Inserting a New Column
We'll now explore another technique for adding a column to a DataFrame. This approach utilizes the insert() method. A key benefit of the insert() method is that it allows you to specify the position of the new column within the DataFrame.
df.insert(column_index, 'column_name', [value_1, value_2, value_3])
df: the name of the existing DataFrame;insert(): the method used for adding new columns;column_index: the position where the new column will be inserted (keep in mind that indexing starts at 0);column_name: the name for the new column;[value_1, value_2, value_3]: the values that will populate the new column.
Now we'll turn our attention to the countries DataFrame and demonstrate how to add a new column named 'population', representing the populations of countries, right after the first column ('country').
import pandas as pd countries_data = {'country' : ['Thailand', 'Philippines', 'Monaco', 'Malta', 'Sweden', 'Paraguay', 'Latvia'], 'continent' : ['Asia', 'Asia', 'Europe', 'Europe', 'Europe', 'South America', 'Europe'], 'capital':['Bangkok', 'Manila', 'Monaco', 'Valletta', 'Stockholm', 'Asuncion', 'Riga']} countries = pd.DataFrame(countries_data) countries.insert(1, 'population', [61399000, 75967000, 39244, 380200, 10380491, 5496000, 2424200]) print(countries)
Task
Swipe to start coding
You are given a list named cars_data.
- Given this list, create a
DataFramenamedaudi_cars. - Insert a column named
'price'between the'year'and'fueltype'columns and populate this column with the following values:[12500, 16500, 16800, 17300, 13900].
Solution
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