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import pandas as pd 
import glob
import os

path = r'C:\Users\Ty Dickinson\Documents\Hollings Code Output Excels\Max Precip'
all_files = glob.glob(os.path.join(path, "*.csv"))

Table = pd.concat((pd.read_csv(f, usecols=range(1,9)) for f in all_files))
Table = Table.sort_index(axis=0)

Winter1Day = []
Spring1Day = []
Summer1Day = []
Fall1Day = []
Winter2Day = []
Spring2Day = []
Summer2Day = []
Fall2Day = []

x=0
while x<=36:
    table = Table.loc[x:x]
    Winter1Day.insert(x, max(table['Winter 1 Day Precip']))
    Spring1Day.insert(x, max(table['Spring 1 Day Precip']))
    Summer1Day.insert(x, max(table['Summer 1 Day Precip']))
    Fall1Day.insert(x, max(table['Fall 1 Day Precip']))
    Winter2Day.insert(x, max(table['Winter 2 Day Precip']))
    Spring2Day.insert(x, max(table['Spring 2 Day Precip']))
    Summer2Day.insert(x, max(table['Summer 2 Day Precip']))
    Fall2Day.insert(x, max(table['Fall 2 Day Precip']))
    x +=1
    
df1 = pd.DataFrame({'Winter 1 Day Max':Winter1Day})
df2 = pd.DataFrame({'Spring 1 Day Max':Spring1Day})
df3 = pd.DataFrame({'Summer 1 Day Max':Summer1Day})
df4 = pd.DataFrame({'Fall 1 Day Max':Fall1Day})
df5 = pd.DataFrame({'Winter 2 Day Max':Winter2Day})
df6 = pd.DataFrame({'Spring 2 Day Max':Spring2Day})
df7 = pd.DataFrame({'Summer 2 Day Max':Summer2Day})
df8 = pd.DataFrame({'Fall 2 Day Max':Fall2Day})
dftot = pd.concat([df1, df2, df3, df4, df5, df6, df7, df8],
                 axis=1)
#dftot.to_csv('Maximum Rainfall.csv')


    

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