Hi,
I am new to Pandas. I am trying to remove the lower and upper 15 percentiles of
interest rates within a day. The index column is the date. Below is some code,
but how do I apply the trim function day-by-day? I tried using grouped() in
conjunction with apply(), but that turned out to be an efficient way to slow my
computer down and choke it. Any thoughts?
import pandas as pd
records = pd.read_table("blah.csv", sep=";", parse_dates=[2], index_col=2,
low_memory=False)
def trim(df, colname, boundaries=(0.15, 0.85)):
lo = df[colname] >= df[colname].quantile(boundaries[0])
hi = df[colname] <= df[colname].quantile(boundaries[1])
return df[lo & hi]
trimmed = trim(records, 'pct_12m') # this trims across all data, not
day-by-day, which I want.
Oh, and is something like the following possible instead of df[lo & hi]?
df[lo <= df[colname] <= hi] # looks nice, but gives ValueError
Thanks in advance!
Regards,
Albert-Jan
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
All right, but apart from the sanitation, the medicine, education, wine, public
order, irrigation, roads, a
fresh water system, and public health, what have the Romans ever done for us?
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
--
https://mail.python.org/mailman/listinfo/python-list
