Ctrl+K

Home assignment 2

Home assignment 2#

Last updated: 2024-02-24 18:05:18

Question 1#

  • Read the DEM of the Carmel in 'carmel.csv' into an ndarray object.

  • Calculate how many cells/pixels are in each of 100-m elevation “bins” starting with -100 and ending with 600 meters, i.e., -100-0, 0-100, …, 500-600.

  • The counts need to include the start point but not the end point, i.e., the first bin is \(-100 ≤ x < 0\), the second bin is \(0 ≤ x < 100\), and so on.

  • Store the results in a dictionary, with the dictionary keys being the bin labels, and dictionary values being the pixel counts.

  • Print the dictionary.

{'-100 - 0': 380,
 '0 - 100': 80438,
 '100 - 200': 40877,
 '200 - 300': 20841,
 '300 - 400': 8998,
 '400 - 500': 5116,
 '500 - 600': 476}

Question 2#

  • Read the 'world_cities.csv' file into a DataFrame object.

  • Calculate a new column named 'pop_M' (population in millions), by transforming the 'pop' (population) column.

  • Remove the original 'pop' column.

  • Choose a city that starts with the same English letter as your first name (for example, 'Mexico City' if your first name is Michael).

  • Subset the six biggest (i.e., largest population sizes) cities from the country where your selected city is. (Do not use the country name string in the code; use an expression which returns it.)

  • Print the result.

city country lat lon capital pop_M
23660 Mexico City Mexico 19.43 -99.14 1 8.659409
10135 Ecatepec Mexico 19.60 -99.05 0 1.844447
13180 Guadalajara Mexico 20.67 -103.35 0 1.637213
16484 Juarez Mexico 31.74 -106.49 0 1.449006
38138 Tijuana Mexico 32.53 -117.02 0 1.427118
30002 Puebla Mexico 19.05 -98.22 0 1.416551
Contents