Course Content
Analyzing and Visualizing Real-Life Data
We can see that only two types of data are presented in the dataframe: object
and int64
. Columns that have an object data type contain string objects, which makes aggregation impossible for them. Among these columns are Weekly_Sales
, Temperature
, Fuel_Price
, and others. It is obvious that all the mentioned columns must be numerical. We might be interested in comparing the revenue for different dates, but with object data, it's impossible.
Let's solve problems step by step. First, let's remind ourselves what our data looks like by outputting a single row.
Pay close attention to the values and try to find out why most of the columns are considered object
columns.
What is wrong with the 'Temperature'
, 'Fuel_Price'
, and 'Unemployment'
columns?
Select the correct answer
Everything was clear?