standard hierarchical index object • DateRange: fixed frequency date range generated from a time rule or DateOffset. An ndarray of Python datetime objects 92 Chapter 7. Indexing and selecting data pandas: min_periods: threshold of non-null data points to require (otherwise result is NA) • time_rule: optionally specify a time rule to pre-conform the data to These functions can be applied to ndarrays or Series objects: are given to useful common time series frequencies. We will refer to these aliases as time rules. Rule name Description WEEKDAY business day frequency EOM business month end frequency W@MON weekly frequency

standard hierarchical index object • DateRange: fixed frequency date range generated from a time rule or DateOffset. An ndarray of Python datetime objects 92 Chapter 7. Indexing and selecting data pandas: min_periods: threshold of non-null data points to require (otherwise result is NA) • time_rule: optionally specify a time rule to pre-conform the data to These functions can be applied to ndarrays or Series objects: are given to useful common time series frequencies. We will refer to these aliases as time rules. Rule name Description WEEKDAY business day frequency EOM business month end frequency W@MON weekly frequency

standard hierarchical index object • DateRange: fixed frequency date range generated from a time rule or DateOffset. An ndarray of Python datetime objects 98 Chapter 7. Indexing and selecting data pandas: min_periods: threshold of non-null data points to require (otherwise result is NA) • time_rule: optionally specify a time rule to pre-conform the data to These functions can be applied to ndarrays or Series objects: are given to useful common time series frequencies. We will refer to these aliases as time rules. Rule name Description WEEKDAY business day frequency EOM business month end frequency W@MON weekly frequency

13.1 See the plotting page for much more. 1.10.6 Other API changes • Deprecation of offset, time_rule, and timeRule arguments names in time series functions. Warnings will be printed until pandas 0.9 Index object with Timestamp elements • date_range: fixed frequency date range generated from a time rule or DateOffset. An ndarray of Python datetime objects The motivation for having an Index class in data to. Note that prior to pan- das v0.8.0, a keyword argument time_rule was used instead of freq that referred to the legacy time rule constants These functions can be applied to ndarrays or Series objects:

12.0 See the plotting page for much more. 1.8.6 Other API changes • Deprecation of offset, time_rule, and timeRule arguments names in time series functions. Warnings will be printed until pandas 0.9 standard hierarchical index object • date_range: fixed frequency date range generated from a time rule or DateOffset. An ndarray of Python datetime objects The motivation for having an Index class in data to. Note that prior to pan- das v0.8.0, a keyword argument time_rule was used instead of freq that referred to the legacy time rule constants These functions can be applied to ndarrays or Series objects:

bug causing plots of PeriodIndex timeseries to fail if the frequency is a multiple of the frequency rule code (GH14763) • Fixed bug when plotting a DatetimeIndex with datetime.timezone.utc timezone (GH17173) Day or July 4th) an observance rule determines when that holiday is observed if it falls on a weekend or some other non-observed day. Defined observance rules are: Rule Description nearest_workday move 2012-01 -0.148709 Freq: M, dtype: float64 PeriodIndex supports addition and subtraction with the same rule as Period. 4.13. Time series / date functionality 751 pandas: powerful Python data analysis toolkit

bug causing plots of PeriodIndex timeseries to fail if the frequency is a multiple of the frequency rule code (GH14763) • Fixed bug when plotting a DatetimeIndex with datetime.timezone.utc timezone (GH17173) Day or July 4th) an observance rule determines when that holiday is observed if it falls on a weekend or some other non-observed day. Defined observance rules are: Rule Description nearest_workday move 2012-01 -0.148709 Freq: M, dtype: float64 PeriodIndex supports addition and subtraction with the same rule as Period. 4.13. Time series / date functionality 751 pandas: powerful Python data analysis toolkit

“y”, or “Y” for the “unit” argument (GH23264) • Removed the previously deprecated keyword “time_rule” from (non-public) offsets.generate_range, which has been moved to core.arrays._ranges.generate_range() function can be used: In [154]: pd.isna(pd.NA) Out[154]: True An exception on this basic propagation rule are reductions (such as the mean or the minimum), where pandas defaults to skipping missing values Day or July 4th) an observance rule determines when that holiday is observed if it falls on a weekend or some other non-observed day. Defined observance rules are: Rule Description nearest_workday move

raises a TypeError rather than a ValueError (GH24024) • pd.offsets.generate_range() argument time_rule has been removed; use offset instead (GH24157) 26 Chapter 1. What’s New in 0.24.0 (January 25, 2019) Day or July 4th) an observance rule determines when that holiday is observed if it falls on a weekend or some other non-observed day. Defined observance rules are: Rule Description nearest_workday move 2012-01 -0.329583 Freq: M, dtype: float64 PeriodIndex supports addition and subtraction with the same rule as Period. In [346]: idx = pd.period_range('2014-07-01 09:00', periods=5, freq='H') In [347]: idx

function can be used: In [154]: pd.isna(pd.NA) Out[154]: True An exception on this basic propagation rule are reductions (such as the mean or the minimum), where pandas defaults to skipping missing values Day or July 4th) an observance rule determines when that holiday is observed if it falls on a weekend or some other non-observed day. Defined observance rules are: Rule Description nearest_workday move 2012-01 -0.329583 Freq: M, dtype: float64 PeriodIndex supports addition and subtraction with the same rule as Period. In [351]: idx = pd.period_range('2014-07-01 09:00', periods=5, freq='H') In [352]: idx