The following tutorial is an introduction to built-in Python functions such as average, standard deviation, maximum, minimum, and conditional counting.

import random y = [random.random()*100.0 for i in range(10)] print("Print y") print(y) print("Sorted List") for i in range(len(y)): print("%.2f" % y[i]) def avg(x): return sum(x) / len(x) print("Avg: " + str(avg(y))) print("Max: " + str(max(y))) print("Min: " + str(min(y))) z = sum(1 if i<50.0 else 0 for i in y) print("Number Below 50: " + str(z)) # another method with NumPy import numpy as np print(np.mean(y)) print(np.average(y)) print(np.std(y)) print(np.median(y))

Data statistics can also be completed with a spreadsheet program like Microsoft Excel and MATLAB where the data sets are arrays or matrices instead of tables in a spreadsheet. Click on the appropriate link for additional information and source code.

def P_RK_IG(V, T, do_ideal_gas=False): R = 0.0821 # L-atm/K Pc = 37.2 # atm Tc = 132.5 # K a = 0.427 * pow(R,2) * pow(Tc,2.5) / Pc b = 0.0866 * R * Tc / Pc # Compute in atm P_ig = R * T / V P_rk = R * T / (V-b) - a/(V*(V+b)*pow(T,0.5)) # Convert to Pascals if do_ideal_gas: return P_ig * 101325 else: return P_rk * 101325 for T in range(490,511,10): V = 4.0 while V < 8: print("----- Temperature: " + str(T) + " K") print("P_ig: " + str(P_RK_IG(V,T,True)) + " Pa") print("P_rk: " + str(P_RK_IG(V,T)) + " Pa") V = V + 2.0

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