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Leer Renaming the Column | Preprocessing Data
Advanced Techniques in pandas

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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.

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)
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)
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Explanation:

python
.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'.

Taak

Swipe to start coding

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.

Oplossing

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)

# Rename the column
data.rename(columns = {'Fare': 'Fare_fixed'}, inplace = True)
# Output the name of all columns
print(data.columns)

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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)

# Rename the column
data.___(columns = {___}, ___ = ___)
# Output the name of all columns
print(___)

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