import matplotlib.pyplot as plt
import numpy as np

import numpy as np
x = np.linspace (0,2,100)
y=2*x
fig, ax = plt.subplots()
ax.plot (x,y, color='purple')
ax.set_xlabel("x axis")
ax.set_ylabel("y axis")
plt.show()

x

array([0.        , 0.02020202, 0.04040404, 0.06060606, 0.08080808,
       0.1010101 , 0.12121212, 0.14141414, 0.16161616, 0.18181818,
       0.2020202 , 0.22222222, 0.24242424, 0.26262626, 0.28282828,
       0.3030303 , 0.32323232, 0.34343434, 0.36363636, 0.38383838,
       0.4040404 , 0.42424242, 0.44444444, 0.46464646, 0.48484848,
       0.50505051, 0.52525253, 0.54545455, 0.56565657, 0.58585859,
       0.60606061, 0.62626263, 0.64646465, 0.66666667, 0.68686869,
       0.70707071, 0.72727273, 0.74747475, 0.76767677, 0.78787879,
       0.80808081, 0.82828283, 0.84848485, 0.86868687, 0.88888889,
       0.90909091, 0.92929293, 0.94949495, 0.96969697, 0.98989899,
       1.01010101, 1.03030303, 1.05050505, 1.07070707, 1.09090909,
       1.11111111, 1.13131313, 1.15151515, 1.17171717, 1.19191919,
       1.21212121, 1.23232323, 1.25252525, 1.27272727, 1.29292929,
       1.31313131, 1.33333333, 1.35353535, 1.37373737, 1.39393939,
       1.41414141, 1.43434343, 1.45454545, 1.47474747, 1.49494949,
       1.51515152, 1.53535354, 1.55555556, 1.57575758, 1.5959596 ,
       1.61616162, 1.63636364, 1.65656566, 1.67676768, 1.6969697 ,
       1.71717172, 1.73737374, 1.75757576, 1.77777778, 1.7979798 ,
       1.81818182, 1.83838384, 1.85858586, 1.87878788, 1.8989899 ,
       1.91919192, 1.93939394, 1.95959596, 1.97979798, 2.        ])

#calculate costs of sequencing 245Mbp at 2001 price, $10,000 1Mbp
cost=0.01
bp1=248
bp2=242
total_cost=cost*bp1+cost*bp2
print(total_cost)

4.9

import pandas as pd

data = pd.read_excel("CHrompose.xltx")

data

cost_2001 = 10000
cost_2011 = 0.1
cost_2021 = 0.01

data['sequencing_cost_2001'] = data['baspepiars']*cost_2001/1000000
data['sequencing_cost_2011'] = data['baspepiars']*cost_2011/1000000
data['sequencing_cost_2021'] = data['baspepiars']*cost_2021/1000000

data

total_cost_2001=data['sequencing_cost_2001'].sum()

print(total_cost_2001)

308826983.2

total_cost_2011=data['sequencing_cost_2011'].sum()

print(total_cost_2011)

3088.269832

total_cost_2021=data['sequencing_cost_2021'].sum()

print(total_cost_2021)

308.8269832

	chrmoosomes	baspepiars	sequencing_cost_2001	sequencing_cost_2011	sequencing_cost_2021
0	1	248956422	24895642.2	248.956422	24.895642
1	2	242193529	24219352.9	242.193529	24.219353
2	3	198295559	19829555.9	198.295559	19.829556
3	4	190214555	19021455.5	190.214555	19.021456
4	5	181538259	18153825.9	181.538259	18.153826
5	6	170805979	17080597.9	170.805979	17.080598
6	7	159345973	15934597.3	159.345973	15.934597
7	8	145138636	14513863.6	145.138636	14.513864
8	9	138394717	13839471.7	138.394717	13.839472
9	10	133797422	13379742.2	133.797422	13.379742
10	11	135086622	13508662.2	135.086622	13.508662
11	12	133275309	13327530.9	133.275309	13.327531
12	13	114364328	11436432.8	114.364328	11.436433
13	14	107043718	10704371.8	107.043718	10.704372
14	15	101991189	10199118.9	101.991189	10.199119
15	16	90338345	9033834.5	90.338345	9.033835
16	17	83257441	8325744.1	83.257441	8.325744
17	18	80373285	8037328.5	80.373285	8.037328
18	19	58617616	5861761.6	58.617616	5.861762
19	20	64444167	6444416.7	64.444167	6.444417
20	21	46709983	4670998.3	46.709983	4.670998
21	22	50818468	5081846.8	50.818468	5.081847
22	X	156040895	15604089.5	156.040895	15.604089
23	Y	57227415	5722741.5	57.227415	5.722742