PYTHON JUYPTER NOTEBOOK TASK:

In the file pressurevolume.txt is data from an experiment testing the relationship between and V in a ideal gas. The data is in four columns: P,V, AP, AV. Extract this data into the appropriate four 1D arrays. 1. Plot the data as V vs P, including errorbars and use curve_fit to fit a hyperbola (V = , with a a parameter) to the data. Report the value of a and its uncertainty. 2. Use your measurement class to calculate 1/V and its uncertainty. Plot the data as 1/V vs P and use curve_fit to fit a line (1/V = bP+c, with b and c as parameters). Report the values of b and c and their uncertainties. 3. Use your measurement class to calculate PV and its uncertainty. Plot the data as PV vs P and use curve_fit to fit a line (PV = bP+c, with b and c as parameters). Report the values of b and c and their uncertainties. Does this data come from an ideal gas? from scipy.optimize import curve_fit In the file pressurevolume.txt is data from an experiment testing the relationship between and V in a ideal gas. The data is in four columns: P,V, AP, AV. Extract this data into the appropriate four 1D arrays. 1. Plot the data as V vs P, including errorbars and use curve_fit to fit a hyperbola (V = , with a a parameter) to the data. Report the value of a and its uncertainty. 2. Use your measurement class to calculate 1/V and its uncertainty. Plot the data as 1/V vs P and use curve_fit to fit a line (1/V = bP+c, with b and c as parameters). Report the values of b and c and their uncertainties. 3. Use your measurement class to calculate PV and its uncertainty. Plot the data as PV vs P and use curve_fit to fit a line (PV = bP+c, with b and c as parameters). Report the values of b and c and their uncertainties. Does this data come from an ideal gas? from scipy.optimize import curve_fit