class_docstr: String methods for pandas-on-Spark Series
class_docstr_tok: ["String","methods","for","pandas-on-Spark","Series"]
docstr: Check whether all characters in each string are numeric.
  
  This is equivalent to running the Python string method
  :func:`str.isnumeric` for each element of the Series/Index.
  If a string has zero characters, False is returned for that check.
  
  Examples
  --------
  >>> s1 = ps.Series(['one', 'one1', '1', ''])
  >>> s1.str.isnumeric()
  0    False
  1    False
  2     True
  3    False
  dtype: bool
  
  >>> s2 = ps.Series(['23', '³', '⅕', ''])
  
  The s2.str.isdecimal method checks for characters used to form numbers
  in base 10.
  
  >>> s2.str.isdecimal()
  0     True
  1    False
  2    False
  3    False
  dtype: bool
  
  The s2.str.isdigit method is the same as s2.str.isdecimal but also
  includes special digits, like superscripted and subscripted digits in
  Unicode.
  
  >>> s2.str.isdigit()
  0     True
  1     True
  2    False
  3    False
  dtype: bool
  
  The s2.str.isnumeric method is the same as s2.str.isdigit but also
  includes other characters that can represent quantities such as unicode
  fractions.
  
  >>> s2.str.isnumeric()
  0     True
  1     True
  2     True
  3    False
  dtype: bool
code: def isnumeric(self) -> "ps.Series":
      """
      Check whether all characters in each string are numeric.
  
      This is equivalent to running the Python string method
      :func:`str.isnumeric` for each element of the Series/Index.
      If a string has zero characters, False is returned for that check.
  
      Examples
      --------
      >>> s1 = ps.Series(['one', 'one1', '1', ''])
      >>> s1.str.isnumeric()
      0    False
      1    False
      2     True
      3    False
      dtype: bool
  
      >>> s2 = ps.Series(['23', '³', '⅕', ''])
  
      The s2.str.isdecimal method checks for characters used to form numbers
      in base 10.
  
      >>> s2.str.isdecimal()
      0     True
      1    False
      2    False
      3    False
      dtype: bool
  
      The s2.str.isdigit method is the same as s2.str.isdecimal but also
      includes special digits, like superscripted and subscripted digits in
      Unicode.
  
      >>> s2.str.isdigit()
      0     True
      1     True
      2    False
      3    False
      dtype: bool
  
      The s2.str.isnumeric method is the same as s2.str.isdigit but also
      includes other characters that can represent quantities such as unicode
      fractions.
  
      >>> s2.str.isnumeric()
      0     True
      1     True
      2     True
      3    False
      dtype: bool
      """
  
      def pandas_isnumeric(s) -> ps.Series[bool]:  # type: ignore[no-untyped-def]
          return s.str.isnumeric()
  
      return self._data.pandas_on_spark.transform_batch(
          pandas_isnumeric
      )
  
imports: from typing import Any, Callable, Dict, List, Optional, Union, cast, no_type_check
  import numpy
  import pandas
  from pyspark.sql.types import StringType, BinaryType, ArrayType, LongType, MapType
  from pyspark.sql import functions
  from pyspark.sql.functions import pandas_udf
  import pyspark.pandas
label_desc: Use image node_id 20 for calling the StringMethods obj's underlying member method code with example usage: obj.isnumeric() and returns: self, s