Conteúdo do Curso
Preprocessing Data
Preprocessing Data
Explore the Dataset
Before you start, it's important to take a look at the data you'll work with. There is a list of useful methods which can be applied to the pandas dataframes:
# info about the dataframe shape, data types data.info() # the size of the dataframe data.shape # list of the columns data.columns # returns all distinct values containing in the column called ColumnName data['ColumnName'].unique() # returns the metrics: mean, mode, min, max etc. data.describe() # returns top 5 rows data.head() # returns top 10 rows (or any other number you'll pass) data.head(10) # returns bottom 5 rows data.tail() # returns bottom 10 rows (or any other number) data.tail(10) # returns 10 random rows data.sample(10)
Tarefa
For given dataset data, extract and print 5 rows using sample() function.
Find all the columns' names and put them to the cols variable.
Find the unique values for each column and output these values.
Tarefa
For given dataset data, extract and print 5 rows using sample() function.
Find all the columns' names and put them to the cols variable.
Find the unique values for each column and output these values.
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixoTudo estava claro?
Explore the Dataset
Before you start, it's important to take a look at the data you'll work with. There is a list of useful methods which can be applied to the pandas dataframes:
# info about the dataframe shape, data types data.info() # the size of the dataframe data.shape # list of the columns data.columns # returns all distinct values containing in the column called ColumnName data['ColumnName'].unique() # returns the metrics: mean, mode, min, max etc. data.describe() # returns top 5 rows data.head() # returns top 10 rows (or any other number you'll pass) data.head(10) # returns bottom 5 rows data.tail() # returns bottom 10 rows (or any other number) data.tail(10) # returns 10 random rows data.sample(10)
Tarefa
For given dataset data, extract and print 5 rows using sample() function.
Find all the columns' names and put them to the cols variable.
Find the unique values for each column and output these values.
Tarefa
For given dataset data, extract and print 5 rows using sample() function.
Find all the columns' names and put them to the cols variable.
Find the unique values for each column and output these values.
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixoTudo estava claro?
Explore the Dataset
Before you start, it's important to take a look at the data you'll work with. There is a list of useful methods which can be applied to the pandas dataframes:
# info about the dataframe shape, data types data.info() # the size of the dataframe data.shape # list of the columns data.columns # returns all distinct values containing in the column called ColumnName data['ColumnName'].unique() # returns the metrics: mean, mode, min, max etc. data.describe() # returns top 5 rows data.head() # returns top 10 rows (or any other number you'll pass) data.head(10) # returns bottom 5 rows data.tail() # returns bottom 10 rows (or any other number) data.tail(10) # returns 10 random rows data.sample(10)
Tarefa
For given dataset data, extract and print 5 rows using sample() function.
Find all the columns' names and put them to the cols variable.
Find the unique values for each column and output these values.
Tarefa
For given dataset data, extract and print 5 rows using sample() function.
Find all the columns' names and put them to the cols variable.
Find the unique values for each column and output these values.
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixoTudo estava claro?
Before you start, it's important to take a look at the data you'll work with. There is a list of useful methods which can be applied to the pandas dataframes:
# info about the dataframe shape, data types data.info() # the size of the dataframe data.shape # list of the columns data.columns # returns all distinct values containing in the column called ColumnName data['ColumnName'].unique() # returns the metrics: mean, mode, min, max etc. data.describe() # returns top 5 rows data.head() # returns top 10 rows (or any other number you'll pass) data.head(10) # returns bottom 5 rows data.tail() # returns bottom 10 rows (or any other number) data.tail(10) # returns 10 random rows data.sample(10)
Tarefa
For given dataset data, extract and print 5 rows using sample() function.
Find all the columns' names and put them to the cols variable.
Find the unique values for each column and output these values.
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixoMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo