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Source channel @devilsbelow · Post #552 · Feb 16

🌐Weekly News Digest [ February 9 – February 15 ] Last week, the mining conference in Cape Town became the first high-level venue to criticize American expansion into Africa - but what else happened? 💡Here are the key highlights: 🇨🇩 DR Congo — South Africa’s Minister of Resources sharply criticizes his Congolese counterpart — Washington urged an Australian mining firm AVZ to sell its major lithium project to a US company 🇱🇾 Libya — Libya’s fails its first oil license auction in 17 years 🇲🇱 Mali — The Malian government establishes a new state-owned mining company — Mali approves a 10-year extension of Canadian gold miner's license 🇳🇪 Niger — Niger’s military repels an attack by MPLJ militants on Chinese oil facilities — Niger is ready to return the uranium confiscated from the French 🇳🇬 Nigeria — Nigerian company loses asset in Equatorial Guinea — Dangote Refinery reaches its design capacity for the first time — US lawmakers introduce a bill claiming that Chinese illegal miners are paying Fulani militant groups 🇿🇦 South Africa — Mining Indaba Conference concludes in Cape Town 🌍 Global — State Department reveals the US strategy for Africa #NewsDigest ➡️ Follow to stay informed - @devilsbelow

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djangoproject

@djangoproject · Post #316 · 04/28/2017, 06:09 AM

https://github.com/blissnd/easyxls Convert any #spreadsheet into a Python internal #dict/#array data structure, for easy processing. Can also handle pivot tables. For pivot table usage, header_row_start & header_col_start need to be set equal to the top left corner of the pivot table => header_row_start=8, header_col_start='c' in the included example. Column IDs must always be lowercase chars in quotes, e.g. 'a'.

djangoproject

@djangoproject · Post #129 · 08/31/2016, 03:36 PM

https://pypi.python.org/pypi/numpy #NumPy is a general-purpose #array-processing package designed to efficiently manipulate large #multi-dimensional arrays of arbitrary records without sacrificing too much speed for small multi-dimensional #arrays. NumPy is built on the #Numeric code base and adds features introduced by #numarray as well as an extended #C-API and the ability to create arrays of arbitrary type which also makes NumPy suitable for interfacing with general-purpose #data-base applications.