Hello,
I am new to python so apologies for the newbie question, I have a dataframe containing pct changes of prices for a list of equities, I would like to only select those equities (note the equities are columns in the dataframe) where the price changes are below some threshold. Is there a simple pythonic way of applying a filter to a dataframe to do this?
Regards,
Mark
I believe I solved my own question, here is my solution if anyone is interested,
#get transpose of dataframe
df = df.transpose()
#convert values that are above or below cutoff level to nan
df = df[df > -1.0 * context.price_spike_cutoff ] df = df[df < context.price_spike_cutoff ]
#remove rows with nan
df = df.dropna(how='any')
#convert back to original structure
df = df.transpose()
any suggested improvements are welcome.
Regards,
Mark
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