Logo Freelancer Bagaimana ia berfungsiLayari Pekerjaan
Log Masuk Daftar
Siarkan Projek
MENJELAJAH
Data Entry
Excel
PHP
Web Scraping
Web Search
Gambar muka depan profil
Anda kini mengikuti
Ralat mengikuti pengguna.
Pengguna ini tidak membenarkan pengguna untuk mengikuti mereka.
Anda telah mengikuti pengguna ini.
Pelan keahlian anda hanya membenarkan 0 mengikuti. Naik taraf di sini.
Berjaya menyahikut
Ralat tidak mengikuti pengguna.
Anda berjaya mengesyorkan
Ralat mengesyorkan pengguna.
Sesuatu telah berlaku. Sila segar semula halaman dan cuba lagi.
E-mel berjaya disahkan.
Avatar Pengguna
$5 USD / jam
Bendera EGYPT
kafr el dawwar, egypt
$5 USD / jam
Sekarang jam 12:01 PG di sini
Menyertai Oktober 3, 2020
1 Cadangan

Abdelaziz N.

@Abdelaziz2352000

 4.9 (14 ulasan)
3.9
3.9
90%
90%
$5 USD / jam
Bendera EGYPT
kafr el dawwar, egypt
$5 USD / jam
95%
Pekerjaan Disiapkan
100%
Mengikut Bajet
94%
Tepat Pada Masa
5%
Kadar Upah Semula

Data Engineer & Data Analyst

As a data professional and a Full-Time Freelancer, I'm passionate about delivering successful, efficient, and winning solutions for your business through transparency, reliability, trust, and outstanding customer care. I'd love to have the opportunity to discuss the project with you. Skills: - Python - Excel - SQL - Data Analysis - Machine learning - Dashboard Design (Power Bi) - Web Scraping - Data Entry - Data Engineering ✔ Full-Time Freelancer ✔ 24/7 Service ✔ Unlimited Revisions until client satisfaction ✔ Hourly Rate not Fixed ✔ LinkedIn Account: [login to view URL]
Freelancer Web Scraping Specialists Egypt
Lihat semua Web Scraping Specialists dalam Egypt

Hubungi Abdelaziz N. tentang pekerjaan anda

Log masuk untuk membincangkan sebarang butiran melalui sembang.

Portfolio

9621711
Get self-service analytics at enterprise scale Reduce the added cost, complexity, and security risks of multiple solutions with an analytics platform that scales from individuals to the organization as a whole. Use smart tools for strong results Find and share meaningful insights with hundreds of data visualizations, built-in AI capabilities, tight Excel integration, and pre-built and custom data connectors. Help protect your analytics data Keep your data secure with industry-leading data security capabilities including sensitivity labeling, end-to-end encryption, and real-time access monitoring.
power pi
9427535
Hello, I am a Data Entry Expert. I have good experience working with Data Entry: • Research • Market Research • Python. • SQL. • creating business reports and Dashboards. • Excel / CSV / XML / JSON Processing I will use some Tools and Different search Engines for your project like: • Google. • Bing. • Yahoo • Ask • Aol • Ecosia Regards, Abdelaziz.
Web search for Emails In different search Engines
Hello, I am a Data Entry Expert. I have good experience working with Data Entry: • Research • Market Research • Python. • SQL. • creating business reports and Dashboards. • Excel / CSV / XML / JSON Processing I will use some Tools and Different search Engines for your project like: • Google. • Bing. • Yahoo • Ask • Aol • Ecosia Regards, Abdelaziz.
Web search for Emails In different search Engines
9416506
Table of Contents Introduction Data Wrangling Exploratory Data Analysis Conclusions Introduction To complete my Data Analysis project I am using TMDb movies dataset. This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue. Certain columns, like ‘cast’ and ‘genres’, contain multiple values separated by pipe (|) characters. There are some odd characters in the ‘cast’ column. The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time. From this dataset we could try to solve many different questions such as : Is there an improvement in the quality of movies from year to year? What kinds of properties are associated with movies that have high revenues? Is the number of movies increase from year to year? Is there a relation between a movie runtime and the vote average? Who are the top 5 directors according to high rev
TMDb movie data analysis
Table of Contents Introduction Data Wrangling Exploratory Data Analysis Conclusions Introduction To complete my Data Analysis project I am using TMDb movies dataset. This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue. Certain columns, like ‘cast’ and ‘genres’, contain multiple values separated by pipe (|) characters. There are some odd characters in the ‘cast’ column. The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time. From this dataset we could try to solve many different questions such as : Is there an improvement in the quality of movies from year to year? What kinds of properties are associated with movies that have high revenues? Is the number of movies increase from year to year? Is there a relation between a movie runtime and the vote average? Who are the top 5 directors according to high rev
TMDb movie data analysis
Table of Contents Introduction Data Wrangling Exploratory Data Analysis Conclusions Introduction To complete my Data Analysis project I am using TMDb movies dataset. This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue. Certain columns, like ‘cast’ and ‘genres’, contain multiple values separated by pipe (|) characters. There are some odd characters in the ‘cast’ column. The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time. From this dataset we could try to solve many different questions such as : Is there an improvement in the quality of movies from year to year? What kinds of properties are associated with movies that have high revenues? Is the number of movies increase from year to year? Is there a relation between a movie runtime and the vote average? Who are the top 5 directors according to high rev
TMDb movie data analysis
Table of Contents Introduction Data Wrangling Exploratory Data Analysis Conclusions Introduction To complete my Data Analysis project I am using TMDb movies dataset. This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue. Certain columns, like ‘cast’ and ‘genres’, contain multiple values separated by pipe (|) characters. There are some odd characters in the ‘cast’ column. The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time. From this dataset we could try to solve many different questions such as : Is there an improvement in the quality of movies from year to year? What kinds of properties are associated with movies that have high revenues? Is the number of movies increase from year to year? Is there a relation between a movie runtime and the vote average? Who are the top 5 directors according to high rev
TMDb movie data analysis
Table of Contents Introduction Data Wrangling Exploratory Data Analysis Conclusions Introduction To complete my Data Analysis project I am using TMDb movies dataset. This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue. Certain columns, like ‘cast’ and ‘genres’, contain multiple values separated by pipe (|) characters. There are some odd characters in the ‘cast’ column. The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time. From this dataset we could try to solve many different questions such as : Is there an improvement in the quality of movies from year to year? What kinds of properties are associated with movies that have high revenues? Is the number of movies increase from year to year? Is there a relation between a movie runtime and the vote average? Who are the top 5 directors according to high rev
TMDb movie data analysis
7751104
scraping large data from https://www.local.ch/ website
Total around 10-15.000 entries
scraping large data from https://www.local.ch/ website
Total around 10-15.000 entries
7514546
Scrape data from yellow pages Australia website 300 industries, approximately 340,000 records. but records keep changing continuously. it could be little more or less now. I need 9 pieces (columns) of information for each company. As a sample, 1) Accountants & Auditors
Scrape data from yellow pages australia website
Scrape data from yellow pages Australia website 300 industries, approximately 340,000 records. but records keep changing continuously. it could be little more or less now. I need 9 pieces (columns) of information for each company. As a sample, 1) Accountants & Auditors
Scrape data from yellow pages australia website
Scrape data from yellow pages Australia website 300 industries, approximately 340,000 records. but records keep changing continuously. it could be little more or less now. I need 9 pieces (columns) of information for each company. As a sample, 1) Accountants & Auditors
Scrape data from yellow pages australia website
Scrape data from yellow pages Australia website 300 industries, approximately 340,000 records. but records keep changing continuously. it could be little more or less now. I need 9 pieces (columns) of information for each company. As a sample, 1) Accountants & Auditors
Scrape data from yellow pages australia website
7466926
download some data like images of Huawei protects and its descriptions in form excel file
scraping data from amazon like images and descriptions
download some data like images of Huawei protects and its descriptions in form excel file
scraping data from amazon like images and descriptions
download some data like images of Huawei protects and its descriptions in form excel file
scraping data from amazon like images and descriptions
9621711
Get self-service analytics at enterprise scale Reduce the added cost, complexity, and security risks of multiple solutions with an analytics platform that scales from individuals to the organization as a whole. Use smart tools for strong results Find and share meaningful insights with hundreds of data visualizations, built-in AI capabilities, tight Excel integration, and pre-built and custom data connectors. Help protect your analytics data Keep your data secure with industry-leading data security capabilities including sensitivity labeling, end-to-end encryption, and real-time access monitoring.
power pi
9427535
Hello, I am a Data Entry Expert. I have good experience working with Data Entry: • Research • Market Research • Python. • SQL. • creating business reports and Dashboards. • Excel / CSV / XML / JSON Processing I will use some Tools and Different search Engines for your project like: • Google. • Bing. • Yahoo • Ask • Aol • Ecosia Regards, Abdelaziz.
Web search for Emails In different search Engines
Hello, I am a Data Entry Expert. I have good experience working with Data Entry: • Research • Market Research • Python. • SQL. • creating business reports and Dashboards. • Excel / CSV / XML / JSON Processing I will use some Tools and Different search Engines for your project like: • Google. • Bing. • Yahoo • Ask • Aol • Ecosia Regards, Abdelaziz.
Web search for Emails In different search Engines
9416506
Table of Contents Introduction Data Wrangling Exploratory Data Analysis Conclusions Introduction To complete my Data Analysis project I am using TMDb movies dataset. This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue. Certain columns, like ‘cast’ and ‘genres’, contain multiple values separated by pipe (|) characters. There are some odd characters in the ‘cast’ column. The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time. From this dataset we could try to solve many different questions such as : Is there an improvement in the quality of movies from year to year? What kinds of properties are associated with movies that have high revenues? Is the number of movies increase from year to year? Is there a relation between a movie runtime and the vote average? Who are the top 5 directors according to high rev
TMDb movie data analysis
Table of Contents Introduction Data Wrangling Exploratory Data Analysis Conclusions Introduction To complete my Data Analysis project I am using TMDb movies dataset. This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue. Certain columns, like ‘cast’ and ‘genres’, contain multiple values separated by pipe (|) characters. There are some odd characters in the ‘cast’ column. The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time. From this dataset we could try to solve many different questions such as : Is there an improvement in the quality of movies from year to year? What kinds of properties are associated with movies that have high revenues? Is the number of movies increase from year to year? Is there a relation between a movie runtime and the vote average? Who are the top 5 directors according to high rev
TMDb movie data analysis
Table of Contents Introduction Data Wrangling Exploratory Data Analysis Conclusions Introduction To complete my Data Analysis project I am using TMDb movies dataset. This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue. Certain columns, like ‘cast’ and ‘genres’, contain multiple values separated by pipe (|) characters. There are some odd characters in the ‘cast’ column. The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time. From this dataset we could try to solve many different questions such as : Is there an improvement in the quality of movies from year to year? What kinds of properties are associated with movies that have high revenues? Is the number of movies increase from year to year? Is there a relation between a movie runtime and the vote average? Who are the top 5 directors according to high rev
TMDb movie data analysis
Table of Contents Introduction Data Wrangling Exploratory Data Analysis Conclusions Introduction To complete my Data Analysis project I am using TMDb movies dataset. This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue. Certain columns, like ‘cast’ and ‘genres’, contain multiple values separated by pipe (|) characters. There are some odd characters in the ‘cast’ column. The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time. From this dataset we could try to solve many different questions such as : Is there an improvement in the quality of movies from year to year? What kinds of properties are associated with movies that have high revenues? Is the number of movies increase from year to year? Is there a relation between a movie runtime and the vote average? Who are the top 5 directors according to high rev
TMDb movie data analysis
Table of Contents Introduction Data Wrangling Exploratory Data Analysis Conclusions Introduction To complete my Data Analysis project I am using TMDb movies dataset. This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue. Certain columns, like ‘cast’ and ‘genres’, contain multiple values separated by pipe (|) characters. There are some odd characters in the ‘cast’ column. The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time. From this dataset we could try to solve many different questions such as : Is there an improvement in the quality of movies from year to year? What kinds of properties are associated with movies that have high revenues? Is the number of movies increase from year to year? Is there a relation between a movie runtime and the vote average? Who are the top 5 directors according to high rev
TMDb movie data analysis
7751104
scraping large data from https://www.local.ch/ website
Total around 10-15.000 entries
scraping large data from https://www.local.ch/ website
Total around 10-15.000 entries
7514546
Scrape data from yellow pages Australia website 300 industries, approximately 340,000 records. but records keep changing continuously. it could be little more or less now. I need 9 pieces (columns) of information for each company. As a sample, 1) Accountants & Auditors
Scrape data from yellow pages australia website
Scrape data from yellow pages Australia website 300 industries, approximately 340,000 records. but records keep changing continuously. it could be little more or less now. I need 9 pieces (columns) of information for each company. As a sample, 1) Accountants & Auditors
Scrape data from yellow pages australia website
Scrape data from yellow pages Australia website 300 industries, approximately 340,000 records. but records keep changing continuously. it could be little more or less now. I need 9 pieces (columns) of information for each company. As a sample, 1) Accountants & Auditors
Scrape data from yellow pages australia website
Scrape data from yellow pages Australia website 300 industries, approximately 340,000 records. but records keep changing continuously. it could be little more or less now. I need 9 pieces (columns) of information for each company. As a sample, 1) Accountants & Auditors
Scrape data from yellow pages australia website
7466926
download some data like images of Huawei protects and its descriptions in form excel file
scraping data from amazon like images and descriptions
download some data like images of Huawei protects and its descriptions in form excel file
scraping data from amazon like images and descriptions
download some data like images of Huawei protects and its descriptions in form excel file
scraping data from amazon like images and descriptions

Ulasan

Perubahan disimpan
Menunjukkan 1 - 5 daripada 14 ulasan
 Tapis ulasan mengikut:
5.0
$16.00 USD
Pro-level Educational PowerPoint Designer Needed
he's soo cooperative
Excel
Powerpoint
Word
Presentations
Avatar Pengguna
Bendera Raya A.
@roozzzz8
•
26 hari yang lalu
5.0
$25.00 USD
Script for Web Scrapping from rarity.tools
Abdelaziz did a great job scrapping the data i needed and he did it in a short time, I highly recommend him.
Python
Web Scraping
MySQL
BeautifulSoup
Selenium
Avatar Pengguna
Bendera Leonardo G.
@leonardogutie
•
2 tahun yang lalu
5.0
$3.00 USD
Process data online
Very professional freelancer. Work delivered 100% genuine.
Data Entry
Web Search
H
Bendera Hubert L.
@hubertlis
•
2 tahun yang lalu
5.0
₹600.00 INR
Project 31529549 has been deleted
Satisfied with work perfect work delivers on time.
Avatar Pengguna
Bendera Tushar J.
@tusharjoshi948
•
3 tahun yang lalu
4.0
$25.00 USD
Maps labeling (Arabic is required)
Abdelaziz labelled my map very well and I may hire him for a similar project. Recommended.
Data Entry
JSON
Geographical Information System (GIS)
Avatar Pengguna
Bendera Abdulaziz J.
@aziog91
•
3 tahun yang lalu

Pengalaman

web scraper

upwork
Jan 2018 - Hari ini
the web scraping is considered the best resource of leads, it contains billions of data for all businesses categories, if you would like to take benefits from it, then you are at the right place! We will work together until you get the leads that fit your needs. My spiders are ready for collecting the leads! Just contact me to trigger the start button.

Pendidikan

Bachelor Degree in electronic and communications Engineering

Alexandria University, Egypt 2018 - 2023
(5 tahun)

Kelayakan

Data Analysis Professional Nanodegree Program

Udacity
2021
✅ Develop programs in Python ✅ Manipulate data using NumPy ✅ Load and process data using Pandas ✅ Use Anaconda to manage your programming environment ✅ Investigate a dataset using Python data analysis packages ✅ Perform the entire data analysis process on a dataset ✅ Data Wrangling ✅ Gather data from multiple sources in a variety of formats ✅ Assess the quality and tidiness of data visually and programmatically ✅ Clean data using Python and Pandas

Ask Questions to Make Data-Driven Decisions

Coursera
2021
✅Explain how each step of the problem-solving road map contributes to common analysis scenarios. ✅Discuss the use of data in the decision-making process. ✅Demonstrate the use of spreadsheets to complete basic tasks of the data analyst including entering and organizing data. ✅Describe the key ideas associated with structured thinking. Skills acquired: ▶️Spreadsheet ▶️Questioning ▶️Decision-Making ▶️Problem Solving ▶️Data Analysis

Data Analysis Challenger

Udacity
2021
✅Calculate summary statistics using spreadsheets ✅Create data visualizations using spreadsheets ✅Ask questions and answer them using data ✅Calculate key business metrics in financial analysis and interpret values ✅Forecast financial metrics using scenario analysis

Hubungi Abdelaziz N. tentang pekerjaan anda

Log masuk untuk membincangkan sebarang butiran melalui sembang.

Pengesahan

Pekerja Bebas Pilihan
Identiti Disahkan
Pembayaran Disahkan
Telefon Disahkan
E-mel Disahkan
Facebook Dihubungkan

Kemahiran Teratas

Web Scraping 14
Data Entry 8
PHP 6
Excel 6
Web Search 6

Layari Pekerja Bebas Serupa

Web Scraping Specialists in Egypt
Web Scraping Specialists
Data Entry Clerks
PHP Developers

Layari Pameran Serupa

Web Scraping
Data Entry
PHP
Excel
Pengguna Sebelumnya Pengguna Seterusnya
Jemputan berjaya dihantar!
Terima kasih! Kami telah menghantar pautan melalui e-mel kepada anda untuk menuntut kredit percuma anda.
Sesuatu telah berlaku semasa menghantar e-mel anda. Sila cuba lagi.
Logo Freelancer Malaysia / Bahasa Malaysia Bantuan & Sokongan Pekerja bebas Kategori ProjekPeraduanPekerja BebasEnterprise KeahlianProgram Pekerja Bebas PilihanPengurusan ProjekPekerjaan TempatanPhoto AnywherePameranAPI untuk PembangunDisahkanAplikasi Desktop TentangTentang kamiBagaimana ia BerfungsiKeselamatanPelaburPeta LamanKisahDalam BeritaPasukanAnugerahSiaran AkhbarKerjaya Terma Dasar PrivasiTerma dan SyaratDasar HakciptaTatakelakuanYuran dan Caj Rakan KongsiEscrow.comLoadshiftWarrior Forum AplikasiLogo Apple App StoreLogo Mainan Google
Salin ke papan keratan gagal, sila cuba lagi selepas melaraskan kebenaran anda.
Disalin ke papan keratan.
Pengguna Berdaftar Jumlah Pekerjaan Disiarkan
Freelancer ® is a registered Trademark of Freelancer Technology Pty Limited (ACN 142 189 759)
Copyright © 2024 Freelancer Technology Pty Limited (ACN 142 189 759)
Memuatkan pratonton
Kebenaran diberikan untuk Geolocation.
Sesi log masuk anda telah luput dan telah dilog keluar. Sila log masuk sekali lagi.