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Lernen Renaming Columns | s1
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Track DA with Py - Data Manipulation with pandas
Abschnitt 1. Kapitel 38
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bookRenaming Columns

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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.

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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) data.rename(columns = {'Survived': 'Survived_Passenger'}, inplace = True) print(data.columns)
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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'.

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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.

Lösung

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Abschnitt 1. Kapitel 38
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