pretty mess

import os
import pandas as pd
import numpy as np
from matplotlib import pyplot as plt, gridspec
from matplotlib.backends.backend_pdf import PdfPages
from collections import OrderedDict

from IPython.core.interactiveshell import InteractiveShell
InteractiveShell.ast_node_interactivity = "all"

wkdir = "C:/Users/MAR8RNG/BOSCH-PROJECTS/1-Humidity/python/condensed_CSVs/"

bse_prm ='premium/'
os.chdir(wkdir+bse_prm)

csv_list = os.listdir(wkdir+bse_prm)

for csv in csv_list:    
    imei=csv[:-4]
    imei
    with open(csv) as f:
        df = pd.read_csv(f, parse_dates=['DateTime'])
                
        #For iterating over months and obtaining weeks
        mon_list = df['Month'].unique()
        df.set_index(['Month'], drop=False, inplace=True)
        mon_week = OrderedDict()
        for m in mon_list:
            if m not in mon_week:
                mon_week[m] = df.loc[m]['Week'].unique()
        
        #Month-Week (e.g. Dec-52) Selection     
        df.set_index(['Month', 'Week'], inplace=True)
        df.sort_index(inplace=True)
        
        #Save figs as PDFs
        with PdfPages(wkdir+'figures/'+imei+'.pdf') as pdf:
            
            #Montly-Weekly plots
            for m in mon_list:
                
                #create figure
                fig = plt.figure()
                
                #number of weekly plots in fig
                nweeks = len(mon_week[m])

                #create grid in for figure
                grid = gridspec.GridSpec(3, 3)
                
                #plot monthly and position in grid
                month=plt.subplot(grid[0,:])
                df.loc[m].plot(x='DateTime',
                               y=['VWC', 'dVWC'],
                               figsize=(16,9),ax=month, title=m)
                
                n=5
                i=1
                for w in mon_week[m]:
                    #plot weekly and position in grid
                    week=plt.subplot(grid[i,5%n])
                    df.loc[m, w].plot(x='DateTime',
                                      y=['VWC', 'dVWC'],
                                      ax=week,title=m+'_'+str(w))
                    
                    #sets up week grid positions
                    n-=1
                    if n==2:
                        i=2
                        n=5
       

                    
                plt.tight_layout()
                pdf.savefig(fig)
                plt.close('all')

               
        ####don't forget to add labels####
        ####graph the moving average####
        ####graph all using the same window####            
        
        #save figures as pdfs
        #create more space between the figures
        #better labels
        #create smaller df or only obtain the series to make the algorithm faster
        
        #to do, label maximums
        #label y axis
        #smooth out the graphs
        #arima
        
        #plt.subplot2grid()
        #one figure top MONTH
            #month
            #weeks side by side
        #df_sub = create a data frame with daily high low values