Using the (now) familiar process of adding data to our Watson Studio project, we've created a new asset using a CSV data file and, in an effort to better understand the data, used the Data Refinery feature to analyze, profile, and visualize our asset. From there (as we did in a previous Time series analysis section of this chapter), we used Insert to Code and then Insert pandas DataFrame so that Watson Studio would generate the code required to import the required Python modules, load the data (into a Python DataFrame object, named df_data_1) and print the first five rows, as shown in the following screenshot: