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Title | Home | Emily Grace |
Description | A blog by a PhD student in Chemistry with posts on life as a PhD student, advanced chemistry theories and ideas, basic chemistry help, tutorials and information on scientific programming in python, as well as other programming-related |
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WebSite | emilygraceripka.com |
Host IP | 206.81.5.74 |
Location | United States |
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US$1,811,663
Last updated: 2023-05-17 01:11:34
emilygraceripka.com has Semrush global rank of 5,842,315. emilygraceripka.com has an estimated worth of US$ 1,811,663, based on its estimated Ads revenue. emilygraceripka.com receives approximately 209,038 unique visitors each day. Its web server is located in United States, with IP address 206.81.5.74. According to SiteAdvisor, emilygraceripka.com is safe to visit. |
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emilygraceripka.com. | A | 3599 | IP: 206.81.5.74 |
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emilygraceripka.com. | NS | 1800 | NS Record: ns2.digitalocean.com. |
emilygraceripka.com. | NS | 1800 | NS Record: ns1.digitalocean.com. |
Portfolio Blog Blog Scientific Programming Chemistry Miscellaneous About Me Research Teaching Portfolio April 16th, 2019 Working with multi-scan experimental data in Python using Pandas dataframes Whether you are a chemist, physicist, biologist, or even data scientist, you will often need to work with data that changes as a function of time. This is common in the physical and life sciences if you are working with any type of spectroscopy. It can be difficult to visualize these large data sets and find trends in them without using some type of programming language, as the data tends to be a bit messy and redundant, making it hard to plot and fit in excel. This blog post, with corresponding reference jupyter notebook, shows you how to take advantage of several of Python’s data science stack packages like Pandas, NumPy, and matplotlib, using both dataframes and ndarrays to help you visualize and fit the data. Read the full post February 6th, 2019 The Array Data Structure Using python for |
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