Create and drop columns in Pandas-CodePudding

I have a big data frame with minute wise data as below, where i do some functions and then drop columns.

datetime	E10	E11	E12	E132	E21	E31	E32	E37	E40	E43	E44	E45	E47	E65	E8
24-11-2021 07:30	22	122	62	232	55	874.2	32.8	351.2	1.4	0.3	5.1	4	1	24.2	76
24-11-2021 07:31	23	120	60	232	55	0	33.3	0	1.3	0.3	0	2	1	24.7	80
24-11-2021 07:32	22	123	61	208	54	0	32.9	0	1	0.3	0	3	1	24.7	79
24-11-2021 07:33	21	120	54	296	55	0	33	0	0.9	0.3	0	2	1	24.9	79
24-11-2021 07:34	21	122	58	272	50	0	32.4	0	0.9	0.3	0	3	1	24.3	77

# Arithmetic Functions
df['E08'] = df['E8']   df['E132'].multiply(0.1467)
df['E037'] = df['E37'] - df['E65']
df['E032'] = df['E32'] - df['E40']
df['E010'] = df['E10']   df['E45']   (df['E28'] - df['E48'])
df['E011'] = df['E11'] - df['E44'] - df['E43']
df['E021'] = df['E21'] - df['E50'] - df['E51'] - df['E52'] - df['E53'] - df['E54']
df['E031'] = df['E31'] - df['E41']


# Drop
df.drop([
    'E8', 'E132', 'E37', 'E65', 'E32', 'E40', 'E10', 'E45',
    'E48', 'E11', 'E44', 'E43', 'E21', 'E50', 'E51', 'E52',
    'E53', 'E54', 'E31', 'E41'], axis=1, inplace=True)

I would like to know which is the efficient method

Question 1: Creating a new column or keeping the same column. Example: Option 1: df['E8'] = df['E8'] df['E132'].multiply(0.1467) or Option 2: df['E08'] = df['E8'] df['E132'].multiply(0.1467)

Question 2: Should i apply drop code separately like above, or is there a way to drop 'E8' & 'E132' once E08 is created. I tried df['E08'] = df['E8'] df['E132'].multiply(0.1467).drop(['E8', 'E132'], axis=1, inplace=True)- its not working

CodePudding user response：

If want use and then remove column from original use DataFrame.pop, then drop is not necessary:

df['E08'] = df.pop('E8')   df.pop('E132').multiply(0.1467)
df['E037'] = df.pop('E37') - df.pop('E65')
...