Iterate over pairs of columns and add value from one under condition in new column Python-CodePudding

I have dataframe with steps/action in user behaviour. Sample is provided. There are many steps. Each step contains two columns: subtitle and dimension. I need to merge columns subtitle and dimension for each step new column - if dimension is empty then keep only subtitle, if not keep only dimension.

So new column step0 value: if df['dimension1 (step0)'] not null value then use df['dimension1 (step0)] if df['dimension 1 (step0)] is null then use df['subtitle (step0)'] then repeated for step1.

I am complete newbie.

Expected output:

values for df['step0']: client, homepage, internal values for df['step1']: client, client, map

etc.

Please help by providing code

CodePudding user response：

Assume idVisit is the index. Then you may try .combine_first() method on every odd column (dimension) with every even one (subtitle):

# set the index just in case
df.set_index('idVisit', inplace=True)
# loop over subtitles and dimensions zipped together and enumerated
for n, (subtitle, dimension) in enumerate(zip(df.columns[0::2], df.columns[1::2])):
    df[f'step {n}'] = df[dimension].combine_first(df[subtitle])
# show only added columns
df.iloc[:, 8:]

Output:

# only the added columns are shown 
          step 0    step 1   step 2     step 3
idVisit             
1         client    client   client     client
2         homepage  client   homepage   client
3         internal  map      internal   map