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Competition - City Tree Species

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💾 The data

The team has provided access to the 2015 tree census and geographical information on New York City neighborhoods (trees, neighborhoods):

Tree Census
  • "tree_id" - Unique id of each tree.
  • "tree_dbh" - The diameter of the tree in inches measured at 54 inches above the ground.
  • "curb_loc" - Location of the tree bed in relation to the curb. Either along the curb (OnCurb) or offset from the curb (OffsetFromCurb).
  • "spc_common" - Common name for the species.
  • "status" - Indicates whether the tree is alive or standing dead.
  • "health" - Indication of the tree's health (Good, Fair, and Poor).
  • "root_stone" - Indicates the presence of a root problem caused by paving stones in the tree bed.
  • "root_grate" - Indicates the presence of a root problem caused by metal grates in the tree bed.
  • "root_other" - Indicates the presence of other root problems.
  • "trunk_wire" - Indicates the presence of a trunk problem caused by wires or rope wrapped around the trunk.
  • "trnk_light" - Indicates the presence of a trunk problem caused by lighting installed on the tree.
  • "trnk_other" - Indicates the presence of other trunk problems.
  • "brch_light" - Indicates the presence of a branch problem caused by lights or wires in the branches.
  • "brch_shoe" - Indicates the presence of a branch problem caused by shoes in the branches.
  • "brch_other" - Indicates the presence of other branch problems.
  • "postcode" - Five-digit zip code where the tree is located.
  • "nta" - Neighborhood Tabulation Area (NTA) code from the 2010 US Census for the tree.
  • "nta_name" - Neighborhood name.
  • "latitude" - Latitude of the tree, in decimal degrees.
  • "longitude" - Longitude of the tree, in decimal degrees.
Neighborhoods' geographical information
  • "ntacode" - NTA code (matches Tree Census information).
  • "ntaname" - Neighborhood name (matches Tree Census information).
  • "geometry" - Polygon that defines the neighborhood.

Tree census and neighborhood information from the City of New York NYC Open Data.

Which tree species should the city plant?

📖 Background

You work for a nonprofit organization advising the planning department on ways to improve the quantity and quality of trees in New York City. The urban design team believes tree size (using trunk diameter as a proxy for size) and health are the most desirable characteristics of city trees.

The city would like to learn more about which tree species are the best choice to plant on the streets of Manhattan.

import pandas as pd
import geopandas as gpd
trees = pd.read_csv('data/trees.csv')
trees
neighborhoods = gpd.read_file('data/nta.shp')
neighborhoods

💪 Challenge

Create a report that covers the following:

  • What are the most common tree species in Manhattan?
  • Which are the neighborhoods with the most trees?
  • A visualization of Manhattan's neighborhoods and tree locations.
  • What ten tree species would you recommend the city plant in the future?

What are the most common tree species in Manhattan?

Please note that the dead trees dont have a species indicated, as they have the column 'spc_common' empty.

trees[ trees['status']=='Dead'].head()

Therefore it does not make any difference to filter or not the dead trees when counting the number of trees by species.

Answer

trees['spc_common'].value_counts().head(10)

Which are the neighborhoods with the most trees?

Assuming that only the alive trees count, the folowing are the top 10 neighborhoods with the most trees

Answer

trees_alive = trees[ trees['status']=='Alive' ]
trees_alive['nta_name'].value_counts().head(10)



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