#The Pandas package can be installed via pip from PyPI using "pip install pandas" from a terminal. import pandas as pd #Adjust the path to where you have saved the datam and pandas will read in the data df = pd.read_csv('.../NFWBS_PUF_2016_data.csv') #This command gives you a quick preview of the data that you now have successfully loaded df.head() #This command prints out the list of column headers df.columns #To remap the values in the data, you will need to create dictionaries mapping the dummy values to new values. #Below are examples of how to do so using dictionaries. You can use this format for the remainder of the columns. sample_map = { 1: "General population", 2: "Age 62+ oversample", 3: "Race/ethnicity and poverty oversample" } fpl_map = { 1: "<100% FPL", 2: "100%-199% FPL", 3: "200%+ FPL" } #To map the new values, use the replace function. Specify the columns as the key and the dictionaries mapping the values as the value. #Your data frame will now have updated values for the 'sample' and 'fpl' columns. df.replace({"sample": sample_map, "fpl": fpl_map})