Extra – Steam Tables¶

Saturated Steam table¶

The table below is the saturated liquid and vapour water. The temperatures range from \(0.01 ^{\circ} C\) to \(370.00 ^{\circ} C\) at \(5 ^{\circ} C\) increments.

In [2]:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

df = pd.read_excel('../figures/Module-4/SatTandPofSteam.xlsx', sheet_name='Sheet2', index_col=None, na_values=['NA'])
df.head(75)

Out[2]:

	Temperature (C)	Pressure (MPa)	Volume (l, m3/kg)	Volume (v, m3/kg)	Internal Energy (l, kJ/kg)	Δ Internal Energy of Vapourization (kJ/kg)	Internal Energy (v, kJ/kg)	Enthalpy (l, kJ/kg)	Δ Enthalpy of Vapourization (kJ/kg)	Enthalpy (v, kJ/kg)	Entropy (l, J/g*K)	Δ Entropy of Vapourization (kJ/kg)	Entropy (v, J/g*K)
0	0.01	0.000612	0.001000	205.990000	0.000	2374.900	2374.9	0.000	2500.900	2500.9	0.000000	9.155500	9.1555
1	5.00	0.000873	0.001000	147.010000	21.019	2360.781	2381.8	21.020	2489.080	2510.1	0.076254	8.948546	9.0248
2	10.00	0.001228	0.001000	106.300000	42.020	2346.580	2388.6	42.021	2477.179	2519.2	0.151090	8.748710	8.8998
3	15.00	0.001706	0.001001	77.875000	62.980	2332.520	2395.5	62.981	2465.319	2528.3	0.224460	8.555840	8.7803
4	20.00	0.002339	0.001002	57.757000	83.912	2318.388	2402.3	83.914	2453.486	2537.4	0.296480	8.369520	8.6660
5	25.00	0.003170	0.001003	43.337000	104.830	2304.270	2409.1	104.830	2441.670	2546.5	0.367220	8.189380	8.5566
6	30.00	0.004247	0.001004	32.878000	125.730	2290.170	2415.9	125.730	2429.770	2555.5	0.436750	8.015250	8.4520
7	35.00	0.005629	0.001006	25.205000	146.630	2276.070	2422.7	146.630	2417.870	2564.5	0.505130	7.846570	8.3517
8	40.00	0.007385	0.001008	19.515000	167.530	2261.870	2429.4	167.530	2405.970	2573.5	0.572400	7.683100	8.2555
9	45.00	0.009595	0.001010	15.252000	188.430	2247.670	2436.1	188.430	2393.970	2582.4	0.638610	7.524690	8.1633
10	50.00	0.012352	0.001012	12.027000	209.330	2233.370	2442.7	209.340	2381.960	2591.3	0.703810	7.370990	8.0748
11	55.00	0.015762	0.001015	9.564300	230.240	2219.060	2449.3	230.260	2369.840	2600.1	0.768020	7.221780	7.9898
12	60.00	0.019946	0.001017	7.667200	251.160	2204.740	2455.9	251.180	2357.620	2608.8	0.831290	7.076810	7.9081
13	65.00	0.025042	0.001020	6.193500	272.090	2190.310	2462.4	272.120	2345.380	2617.5	0.893650	6.935950	7.8296
14	70.00	0.031201	0.001023	5.039500	293.030	2175.870	2468.9	293.070	2333.030	2626.1	0.955130	6.798870	7.7540
15	75.00	0.038595	0.001026	4.128900	313.990	2161.210	2475.2	314.030	2320.570	2634.6	1.015800	6.665400	7.6812
16	80.00	0.047414	0.001029	3.405200	334.960	2146.640	2481.6	335.010	2307.990	2643.0	1.075600	6.535500	7.6111
17	85.00	0.057867	0.001032	2.825800	355.950	2131.850	2487.8	356.010	2295.290	2651.3	1.134600	6.408800	7.5434
18	90.00	0.070182	0.001036	2.359100	376.970	2117.030	2494.0	377.040	2282.460	2659.5	1.192900	6.285200	7.4781
19	95.00	0.084608	0.001040	1.980600	398.000	2102.000	2500.0	398.090	2269.510	2667.6	1.250400	6.164700	7.4151
20	100.00	0.101420	0.001043	1.671800	419.060	2086.940	2506.0	419.170	2256.430	2675.6	1.307200	6.046900	7.3541
21	105.00	0.120900	0.001047	1.418400	440.150	2071.750	2511.9	440.270	2243.130	2683.4	1.363300	5.931900	7.2952
22	110.00	0.143380	0.001052	1.209300	461.260	2056.440	2517.7	461.420	2229.680	2691.1	1.418800	5.819300	7.2381
23	115.00	0.169180	0.001056	1.035800	482.410	2040.890	2523.3	482.590	2216.010	2698.6	1.473700	5.709100	7.1828
24	120.00	0.198670	0.001060	0.891210	503.600	2025.300	2528.9	503.810	2202.090	2705.9	1.527900	5.601200	7.1291
25	125.00	0.232240	0.001065	0.770030	524.830	2009.470	2534.3	525.070	2188.030	2713.1	1.581600	5.495400	7.0770
26	130.00	0.270280	0.001070	0.668000	546.090	1993.410	2539.5	546.380	2173.720	2720.1	1.634600	5.391800	7.0264
27	135.00	0.313230	0.001075	0.581730	567.410	1977.290	2544.7	567.740	2159.160	2726.9	1.687200	5.290000	6.9772
28	140.00	0.361540	0.001080	0.508450	588.770	1960.830	2549.6	589.160	2144.240	2733.4	1.739200	5.190100	6.9293
29	145.00	0.415680	0.001085	0.445960	610.190	1944.210	2554.4	610.640	2129.160	2739.8	1.790700	5.091900	6.8826
...	...	...	...	...	...	...	...	...	...	...	...	...	...
45	225.00	2.549700	0.001199	0.078403	963.740	1638.460	2602.2	966.800	1835.300	2802.1	2.564000	3.684300	6.2483
46	230.00	2.797100	0.001209	0.071503	986.810	1616.090	2602.9	990.190	1812.710	2802.9	2.610100	3.602700	6.2128
47	235.00	3.062500	0.001219	0.065298	1010.000	1593.200	2603.2	1013.800	1789.400	2803.2	2.656100	3.521400	6.1775
48	240.00	3.346900	0.001229	0.059705	1033.400	1569.700	2603.1	1037.600	1765.400	2803.0	2.702000	3.440300	6.1423
49	245.00	3.651200	0.001240	0.054654	1057.000	1545.700	2602.7	1061.500	1740.700	2802.2	2.747800	3.359400	6.1072
50	250.00	3.976200	0.001252	0.050083	1080.800	1521.000	2601.8	1085.800	1715.100	2800.9	2.793500	3.278600	6.0721
51	255.00	4.322900	0.001264	0.045938	1104.800	1495.700	2600.5	1110.200	1688.900	2799.1	2.839200	3.197700	6.0369
52	260.00	4.692300	0.001276	0.042173	1129.000	1469.700	2598.7	1135.000	1661.600	2796.6	2.884900	3.116700	6.0016
53	265.00	5.085300	0.001289	0.038746	1153.400	1443.100	2596.5	1160.000	1633.500	2793.5	2.930700	3.035400	5.9661
54	270.00	5.503000	0.001303	0.035621	1178.100	1415.600	2593.7	1185.300	1604.400	2789.7	2.976500	2.953900	5.9304
55	275.00	5.946400	0.001318	0.032766	1203.100	1387.200	2590.3	1210.900	1574.300	2785.2	3.022400	2.872000	5.8944
56	280.00	6.416600	0.001333	0.030153	1228.300	1358.100	2586.4	1236.900	1543.000	2779.9	3.068500	2.789400	5.8579
57	285.00	6.914700	0.001349	0.027756	1253.900	1327.900	2581.8	1263.200	1510.500	2773.7	3.114700	2.706200	5.8209
58	290.00	7.441800	0.001366	0.025555	1279.900	1296.600	2576.5	1290.000	1476.700	2766.7	3.161200	2.622200	5.7834
59	295.00	7.999100	0.001385	0.023529	1306.200	1264.300	2570.5	1317.300	1441.400	2758.7	3.208000	2.537100	5.7451
60	300.00	8.587900	0.001404	0.021660	1332.900	1230.700	2563.6	1345.000	1404.600	2749.6	3.255200	2.450700	5.7059
61	305.00	9.209400	0.001425	0.019933	1360.200	1195.700	2555.9	1373.300	1366.100	2739.4	3.302800	2.362900	5.6657
62	310.00	9.865100	0.001448	0.018335	1387.900	1159.200	2547.1	1402.200	1325.700	2727.9	3.351000	2.273400	5.6244
63	315.00	10.556000	0.001472	0.016851	1416.300	1120.900	2537.2	1431.800	1283.300	2715.1	3.399800	2.181800	5.5816
64	320.00	11.284000	0.001499	0.015471	1445.300	1080.700	2526.0	1462.200	1238.400	2700.6	3.449400	2.087800	5.5372
65	325.00	12.051000	0.001528	0.014183	1475.100	1038.300	2513.4	1493.500	1190.800	2684.3	3.500000	1.990800	5.4908
66	330.00	12.858000	0.001561	0.012979	1505.800	993.400	2499.2	1525.900	1140.100	2666.0	3.551800	1.890400	5.4422
67	335.00	13.707000	0.001597	0.011847	1537.600	945.400	2483.0	1559.500	1085.900	2645.4	3.605000	1.785600	5.3906
68	340.00	14.601000	0.001638	0.010781	1570.600	893.800	2464.4	1594.500	1027.300	2621.8	3.660100	1.675500	5.3356
69	345.00	15.541000	0.001685	0.009769	1605.300	837.800	2443.1	1631.500	963.400	2594.9	3.717600	1.558600	5.2762
70	350.00	16.529000	0.001740	0.008802	1642.100	776.000	2418.1	1670.900	892.700	2563.6	3.778400	1.432600	5.2110
71	355.00	17.570000	0.001808	0.007868	1682.000	706.400	2388.4	1713.700	812.900	2526.6	3.843900	1.294100	5.1380
72	360.00	18.666000	0.001895	0.006949	1726.300	625.500	2351.8	1761.700	719.800	2481.5	3.916700	1.136900	5.0536
73	365.00	19.821000	0.002017	0.006012	1777.800	526.000	2303.8	1817.800	605.100	2422.9	4.001400	0.948300	4.9497
74	370.00	21.046000	0.002216	0.004952	1844.200	385.900	2230.1	1890.900	443.400	2334.3	4.111400	0.689400	4.8008

75 rows × 13 columns

Super Heated Steam Table¶

The following tables are Isobaric superheated steam tables ranging from 1 MPa to 10 Mpa with 1 Mpa increaments

1 MPa¶

In [2]:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

df = pd.read_excel('../figures/Module-4/Steam_1MPa.xlsx', sheet_name='Sheet2', index_col=None, na_values=['NA'])
df

Out[2]:

	Temperature (C)	Pressure (MPa)	Volume (m3/kg)	Internal Energy (kJ/kg)	Enthalpy (kJ/kg)	Entropy (J/g*K)
0	179.88	1	0.19436	2582.7	2777.1	6.5850
1	200.00	1	0.20602	2622.2	2828.3	6.6955
2	250.00	1	0.23275	2710.4	2943.1	6.9265
3	300.00	1	0.25799	2793.6	3051.6	7.1246
4	350.00	1	0.28250	2875.7	3158.2	7.3029
5	400.00	1	0.30661	2957.9	3264.5	7.4669
6	450.00	1	0.33045	3040.9	3371.3	7.6200
7	500.00	1	0.35411	3125.0	3479.1	7.7641
8	550.00	1	0.37766	3210.5	3588.1	7.9008
9	600.00	1	0.40111	3297.5	3698.6	8.0310
10	650.00	1	0.42449	3386.0	3810.5	8.1557
11	700.00	1	0.44783	3476.2	3924.1	8.2755
12	750.00	1	0.47112	3568.1	4039.3	8.3909
13	800.00	1	0.49438	3661.7	4156.1	8.5024
14	850.00	1	0.51762	3757.0	4274.6	8.6103
15	900.00	1	0.54083	3853.9	4394.8	8.7150
16	950.00	1	0.56403	3952.5	4516.5	8.8166
17	1000.00	1	0.58721	4052.7	4639.9	8.9155

2 MPa¶

In [3]:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

df = pd.read_excel('../figures/Module-4/Steam_2MPa.xlsx', sheet_name='Sheet2', index_col=None, na_values=['NA'])
df

Out[3]:

	Temperature (C)	Pressure (MPa)	Volume (m3/kg)	Internal Energy (kJ/kg)	Enthalpy (kJ/kg)	Entropy (J/g*K)
0	212.38	2	0.099585	2599.1	2798.3	6.3390
1	250.00	2	0.111500	2680.2	2903.2	6.5475
2	300.00	2	0.125510	2773.2	3024.2	6.7684
3	350.00	2	0.138600	2860.5	3137.7	6.9583
4	400.00	2	0.151210	2945.9	3248.3	7.1292
5	450.00	2	0.163540	3031.1	3358.2	7.2866
6	500.00	2	0.175680	3116.9	3468.2	7.4337
7	550.00	2	0.187700	3203.6	3579.0	7.5725
8	600.00	2	0.199610	3291.5	3690.7	7.7043
9	650.00	2	0.211460	3380.8	3803.8	7.8302
10	700.00	2	0.223260	3471.6	3918.2	7.9509
11	750.00	2	0.235020	3564.0	4034.1	8.0670
12	800.00	2	0.246740	3658.0	4151.5	8.1790
13	850.00	2	0.258440	3753.6	4270.5	8.2874
14	900.00	2	0.270120	3850.9	4391.1	8.3925
15	950.00	2	0.281780	3949.8	4513.3	8.4945
16	1000.00	2	0.293420	4050.2	4637.0	8.5936

3 MPa¶

In [4]:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

df = pd.read_excel('../figures/Module-4/Steam_3MPa.xlsx', sheet_name='Sheet2', index_col=None, na_values=['NA'])
df

Out[4]:

	Temperature (C)	Pressure (MPa)	Volume (m3/kg)	Internal Energy (kJ/kg)	Enthalpy (kJ/kg)	Entropy (J/g*K)
0	233.85	3	0.066664	2603.2	2803.2	6.1856
1	250.00	3	0.070627	2644.7	2856.5	6.2893
2	300.00	3	0.081179	2750.8	2994.3	6.5412
3	350.00	3	0.090556	2844.4	3116.1	6.7449
4	400.00	3	0.099379	2933.5	3231.7	6.9234
5	450.00	3	0.107890	3021.2	3344.8	7.0856
6	500.00	3	0.116200	3108.6	3457.2	7.2359
7	550.00	3	0.124370	3196.6	3569.7	7.3768
8	600.00	3	0.132450	3285.5	3682.8	7.5103
9	650.00	3	0.140450	3375.6	3796.9	7.6373
10	700.00	3	0.148410	3467.0	3912.2	7.7590
11	750.00	3	0.156320	3559.9	4028.9	7.8758
12	800.00	3	0.164200	3654.3	4146.9	7.9885
13	850.00	3	0.172050	3750.3	4266.5	8.0973
14	900.00	3	0.179880	3847.9	4387.5	8.2028
15	950.00	3	0.187690	3947.0	4510.1	8.3051
16	1000.00	3	0.195490	4047.7	4634.1	8.4045

4 MPa¶

In [5]:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

df = pd.read_excel('../figures/Module-4/Steam_4MPa.xlsx', sheet_name='Sheet2', index_col=None, na_values=['NA'])
df

Out[5]:

	Temperature (C)	Pressure (MPa)	Volume (m3/kg)	Internal Energy (kJ/kg)	Enthalpy (kJ/kg)	Entropy (J/g*K)
0	250.35	4	0.049776	2601.7	2800.8	6.0696
1	300.00	4	0.058870	2726.2	2961.7	6.3639
2	350.00	4	0.066473	2827.4	3093.3	6.5843
3	400.00	4	0.073431	2920.7	3214.5	6.7714
4	450.00	4	0.080043	3011.0	3331.2	6.9386
5	500.00	4	0.086442	3100.3	3446.0	7.0922
6	550.00	4	0.092700	3189.5	3560.3	7.2355
7	600.00	4	0.098859	3279.4	3674.9	7.3705
8	650.00	4	0.104940	3370.3	3790.1	7.4988
9	700.00	4	0.110980	3462.4	3906.3	7.6214
10	750.00	4	0.116970	3555.8	4023.6	7.7390
11	800.00	4	0.122920	3650.6	4142.3	7.8523
12	850.00	4	0.128850	3747.0	4262.4	7.9616
13	900.00	4	0.134760	3844.8	4383.9	8.0674
14	950.00	4	0.140650	3944.2	4506.8	8.1701
15	1000.00	4	0.146520	4045.1	4631.2	8.2697

5 MPa¶

In [6]:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

df = pd.read_excel('../figures/Module-4/Steam_5MPa.xlsx', sheet_name='Sheet2', index_col=None, na_values=['NA'])
df

Out[6]:

	Temperature (C)	Pressure (MPa)	Volume (m3/kg)	Internal Energy (kJ/kg)	Enthalpy (kJ/kg)	Entropy (J/g*K)
0	263.94	5	0.039446	2597.0	2794.2	5.9737
1	300.00	5	0.045346	2699.0	2925.7	6.2110
2	350.00	5	0.051969	2809.5	3069.3	6.4516
3	400.00	5	0.057837	2907.5	3196.7	6.6483
4	450.00	5	0.063323	3000.6	3317.2	6.8210
5	500.00	5	0.068583	3091.7	3434.7	6.9781
6	550.00	5	0.073694	3182.4	3550.9	7.1237
7	600.00	5	0.078704	3273.3	3666.8	7.2605
8	650.00	5	0.083639	3365.0	3783.2	7.3901
9	700.00	5	0.088518	3457.7	3900.3	7.5136
10	750.00	5	0.093355	3551.6	4018.4	7.6320
11	800.00	5	0.098158	3646.9	4137.7	7.7458
12	850.00	5	0.102930	3743.6	4258.3	7.8556
13	900.00	5	0.107690	3841.8	4380.2	7.9618
14	950.00	5	0.112420	3941.5	4503.6	8.0648
15	1000.00	5	0.117150	4042.6	4628.3	8.1648

6 MPa¶

In [7]:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

df = pd.read_excel('../figures/Module-4/Steam_6MPa.xlsx', sheet_name='Sheet2', index_col=None, na_values=['NA'])
df

Out[7]:

	Temperature (C)	Pressure (MPa)	Volume (m3/kg)	Internal Energy (kJ/kg)	Enthalpy (kJ/kg)	Entropy (J/g*K)
0	275.58	6	0.032448	2589.9	2784.6	5.8901
1	300.00	6	0.036189	2668.4	2885.5	6.0703
2	350.00	6	0.042251	2790.4	3043.9	6.3357
3	400.00	6	0.047419	2893.7	3178.2	6.5432
4	450.00	6	0.052166	2989.9	3302.9	6.7219
5	500.00	6	0.056671	3083.1	3423.1	6.8826
6	550.00	6	0.061021	3175.2	3541.3	7.0307
7	600.00	6	0.065265	3267.2	3658.7	7.1693
8	650.00	6	0.069434	3359.6	3776.2	7.3001
9	700.00	6	0.073545	3453.0	3894.3	7.4246
10	750.00	6	0.077614	3547.5	4013.2	7.5438
11	800.00	6	0.081648	3643.2	4133.1	7.6582
12	850.00	6	0.085655	3740.3	4254.2	7.7685
13	900.00	6	0.089641	3838.8	4376.6	7.8751
14	950.00	6	0.093608	3938.7	4500.3	7.9784
15	1000.00	6	0.097560	4040.1	4625.4	8.0786

7 MPa¶

In [8]:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

df = pd.read_excel('../figures/Module-4/Steam_7MPa.xlsx', sheet_name='Sheet2', index_col=None, na_values=['NA'])
df

Out[8]:

	Temperature (C)	Pressure (MPa)	Volume (m3/kg)	Internal Energy (kJ/kg)	Enthalpy (kJ/kg)	Entropy (J/g*K)
0	285.83	7	0.027378	2581.0	2772.6	5.8148
1	300.00	7	0.029492	2633.5	2839.9	5.9337
2	350.00	7	0.035262	2770.1	3016.9	6.2304
3	400.00	7	0.039958	2879.5	3159.2	6.4502
4	450.00	7	0.044187	2979.0	3288.3	6.6353
5	500.00	7	0.048157	3074.3	3411.4	6.8000
6	550.00	7	0.051966	3167.9	3531.6	6.9506
7	600.00	7	0.055665	3260.9	3650.6	7.0910
8	650.00	7	0.059286	3354.3	3769.3	7.2231
9	700.00	7	0.062850	3448.3	3888.2	7.3486
10	750.00	7	0.066370	3543.3	4007.9	7.4685
11	800.00	7	0.069855	3639.5	4128.4	7.5836
12	850.00	7	0.073314	3736.9	4250.1	7.6944
13	900.00	7	0.076750	3835.7	4373.0	7.8014
14	950.00	7	0.080168	3935.9	4497.1	7.9050
15	1000.00	7	0.083571	4037.5	4622.5	8.0055

8 MPa¶

In [9]:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

df = pd.read_excel('../figures/Module-4/Steam_8MPa.xlsx', sheet_name='Sheet2', index_col=None, na_values=['NA'])
df

Out[9]:

	Temperature (C)	Pressure (MPa)	Volume (m3/kg)	Internal Energy (kJ/kg)	Enthalpy (kJ/kg)	Entropy (J/g*K)
0	295.01	8	0.023526	2570.5	2758.7	5.7450
1	300.00	8	0.024279	2592.3	2786.5	5.7937
2	350.00	8	0.029975	2748.3	2988.1	6.1321
3	400.00	8	0.034344	2864.6	3139.4	6.3658
4	450.00	8	0.038194	2967.8	3273.3	6.5579
5	500.00	8	0.041767	3065.4	3399.5	6.7266
6	550.00	8	0.045172	3160.5	3521.8	6.8799
7	600.00	8	0.048463	3254.7	3642.4	7.0221
8	650.00	8	0.051675	3348.9	3762.3	7.1556
9	700.00	8	0.054828	3443.6	3882.2	7.2821
10	750.00	8	0.057937	3539.1	4002.6	7.4028
11	800.00	8	0.061011	3635.7	4123.8	7.5184
12	850.00	8	0.064057	3733.5	4246.0	7.6297
13	900.00	8	0.067082	3832.6	4369.3	7.7371
14	950.00	8	0.070088	3933.1	4493.8	7.8411
15	1000.00	8	0.073079	4035.0	4619.6	7.9419

9 MPa¶

In [10]:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

df = pd.read_excel('../figures/Module-4/Steam_9MPa.xlsx', sheet_name='Sheet2', index_col=None, na_values=['NA'])
df

Out[10]:

	Temperature (C)	Pressure (MPa)	Volume (m3/kg)	Internal Energy (kJ/kg)	Enthalpy (kJ/kg)	Entropy (J/g*K)
0	303.34	9	0.020490	2558.5	2742.9	5.6791
1	350.00	9	0.025816	2724.9	2957.3	6.0380
2	400.00	9	0.029960	2849.2	3118.8	6.2876
3	450.00	9	0.033524	2956.3	3258.0	6.4872
4	500.00	9	0.036793	3056.3	3387.4	6.6603
5	550.00	9	0.039885	3153.0	3512.0	6.8164
6	600.00	9	0.042861	3248.4	3634.1	6.9605
7	650.00	9	0.045755	3343.4	3755.2	7.0953
8	700.00	9	0.048589	3438.8	3876.1	7.2229
9	750.00	9	0.051378	3534.9	3997.3	7.3443
10	800.00	9	0.054132	3632.0	4119.1	7.4606
11	850.00	9	0.056858	3730.2	4241.9	7.5724
12	900.00	9	0.059562	3829.6	4365.7	7.6802
13	950.00	9	0.062248	3930.3	4490.6	7.7844
14	1000.00	9	0.064918	4032.4	4616.7	7.8855

10 MPa¶

In [11]:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

df = pd.read_excel('../figures/Module-4/Steam_10MPa.xlsx', sheet_name='Sheet2', index_col=None, na_values=['NA'])
df

Out[11]:

	Temperature (C)	Pressure (MPa)	Volume (m3/kg)	Internal Energy (kJ/kg)	Enthalpy (kJ/kg)	Entropy (J/g*K)
0	311	10	0.018030	2545.2	2725.5	5.6160
1	350	10	0.022440	2699.6	2924.0	5.9459
2	400	10	0.026436	2833.1	3097.4	6.2141
3	450	10	0.029782	2944.5	3242.3	6.4219
4	500	10	0.032811	3047.0	3375.1	6.5995
5	550	10	0.035654	3145.4	3502.0	6.7585
6	600	10	0.038378	3242.0	3625.8	6.9045
7	650	10	0.041018	3337.9	3748.1	7.0408
8	700	10	0.043597	3434.0	3870.0	7.1693
9	750	10	0.046131	3530.7	3992.0	7.2916
10	800	10	0.048629	3628.2	4114.5	7.4085
11	850	10	0.051099	3726.8	4237.8	7.5207
12	900	10	0.053547	3826.5	4362.0	7.6290
13	950	10	0.055976	3927.5	4487.3	7.7335
14	1000	10	0.058390	4029.9	4613.8	7.8349

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