Calculations Forest floor

import pandas as pd
import numpy as np



# load and prepare data
  #when reading csv files using pandas be sure to use '//' instead of '/' when pasting the pathway
FF_samp=pd.read_csv(LLCS2018FF.csv",
                     header = 0)
FFash=pd.read_csv(LLCS_FF_ash_2018.csv",
                     header = 0)
FF_CHN=pd.read_csv(LLCS_2018FF_CHN.csv",
                     header = 0)


FFmass =pd.DataFrame(FF_samp
             .groupby([ 'ws', 'plot', 'ff_layer'])
             .agg(
                 avg_g_cm2=pd.NamedAgg(column="FF_mass_g_cm2", aggfunc="mean") )
)
FFmass=FFmass.reset_index(drop=False)
# merge tables and add columns with calculations
FFdata=(pd.merge(FFmass, FFash, on=['plot','ff_layer']).merge(FF_CHN, on=['plot','ff_layer']))
FFdata['mass_Mg_ha']=FFdata.avg_g_cm2*100
FFdata['C_Mg_ha']=FFdata.c_per*(FFdata.mass_Mg_ha/100)
FFdata['N_Mg_ha']=FFdata.n_per*(FFdata.mass_Mg_ha/100)

# export table
FFdata.to_csv("2018FFdata.csv")

# sum by plot number carbon and nitrogen, average LOI
df2 =pd.DataFrame(FFdata
             .groupby(['year','ws', 'plot'])
             .agg(
             C_Mg_ha_sum=pd.NamedAgg(column="C_Mg_ha", aggfunc="sum"),
             N_Mg_ha_sum=pd.NamedAgg(column="N_Mg_ha", aggfunc="sum"),
             LOI_avg=pd.NamedAgg(column="loi", aggfunc="mean")
              )
)
#export table
df2.to_csv("2018FF_CNsums.csv")

# sum by treatment type carbon and nitrogen
df =pd.DataFrame(FFdata
             .groupby(['year','ws', 'treatm'])
             .agg(
             C_Mg_ha_sum=pd.NamedAgg(column="C_Mg_ha", aggfunc="sum"),
             N_Mg_ha_sum=pd.NamedAgg(column="N_Mg_ha", aggfunc="sum")
              )
)
df3.to_csv("2018FF_treat_CNsums.csv")