From junior to geek the road is sleek
Here we calculate 0.9th quantile of each column in our dataframe: q = 0.9 for column in df: qr = df[column].quantile(q) print(f”{q*100}% are lower than {qr}”) Here’s a good example to understand quantiles.
In any Python script you can easily count execution time. In Jupiter notebooks simply use built-in magic commands like %%time in the very beginning of the cell. Now with the IDEs like PyCharm you should use something like this: import datetime as dt t1 = dt.datetime.now() # your code here t2 = dt.datetime.now() ft = … Read more