In [1]:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
Download the .txt data for the "Yearly mean total sunspot number [1700 - now]" from the SILSO website. Upload the file to the same directory as this notebook.
In [2]:
import os
assert os.path.isfile('yearssn.dat')
Use np.loadtxt to read the data into a NumPy array called data. Then create two new 1d NumPy arrays named years and ssc that have the sequence of year and sunspot counts.
In [7]:
data = np.loadtxt("yearssn.dat")
a= np.array(data)
a
Out[7]:
array([[ 1.70050000e+03, 5.00000000e+00],
[ 1.70150000e+03, 1.10000000e+01],
[ 1.70250000e+03, 1.60000000e+01],
[ 1.70350000e+03, 2.30000000e+01],
[ 1.70450000e+03, 3.60000000e+01],
[ 1.70550000e+03, 5.80000000e+01],
[ 1.70650000e+03, 2.90000000e+01],
[ 1.70750000e+03, 2.00000000e+01],
[ 1.70850000e+03, 1.00000000e+01],
[ 1.70950000e+03, 8.00000000e+00],
[ 1.71050000e+03, 3.00000000e+00],
[ 1.71150000e+03, 0.00000000e+00],
[ 1.71250000e+03, 0.00000000e+00],
[ 1.71350000e+03, 2.00000000e+00],
[ 1.71450000e+03, 1.10000000e+01],
[ 1.71550000e+03, 2.70000000e+01],
[ 1.71650000e+03, 4.70000000e+01],
[ 1.71750000e+03, 6.30000000e+01],
[ 1.71850000e+03, 6.00000000e+01],
[ 1.71950000e+03, 3.90000000e+01],
[ 1.72050000e+03, 2.80000000e+01],
[ 1.72150000e+03, 2.60000000e+01],
[ 1.72250000e+03, 2.20000000e+01],
[ 1.72350000e+03, 1.10000000e+01],
[ 1.72450000e+03, 2.10000000e+01],
[ 1.72550000e+03, 4.00000000e+01],
[ 1.72650000e+03, 7.80000000e+01],
[ 1.72750000e+03, 1.22000000e+02],
[ 1.72850000e+03, 1.03000000e+02],
[ 1.72950000e+03, 7.30000000e+01],
[ 1.73050000e+03, 4.70000000e+01],
[ 1.73150000e+03, 3.50000000e+01],
[ 1.73250000e+03, 1.10000000e+01],
[ 1.73350000e+03, 5.00000000e+00],
[ 1.73450000e+03, 1.60000000e+01],
[ 1.73550000e+03, 3.40000000e+01],
[ 1.73650000e+03, 7.00000000e+01],
[ 1.73750000e+03, 8.10000000e+01],
[ 1.73850000e+03, 1.11000000e+02],
[ 1.73950000e+03, 1.01000000e+02],
[ 1.74050000e+03, 7.30000000e+01],
[ 1.74150000e+03, 4.00000000e+01],
[ 1.74250000e+03, 2.00000000e+01],
[ 1.74350000e+03, 1.60000000e+01],
[ 1.74450000e+03, 5.00000000e+00],
[ 1.74550000e+03, 1.10000000e+01],
[ 1.74650000e+03, 2.20000000e+01],
[ 1.74750000e+03, 4.00000000e+01],
[ 1.74850000e+03, 6.00000000e+01],
[ 1.74950000e+03, 8.09000000e+01],
[ 1.75050000e+03, 8.34000000e+01],
[ 1.75150000e+03, 4.77000000e+01],
[ 1.75250000e+03, 4.78000000e+01],
[ 1.75350000e+03, 3.07000000e+01],
[ 1.75450000e+03, 1.22000000e+01],
[ 1.75550000e+03, 9.60000000e+00],
[ 1.75650000e+03, 1.02000000e+01],
[ 1.75750000e+03, 3.24000000e+01],
[ 1.75850000e+03, 4.76000000e+01],
[ 1.75950000e+03, 5.40000000e+01],
[ 1.76050000e+03, 6.29000000e+01],
[ 1.76150000e+03, 8.59000000e+01],
[ 1.76250000e+03, 6.12000000e+01],
[ 1.76350000e+03, 4.51000000e+01],
[ 1.76450000e+03, 3.64000000e+01],
[ 1.76550000e+03, 2.09000000e+01],
[ 1.76650000e+03, 1.14000000e+01],
[ 1.76750000e+03, 3.78000000e+01],
[ 1.76850000e+03, 6.98000000e+01],
[ 1.76950000e+03, 1.06100000e+02],
[ 1.77050000e+03, 1.00800000e+02],
[ 1.77150000e+03, 8.16000000e+01],
[ 1.77250000e+03, 6.65000000e+01],
[ 1.77350000e+03, 3.48000000e+01],
[ 1.77450000e+03, 3.06000000e+01],
[ 1.77550000e+03, 7.00000000e+00],
[ 1.77650000e+03, 1.98000000e+01],
[ 1.77750000e+03, 9.25000000e+01],
[ 1.77850000e+03, 1.54400000e+02],
[ 1.77950000e+03, 1.25900000e+02],
[ 1.78050000e+03, 8.48000000e+01],
[ 1.78150000e+03, 6.81000000e+01],
[ 1.78250000e+03, 3.85000000e+01],
[ 1.78350000e+03, 2.28000000e+01],
[ 1.78450000e+03, 1.02000000e+01],
[ 1.78550000e+03, 2.41000000e+01],
[ 1.78650000e+03, 8.29000000e+01],
[ 1.78750000e+03, 1.32000000e+02],
[ 1.78850000e+03, 1.30900000e+02],
[ 1.78950000e+03, 1.18100000e+02],
[ 1.79050000e+03, 8.99000000e+01],
[ 1.79150000e+03, 6.66000000e+01],
[ 1.79250000e+03, 6.00000000e+01],
[ 1.79350000e+03, 4.69000000e+01],
[ 1.79450000e+03, 4.10000000e+01],
[ 1.79550000e+03, 2.13000000e+01],
[ 1.79650000e+03, 1.60000000e+01],
[ 1.79750000e+03, 6.40000000e+00],
[ 1.79850000e+03, 4.10000000e+00],
[ 1.79950000e+03, 6.80000000e+00],
[ 1.80050000e+03, 1.45000000e+01],
[ 1.80150000e+03, 3.40000000e+01],
[ 1.80250000e+03, 4.50000000e+01],
[ 1.80350000e+03, 4.31000000e+01],
[ 1.80450000e+03, 4.75000000e+01],
[ 1.80550000e+03, 4.22000000e+01],
[ 1.80650000e+03, 2.81000000e+01],
[ 1.80750000e+03, 1.01000000e+01],
[ 1.80850000e+03, 8.10000000e+00],
[ 1.80950000e+03, 2.50000000e+00],
[ 1.81050000e+03, 0.00000000e+00],
[ 1.81150000e+03, 1.40000000e+00],
[ 1.81250000e+03, 5.00000000e+00],
[ 1.81350000e+03, 1.22000000e+01],
[ 1.81450000e+03, 1.39000000e+01],
[ 1.81550000e+03, 3.54000000e+01],
[ 1.81650000e+03, 4.58000000e+01],
[ 1.81750000e+03, 4.10000000e+01],
[ 1.81850000e+03, 3.01000000e+01],
[ 1.81950000e+03, 2.39000000e+01],
[ 1.82050000e+03, 1.56000000e+01],
[ 1.82150000e+03, 6.60000000e+00],
[ 1.82250000e+03, 4.00000000e+00],
[ 1.82350000e+03, 1.80000000e+00],
[ 1.82450000e+03, 8.50000000e+00],
[ 1.82550000e+03, 1.66000000e+01],
[ 1.82650000e+03, 3.63000000e+01],
[ 1.82750000e+03, 4.96000000e+01],
[ 1.82850000e+03, 6.42000000e+01],
[ 1.82950000e+03, 6.70000000e+01],
[ 1.83050000e+03, 7.09000000e+01],
[ 1.83150000e+03, 4.78000000e+01],
[ 1.83250000e+03, 2.75000000e+01],
[ 1.83350000e+03, 8.50000000e+00],
[ 1.83450000e+03, 1.32000000e+01],
[ 1.83550000e+03, 5.69000000e+01],
[ 1.83650000e+03, 1.21500000e+02],
[ 1.83750000e+03, 1.38300000e+02],
[ 1.83850000e+03, 1.03200000e+02],
[ 1.83950000e+03, 8.57000000e+01],
[ 1.84050000e+03, 6.46000000e+01],
[ 1.84150000e+03, 3.67000000e+01],
[ 1.84250000e+03, 2.42000000e+01],
[ 1.84350000e+03, 1.07000000e+01],
[ 1.84450000e+03, 1.50000000e+01],
[ 1.84550000e+03, 4.01000000e+01],
[ 1.84650000e+03, 6.15000000e+01],
[ 1.84750000e+03, 9.85000000e+01],
[ 1.84850000e+03, 1.24700000e+02],
[ 1.84950000e+03, 9.61000000e+01],
[ 1.85050000e+03, 6.65000000e+01],
[ 1.85150000e+03, 6.42000000e+01],
[ 1.85250000e+03, 5.41000000e+01],
[ 1.85350000e+03, 3.90000000e+01],
[ 1.85450000e+03, 2.05000000e+01],
[ 1.85550000e+03, 6.70000000e+00],
[ 1.85650000e+03, 4.30000000e+00],
[ 1.85750000e+03, 2.28000000e+01],
[ 1.85850000e+03, 5.50000000e+01],
[ 1.85950000e+03, 9.39000000e+01],
[ 1.86050000e+03, 9.59000000e+01],
[ 1.86150000e+03, 7.72000000e+01],
[ 1.86250000e+03, 5.90000000e+01],
[ 1.86350000e+03, 4.40000000e+01],
[ 1.86450000e+03, 4.70000000e+01],
[ 1.86550000e+03, 3.04000000e+01],
[ 1.86650000e+03, 1.62000000e+01],
[ 1.86750000e+03, 7.30000000e+00],
[ 1.86850000e+03, 3.76000000e+01],
[ 1.86950000e+03, 7.41000000e+01],
[ 1.87050000e+03, 1.39100000e+02],
[ 1.87150000e+03, 1.11100000e+02],
[ 1.87250000e+03, 1.01400000e+02],
[ 1.87350000e+03, 6.60000000e+01],
[ 1.87450000e+03, 4.46000000e+01],
[ 1.87550000e+03, 1.70000000e+01],
[ 1.87650000e+03, 1.13000000e+01],
[ 1.87750000e+03, 1.24000000e+01],
[ 1.87850000e+03, 3.40000000e+00],
[ 1.87950000e+03, 6.00000000e+00],
[ 1.88050000e+03, 3.22000000e+01],
[ 1.88150000e+03, 5.43000000e+01],
[ 1.88250000e+03, 5.94000000e+01],
[ 1.88350000e+03, 6.37000000e+01],
[ 1.88450000e+03, 6.35000000e+01],
[ 1.88550000e+03, 5.18000000e+01],
[ 1.88650000e+03, 2.55000000e+01],
[ 1.88750000e+03, 1.31000000e+01],
[ 1.88850000e+03, 6.70000000e+00],
[ 1.88950000e+03, 6.20000000e+00],
[ 1.89050000e+03, 7.10000000e+00],
[ 1.89150000e+03, 3.57000000e+01],
[ 1.89250000e+03, 7.30000000e+01],
[ 1.89350000e+03, 8.52000000e+01],
[ 1.89450000e+03, 7.80000000e+01],
[ 1.89550000e+03, 6.39000000e+01],
[ 1.89650000e+03, 4.17000000e+01],
[ 1.89750000e+03, 2.62000000e+01],
[ 1.89850000e+03, 2.67000000e+01],
[ 1.89950000e+03, 1.21000000e+01],
[ 1.90050000e+03, 9.40000000e+00],
[ 1.90150000e+03, 2.70000000e+00],
[ 1.90250000e+03, 5.10000000e+00],
[ 1.90350000e+03, 2.44000000e+01],
[ 1.90450000e+03, 4.21000000e+01],
[ 1.90550000e+03, 6.33000000e+01],
[ 1.90650000e+03, 5.41000000e+01],
[ 1.90750000e+03, 6.17000000e+01],
[ 1.90850000e+03, 4.85000000e+01],
[ 1.90950000e+03, 4.39000000e+01],
[ 1.91050000e+03, 1.85000000e+01],
[ 1.91150000e+03, 5.70000000e+00],
[ 1.91250000e+03, 3.60000000e+00],
[ 1.91350000e+03, 1.40000000e+00],
[ 1.91450000e+03, 9.60000000e+00],
[ 1.91550000e+03, 4.74000000e+01],
[ 1.91650000e+03, 5.70000000e+01],
[ 1.91750000e+03, 1.04200000e+02],
[ 1.91850000e+03, 8.08000000e+01],
[ 1.91950000e+03, 6.35000000e+01],
[ 1.92050000e+03, 3.76000000e+01],
[ 1.92150000e+03, 2.61000000e+01],
[ 1.92250000e+03, 1.42000000e+01],
[ 1.92350000e+03, 5.80000000e+00],
[ 1.92450000e+03, 1.67000000e+01],
[ 1.92550000e+03, 4.44000000e+01],
[ 1.92650000e+03, 6.39000000e+01],
[ 1.92750000e+03, 6.88000000e+01],
[ 1.92850000e+03, 7.78000000e+01],
[ 1.92950000e+03, 6.49000000e+01],
[ 1.93050000e+03, 3.56000000e+01],
[ 1.93150000e+03, 2.11000000e+01],
[ 1.93250000e+03, 1.11000000e+01],
[ 1.93350000e+03, 5.50000000e+00],
[ 1.93450000e+03, 8.70000000e+00],
[ 1.93550000e+03, 3.61000000e+01],
[ 1.93650000e+03, 7.97000000e+01],
[ 1.93750000e+03, 1.14400000e+02],
[ 1.93850000e+03, 1.09600000e+02],
[ 1.93950000e+03, 8.88000000e+01],
[ 1.94050000e+03, 6.78000000e+01],
[ 1.94150000e+03, 4.75000000e+01],
[ 1.94250000e+03, 3.04000000e+01],
[ 1.94350000e+03, 1.63000000e+01],
[ 1.94450000e+03, 9.70000000e+00],
[ 1.94550000e+03, 3.32000000e+01],
[ 1.94650000e+03, 9.26000000e+01],
[ 1.94750000e+03, 1.51600000e+02],
[ 1.94850000e+03, 1.36300000e+02],
[ 1.94950000e+03, 1.34700000e+02],
[ 1.95050000e+03, 8.39000000e+01],
[ 1.95150000e+03, 6.94000000e+01],
[ 1.95250000e+03, 3.15000000e+01],
[ 1.95350000e+03, 1.39000000e+01],
[ 1.95450000e+03, 4.40000000e+00],
[ 1.95550000e+03, 3.80000000e+01],
[ 1.95650000e+03, 1.41700000e+02],
[ 1.95750000e+03, 1.90200000e+02],
[ 1.95850000e+03, 1.84800000e+02],
[ 1.95950000e+03, 1.59000000e+02],
[ 1.96050000e+03, 1.12300000e+02],
[ 1.96150000e+03, 5.39000000e+01],
[ 1.96250000e+03, 3.75000000e+01],
[ 1.96350000e+03, 2.79000000e+01],
[ 1.96450000e+03, 1.02000000e+01],
[ 1.96550000e+03, 1.51000000e+01],
[ 1.96650000e+03, 4.70000000e+01],
[ 1.96750000e+03, 9.38000000e+01],
[ 1.96850000e+03, 1.05900000e+02],
[ 1.96950000e+03, 1.05500000e+02],
[ 1.97050000e+03, 1.04500000e+02],
[ 1.97150000e+03, 6.66000000e+01],
[ 1.97250000e+03, 6.89000000e+01],
[ 1.97350000e+03, 3.80000000e+01],
[ 1.97450000e+03, 3.45000000e+01],
[ 1.97550000e+03, 1.55000000e+01],
[ 1.97650000e+03, 1.26000000e+01],
[ 1.97750000e+03, 2.75000000e+01],
[ 1.97850000e+03, 9.25000000e+01],
[ 1.97950000e+03, 1.55400000e+02],
[ 1.98050000e+03, 1.54600000e+02],
[ 1.98150000e+03, 1.40500000e+02],
[ 1.98250000e+03, 1.15900000e+02],
[ 1.98350000e+03, 6.68000000e+01],
[ 1.98450000e+03, 4.57000000e+01],
[ 1.98550000e+03, 1.80000000e+01],
[ 1.98650000e+03, 1.34000000e+01],
[ 1.98750000e+03, 2.94000000e+01],
[ 1.98850000e+03, 1.00200000e+02],
[ 1.98950000e+03, 1.57600000e+02],
[ 1.99050000e+03, 1.42600000e+02],
[ 1.99150000e+03, 1.45700000e+02],
[ 1.99250000e+03, 9.43000000e+01],
[ 1.99350000e+03, 5.46000000e+01],
[ 1.99450000e+03, 2.99000000e+01],
[ 1.99550000e+03, 1.75000000e+01],
[ 1.99650000e+03, 8.60000000e+00],
[ 1.99750000e+03, 2.15000000e+01],
[ 1.99850000e+03, 6.43000000e+01],
[ 1.99950000e+03, 9.33000000e+01],
[ 2.00050000e+03, 1.19600000e+02],
[ 2.00150000e+03, 1.11000000e+02],
[ 2.00250000e+03, 1.04000000e+02],
[ 2.00350000e+03, 6.37000000e+01],
[ 2.00450000e+03, 4.04000000e+01],
[ 2.00550000e+03, 2.98000000e+01],
[ 2.00650000e+03, 1.52000000e+01],
[ 2.00750000e+03, 7.50000000e+00],
[ 2.00850000e+03, 2.90000000e+00],
[ 2.00950000e+03, 3.10000000e+00],
[ 2.01050000e+03, 1.65000000e+01],
[ 2.01150000e+03, 5.57000000e+01],
[ 2.01250000e+03, 5.77000000e+01],
[ 2.01350000e+03, 6.49000000e+01],
[ 2.01450000e+03, 7.89000000e+01]])
In [10]:
years = a[:,0]
years
Out[10]:
array([ 1700.5, 1701.5, 1702.5, 1703.5, 1704.5, 1705.5, 1706.5,
1707.5, 1708.5, 1709.5, 1710.5, 1711.5, 1712.5, 1713.5,
1714.5, 1715.5, 1716.5, 1717.5, 1718.5, 1719.5, 1720.5,
1721.5, 1722.5, 1723.5, 1724.5, 1725.5, 1726.5, 1727.5,
1728.5, 1729.5, 1730.5, 1731.5, 1732.5, 1733.5, 1734.5,
1735.5, 1736.5, 1737.5, 1738.5, 1739.5, 1740.5, 1741.5,
1742.5, 1743.5, 1744.5, 1745.5, 1746.5, 1747.5, 1748.5,
1749.5, 1750.5, 1751.5, 1752.5, 1753.5, 1754.5, 1755.5,
1756.5, 1757.5, 1758.5, 1759.5, 1760.5, 1761.5, 1762.5,
1763.5, 1764.5, 1765.5, 1766.5, 1767.5, 1768.5, 1769.5,
1770.5, 1771.5, 1772.5, 1773.5, 1774.5, 1775.5, 1776.5,
1777.5, 1778.5, 1779.5, 1780.5, 1781.5, 1782.5, 1783.5,
1784.5, 1785.5, 1786.5, 1787.5, 1788.5, 1789.5, 1790.5,
1791.5, 1792.5, 1793.5, 1794.5, 1795.5, 1796.5, 1797.5,
1798.5, 1799.5, 1800.5, 1801.5, 1802.5, 1803.5, 1804.5,
1805.5, 1806.5, 1807.5, 1808.5, 1809.5, 1810.5, 1811.5,
1812.5, 1813.5, 1814.5, 1815.5, 1816.5, 1817.5, 1818.5,
1819.5, 1820.5, 1821.5, 1822.5, 1823.5, 1824.5, 1825.5,
1826.5, 1827.5, 1828.5, 1829.5, 1830.5, 1831.5, 1832.5,
1833.5, 1834.5, 1835.5, 1836.5, 1837.5, 1838.5, 1839.5,
1840.5, 1841.5, 1842.5, 1843.5, 1844.5, 1845.5, 1846.5,
1847.5, 1848.5, 1849.5, 1850.5, 1851.5, 1852.5, 1853.5,
1854.5, 1855.5, 1856.5, 1857.5, 1858.5, 1859.5, 1860.5,
1861.5, 1862.5, 1863.5, 1864.5, 1865.5, 1866.5, 1867.5,
1868.5, 1869.5, 1870.5, 1871.5, 1872.5, 1873.5, 1874.5,
1875.5, 1876.5, 1877.5, 1878.5, 1879.5, 1880.5, 1881.5,
1882.5, 1883.5, 1884.5, 1885.5, 1886.5, 1887.5, 1888.5,
1889.5, 1890.5, 1891.5, 1892.5, 1893.5, 1894.5, 1895.5,
1896.5, 1897.5, 1898.5, 1899.5, 1900.5, 1901.5, 1902.5,
1903.5, 1904.5, 1905.5, 1906.5, 1907.5, 1908.5, 1909.5,
1910.5, 1911.5, 1912.5, 1913.5, 1914.5, 1915.5, 1916.5,
1917.5, 1918.5, 1919.5, 1920.5, 1921.5, 1922.5, 1923.5,
1924.5, 1925.5, 1926.5, 1927.5, 1928.5, 1929.5, 1930.5,
1931.5, 1932.5, 1933.5, 1934.5, 1935.5, 1936.5, 1937.5,
1938.5, 1939.5, 1940.5, 1941.5, 1942.5, 1943.5, 1944.5,
1945.5, 1946.5, 1947.5, 1948.5, 1949.5, 1950.5, 1951.5,
1952.5, 1953.5, 1954.5, 1955.5, 1956.5, 1957.5, 1958.5,
1959.5, 1960.5, 1961.5, 1962.5, 1963.5, 1964.5, 1965.5,
1966.5, 1967.5, 1968.5, 1969.5, 1970.5, 1971.5, 1972.5,
1973.5, 1974.5, 1975.5, 1976.5, 1977.5, 1978.5, 1979.5,
1980.5, 1981.5, 1982.5, 1983.5, 1984.5, 1985.5, 1986.5,
1987.5, 1988.5, 1989.5, 1990.5, 1991.5, 1992.5, 1993.5,
1994.5, 1995.5, 1996.5, 1997.5, 1998.5, 1999.5, 2000.5,
2001.5, 2002.5, 2003.5, 2004.5, 2005.5, 2006.5, 2007.5,
2008.5, 2009.5, 2010.5, 2011.5, 2012.5, 2013.5, 2014.5])
In [12]:
ssc = a[:,1]
ssc
Out[12]:
array([ 5. , 11. , 16. , 23. , 36. , 58. , 29. , 20. ,
10. , 8. , 3. , 0. , 0. , 2. , 11. , 27. ,
47. , 63. , 60. , 39. , 28. , 26. , 22. , 11. ,
21. , 40. , 78. , 122. , 103. , 73. , 47. , 35. ,
11. , 5. , 16. , 34. , 70. , 81. , 111. , 101. ,
73. , 40. , 20. , 16. , 5. , 11. , 22. , 40. ,
60. , 80.9, 83.4, 47.7, 47.8, 30.7, 12.2, 9.6,
10.2, 32.4, 47.6, 54. , 62.9, 85.9, 61.2, 45.1,
36.4, 20.9, 11.4, 37.8, 69.8, 106.1, 100.8, 81.6,
66.5, 34.8, 30.6, 7. , 19.8, 92.5, 154.4, 125.9,
84.8, 68.1, 38.5, 22.8, 10.2, 24.1, 82.9, 132. ,
130.9, 118.1, 89.9, 66.6, 60. , 46.9, 41. , 21.3,
16. , 6.4, 4.1, 6.8, 14.5, 34. , 45. , 43.1,
47.5, 42.2, 28.1, 10.1, 8.1, 2.5, 0. , 1.4,
5. , 12.2, 13.9, 35.4, 45.8, 41. , 30.1, 23.9,
15.6, 6.6, 4. , 1.8, 8.5, 16.6, 36.3, 49.6,
64.2, 67. , 70.9, 47.8, 27.5, 8.5, 13.2, 56.9,
121.5, 138.3, 103.2, 85.7, 64.6, 36.7, 24.2, 10.7,
15. , 40.1, 61.5, 98.5, 124.7, 96.1, 66.5, 64.2,
54.1, 39. , 20.5, 6.7, 4.3, 22.8, 55. , 93.9,
95.9, 77.2, 59. , 44. , 47. , 30.4, 16.2, 7.3,
37.6, 74.1, 139.1, 111.1, 101.4, 66. , 44.6, 17. ,
11.3, 12.4, 3.4, 6. , 32.2, 54.3, 59.4, 63.7,
63.5, 51.8, 25.5, 13.1, 6.7, 6.2, 7.1, 35.7,
73. , 85.2, 78. , 63.9, 41.7, 26.2, 26.7, 12.1,
9.4, 2.7, 5.1, 24.4, 42.1, 63.3, 54.1, 61.7,
48.5, 43.9, 18.5, 5.7, 3.6, 1.4, 9.6, 47.4,
57. , 104.2, 80.8, 63.5, 37.6, 26.1, 14.2, 5.8,
16.7, 44.4, 63.9, 68.8, 77.8, 64.9, 35.6, 21.1,
11.1, 5.5, 8.7, 36.1, 79.7, 114.4, 109.6, 88.8,
67.8, 47.5, 30.4, 16.3, 9.7, 33.2, 92.6, 151.6,
136.3, 134.7, 83.9, 69.4, 31.5, 13.9, 4.4, 38. ,
141.7, 190.2, 184.8, 159. , 112.3, 53.9, 37.5, 27.9,
10.2, 15.1, 47. , 93.8, 105.9, 105.5, 104.5, 66.6,
68.9, 38. , 34.5, 15.5, 12.6, 27.5, 92.5, 155.4,
154.6, 140.5, 115.9, 66.8, 45.7, 18. , 13.4, 29.4,
100.2, 157.6, 142.6, 145.7, 94.3, 54.6, 29.9, 17.5,
8.6, 21.5, 64.3, 93.3, 119.6, 111. , 104. , 63.7,
40.4, 29.8, 15.2, 7.5, 2.9, 3.1, 16.5, 55.7,
57.7, 64.9, 78.9])
In [ ]:
assert len(year)==315
assert year.dtype==np.dtype(float)
assert len(ssc)==315
assert ssc.dtype==np.dtype(float)
Make a line plot showing the sunspot count as a function of year.
In [25]:
plt.plot(years, ssc,)
plt.figsize=(10,8)
In [ ]:
assert True # leave for grading
Describe the choices you have made in building this visualization and how they make it effective.
YOUR ANSWER HERE
Now make 4 subplots, one for each century in the data set. This approach works well for this dataset as it allows you to maintain mild slopes while limiting the overall width of the visualization. Perform similar customizations as above:
In [ ]:
# YOUR CODE HERE
raise NotImplementedError()
In [ ]:
assert True # leave for grading
Content source: sthuggins/phys202-2015-work
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