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사용자 아바타
$10 USD / 시간
국기 (EGYPT)
el-mahalla el-kubra, egypt
$10 USD / 시간
현지시간은 9:28 AM입니다
9월 24, 2022에 가입했습니다
0 건의 추천

Omar Ahmad B.

@Badromar5522

 5.0 (1 건의 리뷰)
0.7
0.7
100%
100%
$10 USD / 시간
국기 (EGYPT)
el-mahalla el-kubra, egypt
$10 USD / 시간
100%
작업 완료
100%
예산 준수
100%
기한 준수
해당 사항 없음.
재고용률

Data Analyst

My name is Omar Ahmed Badr and I am a current student at the College of Engineering. With an IBM certificate in data analysis and experience in Tableau, I have a strong understanding of data visualization and dashboard creation. Additionally, I have expertise in web scraping and data extraction using Python. My skills and experience include: Analyzing data to extract key insights Proficiency in using Excel for data analysis Utilizing tools and techniques such as Python, Pandas, and Matplotlib to analyze and visualize data Creating visually appealing reports and presentations using Tableau Designing interactive dashboards to visualize complex data sets Utilizing web scraping techniques to extract data from websites using Python Collaborating effectively as part of a team or independently to deliver successful data analysis projects Possessing strong problem-solving skills and attention to detail I am confident that my skills and experience make me a valuable asset in any data analysis role, and I look forward to utilizing my expertise to support your business needs.
Freelancer Data Entry Clerks Egypt
Data Entry Clerks 분야의 전체 프리랜서 확인 (대상 국가: Egypt)

직업에 관해 Omar Ahmad B.님에게 연락해보세요

채팅으로 자세한 내용을 논의하려면 로그인하세요.

포트폴리오

10862759
In this project, I conducted data analysis and cleaning, and created visualizations to help better understand the data. Data analysis tools such as Python, Pandas, Matplotlib, and Seaborn were utilized. During the data cleaning stage, missing data, duplicate values, outliers, and data that did not conform to acceptable values were dealt with. Necessary processing operations were carried out to handle this data accurately. Data analysis was then conducted and visualized using the aforementioned tools. Multiple charts were created to illustrate relationships between variables and trends in the data. The visualizations were customized to focus on key findings and provide an overview of the data. Using these tools and techniques, a comprehensive report on the data analysis, cleaning, and visualization was produced. This report can be used for various purposes such as decision-making, strategy development, and policy recommendation.
Data analysis with python
10862688
Data analysis with python
In this project, I conducted data analysis and cleaning, and created visualizations to help better understand the data. Data analysis tools such as Python, Pandas, Matplotlib, and Seaborn were utilized. During the data cleaning stage, missing data, duplicate values, outliers, and data that did not conform to acceptable values were dealt with. Necessary processing operations were carried out to handle this data accurately. Data analysis was then conducted and visualized using the aforementioned tools. Multiple charts were created to illustrate relationships between variables and trends in the data. The visualizations were customized to focus on key findings and provide an overview of the data. Using these tools and techniques, a comprehensive report on the data analysis, cleaning, and visualization was produced. This report can be used for various purposes such as decision-making, strategy development, and policy recommendation.
Data analysis with python
10605336
Format the data as a table: Use the Format as Table option to format the data as a table. Use AutoSum to calculate values: Use AutoSum to find the following values for column 'C' and record each of the values: SUM AVERAGE MIN MAX COUNT Create a Pivot Table: Use the PivotTable feature to create a pivot table that displays the Department field in the Rows section, and the Equipment Count in the Values section, so that the pivot table displays the sum of equipment count by department. Sort the pivot table data: Use the Sort By Value set on the pivot table to sort it in descending order by the sum of equipment count. Make two more pivot tables exactly the same as task 3: Follow the same steps you performed in Tasks 3 and 4 to create two more identical pivot tables so that you end up with 3 worksheets that contain identical pivot tables. Analyze data in the pivot table: Use the PivotTable Fields pane to manipulate and analyze data in the two copied pivot tables as follows: In pivot
Final Assignment – Part 2
Format the data as a table: Use the Format as Table option to format the data as a table. Use AutoSum to calculate values: Use AutoSum to find the following values for column 'C' and record each of the values: SUM AVERAGE MIN MAX COUNT Create a Pivot Table: Use the PivotTable feature to create a pivot table that displays the Department field in the Rows section, and the Equipment Count in the Values section, so that the pivot table displays the sum of equipment count by department. Sort the pivot table data: Use the Sort By Value set on the pivot table to sort it in descending order by the sum of equipment count. Make two more pivot tables exactly the same as task 3: Follow the same steps you performed in Tasks 3 and 4 to create two more identical pivot tables so that you end up with 3 worksheets that contain identical pivot tables. Analyze data in the pivot table: Use the PivotTable Fields pane to manipulate and analyze data in the two copied pivot tables as follows: In pivot
Final Assignment – Part 2
Format the data as a table: Use the Format as Table option to format the data as a table. Use AutoSum to calculate values: Use AutoSum to find the following values for column 'C' and record each of the values: SUM AVERAGE MIN MAX COUNT Create a Pivot Table: Use the PivotTable feature to create a pivot table that displays the Department field in the Rows section, and the Equipment Count in the Values section, so that the pivot table displays the sum of equipment count by department. Sort the pivot table data: Use the Sort By Value set on the pivot table to sort it in descending order by the sum of equipment count. Make two more pivot tables exactly the same as task 3: Follow the same steps you performed in Tasks 3 and 4 to create two more identical pivot tables so that you end up with 3 worksheets that contain identical pivot tables. Analyze data in the pivot table: Use the PivotTable Fields pane to manipulate and analyze data in the two copied pivot tables as follows: In pivot
Final Assignment – Part 2
Format the data as a table: Use the Format as Table option to format the data as a table. Use AutoSum to calculate values: Use AutoSum to find the following values for column 'C' and record each of the values: SUM AVERAGE MIN MAX COUNT Create a Pivot Table: Use the PivotTable feature to create a pivot table that displays the Department field in the Rows section, and the Equipment Count in the Values section, so that the pivot table displays the sum of equipment count by department. Sort the pivot table data: Use the Sort By Value set on the pivot table to sort it in descending order by the sum of equipment count. Make two more pivot tables exactly the same as task 3: Follow the same steps you performed in Tasks 3 and 4 to create two more identical pivot tables so that you end up with 3 worksheets that contain identical pivot tables. Analyze data in the pivot table: Use the PivotTable Fields pane to manipulate and analyze data in the two copied pivot tables as follows: In pivot
Final Assignment – Part 2
10605327
Save the CSV file as an XLSX file: Click the 'Edit Workbook' button in the ToolTip to save the file as an XLSX file. The file is converted when you click 'OK' in the prompt. Column widths: Sort out the widths of all columns so that the data is clearly visible in all cells. Empty rows: Use the Filter feature to look for blanks and remove all empty rows from the data. Duplicate records: Use either the Conditional Formatting or Remove Duplicates feature to look for and remove any duplicated records from the data. Spelling: The original source file data has not been checked for errors in spelling. Check for spelling mistakes in the data and fix them. Whitespace: Use the Find and Replace feature to remove all double spaces from the data.
Final Assignment – Part 1 In IBM Certificate
10862759
In this project, I conducted data analysis and cleaning, and created visualizations to help better understand the data. Data analysis tools such as Python, Pandas, Matplotlib, and Seaborn were utilized. During the data cleaning stage, missing data, duplicate values, outliers, and data that did not conform to acceptable values were dealt with. Necessary processing operations were carried out to handle this data accurately. Data analysis was then conducted and visualized using the aforementioned tools. Multiple charts were created to illustrate relationships between variables and trends in the data. The visualizations were customized to focus on key findings and provide an overview of the data. Using these tools and techniques, a comprehensive report on the data analysis, cleaning, and visualization was produced. This report can be used for various purposes such as decision-making, strategy development, and policy recommendation.
Data analysis with python
10862688
Data analysis with python
In this project, I conducted data analysis and cleaning, and created visualizations to help better understand the data. Data analysis tools such as Python, Pandas, Matplotlib, and Seaborn were utilized. During the data cleaning stage, missing data, duplicate values, outliers, and data that did not conform to acceptable values were dealt with. Necessary processing operations were carried out to handle this data accurately. Data analysis was then conducted and visualized using the aforementioned tools. Multiple charts were created to illustrate relationships between variables and trends in the data. The visualizations were customized to focus on key findings and provide an overview of the data. Using these tools and techniques, a comprehensive report on the data analysis, cleaning, and visualization was produced. This report can be used for various purposes such as decision-making, strategy development, and policy recommendation.
Data analysis with python
10605336
Format the data as a table: Use the Format as Table option to format the data as a table. Use AutoSum to calculate values: Use AutoSum to find the following values for column 'C' and record each of the values: SUM AVERAGE MIN MAX COUNT Create a Pivot Table: Use the PivotTable feature to create a pivot table that displays the Department field in the Rows section, and the Equipment Count in the Values section, so that the pivot table displays the sum of equipment count by department. Sort the pivot table data: Use the Sort By Value set on the pivot table to sort it in descending order by the sum of equipment count. Make two more pivot tables exactly the same as task 3: Follow the same steps you performed in Tasks 3 and 4 to create two more identical pivot tables so that you end up with 3 worksheets that contain identical pivot tables. Analyze data in the pivot table: Use the PivotTable Fields pane to manipulate and analyze data in the two copied pivot tables as follows: In pivot
Final Assignment – Part 2
Format the data as a table: Use the Format as Table option to format the data as a table. Use AutoSum to calculate values: Use AutoSum to find the following values for column 'C' and record each of the values: SUM AVERAGE MIN MAX COUNT Create a Pivot Table: Use the PivotTable feature to create a pivot table that displays the Department field in the Rows section, and the Equipment Count in the Values section, so that the pivot table displays the sum of equipment count by department. Sort the pivot table data: Use the Sort By Value set on the pivot table to sort it in descending order by the sum of equipment count. Make two more pivot tables exactly the same as task 3: Follow the same steps you performed in Tasks 3 and 4 to create two more identical pivot tables so that you end up with 3 worksheets that contain identical pivot tables. Analyze data in the pivot table: Use the PivotTable Fields pane to manipulate and analyze data in the two copied pivot tables as follows: In pivot
Final Assignment – Part 2
Format the data as a table: Use the Format as Table option to format the data as a table. Use AutoSum to calculate values: Use AutoSum to find the following values for column 'C' and record each of the values: SUM AVERAGE MIN MAX COUNT Create a Pivot Table: Use the PivotTable feature to create a pivot table that displays the Department field in the Rows section, and the Equipment Count in the Values section, so that the pivot table displays the sum of equipment count by department. Sort the pivot table data: Use the Sort By Value set on the pivot table to sort it in descending order by the sum of equipment count. Make two more pivot tables exactly the same as task 3: Follow the same steps you performed in Tasks 3 and 4 to create two more identical pivot tables so that you end up with 3 worksheets that contain identical pivot tables. Analyze data in the pivot table: Use the PivotTable Fields pane to manipulate and analyze data in the two copied pivot tables as follows: In pivot
Final Assignment – Part 2
Format the data as a table: Use the Format as Table option to format the data as a table. Use AutoSum to calculate values: Use AutoSum to find the following values for column 'C' and record each of the values: SUM AVERAGE MIN MAX COUNT Create a Pivot Table: Use the PivotTable feature to create a pivot table that displays the Department field in the Rows section, and the Equipment Count in the Values section, so that the pivot table displays the sum of equipment count by department. Sort the pivot table data: Use the Sort By Value set on the pivot table to sort it in descending order by the sum of equipment count. Make two more pivot tables exactly the same as task 3: Follow the same steps you performed in Tasks 3 and 4 to create two more identical pivot tables so that you end up with 3 worksheets that contain identical pivot tables. Analyze data in the pivot table: Use the PivotTable Fields pane to manipulate and analyze data in the two copied pivot tables as follows: In pivot
Final Assignment – Part 2
10605327
Save the CSV file as an XLSX file: Click the 'Edit Workbook' button in the ToolTip to save the file as an XLSX file. The file is converted when you click 'OK' in the prompt. Column widths: Sort out the widths of all columns so that the data is clearly visible in all cells. Empty rows: Use the Filter feature to look for blanks and remove all empty rows from the data. Duplicate records: Use either the Conditional Formatting or Remove Duplicates feature to look for and remove any duplicated records from the data. Spelling: The original source file data has not been checked for errors in spelling. Check for spelling mistakes in the data and fix them. Whitespace: Use the Find and Replace feature to remove all double spaces from the data.
Final Assignment – Part 1 In IBM Certificate

리뷰

수정 사항에 대한 저장 완료
현재 1 ~ 1 번째 리뷰 표시 중(전체 1 건)
 리뷰에 대한 필터 유형:
5.0
€20.00 EUR
e GANTT charts needs to be created in 24 hours -- 2
Highly qualified , on time, will work together again for sure
Data Processing
Data Entry
Charts
H
국기 () Hadi H.
@Hadi177
•
2년 전

직업에 관해 Omar Ahmad B.님에게 연락해보세요

채팅으로 자세한 내용을 논의하려면 로그인하세요.

인증

우수 프리랜서
신분 인증(여부)
지불 인증(여부)
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이메일 인증(여부)
페이스북 연결(여부)

최고 기술

Data Entry 1
Python
Wireless
Excel
SQL

유사한 프리랜서 탐색

Data Entry Clerks in Egypt
Data Entry Clerks
Python Developers
Wireless Engineers

유사한 모범 사례 탐색

Data Entry
Python
Wireless
Excel
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