Question
It is a PYTHON program. Thank you Wildfire frequency and size has had devastating impacts on the state of California in recent years. There's a
It is a PYTHON program. Thank you
Wildfire frequency and size has had devastating impacts on the state of California in recent years.
There's a wealth of data available which can be downloaded and analyzed. A useful dataset from the USGS includes data for every reported fire from 1950 to 2017, which I've copied here: calfire_frap.csv.
Import this dataset and create a plot that displays how many fires were reported each year that was reported. Add an additional line (on the same chart) that displays only fires that were over 500 acres in size (the column "gis_acres" is the size of the fire). Use different colors, markers and line styles for each series. Add appropriate chart and axes titles, and a legend.
Output each year and associated number of fires over 500 acres to a csv file.
Hint: loading the data using a pandas dataframe first, then converting columns of interest to arrays is probably easiest. You can convert a column of pandas data to a numpy array using:
myArray = myDataframe['columnName'].to_numpy()
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