After doing these courses, I feel confident creating professional visualizations and dashboards
Shoebur RahmanProcurement Specialist, Giz Bangladesh
कोर्स विवरण
Say you've found a great dataset and would like to learn more about it. How can you start to answer the questions you have about the data? You can use dplyr to answer those questions—it can also help with basic transformations of your data. You'll also learn to aggregate your data and add, remove, or change the variables. Along the way, you'll explore a dataset containing information about counties in the United States. You'll finish the course by applying these tools to the babynames dataset to explore trends of baby names in the United States.The videos contain live transcripts you can reveal by clicking "Show transcript" at the bottom left of the videos.The course glossary can be found on the right in the resources section.To obtain CPE credits you need to complete the course and reach a score of 70% on the qualified assessment. You can navigate to the assessment by clicking on the CPE credits callout on the right.
पूर्वापेक्षाएँ
पाठ्यक्रम
कोर्स रूपरेखा
1
Transforming Data with dplyr
Learn verbs you can use to transform your data, including select, filter, arrange, and mutate. You'll use these functions to modify the counties dataset to view particular observations and answer questions about the data.
- Exploring data with dplyr50 XP
- Understanding your data50 XP
- Selecting columns100 XP
- The filter and arrange verbs50 XP
- Arranging observations100 XP
- Filtering for conditions100 XP
- Filtering and arranging100 XP
- The mutate() verb50 XP
- Calculating the number of government employees100 XP
- Calculating the percentage of women in a county100 XP
- Mutate, filter, and arrange100 XP
2
Aggregating Data
Now that you know how to transform your data, you'll want to know more about how to aggregate your data to make it more interpretable. You'll learn a number of functions you can use to take many observations in your data and summarize them, including count, group_by, summarize, ungroup, and slice_min/slice_max.
3
Selecting and Transforming Data
Learn advanced methods to select and transform columns. Also, learn about select helpers, which are functions that specify criteria for columns you want to choose, as well as the rename verb.
4
Case Study: The babynames Dataset
Work with a new dataset that represents the names of babies born in the United States each year. Learn how to use grouped mutates and window functions to ask and answer more complex questions about your data. And use a combination of dplyr and ggplot2 to make interesting graphs to further explore your data.
R
Data Manipulation with dplyr
कोर्स
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