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Tag: match

How to improve performance of dataframe slices matching?

I need to improve the performance of the following dataframe slices matching. What I need to do is find the matching trips between 2 dataframes, according to the sequence column values with order conserved. My 2 dataframes: Expected output: This is the following code I’ m using: Despite working, this is very time costly and unefficient as my real dataframes

Count number of matches in pairs of pandas dataframe rows

I have been trying to count the number of times different values in a row of dataframe matches with column-wise values in other rows and provide an output. To illustrate, I have a dataframe (df_testing) as follows: I am looking to count the number of exact matches among rows for values in Col_1 to Col_4. For example, Row 0 has

Python Match Case (Switch) Performance

I was expecting the Python match/case to have equal time access to each case, but seems like I was wrong. Any good explanation why? Lets use the following example: And define a quick tool to measure the time: If we run each 10000000 times each case, the times are the following: Just wondering why the access times are different. Isn’t

Regex: allow comma-separated strings, including characters and non-characters

I’m finding it difficult to complete this regex. The following regex checks for the validity of comma-separated strings: ^(w+)(,s*w+)*$ So, this will match the following comma-separated strings: Then, I can do the same for non-characters, using ^(W+)(,s*W+)*$, which will match: I would like to create a regex which matches strings which include special characters, and hyphens and underscore, e.g. foo-bar,

Dictionary keys match on list; get key/value pair

In python… I have a list of elements ‘my_list’, and a dictionary ‘my_dict’ where some keys match in ‘my_list’. I would like to search the dictionary and retrieve key/value pairs for the keys matching the ‘my_list’ elements. I tried this… But it doesn’t do the job. Answer (I renamed list to my_list and dict to my_dict to avoid the conflict

What is the difference between re.search and re.match?

What is the difference between the search() and match() functions in the Python re module? I’ve read the Python 2 documentation (Python 3 documentation), but I never seem to remember it. I keep having to look it up and re-learn it. I’m hoping that someone will answer it clearly with examples so that (perhaps) it will stick in my head.

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