class_docstr: Date/Time methods for pandas-on-Spark Series
class_docstr_tok: ["Date\/Time","methods","for","pandas-on-Spark","Series"]
docstr: Indicator for whether the date is the first day of a quarter.
  
  Returns
  -------
  is_quarter_start : Series
      The same type as the original data with boolean values. Series will
      have the same name and index.
  
  See Also
  --------
  quarter : Return the quarter of the date.
  is_quarter_end : Similar property for indicating the quarter start.
  
  Examples
  --------
  This method is available on Series with datetime values under
  the ``.dt`` accessor.
  
  >>> df = ps.DataFrame({'dates': pd.date_range("2017-03-30",
  ...                   periods=4)})
  >>> df
         dates
  0 2017-03-30
  1 2017-03-31
  2 2017-04-01
  3 2017-04-02
  
  >>> df.dates.dt.quarter
  0    1
  1    1
  2    2
  3    2
  Name: dates, dtype: int32
  
  >>> df.dates.dt.is_quarter_start
  0    False
  1    False
  2     True
  3    False
  Name: dates, dtype: bool
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code: def is_quarter_start(self) -> "ps.Series":
      """
      Indicator for whether the date is the first day of a quarter.
  
      Returns
      -------
      is_quarter_start : Series
          The same type as the original data with boolean values. Series will
          have the same name and index.
  
      See Also
      --------
      quarter : Return the quarter of the date.
      is_quarter_end : Similar property for indicating the quarter start.
  
      Examples
      --------
      This method is available on Series with datetime values under
      the ``.dt`` accessor.
  
      >>> df = ps.DataFrame({'dates': pd.date_range("2017-03-30",
      ...                   periods=4)})
      >>> df
             dates
      0 2017-03-30
      1 2017-03-31
      2 2017-04-01
      3 2017-04-02
  
      >>> df.dates.dt.quarter
      0    1
      1    1
      2    2
      3    2
      Name: dates, dtype: int32
  
      >>> df.dates.dt.is_quarter_start
      0    False
      1    False
      2     True
      3    False
      Name: dates, dtype: bool
      """
  
      def pandas_is_quarter_start(s) -> ps.Series[bool]:  # type: ignore[no-untyped-def]
          return s.dt.is_quarter_start
  
      return self._data.pandas_on_spark.transform_batch(
          pandas_is_quarter_start
      )
  
imports: from typing import Any, Optional, Union, no_type_check
  import numpy
  import pandas
  from pandas.tseries.offsets import DateOffset
  import pyspark.pandas
  import pyspark.sql.functions
  from pyspark.sql.types import DateType, TimestampType, TimestampNTZType, IntegerType
  from pyspark.pandas import DataFrame
  from pyspark.pandas.config import option_context
label_desc: Use image node_id 20 for calling the DatetimeMethods obj's underlying member method code with example usage: obj.is_quarter_start() and returns: self, s