Hands-On Data Analysis with Pandas

The wide data format

With wide format data, we represent measurements of variables with their own columns, and each row represents an observation of those variables. This makes it easy for us to compare variables across observations, get summary statistics, perform operations, and present our data; however, some visualizations don't work with this data format because they may rely on the long format to split, size, and/or color the plot content.

Let's look at the top six observations from the wide format data in wide_df:

>>> wide_df.head(6)

Each column contains the top six observations of a specific class of temperature data in degrees Celsius—maximum temperature (TMAX), minimum temperature (TMIN), and temperature at time of observation ...