SPSS to R Reference Card

Data Import and Export

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What you do in SPSS	SPSS Menu Path	R Code
Open SPSS file	File > Open > Data	haven::read_sav("file.sav")
Open CSV file	File > Open > Data (CSV)	readr::read_csv("file.csv")
Open Excel file	—	readxl::read_excel("file.xlsx")
Save as CSV	File > Save As > CSV	readr::write_csv(df, "file.csv")

Inspecting Data

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What you do in SPSS	SPSS Menu Path	R Code
View data	Data View tab	View(df)
Variable info	Variable View tab	str(df) or dplyr::glimpse(df)
First rows	—	head(df)
Dimensions	—	nrow(df) / ncol(df) / dim(df)

Descriptive Statistics

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What you do in SPSS	SPSS Menu Path	R Code
Descriptives	Analyze > Descriptive Statistics > Descriptives	summary(df$var)
Frequencies	Analyze > Descriptive Statistics > Frequencies	table(df$var)
Crosstabs	Analyze > Descriptive Statistics > Crosstabs	table(df$var1, df$var2)
Mean by group	Analyze > Compare Means > Means	df |> group_by(group) |> summarise(mean(var))

Data Manipulation

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What you do in SPSS	SPSS Menu Path	R Code
Filter cases	Data > Select Cases	dplyr::filter(df, condition)
Sort	Data > Sort Cases	dplyr::arrange(df, var)
New variable	Transform > Compute Variable	dplyr::mutate(df, new = ...)
Recode	Transform > Recode	dplyr::case_when()
Select columns	—	dplyr::select(df, var1, var2)
Split file	Data > Split File	dplyr::group_by(df, var)
Aggregate	Data > Aggregate	df |> group_by(var) |> summarise(...)
Merge (add cases)	Data > Merge Files > Add Cases	dplyr::bind_rows(df1, df2)
Merge (add variables)	Data > Merge Files > Add Variables	dplyr::left_join(df1, df2, by = "id")

Statistical Tests

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What you do in SPSS	SPSS Menu Path	R Code
Independent t-test	Analyze > Compare Means > Independent-Samples T Test	t.test(y ~ group, data = df)
Paired t-test	Analyze > Compare Means > Paired-Samples T Test	t.test(x, y, paired = TRUE)
One-way ANOVA	Analyze > Compare Means > One-Way ANOVA	aov(y ~ group, data = df) |> summary()
Post-hoc tests	(within ANOVA dialog)	TukeyHSD(aov_result)
Correlation	Analyze > Correlate > Bivariate	cor.test(df$x, df$y)
Linear regression	Analyze > Regression > Linear	lm(y ~ x1 + x2, data = df) |> summary()
Chi-square	Analyze > Descriptive Statistics > Crosstabs (Statistics)	chisq.test(table(df$var1, df$var2))
Reliability	Analyze > Scale > Reliability Analysis	psych::alpha(df[, items])

Visualization

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What you do in SPSS	SPSS Chart Builder	R Code (ggplot2)
Bar chart	Bar element	ggplot(df, aes(x)) + geom_bar()
Histogram	Histogram element	ggplot(df, aes(x)) + geom_histogram()
Scatterplot	Scatter/Dot element	ggplot(df, aes(x, y)) + geom_point()
Line chart	Line element	ggplot(df, aes(x, y)) + geom_line()
Boxplot	Boxplot element	ggplot(df, aes(x, y)) + geom_boxplot()
Add labels	—	+ labs(title = "...", x = "...", y = "...")
Change theme	—	+ theme_minimal()

Useful Packages

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Package	Purpose
tidyverse	Collection: dplyr, ggplot2, readr, tidyr, and more
haven	Read/write SPSS, Stata, and SAS files
readxl	Read Excel files
rmarkdown	Reproducible reports
broom	Tidy statistical output into data frames
psych	Descriptive stats, reliability analysis, factor analysis
WDI	World Bank data directly in R
cbsodataR	CBS Netherlands StatLine data (including BES islands)