. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 5.2 DataFrame . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . automatically in many cases, in particular when taking 1D slices of DataFrame as you will see below. 5.2 DataFrame DataFrame is a 2-dimensional labeled data structure with columns of potentially different ....: ’two’ : Series([1., 2., 3., 4.], index=[’a’, ’b’, ’c’, ’d’])} In [254]: df = DataFrame(d) 5.2. DataFrame 27 pandas: powerful Python data analysis toolkit, Release 0.7.1 In [255]: df Out[255]:

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 5.2 DataFrame . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . automatically in many cases, in particular when taking 1D slices of DataFrame as you will see below. 5.2 DataFrame DataFrame is a 2-dimensional labeled data structure with columns of potentially different ....: ’two’ : Series([1., 2., 3., 4.], index=[’a’, ’b’, ’c’, ’d’])} In [254]: df = DataFrame(d) 5.2. DataFrame 27 pandas: powerful Python data analysis toolkit, Release 0.7.2 In [255]: df Out[255]:

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 5.2 DataFrame . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . automatically in many cases, in particular when taking 1D slices of DataFrame as you will see below. 5.2 DataFrame DataFrame is a 2-dimensional labeled data structure with columns of potentially different ....: ’two’ : Series([1., 2., 3., 4.], index=[’a’, ’b’, ’c’, ’d’])} In [254]: df = DataFrame(d) 5.2. DataFrame 31 pandas: powerful Python data analysis toolkit, Release 0.7.3 In [255]: df Out[255]:

What’s new in 1.1.0 (July 28, 2020) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2485 5.2 Version 1.0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . entries in a pandas.Index are NA. The result is an array. >>> idx = pd.Index([5.2, 6.0, np.NaN]) >>> idx Float64Index([5.2, 6.0, nan], dtype='float64') >>> idx.isna() array([False, False, True]) Empty entries in a pandas.Index are NA. The result is an array. >>> idx = pd.Index([5.2, 6.0, np.NaN]) >>> idx Float64Index([5.2, 6.0, nan], dtype='float64') >>> idx.isna() array([False, False, True]) Empty

What’s new in 1.1.0 (July 28, 2020) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2483 5.2 Version 1.0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . entries in a pandas.Index are NA. The result is an array. >>> idx = pd.Index([5.2, 6.0, np.NaN]) >>> idx Float64Index([5.2, 6.0, nan], dtype='float64') >>> idx.isna() array([False, False, True]) Empty entries in a pandas.Index are NA. The result is an array. >>> idx = pd.Index([5.2, 6.0, np.NaN]) >>> idx Float64Index([5.2, 6.0, nan], dtype='float64') >>> idx.isna() array([False, False, True]) Empty

What’s new in 1.2.0 (December 26, 2020) . . . . . . . . . . . . . . . . . . . . . . . . . . . 2545 5.2 Version 1.1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . entries in a pandas.Index are NA. The result is an array. >>> idx = pd.Index([5.2, 6.0, np.NaN]) >>> idx Float64Index([5.2, 6.0, nan], dtype='float64') >>> idx.isna() array([False, False, True]) Empty entries in a pandas.Index are NA. The result is an array. >>> idx = pd.Index([5.2, 6.0, np.NaN]) >>> idx Float64Index([5.2, 6.0, nan], dtype='float64') >>> idx.isna() array([False, False, True]) Empty

What’s new in 1.2.0 (December 26, 2020) . . . . . . . . . . . . . . . . . . . . . . . . . . . 2533 5.2 Version 1.1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . entries in a pandas.Index are NA. The result is an array. >>> idx = pd.Index([5.2, 6.0, np.NaN]) >>> idx Float64Index([5.2, 6.0, nan], dtype='float64') >>> idx.isna() array([False, False, True]) Empty entries in a pandas.Index are NA. The result is an array. >>> idx = pd.Index([5.2, 6.0, np.NaN]) >>> idx Float64Index([5.2, 6.0, nan], dtype='float64') >>> idx.isna() array([False, False, True]) Empty

What’s new in 1.0.0 (January 29, 2020) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2398 5.2 Version 0.25 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . entries in a pandas.Index are NA. The result is an array. >>> idx = pd.Index([5.2, 6.0, np.NaN]) >>> idx Float64Index([5.2, 6.0, nan], dtype='float64') >>> idx.isna() array([False, False, True], dtype=bool) entries in a pandas.Index are NA. The result is an array. >>> idx = pd.Index([5.2, 6.0, np.NaN]) >>> idx Float64Index([5.2, 6.0, nan], dtype='float64') >>> idx.isna() array([False, False, True], dtype=bool)

What’s new in 1.0.0 (January 29, 2020) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2393 5.2 Version 0.25 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . entries in a pandas.Index are NA. The result is an array. >>> idx = pd.Index([5.2, 6.0, np.NaN]) >>> idx Float64Index([5.2, 6.0, nan], dtype='float64') >>> idx.isna() array([False, False, True], dtype=bool) entries in a pandas.Index are NA. The result is an array. >>> idx = pd.Index([5.2, 6.0, np.NaN]) >>> idx Float64Index([5.2, 6.0, nan], dtype='float64') >>> idx.isna() array([False, False, True], dtype=bool)

What’s new in 1.4.0 (January 22, 2022) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2858 5.2 Version 1.3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . entries in a pandas.Index are NA. The result is an array. >>> idx = pd.Index([5.2, 6.0, np.NaN]) >>> idx Float64Index([5.2, 6.0, nan], dtype='float64') >>> idx.isna() array([False, False, True]) Empty entries in a pandas.Index are NA. The result is an array. >>> idx = pd.Index([5.2, 6.0, np.NaN]) >>> idx Float64Index([5.2, 6.0, nan], dtype='float64') >>> idx.isna() array([False, False, True]) Empty