File headings conversions

Column headings and things to be aware of

File 1 — Strata

df = df.rename(columns = {“name”:”strata_name”,

“round.area.name”:”cea”,

“round_name”:”period”,

“area_ha”: “strata_area_ha”,

“round.area.area_ha”:”cea_area_ha”

})

File 6 — core sublayers

df = pd.read_excel( ‘6-core-sublayer-’ + property.iloc[4] + ‘.xlsx’)

df = df.rename(columns {“s6_socl_core_sublayer_carbon_mass”:”sub_lay_carbon_mass”,

“cum_sublayer_carbon_mass”:”cum_sub_lay_carbon_mass”, “stata_name”:”strata_name”})

### Note that sublayers look like 1 & 2 in the initial view, however in T1 there are 23 layers. If you select ‘layer’ == 2 it won’t be what one expects for T1 ###

File 11 — core level

df = pd.read_csv( ‘11-core-report-layer-’ + property.iloc[4] + ‘.csv’)

df = df.rename(columns = {“e53_soci_core_report_layer_esm_carbon_mass”:”carbon_mass”, “round_name”:”period”})

File 13 — CEA round comparison

df = pd.read_excel(‘13-report-layer-cea-round’ + ‘-’ ‘ALBE’ + ‘.xlsx’)

df = df.rename(columns = {‘e60_soccea_mean_cea_soc_stock’:’carbon_mass’,’cea_name’:’cea’,’round_name’:’period’}) #

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Melanie Zeppel

Women in AI: Agribusiness winner - 2022 Superstar of STEM 2022-2023 Scopus Sustainability Researcher of the Year - 2019