Skip to content
Advertisement

Tag: count

Pandas pivot table count

I would like to ask a question concerning pivot tables in Pandas. I have been trying to make a pivot table for this kind of table: sector score US null US null US 1 EU null EU 2 EU 2 EU 4 UK null UK null UK null UK 4 UK 4 Eventually, I would like this table to be

count the files in directory and loop one by one

I have some different format files in a one directory, but i want to read only .txt file and print the based on the count , Example: (one.txt,two.txt,three.txt,four.txt,one.xlsx,two.xlsx) here i want to count the .txt files and read all .txt file one by one , here the count is 4 read file one.txt print(“hello”) read file two.txt print(“hello”) read file

Can repeating query be saved?

In my Python / Sqlite program, I am running queries like this So the “basic” query is the same, and the rows Sqlite gathers are the same, but because of the different grouping , I have to run the same query multiple times. I wonder if there is a way to achieve the same output more effectively, ie. run the

frequency of unique values for 2d numpy array

I have a 2-dimensional numpy array of following format: now how to print the frequency of unique elements in this 2d numpy array, so that it returns count([1. 0.]) = 1 and count([0. 1.]) = 1? I know how to do this using loops, but is there any better pythonic way to do this. Answer You can use numpy.unique(), for

Advertisement