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Advanced Techniques in pandas
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Advanced Techniques in pandas

Advanced Techniques in pandas

1. Getting Familiar With Indexing and Selecting Data
Outputting Columns by TitleOutputting Rows by IndexSelecting Specific Rows and ColumnsLearning More About IndexationGetting Familiar With lambda FunctionsExpanding Functionality of the .iloc[] Attribute
2. Dealing With Conditions
Setting ConditionSelecting Data Based on ConditionDealing With Several ConditionsMaking Your Code BeautifulConditions Quiz
3. Extracting Data
Is Data in ...?Combining Your KnowledgeBetween MethodExtracting Specific DataFinding the Smallest Values of a ColumnFinding the Largest Values of a ColumnFinding the Correlation
4. Aggregating Data
Getting Familiar With the .groupby() MethodGrouping by Several ColumnsComplicated GroupingAdvanced GroupingDealing With Pivot TablesCreating a Pivot Table
5. Preprocessing Data
Checking for Missing ValuesCalculating the Number of Missing ValuesWhat Will We Do With the NaN Values?How to Delete Only NaN Values?Filling In the Missing ValuesManaging Categorical VariablesChecking the Column TypeManaging an Incorrect ColumnRenaming the Column

Renaming the Column

In the previous chapter, you dealt with the incorrect values in a column. It is an excellent time to fix any changes. In our case, we can rename the column to pin that it was changed.

To rename a column, use the .rename() method. Look at the example where we will rename the column 'Survived', and then output the column names.


              
1234

            
import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/titanic4.csv', index_col = 0)
data.rename(columns = {'Survived': 'Survived_Passenger'}, inplace = True)
print(data.columns)
copy

Explanation:

  • .rename() - a method that we apply to the dataset to rename columns name;
  • columns = {'Survived': 'Survived_Passenger'} - in the curly brackets, you specify all columns and their new names. In this case, we renamed just one column, but you can put several of them here separated by commas.

.columns - an attribute that outputs the column names. In our case, we can no longer see the column name 'Survived'.

Tarefa

Your task here is to:

  1. Rename the column 'Fare' to 'Fare_fixed'. Use the inplace = True argument.
  2. Output all column names of the data dataset.

Tarefa

Your task here is to:

  1. Rename the column 'Fare' to 'Fare_fixed'. Use the inplace = True argument.
  2. Output all column names of the data dataset.

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Seção 5. Capítulo 9
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Renaming the Column

In the previous chapter, you dealt with the incorrect values in a column. It is an excellent time to fix any changes. In our case, we can rename the column to pin that it was changed.

To rename a column, use the .rename() method. Look at the example where we will rename the column 'Survived', and then output the column names.


              
1234

            
import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/titanic4.csv', index_col = 0)
data.rename(columns = {'Survived': 'Survived_Passenger'}, inplace = True)
print(data.columns)
copy

Explanation:

  • .rename() - a method that we apply to the dataset to rename columns name;
  • columns = {'Survived': 'Survived_Passenger'} - in the curly brackets, you specify all columns and their new names. In this case, we renamed just one column, but you can put several of them here separated by commas.

.columns - an attribute that outputs the column names. In our case, we can no longer see the column name 'Survived'.

Tarefa

Your task here is to:

  1. Rename the column 'Fare' to 'Fare_fixed'. Use the inplace = True argument.
  2. Output all column names of the data dataset.

Tarefa

Your task here is to:

  1. Rename the column 'Fare' to 'Fare_fixed'. Use the inplace = True argument.
  2. Output all column names of the data dataset.

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

Tudo estava claro?

Seção 5. Capítulo 9
toggle bottom row

Renaming the Column

In the previous chapter, you dealt with the incorrect values in a column. It is an excellent time to fix any changes. In our case, we can rename the column to pin that it was changed.

To rename a column, use the .rename() method. Look at the example where we will rename the column 'Survived', and then output the column names.


              
1234

            
import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/titanic4.csv', index_col = 0)
data.rename(columns = {'Survived': 'Survived_Passenger'}, inplace = True)
print(data.columns)
copy

Explanation:

  • .rename() - a method that we apply to the dataset to rename columns name;
  • columns = {'Survived': 'Survived_Passenger'} - in the curly brackets, you specify all columns and their new names. In this case, we renamed just one column, but you can put several of them here separated by commas.

.columns - an attribute that outputs the column names. In our case, we can no longer see the column name 'Survived'.

Tarefa

Your task here is to:

  1. Rename the column 'Fare' to 'Fare_fixed'. Use the inplace = True argument.
  2. Output all column names of the data dataset.

Tarefa

Your task here is to:

  1. Rename the column 'Fare' to 'Fare_fixed'. Use the inplace = True argument.
  2. Output all column names of the data dataset.

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

Tudo estava claro?

In the previous chapter, you dealt with the incorrect values in a column. It is an excellent time to fix any changes. In our case, we can rename the column to pin that it was changed.

To rename a column, use the .rename() method. Look at the example where we will rename the column 'Survived', and then output the column names.


              
1234

            
import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/titanic4.csv', index_col = 0)
data.rename(columns = {'Survived': 'Survived_Passenger'}, inplace = True)
print(data.columns)
copy

Explanation:

  • .rename() - a method that we apply to the dataset to rename columns name;
  • columns = {'Survived': 'Survived_Passenger'} - in the curly brackets, you specify all columns and their new names. In this case, we renamed just one column, but you can put several of them here separated by commas.

.columns - an attribute that outputs the column names. In our case, we can no longer see the column name 'Survived'.

Tarefa

Your task here is to:

  1. Rename the column 'Fare' to 'Fare_fixed'. Use the inplace = True argument.
  2. Output all column names of the data dataset.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Seção 5. Capítulo 9
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
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