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author | mpro <magdalena.proszewska@gmail.com> | 2019-11-18 22:49:20 +0100 |
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committer | mpro <magdalena.proszewska@gmail.com> | 2019-11-18 22:49:20 +0100 |
commit | cef6aa3830f915f9589a50700670da062e6acffd (patch) | |
tree | cd588909066856eebcfe2c6ae84d0e78806ec414 | |
parent | ab90c876b0fead1b923b1616f8f50a5fded83de6 (diff) | |
download | numpy-cef6aa3830f915f9589a50700670da062e6acffd.tar.gz |
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-rw-r--r-- | numpy/core/_add_newdocs.py | 9 |
1 files changed, 3 insertions, 6 deletions
diff --git a/numpy/core/_add_newdocs.py b/numpy/core/_add_newdocs.py index 2396437c1..4ddd59a72 100644 --- a/numpy/core/_add_newdocs.py +++ b/numpy/core/_add_newdocs.py @@ -3953,25 +3953,22 @@ add_newdoc('numpy.core.multiarray', 'ndarray', ('tolist', Examples -------- - For a 1D array, ``a.tolist()`` is almost the same as ``list(a)``, except that it changes numpy scalars to Python scalars: + For a 1D array, ``a.tolist()`` is almost the same as ``list(a)``, + except that ``tolist`` changes numpy scalars to Python scalars: >>> a = np.uint32([1, 2]) >>> a_list = list(a) >>> a_list [1, 2] - >>> type(a_list) - <class 'list'> >>> type(a_list[0]) <class 'numpy.uint32'> >>> a_tolist = a.tolist() >>> a_tolist [1, 2] - >>> type(a_tolist) - <class 'list'> >>> type(a_tolist[0]) <class 'int'> - However, for a 2D array, ``tolist`` applies recursively: + Additionally, for a 2D array, ``tolist`` applies recursively: >>> a = np.array([[1, 2], [3, 4]]) >>> list(a) |