#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Felix Muzny
10/21/2022
DS 2000
Lecture 13 - functions and program design, HW 5 help

A program to read and analyze some small weather data
"""
import data_utils
import matplotlib.pyplot as plt

WEATHER_DATA = "weather_sample.csv"

def read_data(filename, skip_header = False):
    """
    Reads in the data in a given file
    and stores the values in a list of lists of strings.
    Assumes that commas separate row items in the given file.

    Parameters
    ----------
    filename : string
        name of the file
    skip_header: boolean, optional
        whether or not to skip a header row. Default to False.
    Returns
    -------
    data : list of lists
        list of lists of string values for all lines in the file

    """
    file = open(filename, "r")
    
    # before we start processing each line,
    # we need to create an empty list to hold everything
    data = []
    
    # do we need to skip the first row?
    if skip_header:
        file.readline()
        
    # processing each line
    for line in file:
        pieces = line.strip().split(",")

        # replace empty strings with 0s (for all columns)        
        # we know empty strings happen in this column
        # use a for loop if you want to do this for all columns!
        if pieces[2] == "":
            pieces[2] = "0.0"
        
        # change temp to ints
        pieces[1] = int(pieces[1])
        
        # change precip to floats
        pieces[2] = float(pieces[2])
        
        # change temp to celcius
        # C = 5/9(F-32)
        pieces[1] = (5/9) * (pieces[1] - 32)
        
        # make sure I only have the data that I want?
        # build a new list for this row
        # I don't care about the "cloudy" column,
        # so I just won't put it in the new row
        row = [pieces[0], pieces[1], pieces[2]]
        
        data.append(row)
        
    return data


def my_minimum(data, col_index):
    # option 2 - pretend that min() doesn't exist
    # None is a special value in python that indicates
    # nothingness or something we've never set
    
    min_temp = None # float("inf")
    # min_temp = weather_data[0][1]
    for row in data:
        # if I didn't yet set min_temp or min_temp is larger
        # than what I'm currently looking at
        if min_temp is None or min_temp > row[col_index]:
            min_temp = row[col_index]
    return min_temp

# For functions that only print things
def display_day(day_list):
    print("date:", day_list[0])
    print("temp:", day_list[1])
    # return None

def main():
    print("fake HW 5/Weather data analysis")
    weather_data = read_data(WEATHER_DATA, skip_header=True)
    print(weather_data)
    
    # 2) calculates the minimum temperature
    # similar to the strategy for find_most_similar_planet
    my_min_temp = my_minimum(weather_data, 1)
    print("my min temp", my_min_temp)
    my_min_precip = my_minimum(weather_data, 2)
    print("my min precip", my_min_precip)
    
    # option 1 - put temps into a list
    temps = []
    for row in weather_data:
        temps.append(row[1])
        
    min_temp = min(temps)
    print("min temp", min_temp) 
    
    # 3) graphs the temperature-per-day
    temps = data_utils.get_column(weather_data, 1)
    print(temps)
    days = data_utils.get_column(weather_data, 0)
    print(days)
    day_nums = []
    for i in range(len(temps)):
        day_nums.append(len(temps) - i)
    
    plt.plot(day_nums, temps)
    # plt.xticks(days)
    
    display_day(weather_data[0])
    
    
main()