Calculating the Average and SD in R group_by() and summarize() # - PowerPoint PPT Presentation

Calculating the Average and SD in R group_by() and summarize()

# group and summarize data grouped_df <- group_by(nominate, party, congress) smry <- summarize(grouped_df, average_ideology = mean(ideology), sd_ideology = sd(ideology))

function that applies groups to the data frame # group and summarize data grouped_df <- group_by(nominate, party, congress) smry <- summarize(grouped_df, average_ideology = mean(ideology), sd_ideology = sd(ideology))

1st argument: data frame to group # group and summarize data grouped_df <- group_by(nominate, party, congress) smry <- summarize(grouped_df, average_ideology = mean(ideology), sd_ideology = sd(ideology))

2nd argument: a grouping variable # group and summarize data grouped_df <- group_by(nominate, party, congress) smry <- summarize(grouped_df, average_ideology = mean(ideology), sd_ideology = sd(ideology))

3rd argument: a(nother) grouping variable # group and summarize data grouped_df <- group_by(nominate, party, congress) smry <- summarize(grouped_df, average_ideology = mean(ideology), sd_ideology = sd(ideology))

We could add a 3rd and 4th grouping variable if we wanted. Or we could have only one grouping variable. # group and summarize data grouped_df <- group_by(nominate, party, congress) smry <- summarize(grouped_df, average_ideology = mean(ideology), sd_ideology = sd(ideology))

A function that computes statistics (i.e., “summaries”) within each group of a grouped data frame. # group and summarize data grouped_df <- group_by(nominate, party, congress) smry <- summarize(grouped_df, average_ideology = mean(ideology), sd_ideology = sd(ideology))

1st argument: a grouped data frame # group and summarize data grouped_df <- group_by(nominate, party, congress) smry <- summarize(grouped_df, average_ideology = mean(ideology), sd_ideology = sd(ideology))

2nd argument: a quantity calculated using a variable in the grouped data frame. It is explicitly named, but you choose the name. # group and summarize data grouped_df <- group_by(nominate, party, congress) smry <- summarize(grouped_df, average_ideology = mean(ideology), sd_ideology = sd(ideology))

3rd argument: a(nother) quantity calculated using a variable in the grouped data frame. Again, it is explicitly named, but you choose the name. # group and summarize data grouped_df <- group_by(nominate, party, congress) smry <- summarize(grouped_df, average_ideology = mean(ideology), sd_ideology = sd(ideology))

# group and summarize data grouped_df <- group_by(nominate, party, congress) smry <- summarize(grouped_df, average_ideology = mean(ideology), sd_ideology = sd(ideology)) Question: If we run this code, what is smry ?

# group and summarize data grouped_df <- group_by(nominate, party, congress) smry <- summarize(grouped_df, average_ideology = mean(ideology), sd_ideology = sd(ideology)) Question: If we run this code, what is smry ? Answer: A data frame.

# group and summarize data grouped_df <- group_by(nominate, party, congress) smry <- summarize(grouped_df, average_ideology = mean(ideology), sd_ideology = sd(ideology)) > glimpse(smry) Observations: 28 Variables: 4 $ party (fctr) Democrat, Democrat, Democrat, Democrat, Democrat, Democrat, De... $ congress (int) 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112... $ average_ideology (dbl) -0.2997308, -0.3024198, -0.3018587, -0.3138217, -0.3383846, -0.... $ sd_ideology (dbl) 0.1596674, 0.1619839, 0.1630104, 0.1566859, 0.1479384, 0.136459...

Key Point Combining group_by() and summarize() creates a data frame with the following variables: • the grouping variables - party - congress • the summaries (argument names become variable names) - average_ideology - sd_ideology

# group and summarize data grouped_df <- group_by(nominate, party, congress) smry <- summarize(grouped_df, average_ideology = mean(ideology), sd_ideology = sd(ideology)) > glimpse(smry) Observations: 28 Variables: 4 $ party (fctr) Democrat, Democrat, Democrat, Democrat, Democrat, Democrat, De... $ congress (int) 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112... $ average_ideology (dbl) -0.2997308, -0.3024198, -0.3018587, -0.3138217, -0.3383846, -0.... $ sd_ideology (dbl) 0.1596674, 0.1619839, 0.1630104, 0.1566859, 0.1479384, 0.136459...

Most importantly, we can use ggplot() with smry .

# create line plot ggplot(smry, aes(x = congress, y = average_ideology, color = party)) + geom_line()

Calculating the Average and SD in R group_by() and summarize() # - PowerPoint PPT Presentation

Calculating the Average and SD in R group_by() and summarize() # group and summarize data grouped_df <- group_by(nominate, party, congress) smry <- summarize(grouped_df, average_ideology = mean(ideology), sd_ideology = sd(ideology))

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