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To generate a statistical summary for each of our numerical attributes, use the Pandas DataFrame describe() function on our forestfire_df.   # TODO 1 ff_describe = display(ff_describe) todo_check([ (ff_describe.shape == (8,11),'ff_describe shape did not match (8, 11)'), (np.all(np.isclose(ff_describe.values[:4,2:4].flatten(), np.array([517. ,517. ,90.64468085,110.87234043,5.52011085,64.04648225,18.7,1.1]),rtol=.01)),'The values of ff_describe were wrong!'), ])

To generate a statistical summary for each of our numerical attributes, use the Pandas DataFrame describe() function on our forestfire_df.   # TODO 1 ff_describe = display(ff_describe) todo_check([ (ff_describe.shape == (8,11),'ff_describe shape did not match (8, 11)'), (np.all(np.isclose(ff_describe.values[:4,2:4].flatten(), np.array([517. ,517. ,90.64468085,110.87234043,5.52011085,64.04648225,18.7,1.1]),rtol=.01)),'The values of ff_describe were wrong!'), ])

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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TODO 1: To generate a statistical summary for each of our numerical attributes, use the Pandas DataFrame describe() function on our forestfire_df.

 

# TODO 1
ff_describe =
display(ff_describe)

todo_check([
(ff_describe.shape == (8,11),'ff_describe shape did not match (8, 11)'),
(np.all(np.isclose(ff_describe.values[:4,2:4].flatten(), np.array([517. ,517. ,90.64468085,110.87234043,5.52011085,64.04648225,18.7,1.1]),rtol=.01)),'The values of ff_describe were wrong!'),
])
 
 
The table provides a statistical summary of data related to a dataset, likely concerning environmental or meteorological factors, as indicated by the column headers. Here is a detailed breakdown of each column: - **X and Y**: Coordinates relating to the geographical location. Each has 517 data points, with similar statistics: - Mean: X is 4.669 and Y is 4.299 - Standard Deviation (std): X is 2.314 and Y is 1.230 - Minimum: X is 1, Y is 2 - Maximum: X is 9, Y is 9 - **FFMC (Fine Fuel Moisture Code)**: Reflects moisture content of litter fuels and has 517 entries. - Mean: 90.645 - Std: 5.520 - Min: 18.7 - 25% percentile: 90.2 - 50% percentile (Median): 91.6 - 75% percentile: 92.9 - Max: 96.2 - **DMC (Duff Moisture Code)**: Indicates moisture level in loosely compacted organic layers. - Mean: 110.872 - Std: 64.046 - Min: 1.1 - **DC (Drought Code)**: Represents soil moisture affecting vegetation. - Mean: 547.940 - Std: 248.066 - Min: 7.9 - **ISI (Initial Spread Index)**: Index predicting fire spread. - Mean: 9.022 - Std: 4.559 - Min: 0.0 - **Temp (Temperature in Celsius)**: - Mean: 18.889 - Std: 5.807 - Range: 2.2 to 33.3 - **RH (Relative Humidity in percentage)**: - Mean: 44.288 - Std: 16.317 - Range: 15 to 100 - **Wind (Wind speed in km/h)**: - Mean: 4.018 - Std: 1.792 - Range: 0.4 to 9.4 - **Rain (Rain in mm)**: - Mean
Transcribed Image Text:The table provides a statistical summary of data related to a dataset, likely concerning environmental or meteorological factors, as indicated by the column headers. Here is a detailed breakdown of each column: - **X and Y**: Coordinates relating to the geographical location. Each has 517 data points, with similar statistics: - Mean: X is 4.669 and Y is 4.299 - Standard Deviation (std): X is 2.314 and Y is 1.230 - Minimum: X is 1, Y is 2 - Maximum: X is 9, Y is 9 - **FFMC (Fine Fuel Moisture Code)**: Reflects moisture content of litter fuels and has 517 entries. - Mean: 90.645 - Std: 5.520 - Min: 18.7 - 25% percentile: 90.2 - 50% percentile (Median): 91.6 - 75% percentile: 92.9 - Max: 96.2 - **DMC (Duff Moisture Code)**: Indicates moisture level in loosely compacted organic layers. - Mean: 110.872 - Std: 64.046 - Min: 1.1 - **DC (Drought Code)**: Represents soil moisture affecting vegetation. - Mean: 547.940 - Std: 248.066 - Min: 7.9 - **ISI (Initial Spread Index)**: Index predicting fire spread. - Mean: 9.022 - Std: 4.559 - Min: 0.0 - **Temp (Temperature in Celsius)**: - Mean: 18.889 - Std: 5.807 - Range: 2.2 to 33.3 - **RH (Relative Humidity in percentage)**: - Mean: 44.288 - Std: 16.317 - Range: 15 to 100 - **Wind (Wind speed in km/h)**: - Mean: 4.018 - Std: 1.792 - Range: 0.4 to 9.4 - **Rain (Rain in mm)**: - Mean
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