gat | An HTTP caching server | HTTP library

The script below takes one string input as a polyline and returns a data frame with the corresponding latitude/longitude pairs.

I would like to input to be a data set as follows:

ActivityID Polyline 1 PolyLineValue1 2 PolyLineValue2 3 PolyLineValue2

and the output to be (keeping the ActivityID)

ActivityID latitude longitude 1 123 123 1 123 123 1 123 123 2 123 123 2 123 123 2 123 123 3 123 123 3 123 123 3 123 123

I was thinking along the lines of iterating over the input dataset to do this but I've read here that's not a great idea performance wise.

Please can someone advice how to do this in Python?

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I'm trying to sort a report on a column that is the count of total problem codes. I didn't create the original report and I've never used these before, so I'm trying to figure out how to modify the report without starting from scratch. I tried using a sub-query to give me a column I could use to sort, but I keep running into the same problem whenever I try and sort on the aggregate.

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I had no error. Always refresh cache and local memory.

Resources for Verifying Translations:

[NCBI Protein Translation Tool][1] (Validation)

[Text Compare][2] (Verification)

[Solution Inspiration][3]

300 DNA chars -> 100 protein chars.

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I'm trying to look through my file to find the total number of times it says 'CDS' and I'd like to use regex for this. I'm new to python and would like to try this out.

I've tried to use re.findall(r'CDS') but it doesn't work

A sample of my file is:

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I am using the Python regex module for approximate string matching. I have a DNA sequence which I would like to search for a specific pattern, while allowing for at most 1 substitution: {s<=1}. In the DNA sequence, multiple patterns are acceptable. For example, the first three characters can either be 'GAG' or 'GAT', and the same principle holds true for the rest of the DNA sequence.

I made an example below, where I want to use regex search on a 9 character long string. To my understanding, the pattern should match the string without any subtitution.

However, regex gives me a match with a fuzzy count of 1 for substitutions (see below). I do not understand this, as the sequence matches the pattern.

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I have a list of pandas data frames that I got applying the groupby function and I want to add to them a new column with the frequency of each kmer. I did that with a loop but I got a message warning that I need to use df.loc[index, col_names]. Here it is a link to one example of the csv file: https://drive.google.com/file/d/17vYbIEza7l-1mFnavGGO1QjCjPdhxG7C/view?usp=sharing

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I have two dataframes

df1

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I am new to Python and lost in the way to approach this problem: I have a dataframe where the information I need is mostly grouped in layers of 2,3 and 4 rows. Each group has a different ID in one of the columns. I need to create another dataframe where the groups of rows are now a single row, where the information is unstacked in more columns. Later I can drop unwanted/redundant columns.

I think I need to iterate through the dataframe rows and filter for each ID unstacking the rows into a new dataframe. I cannot obtain much from unstack or groupby functions. Is there a easy function or combination that can make this task?

Here is a sample of the dataframe:

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As I was bored and wanted to practice my python, I thought I'd write a script that took some genetic code and converted it into the amino acid sequence. It looks through the code one letter at a time and when it sees a certain sequence, starts translating triplets of genetic code into their equivalent amino acid and strings them together until it reaches a triplet of genetic code that doesn't encode an amino acid. The script then goes back to where it started this translation, and restarts iterating through the code until it finds another start sequence.

The script works, up to a point. I started off using a while loop to iterate through the triplets of genetic code after a start sequence, but when it reaches the end of the genetic code, it goes out of range:

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