#net1

[chatpile]

And yes, a lot of this is The Call Is Coming From Inside The Room. A lot of my frustration stems from my lack of agency in my everyday life and at the most basic level that's not Danny's fault. If anything I'm going to blame my family for failing to equip me adequately for adult life but even then the deeper issue is CapitalismTM and how it's just impossible to survive without a safety net1

[inventivaindia]

Exclusive: Mobikwik raises over $3 million in bridge round led by Sequoia

Exclusive: Mobikwik raises over $3 million in bridge round led by Sequoia

With players like Paytm, Mobikwik, and PhonePe launching new services and features every day to outdo each other, digital payments space is laden with intense competition.

However, as much as these services help fight competition, they dry up funds at a faster pace.

Mobikwik, one such comprehensive digital payments major, had not been in any fundraising reports since last year. But, as per…

[antoniwebid]

Kominfo Cabut Izin Net1 Indonesia, Selanjutnya Ini Dia Kewajiban yang Perlu Dipenuhi - Antoni Blog

Kominfo Cabut Izin Net1 Indonesia, Selanjutnya Ini Dia Kewajiban yang Perlu Dipenuhi – Antoni Blog

Jakarta, Antoni Blog – Menteri Komunikasi dan Infomatika telah menjatuhkan sanksi administratif berupa pencabutan Izin Pita Frekuensi Radio kepada PT Net Satu Indonesia (Net1 Indonesia) pada tanggal 30 November 2021 melalui Keputusan Menteri Komunikasi dan Informatika Nomor 517 Tahun 2021 Tentang Pencabutan Izin Pita Frekuensi Radio Pada Rentang 450 – 457.5 MHz berpasangan dengan 460 – 467.5 MHz…

[whoknowsbud]

For people who want a little more realism on their beach(es), I made jellyfish to diehang out on them! (Other patterns I used in the area were grabbed by searching driftwood, fishing net, fishing net1, fishing net2, kelp, & seaweed. I also later added sand dollar, sand dollar 2, & sand dollar 3)

[uspscourse]

Data Analyst - Gapminder

1) program: gapminder3.py

import pandas import numpy # any additional libraries would be imported here

data = pandas.read_csv('gapminder.csv', low_memory=False)

# checking the format of your variables data['country'].dtype

""" #setting variables you will be working with to numeric data['co2emissions'] = pandas.to_numeric(data['co2emissions']) data['internetuserate'] = pandas.to_numeric(data['internetuserate']) data['lifeexpectancy'] = pandas.to_numeric(data['lifeexpectancy']) """

""" Subset of employrate less than 50, greater than 50 but less 75 and greater than 75 percent """ employ_sub1=data[(data['employrate'] <= '75')] employ_sub2=data[(data['employrate'] > '75')]

""" Subset of lifeexpectancy less than 51, greater than 50 but less 76 and greater than 75 """ life_sub1=data[(data['lifeexpectancy'] <= '50')] life_sub2=data[(data['lifeexpectancy'] > '50') & (data['lifeexpectancy'] <= '75')] life_sub3=data[(data['lifeexpectancy'] > '75')]

""" Subset of internetuserate less than 26, greater than 25 but less 51, greater than 50 but less than 76 and greater than 75 """ net_sub1=data[(data['internetuserate'] <= '25')] net_sub2=data[(data['internetuserate'] > '25') & (data['internetuserate'] <= '50')] net_sub3=data[(data['internetuserate'] > '50') & (data['internetuserate'] <= '75')] net_sub4=data[(data['internetuserate'] > '75')]

""" make a copy of all subsetted datas """ employ_copy1 = employ_sub1.copy() employ_copy2 = employ_sub2.copy() life_copy1 = life_sub1.copy() life_copy2 = life_sub2.copy() life_copy3 = life_sub3.copy() net_copy1 = net_sub1.copy() net_copy2 = net_sub2.copy() net_copy3 = net_sub3.copy() net_copy4 = net_sub4.copy()

""" displaying co 2 emissions by break downs """ print ("counts and countries for original 'employrate' less than 50%") employ1 = employ_copy1['employrate'].value_counts(sort=False, dropna=False) print(len(employ_copy1['employrate']), "countries with less than 50% employ rate") print(employ_copy1['country'])

print ("counts and countries for original 'employrate' greater 75%") employ2 = employ_copy2['employrate'].value_counts(sort=False, dropna=False) print(len(employ_copy2['employrate']), "countries with employ rate greater than 75%") print(employ_copy2['country'])

""" displaying internet usage by break downs """ print ("counts and countries for original 'internetuserate' less than 26") net1 = net_copy1['internetuserate'].value_counts(sort=False, dropna=False) print(len(net_copy1['internetuserate']), "countries with internet usage rate below 25%") print(net_copy1['country'])

print ("counts and countries for original 'internetuserate' between 25 and 50") net2 = net_copy2['internetuserate'].value_counts(sort=False, dropna=False) print(len(net_copy2['internetuserate']), "countries with internet usage rate between 25 and 50%") print(net_copy2['country'])

print ("counts and countries for original 'internetuserate' between 50 and 75") net3 = net_copy3['internetuserate'].value_counts(sort=False, dropna=False) print(len(net_copy3['internetuserate']), "countries with internet usage rate between 50 and 75%") print(net_copy3['country'])

print ("counts and countries for original 'internetuserate' greater than 75") net4 = net_copy4['internetuserate'].value_counts(sort=False, dropna=False) print(len(net_copy4['internetuserate']), "countries with internet usage rate greater than 75%") print(net_copy4['country'])

""" displaying life expectancy by break downs """ print ("counts countries for original 'lifeexpectancy' less than 51") life1 = life_copy1['lifeexpectancy'].value_counts(sort=False, dropna=False) print(len(life_copy1['lifeexpectancy']), "countries with life expectancy below 51") print(life_copy1['country'])

print ("counts countries for original 'lifeexpectancy' less than 76") life2 = life_copy2['lifeexpectancy'].value_counts(sort=False, dropna=False) print(len(life_copy2['lifeexpectancy']), "countries with life expectancy between 50 and 75") print(life_copy2['country'])

print ("counts countries for original 'lifeexpectancy' greater than 75") life3 = life_copy3['lifeexpectancy'].value_counts(sort=False, dropna=False) print(len(life_copy3['lifeexpectancy']), "countries with life expectancy over 75") print(life_copy3['country'])

""" recode missing values to python missing (NaN)  """ employ_copy1['employrate']=employ_copy1['employrate'].replace(0, numpy.nan) employ_copy2['employrate']=employ_copy2['employrate'].replace(0, numpy.nan) net_copy1['internetuserate']=net_copy1['internetuserate'].replace(0, numpy.nan) net_copy2['internetuserate']=net_copy2['internetuserate'].replace(0, numpy.nan) net_copy3['internetuserate']=net_copy3['internetuserate'].replace(0, numpy.nan) net_copy4['internetuserate']=net_copy4['internetuserate'].replace(0, numpy.nan) life_copy1['lifeexpectancy']=life_copy1['lifeexpectancy'].replace(0, numpy.nan) life_copy2['lifeexpectancy']=life_copy2['lifeexpectancy'].replace(0, numpy.nan) life_copy3['lifeexpectancy']=life_copy3['lifeexpectancy'].replace(0, numpy.nan)

2) Output:

counts and countries for original 'employrate' less than 50% 199 countries with less than 50% employ rate 0              Afghanistan 1                  Albania 2                  Algeria 3                  Andorra 5      Antigua and Barbuda

208                Vietnam 209     West Bank and Gaza 210            Yemen, Rep. 211                 Zambia 212               Zimbabwe Name: country, Length: 199, dtype: object counts and countries for original 'employrate' greater 75% 14 countries with employ rate greater than 75% 4                    Angola 28             Burkina Faso 29                  Burundi 30                 Cambodia 60                 Ethiopia 78                   Guinea 103                    Laos 114              Madagascar 131              Mozambique 156                   Qatar 160                  Rwanda 189                Tanzania 199                  Uganda 201    United Arab Emirates Name: country, dtype: object counts and countries for original 'internetuserate' less than 26 73 countries with internet usage rate below 25% 2           Algeria 18           Belize 21           Bhutan 22          Bolivia 28     Burkina Faso

199          Uganda 205      Uzbekistan 210     Yemen, Rep. 211          Zambia 212        Zimbabwe Name: country, Length: 73, dtype: object counts and countries for original 'internetuserate' between 25 and 50 66 countries with internet usage rate between 25 and 50% 0             Afghanistan 1                 Albania 6               Argentina 7                 Armenia 8                   Aruba

200               Ukraine 204               Uruguay 207             Venezuela 208               Vietnam 209    West Bank and Gaza Name: country, Length: 66, dtype: object counts and countries for original 'internetuserate' between 50 and 75 41 countries with internet usage rate between 50 and 75% 10                    Austria 13                    Bahrain 15                   Barbados 17                    Belgium 23     Bosnia and Herzegovina 34             Cayman Islands 46                    Croatia 48                     Cyprus 49                 Czech Rep. 51                   Djibouti 57          Equatorial Guinea 59                    Estonia 66                      Gabon 71                  Gibraltar 73                  Greenland 83           Hong Kong, China 84                    Hungary 86                      India 90                    Ireland 91                     Israel 92                      Italy 103                      Laos 104                    Latvia 107                   Liberia 110                 Lithuania 112              Macao, China 113            Macedonia, FYR 116                  Malaysia 119                     Malta 129                Montenegro 133                   Namibia 135                     Nepal 145                      Oman 153                    Poland 154                  Portugal 164                     Samoa 173                 Singapore 175                  Slovenia 179                     Spain 203             United States 206                   Vanuatu Name: country, dtype: object counts and countries for original 'internetuserate' greater than 75 33 countries with internet usage rate greater than 75% 3                    Andorra 4                     Angola 5        Antigua and Barbuda 9                  Australia 20                   Bermuda 32                    Canada 50                   Denmark 61            Faeroe Islands 63                   Finland 64                    France 67                    Gambia 69                   Germany 70                     Ghana 81                     Haiti 85                   Iceland 87                 Indonesia 94                     Japan 98                  Kiribati 100              Korea, Rep. 109            Liechtenstein 111               Luxembourg 136              Netherlands 139              New Zealand 140                Nicaragua 144                   Norway 156                    Qatar 161    Saint Kitts and Nevis 174          Slovak Republic 183                Swaziland 184                   Sweden 185              Switzerland 201     United Arab Emirates 202           United Kingdom Name: country, dtype: object counts countries for original 'lifeexpectancy' less than 51 31 countries with life expectancy below 51 0                Afghanistan 3                    Andorra 5        Antigua and Barbuda 20                   Bermuda 34            Cayman Islands 35      Central African Rep. 36                      Chad 41          Congo, Dem. Rep. 43              Cook Islands 52                  Dominica 61            Faeroe Islands 71                 Gibraltar 73                 Greenland 79             Guinea-Bissau 98                  Kiribati 106                  Lesotho 109            Liechtenstein 120         Marshall Islands 127                   Monaco 134                    Nauru 143                     Niue 147                    Palau 161    Saint Kitts and Nevis 165               San Marino 170    Serbia and Montenegro 171               Seychelles 172             Sierra Leone 183                Swaziland 187                   Taiwan 198                   Tuvalu 211                   Zambia Name: country, dtype: object counts countries for original 'lifeexpectancy' less than 76 117 countries with life expectancy between 50 and 75 2                 Algeria 4                  Angola 7                 Armenia 11             Azerbaijan 14             Bangladesh

206               Vanuatu 207             Venezuela 209    West Bank and Gaza 210           Yemen, Rep. 212              Zimbabwe Name: country, Length: 117, dtype: object counts countries for original 'lifeexpectancy' greater than 75 65 countries with life expectancy over 75 1                   Albania 6                 Argentina 8                     Aruba 9                 Australia 10                  Austria

201    United Arab Emirates 202          United Kingdom 203           United States 204                 Uruguay 208                 Vietnam Name: country, Length: 65, dtype: object

[hiphoptilinfin]

Nod Faktor Single Bars & Beats Played On The Killshot Hour 7/17/20 

I want to send a big shout out to Stephanie Marie, the program director of The Killshot Hour for playing Bars & Beats featuring Craig G, HeadKrack & RA Cyph on their July 17, 2020 episode.  

The Killshot Hour is a syndicated radio show based in Columbus Ohio.  The Killshot Hour can also be heard in Detroit on Blast Global Radio Mon-Fri at 11pm EST, In Philadephia on GSFM Radio on Tuesday at 8pm EST, In Miami on WNDO 109.9 FM Fri & Sat at 6pm EST & In New Jersey on WBAP Bluntzville Radio Mon-Fri at 10pm EST.  

Everyone can listen to the Killshot Hour at http://net1.citrus3.com:8492/index.html

PROMOTE YOUR MUSIC OR YOUR BUSINESS ON THE HIP HOP TIL INFINITY BANGERZ SPOTIFY PLAYLIST VIP EMAIL LIST

Do you have music or a business you want to promote? You can promote your music or your business to thousands of people worldwide, who subscribe to the Hip Hop Til Infinity Bangerz Spotify Playlist VIP email list for one month for only $99.99.  Send us an email today to promote your music or your business at hhtill99@gmail.com.  

To work with Nod Faktor on hip hop remixes & hip hop music production projects.  Send an email to nodfaktorbeats@gmail.com   Dope hip hop artists wanting to take your music career to the next level & work with Hip Hop Til Infinity on digital marketing, album promotion & radio promotion.  Send an email to hiphoptilinfinity@gmail.com 

If you enjoy this hip hop content and would like to donate to Hip Hop Til Infinity so we can continue creating good content for hip hop fans worldwide.  You can send donations by cashapp to $hiphoptil, send donations by paypal at hhtill99@gmail.com & send donations by zelle at globalracks99@gmail.com      Follow The Killshot Hour On Social Media Platforms https://www.facebook.com/614promogod 

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https://www.youtube.com/c/PROMOGODUndergroundSoundOff   Follow Nod Faktor On Social Media Platforms  https://www.facebook.com/nodfaktor  

https://twitter.com/nodfaktorbeats  

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https://www.youtube.com/channel/UCFhcIhflUkYC6ie13IA8V5w/playlists   Follow Hip Hop Til Infinity On Social Media Platforms 

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#thekillshothour #hiphoptilinfinity #hiphop #nodfaktor #buffalonystateofmind #boombap #goldenera #fortheculture #keepgrindin #keepshinin   

[magtira]

ISP startup Net1 launches prepaid Wi-Fi service

ISP startup Net1 launches prepaid Wi-Fi service

Filipinos now have a reason to rejoice as they have another option for connecting to the Internet. This is through Net1, a startup Internet service provider that aims to connect unserved and underserved areas in the country via fixed wireless broadband. Simply put, communities that are not reached by other telcos can now have Wi-Fi installed in their homes or at small- or medium-sized enterprises…

[gizmologi]

Net1 Indonesia Respon Cepat Gempa Lombok dengan Bagikan WiFi 4G LTE

Net1 Indonesia Respon Gempa Lombok dengan Bagikan WiFi 4G LTE

Gempa bumi berkekuatan 7 Skala Richter di Lombok Minggu lalu turut berdampak pada terganggunya infrastruktur telekomunikasi bagi warga di Lombok dan sekitarnya. Respon Net1 Indonesia terhitung cepat, yakni dengan menyediakan WiFi 4G LTE ke para pengungsi gempa di Lombok dan sekitarnya.

Respon Net1 Indonesia ini dilakukan dengan menggandeng Dinas Komunikasi dan Informatika (Diskominfo) Pemerintah…

[myshitblogger-blog]

Sassa tells Net1 to retract 'misleading' pamphlet

Sassa tells Net1 to retract ‘misleading’ pamphlet

[ad_1]

The South African Social Security Agency (Sassa) has given Grindrod Bank and Net1 five days to retract a “misleading” pamphlet being distributed to social grant beneficiaries across the country.

Sassa accounts have for the last six years been held at Grindrod Bank on behalf of Cash Paymaster Services (CPS), which used to pay all the social grants, GroundUp reported on Wednesday.

Net1 is…

[selularid]

Incar IoT Pedesaan, Net1 Indonesia Fokus Garap B2B

Incar IoT Pedesaan, Net1 Indonesia Fokus Garap B2B

Jakarta, Selular.ID – Setelah mengantongi izin untuk menggelar jaringan 4G LTE di frekuensi 450MHz secara nasional, Net1 Indonesia mulai mengaktifkan layanannya tahun ini. Dimulai dari Aceh, Banten, Lombok, Sulawesi Selatan, Maluku, dan yang terbaru di Pulau Dewata Bali. Lokasi-lokasi itu merupakan area operasional Ceria, layanan CDMA milik Sampoerna Telekomunikasi Indonesia (STI). STI saat ini…

[techfinancialsza-blog]

SA's Net1 Buys a Stake in Bank Based in one of the Smallest Countries in the World

SA’s Net1 Buys a Stake in Bank Based in one of the Smallest Countries in the World

by Staff Writer

JSE and Nasdaq-listed tech firm Net1 announced on Tuesday it has acquired a strategic stake in Bank Frick, which is based in Balzers, Liechtenstein.

Liechtenstein is the sixth-smallest country in the world. It lies in the heart of the Alps between Switzerland and Austria. It is a is a doubly landlocked German-speaking microstate in Central Europe.[8] It is a constitutional monarchy

[kavinsaunders]

Throw Back photo...d.J. Access Hpc Records #DjAccess1 https://gospelandministry1.wixsite.com/net1 https://www.instagram.com/p/CosfYkwukM0/?igshid=NGJjMDIxMWI=

[pannimanagementteam]

Erp Today Issue Four By Paul Esherwood

Thousands of organizations around the globe depend on Oracle E-Business Suite to run their key enterprise operations. Oracle continues to invest in the suite with a give attention to functional advances, mobility, UI modernization, and operational efficiency. Its an entire, modular solution that gets any manufacturing environment prepared for the future of manufacturing. By gathering perception sage x3 cannabis on their entire production, Prodsmart helps them totally understand their surroundings, optimize their operations and reply to vary rapidly. This offers SMBs the confidence to make choices based on knowledge, negotiate from a position of power, and gasoline business growth.

M1 is a subscription cloud-based or on-premise ERP software for manufacturers, enabling you to tie your business operations collectively in a single system to centralize your data. It lets you coordinate and share knowledge throughout numerous features inside your corporation from sales, inventory, scheduling, production, delivery, and more. The resolution is appropriate for small to midsize firms that manufacture via repetitive, make-to-stock, make-to-order and engineer-to-order processes. M1’s product configurator provides a multi-level, automated configuration that builds product configurations from a BOM, together with all sub-assemblies. Users can even add additional guidelines and formulation after the wizard is complete. With M1, you even have entry to differentiators like Alora Machine Intelligence, Avalara, uniPoint, KnowledgeSync, Net1, and a lot of others.

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Essentially, the Odoo ERP combines a collection of enterprise administration software program instruments that can be used company-wide, across small and mid-sized companies. Omnna is an entire enterprise platform that consolidates your individuals, merchandise and processes right into a single database providing visibility and management of your organization. Software for Cold Storage Management, Food Production, Food Distribution, Distribution, or Service Providers. To high all of it, it works on any web-enabled gadget like computer systems, tablets, good phones, and handheld bar code scanners. Enjoy the convenience of having every little thing you need all in one place, and likewise having the ability to customise our already unmatched ERP system to further suit your unique business wants. "Go Live" in document time with our feature-driven turnkey solution, or tell us what you're in search of and we'll create a custom-written bundle just for you.

Sage X3 is designed to evolve easily as your small business grows or modifications, supplying you with greater control and broader flexibility to support your small business technique and improvement — not hinder it. Sage ERP X3, a sooner, easier, and flexible enterprise useful resource planning solution, gives you the best instruments and perception to scale back costs, grow revenues, and win new prospects. Let us present you how Sage ERP X3 can allow you to accelerate your corporation development in a more efficient method while reducing prices, higher serving your prospects, and staying a step ahead of the competition. NexTec Group is an award-winning business software program consulting firm with over 25 years’ expertise.

Operating in a fancy regulatory setting rife with competitors, demanding clients and requires transparency is extremely troublesome. Software for the trade helps oilfield companies firms make quicker enterprise decisions, handle advanced tasks and increase earnings and margins. Go past ERP with a sooner, easier and more flexible enterprise administration system. Sage X3 offers a greater method to manage your entire enterprise, at a decrease value and on a worldwide scale.

NexTec meals and agriculture specialists have partnered with leading cannabis trade specialists to develop cannabis ERP software program that can handle your cannabis enterprise because it should. Their answer not solely tracks seed gross sales transactions however covers your whole cannabis transactions. Our highly effective cloud-based enterprise useful resource planning options assist greenhouses grow their products and their business with robust administration options for finances, planning, supply chain management, gross sales and extra. With instruments from the Microsoft Dynamics line of products, Velosio’s plant nursery software program solutions might help you stay forward of the curve with best-fit functions for a digitally targeted enterprise world.

MRPeasy is a mix of a ERP and MRP system into a single cloud-based solution tailored to the wants of small and midsize producers. Dynamics 365 Customer Voice is a suggestions administration system that helps Customer Engagement professionals take heed to clients, floor insights, and in... Manage the full customer lifecycle for social and digital touchpoints with an information platform from Microsoft that mixes CRM, marketing sage x3 hemp, internet analytics ... Kechie is reinventing how small to medium sized organisations in manufacturing, distribution, and retail operate by enabling you to fully combine yo... JustFoodERP Foundation Edition delivers food processors and distributors an answer and a risk-reduced ERP implementation that will tackle the entire... JOMAR’s ERP and Enterprise Application Suite is aimed is medium to large sized organizations in manufacturing and distribution.