Adding a New Column

We've learned how to create a DataFrame. Now let's explore what we can do with it. First, we'll create a compact DataFrame consisting of 3 columns and 7 rows.


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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)
print(countries)

You can expand the DataFrame by adding new columns, and the most common way to do it is as follows:

dataframe is the name of our existing DataFrame to which we'll add new columns;
name_of_new_column is the name you're giving to the new column you're adding;
value_1, value_2, value_3 are the values that will populate the new column.

Note

The name of the new column should be enclosed in quotation marks and wrapped in square brackets, such as ['NewColumnName']. The values assigned to the new column should also be within square brackets, for example, data['NewColumnName'] = [value1, value2, value3]. If the values are numeric, they can be written without quotes, like [1, 2, 3]. If the values are strings, each one should be enclosed in quotes, like ['A', 'B', 'C'].

Now, we'll add a 'population' column to our pre-existing countries DataFrame.


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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['population'] = [61399000, 75967000, 39244, 380200, 10380491, 5496000, 2424200]
print(countries)

You can also use dot notation (e.g., df.column) for accessing existing columns, but it cannot be used to create new columns. Always use square brackets (e.g., df['column']) for this purpose.


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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.population = [61399000, 75967000, 39244, 380200, 10380491, 5496000, 2424200]
print(countries)

As expected, the 'population' column was not created since Pandas doesn't allow columns to be created using this approach.

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Seção 1. Capítulo 7

Pandas First Steps

Adding a New Column