From the course: Python for Marketing (2019)

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Fixing missing values

Fixing missing values - Python Tutorial

From the course: Python for Marketing (2019)

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Fixing missing values

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- [Instructor] First thing we're going to do for Timeseries data is fix the missing values that are in it. And how do I know there are missing values? Well, let's have a look. First we're going to import our library sort using Pandas and Matplotlib. Next we're going to read in Google Analytics Page Traffic Data. We're going to skip the first 386 rules. We're only going to look at number for rows 366. We only want to use the columns Day, Index, and Pageview. We're going to parse the Day Index as a date time, and then we're going to set the Day Index as an index column. We're also going to import some PPC data that we will use a little later on. So we're going to parse dates as Day and set the index column as Day, too. Now, let's quickly explore this data set and we'll see how we find the problems. So look at the head, everything looks fine. And we look at info, again, everything looks fine, we have an integer, we have…

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