Question

in data analysis, we often need to calculate the frequency of each category in a vector or series. if youre using python, you would write: import pandas as pd pd.series(\apple\, \banana\, \apple\, \orange\).value_counts() if youre using r, you would write: table(c(\apple\, \banana\, \apple\, \orange\)) which of the following correctly identifies the functions used in each language? a. table() (in r); value_counts() (in python) b. sum() (in r); sum() (in python) c. totals() (in r); totals() (in python) d. categories() (in r); categories() (in python)

Explanation:

In the provided Python code, value_counts() is used to calculate the frequency of each category in a pandas.Series. In the R code, table() is used for the same purpose of counting the occurrences of each element in a vector. The other function - names in the options are not the correct ones for this task.

Answer:

A. table() (in R); value_counts() (in Python)