Load your time series data

The most common way to import time series data in Python is by using the pandas library. You can use the read_csv() from pandas to read the contents of a file into a DataFrame. This can be achieved using the following command:

df = pd.read_csv("name_of_your_file.csv")

Once your data is loaded into Python, you can display the first rows of your DataFrame by calling the .head(n=5) method, where n=5 indicates that you want to print the first five rows of your DataFrame.

In this exercise, you will read in a time series dataset that contains the number of "great" inventions and scientific discoveries from 1860 to 1959, and display its first five rows.

This exercise is part of the course

Visualizing Time Series Data in Python

View Course

Exercise instructions

Import the pandas library using the pd alias.
Read in the time series data from the csv file located at url_discoveries into a DataFrame called discoveries.
Print the first 5 lines of the DataFrame using the .head() method.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Import pandas
____

# Read in the file content in a DataFrame called discoveries
discoveries = ____(url_discoveries)

# Display the first five lines of the DataFrame
print(discoveries.____)

Edit and Run Code