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User Help

Thecus NAS USB Crypt Key – How to Backup?

Hej, I encrypted my Thecus n2350 RAID. I would like to backup the key from the usb Image. I plugged in the USB Stick to my Linux, fdisk -l show a /dev/mapper/luks-c1f80955-5030-4fa6-96ad-db828556a5f5 and I tried to open it with cryptsetup -> No valid LUKS Device. Can some one give me a hint, how to backup […]

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Development Linux Ubuntu

Best partitions configuration on Lubuntu installing on UEFI & Atom CPU

Hej, I prepared bootable UEFI usb with Lubuntu 19x. I ran this installation source in my laptop, and installlation’s proccess is proceeding well. But I stuckied on screen, where I should configure all partitions for UEFI requirements. I have to set up all of options manually, and I am little confused. I have really small […]

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Development User Help

Are any other distrons which will work on UEFI & Intel Atom CPU (instead of Lubutnu)? [closed]

Hej, I am looking for **very lightweight ** linux distro to set up on a little trashy notebook. Im gonna using this gear to learning and playing with server software, like apache http server, nginx, maybe some ftp servers etc. I am using Lubuntu now, but I feel the need to try other distros as […]

Categories
Development Linux Ubuntu

Are any other distrons which will work on UEFI & Intel Atom CPU (instead of Lubutnu)?

Hej, I am looking for **very lightweight ** linux distro to set up on a little trashy notebook. Im gonna using this gear to learnigng and playing with server software, like apache http server, nginx, maybe some ftp servers etc. I have here Lubuntu now, but I feel the need to check something other. Is […]

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Development

Reduce comma separated str in df if all strs identical

This is my code so far import pandas as pd from io import StringIO data = StringIO(“”” “name1″,”hej”,”7aa”,”a” “name1″,”du”,”71al”,”a” “name1″,”aj”,”74a”,”a” “name1″,”oj”,”7aj”,”a” “name2″,”fin”,”7ag”,”a” “name2″,”katt”,”7a”,”a” “””) df = pd.read_csv(data, header=0, names=[“name”,”text2″,”text”,”as”]) df[[‘text2′,’text’,’as’]] = df.groupby([‘name’]).transform(lambda x: ‘,’.join(x)) df = df[[‘name’,’text’,’text2′,’as’]].drop_duplicates() df Gets me most of the way. df name text text2 as 0 name1 71al,74a,7aj du,aj,oj a,a,a 3 […]