Subtract one dataframe from another excluding the first column Pandas

Question

I have to dataframes with the same columns. My task should be to subtract the df_tot from df_nap without touching the first column (\'A\'). What is the easiest solution for it?<

Answer 1

Set the common index for both dataframes before using pd.DataFrame.sub:

df_tot = df_tot.set_index('Wavelength')
df_nap = df_nap.set_index('Wavelength')

res = df_tot.sub(df_nap)

If you require 'Wavelength' as a series rather than an index, you can call reset_index on the result:

res = res.reset_index()

However, there are certain benefits attached to storing a unique row-identifier as an index rather than a series. For example, more efficient lookup and merge functionality.

Answer 2

you can also use join and iloc:

df_tot.iloc[:,:1].join(df_tot.iloc[:,1:]-df_nap.iloc[:,1:])

but this implies to have the same order of columns and 'wavelength' being the first one

Answer 3

Simply subtract the entire DataFrames, then reassign the desired values to the Wavelength column.

result = df_tot - df_nap
result['Wavelength'] = df_tot['Wavelength']

For example,

import numpy as np
import pandas as pd

df_tot = pd.DataFrame(np.random.randint(10, size=(3,4)), columns=list('ABCD'))
df_nap = pd.DataFrame(np.random.randint(10, size=(3,4)), columns=list('ABCD'))
# df_tot['A'] = df_nap['A']   # using column A as the "Wavelength" column

result = df_tot - df_nap
result['A'] = df_tot['A']

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Alternatively, or if Wavelength column were not numeric, you could subtract everything except the Wavelength, then reassign that column:

result = df_tot.drop('Wavelength', axis=1) - df_nap.drop('Wavelength', axis=1)
result['Wavelength'] = df_tot['Wavelength']