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Renaming the Column | Preprocessing Data
Advanced Techniques in pandas
course content

Contenido del Curso

Advanced Techniques in pandas

Advanced Techniques in pandas

1. Getting Familiar With Indexing and Selecting Data
2. Dealing With Conditions
3. Extracting Data
4. Aggregating Data
5. Preprocessing Data

bookRenaming 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'.

Tarea

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.

Switch to desktopCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
¿Todo estuvo claro?

¿Cómo podemos mejorarlo?

¡Gracias por tus comentarios!

Sección 5. Capítulo 9
toggle bottom row

bookRenaming 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'.

Tarea

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.

Switch to desktopCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
¿Todo estuvo claro?

¿Cómo podemos mejorarlo?

¡Gracias por tus comentarios!

Sección 5. Capítulo 9
toggle bottom row

bookRenaming 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'.

Tarea

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.

Switch to desktopCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
¿Todo estuvo claro?

¿Cómo podemos mejorarlo?

¡Gracias por tus comentarios!

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'.

Tarea

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.

Switch to desktopCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
Sección 5. Capítulo 9
Switch to desktopCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
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