Missing Stock Prices (Hacker Rank challenge)

stock-prices.py

#!/usr/bin/env python3

# Challenge available at:
#   https://www.hackerrank.com/challenges/missing-stock-prices/problem

import pandas
import numpy

count = int(input().strip())

def normalize_value(value):
    if value[0:7] == 'Missing':
        return numpy.nan
    else:
        return float(value)

data = []
missing = []
for index in range(count):
    [date, price] = input().split("\t")
    data.append([
        date,
        normalize_value(price)
    ])
    if price[0:7] == 'Missing':
        [_, order] = price.split('Missing_')
        entry = [ index, 1, int(order) ]
        missing.append(entry)
    else:
        pass

date_series = [date for [date, _] in data]
price_series = [price for [_, price] in data]

dataframe = pandas.DataFrame({
    'date': pandas.Series(date_series),
    'price': pandas.Series(price_series),
})

dataframe = dataframe.assign(
    DIdx=pandas.to_datetime(
        dataframe.date,
        format="%m/%d/%Y %H:%M:%S"
    )
)

dataframe = dataframe.set_index('DIdx')

dataframe = dataframe.assign(
    IPrice=dataframe.price.interpolate(
        method='time'
    )
)

result = [None for _ in range(len(missing))]

for [line, column, order] in missing:
    value = dataframe.iloc[line, column + 1]
    result[order - 1] = float(str(value))

for value in result:
    print(value)

# end