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.
1234import 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)
Explanation:
.rename(columns = {'Survived': 'Survived_Passenger'}, inplace = True)
.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'.
Swipe to start coding
Your task here is to:
- Rename the column
'Fare'to'Fare_fixed'. Use theinplace = Trueargument. - Output all column names of the
datadataset.
Solución
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Completion rate improved to 3.03Renaming 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.
1234import 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)
Explanation:
.rename(columns = {'Survived': 'Survived_Passenger'}, inplace = True)
.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'.
Swipe to start coding
Your task here is to:
- Rename the column
'Fare'to'Fare_fixed'. Use theinplace = Trueargument. - Output all column names of the
datadataset.
Solución
Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones¡Gracias por tus comentarios!
single
Awesome!
Completion rate improved to 3.03Renaming the Column
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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.
1234import 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)
Explanation:
.rename(columns = {'Survived': 'Survived_Passenger'}, inplace = True)
.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'.
Swipe to start coding
Your task here is to:
- Rename the column
'Fare'to'Fare_fixed'. Use theinplace = Trueargument. - Output all column names of the
datadataset.
Solución
Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones¡Gracias por tus comentarios!
