Building Datasets in Excel

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Marcus Marktanner

4:38:39

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1.1 Dataset Building Course Files.zip

1. Introduction.mp4

03:08

2. Downloading the Data.mp4

13:11

3. Converting Data Files to Latest Excel Version.mp4

08:11

4. Extracting Life Ladder Data from World Happiness Report.mp4

05:44

5. Extracting the Gini Coefficient from the World Income Inequality Database.mp4

02:47

6. Extracting Math Achievement Data from the World Inequality Database on Education.mp4

07:39

7. Extracting the Corruption Perception Index from Transparency International.mp4

22:50

8. Extracting Total Factor Productivity Data from the Penn World Tables.mp4

13:53

9. Extracting Democracy Index Data from the Economist Inteligence Unit.mp4

17:20

10. Exracting Data from the World Development Indicators Databse.mp4

18:29

11. Data Consolidation Step 1 Put all Data Lists into a Single File.mp4

09:53

12. Data Consolidation Step 2 Define Data Frame.mp4

29:17

13. Data Consolidation Step 3 Add Uniform IDs to All Data Lists.mp4

47:30

14. Data Consolidation Step 4 Add Data to Data Frame.mp4

14:12

15. Missing Observations Option 1 Averages.mp4

14:16

16. Missing Observations Option 2 Next Best Available Approach.mp4

23:23

17. Missing Observations Option 3 Interpolation.mp4

26:56

Description

Tips and Tricks from A like Addressing Missing Observations to Z like Zipping Data from Various Sources.

What You'll Learn?

Learn how to build datasets with Excel by following an example from downloading real world data from various sources to a consolidated final dataset.
See Excel formulas like IF and VLOOKUP and built-in functions like Sort, Remove Duplicates and Pivot Tables in action.
Apply advanced excel Formulas provided to quickly convert data from table into list formats.
Replace missing observations in stacked time series data with various techniques, including interpolation.

Who is this for?

Students and researchers who need to build datasets in Excel from various sources and combine them into a single file.

Students and researchers who prefer real-world data learning by doing.

What You Need to Know?

This tutorial does not require advanced Excel skills such as writing macros or writing custom formulas.

I will start with very basic operations and gradually introduce more challenging tasks.

More details

Description
This course is designed to provide you with essential skills for efficiently cleaning, organizing, and combining data from multiple sources in Excel. These skills are critical for data analysis, but are often underestimated.
Target Audience:
This course is designed for anyone who wants to improve their data wrangling skills in Excel and does not require prior experience with advanced features such as macros or custom formulas.
Key Learnings:
Techniques for harmonizing data from different sources with incompatible structures (e.g., standardizing different names used by different data sources for the same country).
Restructuring data sets from tabular format to a format compatible with statistical analysis software (i.e., one variable per column).
Estimate missing data points in complex datasets (such as stacked time-series panel data structures) using various techniques, including interpolation.
Use useful Excel formulas and built-in functions to manipulate data (e.g., If-Then, Sort, Remove Duplicates, and Pivot Table).
Tips and tricks for speeding up common data manipulation tasks using provided helper files.
Benefits:
Gain the ability to tackle real-world dataset building challenges in less time.
Improve efficiency in preparing data for analysis.
Enhance your data analysis skills.
This course is based on the instructor's experience conducting real-world research, consulting, and working with students who have gone on to successful data analysis careers.
Who this course is for:
Students and researchers who need to build datasets in Excel from various sources and combine them into a single file.
Students and researchers who prefer real-world data learning by doing.

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Marcus Marktanner is Professor of Economics. He received his Ph.D. from the Technical University of Ilmenau, Germany in 1997. He has held teaching and research positions in Germany, Lebanon, Indonesia, and the United States. His data-driven research focuses on comparative economics, economic development, and the economics of conflict. He has served as a consultant to the United Nations Economic and Social Commission for Western Asia (ESCWA), the World Food Program (WFP), and the Food and Agriculture Organization (FAO). He also regularly contributes to the work of the Konrad Adenauer Foundation, a German think tank, as a writer and speaker on social market economics.

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