Contenido del Curso
Advanced Techniques in pandas
Advanced Techniques in pandas
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.
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)
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'
.
Swipe to show code editor
Your task here is to:
- Rename the column
'Fare'
to'Fare_fixed'
. Use theinplace = True
argument. - Output all column names of the
data
dataset.
¡Gracias por tus comentarios!
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.
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)
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'
.
Swipe to show code editor
Your task here is to:
- Rename the column
'Fare'
to'Fare_fixed'
. Use theinplace = True
argument. - Output all column names of the
data
dataset.
¡Gracias por tus comentarios!
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.
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)
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'
.
Swipe to show code editor
Your task here is to:
- Rename the column
'Fare'
to'Fare_fixed'
. Use theinplace = True
argument. - Output all column names of the
data
dataset.
¡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.
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)
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'
.
Swipe to show code editor
Your task here is to:
- Rename the column
'Fare'
to'Fare_fixed'
. Use theinplace = True
argument. - Output all column names of the
data
dataset.