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The Python pandas software library can extract tables from HTML webpages via its read_html() function. More challenging is table extraction from PDFs or scanned images, where there usually is no table-specific machine readable markup. [1] Systems that extract data from tables in scientific PDFs have been described. [2] [3]
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Pandas is built around data structures called Series and DataFrames. Data for these collections can be imported from various file formats such as comma-separated values, JSON, Parquet, SQL database tables or queries, and Microsoft Excel. [8] A Series is a 1-dimensional data structure built on top of NumPy's array.
Note how the use of A[i][j] with multi-step indexing as in C, as opposed to a neutral notation like A(i,j) as in Fortran, almost inevitably implies row-major order for syntactic reasons, so to speak, because it can be rewritten as (A[i])[j], and the A[i] row part can even be assigned to an intermediate variable that is then indexed in a separate expression.
TCPDF is the only PHP-based library that includes complete support for UTF-8 Unicode and right-to-left languages, including the bidirectional algorithm. [ 2 ] In 2009, TCPDF was one of the most active of over 200,000 projects hosted on SourceForge (best ranked 6th on 3 April 2010).
In addition, this specification defines objects to be used within threaded web applications for the synchronous reading of files. The File API describes how interactions with files are handled, for reading information about them and their data as well, to be able to upload it. Despite the name, the File API is not part of HTML5.
The last version of Numeric (v24.2) was released on 11 November 2005, while the last version of numarray (v1.5.2) was released on 24 August 2006. [ 13 ] There was a desire to get Numeric into the Python standard library, but Guido van Rossum decided that the code was not maintainable in its state then.
It contained a bug which allowed an attacker to grant themselves privileges in accessing the production version of the site. Stack Overflow published on their blog that approximately 184 public network users were affected by this breach, which "could have returned IP address, names, or emails".