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Using Pandas to Read Large Excel Files in Python

Using Pandas to Read Large Excel Files in Python

By admin / June 3, 2018
Using Pandas to Read Large Excel Files in Python

Panda is a wonderful tool to use to analyze data. It can be a bit tough importing data from larger files, especially Microsoft Excel. This tutorial guides you in how you can use Panda for larger excel files to read and analyze data.

You want to start off by downloading the Excel file. Now for large Excel file, your Excel will probably not be able to open the file. Since Excel can only handle files up to 1 million rows at a time. These files would exceed that limit. So you will have to open the file using Panda.

Using Panda

Import the file into Panda. Panda will take some time to read and open the file since it has a lot of data. The time completely depends on your system’s memory. You can then see the number of rows in the dataset along with the name of headers.

You want to make sure that Panda has picked up all the data and there is no missing. You need to read the first header after the number of rows listed. If it starts with “\x” then it means that the values are hexadecimal. If you see extra symbols then it may mean the data is missing because when data is missing the script is thrown off. So pay close attention to the header. When you have ensured that the data is clean you can start the process of analysis.

Analyzing with Panda

If you are familiar with SQL, analyzing shouldn’t be that hard. You can use the same coding as Select, Where, And/OR with the keywords you want to search to make searches easier. You can start your search using keywords along with Panda command and it will provide you the data you need.

To analyze the file, you should already have an idea of the analysis commands on Panda. But Panda is a wonderful tool to analyze data from larger files. It can make the whole process much easier.

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