1/15 Quickly Estimating Powers-of-Two Andreas Weis Woven Planet CppCon 20212/15 About me ComicSansMS @DerGhulbus Co-organizer of the Munich C++ User Group Currently working as a Runtime Framework 223 =? 236 =? 2128 =?4/15 Small Powers of Two 21 = 2 22 = 4 23 = 8 24 = 16 25 = 32 26 = 64 27 = 128 28 = 256 29 = 5125/15 Small Powers of Two 21 = 2 22 = 4 23 = 8 24 = 16 25 = 32 26 = 5126/15 Small Powers of Two 21 = 2 22 = 4 23 = 8 24 = 16 25 = 32 26 = 64 27 = 128 28 = 256 (Number of states in an 8 bit char) 29 = 5127/15 Small Powers of Two 21 = 2 22 = 4 23 = 8 ⋄ 24

sets. The data actually need not be labeled at all to be placed into a pandas data structure The two primary data structures of pandas, Series (1-dimensional) and DataFrame (2-dimensional), handle the index columns • Added nrows, chunksize, and iterator arguments to read_csv and read_table. The last two return a new TextParser class capable of lazily iterating through chunks of a flat file (GH242) • instance methods isnull and notnull to Series (PR209, GH203) • Added Series.align method for aligning two series with choice of join method (ENH56) • Added method get_level_values to MultiIndex (IS188) •

sets. The data actually need not be labeled at all to be placed into a pandas data structure The two primary data structures of pandas, Series (1-dimensional) and DataFrame (2-dimensional), handle the Release 0.7.2 • Added nrows, chunksize, and iterator arguments to read_csv and read_table. The last two return a new TextParser class capable of lazily iterating through chunks of a flat file (GH242) • instance methods isnull and notnull to Series (PR209, GH203) • Added Series.align method for aligning two series with choice of join method (ENH56) • Added method get_level_values to MultiIndex (IS188) •

sets. The data actually need not be labeled at all to be placed into a pandas data structure The two primary data structures of pandas, Series (1-dimensional) and DataFrame (2-dimensional), handle the ’bar’, ’foo’, ’bar’, .....: ’foo’, ’bar’, ’foo’, ’foo’], .....: ’B’ : [’one’, ’one’, ’two’, ’three’, .....: ’two’, ’two’, ’one’, ’three’], .....: ’C’ : np.random.randn(8), ’D’ : np.random.randn(8)}) In 541264 2.801614 1 bar one -0.722290 1.669853 2 foo two -0.478428 0.254501 3 bar three 2.850221 -0.682682 4 foo two -0.350942 -0.697727 5 bar two -1.581790 -1.092094 6 foo one 1.113061 0.321042 7

why did you plan to write this book? At about July 2016, after (not very intensively) using Go for two years, I felt that Go is a simple language and I had mastered Go programming. At that time, I had collected features which are usually only available in dynamic script languages. It is hard to combine these two kinds into one language, but Go did it. In other words, Go owns both the strictness of static languages languages and the flexibility of dynamic languages. I can't say there are not any compromises between the two, but the effect of the compromises is much weaker than the benefits of the combination in Go. Readability

why did you plan to write this book? At about July 2016, after (not very intensively) using Go for two years, I felt that Go is a simple language and I had mastered Go programming. At that time, I had features which are usually only available in dynamic script languages. It is hard to combine these two kinds into one language, but Go did it. In other words, Go owns both the strictness of static languages languages and the flexibility of dynamic languages. I can't say there are not any compromises between the two, but the effect of the compromises is much weaker than the benefits of the combination in Go. Readability

why did you plan to write this book? At about July 2016, after (not very intensively) using Go for two years, I felt that Go is a simple language and I had mastered Go programming. At that time, I had available in dynamic script languages. It is hard to combine these §2. An Introduction of Go 10 two kinds into one language, but Go did it. In other words, Go owns both the strictness of static languages languages and the flexibility of dynamic languages. I can't say there are not any compromises between the two, but the effect of the compromises is much weaker than the benefits of the combination in Go. Readability

sets. The data actually need not be labeled at all to be placed into a pandas data structure The two primary data structures of pandas, Series (1-dimensional) and DataFrame (2-dimensional), handle the appending tables. In [21]: index = MultiIndex(levels=[[’foo’, ’bar’, ’baz’, ’qux’], ....: [’one’, ’two’, ’three’]], ....: labels=[[0, 0, 0, 1, 1, 2, 2, 3, 3, 3], ....: [0, 1, 2, 0, 1, 1, 2, 0, 1, 2]] 410679 -0.938918 -1.452154 two 0.835328 -0.698888 0.766402 three 0.536443 -0.147986 0.339040 bar one -0.195183 -1.332316 1.684194 two -0.137506 2.138582 0.118417 baz two 0.517623 1.646523 2.036856

William Ayd • jbrockmendel {{ header }} 4 Chapter 1. Whats new in 0.25.2 (October 15, 2019) CHAPTER TWO INSTALLATION The easiest way to install pandas is to install it as part of the Anaconda distribution sets. The data actually need not be labeled at all to be placed into a pandas data structure The two primary data structures of pandas, Series (1-dimensional) and DataFrame (2-dimensional), handle the Using the isin() method for filtering: In [41]: df2 = df.copy() In [42]: df2['E'] = ['one', 'one', 'two', 'three', 'four', 'three'] In [43]: df2 Out[43]: A B C D E 2013-01-01 1.832747 1.515386 1.793547

screen? And can you guess what the Nim statement 'echo 1, 2' would print? Are you sure that the two arguments provided to the echo statement are separated with a space? I just tested it. I run the circuits, can perform very basic mathematical and logical operations on numbers, such as adding two numbers or determining whether one number is larger or smaller than another. Most computer CPUs can Before use, each partition is generally formatted, at which point a file system (FS) is created. These two steps create an internal structure on the storage device, which allows us to store and retrieve individual