import pandas as pd

locs = ['BeachieCr', 'EagleCr', 'Goodell', 'Maple']
bdate = ['9/8/2020', '9/4/2017', '8/19/2015', '8/8/2018']


def merge(loc, bdate):
    print(loc)
    pnnl = pd.read_csv('pnnl_{}.csv'.format(loc))
    t7 = pd.read_csv('gmet/Tmax7_{}.csv'.format(loc))
    t60 = pd.read_csv('gmet/Tmax60_{}.csv'.format(loc))
    
    tmx = pd.concat([t7, t60], axis=1)
    tmx.columns = ['times', 'TMX7', '', 'TMX60']
    tmx = tmx[['times', 'TMX7', 'TMX60']]
    
    df = pd.merge(tmx, pnnl)
    df['loc'] = loc
    df['burn_date'] = pd.to_datetime(bdate)
    df['isBurn'] = (df.times == df.burn_date) + 0
    #df = df.melt(id_vars=['times', 'loc'])
    #df.to_csv('{}_merge.csv'.format(loc), index=False)
    return df

df = pd.DataFrame()
for i in range(len(locs)):
    dx = merge(locs[i], bdate[i])
    df = pd.concat([df, dx])

df.to_csv('burn_scatter_data.csv', index=False, float_format='%5f')