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def loading_generation_profile_data_from_ninja(PARAMS, WEATHER_YEAR, CAPACITY_CAL):

    """for a selected parameter dictionary, weather year, and capacity volume, an hourly capacity factor data frame is calculated.
    in:  parameters
    out: dataframe
    """
    
    TOKEN_ORDER = 0

    TOKEN_LIST = LIST_OF_TOKENS

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TRACKING_OPTIONS_LIST = [0, 1, 2]

TILT_DEGREE_OPTIONS_LIST = [0, 10, 20, 30, 40, 50, 60, 70, 80, 90]

AZIMUTH_DEGREE_OPTIONS_LIST = [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180]

# Coordinates of the Chelsea and Westminster Hospital
LATITUDE = 51.48437
LONGITUDE = -0.18183
YEAR = 2017

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df_CSV_Files = pd.DataFrame([x.split('_') for x in 
                                  
                                  glob.glob('Data/'+ 'ninja_pv_coordinate_*.csv')],
                                 
    columns=['NINJA', 'RENEWABLE', 'TYPE', 'YEAR', 'LATITUDE', 'LONGITUDE', 'SYSTEM_LOSS', 
             'TRACKING', 'TILT_DEGREE', 'AZIMUTH_DEGREE', 'EXTENSION']).astype(str)


df_CSV_Files['CF'] = pd.Series([pd.read_csv(x)['CF'].mean() for x in 
                                     glob.glob('Data/'+ 'ninja_pv_coordinate_*.csv')])

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# !pip install webdriver-manager
from selenium import webdriver
from webdriver_manager.chrome import ChromeDriverManager
import time
import pandas as pd

from bs4 import BeautifulSoup
from urllib.request import Request, urlopen
import re

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def BRING_SEASONAL_PLAYER_STATS(URL_LINK):

    driver = webdriver.Chrome(ChromeDriverManager().install())
    
    # Open the URL on a google chrome window
    driver.get(URL_LINK)
    
    # As this is a dynamic html web-page, wait for 3 seconds for everything to be loaded
    time.sleep(3)
    

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for INDEX, ROW in df_Players.iterrows():
    
    # In order not to get the HTTP 429 Too Many Requests error, we're sleeping the script for some time.
    time.sleep(5)
    
    try: 
    
        site= 'https://www.google.com/search?q={}+nba+espn+gamelog'.format(df_Players.loc[INDEX, 
                                                                                      'PLAYER'].replace(' ', '+'))

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def get_yearly_player_gamelog(PLAYER_URL, YEAR, PLAYER_NAME):
    
    try:
    
        HTML_RESULTS = pd.read_html('{}{}'.format(PLAYER_URL, YEAR))

        LEN_HTML_RESULTS = len(HTML_RESULTS)

        EMPTY_LIST = []

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df_Players_Drafted_2000 = df_Players[
                                    df_Players['DRAFT YEAR']=='2000'
                                  ][
    ['PLAYER', 'TEAM', 'AGE', 'HEIGHT', 'WEIGHT', 'COLLEGE COUNTRY','DRAFT YEAR', 'ESPN_GAMELOG_ID']
                                    ].reset_index(drop=True)


SEASON_2000_2001_CAREER_LIST_TO_CONCAT = []

for INDEX, ROW in df_Players_Drafted_2000.iterrows():

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# !pip install pulp
import pulp as plp
# %matplotlib inline
from matplotlib import pyplot as plt
import cv2
import numpy as np
from pytesseract import image_to_string
import pytesseract
pytesseract.pytesseract.tesseract_cmd = r'/usr/local/bin/tesseract/'
# !pip install streamlit==0.72.0

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WITH date_table AS ( WITH recursive date_in_range(day) AS ( VALUES('2019-12-30')
UNION ALL
SELECT date(day, '+7 day')
FROM   date_in_range
WHERE  date(day, '+7 day') < '2020-10-19' )
SELECT   strftime('%Y-%W', day)          AS year_week,
         row_number() OVER(ORDER BY day) AS yw_id
FROM     date_in_range)
SELECT table_for_flags.user_id ,
       table_for_flags.year_week ,