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$10 USD / heure
Drapeau de EGYPT
el-mahalla el-kubra, egypt
$10 USD / heure
Il est actuellement 3:01 PM ici
Rejoint le septembre 24, 2022
0 Recommandations

Omar Ahmad B.

@Badromar5522

 5,0 (1 commentaire)
0,7
0,7
100%
100%
$10 USD / heure
Drapeau de EGYPT
el-mahalla el-kubra, egypt
$10 USD / heure
100 %
Travaux complétés
100 %
Suivant le budget
100 %
Dans les temps
N/A
Taux de réembauche

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.
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Portfolio

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

Commentaires

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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
Drapeau de Hadi H.
@Hadi177
•
il y a 2 ans

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Meilleures compétences

Data Entry 1
Python
Wireless
Excel
SQL

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