Dynamically evaluate an expression from a formula in Pandas

You can use 1) pd.eval(), 2) df.query(), or 3) df.eval(). Their various features and functionality are discussed below. Examples will involve these dataframes (unless otherwise specified). np.random.seed(0) df1 = pd.DataFrame(np.random.choice(10, (5, 4)), columns=list(‘ABCD’)) df2 = pd.DataFrame(np.random.choice(10, (5, 4)), columns=list(‘ABCD’)) df3 = pd.DataFrame(np.random.choice(10, (5, 4)), columns=list(‘ABCD’)) df4 = pd.DataFrame(np.random.choice(10, (5, 4)), columns=list(‘ABCD’)) 1) pandas.eval This is … Read more

Formula with dynamic number of variables

See ?as.formula, e.g.: factors <- c(“factor1”, “factor2”) as.formula(paste(“y~”, paste(factors, collapse=”+”))) # y ~ factor1 + factor2 where factors is a character vector containing the names of the factors you want to use in the model. This you can paste into an lm model, e.g.: set.seed(0) y <- rnorm(100) factor1 <- rep(1:2, each=50) factor2 <- rep(3:4, … Read more

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