetters[NamedDoricColumn] {
       * @group All Types
       * @return
       *   Boolean DoricColumn
+      * @see [[org.apache.spark.sql.Column.isNotNull]]
       */
     def isNotNull: BooleanColumn = column.elem.map(_.isNotNull).toDC
 
diff --git a/core/src/main/scala/doric/syntax/DateColumns.scala b/core/src/main/scala/doric/syntax/DateColumns.scala
index 4b21001ff..c30e43889 100644
--- a/core/src/main/scala/doric/syntax/DateColumns.scala
+++ b/core/src/main/scala/doric/syntax/DateColumns.scala
@@ -15,6 +15,7 @@ private[syntax] trait DateColumns {
     * All calls of current_date within the same query return the same value.
     *
     * @group Date Type
+    * @see [[org.apache.spark.sql.functions.current_date]]
     */
   def currentDate(): DateColumn = f.current_date().asDoric[Date]
 
@@ -32,6 +33,7 @@ private[syntax] trait DateColumns {
       *   Date column after adding months
       * @note
       *   Timestamp columns will be truncated to Date column
+      * @see [[org.apache.spark.sql.functions.add_months(startDate:org\.apache\.spark\.sql\.Column,numMonths:org\.apache\.spark\.sql\.Column):* org.apache.spark.sql.functions.add_months]]
       */
     def addMonths(nMonths: IntegerColumn): DateColumn =
       (column.elem, nMonths.elem).mapN(f.add_months).toDC
@@ -44,6 +46,7 @@ private[syntax] trait DateColumns {
       * @note
       *   Timestamp columns will be truncated to Date column
       * @group Date & Timestamp Type
+      * @see [[org.apache.spark.sql.functions.date_add(start:org\.apache\.spark\.sql\.Column,days:org\.apache\.spark\.sql\.Column):* org.apache.spark.sql.functions.date_add]]
       */
     def addDays(days: IntegerColumn): DateColumn =
       (column.elem, days.elem).mapN(f.date_add).toDC
@@ -59,6 +62,7 @@ private[syntax] trait DateColumns {
       *   Use specialized functions like 'year' whenever possible as they benefit from a
       *   specialized implementation.
       * @group Date & Timestamp Type
+      * @see [[org.apache.spark.sql.functions.date_format]]
       */
     def format(format: StringColumn): StringColumn =
       (column.elem, format.elem)
@@ -75,6 +79,7 @@ private[syntax] trait DateColumns {
       * @note
       *   Timestamp columns will be truncated to Date column
       * @group Date & Timestamp Type
+      * @see [[org.apache.spark.sql.functions.date_sub(start:org\.apache\.spark\.sql\.Column,days:org\.apache\.spark\.sql\.Column):* org.apache.spark.sql.functions.date_sub]]
       */
     def subDays(days: IntegerColumn): DateColumn =
       (column.elem, days.elem).mapN(f.date_sub).toDC
@@ -85,6 +90,7 @@ private[syntax] trait DateColumns {
       * @param dateCol
       *   A Date or Timestamp column
       * @group Date & Timestamp Type
+      * @see [[org.apache.spark.sql.functions.datediff]]
       */
     def diff(dateCol: DoricColumn[T]): IntegerColumn =
       (column.elem, dateCol.elem)
@@ -95,6 +101,7 @@ private[syntax] trait DateColumns {
       * Extracts the day of the month as an integer from a given date.
       *
       * @group Date & Timestamp Type
+      * @see [[org.apache.spark.sql.functions.dayofmonth]]
       */
     def dayOfMonth: IntegerColumn = column.elem.map(f.dayofmonth).toDC
 
@@ -103,6 +110,7 @@ private[syntax] trait DateColumns {
       * Ranges from 1 for a Sunday through to 7 for a Saturday
       *
       * @group Date & Timestamp Type
+      * @see [[org.apache.spark.sql.functions.dayofweek]]
       */
     def dayOfWeek: IntegerColumn = column.elem.map(f.dayofweek).toDC
 
@@ -110,6 +118,7 @@ private[syntax] trait DateColumns {
       * Extracts the day of the year as an integer from a given date.
       *
       * @group Date & Timestamp Type
+      * @see [[org.apache.spark.sql.functions.dayofyear]]
       */
     def dayOfYear: IntegerColumn = column.elem.map(f.dayofyear).toDC
 
@@ -117,6 +126,7 @@ private[syntax] trait DateColumns {
       * Sets the moment to the last day of the same month.
       *
       * @group Date & Timestamp Type
+      * @see [[org.apache.spark.sql.functions.last_day]]
       */
     def endOfMonth: DateColumn = lastDayOfMonth
 
@@ -126,6 +136,7 @@ private[syntax] trait DateColumns {
       * month in July 2015.
       *
       * @group Date & Timestamp Type
+      * @see [[org.apache.spark.sql.functions.last_day]]
       */
     def lastDayOfMonth: DateColumn = column.elem.map(f.last_day).toDC
 
@@ -133,6 +144,7 @@ private[syntax] trait DateColumns {
       * Extracts the month as an integer from a given date.
       *
       * @group Date & Timestamp Type
+      * @see [[org.apache.spark.sql.functions.month]]
       */
     def month: IntegerColumn = column.elem.map(f.month).toDC
 
@@ -143,7 +155,7 @@ private[syntax] trait DateColumns {
       * of their respective months. Otherwise, the difference is calculated assuming 31 days per month.
       *
       * For example:
-      * {{{
+      * @example {{{
       * Date("2017-11-14").monthsBetween(Date("2017-07-14"))                              // returns 4.0
       * Date("2017-01-01").monthsBetween(Date("2017-01-10"))                              // returns 0.29032258
       * Timestamp("2017-06-01 00:00:00").monthsBetween(Timestamp("2017-06-16 12:00:00"))  // returns -0.5
@@ -152,6 +164,7 @@ private[syntax] trait DateColumns {
       * @param dateCol
       *   Date or Timestamp column
       * @group Date & Timestamp Type
+      * @see [[org.apache.spark.sql.functions.months_between(end:org\.apache\.spark\.sql\.Column,start:org\.apache\.spark\.sql\.Column):* org.apache.spark.sql.functions.months_between]]
       */
     def monthsBetween(dateCol: DoricColumn[T]): DoubleColumn =
       (column.elem, dateCol.elem).mapN(f.months_between).toDC
@@ -165,6 +178,7 @@ private[syntax] trait DateColumns {
       *   If `roundOff` is set to true, the result is rounded off to 8 digits;
       *   it is not rounded otherwise.
       * @group Date & Timestamp Type
+      * @see [[org.apache.spark.sql.functions.months_between(end:org\.apache\.spark\.sql\.Column,start:org\.apache\.spark\.sql\.Column,roundOff:* org.apache.spark.sql.functions.months_between]]
       */
     def monthsBetween(
         dateCol: DoricColumn[T],
@@ -180,14 +194,15 @@ private[syntax] trait DateColumns {
       * Returns the first date which is later than the value of the `date` column that is on the
       * specified day of the week.
       *
-      * For example, `Date("2015-07-27").nextDay("Sunday")` returns Date("2015-08-02") because
-      * that is the first Sunday after 2015-07-27.
+      * @example For example, `Date("2015-07-27").nextDay("Sunday")` returns Date("2015-08-02")
+      * because that is the first Sunday after 2015-07-27.
       *
       * @param dayOfWeek
       *   Case insensitive, and accepts: "Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"
       * @note
       *   Timestamp columns will be truncated to Date column
       * @group Date & Timestamp Type
+      * @see [[org.apache.spark.sql.functions.next_day]]
       */
     def nextDay(dayOfWeek: StringColumn): DateColumn =
       (column.elem, dayOfWeek.elem)
@@ -200,28 +215,30 @@ private[syntax] trait DateColumns {
       * Extracts the quarter as an integer from a given date.
       *
       * @group Date & Timestamp Type
+      * @see [[org.apache.spark.sql.functions.quarter]]
       */
     def quarter: IntegerColumn = column.elem.map(f.quarter).toDC
 
     /**
       * Returns date truncated to the unit specified by the format.
       *
-      * For example, `Timestamp("2018-11-19 12:01:19").trunc("year")` returns Date("2018-01-01")
+      * @example For example, `Timestamp("2018-11-19 12:01:19").trunc("year")` returns Date("2018-01-01")
       *
       * @param format
-      *   if date:
-      *     * 'year', 'yyyy', 'yy' to truncate by year,
-      *     * 'month', 'mon', 'mm' to truncate by month
-      *     Other options are: 'week', 'quarter'
-      *   if timestamp:
-      *     * 'year', 'yyyy', 'yy' to truncate by year,
-      *     * 'month', 'mon', 'mm' to truncate by month,
-      *     * 'day', 'dd' to truncate by day,
-      *     Other options are:
-      *     * 'microsecond', 'millisecond', 'second', 'minute', 'hour', 'week', 'quarter'
+      *   - if <b>date</b>:
+      *     - 'year', 'yyyy', 'yy' to truncate by year,
+      *     - 'month', 'mon', 'mm' to truncate by month
+      *     - __Other options are__: 'week', 'quarter'
+      *   - if <b>timestamp</b>:
+      *     - 'year', 'yyyy', 'yy' to truncate by year,
+      *     - 'month', 'mon', 'mm' to truncate by month,
+      *     - 'day', 'dd' to truncate by day,
+      *     - __Other options are__:  'microsecond', 'millisecond', 'second', 'minute', 'hour', 'week', 'quarter'
       * @note
       *   Timestamp columns will be truncated to Date column
       * @group Date & Timestamp Type
+      * @see [[org.apache.spark.sql.functions.trunc]]
+      * @see [[org.apache.spark.sql.functions.date_trunc]]
       */
     def truncate(format: StringColumn): DoricColumn[T] =
       (column.elem, format.elem)
@@ -243,6 +260,7 @@ private[syntax] trait DateColumns {
       *   A long
       *
       * @group Date & Timestamp Type
+      * @see [[org.apache.spark.sql.functions.unix_timestamp(s:org\.apache\.spark\.sql\.Column):* org.apache.spark.sql.functions.unix_timestamp]]
       */
     def unixTimestamp: LongColumn = column.elem.map(f.unix_timestamp).toDC
 
@@ -253,6 +271,7 @@ private[syntax] trait DateColumns {
       * as defined by ISO 8601
       *
       * @group Date & Timestamp Type
+      * @see [[org.apache.spark.sql.functions.weekofyear]]
       */
     def weekOfYear: IntegerColumn = column.elem.map(f.weekofyear).toDC
 
@@ -260,6 +279,7 @@ private[syntax] trait DateColumns {
       * Extracts the year as an integer from a given date.
       *
       * @group Date & Timestamp Type
+      * @see [[org.apache.spark.sql.functions.year]]
       */
     def year: IntegerColumn = column.elem.map(f.year).toDC
 
@@ -267,6 +287,7 @@ private[syntax] trait DateColumns {
       * Transform date to timestamp
       *
       * @group Date Type
+      * @see [[org.apache.spark.sql.functions.to_timestamp(s:org\.apache\.spark\.sql\.Column):* org.apache.spark.sql.functions.to_timestamp]]
       */
     def toTimestamp: TimestampColumn = column.elem.map(f.to_timestamp).toDC
 
@@ -274,6 +295,7 @@ private[syntax] trait DateColumns {
       * Transform date to Instant
       *
       * @group Date Type
+      * @see [[org.apache.spark.sql.functions.to_timestamp(s:org\.apache\.spark\.sql\.Column):* org.apache.spark.sql.functions.to_timestamp]]
       */
     def toInstant: InstantColumn = column.elem.map(f.to_timestamp).toDC
   }
diff --git a/core/src/main/scala/doric/syntax/StringColumns.scala b/core/src/main/scala/doric/syntax/StringColumns.scala
index ab6d98004..c29a472ee 100644
--- a/core/src/main/scala/doric/syntax/StringColumns.scala
+++ b/core/src/main/scala/doric/syntax/StringColumns.scala
@@ -17,6 +17,7 @@ private[syntax] trait StringColumns {
     * @return
     *   a reference of a single DoricColumn with all strings concatenated. If at
     *   least one is null will return null.
+    * @see [[org.apache.spark.sql.functions.concat]]
     */
   def concat(cols: StringColumn*): StringColumn =
     cols.map(_.elem).toList.sequence.map(f.concat(_: _*)).toDC
@@ -63,6 +64,7 @@ private[syntax] trait StringColumns {
     * @return
     *   Formats the arguments in printf-style and returns the result as a string
     *   column.
+    * @see [[org.apache.spark.sql.functions.format_string]]
     */
   def formatString(
       format: StringColumn,
@@ -109,6 +111,7 @@ private[syntax] trait StringColumns {
       * and returns the result as an int column.
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.ascii]]
       */
     def ascii: IntegerColumn = s.elem.map(f.ascii).toDC
 
@@ -116,11 +119,12 @@ private[syntax] trait StringColumns {
       * Returns a new string column by converting the first letter of each word
       * to uppercase. Words are delimited by whitespace.
       *
-      * For example, "hello world" will become "Hello World".
+      * @example For example, "hello world" will become "Hello World".
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.initcap]]
       */
-    def initcap: StringColumn = s.elem.map(f.initcap).toDC
+    def initCap: StringColumn = s.elem.map(f.initcap).toDC
 
     /**
       * Locate the position of the first occurrence of substr column in the
@@ -130,8 +134,9 @@ private[syntax] trait StringColumns {
       * @note
       *   The position is not zero based, but 1 based index. Returns 0 if substr
       *   could not be found in str.
+      * @see [[org.apache.spark.sql.functions.instr]]
       */
-    def instr(substring: StringColumn): IntegerColumn =
+    def inStr(substring: StringColumn): IntegerColumn =
       (s.elem, substring.elem)
         .mapN((str, substr) => {
           new Column(StringInstr(str.expr, substr.expr))
@@ -144,6 +149,7 @@ private[syntax] trait StringColumns {
       * spaces. The length of binary strings includes binary zeros.
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.length]]
       */
     def length: IntegerColumn = s.elem.map(f.length).toDC
 
@@ -151,6 +157,7 @@ private[syntax] trait StringColumns {
       * Computes the Levenshtein distance of the two given string columns.
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.levenshtein]]
       */
     def levenshtein(dc: StringColumn): IntegerColumn =
       (s.elem, dc.elem).mapN(f.levenshtein).toDC
@@ -163,6 +170,8 @@ private[syntax] trait StringColumns {
       * @note
       *   The position is not zero based, but 1 based index. returns 0 if substr
       *   could not be found in str.
+      * @see org.apache.spark.sql.functions.locate
+      * @todo scaladoc link (issue #135)
       */
     def locate(
         substr: StringColumn,
@@ -178,6 +187,7 @@ private[syntax] trait StringColumns {
       * Converts a string column to lower case.
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.lower]]
       */
     def lower: StringColumn = s.elem.map(f.lower).toDC
 
@@ -187,6 +197,7 @@ private[syntax] trait StringColumns {
       * characters.
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.lpad]]
       */
     def lpad(len: IntegerColumn, pad: StringColumn): StringColumn =
       (s.elem, len.elem, pad.elem)
@@ -199,6 +210,7 @@ private[syntax] trait StringColumns {
       * Trim the spaces from left end for the specified string value.
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.ltrim(e:org\.apache\.spark\.sql\.Column):* org.apache.spark.sql.functions.ltrim]]
       */
     def ltrim: StringColumn = s.elem.map(f.ltrim).toDC
 
@@ -207,6 +219,7 @@ private[syntax] trait StringColumns {
       * string column.
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.ltrim(e:org\.apache\.spark\.sql\.Column,trimString:* org.apache.spark.sql.functions.ltrim]]
       */
     def ltrim(trimString: StringColumn): StringColumn =
       (s.elem, trimString.elem)
@@ -220,6 +233,7 @@ private[syntax] trait StringColumns {
       * byte position `pos` of `src` and proceeding for `len` bytes.
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.overlay(src:org\.apache\.spark\.sql\.Column,replace:org\.apache\.spark\.sql\.Column,pos:org\.apache\.spark\.sql\.Column,len:org\.apache\.spark\.sql\.Column):* org.apache.spark.sql.functions.overlay]]
       */
     def overlay(
         replace: StringColumn,
@@ -237,6 +251,7 @@ private[syntax] trait StringColumns {
       *
       * @throws java.lang.IllegalArgumentException if the specified group index exceeds the group count of regex
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.regexp_extract]]
       */
     def regexpExtract(
         exp: StringColumn,
@@ -253,6 +268,7 @@ private[syntax] trait StringColumns {
       * with replacement.
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.regexp_replace(e:org\.apache\.spark\.sql\.Column,pattern:org\.apache\.spark\.sql\.Column,* org.apache.spark.sql.functions.regexp_replace]]
       */
     def regexpReplace(
         pattern: StringColumn,
@@ -264,6 +280,7 @@ private[syntax] trait StringColumns {
       * Repeats a string column n times, and returns it as a new string column.
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.repeat]]
       */
     def repeat(n: IntegerColumn): StringColumn = (s.elem, n.elem)
       .mapN((str, times) => new Column(StringRepeat(str.expr, times.expr)))
@@ -275,6 +292,7 @@ private[syntax] trait StringColumns {
       * characters.
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.rpad]]
       */
     def rpad(len: IntegerColumn, pad: StringColumn): StringColumn =
       (s.elem, len.elem, pad.elem)
@@ -285,6 +303,7 @@ private[syntax] trait StringColumns {
       * Trim the spaces from right end for the specified string value.
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.rtrim(e:org\.apache\.spark\.sql\.Column):* org.apache.spark.sql.functions.rtrim]]
       */
     def rtrim: StringColumn = s.elem.map(f.rtrim).toDC
 
@@ -293,6 +312,7 @@ private[syntax] trait StringColumns {
       * string column.
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.rtrim(e:org\.apache\.spark\.sql\.Column,trimString:* org.apache.spark.sql.functions.rtrim]]
       */
     def rtrim(trimString: StringColumn): StringColumn =
       (s.elem, trimString.elem)
@@ -303,21 +323,10 @@ private[syntax] trait StringColumns {
       * Returns the soundex code for the specified expression.
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.soundex]]
       */
     def soundex: StringColumn = s.elem.map(f.soundex).toDC
 
-    /**
-      * Splits str around matches of the given pattern.
-      *
-      * @param pattern
-      *   a string representing a regular expression. The regex string should be
-      *   a Java regular expression.
-      *
-      * @group String Type
-      */
-    def split(pattern: StringColumn): ArrayColumn[String] =
-      split(pattern, (-1).lit)
-
     /**
       * Splits str around matches of the given pattern.
       *
@@ -326,16 +335,18 @@ private[syntax] trait StringColumns {
       *   a string representing a regular expression. The regex string should be
       *   a Java regular expression.
       * @param limit
-      *   an integer expression which controls the number of times the regex is
-      *   applied. <ul> <li>limit greater than 0: The resulting array's length
-      *   will not be more than limit, and the resulting array's last entry will
-      *   contain all input beyond the last matched regex.</li> <li>limit less
-      *   than or equal to 0: `regex` will be applied as many times as possible,
-      *   and the resulting array can be of any size.</li> </ul>
+      *   an integer expression which controls the number of times the regex is applied.
+      *     - __limit greater than 0__: The resulting array's length
+      *       will not be more than limit, and the resulting array's last entry will
+      *       contain all input beyond the last matched regex.
+      *     - __limit less than or equal to 0__: `regex` will be applied as many times as possible,
+      *       and the resulting array can be of any size.
+      * @see org.apache.spark.sql.functions.split
+      * @todo scaladoc link (issue #135)
       */
     def split(
         pattern: StringColumn,
-        limit: IntegerColumn
+        limit: IntegerColumn = (-1).lit
     ): ArrayColumn[String] =
       (s.elem, pattern.elem, limit.elem)
         .mapN((str, p, l) => new Column(StringSplit(str.expr, p.expr, l.expr)))
@@ -349,6 +360,7 @@ private[syntax] trait StringColumns {
       * @group String Type
       * @note
       *   The position is not zero based, but 1 based index.
+      * @see [[org.apache.spark.sql.functions.substring]]
       */
     def substring(pos: IntegerColumn, len: IntegerColumn): StringColumn =
       (s.elem, pos.elem, len.elem)
@@ -364,6 +376,7 @@ private[syntax] trait StringColumns {
       * for delim.
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.substring_index]]
       */
     def substringIndex(
         delim: StringColumn,
@@ -382,6 +395,7 @@ private[syntax] trait StringColumns {
       * string matches the character in the `matchingString`.
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.translate]]
       */
     def translate(
         matchingString: StringColumn,
@@ -397,6 +411,7 @@ private[syntax] trait StringColumns {
       * Trim the spaces from both ends for the specified string column.
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.trim(e:org\.apache\.spark\.sql\.Column):* org.apache.spark.sql.functions.trim]]
       */
     def trim: StringColumn = s.elem.map(f.trim).toDC
 
@@ -405,6 +420,7 @@ private[syntax] trait StringColumns {
       * column (literal).
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.trim(e:org\.apache\.spark\.sql\.Column,trimString:* org.apache.spark.sql.functions.trim]]
       */
     def trim(trimString: StringColumn): StringColumn =
       (s.elem, trimString.elem)
@@ -417,6 +433,7 @@ private[syntax] trait StringColumns {
       * Converts a string column to upper case.
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.upper]]
       */
     def upper: StringColumn = s.elem.map(f.upper).toDC
 
@@ -431,6 +448,7 @@ private[syntax] trait StringColumns {
       * match.
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.Column.contains]]
       */
     def contains(dc: StringColumn): BooleanColumn =
       (s.elem, dc.elem).mapN(_.contains(_)).toDC
@@ -439,6 +457,7 @@ private[syntax] trait StringColumns {
       * String ends with. Returns a boolean column based on a string match.
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.Column.endsWith(other:* org.apache.spark.sql.Column.endsWith]]
       */
     def endsWith(dc: StringColumn): BooleanColumn =
       (s.elem, dc.elem).mapN(_.endsWith(_)).toDC
@@ -447,6 +466,7 @@ private[syntax] trait StringColumns {
       * SQL like expression. Returns a boolean column based on a SQL LIKE match.
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.Column.like]]
       */
     def like(literal: StringColumn): BooleanColumn =
       (s.elem, literal.elem)
@@ -458,6 +478,7 @@ private[syntax] trait StringColumns {
       * on a regex match.
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.Column.rlike]]
       */
     def rLike(literal: StringColumn): BooleanColumn =
       (s.elem, literal.elem)
@@ -468,6 +489,7 @@ private[syntax] trait StringColumns {
       * String starts with. Returns a boolean column based on a string match.
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.Column.startsWith(other:* org.apache.spark.sql.Column.startsWith]]
       */
     def startsWith(dc: StringColumn): BooleanColumn =
       (s.elem, dc.elem).mapN(_.startsWith(_)).toDC
@@ -479,6 +501,7 @@ private[syntax] trait StringColumns {
       * on a regex match.
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.Column.rlike]]
       */
     def matchRegex(literal: StringColumn): BooleanColumn = rLike(literal)
 
@@ -488,6 +511,7 @@ private[syntax] trait StringColumns {
       * If either argument is null, the result will also be null.
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.encode]]
       */
     def encode(charset: StringColumn): BinaryColumn =
       (s.elem, charset.elem)
@@ -501,6 +525,7 @@ private[syntax] trait StringColumns {
       * This is the reverse of base64.
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.unbase64]]
       */
     def unbase64: BinaryColumn = s.elem.map(f.unbase64).toDC
 
@@ -512,6 +537,7 @@ private[syntax] trait StringColumns {
       *   A long
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.unix_timestamp(s:org\.apache\.spark\.sql\.Column):* org.apache.spark.sql.functions.unix_timestamp]]
       */
     def unixTimestamp: LongColumn = s.elem.map(f.unix_timestamp).toDC
 
@@ -523,6 +549,7 @@ private[syntax] trait StringColumns {
       * @throws java.lang.IllegalArgumentException if invalid pattern
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.unix_timestamp(s:org\.apache\.spark\.sql\.Column,p:* org.apache.spark.sql.functions.unix_timestamp]]
       */
     def unixTimestamp(pattern: StringColumn): LongColumn =
       (s.elem, pattern.elem)
@@ -541,6 +568,7 @@ private[syntax] trait StringColumns {
       * Similar to concat doric function, but only with two columns
       *
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.concat]]
       */
     def +(s2: StringColumn): StringColumn = concat(s, s2)
 
@@ -557,6 +585,7 @@ private[syntax] trait StringColumns {
       * @return
       *   A date, or null if `e` was a string that could not be cast to a date
       *   or `format` was an invalid format
+      * @see [[org.apache.spark.sql.functions.to_date(e:org\.apache\.spark\.sql\.Column,fmt:* org.apache.spark.sql.functions.to_date]]
       */
     def toDate(format: StringColumn): LocalDateColumn =
       (s.elem, format.elem)
@@ -578,6 +607,7 @@ private[syntax] trait StringColumns {
       * @return
       *   A timestamp, or null if `s` was a string that could not be cast to a
       *   timestamp or `format` was an invalid format
+      * @see [[org.apache.spark.sql.functions.to_timestamp(s:org\.apache\.spark\.sql\.Column,fmt:* org.apache.spark.sql.functions.to_timestamp]]
       */
     def toTimestamp(format: StringColumn): InstantColumn =
       (s.elem, format.elem)
@@ -597,6 +627,7 @@ private[syntax] trait StringColumns {
       *
       * @throws java.lang.RuntimeException with the error message
       * @group String Type
+      * @see [[org.apache.spark.sql.functions.raise_error]]
       */
     def raiseError: NullColumn = s.elem.map(f.raise_error).toDC
   }
diff --git a/core/src/main/scala/doric/syntax/TimestampColumns.scala b/core/src/main/scala/doric/syntax/TimestampColumns.scala
index 0fc873b38..414e86b02 100644
--- a/core/src/main/scala/doric/syntax/TimestampColumns.scala
+++ b/core/src/main/scala/doric/syntax/TimestampColumns.scala
@@ -17,6 +17,7 @@ private[syntax] trait TimestampColumns {
     * All calls of current_timestamp within the same query return the same value.
     *
     * @group Timestamp Type
+    * @see [[org.apache.spark.sql.functions.current_timestamp]]
     */
   def currentTimestamp(): TimestampColumn =
     f.current_timestamp().asDoric[Timestamp]
@@ -32,6 +33,8 @@ private[syntax] trait TimestampColumns {
       *
       * @throws java.time.DateTimeException if invalid timeZone
       * @group Timestamp Type
+      * @see org.apache.spark.sql.functions.from_utc_timestamp
+      * @todo scaladoc link (issue #135)
       */
     def fromUtc(timeZone: StringColumn): TimestampColumn =
       (column.elem, timeZone.elem)
@@ -47,6 +50,8 @@ private[syntax] trait TimestampColumns {
       *
       * @throws java.time.DateTimeException if invalid timeZone
       * @group Timestamp Type
+      * @see org.apache.spark.sql.functions.to_utc_timestamp
+      * @todo scaladoc link (issue #135)
       */
     def toUtc(timeZone: StringColumn): TimestampColumn =
       (column.elem, timeZone.elem)
@@ -59,6 +64,7 @@ private[syntax] trait TimestampColumns {
       * Extracts the seconds as an integer from a given timestamp.
       *
       * @group Timestamp Type
+      * @see [[org.apache.spark.sql.functions.second]]
       */
     def second: IntegerColumn = column.elem.map(f.second).toDC
 
@@ -70,6 +76,7 @@ private[syntax] trait TimestampColumns {
       *                       `1 second`. Check `org.apache.spark.unsafe.types.CalendarInterval` for
       *                       valid duration identifiers.
       * @group Timestamp Type
+      * @see [[org.apache.spark.sql.functions.window(timeColumn:org\.apache\.spark\.sql\.Column,windowDuration:String):* org.apache.spark.sql.functions.window]]
       */
     def window(windowDuration: String): RowColumn =
       column.elem.map(x => f.window(x, windowDuration)).toDC
@@ -97,6 +104,7 @@ private[syntax] trait TimestampColumns {
       *   start 15 minutes past the hour, e.g. 12:15-13:15, 13:15-14:15... provide
       *   `startTime` as `15 minutes`.
       * @group Timestamp Type
+      * @see [[org.apache.spark.sql.functions.window(timeColumn:org\.apache\.spark\.sql\.Column,windowDuration:String,slideDuration:String,startTime:* org.apache.spark.sql.functions.window]]
       */
     def window(
         windowDuration: String,
@@ -113,6 +121,7 @@ private[syntax] trait TimestampColumns {
       * @group Timestamp Type
       * @return
       *   a Date Column without the hour
+      * @see [[org.apache.spark.sql.functions.to_date(e:org\.apache\.spark\.sql\.Column):* org.apache.spark.sql.functions.to_date]]
       */
     def toDate: DateColumn = column.elem.map(f.to_date).toDC
 
@@ -122,6 +131,7 @@ private[syntax] trait TimestampColumns {
       * @group Timestamp Type
       * @return
       *   a LocalDate Column without the hour
+      * @see [[org.apache.spark.sql.functions.to_date(e:org\.apache\.spark\.sql\.Column):* org.apache.spark.sql.functions.to_date]]
       */
     def toLocalDate: LocalDateColumn = column.elem.map(f.to_date).toDC
   }
diff --git a/core/src/test/scala/doric/syntax/StringColumnsSpec.scala b/core/src/test/scala/doric/syntax/StringColumnsSpec.scala
index 5ad0efaff..88c9966de 100644
--- a/core/src/test/scala/doric/syntax/StringColumnsSpec.scala
+++ b/core/src/test/scala/doric/syntax/StringColumnsSpec.scala
@@ -129,7 +129,7 @@ class StringColumnsSpec
         .toDF("col1")
 
       df.testColumns("col1")(
-        c => colString(c).initcap,
+        c => colString(c).initCap,
         c => f.initcap(f.col(c)),
         List("Hello World", "Ñañeñiño", "Tú Vas A Ir A Álaba", "1", null)
           .map(Option(_))
@@ -145,7 +145,7 @@ class StringColumnsSpec
         .toDF("col1")
 
       df.testColumns2("col1", "a")(
-        (c, str) => colString(c).instr(str.lit),
+        (c, str) => colString(c).inStr(str.lit),
         (c, str) => f.instr(f.col(c), str),
         List(Some(0), Some(2), Some(5), Some(0), None)
       )