hawaii_co2.md

Hawaii CO2 plot

Exercise 1 (data manipulation)

• Navigate to https://www.esrl.noaa.gov/gmd/ccgg/trends/data.html.
• Download Mauna Loa CO2 monthly mean data
• Write some Python to divide the data into CSV files for each decade, each containing just decimal date and the average value for each month.

Useful modules include csv, datetime, pandas

Example output

Names:

co2_mm_1960s.csv
co2_mm_1970s.csv
co2_mm_1980s.csv
co2_mm_1990s.csv
etc...

Contents:

decimal_date,interpolated
1958.208,315.71
1958.292,317.45
1958.375,317.50
1958.458,317.10
1958.542,315.86
1958.625,314.93
1958.708,313.20
1958.792,312.66

Exercise 2 (plotting)

Recreate the following plot using Pandas and Matplotlib.

The following code will load the data into a Pandas dataframe:

df = pd.read_csv('co2_mm_mlo.txt', 
                 comment='#', 
                 sep="\s+", 
                 header=None, 
                 index_col=1, 
                 names=names, 
                 na_values=[-99.99, -1], 
                 parse_dates={'date':[0, 1]}
                 )

Features to recreate:

• 'average' column plotted in red
• 'trend' column plotted in black (behind the red)
• Axis labels
• Title
• "Scripps Institution..." text box
• "April 2019" text box
• Axis minor ticks
• Embedded images

Bonus extra features:

• Legend
• 5-year running maximum line
• 5-year running minimum line