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Data Extraction

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Muhammad A.

@mohdawais944

5,0

2

3,1

3,1

100%

Excel Expert | Data Analyst | Python

$20 USD / hora

・

Germany (8:30 a. m.)

・

Se unió el julio 22, 2020

$20 USD / hora

・

Hi there, I am Muhammad Awais residing in Germany. I am an experienced freelancer specializing in Excel, data analysis, and Python programming. With expertise in advanced Excel functions, data manipulation, statistical analysis, and Python scripting, I can help you unlock valuable insights from your data. Let's collaborate on your project and turn data into actionable results. Contact me today to get started.

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100 %

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100 %

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100 %

Ver todo Data Entry Clerks en Germany

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In this project, I utilized web scraping techniques to gather information from vape store websites in New York. I extracted essential details such as store names, websites, addresses, and phone numbers. By employing specialized tools and scripts, I automated the process of data collection and ensured accurate and comprehensive results. The extracted data was then exported to an Excel file for easy analysis and further use. This project enabled clients to access a curated database of vape stores in New York, empowering them with valuable insights for market research, business planning, and decision-making.

Web Scrapping and Exporting Data to Excel

In this project, I utilized web scraping techniques to gather information from vape store websites in New York. I extracted essential details such as store names, websites, addresses, and phone numbers. By employing specialized tools and scripts, I automated the process of data collection and ensured accurate and comprehensive results. The extracted data was then exported to an Excel file for easy analysis and further use. This project enabled clients to access a curated database of vape stores in New York, empowering them with valuable insights for market research, business planning, and decision-making.

Web Scrapping and Exporting Data to Excel

In this project, I utilized web scraping techniques to gather information from vape store websites in New York. I extracted essential details such as store names, websites, addresses, and phone numbers. By employing specialized tools and scripts, I automated the process of data collection and ensured accurate and comprehensive results. The extracted data was then exported to an Excel file for easy analysis and further use. This project enabled clients to access a curated database of vape stores in New York, empowering them with valuable insights for market research, business planning, and decision-making.

Web Scrapping and Exporting Data to Excel

11136844

More information can ve found on my Github account: https://github.com/awais345

The repository contains the data analysis of the sales for an electronic store for the year 2019. The analysis is performed using Python programming language and various data analysis libraries.

A Journey through Exploratory Data Analysis

11136839

Read amore about the project on my Githun account: https://github.com/awais345

This repository contains the step by step analysis of Electric Vehicles and price prediction using linear regression model

Exploring EV Data: Insights and Price Prediction

Read amore about the project on my Githun account: https://github.com/awais345

This repository contains the step by step analysis of Electric Vehicles and price prediction using linear regression model

Exploring EV Data: Insights and Price Prediction

11136794

Data Analysis with Python - complete analysis can be found on my github account: https://github.com/awais345

Dataset: The dataset 'station_data_dataverse' is provided in a .CSV format. It contains anonymized data, ensuring the privacy of the individuals and organizations involved. Each charging session record includes details such as charging duration, energy consumption, charging cost, station ID, site information, and driver information.

Analysis Methodology: The analysis of the dataset is performed using Python and various data analysis libraries, such as Pandas, NumPy, seaborn and Matplotlib.

Results and Insights: The analysis yields valuable insights into charging behavior, power consumption, charging costs, devices (android, IOS, web) used to log charging session, and the charging pattern at various location.

Data Analysis - Electric Vehicle Charging Sessions Analysis

Data Analysis with Python - complete analysis can be found on my github account: https://github.com/awais345

Dataset: The dataset 'station_data_dataverse' is provided in a .CSV format. It contains anonymized data, ensuring the privacy of the individuals and organizations involved. Each charging session record includes details such as charging duration, energy consumption, charging cost, station ID, site information, and driver information.

Analysis Methodology: The analysis of the dataset is performed using Python and various data analysis libraries, such as Pandas, NumPy, seaborn and Matplotlib.

Results and Insights: The analysis yields valuable insights into charging behavior, power consumption, charging costs, devices (android, IOS, web) used to log charging session, and the charging pattern at various location.

Data Analysis - Electric Vehicle Charging Sessions Analysis

Data Analysis with Python - complete analysis can be found on my github account: https://github.com/awais345

Dataset: The dataset 'station_data_dataverse' is provided in a .CSV format. It contains anonymized data, ensuring the privacy of the individuals and organizations involved. Each charging session record includes details such as charging duration, energy consumption, charging cost, station ID, site information, and driver information.

Analysis Methodology: The analysis of the dataset is performed using Python and various data analysis libraries, such as Pandas, NumPy, seaborn and Matplotlib.

Results and Insights: The analysis yields valuable insights into charging behavior, power consumption, charging costs, devices (android, IOS, web) used to log charging session, and the charging pattern at various location.

Data Analysis - Electric Vehicle Charging Sessions Analysis

In this project, I utilized web scraping techniques to gather information from vape store websites in New York. I extracted essential details such as store names, websites, addresses, and phone numbers. By employing specialized tools and scripts, I automated the process of data collection and ensured accurate and comprehensive results. The extracted data was then exported to an Excel file for easy analysis and further use. This project enabled clients to access a curated database of vape stores in New York, empowering them with valuable insights for market research, business planning, and decision-making.

Web Scrapping and Exporting Data to Excel

In this project, I utilized web scraping techniques to gather information from vape store websites in New York. I extracted essential details such as store names, websites, addresses, and phone numbers. By employing specialized tools and scripts, I automated the process of data collection and ensured accurate and comprehensive results. The extracted data was then exported to an Excel file for easy analysis and further use. This project enabled clients to access a curated database of vape stores in New York, empowering them with valuable insights for market research, business planning, and decision-making.

Web Scrapping and Exporting Data to Excel

In this project, I utilized web scraping techniques to gather information from vape store websites in New York. I extracted essential details such as store names, websites, addresses, and phone numbers. By employing specialized tools and scripts, I automated the process of data collection and ensured accurate and comprehensive results. The extracted data was then exported to an Excel file for easy analysis and further use. This project enabled clients to access a curated database of vape stores in New York, empowering them with valuable insights for market research, business planning, and decision-making.

Web Scrapping and Exporting Data to Excel

11136844

More information can ve found on my Github account: https://github.com/awais345

The repository contains the data analysis of the sales for an electronic store for the year 2019. The analysis is performed using Python programming language and various data analysis libraries.

A Journey through Exploratory Data Analysis

11136839

Read amore about the project on my Githun account: https://github.com/awais345

This repository contains the step by step analysis of Electric Vehicles and price prediction using linear regression model

Exploring EV Data: Insights and Price Prediction

Read amore about the project on my Githun account: https://github.com/awais345

This repository contains the step by step analysis of Electric Vehicles and price prediction using linear regression model

Exploring EV Data: Insights and Price Prediction

11136794

Data Analysis with Python - complete analysis can be found on my github account: https://github.com/awais345

Dataset: The dataset 'station_data_dataverse' is provided in a .CSV format. It contains anonymized data, ensuring the privacy of the individuals and organizations involved. Each charging session record includes details such as charging duration, energy consumption, charging cost, station ID, site information, and driver information.

Analysis Methodology: The analysis of the dataset is performed using Python and various data analysis libraries, such as Pandas, NumPy, seaborn and Matplotlib.

Results and Insights: The analysis yields valuable insights into charging behavior, power consumption, charging costs, devices (android, IOS, web) used to log charging session, and the charging pattern at various location.

Data Analysis - Electric Vehicle Charging Sessions Analysis

Data Analysis with Python - complete analysis can be found on my github account: https://github.com/awais345

Dataset: The dataset 'station_data_dataverse' is provided in a .CSV format. It contains anonymized data, ensuring the privacy of the individuals and organizations involved. Each charging session record includes details such as charging duration, energy consumption, charging cost, station ID, site information, and driver information.

Analysis Methodology: The analysis of the dataset is performed using Python and various data analysis libraries, such as Pandas, NumPy, seaborn and Matplotlib.

Results and Insights: The analysis yields valuable insights into charging behavior, power consumption, charging costs, devices (android, IOS, web) used to log charging session, and the charging pattern at various location.

Data Analysis - Electric Vehicle Charging Sessions Analysis

Data Analysis with Python - complete analysis can be found on my github account: https://github.com/awais345

Dataset: The dataset 'station_data_dataverse' is provided in a .CSV format. It contains anonymized data, ensuring the privacy of the individuals and organizations involved. Each charging session record includes details such as charging duration, energy consumption, charging cost, station ID, site information, and driver information.

Analysis Methodology: The analysis of the dataset is performed using Python and various data analysis libraries, such as Pandas, NumPy, seaborn and Matplotlib.

Results and Insights: The analysis yields valuable insights into charging behavior, power consumption, charging costs, devices (android, IOS, web) used to log charging session, and the charging pattern at various location.

Data Analysis - Electric Vehicle Charging Sessions Analysis

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5.0 · 2 Reviews

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