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difference in this tutorial we are going to look at how to handle missing data in pandas now often when you are downloading data from internet or less say getting it from any other source it might have missing values as shown in this CSV file this file contains New York Citys weather data and you can see that some of these cells are not having any value in it also it is missing the data for 2nd and 3rd January ok so when youre processing this kind of information in pandas we will see how you can deal with these missing values using fill na interpolate and drop any methods I have more tutorials on how to handle missing data but this is just to start and we are only covering these three methods ok so as usual Im going to start my Jupiter not book now if you dont know what is Jupiter not book I have a separate tutorial on it but you can also use any IDE of your choice such as py charm or not pay plus plus whatever you prefer I like Jupiter not book because it is great with data visua