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Pandas First Steps
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Pandas First Steps

Pandas First Steps

1. The Very First Steps
What is pandas? SeriesCreating a SeriesDataFrameSeries QuizCreating a DataFrame QuizAdding a New ColumnInserting a New ColumnDeleting a Row/Column Matching the FunctionsWorking with ColumnsExtracting Columns Quiziloc BasicsUsing iloc
2. Reading Files in Pandas
CSV FilesTXT FilesWorking with Files QuizAccessing the Columns
3. Analyzing the Data
Viewing the DataHead QuizHead and Tail QuizInformation on the DataColumn Names and Data TypesFinding Null ValuesIdentifying Null Values QuizDropping Null ValuesFilling Null ValuesNull Values QuizDescribing the DataCalculating Descriptive Statisticsmax() and min()Statistical Operations Quizsum() and count()Unique Values

Unique Values

Data often gets duplicated in DataFrames. For instance, in our countries DataFrame, the continent column has repeated entries. There's a function that retrieves an array of distinct values from a specific DataFrame column. Let's revisit this DataFrame.


              
1234567

            
import pandas as pd 

dataset = {'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(dataset)
print(countries)
copy

Now, let's apply the unique() method to the 'continent' and 'country' columns.


              
12345678910

            
import pandas as pd

dataset = {'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(dataset)
unique_countries = countries['country'].unique()
unique_continents = countries['continent'].unique()
print(unique_countries)
print(unique_continents)
copy

Tarefa

Given the audi_cars DataFrame, please identify all distinct values in the 'year' and 'fueltype' columns.

Tarefa

Given the audi_cars DataFrame, please identify all distinct values in the 'year' and 'fueltype' columns.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?

Seção 3. Capítulo 16
toggle bottom row

Unique Values

Data often gets duplicated in DataFrames. For instance, in our countries DataFrame, the continent column has repeated entries. There's a function that retrieves an array of distinct values from a specific DataFrame column. Let's revisit this DataFrame.


              
1234567

            
import pandas as pd 

dataset = {'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(dataset)
print(countries)
copy

Now, let's apply the unique() method to the 'continent' and 'country' columns.


              
12345678910

            
import pandas as pd

dataset = {'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(dataset)
unique_countries = countries['country'].unique()
unique_continents = countries['continent'].unique()
print(unique_countries)
print(unique_continents)
copy

Tarefa

Given the audi_cars DataFrame, please identify all distinct values in the 'year' and 'fueltype' columns.

Tarefa

Given the audi_cars DataFrame, please identify all distinct values in the 'year' and 'fueltype' columns.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?

Seção 3. Capítulo 16
toggle bottom row

Unique Values

Data often gets duplicated in DataFrames. For instance, in our countries DataFrame, the continent column has repeated entries. There's a function that retrieves an array of distinct values from a specific DataFrame column. Let's revisit this DataFrame.


              
1234567

            
import pandas as pd 

dataset = {'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(dataset)
print(countries)
copy

Now, let's apply the unique() method to the 'continent' and 'country' columns.


              
12345678910

            
import pandas as pd

dataset = {'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(dataset)
unique_countries = countries['country'].unique()
unique_continents = countries['continent'].unique()
print(unique_countries)
print(unique_continents)
copy

Tarefa

Given the audi_cars DataFrame, please identify all distinct values in the 'year' and 'fueltype' columns.

Tarefa

Given the audi_cars DataFrame, please identify all distinct values in the 'year' and 'fueltype' columns.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?

Data often gets duplicated in DataFrames. For instance, in our countries DataFrame, the continent column has repeated entries. There's a function that retrieves an array of distinct values from a specific DataFrame column. Let's revisit this DataFrame.


              
1234567

            
import pandas as pd 

dataset = {'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(dataset)
print(countries)
copy

Now, let's apply the unique() method to the 'continent' and 'country' columns.


              
12345678910

            
import pandas as pd

dataset = {'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(dataset)
unique_countries = countries['country'].unique()
unique_continents = countries['continent'].unique()
print(unique_countries)
print(unique_continents)
copy

Tarefa

Given the audi_cars DataFrame, please identify all distinct values in the 'year' and 'fueltype' columns.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Seção 3. Capítulo 16
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
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