Add new column to Python Pandas DataFrame based on multiple conditions

Add new column to Python Pandas DataFrame based on multiple conditions

You can apply an arbitrary function across a dataframe row using DataFrame.apply.

In your case, you could define a function like:

def conditions(s):
    if (s[discount] > 20) or (s[tax] == 0) or (s[total] > 100):
        return 1
    else:
        return 0

And use it to add a new column to your data:

df_full[Class] = df_full.apply(conditions, axis=1)

Judging by the image of your data is rather unclear what you mean by a discount 20%.

However, you can likely do something like this.

df[class] = 0 # add a class column with 0 as default value

# find all rows that fulfills your conditions and set class to 1
df.loc[(df[discount] / df[total] > .2) & # if discount is more than .2 of total 
       (df[tax] == 0) & # if tax is 0
       (df[total] > 100), # if total is > 100 
       class] = 1 # then set class to 1

Note that & means and here, if you want or instead use |.

Add new column to Python Pandas DataFrame based on multiple conditions