[Python] How do I restrict Dataframe to two columns, filter both columns, then drop Nan to get...

For a problem, I need to restrict dataframe to two columns, filter them for desired values, drop Nan so that a correlation can be found. I know the rows need to be a certain amount and I am getting more rows then I should

numpy and pandas imported

df = pd.read_csv("assets/NISPUF17.csv")

#restricting to wanted columns
wantedcolumns = df[["HAD_CPOX","P_NUMVRC"]]

#filter columns

had_cpox = wantedcolumns[(wantedcolumns["HAD_CPOX"] >=1)&(wantedcolumns["HAD_CPOX"]<=2)]
cpox_vax = wantedcolumns[wantedcolumns["P_NUMVRC"] >=1.0]

#drop missing values
wantedcolumns.dropna()

#print number of rows
print(len(wantedcolumns))

corr, pval=stats.pearsonr(column 1, column 2)


What I have tried: wantedcolumns[had_cpox & cpox_vax] - traceback

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