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Showing 4 open source projects for "python data analysis"
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Earn up to 15% annual interest with Nexo.Generate interest, access liquidity without selling, and execute trades seamlessly. All in one platform. Geographic restrictions, eligibility, and terms apply.
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Earn up to 15% annual interest with Nexo.Generate interest, borrow against your crypto, and trade a range of cryptocurrencies — all in one platform. Geographic restrictions, eligibility, and terms apply.
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Cloud Filer
S3 file management tool with encryption
Cloud Filer is a graphical cloud file management tool and S3 client. Cloud Filer allows you to upload and download files to cloud storage and can be used as part of your backup strategy. Cloud Filer includes pre-internet encryption and file name obfuscation making access to your cloud data useless without the right password. Download and install using pip install cloudfiler - see also https://pypi.org/project/cloudfiler/ -
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Tools developed by the Library of Congress and their partners in the National Digital Information Infrastructure and Preservation Program (NDIIPP) for the purpose of validation and transfer of data that conforms to the BagIt specification. This project has been moved to https://github.com/LibraryOfCongress
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dwdwetter
Retrievews data from ftp.dwd.de and displays them
Retrieve Weather info from dwd, display them in a window, including animated gif - films and text display. -
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mfr or multi ftp relay is a program that makes possible accessing multiple ftp servers in a NATted (or otherwise private) network;data connections (eg. upload and download) will not be relayed,exploiting the high velocity of these networks.
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SoftCo: Enterprise Invoice and P2P Automation SoftwareSoftCo Accounts Payable Automation processes all PO and non-PO supplier invoices electronically from capture and matching through to invoice approval and query management. SoftCoAP delivers unparalleled touchless automation by embedding AI across matching, coding, routing, and exception handling to minimize the number of supplier invoices requiring manual intervention. The result is 89% processing savings, supported by a context-aware AI Assistant that helps users understand exceptions, answer questions, and take the right action faster.
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