Unikke Værdier

Data bliver ofte duplikeret i DataFrames. For eksempel har countries kolonnen i 'continent' DataFrame gentagne indgange. Der er en metode, der henter et array af unikke værdier fra en specifik DataFrame kolonne.

import pandas as pd

country_data = {'country' : ['Thailand', 'Philippines', 'Monaco', 'Malta', 'Sweden', 'Paraguay', 'Latvia'],

'continent' : ['Asia', 'Asia', 'Europe', 'Europe', 'Europe', 'South America', 'Europe'],

'capital':['Bangkok', 'Manila', 'Monaco', 'Valletta', 'Stockholm', 'Asuncion', 'Riga']}

countries = pd.DataFrame(country_data)

print(countries)


              1234567
            
import pandas as pd 

country_data = {'country' : ['Thailand', 'Philippines', 'Monaco', 'Malta', 'Sweden', 'Paraguay', 'Latvia'],
          'continent' : ['Asia', 'Asia', 'Europe', 'Europe', 'Europe', 'South America', 'Europe'],
          'capital':['Bangkok', 'Manila', 'Monaco', 'Valletta', 'Stockholm', 'Asuncion', 'Riga']}
countries = pd.DataFrame(country_data)
print(countries)

Nu vil vi anvende unique() metoden på 'continent' og 'country' kolonnerne:

import pandas as pd

country_data = {'country' : ['Thailand', 'Philippines', 'Monaco', 'Malta', 'Sweden', 'Paraguay', 'Latvia'],

'continent' : ['Asia', 'Asia', 'Europe', 'Europe', 'Europe', 'South America', 'Europe'],

'capital':['Bangkok', 'Manila', 'Monaco', 'Valletta', 'Stockholm', 'Asuncion', 'Riga']}

countries = pd.DataFrame(country_data)

unique_countries = countries['country'].unique()

unique_continents = countries['continent'].unique()

print(unique_countries)

print(unique_continents)


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import pandas as pd

country_data = {'country' : ['Thailand', 'Philippines', 'Monaco', 'Malta', 'Sweden', 'Paraguay', 'Latvia'],
          'continent' : ['Asia', 'Asia', 'Europe', 'Europe', 'Europe', 'South America', 'Europe'],
          'capital':['Bangkok', 'Manila', 'Monaco', 'Valletta', 'Stockholm', 'Asuncion', 'Riga']}
countries = pd.DataFrame(country_data)
unique_countries = countries['country'].unique()
unique_continents = countries['continent'].unique()
print(unique_countries)
print(unique_continents)

For at tælle antallet af unikke værdier i en specifik kolonne, kan du bruge nunique() metoden:

import pandas as pd

country_data = {'country' : ['Thailand', 'Philippines', 'Monaco', 'Malta', 'Sweden', 'Paraguay', 'Latvia'],

'continent' : ['Asia', 'Asia', 'Europe', 'Europe', 'Europe', 'South America', 'Europe'],

'capital':['Bangkok', 'Manila', 'Monaco', 'Valletta', 'Stockholm', 'Asuncion', 'Riga']}

countries = pd.DataFrame(country_data)

print(countries['continent'].nunique())


              1234567
            
import pandas as pd

country_data = {'country' : ['Thailand', 'Philippines', 'Monaco', 'Malta', 'Sweden', 'Paraguay', 'Latvia'],
          'continent' : ['Asia', 'Asia', 'Europe', 'Europe', 'Europe', 'South America', 'Europe'],
          'capital':['Bangkok', 'Manila', 'Monaco', 'Valletta', 'Stockholm', 'Asuncion', 'Riga']}
countries = pd.DataFrame(country_data)
print(countries['continent'].nunique())

Opgave

Swipe to start coding

Du har fået en DataFrame ved navn audi_cars.

Identificer alle unikke værdier i 'year' kolonnen og gem resultatet i unique_years kolonnen.
Identificer alle unikke værdier i 'fueltype' kolonnen og gem resultatet i unique_fueltype variablen.
Bestem antallet af unikke brændstoftyper og gem resultatet i count_unique_fueltypes variablen.

Løsning

import pandas as pd

cars_data = {'model': ['audi A1', 'audi A6', 'audi A4', 'audi A3','audi A1'],

'year': [2017, 2016, 2017, 2019, 2016],

'fueltype': ['petrol', 'diesel', 'diesel', 'petrol', 'petrol'],

'capital': ['Manila', 'Monaco', 'Bangkok', 'Stockhol', 'Valletta']}

audi_cars = pd.DataFrame(cars_data)

# Write your code below

unique_years = audi_cars['year'].unique()

unique_fueltype = audi_cars['fueltype'].unique()

count_unique_fueltypes = audi_cars['fueltype'].nunique()

# Testing the result

print(unique_years)

print(unique_fueltype)

print(count_unique_fueltypes)

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Sektion 3. Kapitel 15

import pandas as pd

cars_data = {'model': ['audi A1', 'audi A6', 'audi A4', 'audi A3','audi A1'],

'year': [2017, 2016, 2017, 2019, 2016],

'fueltype': ['petrol', 'diesel', 'diesel', 'petrol', 'petrol'],

'capital': ['Manila', 'Monaco', 'Bangkok', 'Stockhol', 'Valletta']}

audi_cars = pd.DataFrame(cars_data)

# Write your code below

unique_years = ___

unique_fueltype = ___

count_unique_fueltypes = ___

# Testing the result

print(unique_years)

print(unique_fueltype)

print(count_unique_fueltypes)

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