Load and Inspect Data

What to do on this page: run the Python code below as written, in translation.ipynb, one cell at a time — click the play button beside each cell or press Shift+Enter, and the output appears below the cell. You are not asked to translate this Python into R or to modify it. Instead, compare each output with the matching R command in the table at the bottom; you built the R side in R Deepening and Parity Check.

Load The NHANES Snapshot

In translation.ipynb, load the same CSV used in the R example:

import pandas as pd

nhanes = pd.read_csv("../../../examples/nhanes-equity/data/nhanes_equity_v6.csv")

Inspect Before Summarising

nhanes.head()

nhanes.shape

nhanes.columns.tolist()

nhanes[["BMI", "IncomeGroup", "Gender"]].isna().sum()

Compare To R

Question	R	Python
How many rows?	nrow(nhanes)	len(nhanes)
How many columns?	ncol(nhanes)	nhanes.shape[1]
What are the column names?	names(nhanes)	nhanes.columns.tolist()
How many missing BMI values?	sum(is.na(nhanes$BMI))	nhanes["BMI"].isna().sum()

Student Check

Before asking AI for any transformation, write down the raw row count, column count, and missingness count for BMI.