How to do it...

  1. In the first section on data manipulation, we saw the summary statistics for our datasets. However, we have not looked at this since imputing the missing values.

Let's now look at the data and its basic statistics using the following code:

# To take a look at the top 5 rows in the datasethousepricesdata.head(5)# To display the summary statistics for all variableshousepricesdata.describe()
  1. With the preceding code, we can see the summary statistics of the variables in the earlier section.

Now let's see how many columns there are by datatype:

# How many columns with different datatypes are there?housepricesdata.get_dtype_counts()

The following code shows us how many variables there are for each datatype. We can see that we ...

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