Data
CDP-Challenge-Cities-KPI

CDP-Challenge-Cities-KPI

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Context This dataset is generated after an epxloratory analysis of data provided by Carbon Disclosure Project in the following competition: CDP: Unlocking Climate Solutions. It contains a compilation of indicators extracted and calculated based on cities' reponses to CDP disclosure for the year of 2020. Content Governance Data Management Sustainability.Targets.Master.Planning (Question 1.0): Cities report if they incorporate sustainability goals and targets into the master planning Climate hazards and vulnerability Risk.Assessment.Actions (Question 2.0): Cities report if a climate change risk or vulnerability assessment been undertaken Nb.Hazards.Type (Question 2.1): Counting the number of reported hazards by organization Hazards.Exposure.Level (Question 2.1): The weighted sum of reported hazards and porbability Adaptation.Challenges.Economic (Question 2.2): Number of reported significant adaptation challenges related to economic sector Adaptation.Challenges.Health (Question 2.2): Number of reported significant adaptation challenges related to health sector Adaptation.Challenges.Education (Question 2.2): Number of reported significant adaptation challenges related to education sector Adaptation.Challenges.Habitat (Question 2.2): Number of reported significant adaptation challenges related to habitation sector Adaptation.Challenges.Infrastructure (Question 2.2): Number of reported significant adaptation challenges related to infrastructure Adaptation.Challenges.Social (Question 2.2): Number of reported significant adaptation challenges related to social issues Adaptation.Challenges.Environment (Question 2.2): Number of reported significant adaptation challenges related to environmental issues Adaptation.Challenges.Governance (Question 2.2): Number of reported significant adaptation challenges related to governance Adaptation.Challenges.Level (Question 2.2): Sum of reported significant adaptation challenges Risk.Health.System (Question 2.3): Cities indicate if they face risks to public health systems associated with climate change Adaptation Nb.Adaptations.Actions (Question 3.0): Number of reported adaptation actions cities are taking to reduce the risk to climate change hazards Adaptation.Plan (Question 3.2): Cities indicating if they have a published plan that addresses climate change adaptation City-wide emissions City.Wide.Emissions.Inventory (Question 4.0): Answering if they have a city-wide emissions inventory to report GHG.Emissions.Primary.protocol (Question 4.3): The name of the primary protocol, standard, or methodology you have used to calculate your citys city-wide GHG emissions GHG.Emissions.Evolution (Question 4.8): Indication if the city-wide emissions have increased, decreased, or stayed the same since the last emissions inventory GHG.Emissions.Consumption (Question 4.9): Indication if the city-wide emissions have increased, decreased, or stayed the same since the last emissions inventory GHG.Emissions.External.Verification (Question 4.12): Indication if the GHG emissions data heve been externally verified or audited Emission reduction GHG.Emissions.Reductions.Targets (Question 5.0):Cities are reporting if they have a GHG emissions reduction target(s) in place at the city-wide level Emissions.Reductions.Mitigation.Planning (Question 5.5):Cities are reporting if they have a climate change mitigation or energy access plan for reducing city-wide GHG emissions Opportunities Opportunities.Collaboration (Question 6.2):Cities are reporting if they collaborate in partnership with businesses on sustainability projects Energy Renewable.Energy.Target (Question 8.0):Cities are reporting if they have a renewable energy or electricity target Electricity.Source.Renewable (Question 8.1): Percent of renewable source mix of eleictricity consumed in the city Energy.Efficnecy.Target (Question 8.5): Cities are reporting if they have a target to increase energy efficiency Transport Transport.Mode.Passenger.Private.motorized (Question 10.1): Percent of private motorized transport mode in city passenger transport Transport.Mode.Passenger.Walking (Question 10.1): Percent of walking transport mode in city passenger transport Transport.Mode.Passenger.Public (Question 10.1): Percent of public transport mode in city passenger transport Transport.Mode.Passenger.Cycling (Question 10.1): Percent of cycling transport mode in city passenger transport Transport.Mode.Passenger.Other (Question 10.1): Percent of other transport mode in city passenger transport Low.Zero.Emission.Zone (Question 10.7): Cities are reporting if they have a low or zero-emission zone Food Food.Consumption.Policies (Question 12.3): Cities are reporting if they have any policies relating to food consumption Water security Potable.Water.Supply.Percent (Question 14.1): Percentage of city's population having potable water supply service Potable.Water.Supply.Percent (Question 14.4): Cities are reporting if they have have a publicly available Water Resource Management strategy Acknowledgements This dataset is generated by this notebook: https://www.kaggle.com/shabou/exploratory-analysis-of-cities-responses This datset is based on dataset provded by CDP challenge: https://www.kaggle.com/c/cdp-unlocking-climate-solutions Inspiration Multivariate analysis of cities' KPIs Cities culstering based on the proposed KPIs

58 features

Unnamed:_0numeric615 unique values
0 missing
Year.Reported.to.CDPnumeric1 unique values
0 missing
Account.Numbernumeric566 unique values
0 missing
Organizationstring566 unique values
0 missing
Citystring447 unique values
125 missing
Countrystring75 unique values
0 missing
CDP.Regionstring8 unique values
0 missing
First.Time.Discloserstring2 unique values
0 missing
Populationnumeric564 unique values
1 missing
City.Locationstring407 unique values
170 missing
Sustainability.Targets.Master.Planningstring5 unique values
10 missing
Risk.Assessment.Actionsstring5 unique values
7 missing
Nb.Hazards.Typenumeric21 unique values
30 missing
Hazards.Exposure.Levelnumeric156 unique values
42 missing
Adaptation.Challenges.Healthnumeric3 unique values
421 missing
Adaptation.Challenges.Economicnumeric4 unique values
421 missing
Adaptation.Challenges.Environmentnumeric4 unique values
421 missing
Adaptation.Challenges.Infrastructurenumeric4 unique values
421 missing
Adaptation.Challenges.Socialnumeric3 unique values
421 missing
Adaptation.Challenges.Governancenumeric4 unique values
421 missing
Adaptation.Challenges.Educationnumeric2 unique values
421 missing
Adaptation.Challenges.Levelnumeric8 unique values
421 missing
Risk.Health.Systemstring3 unique values
141 missing
Nb.Adaptation.Actionsnumeric26 unique values
0 missing
Adaptation.Planstring5 unique values
25 missing
City.Wide.Emissions.Inventorystring4 unique values
16 missing
GHG.Emissions.Primary.protocolstring6 unique values
152 missing
GHG.Emissions.Evolutionstring5 unique values
215 missing
GHG.Emissions.Consumptionstring5 unique values
222 missing
GHG.Emissions.External.Verificationstring5 unique values
195 missing
GHG.Emissions.Reductions.Targetsstring5 unique values
29 missing
Emissions.Reductions.Mitigation.Planningstring5 unique values
47 missing
Opportunities.Collaborationstring5 unique values
51 missing
Renewable.Energy.Targetstring5 unique values
39 missing
Electricity.Source.Biomassnumeric106 unique values
224 missing
Electricity.Source.Coalnumeric179 unique values
208 missing
Electricity.Source.Gasnumeric202 unique values
189 missing
Electricity.Source.Geothermalnumeric42 unique values
240 missing
Electricity.Source.Hydronumeric171 unique values
185 missing
Electricity.Source.Nuclearnumeric128 unique values
218 missing
Electricity.Source.Oilnumeric104 unique values
216 missing
Electricity.Source.Othernumeric117 unique values
232 missing
Electricity.Source.Solarnumeric119 unique values
210 missing
Electricity.Source.Windnumeric141 unique values
213 missing
Electricity.Source.Renewablenumeric201 unique values
254 missing
Energy.Efficnecy.Targetstring5 unique values
163 missing
Transport.Mode.Passenger.Publicnumeric144 unique values
350 missing
Transport.Mode.Passenger.Cyclingnumeric91 unique values
373 missing
Transport.Mode.Passenger.Othernumeric110 unique values
379 missing
Transport.Mode.Passenger.Private.motorizednumeric152 unique values
359 missing
Transport.Mode.Passenger.Walkingnumeric122 unique values
370 missing
Low.Zero.Emission.Zonestring3 unique values
72 missing
Food.Consumption.Policiesstring3 unique values
95 missing
Potable.Water.Supply.Percentnumeric71 unique values
95 missing
Water.Resource.Management.strategystring4 unique values
82 missing
latnumeric542 unique values
0 missing
longnumeric542 unique values
0 missing
Country.Code.3string75 unique values
0 missing

19 properties

615
Number of instances (rows) of the dataset.
58
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
9612
Number of missing values in the dataset.
567
Number of instances with at least one value missing.
34
Number of numeric attributes.
0
Number of nominal attributes.
0
Percentage of binary attributes.
92.2
Percentage of instances having missing values.
26.95
Percentage of missing values.
Average class difference between consecutive instances.
58.62
Percentage of numeric attributes.
0.09
Number of attributes divided by the number of instances.
0
Percentage of nominal attributes.
Percentage of instances belonging to the most frequent class.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.

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