Manipulating data with Pandas

You can combine data from different sources into a single DataFrame.

Imagine that you are tasked with calculating GDP to understand the health of the US economy. You have gathered the data you need from disparate sources in different formats.

You can calculate gross domestic product using the supplied DataFrames for personal consumption expenditures, government expenditures, gross private domestic investment, and net exports. The DataFrames ge, gpdi, ne, and pce are provided.

Bu egzersiz

Intermediate Python for Finance

kursunun bir parçasıdır

Kursu Görüntüle

Egzersiz talimatları

Combine the supplied source DataFrames ge, gpdi, ne and pce in that order into a single new DataFrame.
Sum the values in each row to produce the GDP per year.

Uygulamalı interaktif egzersiz

Bu örnek kodu tamamlayarak bu egzersizi bitirin.

# Combine the source DataFrames into one
gdp = pd.____([ge, gpdi, ____, ____], axis=1)

# Add the columns and create a new column with the result
gdp['GDP'] = gdp.____(np.sum, axis=1)

Kodu Düzenle ve Çalıştır