Rank of Last Close Price vs Previous Prices¶

#Import things we'll need
from quantopian.pipeline import Pipeline, CustomFactor  
from quantopian.research import run_pipeline

from quantopian.pipeline.data.builtin import USEquityPricing

import numpy as np
import pandas as pd

# Class using a Pandas dataframe
class RankOfLastPrice_pd(CustomFactor):  
    inputs = [USEquityPricing.close]  
    window_length = 1
    
    def compute(self, today, assets, out, prices):
        # first change the numpy array into a dataframe then use rank method
        prices_df = pd.DataFrame(prices)
        out[:] = prices_df.rank(axis=0).tail(1)

# Class using Numpy methods
class RankOfLastPrice_np(CustomFactor):  
    inputs = [USEquityPricing.close]  
    window_length = 2
    
    def compute(self, today, assets, out, prices):
        # This doesn't handle duplicates, NaNs, and special case of n=1 well
        out[:] = prices.argsort(axis=0).argsort(axis=0)[-1] + 1

# Create a pipeline showing our two versions of ranking

p = Pipeline()
p.add(RankOfLastPrice_pd(window_length = 3), 'rank_pd') 
p.add(RankOfLastPrice_np(window_length = 3), 'rank_np') 

results = run_pipeline(p, '2016-03-01', '2016-03-01')
results