Please use BS4, Regular Expressions or Pandas to read in the two data files below. Then calculate the average of 'decimal' column in co2.html, 'TOPEX' column in SeaLevel.csv for each year. Finally, combine those 2 data into 1 to printout. Sample could be: Year CO2 Sea_Level 1959 ......... ......... Co2.html: # Total carbon emissions # (million metric tons of C) yearmonthdecimalaverageinterpolatedtrend#days 195911959.042315.62315.62315.70-1 195921959.125316.38316.38315.88-1 195931959.208316.71316.71315.62-1 195941959.292317.72317.72315.56-1 195951959.375318.29318.29315.50-1 195961959.458318.15318.15315.92-1 195971959.542316.54316.54315.66-1 195981959.625314.80314.80315.81-1 195991959.708313.84313.84316.55-1 1959101959.792313.26313.26316.19-1 1959111959.875314.80314.80316.78-1 ... SeaLevel.csv #title = mean sea level anomaly global ocean (66S to 66N) (Annual signals retained) #institution = NOAA/Laboratory for Satellite Altimetry #references = NOAA Sea Level Rise year,TOPEX/Poseidon,Jason-1,Jason-2,Jason-3 1992.9614,-16.27000, 1992.9865,-17.97000, 1993.0123,-14.87000, 1993.0407,-19.87000, 1993.0660,-25.27000, 1993.0974,-29.37000, 1993.1206,-27.67000, 1993.1493,-21.87000, 1993.1765,-18.97000, 1993.2037,-19.47000, 1993.2307,-22.97000, 1993.2851,-26.27000, 1993.3123,-20.07000, 1993.3394,-19.87000, 1998.8234,6.53000, 1998.8505,2.53000, 1998.8775,-4.07000, 1998.9046,-10.17000, 1998.9319,-3.97000, 1998.9591,-3.27000, 1998.9862,0.13000, 1999.0133,-4.17000, 1999.0405,-6.87000, 1999.0948,-11.17000, 1999.1256,3.73000, 1999.1491,-1.27000, 1999.1763,-6.37000, 1999.2034,-11.77000, 1999.2306,-10.37000, 1999.2577,-7.87000, 1999.2848,-5.37000, 1999.3392,-8.27000, 1999.3663,-13.77000, 2001.6738,5.43000, 2001.7010,15.73000, 2001.7283,16.73000, 2001.7553,14.93000, 2001.7825,7.73000, 2001.8096,4.03000, 2001.8368,11.63000, 2001.8639,16.53000, 2001.8918,14.53000, 2001.9182,10.93000, 2001.9454,4.73000, 2001.9725,3.63000, 2002.1083,-1.67000,6.23000, 2002.1352,6.33000, 2002.1354,-0.17000, 2002.1626,4.43000,4.93000, 2002.1897,4.93000, 2002.1898,-1.27000, ...
Please use BS4, Regular Expressions or Pandas to read in the two data files below. Then calculate the average of 'decimal' column in co2.html, 'TOPEX' column in SeaLevel.csv for each year. Finally, combine those 2 data into 1 to printout. Sample could be: Year CO2 Sea_Level 1959 ......... ......... Co2.html: # Total carbon emissions # (million metric tons of C) yearmonthdecimalaverageinterpolatedtrend#days 195911959.042315.62315.62315.70-1 195921959.125316.38316.38315.88-1 195931959.208316.71316.71315.62-1 195941959.292317.72317.72315.56-1 195951959.375318.29318.29315.50-1 195961959.458318.15318.15315.92-1 195971959.542316.54316.54315.66-1 195981959.625314.80314.80315.81-1 195991959.708313.84313.84316.55-1 1959101959.792313.26313.26316.19-1 1959111959.875314.80314.80316.78-1 ... SeaLevel.csv #title = mean sea level anomaly global ocean (66S to 66N) (Annual signals retained) #institution = NOAA/Laboratory for Satellite Altimetry #references = NOAA Sea Level Rise year,TOPEX/Poseidon,Jason-1,Jason-2,Jason-3 1992.9614,-16.27000, 1992.9865,-17.97000, 1993.0123,-14.87000, 1993.0407,-19.87000, 1993.0660,-25.27000, 1993.0974,-29.37000, 1993.1206,-27.67000, 1993.1493,-21.87000, 1993.1765,-18.97000, 1993.2037,-19.47000, 1993.2307,-22.97000, 1993.2851,-26.27000, 1993.3123,-20.07000, 1993.3394,-19.87000, 1998.8234,6.53000, 1998.8505,2.53000, 1998.8775,-4.07000, 1998.9046,-10.17000, 1998.9319,-3.97000, 1998.9591,-3.27000, 1998.9862,0.13000, 1999.0133,-4.17000, 1999.0405,-6.87000, 1999.0948,-11.17000, 1999.1256,3.73000, 1999.1491,-1.27000, 1999.1763,-6.37000, 1999.2034,-11.77000, 1999.2306,-10.37000, 1999.2577,-7.87000, 1999.2848,-5.37000, 1999.3392,-8.27000, 1999.3663,-13.77000, 2001.6738,5.43000, 2001.7010,15.73000, 2001.7283,16.73000, 2001.7553,14.93000, 2001.7825,7.73000, 2001.8096,4.03000, 2001.8368,11.63000, 2001.8639,16.53000, 2001.8918,14.53000, 2001.9182,10.93000, 2001.9454,4.73000, 2001.9725,3.63000, 2002.1083,-1.67000,6.23000, 2002.1352,6.33000, 2002.1354,-0.17000, 2002.1626,4.43000,4.93000, 2002.1897,4.93000, 2002.1898,-1.27000, ...
Chapter2: Formatting Workbook Text And Data
Section: Chapter Questions
Problem 2.10CP
Related questions
Question
Please use BS4, Regular Expressions or Pandas to read in the two data files below.
Then calculate the average of 'decimal' column in co2.html, 'TOPEX' column in SeaLevel.csv for each year.
Finally, combine those 2 data into 1 to printout.
Sample could be:
Year CO2 Sea_Level
1959 ......... .........
Co2.html:
<TABLE summary="csv2html program output">
<TBODY><TR><TD># Total carbon emissions </TD></TR></TBODY>
<TBODY><TR><TD># (million metric tons of C)</TD></TR></TBODY>
<TBODY><TR><TD>year</TD><TD>month</TD><TD>decimal</TD><TD>average</TD><TD>interpolated</TD><TD>trend</TD><TD>#days</TD></TR></TBODY>
<TBODY><TR><TD>1959</TD><TD>1</TD><TD>1959.042</TD><TD>315.62</TD><TD>315.62</TD><TD>315.70</TD><TD>-1</TD></TR></TBODY>
<TBODY><TR><TD>1959</TD><TD>2</TD><TD>1959.125</TD><TD>316.38</TD><TD>316.38</TD><TD>315.88</TD><TD>-1</TD></TR></TBODY>
<TBODY><TR><TD>1959</TD><TD>3</TD><TD>1959.208</TD><TD>316.71</TD><TD>316.71</TD><TD>315.62</TD><TD>-1</TD></TR></TBODY>
<TBODY><TR><TD>1959</TD><TD>4</TD><TD>1959.292</TD><TD>317.72</TD><TD>317.72</TD><TD>315.56</TD><TD>-1</TD></TR></TBODY>
<TBODY><TR><TD>1959</TD><TD>5</TD><TD>1959.375</TD><TD>318.29</TD><TD>318.29</TD><TD>315.50</TD><TD>-1</TD></TR></TBODY>
<TBODY><TR><TD>1959</TD><TD>6</TD><TD>1959.458</TD><TD>318.15</TD><TD>318.15</TD><TD>315.92</TD><TD>-1</TD></TR></TBODY>
<TBODY><TR><TD>1959</TD><TD>7</TD><TD>1959.542</TD><TD>316.54</TD><TD>316.54</TD><TD>315.66</TD><TD>-1</TD></TR></TBODY>
<TBODY><TR><TD>1959</TD><TD>8</TD><TD>1959.625</TD><TD>314.80</TD><TD>314.80</TD><TD>315.81</TD><TD>-1</TD></TR></TBODY>
<TBODY><TR><TD>1959</TD><TD>9</TD><TD>1959.708</TD><TD>313.84</TD><TD>313.84</TD><TD>316.55</TD><TD>-1</TD></TR></TBODY>
<TBODY><TR><TD>1959</TD><TD>10</TD><TD>1959.792</TD><TD>313.26</TD><TD>313.26</TD><TD>316.19</TD><TD>-1</TD></TR></TBODY>
<TBODY><TR><TD>1959</TD><TD>11</TD><TD>1959.875</TD><TD>314.80</TD><TD>314.80</TD><TD>316.78</TD><TD>-1</TD></TR></TBODY>
<TBODY><TR><TD># Total carbon emissions </TD></TR></TBODY>
<TBODY><TR><TD># (million metric tons of C)</TD></TR></TBODY>
<TBODY><TR><TD>year</TD><TD>month</TD><TD>decimal</TD><TD>average</TD><TD>interpolated</TD><TD>trend</TD><TD>#days</TD></TR></TBODY>
<TBODY><TR><TD>1959</TD><TD>1</TD><TD>1959.042</TD><TD>315.62</TD><TD>315.62</TD><TD>315.70</TD><TD>-1</TD></TR></TBODY>
<TBODY><TR><TD>1959</TD><TD>2</TD><TD>1959.125</TD><TD>316.38</TD><TD>316.38</TD><TD>315.88</TD><TD>-1</TD></TR></TBODY>
<TBODY><TR><TD>1959</TD><TD>3</TD><TD>1959.208</TD><TD>316.71</TD><TD>316.71</TD><TD>315.62</TD><TD>-1</TD></TR></TBODY>
<TBODY><TR><TD>1959</TD><TD>4</TD><TD>1959.292</TD><TD>317.72</TD><TD>317.72</TD><TD>315.56</TD><TD>-1</TD></TR></TBODY>
<TBODY><TR><TD>1959</TD><TD>5</TD><TD>1959.375</TD><TD>318.29</TD><TD>318.29</TD><TD>315.50</TD><TD>-1</TD></TR></TBODY>
<TBODY><TR><TD>1959</TD><TD>6</TD><TD>1959.458</TD><TD>318.15</TD><TD>318.15</TD><TD>315.92</TD><TD>-1</TD></TR></TBODY>
<TBODY><TR><TD>1959</TD><TD>7</TD><TD>1959.542</TD><TD>316.54</TD><TD>316.54</TD><TD>315.66</TD><TD>-1</TD></TR></TBODY>
<TBODY><TR><TD>1959</TD><TD>8</TD><TD>1959.625</TD><TD>314.80</TD><TD>314.80</TD><TD>315.81</TD><TD>-1</TD></TR></TBODY>
<TBODY><TR><TD>1959</TD><TD>9</TD><TD>1959.708</TD><TD>313.84</TD><TD>313.84</TD><TD>316.55</TD><TD>-1</TD></TR></TBODY>
<TBODY><TR><TD>1959</TD><TD>10</TD><TD>1959.792</TD><TD>313.26</TD><TD>313.26</TD><TD>316.19</TD><TD>-1</TD></TR></TBODY>
<TBODY><TR><TD>1959</TD><TD>11</TD><TD>1959.875</TD><TD>314.80</TD><TD>314.80</TD><TD>316.78</TD><TD>-1</TD></TR></TBODY>
...
SeaLevel.csv
#title = mean sea level anomaly global ocean (66S to 66N) (Annual signals retained)
#institution = NOAA/Laboratory for Satellite Altimetry
#references = NOAA Sea Level Rise
year,TOPEX/Poseidon,Jason-1,Jason-2,Jason-3
1992.9614,-16.27000,
1992.9865,-17.97000,
1993.0123,-14.87000,
1993.0407,-19.87000,
1993.0660,-25.27000,
1993.0974,-29.37000,
1993.1206,-27.67000,
1993.1493,-21.87000,
1993.1765,-18.97000,
1993.2037,-19.47000,
1993.2307,-22.97000,
1993.2851,-26.27000,
1993.3123,-20.07000,
1993.3394,-19.87000,
1998.8234,6.53000,
1998.8505,2.53000,
1998.8775,-4.07000,
1998.9046,-10.17000,
1998.9319,-3.97000,
1998.9591,-3.27000,
1998.9862,0.13000,
1999.0133,-4.17000,
1999.0405,-6.87000,
1999.0948,-11.17000,
1999.1256,3.73000,
1999.1491,-1.27000,
1999.1763,-6.37000,
1999.2034,-11.77000,
1999.2306,-10.37000,
1999.2577,-7.87000,
1999.2848,-5.37000,
1999.3392,-8.27000,
1999.3663,-13.77000,
2001.6738,5.43000,
2001.7010,15.73000,
2001.7283,16.73000,
2001.7553,14.93000,
2001.7825,7.73000,
2001.8096,4.03000,
2001.8368,11.63000,
2001.8639,16.53000,
2001.8918,14.53000,
2001.9182,10.93000,
2001.9454,4.73000,
2001.9725,3.63000,
2002.1083,-1.67000,6.23000,
2002.1352,6.33000,
2002.1354,-0.17000,
2002.1626,4.43000,4.93000,
2002.1897,4.93000,
2002.1898,-1.27000,
#institution = NOAA/Laboratory for Satellite Altimetry
#references = NOAA Sea Level Rise
year,TOPEX/Poseidon,Jason-1,Jason-2,Jason-3
1992.9614,-16.27000,
1992.9865,-17.97000,
1993.0123,-14.87000,
1993.0407,-19.87000,
1993.0660,-25.27000,
1993.0974,-29.37000,
1993.1206,-27.67000,
1993.1493,-21.87000,
1993.1765,-18.97000,
1993.2037,-19.47000,
1993.2307,-22.97000,
1993.2851,-26.27000,
1993.3123,-20.07000,
1993.3394,-19.87000,
1998.8234,6.53000,
1998.8505,2.53000,
1998.8775,-4.07000,
1998.9046,-10.17000,
1998.9319,-3.97000,
1998.9591,-3.27000,
1998.9862,0.13000,
1999.0133,-4.17000,
1999.0405,-6.87000,
1999.0948,-11.17000,
1999.1256,3.73000,
1999.1491,-1.27000,
1999.1763,-6.37000,
1999.2034,-11.77000,
1999.2306,-10.37000,
1999.2577,-7.87000,
1999.2848,-5.37000,
1999.3392,-8.27000,
1999.3663,-13.77000,
2001.6738,5.43000,
2001.7010,15.73000,
2001.7283,16.73000,
2001.7553,14.93000,
2001.7825,7.73000,
2001.8096,4.03000,
2001.8368,11.63000,
2001.8639,16.53000,
2001.8918,14.53000,
2001.9182,10.93000,
2001.9454,4.73000,
2001.9725,3.63000,
2002.1083,-1.67000,6.23000,
2002.1352,6.33000,
2002.1354,-0.17000,
2002.1626,4.43000,4.93000,
2002.1897,4.93000,
2002.1898,-1.27000,
...
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