Calculations Mineral soils data 2018

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
soils_BD=pd.read_csv("LLSC_2018BD_soils.csv",
                     header = 0)
soils_CHN=pd.read_csv("LLCS_soil_CHN_2018.csv",
           header = 0)

# average bulk density (BD)
soils_BD2 =pd.DataFrame(soils_BD
             .groupby(['treatm', 'ws', 's_type','plot', 's_depth_cm'])
             .agg(
             BD=pd.NamedAgg(column="BD_g_cm3", aggfunc="mean")
              ))
soils_BD2=soils_BD2.reset_index(drop=False) 

#average analyte percent
soils_CHN2 =pd.DataFrame(soils_CHN 
             .groupby(['ws', 'plot', 's_depth_cm'])
             .agg(
             C_per=pd.NamedAgg(column="c_per", aggfunc="mean"),
             N_per=pd.NamedAgg(column="n_per", aggfunc="mean"),
))

soils_CHN2=soils_CHN2.reset_index(drop=False)
#combine two averaged data sets
soils_pl_s=pd.merge(soils_CHN2, soils_BD2, how="outer", on=['ws', 'plot','s_depth_cm'])
soils_pl_s["BD"].fillna(1.38, inplace=True)
soils_pl_s.to_csv("C:\\Users\\Name\\Desktop\\Folder\\soils_pl_s.csv")
soils_CHN2.to_csv("C:\\Users\\Name\\Desktop\\Folder\\soils_CHN2.csv")

# calculate analyte percent to Megagrams/hectare
df=soils_pl_s
C=df.C_per
N=df.N_per
i=df.interval_cm
bd=df.BD
df["year"]=2018
df['C_Mg_ha']=(bd*i*100*(C/100)) # carbon calculation
df['N_Mg_ha']=(bd*i*100*(N/100)) #nitrogen calculation
df.to_csv("C:\\Users\\Name\\Desktop\\Folder\\2018mineralSoils.csv")

# sum all Mg/ha analyte within the same plot
df2 =pd.DataFrame(df
             .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")
              )
)
df2.to_csv("C:\\Users\\Name\\Desktop\\Folder\\2018min_S_CNsums.csv")
# sum all Mg/ha analyte within the same treatment type (only available for 2022)
df3 =pd.DataFrame(df
             .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")
              )
)
#export table
df3.to_csv("2018_treat_CNsums.csv")