d') The time values in Period and PeriodIndex objects are now set to ‘23:59:59.999999999’ when calling Series.dt.end_time, Period.end_time, PeriodIndex.end_time, Period.to_timestamp() with how='end', 00:00:00) In [5]: p.end_time Out[5]: Timestamp(2017-01-01 23:59:59.999999999) New Behavior: Calling Series.dt.end_time will now result in a time of ‘23:59:59.999999999’ as is the case with Period. OverflowError: Trying to coerce negative values to unsigned integers 1.2.16 Concatenation Changes Calling pandas.concat() on a Categorical of ints with NA values now causes them to be processed as objects

converting to a NumPy array missing values will be pd.NA, which cannot be converted to a float. So calling np.asarray(integer_array, dtype="float") will now raise. pandas 0.25.x >>> np.asarray(a, dtype="float") pandas from source, you should no longer need to install Cython into your build environment before calling pip install pandas. 1.5.14 Other API changes • core.groupby.GroupBy.transform now raises on invalid implicitly losing the dtype of extension types in the future. Convert to the correct dtype before calling diff instead (GH31025) Selecting Columns from a Grouped DataFrame When selecting columns from a

set_index() now works for instances of abc.Iterator, provided their output is of the same length as the calling frame (GH22484, GH24984) • DatetimeIndex.union() now supports the sort argument. The behavior of 1.2.9 DataFrame describe on an empty categorical / object column will return top and freq When calling DataFrame.describe() with an empty categorical / object column, the ‘top’ and ‘freq’ columns were Indexing • Improved exception message when calling DataFrame.iloc() with a list of non-numeric objects (GH25753). • Improved exception message when calling .iloc or .loc with a boolean indexer with different

set_index() now works for instances of abc.Iterator, provided their output is of the same length as the calling frame (GH22484, GH24984) • DatetimeIndex.union() now supports the sort argument. The behavior of 1.2.9 DataFrame describe on an empty categorical / object column will return top and freq When calling DataFrame.describe() with an empty categorical / object column, the ‘top’ and ‘freq’ columns were Indexing • Improved exception message when calling DataFrame.iloc() with a list of non-numeric objects (GH25753). • Improved exception message when calling .iloc or .loc with a boolean indexer with different

is installed, and return value of sum and prod on an empty Series has changed (GH9422, GH15507). Calling sum or prod on an empty or all-NaN Series, or columns of a DataFrame, will result in NaN. See the '2017Q3'], dtype='period[2Q-DEC]', freq='2Q-DEC') Upsampling and calling .ohlc() previously returned a Series, basically identical to calling .asfreq(). OHLC upsampling now returns a DataFrame with columns index.memory_usage(deep=True) Out[11]: 260 1.5.2.10 DataFrame.sort_index changes In certain cases, calling .sort_index() on a MultiIndexed DataFrame would return the same DataFrame without seeming to sort

for Python runtime 79 11.1 Function Name Convention . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 11.2 Parameter Convention . . . . . . . . . . . . . . . . . . . . javascript for Node runtime 85 12.1 Function Name Convention . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 12.2 Parameter Convention . . . . . . . . . . . . . . . . . . . . Runtime Module 105 15.1 Protocol Convention . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 15.2 Configuration Convention . . . . . . . . . . . . . . . . .

1 10.34 1.66 No Dinner 2 21.01 3.50 No Dinner 3 23.68 3.31 No Dinner 4 24.59 3.61 No Dinner Calling the DataFrame without the list of column names would display all columns (akin to SQL’s *). In SQL [2]: import numpy as np Note: Throughout this tutorial, the pandas DataFrame will be displayed by calling df.head(), which displays the first N (default 5) rows of the DataFrame. This is often used in interactive [2]: import numpy as np Note: Throughout this tutorial, the pandas DataFrame will be displayed by calling df.head(), which displays the first N (default 5) rows of the DataFrame. This is often used in interactive

1 10.34 1.66 No Dinner 2 21.01 3.50 No Dinner 3 23.68 3.31 No Dinner 4 24.59 3.61 No Dinner Calling the DataFrame without the list of column names would display all columns (akin to SQL’s *). In SQL [2]: import numpy as np Note: Throughout this tutorial, the pandas DataFrame will be displayed by calling df.head(), which displays the first N (default 5) rows of the DataFrame. This is often used in interactive [2]: import numpy as np Note: Throughout this tutorial, the pandas DataFrame will be displayed by calling df.head(), which displays the first N (default 5) rows of the DataFrame. This is often used in interactive

medium 0 good 2 very good 3 dtype: int64 Plotting See the Plotting docs. We use the standard convention for referencing the matplotlib API: In [131]: import matplotlib.pyplot as plt In [132]: plt.close('all') DataFrame’s index. New in version 0.21.0. DataFrame.reindex() also supports an “axis-style” calling convention, where you specify a single labels argument and the axis it applies to. 114 Chapter 1. Getting joining and merging): • join='outer': take the union of the indexes (default) • join='left': use the calling object’s index • join='right': use the passed object’s index • join='inner': intersect the indexes

medium 0 good 2 very good 3 dtype: int64 Plotting See the Plotting docs. We use the standard convention for referencing the matplotlib API: In [131]: import matplotlib.pyplot as plt In [132]: plt.close('all') DataFrame’s index. New in version 0.21.0. DataFrame.reindex() also supports an “axis-style” calling convention, where you specify a single labels argument and the axis it applies to. 114 Chapter 1. Getting joining and merging): • join='outer': take the union of the indexes (default) • join='left': use the calling object’s index • join='right': use the passed object’s index • join='inner': intersect the indexes